http://2012.igem.org/wiki/index.php?title=Special:Contributions/Aispas&feed=atom&limit=50&target=Aispas&year=&month=2012.igem.org - User contributions [en]2024-03-29T10:35:52ZFrom 2012.igem.orgMediaWiki 1.16.0http://2012.igem.org/Team:Arizona_State/FieldApplicationsTeam:Arizona State/FieldApplications2012-10-27T03:54:56Z<p>Aispas: </p>
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<h1><i>Escherichia Coli</i> Case Studies</h1><br />
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<h2> What is the timeline of an outbreak? </h2><br />
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<p><br />
In order to implement the biosensor correctly, it is imperative to find data about how <i>E.coli</i> outbreaks progressed. Last year, there was on outbreak of <i>E.coli</i> O104:H4 in Germany. It was first detected in early May of 2011, by causing an increased amount of patient who presented hemolytic uremic syndrome (Rohde). As the <i>E.coli</i> outbreak continued to spread, traces of <i>E.coli</i> were present in different foods. According to Dr. Rohde in the Open-Source Genomic Analysis of Shiga-Toxin-Producing <i>E.coli</i> O104:H4 case study, the genomic experiments began with how the <i>E.coli</i> phenotype was determined (Rohde). It wasn’t until five days after the first detection of the <i>E.coli</i> did lab work begin (Rohde). Although this case study reference is a food <i>E.coli</i> outbreak, it continued to grow in size as more food was found to be contaminated. This scenario is similar to a water based <i>E.coli</i> outbreak because typically in larger outbreaks it will affect more than one geographic area. Using this timeline as an example, between the first detection of the outbreak to the <i>E.coli</i> phenotype being determined, it was a period of three weeks. </p><br />
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<p>According to research, detection of the pathogen took a very small amount of time compared to determining the phenotype of the pathogen (Rohde). At this point in time there would have been many sick patients and potentially deaths depending on the severity of the outbreak. With our biosensor, this time could be dramatically reduced. Our biosensor could detect ideally any pathogen of interest. In a hypothetical situation, a potential timeline would be that the water would be tested the day a potential contamination would occur. This contamination could come from heavy rain, flooding, development of a new community, natural disaster, etc. Within minutes of the test being initiated, a pathogen would be able to be detected. This would greatly decrease the amount of locals that could get infected with the pathogen because a contamination warning would be implemented the same day. According to current practices and timelines, a water contamination warning would not be able to go out until two days after the pathogen was detected (Pitkanen). Our biosensor would reduce this time by turning days into minutes. By using the team’s biosensor, we are able to engineer our biosensor to a specific phenotype of pathogen. We would be able to do this onsite or have our biosensor pre-designed before its implemented. This would eliminate expensive lab experiments and time by already having the phenotype of the pathogen determined.</p><br />
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</p><br />
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<h2> What are the possible sources of an outbreak? </h2><br />
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<p><br />
As defined an outbreak is an occurrence of a disease greater than two or more infected patients caused by the same water exposure (Centers for Disease Control and Prevention). Though many of these instances occur in developing countries with lack of sanitation and public health awareness, outbreaks still occurred in industrialized nations such as the United States and Canada (Shannon). For example, in Denmark there was an outbreak of Campylobacter jejuni that happened between the years 1995-1996 (Engberg). This bacterium is similar to <i>E.coli</i> in that it behaves very similar. Campylobacter jejuni is one of the most common bacterial causes of diarrhea in humans in developing countries (Engberg).</p><br />
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<p>In December of 1995, a procedure was performed to test the amount of nitrate in the ground water. In the process of testing this, a sewage pipe was damaged and then leaked into the ground water supply. It took over a four weeks for the water pump to be turned off from the initial contamination (Engberg). For this particular case, a very high coliform count was found in the infected water. A coliform count is recognized as a water contamination test. The test involves the counting of colonies of the coliform-bacteria <i>Escherichia coli</i> (<i>E.coli</i>)in a 100 milliliter water sample. The result is given as "Coliform Microbial Density". This indicates the amount of feces present in the contaminated water sample(The Law Dictionary).</p> <br />
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<p>The Environmental Protection Agency, instituted rules for beaches and recreational waters to ensure that people who came into contact with bodies of water would not become ill. These regulations stated that for any bodies of freshwater, the advisory limits are 235 CFU/100 ml for <i>E.coli</i> (Kinzelman). The standards for common water quality are that recreational water cannot test positive for more than 1000 colonies per 100ml (The Law Dictionary). In Canada, before water can be re-used, it must go through treatments to eliminate pathogens or particles. Under ideal conditions, the efficiency of the pathogen removal system is measured in effluents. This accounts for the amount of waste water being treated for the removal of pathogens. By the guidelines issued by Environment Canada, fecal coliforms in effluents are 400 CFU per 100 ml (Shannon). It is at these concentrations which can be harmful to human populations. With the use of our biosensor we would be able to test any water sources to see if pathogens were present. Our biosensor is both portable and efficient, which would allow for finding the source of an outbreak much easier.</p><br />
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</p><br />
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<h2> What if the <i>E.coli</i> strain mutated or the <i>E.coli</i> was undetectable?</h2><br />
<h4>What are the chances of a mutation occurring or what should be done if a mutation occurs? </h4><br />
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<p><br />
Currently there is a controversial hypothesis that although <i>E.coli</i> can be detected it is viable but its non-culturable (Bogosian). This topic pertains to our biosensor because there could be pathogens present in water, This would affect the timeline of an outbreak as well as infect more people with contaminated water. This poses as a public health issue because of the developing nations who do not have the equipment or technology for this kind of situation. It has been shown that although this is health risk, it has only contributed to 22 deaths and 104 total cases in the last seventy years (Bogosian). It has been shown that although the <i>E.coli</i> is present, the cells actually die off based on their living conditions. A study was conducted to determine if changes in cell populations were due to cell death or to the cells maturing into the non-culturable state (Bogosian). This proved to be very useful because the study tested what kinds of environment the <i>E.coli</i> cells would either reject their populations or thrive to cause an outbreak. The results were that <i>E.coli</i> cells will not thrive in these environments (Bogosian). This proves that when an <i>E.coli</i> outbreak occurs it will be because the cells are in an ideal environment where they are able to grow readily. Although <i>E.coli</i> can be present in water does not mean an outbreak will occur. Our biosensor would ideally be able to detect these pathogens no matter how many colonies were present. Although an outbreak may not occur, the water could still be monitored more closely to prevent an outbreak. <br />
</p><br />
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<h2> How many tests should be done for an outbreak? </h2><br />
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<p><br />
In each of the case studies that were researched, it became apparent that each outbreak has its own characteristics. For example, in 2011, there was an outbreak that took place in Germany where there was a very high rate of expression in adults, especially women (Rohde). Since each outbreak is unique in its own way, it is difficult to determine how many tests should be done to determine the severity of the outbreak. According to a case study about an outbreak that took place in Alpine, Wyoming, physicians were seeing an increased rate of patients who presented with bloody diarrhea (Olsen). More cases began showing up not only in Wyoming, but also in the states Utah and Washington (Olsen). Prior to the outbreak, the Alpine municipal water system was tested multiple times each month for coliform counts. In this case, they were positive for <i>E.coli</i> in the months April, May, and June (Olsen). It was not until late June that the outbreak occurred, and by middle of July they had found the source of this occurrence. Once the outbreak was detected, stool samples from infected patients were then sent to a lab for further testing. From the time that the outbreak began to the time that the source was found was about 3-4 weeks (Olsen). During this time, tests were being done by multiple agencies such as the Wyoming State laboratory and the Utah Department of Health State Laboratory (Olsen). Using the biosensor that our team has developed, the severity of the outbreak would be extremely decreased. Although regular water samples are taken, once the water tested positive for pathogens, water contamination warnings should have been implemented in ensure that an outbreak was minimalized. With the biosensor designed by the ASU iGEM team, our biosensor would be pathogen specific to detect whether that pathogen is present or not in water. Our biosensor would be able detect pathogens in water within minutes of running the experiment. This would greatly decrease the amount of people that potentially could get sick. <br />
</p><br />
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<h2> What are the current practices? </h2><br />
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<p><br />
<i>E.coli</i> outbreaks have been known to occur in different sources, such as food, water, and plants. It has been shown that before an outbreak takes place in water, there are usually signs of <i>E.coli</i> being present (Olsen). Before an outbreak can occur the cells must be able to survive in their environment. In recent case studies it has been found that although <i>E.coli</i> was found to be present in the water supply, although the amount of <i>E.coli</i> was insufficient. It was not until after an outbreak occurred and patients began having symptoms did the amount of <i>E.coli</i> becomes a problem. Once the <i>E.coli</i> outbreak has occurred, it will usually take a few weeks to run tests. These experiments can be determining the phenotype of <i>E.coli</i> or just to determine how many people could potentially be affected by the outbreak. It is quite common during <i>E.coli</i> water outbreaks for the cohort case studies to take place. These studies determine a statistical analysis of the outbreak, where the statisticians where able to see how the outbreak progressed with how many people it infected (Olsen). When <i>E.coli</i> is present in other sources such as food and plants, it is usually not known that this is the source until after the outbreak has already occurred. The biosensor developed by the ASU team, eliminated many of these issues. By engineering the biosensor to already be pathogen specific, it decreases the amount of time to determine what the pathogen. The efficiency of our biosensor allows for the efforts the community to then be focused on water purification, instead of waiting for lab results. <br />
</p><br />
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<h2> How does the biosensor improve sanitation?</h2><br />
<h4> Why is there a need for a real time/faster response for the biosensor needed? </h4><br />
<br />
<p>Improving sanitation and hygiene of water has been one of the primary goals for Arizona State’s iGEM team. As a result of producing a biosensor to detect pathogens, it has the ability to not only prevent outbreaks from occurring but also to minimize them. Our biosensor has the ability to be used to detect different kinds of pathogens. This is very useful because if an outbreak were to occur, the amount of time in spending on determining the phenotype of the pathogen can then be spent on eliminating it from water sources. This is another reason why our biosensor can be so effective by being able to detect specific pathogens, but it is also able to give you the answers in real time. This eliminates even more time in the process of determining the pathogen. By being able to prevent an outbreak from occurring, we would be able to improve the sanitation of water, especially in developing countries. It is in developing nations where the outbreaks are the most prevalent. Our biosensor was designed to be easy to use and efficient. This would allow for it to be portable to test many different kinds of water sources. The more our biosensor is used, the more safety and sanitation would be improved. <br />
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</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ProblemTeam:Arizona State/Problem2012-10-27T03:49:15Z<p>Aispas: </p>
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<h1>The Problem</h1><br />
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<p><br />
Viewed as a minor inconvenience in the developed world, diarrhea can be a death sentence. Diarrhea can be life threatening as it causes severe dehydration as a result of extensive fluid loss. An estimated 2.0 billion cases of diarrhea occur each year amongst children under five years of age. Of these cases, 1.5 million children die. The major pathogens that most frequently cause acute childhood diarrhea cases are bacterial pathogens such as <i>E. coli, Shigella, Campylobacter and Salmonella</i>. Currently, existing biosensors for water-borne pathogens are either costly, inaccessible to developing countries, difficult to use without training, and not very reliable. For example, immunoassays, which uses antibodies specific for certain antigens on pathogenic diarrhea, have a good turnaround time. However, not all antigens have available antibodies that can be used for detection, and those antibodies that are available can be very costly. As such, the ASU iGEM team plans to develop an inexpensive way for communities to test the purity of water sources. To this end, we aimed to identify the specific pathogens in the water source in efforts of reducing the incidence of childhood diarrhea and ultimately decreasing mortality rates. <br />
</p><br />
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<br /><br />
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<table align="center"><br />
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<img src="https://static.igem.org/mediawiki/2012/thumb/3/33/Arizona_State_Diarrhea_key.png/800px-Arizona_State_Diarrhea_key.png" width="800"><br />
</tr></td><br />
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<div class="figText">Figure 1: Epidemiology map indicating disability-adjusted life year for diarrhea per 100,000 inhabitants (2004).<br>Image source: <a href="http://commons.wikimedia.org/w/index.php?title=File:Diarrhoeal_diseases_world_map_-_DALY_-_WHO2004.svg&page=1">Wikimedia Commons</a>.</div><br />
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</table><br />
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<h2>Quantitative considerations</h2><br />
<br />
<br />
<p><b>What concentration of pathogens causes sickness?</b><br />
<br />
<p>A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria <i>Escherichia coli (E.coli)</i> per 100 milliliter of water is present in a sample (The Law Dictionary). The result is expressed as “Coliform Microbial Density” and indicates the amount of fecal matter (The Law Dictionary). The Environmental Protection Agency has standards that define non-potable water as a sample that contains one bacterium per 100 mL.<br />
<br />
<br /><br />
<p><b>What specific design approaches did we take to try to reduce false positives, while making the biosensor effective? </b><br />
<br />
<p>We incorporated a mutational version of split beta-galactosidase that reforms into a functional enzyme unit only when the halves are brought into close proximity. This mutational version of split beta-galactosidase effectively reduces false positive created by chance interactions in the wild-type split beta-galactosidase. <br />
<br />
<p><br />
<br />
<br />
</p><br />
<br /><br />
<br />
<h2>Why are we doing this?</h2><br />
<br />
<br />
<p><br />
<p><b>What do we hope to accomplish/want to figure out?</b><br />
<p><br />
For this project we are hoping to make our biosensor as user friendly and most cost effective product as possible. In the process in making this design we also wanted to address the results from using the biosensor. We wanted our project to give results in real time and be able to determine the phenotype of the potential pathogen. <br />
<br /><br />
<p><b>Who are we doing this for? What do we care about? </b><br />
<p> This project is primarily based on its applications. We wanted to develop a low-cost biosensor that could be implemented in developing countries. This is because pathogenic bacteria causes diarrhea which is one of the world's leading global health issues. By designing our biosensor it would be a potential solution to this problem. <br />
<br />
<br /><br />
<p><b>What is our ultimate goal?</b><br />
<p>Our ultimate goal for the project is to be able to see our biosensor used in developing nations. Ideally our biosensor would be able to be used as an early detection device in order to prevent future pathogenic outbreaks. This would be a solution to not only maintaining a healthy water supply but also to also improve the overall sanitation of developing nations. <br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ProblemTeam:Arizona State/Problem2012-10-27T03:48:06Z<p>Aispas: </p>
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<div>{{:Team:Arizona_State/Template:Header}}<br />
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<html><br />
<body><br />
<br />
<br /><br />
<h1>The Problem</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<p><br />
Viewed as a minor inconvenience in the developed world, diarrhea can be a death sentence. Diarrhea can be life threatening as it causes severe dehydration as a result of extensive fluid loss. An estimated 2.0 billion cases of diarrhea occur each year amongst children under five years of age. Of these cases, 1.5 million children die. The major pathogens that most frequently cause acute childhood diarrhea cases are bacterial pathogens such as <i>E. coli, Shigella, Campylobacter and Salmonella</i>. Currently, existing biosensors for water-borne pathogens are either costly, inaccessible to developing countries, difficult to use without training, and not very reliable. For example, immunoassays, which uses antibodies specific for certain antigens on pathogenic diarrhea, have a good turnaround time. However, not all antigens have available antibodies that can be used for detection, and those antibodies that are available can be very costly. As such, the ASU iGEM team plans to develop an inexpensive way for communities to test the purity of water sources. To this end, we aimed to identify the specific pathogens in the water source in efforts of reducing the incidence of childhood diarrhea and ultimately decreasing mortality rates. <br />
</p><br />
<br />
<br /><br />
<br />
<table align="center"><br />
<tr><td><br />
<img src="https://static.igem.org/mediawiki/2012/thumb/3/33/Arizona_State_Diarrhea_key.png/800px-Arizona_State_Diarrhea_key.png" width="800"><br />
</tr></td><br />
<tr><td><br />
<div class="figText">Figure 1: Epidemiology map indicating disability-adjusted life year for diarrhea per 100,000 inhabitants (2004).<br>Image source: <a href="http://commons.wikimedia.org/w/index.php?title=File:Diarrhoeal_diseases_world_map_-_DALY_-_WHO2004.svg&page=1">Wikimedia Commons</a>.</div><br />
</td></tr><br />
</table><br />
<br />
<br /><br />
<br />
<h2>Quantitative considerations</h2><br />
<br />
<br />
<p><b>What concentration of pathogens causes sickness?</b><br />
<br />
<p>A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria <i>Escherichia coli (E.coli)</i> per 100 milliliter of water is present in a sample. The result is expressed as “Coliform Microbial Density” and indicates the amount of fecal matter. The Environmental Protection Agency has standards that define non-potable water as a sample that contains one bacterium per 100 mL.<br />
<br />
<br /><br />
<p><b>What specific design approaches did we take to try to reduce false positives, while making the biosensor effective? </b><br />
<br />
<p>We incorporated a mutational version of split beta-galactosidase that reforms into a functional enzyme unit only when the halves are brought into close proximity. This mutational version of split beta-galactosidase effectively reduces false positive created by chance interactions in the wild-type split beta-galactosidase. <br />
<br />
<p><br />
<br />
<br />
</p><br />
<br /><br />
<br />
<h2>Why are we doing this?</h2><br />
<br />
<br />
<p><br />
<p><b>What do we hope to accomplish/want to figure out?</b><br />
<p><br />
For this project we are hoping to make our biosensor as user friendly and most cost effective product as possible. In the process in making this design we also wanted to address the results from using the biosensor. We wanted our project to give results in real time and be able to determine the phenotype of the potential pathogen. <br />
<br /><br />
<p><b>Who are we doing this for? What do we care about? </b><br />
<p> This project is primarily based on its applications. We wanted to develop a low-cost biosensor that could be implemented in developing countries. This is because pathogenic bacteria causes diarrhea which is one of the world's leading global health issues. By designing our biosensor it would be a potential solution to this problem. <br />
<br />
<br /><br />
<p><b>What is our ultimate goal?</b><br />
<p>Our ultimate goal for the project is to be able to see our biosensor used in developing nations. Ideally our biosensor would be able to be used as an early detection device in order to prevent future pathogenic outbreaks. This would be a solution to not only maintaining a healthy water supply but also to also improve the overall sanitation of developing nations. <br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ProblemTeam:Arizona State/Problem2012-10-27T03:46:10Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<br />
<br /><br />
<h1>The Problem</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<p><br />
Viewed as a minor inconvenience in the developed world, diarrhea can be a death sentence. Diarrhea can be life threatening as it causes severe dehydration as a result of extensive fluid loss. An estimated 2.0 billion cases of diarrhea occur each year amongst children under five years of age. Of these cases, 1.5 million children die. The major pathogens that most frequently cause acute childhood diarrhea cases are bacterial pathogens such as <i>E. coli, Shigella, Campylobacter and Salmonella</i>. Currently, existing biosensors for water-borne pathogens are either costly, inaccessible to developing countries, difficult to use without training, and not very reliable. For example, immunoassays, which uses antibodies specific for certain antigens on pathogenic diarrhea, have a good turnaround time. However, not all antigens have available antibodies that can be used for detection, and those antibodies that are available can be very costly. As such, the ASU iGEM team plans to develop an inexpensive way for communities to test the purity of water sources. To this end, we aimed to identify the specific pathogens in the water source in efforts of reducing the incidence of childhood diarrhea and ultimately decreasing mortality rates. <br />
</p><br />
<br />
<br /><br />
<br />
<table align="center"><br />
<tr><td><br />
<img src="https://static.igem.org/mediawiki/2012/0/03/Asuigem_diseasemap.png" width="800"><br />
</tr></td><br />
<tr><td><br />
<div class="figText">Figure 1: Epidemiology map indicating disability-adjusted life year for diarrhea per 100,000 inhabitants (2004).<br>Image shown above is from the Wikimedia Commons, http://commons.wikimedia.org/wiki/Main_Page Wikimedia Commons.</div><br />
</td></tr><br />
</table><br />
<br />
<br /><br />
<br />
<h2>Quantitative considerations</h2><br />
<br />
<br />
<p><b>What concentration of pathogens causes sickness?</b><br />
<br />
<p>A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria <i>Escherichia coli (E.coli)</i> per 100 milliliter of water is present. The result is expressed as “Coliform Microbial Density” and indicates the extent of fecal matter. Environmental Protection Agency standards define non-potable water as a sample that contains one bacterium per 100 mL.<br />
<br />
<br /><br />
<p><b>What specific design approaches did we take to try to reduce false positives, while making the biosensor effective? </b><br />
<br />
<p>We incorporated a mutational version of split beta-galactosidase that reforms into a functional enzyme unit only when the halves are brought into close proximity. This mutational version of split beta-galactosidase effectively reduces false positive created by chance interactions in the wild-type split beta-galactosidase. <br />
<br />
<p><br />
<br />
<br />
</p><br />
<br /><br />
<br />
<h2>Why are we doing this?</h2><br />
<br />
<br />
<p><br />
<p><b>What do we hope to accomplish/want to figure out?</b><br />
<p><br />
For this project we are hoping to make our biosensor as user friendly and most cost effective product as possible. In the process in making this design we also wanted to address the results from using the biosensor. We wanted our project to give results in real time and be able to determine the phenotype of the potential pathogen. <br />
<br /><br />
<p><b>Who are we doing this for? What do we care about? </b><br />
<p> This project is primarily based on its applications. We wanted to develop a low-cost biosensor that could be implemented in developing countries. This is because pathogenic bacteria causes diarrhea which is one of the world's leading global health issues. By designing our biosensor it would be a potential solution to this problem. <br />
<br />
<br /><br />
<p><b>What is our ultimate goal?</b><br />
<p>Our ultimate goal for the project is to be able to see our biosensor used in developing nations. Ideally our biosensor would be able to be used as an early detection device in order to prevent future pathogenic outbreaks. This would be a solution to not only maintaining a healthy water supply but also to also improve the overall sanitation of developing nations. <br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ProblemTeam:Arizona State/Problem2012-10-27T03:44:51Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<br />
<br /><br />
<h1>The Problem</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<p><br />
Viewed as a minor inconvenience in the developed world, diarrhea can be a death sentence. Diarrhea can be life threatening as it causes severe dehydration as a result of extensive fluid loss. An estimated 2.0 billion cases of diarrhea occur each year amongst children under five years of age. Of these cases, 1.5 million children die. The major pathogens that most frequently cause acute childhood diarrhea cases are bacterial pathogens such as <i>E. coli, Shigella, Campylobacter and Salmonella</i>. Currently, existing biosensors for water-borne pathogens are either costly, inaccessible to developing countries, difficult to use without training, and not very reliable. For example, immunoassays, which uses antibodies specific for certain antigens on pathogenic diarrhea, have a good turnaround time. However, not all antigens have available antibodies that can be used for detection, and those antibodies that are available can be very costly. As such, the ASU iGEM team plans to develop an inexpensive way for communities to test the purity of water sources. To this end, we aimed to identify the specific pathogens in the water source in efforts of reducing the incidence of childhood diarrhea and ultimately decreasing mortality rates. <br />
</p><br />
<br />
<br /><br />
<br />
<table align="center"><br />
<tr><td><br />
<img src="https://static.igem.org/mediawiki/2012/0/03/Asuigem_diseasemap.png" width="800"><br />
</tr></td><br />
<tr><td><br />
<div class="figText">Figure 1: Epidemiology map indicating disability-adjusted life year for diarrhea per 100,000 inhabitants (2004).<br>Image shown above is from the Wikimedia Commons, http://commons.wikimedia.org/wiki/Main_Page Wikimedia Commons.</div><br />
</td></tr><br />
</table><br />
<br />
<br /><br />
<br />
<h2>Quantitative considerations</h2><br />
<br />
<br />
<p><b>What concentration of pathogens causes sickness?</b><br />
<br />
<p>A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria <i>Escherichia coli (E.coli)</i> per 100 milliliter of water is present. The result is expressed as “Coliform Microbial Density” and indicates the extent of fecal matter. According to common water quality standards water can have about 200 colonies, and about 1000 in recreational water” (Business Dictionary). <br />
Environmental Protection Agency standards define non-potable water as a sample that contains one bacterium per 100 mL.<br />
<br />
<br /><br />
<p><b>What specific design approaches did we take to try to reduce false positives, while making the biosensor effective? </b><br />
<br />
<p>We incorporated a mutational version of split beta-galactosidase that reforms into a functional enzyme unit only when the halves are brought into close proximity. This mutational version of split beta-galactosidase effectively reduces false positive created by chance interactions in the wild-type split beta-galactosidase. <br />
<br />
<p><br />
<br />
<br />
</p><br />
<br /><br />
<br />
<h2>Why are we doing this?</h2><br />
<br />
<br />
<p><br />
<p><b>What do we hope to accomplish/want to figure out?</b><br />
<p><br />
For this project we are hoping to make our biosensor as user friendly and most cost effective product as possible. In the process in making this design we also wanted to address the results from using the biosensor. We wanted our project to give results in real time and be able to determine the phenotype of the potential pathogen. <br />
<br /><br />
<p><b>Who are we doing this for? What do we care about? </b><br />
<p> This project is primarily based on its applications. We wanted to develop a low-cost biosensor that could be implemented in developing countries. This is because pathogenic bacteria causes diarrhea which is one of the world's leading global health issues. By designing our biosensor it would be a potential solution to this problem. <br />
<br />
<br /><br />
<p><b>What is our ultimate goal?</b><br />
<p>Our ultimate goal for the project is to be able to see our biosensor used in developing nations. Ideally our biosensor would be able to be used as an early detection device in order to prevent future pathogenic outbreaks. This would be a solution to not only maintaining a healthy water supply but also to also improve the overall sanitation of developing nations. <br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ReferencesTeam:Arizona State/References2012-10-27T03:40:33Z<p>Aispas: </p>
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<div>{{:Team:Arizona_State/Template:Header}}<br />
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<body><br />
<h1>References</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<h2>Streptavidin</h2><br />
<br />
<p><br />
<ul><br />
<li><br />
Laitinen, O. H., V. P. Hytönen, H. R. Nordlund, and M. S. Kulomaa. "Genetically Engineered Avidins and Streptavidins." Cellular and Molecular Life Sciences 63.24 (2006): 2992-3017. Print.<br />
</li><br />
<li><br />
Szafranski, Przemyslaw, Charlene M. Mello, Takeshi Sano, Cassandra L. Smith, David L. Kaplan, and Charles R. Cantor. "A New Approach for Containment of Microorganisms: Dual Control of Streptavidin Expression by Antisense RNA and the T7 Transcription System." Applied Biological Sciences 94 (1997): 1059-063. Print.<br />
</li><br />
</ul><br />
</p><br />
<br />
<h2>Topoisomerase</h2><br />
<br />
<p><br />
<ul><br />
<li><br />
Hwang, Y., N. Minkah, K. Perry, G. D. Van Duyne, and F. D. Bushman. "Regulation of Catalysis by the Smallpox Virus Topoisomerase." Journal of Biological Chemistry 281.49 (2006): 38052-8060. Print. <br />
</li><br />
<li><br />
Sekiguchi, JoAnn, and Stewart Shuman. "Requirements for Noncovalent Binding of Vaccinia Topoisomerase I to Duplex DNA." Nucleic Acids Research 22.24 (1994): 5360-365. Print.<br />
</li><br />
<li><br />
Shuman, S. "Recombination Mediated by Vaccinia Virus DNA Topoisomerase I in Escherichia Coli Is Sequence Specific." Proceedings of the National Academy of Sciences 88.22 (1991): 10104-0108. Print. <br />
</li><br />
<li><br />
Shuman, Steward. "Site-specific Interaction of Vaccinia Virus Topoisomerase WI Ith Duplex DNA." The Journal of Biological Chemistry 266.17 (1991): 11372-1379. Print. <br />
</li><br />
</ul><br />
</p><br />
<br />
<h2>Human Practices</h2><br />
<br />
<p><br />
<ul><br />
<li><br />
Arora, Kavita, Subhash Chand, and B. D. Malhotra. "Recent Developments in Bio-molecular Techniques for Food Pathogens." Analytica Chimica Acta (2006): 259-74. Web. <br />
</li><br />
<li><br />
Bai, Sulan, Jinyi Zhao, Yaochuan Zhang, Wensheng Huang, Shi Xu, Haodong Chen, Liu-Min Fan, Ying Chen, and Xing Wang Deng. "Rapid and Reliable Detection of 11 Food-borne Pathogens Using Thin-film Biosensor Chips." Applied Microbiology and Biotechnology 86.3 (2010): 983-90. Print. <br />
</li><br />
<li><br />
Beatty, Mark. "Clinical Infectious Diseases." Epidemic Diarrhea Due to Enterotoxigenic Escherichia Coli. N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://cid.oxfordjournals.org/content/42/3/329.full">http://cid.oxfordjournals.org/content/42/3/329.full</a><br />
&gt;.<br />
</li><br />
<li><br />
Bogosian, Gregg. "American Society for MicrobiologyApplied and Environmental Microbiology." Death of the Escherichia Coli K-12 Strain W3110 in Soil and Water. N.p., 11 June 1996. Web. 03 Oct. 2012. &lt;<br />
<a href="http://aem.asm.org/content/62/11/4114.full.pdf html">http://aem.asm.org/content/62/11/4114.full.pdf</a><br />
&gt; html.<br />
</li><br />
<li><br />
Cairncross, Sandy, Caroline Hunt, Sophie Boisson, Kristof Bostoen, Val Curtis, Isaac CH Fung, and Wolf-Peter Smidth. "Water, Sanitation, and Hygiene of Diarrhoea." International Journal of Epidemiology 39 (2010): 193-205. Print. <br />
</li><br />
<li><br />
Carothers, Thomas. "Revitalizing Democracy Assistance: The Challenge of USAID -Carnegie Endowment for International Peace." Carnegie Endowment for International Peace. N.p., n.d. Web. 24 Oct. 2012. <http://www.carnegieendowment.org/2009/10/27/revitalizing-democracy-assistance-challenge-of-usaid/3hc>.<br />
</li><br />
<li><br />
"Coliform Count." Business Dictionary. N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://www.businessdictionary.com/definition/coliform-count.html">http://www.businessdictionary.com/definition/coliform-count.html</a><br />
&gt;.<br />
</li><br />
<li><br />
De Boer, Enne, and Rijkelt R. Beumer. "Methodology for Detection and Typing of Foodborne Microorganisms." International Journal of Food Microbiology (1999): 119-30. Web. <br />
</li><br />
<li><br />
Engberg, Jørgen. "Water-borne Campylobacter Jejuni Infection in a Danish Town-a 6-week Continuous Source Outbreak." Wiley-Online Library. N.p., 27 Oct. 2008. Web. 03 Oct. 2012. &lt;<br />
<a href="http://onlinelibrary.wiley.com/doi/10.1111/j.1469-0691.1998.tb00348.x/full">http://onlinelibrary.wiley.com/doi/10.1111/j.1469-0691.1998.tb00348.x/full</a><br />
&gt;.<br />
</li><br />
<li><br />
England, Roger. “The Fight Against AIDS in the Larger Context: the end of ‘AIDS exceptionalism’.” UNU-Cornell Africa Series Symposium: The social and economic dimensions of HIV/AIDS in Africa. New York, September 9, 2008. <br />
</li><br />
<li><br />
Heijnen, Leo. "Quantitative Detection of E. Coli, E. Coli O157 and Other Shiga Toxin Producing E. Coli in Water Samples Using a Culture Method Combined with Real-time PCR." Journal of Water and Health 4.4 (2006): n. pag. Web. 20 Oct. 2012. <http://www.iwaponline.com/jwh/004/0487/0040487.pdf>.<br />
</li><br />
<li><br />
Hunter, Paul, Paul Jagals, and Katherine Pond. Valuing Water, Valuing Livelihoods. Ed. John Cameron. London: IWA, 2011. Web.<br />
</li><br />
<li><br />
Johansson, Emily W., and Tessa Wardlaw. Diarrhoea: Why Children Are Still Dying and What Can Be Done. Publication. World Health Organization, 2009. Web. <br />
</li><br />
<li><br />
Kinzelman, Julie. "Enterococci as Indicators of Lake Michigan Recreational Water Quality: Comparison of Two Methodologies and Their Impacts on Public Health Regulatory Events." Applied and Environmental Microbiology 69.1 (2003): n. pag. Print.<br />
</li><br />
<li><br />
McMeekin, T.a., C. Hill, M. Wagner, A. Dahl, and T. Ross. "Ecophysiology of Food-borne Pathogens: Essential Knowledge to Improve Food Safety." International Journal of Food Microbiology 139 (2010): S64-78. Print. <br />
</li><br />
<li><br />
Mellmann, Alexander. "Prospective Genomic Characterization of the German Enterohemorrhagic Escherichia Coli O104:H4 Outbreak by Rapid Next Generation Sequencing Technology." PLOS ONE:. N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0022751?imageURI=info:doi/10.1371/journal.pone.0022751.g001">http://www.plosone.org/article/info:doi/10.1371/journal.pone.0022751?imageURI=info:doi/10.1371/journal.pone.0022751.g001</a><br />
&gt;.<br />
</li><br />
<li><br />
Newkirk, Brian J. "Turning Quicksand into Bedrock: Understanding the Dynamic Effects of Disease-focused Global Health Aid on Health Systems." Harvard-MIT Division of Health Sciences and Technology (2009): 1-90. Web.<br />
</li><br />
<li><br />
Olsen, Sonja J., Gayle Miller, Thomas Breuer, Malinda Kennedy, Charles Higgins, Jim Walford, Gary McKee, Kim Fox, William Bibb, and Paul Mead. "Abstract." National Center for Biotechnology Information. U.S. National Library of Medicine, 21 Sept. 0005. Web. 03 Oct. 2012. &lt;<br />
<a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2730238/">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2730238/</a><br />
&gt;.<br />
</li><br />
<li><br />
Palchetti, Ilaria, and Marco Mascini. "Electroanalytical Biosensors and Their Potential for Food Pathogen and Toxin Detection." Review. 8 Jan. 2008. Print. <br />
</li><br />
<li><br />
Pitkanen, Tarja. "Faecal Contamination of a Municipal Drinking Water Distribution System in Association with Campylobacter Jejuni Infections." Journal of Water and Health 6.3 (2008): n. pag. Web. 21 Oct. 2012. <http://www.iwaponline.com/jwh/006/0365/0060365.pdf>.<br />
</li><br />
<li><br />
Rohde, Holger, MD. "The New England Journal of Medicine." Open-Source Genomic Analysis of Shiga-Toxinâ Producing E. Coli O104:H4 âNEJM. N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://www.nejm.org/doi/full/10.1056/nejmoa1107643">http://www.nejm.org/doi/full/10.1056/nejmoa1107643</a><br />
&gt;.<br />
</li><br />
<li><br />
Shannon, K. E. "Application of Real-time Quantitative PCR for the Detection of Selected Bacterial Pathogens during Municipal Wastewater Treatment." Science of The Total Environment 382.1 (2007): 121-29. Sciverse. Web. 20 Oct. 2012. <http://www.sciencedirect.com.ezproxy1.lib.asu.edu/science/article/pii/S0048969707002963#>.<br />
</li><br />
<li><br />
Swerdlow DL. "Waterborne Outbreak in Missouri of Escherichia Coli O157:H7 Associated with Bloody Diarrhea and Death." A Waterborne Outbreak in Missouri of Escherichia Coli O157:H7 Associated with Bloody Diarrhea... N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://ukpmc.ac.uk/abstract/MED/1416555/reload=0;jsessionid=485eElQK2FrO5B4oKFQ1.0">http://ukpmc.ac.uk/abstract/MED/1416555/reload=0;jsessionid=485eElQK2FrO5B4oKFQ1.0</a><br />
&gt;.<br />
</li><br />
<li><br />
"THE DUAL-USE DILEMMA." Parliamentary Office of Science and Technology 340 (2009): n. pag. Print.<br />
</li><br />
<li><br />
"Water-related Diseases." World Health Organization. Web. 02 Oct. 2012. &lt;<br />
<a href="http://www.who.int/water_sanitation_health/diseases/diarrhoea/en/">http://www.who.int/water_sanitation_health/diseases/diarrhoea/en/</a><br />
&gt;. <br />
</li><br />
<li><br />
"What Is COLIFORM COUNT?" Definition of COLIFORM COUNT (Black's Law Dictionary). N.p., n.d. Web. 26 Oct. 2012. <http://thelawdictionary.org/coliform-count/>.<br />
</li><br />
<li><br />
World Health Organization and UNICEF. Progress of Sanitation and Drinking Water. World Health Organization and UNICEF, 2010. Print. <br />
</li><br />
<li><br />
World Health Organization. Emerging Issues in Water and Infectious Disease. World Health Organization, 2003. Print. <br />
</li><br />
<li><br />
World Health Organization. Guidelines for the Control of Shigellosis, including Epidemics Due to Shigallea Dysenteriae. Geneva: World Health Organization, 2005. Print. <br />
</li><br />
<li><br />
World Health Organization. Water Safety Plan Manual. Geneva: World Health Organization, 2009. Print.<br />
</li><br />
</ul><br />
</p><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ProblemTeam:Arizona State/Problem2012-10-27T03:36:26Z<p>Aispas: </p>
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<br />
<br /><br />
<h1>The Problem</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<p><br />
Viewed as a minor inconvenience in the developed world, diarrhea can be a death sentence. Diarrhea can be life threatening as it causes severe dehydration as a result of extensive fluid loss. An estimated 2.0 billion cases of diarrhea occur each year amongst children under five years of age. Of these cases, 1.5 million children die. The major pathogens that most frequently cause acute childhood diarrhea cases are bacterial pathogens such as <i>E. coli, Shigella, Campylobacter and Salmonella</i>. Currently, existing biosensors for water-borne pathogens are either costly, inaccessible to developing countries, difficult to use without training, and not very reliable. For example, immunoassays, which uses antibodies specific for certain antigens on pathogenic diarrhea, have a good turnaround time. However, not all antigens have available antibodies that can be used for detection, and those antibodies that are available can be very costly. As such, the ASU iGEM team plans to develop an inexpensive way for communities to test the purity of water sources. To this end, we aimed to identify the specific pathogens in the water source in efforts of reducing the incidence of childhood diarrhea and ultimately decreasing mortality rates. <br />
</p><br />
<br />
<br /><br />
<br />
<table align="center"><br />
<tr><td><br />
<img src="https://static.igem.org/mediawiki/2012/0/03/Asuigem_diseasemap.png" width="800"><br />
</tr></td><br />
<tr><td><br />
<div class="figText">Figure 1: Epidemiology map indicating disability-adjusted life year for diarrhea per 100,000 inhabitants (2004).<br>Image shown above is from the Wikimedia Commons, http://commons.wikimedia.org/wiki/Main_Page Wikimedia Commons.</div><br />
</td></tr><br />
</table><br />
<br />
<br /><br />
<br />
<h2>Quantitative considerations</h2><br />
<br />
<br />
<p><b>What concentration of pathogens causes sickness?</b><br />
<br />
<p>In determining what kinds of scenarios our biosensor would work in, a concentration had to be determined for what would be considered an outbreak. Based on research that was found for our project, patients' stool samples were tested for antibodies that were specific to <i>E.coli</i> (Olsen). <br />
<br /><br />
<p><b>What specific design approaches did we take to try to reduce false positives, while making the biosensor effective? </b><br />
<p> A coliform count is a test of the pathogens in a sample of water. The results are based on the number of the colonies of coliform-bacteria <i>Escherichia coli (E.coli)</i> per 100 milliliter water sample. The result will be expressed as “Coliform Microbial Density” which gives an amount of feces in the water sample(The Law Dictionary). <br />
<p><br />
Environmental Protection Agency standards define non-potable water as a sample that contains one bacterium per 100 mL.<br />
</p><br />
<br /><br />
<br />
<h2>Why are we doing this?</h2><br />
<br />
<br />
<p><br />
<p><b>What do we hope to accomplish/want to figure out?</b><br />
<p><br />
For this project we are hoping to make our biosensor as user friendly and most cost effective product as possible. In the process in making this design we also wanted to address the results from using the biosensor. We wanted our project to give results in real time and be able to determine the phenotype of the potential pathogen. <br />
<br /><br />
<p><b>Who are we doing this for? What do we care about? </b><br />
<p> This project is primarily based on its applications. We wanted to develop a low-cost biosensor that could be implemented in developing countries. This is because pathogenic bacteria causes diarrhea which is one of the world's leading global health issues. By designing our biosensor it would be a potential solution to this problem. <br />
<br />
<br /><br />
<p><b>What is our ultimate goal?</b><br />
<p>Our ultimate goal for the project is to be able to see our biosensor used in developing nations. Ideally our biosensor would be able to be used as an early detection device in order to prevent future pathogenic outbreaks. This would be a solution to not only maintaining a healthy water supply but also to also improve the overall sanitation of developing nations. <br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ProblemTeam:Arizona State/Problem2012-10-27T03:33:08Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<br />
<br /><br />
<h1>The Problem</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<p><br />
Viewed as a minor inconvenience in the developed world, diarrhea can be a death sentence. Diarrhea can be life threatening as it causes severe dehydration as a result of extensive fluid loss. An estimated 2.0 billion cases of diarrhea occur each year amongst children under five years of age. Of these cases, 1.5 million children die. The major pathogens that most frequently cause acute childhood diarrhea cases are bacterial pathogens such as <i>E. coli, Shigella, Campylobacter and Salmonella</i>. Currently, existing biosensors for water-borne pathogens are either costly, inaccessible to developing countries, difficult to use without training, and not very reliable. For example, immunoassays, which uses antibodies specific for certain antigens on pathogenic diarrhea, have a good turnaround time. However, not all antigens have available antibodies that can be used for detection, and those antibodies that are available can be very costly. As such, the ASU iGEM team plans to develop an inexpensive way for communities to test the purity of water sources. To this end, we aimed to identify the specific pathogens in the water source in efforts of reducing the incidence of childhood diarrhea and ultimately decreasing mortality rates. <br />
</p><br />
<br />
<br /><br />
<br />
<table align="center"><br />
<tr><td><br />
<img src="https://static.igem.org/mediawiki/2012/0/03/Asuigem_diseasemap.png" width="800"><br />
</tr></td><br />
<tr><td><br />
<div class="figText">Figure 1: Epidemiology map indicating disability-adjusted life year for diarrhea per 100,000 inhabitants (2004).<br>Image shown above is from the Wikimedia Commons, http://commons.wikimedia.org/wiki/Main_Page Wikimedia Commons.</div><br />
</td></tr><br />
</table><br />
<br />
<br /><br />
<br />
<h2>Quantitative considerations</h2><br />
<br />
<br />
<p><b>What concentration of pathogens causes sickness?</b><br />
<br />
<p>In determining what kinds of scenarios our biosensor would work in, a concentration had to be determined for what would be considered an outbreak. Based on research that was found for our project, patients' stool samples were tested for antibodies. According to Olsen, an antibody is considered positive if the ratio for IgM is greater than 1:320 or greater than 1:160 for IgG.<br />
<br /><br />
<p><b>What specific design approaches did we take to try to reduce false positives, while making the biosensor effective? </b><br />
<p> A coliform count is a test of the pathogens in a sample of water. The results are based on the number of the colonies of coliform-bacteria <i>Escherichia coli (E.coli)</i> per 100 milliliter water sample. The result will be expressed as “Coliform Microbial Density” which gives an amount of feces in the water sample. According to common water quality standards water can have about 200 colonies, and about 1000 in recreational water” (Business Dictionary). <br />
<p><br />
Environmental Protection Agency standards define non-potable water as a sample that contains one bacterium per 100 mL.<br />
</p><br />
<br /><br />
<br />
<h2>Why are we doing this?</h2><br />
<br />
<br />
<p><br />
<p><b>What do we hope to accomplish/want to figure out?</b><br />
<p><br />
For this project we are hoping to make our biosensor as user friendly and most cost effective product as possible. In the process in making this design we also wanted to address the results from using the biosensor. We wanted our project to give results in real time and be able to determine the phenotype of the potential pathogen. <br />
<br /><br />
<p><b>Who are we doing this for? What do we care about? </b><br />
<p> This project is primarily based on its applications. We wanted to develop a low-cost biosensor that could be implemented in developing countries. This is because pathogenic bacteria causes diarrhea which is one of the world's leading global health issues. By designing our biosensor it would be a potential solution to this problem. <br />
<br />
<br /><br />
<p><b>What is our ultimate goal?</b><br />
<p>Our ultimate goal for the project is to be able to see our biosensor used in developing nations. Ideally our biosensor would be able to be used as an early detection device in order to prevent future pathogenic outbreaks. This would be a solution to not only maintaining a healthy water supply but also to also improve the overall sanitation of developing nations. <br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/FieldApplicationsTeam:Arizona State/FieldApplications2012-10-27T03:24:08Z<p>Aispas: </p>
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<h1><i>Escherichia Coli</i> Case Studies</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<h2> Timeline of an outbreak </h2><br />
<br />
<p><br />
In order to implement the biosensor correctly, it is imperative to find data about how <i>E.coli</i> outbreaks progressed. Last year, there was on outbreak of <i>E.coli</i> O104:H4 in Germany. It was first detected in early May of 2011, by causing an increased amount of patient who presented hemolytic uremic syndrome (Rohde). As the <i>E.coli</i> outbreak continued to spread, traces of <i>E.coli</i> were present in different foods. According to Dr. Rohde in the Open-Source Genomic Analysis of Shiga-Toxin-Producing <i>E.coli</i> O104:H4 case study, the genomic experiments began with how the <i>E.coli</i> phenotype was determined (Rohde). It wasn’t until five days after the first detection of the <i>E.coli</i> did lab work begin (Rohde). Although this case study reference is a food <i>E.coli</i> outbreak, it continued to grow in size as more food was found to be contaminated. This scenario is similar to a water based <i>E.coli</i> outbreak because typically in larger outbreaks it will affect more than one geographic area. Using this timeline as an example, between the first detection of the outbreak to the <i>E.coli</i> phenotype being determined, it was a period of three weeks. </p><br />
<br />
<p>According to research, detection of the pathogen took a very small amount of time compared to determining the phenotype of the pathogen (Rohde). At this point in time there would have been many sick patients and potentially deaths depending on the severity of the outbreak. With our biosensor, this time could be dramatically reduced. Our biosensor could detect ideally any pathogen of interest. In a hypothetical situation, a potential timeline would be that the water would be tested the day a potential contamination would occur. This contamination could come from heavy rain, flooding, development of a new community, natural disaster, etc. Within minutes of the test being initiated, a pathogen would be able to be detected. This would greatly decrease the amount of locals that could get infected with the pathogen because a contamination warning would be implemented the same day. According to current practices and timelines, a water contamination warning would not be able to go out until two days after the pathogen was detected (Pitkanen). Our biosensor would reduce this time by turning days into minutes. By using the team’s biosensor, we are able to engineer our biosensor to a specific phenotype of pathogen. We would be able to do this onsite or have our biosensor pre-designed before its implemented. This would eliminate expensive lab experiments and time by already having the phenotype of the pathogen determined.</p><br />
<br />
<br />
</p><br />
<br /><br />
<br />
<h2> Finding the source of an outbreak? </h2><br />
<br />
<p><br />
As defined an outbreak is an occurrence of a disease greater than two or more infected patients caused by the same water exposure (Centers for Disease Control and Prevention). Though many of these instances occur in developing countries with lack of sanitation and public health awareness, outbreaks still occurred in industrialized nations such as the United States and Canada (Shannon). For example, in Denmark there was an outbreak of Campylobacter jejuni that happened between the years 1995-1996 (Engberg). This bacterium is similar to <i>E.coli</i> in that it behaves very similar. Campylobacter jejuni is one of the most common bacterial causes of diarrhea in humans in developing countries (Engberg).</p><br />
<br />
<p>In December of 1995, a procedure was performed to test the amount of nitrate in the ground water. In the process of testing this, a sewage pipe was damaged and then leaked into the ground water supply. It took over a four weeks for the water pump to be turned off from the initial contamination (Engberg). For this particular case, a very high coliform count was found in the infected water. “A coliform count is a water contamination test. The test involves the counting of colonies of the coliform-bacteria <i>Escherichia coli</i> (<i>E.coli</i>)in a 100 milliliter water sample. The result is given as "Coliform Microbial Density". This indicates the amount of feces present in the contaminated water sample(The Law Dictionary).</p> <br />
<br />
<p>The Environmental Protection Agency, instituted rules for beaches and recreational waters to ensure that people who came into contact with bodies of water would not become ill. These regulations stated that for any bodies of freshwater, the advisory limits are 235 CFU/100 ml for <i>E.coli</i> (Kinzelman). The standards for common water quality are that recreational water cannot test positive for more than 1000 colonies per 100ml (The Law Dictionary). In Canada, before water can be re-used, it must go through treatments to eliminate pathogens or particles. Under ideal conditions, the efficiency of the pathogen removal system is measured in effluents. This accounts for the amount of waste water being treated for the removal of pathogens. By the guidelines issued by Environment Canada, fecal coliforms in effluents are 400 CFU per 100 ml (Shannon). It is at these concentrations which can be harmful to human populations. With the use of our biosensor we would be able to test any water sources to see if pathogens were present. Our biosensor is both portable and efficient, which would allow for finding the source of an outbreak much easier.</p><br />
<br />
</p><br />
<br /><br />
<br />
<h2> What if the <i>E.coli</i> strain mutated or the <i>E.coli</i> was undetectable?</h2><br />
<h4>What are the chances of a mutation occurring or what should be done if a mutation occurs? </h4><br />
<br />
<p><br />
Currently there is a controversial hypothesis that although <i>E.coli</i> can be detected it is viable but its non-culturable (Bogosian). This topic pertains to our biosensor because there could be pathogens present in water, This would affect the timeline of an outbreak as well as infect more people with contaminated water. This poses as a public health issue because of the developing nations who do not have the equipment or technology for this kind of situation. It has been shown that although this is health risk, it has only contributed to 22 deaths and 104 total cases in the last seventy years (Bogosian). It has been shown that although the <i>E.coli</i> is present, the cells actually die off based on their living conditions. A study was conducted to determine if changes in cell populations were due to cell death or to the cells maturing into the non-culturable state (Bogosian). This proved to be very useful because the study tested what kinds of environment the <i>E.coli</i> cells would either reject their populations or thrive to cause an outbreak. The results were that <i>E.coli</i> cells will not thrive in these environments (Bogosian). This proves that when an <i>E.coli</i> outbreak occurs it will be because the cells are in an ideal environment where they are able to grow readily. Although <i>E.coli</i> can be present in water does not mean an outbreak will occur. Our biosensor would ideally be able to detect these pathogens no matter how many colonies were present. Although an outbreak may not occur, the water could still be monitored more closely to prevent an outbreak. <br />
</p><br />
<br /><br />
<br />
<h2> How many tests should be done for an outbreak? </h2><br />
<br />
<p><br />
In each of the case studies that were researched, it became apparent that each outbreak has its own characteristics. For example, in 2011, there was an outbreak that took place in Germany where there was a very high rate of expression in adults, especially women (Rohde). Since each outbreak is unique in its own way, it is difficult to determine how many tests should be done to determine the severity of the outbreak. According to a case study about an outbreak that took place in Alpine, Wyoming, physicians were seeing an increased rate of patients who presented with bloody diarrhea (Olsen). More cases began showing up not only in Wyoming, but also in the states Utah and Washington (Olsen). Prior to the outbreak, the Alpine municipal water system was tested multiple times each month for coliform counts. In this case, they were positive for <i>E.coli</i> in the months April, May, and June (Olsen). It was not until late June that the outbreak occurred, and by middle of July they had found the source of this occurrence. Once the outbreak was detected, stool samples from infected patients were then sent to a lab for further testing. From the time that the outbreak began to the time that the source was found was about 3-4 weeks (Olsen). During this time, tests were being done by multiple agencies such as the Wyoming State laboratory and the Utah Department of Health State Laboratory (Olsen). Using the biosensor that our team has developed, the severity of the outbreak would be extremely decreased. Although regular water samples are taken, once the water tested positive for pathogens, water contamination warnings should have been implemented in ensure that an outbreak was minimalized. With the biosensor designed by the ASU iGEM team, our biosensor would be pathogen specific to detect whether that pathogen is present or not in water. Our biosensor would be able detect pathogens in water within minutes of running the experiment. This would greatly decrease the amount of people that potentially could get sick. <br />
</p><br />
<br /><br />
<br />
<h2> What are the current practices? </h2><br />
<br />
<p><br />
<i>E.coli</i> outbreaks have been known to occur in different sources, such as food, water, and plants. It has been shown that before an outbreak takes place in water, there are usually signs of <i>E.coli</i> being present (Olsen). Before an outbreak can occur the cells must be able to survive in their environment. In recent case studies it has been found that although <i>E.coli</i> was found to be present in the water supply, although the amount of <i>E.coli</i> was insufficient. It was not until after an outbreak occurred and patients began having symptoms did the amount of <i>E.coli</i> becomes a problem. Once the <i>E.coli</i> outbreak has occurred, it will usually take a few weeks to run tests. These experiments can be determining the phenotype of <i>E.coli</i> or just to determine how many people could potentially be affected by the outbreak. It is quite common during <i>E.coli</i> water outbreaks for the cohort case studies to take place. These studies determine a statistical analysis of the outbreak, where the statisticians where able to see how the outbreak progressed with how many people it infected (Olsen). When <i>E.coli</i> is present in other sources such as food and plants, it is usually not known that this is the source until after the outbreak has already occurred. The biosensor developed by the ASU team, eliminated many of these issues. By engineering the biosensor to already be pathogen specific, it decreases the amount of time to determine what the pathogen. The efficiency of our biosensor allows for the efforts the community to then be focused on water purification, instead of waiting for lab results. <br />
</p><br />
<br /><br />
<br />
<h2> How does the biosensor improve sanitation?</h2><br />
<h4> Why is there a need for a real time/faster response for the biosensor needed? </h4><br />
<br />
<p>Improving sanitation and hygiene of water has been one of the primary goals for Arizona State’s iGEM team. As a result of producing a biosensor to detect pathogens, it has the ability to not only prevent outbreaks from occurring but also to minimize them. Our biosensor has the ability to be used to detect different kinds of pathogens. This is very useful because if an outbreak were to occur, the amount of time in spending on determining the phenotype of the pathogen can then be spent on eliminating it from water sources. This is another reason why our biosensor can be so effective by being able to detect specific pathogens, but it is also able to give you the answers in real time. This eliminates even more time in the process of determining the pathogen. By being able to prevent an outbreak from occurring, we would be able to improve the sanitation of water, especially in developing countries. It is in developing nations where the outbreaks are the most prevalent. Our biosensor was designed to be easy to use and efficient. This would allow for it to be portable to test many different kinds of water sources. The more our biosensor is used, the more safety and sanitation would be improved. <br />
</p><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/FieldApplicationsTeam:Arizona State/FieldApplications2012-10-27T03:08:10Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1><i>Escherichia Coli</i> Case Studies</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<h2> Timeline of an outbreak </h2><br />
<br />
<p><br />
In order to implement the biosensor correctly, it is imperative to find data about how <i>E.coli</i> outbreaks progressed. Last year, there was on outbreak of <i>E.coli</i> O104:H4 in Germany. It was first detected in early May of 2011, by causing an increased amount of patient who presented hemolytic uremic syndrome (Rohde). As the <i>E.coli</i> outbreak continued to spread, traces of <i>E.coli</i> were present in different foods. According to Dr. Rohde in the Open-Source Genomic Analysis of Shiga-Toxin-Producing <i>E.coli</i> O104:H4 case study, the genomic experiments began with how the <i>E.coli</i> phenotype was determined (Rohde). It wasn’t until five days after the first detection of the <i>E.coli</i> did lab work begin (Rohde). Although this case study reference is a food <i>E.coli</i> outbreak, it continued to grow in size as more food was found to be contaminated. This scenario is similar to a water based <i>E.coli</i> outbreak because typically in larger outbreaks it will affect more than one geographic area. Using this timeline as an example, between the first detection of the outbreak to the <i>E.coli</i> phenotype being determined, it was a period of three weeks. </p><br />
<br />
<p>According to research, detection of the pathogen took a very small amount of time compared to determining the phenotype of the pathogen (Rohde). At this point in time there would have been many sick patients and potentially deaths depending on the severity of the outbreak. With our biosensor, this time could be dramatically reduced. Our biosensor could detect ideally any pathogen of interest. In a hypothetical situation, a potential timeline would be that the water would be tested the day a potential contamination would occur. This contamination could come from heavy rain, flooding, development of a new community, natural disaster, etc. Within minutes of the test being initiated, a pathogen would be able to be detected. This would greatly decrease the amount of locals that could get infected with the pathogen because a contamination warning would be implemented the same day. According to current practices and timelines, a water contamination warning would not be able to go out until two days after the pathogen was detected (Pitkanen). Our biosensor would reduce this time by turning days into minutes. By using the team’s biosensor, we are able to engineer our biosensor to a specific phenotype of pathogen. We would be able to do this onsite or have our biosensor pre-designed before its implemented. This would eliminate expensive lab experiments and time by already having the phenotype of the pathogen determined.</p><br />
<br />
<br />
</p><br />
<br /><br />
<br />
<h2> Finding the source of an outbreak? </h2><br />
<br />
<p><br />
As defined an outbreak is an occurrence of a disease greater than two or more infected patients caused by the same water exposure (Centers for Disease Control and Prevention). Though many of these instances occur in developing countries with lack of sanitation and public health awareness, outbreaks still occurred in industrialized nations such as the United States and Canada (Shannon). For example, in Denmark there was an outbreak of Campylobacter jejuni that happened between the years 1995-1996 (Engberg). This bacterium is similar to <i>E.coli</i> in that it behaves very similar. Campylobacter jejuni is one of the most common bacterial causes of diarrhea in humans in developing countries (Engberg).</p><br />
<br />
<p>In December of 1995, a procedure was performed to test the amount of nitrate in the ground water. In the process of testing this, a sewage pipe was damaged and then leaked into the ground water supply. It took over a four weeks for the water pump to be turned off from the initial contamination (Engberg). For this particular case, a very high coliform count was found in the infected water. “A coliform count is a water contamination test. The test involves the counting of colonies of the coliform-bacteria <i>Escherichia coli</i> (<i>E.coli</i>)in a 100 milliliter water sample. The result is given as "Coliform Microbial Density". This indicates the amount of feces present in the contaminated water sample(The Law Dictionary).</p> <br />
<br />
<p>The Environmental Protection Agency, instituted regulations for beaches and recreational waters to ensure that people who came into contact with bodies of water would not become ill. These regulations stated that for freshwater the advisory limits are 235 CFU/100 ml for <i>E.coli</i> (Kinzelman). The standards for common water quality are that recreational water cannot test positive for more than 1000 colonies. All drinking water must be negative for any colonies (The Law Dictionary). In Canada, before water can be re-used, it must go through treatments to eliminate pathogens or particles. It is under normal operating conditions, the efficiency of pathogen removal is measured in the final effluent. This accounts for the amount of waste water being treated for the removal of pathogens. Under the guidelines issued by Environment Canada, fecal coliforms in final effluents are limited to 400 CFU per 100 ml after disinfection (Shannon). It is at these concentrations which can be harmful to human populations. With the use of our biosensor we would be able to test any water sources to see if pathogens were present. Our biosensor is both portable and efficient, which would allow for finding the source of an outbreak much easier.</p><br />
<br />
</p><br />
<br /><br />
<br />
<h2> What if the <i>E.coli</i> strain mutated or the <i>E.coli</i> was undetectable?</h2><br />
<h4>What are the chances of a mutation occurring or what should be done if a mutation occurs? </h4><br />
<br />
<p><br />
Currently there is a controversial hypothesis that although <i>E.coli</i> can be detected it is viable but its non-culturable (Bogosian). This topic pertains to our biosensor because there could be pathogens present in water, but not enough to cause an outbreak. This holds true for any bacteria that cannot be cultured by standard methods. A culturable bacterium is inoculated into a sterile microcosm, most commonly seawater or river water, and incubated for a number of days with regular monitoring (Bogosian). This would affect the timeline of an outbreak as well as infect more people with contaminated water. This poses as an obvious public health issue for developing nations who do not have the equipment or technology for this kind of situation. Thus far it has been shown that although this poses as a health risk, it has only been attributed to 22 deaths and 104 total cases in the United States in the last 70 years (Bogosian). It has been shown that although the <i>E.coli</i> is present, the cells actually die off based on their living conditions. A study was conducted to determine if changes in cell populations were due to cell death or to the cells developing into the non-culturable state (Bogosian). This proved to be very useful because the study tested what kinds of environment the <i>E.coli</i> cells would either decline in their populations or thrive to cause an outbreak. The conclusion is that <i>E.coli</i> cells did not thrive in non-sterile environments (Bogosian). This proves that when an <i>E.coli</i> outbreak occurs it will be because the cells are in an optimum environment where they are able to grow readily. Although <i>E.coli</i> can be present in water does not mean an outbreak will occur. Our biosensor would ideally be able to detect these pathogens no matter how many colonies were present. Although an outbreak may not occur, the water could still be monitored more closely to prevent an outbreak. <br />
</p><br />
<br /><br />
<br />
<h2> How many tests should be done for an outbreak? </h2><br />
<br />
<p><br />
In each of the case studies that were researched, it became apparent that each outbreak has its own characteristics. For example, in 2011, there was an outbreak that took place in Germany where there was a very high incidence in adults, especially women (Rohde). Since each outbreak is unique in its own way, it is difficult to determine how many tests should be done to determine the severity of the outbreak. According to case study about an outbreak that took place in Alpine, Wyoming, physicians began seeing more patients with bloody diarrhea (Olsen). More cases began showing up not only in Wyoming, but also Utah and Washington (Olsen). During the lab investigation of this outbreak, serum was tested from town residents to check for IgM antibodies to the O157 lipopolysaccharides (Olsen). Prior to the outbreak, the Alpine municipal water system was tested multiple times each month for coliform counts. In this case, they were positive results for <i>E.coli</i> in April, May, and June of that year (Olsen). It was in late June that the outbreak occurred, and by middle of July they had found the source of this occurrence. Once the outbreak was detected, stool samples from infected patients were then sent to a lab for further testing. From the time that the outbreak began to the time that the source was found was about 3-4 weeks (Olsen). During this time, tests were being done by multiple agencies such as the Wyoming State laboratory and the Utah Department of Health State Laboratory (Olsen). Using the biosensor that our team has developed, the severity of the outbreak would be extremely decreased. Although regular water samples are taken, once the water tested positive for pathogens, water contamination warnings should have been implemented in ensure that an outbreak was minimalized. With the biosensor designed by the ASU iGEM team, our biosensor would be pathogen specific to detect whether that pathogen is present or not in water. Our biosensor would be able detect pathogens in water within minutes of running the experiment. This would greatly decrease the amount of people that potentially could get sick. <br />
</p><br />
<br /><br />
<br />
<h2> What are the current practices? </h2><br />
<br />
<p><br />
<i>E.coli</i> outbreaks have been known to occur in different sources, such as food, water, and plants. It has been shown that before an outbreak takes place in water, there are typically signs that <i>E.coli</i> is present (Olsen). This is because before an outbreak can occur the cells must be able to survive in their environment. In recent case studies it has been found that although <i>E.coli</i> was found to be present in the water supply, although the amount of <i>E.coli</i> was insufficient. It was not until after an outbreak occurred and patients began having symptoms did the amount of <i>E.coli</i> becomes a problem. Once the <i>E.coli</i> outbreak has occurred, it will usually take a few weeks to run tests. These experiments can be determining the phenotype of <i>E.coli</i> or just to determine how many people could potentially be affected by the outbreak. It is quite common during <i>E.coli</i> water outbreaks for the cohort case studies to take place. These studies determine the statistical analysis of the outbreak, where the analysts can see how the outbreak progressed with how many people it infected (Olsen). When <i>E.coli</i> is present in other sources such as food and plants, it is usually not known that this is the source until after the outbreak has already occurred. The biosensor developed by the ASU team, eliminated many of these issues. By engineering the biosensor to already be pathogen specific, it decreases the amount of time to determine what the pathogen. The efficiency of our biosensor allows for the efforts the community to then be focused on water purification, instead of waiting for lab results. <br />
</p><br />
<br /><br />
<br />
<h2> How does the biosensor improve sanitation?</h2><br />
<h4> Why is there a need for a real time/faster response for the biosensor needed? </h4><br />
<br />
<p>Improving sanitation and hygiene of water has been one of the primary goals for Arizona State’s iGEM team. As a result of producing a biosensor to detect pathogens, it has the ability to not only prevent outbreaks from occurring but also to minimize them. Our biosensor has the ability to be used to detect different kinds of pathogens. This is very useful because if an outbreak were to occur, the amount of time in spending on determining the phenotype of the pathogen can then be spent on eliminating it from water sources. This is another reason why our biosensor can be so effective by being able to detect specific pathogens, but it is also able to give you the answers in real time. This eliminates even more time in the process of determining the pathogen. By being able to prevent an outbreak from occurring, we would be able to improve the sanitation of water, especially in developing countries. It is in developing nations where the outbreaks are the most prevalent. Our biosensor was designed to be easy to use and efficient. This would allow for it to be portable to test many different kinds of water sources. The more our biosensor is used, the more safety and sanitation would be improved. <br />
</p><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/FieldApplicationsTeam:Arizona State/FieldApplications2012-10-27T02:52:29Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1><i>Escherichia Coli</i> Case Studies</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<h2> Timeline of an outbreak </h2><br />
<br />
<p><br />
In order to implement the biosensor correctly, it is imperative to find data about how <i>E.coli</i> outbreaks progressed. Last year, there was on outbreak of <i>E.coli</i> O104:H4 in Germany. It was first detected in early May of 2011, by causing an increased frequency of hemolytic uremic syndrome (Rohde). As the <i>E.coli</i> outbreak continued to spread, traces of <i>E.coli</i> were present in different foods. According to Dr. Rohde in the Open-Source Genomic Analysis of Shiga-Toxin-Producing <i>E.coli</i> O104:H4 case study, the genomic events began with how the <i>E.coli</i> phenotype was determined (Rohde). It wasn’t until five days after the first detection of the <i>E.coli</i> did lab work begin (Rohde). Although this case study reference is a food <i>E.coli</i> outbreak, it continued to grow in size as more food was found to be contaminated. This scenario is similar to a water based <i>E.coli</i> outbreak because typically in larger outbreaks it will affect more than one geographic area. Using this timeline as an example, between the first detection of the outbreak to the <i>E.coli</i> phenotype being determined, it was a period of three weeks. </p><br />
<br />
<p>According to research, detection of the pathogen took a very small amount of time compared to determining the phenotype of the pathogen (Rohde). At this point in time there would have been many sick patients and potentially deaths depending on the severity of the outbreak. With our biosensor, this time could be dramatically reduced. Our biosensor could detect ideally any pathogen of interest. In a hypothetical situation, a potential timeline would be that the water would be tested the day a potential contamination would occur. This contamination could come from heavy rain, flooding, development of a new community, natural disaster, etc. Within minutes of the test being initiated, a pathogen would be able to be detected. This would greatly decrease the amount of locals that could get infected with the pathogen because a contamination warning would be implemented the same day. According to current practices and timelines, a water contamination warning would not be able to go out until two days after the pathogen was detected (Pitkanen). Our biosensor would reduce this time by turning days into minutes. By using the team’s biosensor, we are able to engineer our biosensor to a specific phenotype of pathogen. We would be able to do this onsite or have our biosensor pre-designed before its implemented. This would eliminate expensive lab experiments and time by already having the phenotype of the pathogen determined.</p><br />
<br />
<br />
</p><br />
<br /><br />
<br />
<h2> Finding the source of an outbreak? </h2><br />
<br />
<p><br />
As defined an outbreak is an occurrence of a disease greater than two or more infections caused by the same water exposure (Centers for Disease Control and Prevention). Though many of these infections occur in developing countries with lower levels of sanitation and less public health awareness, outbreaks have occurred in developed countries such as the United States and Canada (Shannon). For example, in Denmark there was an outbreak of Campylobacter jejuni that happened between the years 1995-1996 (Engberg). This bacterium is similar to <i>E.coli</i> in that it behaves very similar. Campylobacter jejuni is the most commonly reported bacterial cause of diarrhea in humans in developing countries (Engberg).</p><br />
<br />
<p>In December of 1995, a procedure was performed to test the amount of nitrate in the ground water. In the process of testing this, a sewage pipe was damaged and then leaked into the ground water supply. It took over a month for the water pump to be turned off from the initial point of contamination (Engberg). For this particular case, a very high coliform count was found in the infected water. “A coliform count is a water contamination test. The test involves the counting of colonies of the coliform-bacteria <i>Escherichia coli</i> (<i>E.coli</i>) per 100 milliliter of water. The result is expressed as "Coliform Microbial Density". This indicates the extent of fecal matter present in the contaminated water(The Law Dictionary).</p> <br />
<br />
<p>The Environmental Protection Agency, instituted regulations for beaches and recreational waters to ensure that people who came into contact with bodies of water would not become ill. These regulations stated that for freshwater the present single-sample advisory limits are 235 CFU/100 ml for <i>E.coli</i> (Kinzelman). “According to common water quality standards, recreational (fishing and boating) water can have no more than 1000 colonies. Drinking water must be completely free from any colonies, bathing and swimming pool water can have no more than 200 colonies” (The Law Dictionary). In Canada, before water can be re-used, it must go through treatments to eliminate pathogens or particles. It is under normal operating conditions, the efficiency of pathogen removal is measured in the final effluent. This accounts for the amount of waste water being treated for the removal of pathogens. Under the guidelines issued by Environment Canada, fecal coliforms in final effluents are limited to 400 CFU per 100 ml after disinfection (Shannon). It is at these concentrations which can be harmful to human populations. With the use of our biosensor we would be able to test any water sources to see if pathogens were present. Our biosensor is both portable and efficient, which would allow for finding the source of an outbreak much easier.</p><br />
<br />
</p><br />
<br /><br />
<br />
<h2> What if the <i>E.coli</i> strain mutated or the <i>E.coli</i> was undetectable?</h2><br />
<h4>What are the chances of a mutation occurring or what should be done if a mutation occurs? </h4><br />
<br />
<p><br />
Currently there is a controversial hypothesis that although <i>E.coli</i> can be detected it is viable but its non-culturable (Bogosian). This topic pertains to our biosensor because there could be pathogens present in water, but not enough to cause an outbreak. This holds true for any bacteria that cannot be cultured by standard methods. A culturable bacterium is inoculated into a sterile microcosm, most commonly seawater or river water, and incubated for a number of days with regular monitoring (Bogosian). This would affect the timeline of an outbreak as well as infect more people with contaminated water. This poses as an obvious public health issue for developing nations who do not have the equipment or technology for this kind of situation. Thus far it has been shown that although this poses as a health risk, it has only been attributed to 22 deaths and 104 total cases in the United States in the last 70 years (Bogosian). It has been shown that although the <i>E.coli</i> is present, the cells actually die off based on their living conditions. A study was conducted to determine if changes in cell populations were due to cell death or to the cells developing into the non-culturable state (Bogosian). This proved to be very useful because the study tested what kinds of environment the <i>E.coli</i> cells would either decline in their populations or thrive to cause an outbreak. The conclusion is that <i>E.coli</i> cells did not thrive in non-sterile environments (Bogosian). This proves that when an <i>E.coli</i> outbreak occurs it will be because the cells are in an optimum environment where they are able to grow readily. Although <i>E.coli</i> can be present in water does not mean an outbreak will occur. Our biosensor would ideally be able to detect these pathogens no matter how many colonies were present. Although an outbreak may not occur, the water could still be monitored more closely to prevent an outbreak. <br />
</p><br />
<br /><br />
<br />
<h2> How many tests should be done for an outbreak? </h2><br />
<br />
<p><br />
In each of the case studies that were researched, it became apparent that each outbreak has its own characteristics. For example, in 2011, there was an outbreak that took place in Germany where there was a very high incidence in adults, especially women (Rohde). Since each outbreak is unique in its own way, it is difficult to determine how many tests should be done to determine the severity of the outbreak. According to case study about an outbreak that took place in Alpine, Wyoming, physicians began seeing more patients with bloody diarrhea (Olsen). More cases began showing up not only in Wyoming, but also Utah and Washington (Olsen). During the lab investigation of this outbreak, serum was tested from town residents to check for IgM antibodies to the O157 lipopolysaccharides (Olsen). Prior to the outbreak, the Alpine municipal water system was tested multiple times each month for coliform counts. In this case, they were positive results for <i>E.coli</i> in April, May, and June of that year (Olsen). It was in late June that the outbreak occurred, and by middle of July they had found the source of this occurrence. Once the outbreak was detected, stool samples from infected patients were then sent to a lab for further testing. From the time that the outbreak began to the time that the source was found was about 3-4 weeks (Olsen). During this time, tests were being done by multiple agencies such as the Wyoming State laboratory and the Utah Department of Health State Laboratory (Olsen). Using the biosensor that our team has developed, the severity of the outbreak would be extremely decreased. Although regular water samples are taken, once the water tested positive for pathogens, water contamination warnings should have been implemented in ensure that an outbreak was minimalized. With the biosensor designed by the ASU iGEM team, our biosensor would be pathogen specific to detect whether that pathogen is present or not in water. Our biosensor would be able detect pathogens in water within minutes of running the experiment. This would greatly decrease the amount of people that potentially could get sick. <br />
</p><br />
<br /><br />
<br />
<h2> What are the current practices? </h2><br />
<br />
<p><br />
<i>E.coli</i> outbreaks have been known to occur in different sources, such as food, water, and plants. It has been shown that before an outbreak takes place in water, there are typically signs that <i>E.coli</i> is present (Olsen). This is because before an outbreak can occur the cells must be able to survive in their environment. In recent case studies it has been found that although <i>E.coli</i> was found to be present in the water supply, although the amount of <i>E.coli</i> was insufficient. It was not until after an outbreak occurred and patients began having symptoms did the amount of <i>E.coli</i> becomes a problem. Once the <i>E.coli</i> outbreak has occurred, it will usually take a few weeks to run tests. These experiments can be determining the phenotype of <i>E.coli</i> or just to determine how many people could potentially be affected by the outbreak. It is quite common during <i>E.coli</i> water outbreaks for the cohort case studies to take place. These studies determine the statistical analysis of the outbreak, where the analysts can see how the outbreak progressed with how many people it infected (Olsen). When <i>E.coli</i> is present in other sources such as food and plants, it is usually not known that this is the source until after the outbreak has already occurred. The biosensor developed by the ASU team, eliminated many of these issues. By engineering the biosensor to already be pathogen specific, it decreases the amount of time to determine what the pathogen. The efficiency of our biosensor allows for the efforts the community to then be focused on water purification, instead of waiting for lab results. <br />
</p><br />
<br /><br />
<br />
<h2> How does the biosensor improve sanitation?</h2><br />
<h4> Why is there a need for a real time/faster response for the biosensor needed? </h4><br />
<br />
<p>Improving sanitation and hygiene of water has been one of the primary goals for Arizona State’s iGEM team. As a result of producing a biosensor to detect pathogens, it has the ability to not only prevent outbreaks from occurring but also to minimize them. Our biosensor has the ability to be used to detect different kinds of pathogens. This is very useful because if an outbreak were to occur, the amount of time in spending on determining the phenotype of the pathogen can then be spent on eliminating it from water sources. This is another reason why our biosensor can be so effective by being able to detect specific pathogens, but it is also able to give you the answers in real time. This eliminates even more time in the process of determining the pathogen. By being able to prevent an outbreak from occurring, we would be able to improve the sanitation of water, especially in developing countries. It is in developing nations where the outbreaks are the most prevalent. Our biosensor was designed to be easy to use and efficient. This would allow for it to be portable to test many different kinds of water sources. The more our biosensor is used, the more safety and sanitation would be improved. <br />
</p><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/FieldApplicationsTeam:Arizona State/FieldApplications2012-10-27T01:23:18Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1><i>Escherichia Coli</i> Case Studies</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<h2> Timeline of an outbreak </h2><br />
<br />
<p><br />
In order to implement the biosensor correctly, it is imperative to find data about how <i>E.coli</i> outbreaks progressed. Last year, there was on outbreak of <i>E.coli</i> O104:H4 in Germany. It was first detected in early May of 2011, by causing an increased frequency of hemolytic uremic syndrome (Rohde). As the <i>E.coli</i> outbreak continued to spread, traces of <i>E.coli</i> were present in different foods. According to Dr. Rohde in the Open-Source Genomic Analysis of Shiga-Toxin-Producing <i>E.coli</i> O104:H4 case study, the genomic events began with how the <i>E.coli</i> phenotype was determined (Rohde). It wasn’t until five days after the first detection of the <i>E.coli</i> did lab work begin (Rohde). Although this case study reference is a food <i>E.coli</i> outbreak, it continued to grow in size as more food was found to be contaminated. This scenario is similar to a water based <i>E.coli</i> outbreak because typically in larger outbreaks it will affect more than one geographic area. Using this timeline as an example, between the first detection of the outbreak to the <i>E.coli</i> phenotype being determined, it was a period of three weeks. <br />
<br />
<br />
According to research, detection of the pathogen took a very small amount of time compared to determining the phenotype of the pathogen (Rohde). At this point in time there would have been many sick patients and potentially deaths depending on the severity of the outbreak. With our biosensor, this time could be dramatically reduced. Our biosensor could detect ideally any pathogen of interest. In a hypothetical situation, a potential timeline would be that the water would be tested the day a potential contamination would occur. This contamination could come from heavy rain, flooding, development of a new community, natural disaster, etc. Within minutes of the test being initiated, a pathogen would be able to be detected. This would greatly decrease the amount of locals that could get infected with the pathogen because a contamination warning would be implemented the same day. According to current practices and timelines, a water contamination warning would not be able to go out until two days after the pathogen was detected (Pitkanen). Our biosensor would reduce this time by turning days into minutes. By using the team’s biosensor, we are able to engineer our biosensor to a specific phenotype of pathogen. We would be able to do this onsite or have our biosensor pre-designed before its implemented. This would eliminate expensive lab experiments and time by already having the phenotype of the pathogen determined. <br />
<br />
<br />
</p><br />
<br /><br />
<br />
<h2> Finding the source of an outbreak? </h2><br />
<br />
<p><br />
According to the Center of Disease Control and Prevention, a waterborne outbreak is a cluster of two or more infections caused by the same agent(s) and linked to the same water exposure (Centers for Disease Control and Prevention). Outbreaks can be caused by water contaminated with pathogens, chemicals, or toxins which can be spread through ingestion of, contact with, or breathing contaminated water (Centers for Disease Control and Prevention). Though many of these infections occur in developing countries with lower levels of sanitation and less public health awareness, outbreaks have occurred in developed countries such as the United States and Canada (Shannon).For example, in Denmark there was an outbreak of Campylobacter jejuni that happened between the years 1995-1996 (Engberg). This bacterium is similar to <i>E.coli</i> in that it behaves very similar. Campylobacter jejuni is the most commonly reported bacterial cause of diarrhea in humans in developing countries (Engberg).<br />
<br />
<br />
In December of 1995, a procedure was performed to test the amount of nitrate in the ground water. In the process of testing this, a sewage pipe was damaged and then leaked into the ground water supply. It took over a month for the water pump to be turned off from the initial point of contamination (Engberg). For this particular case, a very high coliform count was found in the infected water. “A coliform count is a water contamination test, counting colonies of coliform-bacteria <i>Escherichia coli</i> (<i>E.coli</i>) per 100 milliliter of water. The counted result is expressed as ‘Coliform Microbial Density’ and indicates the extent of fecal matter present (The Law Dictionary). <br />
<br />
<br />
The Environmental Protection Agency, instituted regulations for beaches and recreational waters to ensure that people who came into contact with bodies of water would not become ill. These regulations stated that for freshwater the present single-sample advisory limits are 235 CFU/100 ml for <i>E.coli</i> (Kinzelman). “According to common water quality standards, recreational (fishing and boating) water can have no more than 1000 colonies. Drinking water must be completely free from any colonies, bathing and swimming pool water can have no more than 200 colonies” (The Law Dictionary). In Canada, before water can be re-used, it must go through treatments to eliminate pathogens or particles. It is under normal operating conditions, the efficiency of pathogen removal is measured in the final effluent. This accounts for the amount of waste water being treated for the removal of pathogens. Under the guidelines issued by Environment Canada, fecal coliforms in final effluents are limited to 400 CFU per 100 ml after disinfection (Shannon). It is at these concentrations which can be harmful to human populations. With the use of our biosensor we would be able to test any water sources to see if pathogens were present. Our biosensor is both portable and efficient, which would allow for finding the source of an outbreak much easier.<br />
<br />
<br />
</p><br />
<br /><br />
<br />
<h2> What if the <i>E.coli</i> strain mutated or the <i>E.coli</i> was undetectable?</h2><br />
<h4>What are the chances of a mutation occurring or what should be done if a mutation occurs? </h4><br />
<br />
<p><br />
Currently there is a controversial hypothesis that although <i>E.coli</i> can be detected it is viable but its non-culturable (Bogosian). This topic pertains to our biosensor because there could be pathogens present in water, but not enough to cause an outbreak. This holds true for any bacteria that cannot be cultured by standard methods. A culturable bacterium is inoculated into a sterile microcosm, most commonly seawater or river water, and incubated for a number of days with regular monitoring (Bogosian). This would affect the timeline of an outbreak as well as infect more people with contaminated water. This poses as an obvious public health issue for developing nations who do not have the equipment or technology for this kind of situation. Thus far it has been shown that although this poses as a health risk, it has only been attributed to 22 deaths and 104 total cases in the United States in the last 70 years (Bogosian). It has been shown that although the <i>E.coli</i> is present, the cells actually die off based on their living conditions. A study was conducted to determine if changes in cell populations were due to cell death or to the cells developing into the non-culturable state (Bogosian). This proved to be very useful because the study tested what kinds of environment the <i>E.coli</i> cells would either decline in their populations or thrive to cause an outbreak. The conclusion is that <i>E.coli</i> cells did not thrive in non-sterile environments (Bogosian). This proves that when an <i>E.coli</i> outbreak occurs it will be because the cells are in an optimum environment where they are able to grow readily. Although <i>E.coli</i> can be present in water does not mean an outbreak will occur. Our biosensor would ideally be able to detect these pathogens no matter how many colonies were present. Although an outbreak may not occur, the water could still be monitored more closely to prevent an outbreak. <br />
</p><br />
<br /><br />
<br />
<h2> How many tests should be done for an outbreak? </h2><br />
<br />
<p><br />
In each of the case studies that were researched, it became apparent that each outbreak has its own characteristics. For example, in 2011, there was an outbreak that took place in Germany where there was a very high incidence in adults, especially women (Rohde). Since each outbreak is unique in its own way, it is difficult to determine how many tests should be done to determine the severity of the outbreak. According to case study about an outbreak that took place in Alpine, Wyoming, physicians began seeing more patients with bloody diarrhea (Olsen). More cases began showing up not only in Wyoming, but also Utah and Washington (Olsen). During the lab investigation of this outbreak, serum was tested from town residents to check for IgM antibodies to the O157 lipopolysaccharides (Olsen). Prior to the outbreak, the Alpine municipal water system was tested multiple times each month for coliform counts. In this case, they were positive results for <i>E.coli</i> in April, May, and June of that year (Olsen). It was in late June that the outbreak occurred, and by middle of July they had found the source of this occurrence. Once the outbreak was detected, stool samples from infected patients were then sent to a lab for further testing. From the time that the outbreak began to the time that the source was found was about 3-4 weeks (Olsen). During this time, tests were being done by multiple agencies such as the Wyoming State laboratory and the Utah Department of Health State Laboratory (Olsen). Using the biosensor that our team has developed, the severity of the outbreak would be extremely decreased. Although regular water samples are taken, once the water tested positive for pathogens, water contamination warnings should have been implemented in ensure that an outbreak was minimalized. With the biosensor designed by the ASU iGEM team, our biosensor would be pathogen specific to detect whether that pathogen is present or not in water. Our biosensor would be able detect pathogens in water within minutes of running the experiment. This would greatly decrease the amount of people that potentially could get sick. <br />
</p><br />
<br /><br />
<br />
<h2> What are the current practices? </h2><br />
<br />
<p><br />
<i>E.coli</i> outbreaks have been known to occur in different sources, such as food, water, and plants. It has been shown that before an outbreak takes place in water, there are typically signs that <i>E.coli</i> is present (Olsen). This is because before an outbreak can occur the cells must be able to survive in their environment. In recent case studies it has been found that although <i>E.coli</i> was found to be present in the water supply, although the amount of <i>E.coli</i> was insufficient. It was not until after an outbreak occurred and patients began having symptoms did the amount of <i>E.coli</i> becomes a problem. Once the <i>E.coli</i> outbreak has occurred, it will usually take a few weeks to run tests. These experiments can be determining the phenotype of <i>E.coli</i> or just to determine how many people could potentially be affected by the outbreak. It is quite common during <i>E.coli</i> water outbreaks for the cohort case studies to take place. These studies determine the statistical analysis of the outbreak, where the analysts can see how the outbreak progressed with how many people it infected (Olsen). When <i>E.coli</i> is present in other sources such as food and plants, it is usually not known that this is the source until after the outbreak has already occurred. The biosensor developed by the ASU team, eliminated many of these issues. By engineering the biosensor to already be pathogen specific, it decreases the amount of time to determine what the pathogen. The efficiency of our biosensor allows for the efforts the community to then be focused on water purification, instead of waiting for lab results. <br />
</p><br />
<br /><br />
<br />
<h2> How does the biosensor improve sanitation?</h2><br />
<h4> Why is there a need for a real time/faster response for the biosensor needed? </h4><br />
<br />
<p>Improving sanitation and hygiene of water has been one of the primary goals for Arizona State’s iGEM team. As a result of producing a biosensor to detect pathogens, it has the ability to not only prevent outbreaks from occurring but also to minimize them. Our biosensor has the ability to be used to detect different kinds of pathogens. This is very useful because if an outbreak were to occur, the amount of time in spending on determining the phenotype of the pathogen can then be spent on eliminating it from water sources. This is another reason why our biosensor can be so effective by being able to detect specific pathogens, but it is also able to give you the answers in real time. This eliminates even more time in the process of determining the pathogen. By being able to prevent an outbreak from occurring, we would be able to improve the sanitation of water, especially in developing countries. It is in developing nations where the outbreaks are the most prevalent. Our biosensor was designed to be easy to use and efficient. This would allow for it to be portable to test many different kinds of water sources. The more our biosensor is used, the more safety and sanitation would be improved. <br />
</p><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/FieldApplicationsTeam:Arizona State/FieldApplications2012-10-27T01:17:26Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1><i>Escherichia Coli</i> Case Studies</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<h2> Timeline of an outbreak </h2><br />
<br />
<p><br />
In order to implement the biosensor correctly, it is imperative to find data about how <i>E.coli</i> outbreaks progressed. Last year, there was on outbreak of E.coli O104:H4 in Germany. It was first detected in early May of 2011, by causing an increased frequency of hemolytic uremic syndrome (Rohde). As the E.coli outbreak continued to spread, traces of E.coli were present in different foods. According to Dr. Rohde in the Open-Source Genomic Analysis of Shiga-Toxin-Producing E.coli O104:H4 case study, the genomic events began with how the E.coli phenotype was determined (Rohde). It wasn’t until five days after the first detection of the E.coli did lab work begin (Rohde). Although this case study reference is a food E.coli outbreak, it continued to grow in size as more food was found to be contaminated. This scenario is similar to a water based E.coli outbreak because typically in larger outbreaks it will affect more than one geographic area. Using this timeline as an example, between the first detection of the outbreak to the E.coli phenotype being determined, it was a period of three weeks. <br />
<br />
<br />
According to research, detection of the pathogen took a very small amount of time compared to determining the phenotype of the pathogen (Rohde). At this point in time there would have been many sick patients and potentially deaths depending on the severity of the outbreak. With our biosensor, this time could be dramatically reduced. Our biosensor could detect ideally any pathogen of interest. In a hypothetical situation, a potential timeline would be that the water would be tested the day a potential contamination would occur. This contamination could come from heavy rain, flooding, development of a new community, natural disaster, etc. Within minutes of the test being initiated, a pathogen would be able to be detected. This would greatly decrease the amount of locals that could get infected with the pathogen because a contamination warning would be implemented the same day. According to current practices and timelines, a water contamination warning would not be able to go out until two days after the pathogen was detected (Pitkanen). Our biosensor would reduce this time by turning days into minutes. By using the team’s biosensor, we are able to engineer our biosensor to a specific phenotype of pathogen. We would be able to do this onsite or have our biosensor pre-designed before its implemented. This would eliminate expensive lab experiments and time by already having the phenotype of the pathogen determined. <br />
<br />
<br />
</p><br />
<br /><br />
<br />
<h2> Finding the source of an outbreak? </h2><br />
<br />
<p><br />
According to the Center of Disease Control and Prevention, a waterborne outbreak is a cluster of two or more infections caused by the same agent(s) and linked to the same water exposure (Centers for Disease Control and Prevention). Outbreaks can be caused by water contaminated with pathogens, chemicals, or toxins which can be spread through ingestion of, contact with, or breathing contaminated water (Centers for Disease Control and Prevention). Though many of these infections occur in developing countries with lower levels of sanitation and less public health awareness, outbreaks have occurred in developed countries such as the United States and Canada (Shannon).For example, in Denmark there was an outbreak of Campylobacter jejuni that happened between the years 1995-1996 (Engberg). This bacterium is similar to E.coli in that it behaves very similar. Campylobacter jejuni is the most commonly reported bacterial cause of diarrhea in humans in developing countries (Engberg).<br />
<br />
<br />
In December of 1995, a procedure was performed to test the amount of nitrate in the ground water. In the process of testing this, a sewage pipe was damaged and then leaked into the ground water supply. It took over a month for the water pump to be turned off from the initial point of contamination (Engberg). For this particular case, a very high coliform count was found in the infected water. “A coliform count is a water contamination test, counting colonies of coliform-bacteria Escherichia coli (E. coli) per 100 milliliter of water. The counted result is expressed as ‘Coliform Microbial Density’ and indicates the extent of fecal matter present (The Law Dictionary). <br />
<br />
<br />
The Environmental Protection Agency, instituted regulations for beaches and recreational waters to ensure that people who came into contact with bodies of water would not become ill. These regulations stated that for freshwater the present single-sample advisory limits are 235 CFU/100 ml for E. coli (Kinzelman). “According to common water quality standards, recreational (fishing and boating) water can have no more than 1000 colonies. Drinking water must be completely free from any colonies, bathing and swimming pool water can have no more than 200 colonies” (The Law Dictionary). In Canada, before water can be re-used, it must go through treatments to eliminate pathogens or particles. It is under normal operating conditions, the efficiency of pathogen removal is measured in the final effluent. This accounts for the amount of wastewater being treated for the removal of pathogens. Under the guidelines issued by Environment Canada, fecal coliforms in final effluents are limited to 400 CFU per 100 mL after disinfection (Shannon). It is at these concentrations which can be harmful to human populations. With the use of our biosensor we would be able to test any water sources to see if pathogens were present. Our biosensor is both portable and efficient, which would allow for finding the source of an outbreak much easier.<br />
<br />
<br />
</p><br />
<br /><br />
<br />
<h2> What if the <i>E.coli</i> strain mutated or the <i>E.coli</i> was undetectable?</h2><br />
<h4>What are the chances of a mutation occurring or what should be done if a mutation occurs? </h4><br />
<br />
<p><br />
Currently there is a controversial hypothesis that although E.coli can be detected it is viable but its non-culturable (Bogosian). This topic pertains to our biosensor because there could be pathogens present in water, but not enough to cause an outbreak. This holds true for any bacteria that cannot be cultured by standard methods. A culturable bacterium is inoculated into a sterile microcosm, most commonly seawater or river water, and incubated for a number of days with regular monitoring (Bogosian). This would affect the timeline of an outbreak as well as infect more people with contaminated water. This poses as an obvious public health issue for developing nations who do not have the equipment or technology for this kind of situation. Thus far it has been shown that although this poses as a health risk, it has only been attributed to 22 deaths and 104 total cases in the United States in the last 70 years (Bogosian). It has been shown that although the E.coli is present, the cells actually die off based on their living conditions. A study was conducted to determine if changes in cell populations were due to cell death or to the cells developing into the non-culturable state (Bogosian). This proved to be very useful because the study tested what kinds of environment the E.coli cells would either decline in their populations or thrive to cause an outbreak. The conclusion the E.coli cells did not thrive in non-sterile environments (Bogosian). This proves that when an E.coli outbreak occurs it will be because the cells are in an optimum environment where they are able to grow readily. Although E.coli can be present in water does not mean an outbreak will occur. Our biosensor would ideally be able to detect these pathogens no matter how many colonies were present. Although an outbreak may not occur, the water could still be monitored more closely to prevent an outbreak. <br />
</p><br />
<br /><br />
<br />
<h2> How many tests should be done for an outbreak? </h2><br />
<br />
<p><br />
In each of the case studies that were researched, it became apparent that each outbreak has its own characteristics. For example, in 2011, there was an outbreak that took place in Germany where there was a very high incidence in adults, especially women (Rohde). Since each outbreak is unique in its own way, it is difficult to determine how many tests should be done to determine the severity of the outbreak. According to case study about an outbreak that took place in Alpine, Wyoming, physicians began seeing more patients with bloody diarrhea (Olsen). More cases began showing up not only in Wyoming, but also Utah and Washington (Olsen). During the lab investigation of this outbreak, serum was tested from town residents to check for IgM antibodies to the O157 lipopolysaccharides (Olsen). Prior to the outbreak, the Alpine municipal water system was tested multiple times each month for coliform counts. In this case, they were positive results for E.coli in April, May, and June of that year (Olsen). It was in late June that the outbreak occurred, and by middle of July they had found the source of this occurrence. Once the outbreak was detected, stool samples from infected patients were then sent to a lab for further testing. From the time that the outbreak began to the time that the source was found was about 3-4 weeks (Olsen). During this time, tests were being done by multiple agencies such as the Wyoming State laboratory and the Utah Department of Health State Laboratory (Olsen). Using the biosensor that our team has developed, the severity of the outbreak would be extremely decreased. Although regular water samples are taken, once the water tested positive for pathogens, water contamination warnings should have been implemented in ensure that an outbreak was minimalized. With the biosensor designed by the ASU iGEM team, our biosensor would be pathogen specific to detect whether that pathogen is present or not in water. Our biosensor would be able detect pathogens in water within minutes of running the experiment. This would greatly decrease the amount of people that potentially could get sick. <br />
</p><br />
<br /><br />
<br />
<h2> What are the current practices? </h2><br />
<br />
<p><br />
E.coli outbreaks have been known to occur in different sources, such as food, water, and plants. It has been shown that before an outbreak takes place in water, there are typically signs that E.coli is present (Olsen). This is because before an outbreak can occur the cells must be able to survive in their environment. In recent case studies it has been found that although E.coli was found to be present in the water supply, although the amount of E.coli was insufficient. It was not until after an outbreak occurred and patients began having symptoms did the amount of E.coli becomes a problem. Once the E.coli outbreak has occurred, it will usually take a few weeks to run tests. These experiments can be determining the phenotype of E.coli or just to determine how many people could potentially be affected by the outbreak. It is quite common during E.coli water outbreaks for the cohort case studies to take place. These studies determine the statistical analysis of the outbreak, where the analysts can see how the outbreak progressed with how many people it infected (Olsen). When E.coli is present in other sources such as food and plants, it is usually not known that this is the source until after the outbreak has already occurred. The biosensor developed by the ASU team, eliminated many of these issues. By engineering the biosensor to already be pathogen specific, it decreases the amount of time to determine what the pathogen. The efficiency of our biosensor allows for the efforts the community to then be focused on water purification, instead of waiting for lab results. <br />
</p><br />
<br /><br />
<br />
<h2> How does the biosensor improve sanitation?</h2><br />
<h4> Why is there a need for a real time/faster response for the biosensor needed? </h4><br />
<br />
<p>Improving sanitation and hygiene of water has been one of the primary goals for Arizona State’s iGEM team. As a result of producing a biosensor to detect pathogens, it has the ability to not only prevent outbreaks from occurring but also to minimize them. Our biosensor has the ability to be used to detect different kinds of pathogens. This is very useful because if an outbreak were to occur, the amount of time in spending on determining the phenotype of the pathogen can then be spent on eliminating it from water sources. This is another reason why our biosensor can be so effective by being able to detect specific pathogens, but it is also able to give you the answers in real time. This eliminates even more time in the process of determining the pathogen. By being able to prevent an outbreak from occurring, we would be able to improve the sanitation of water, especially in developing countries. It is in developing nations where the outbreaks are the most prevalent. Our biosensor was designed to be easy to use and efficient. This would allow for it to be portable to test many different kinds of water sources. The more our biosensor is used, the more safety and sanitation would be improved. <br />
</p><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/FieldApplicationsTeam:Arizona State/FieldApplications2012-10-27T01:14:43Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1><i>Escherichia Coli</i> Case Studies</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<h2> Timeline of an outbreak </h2><br />
<br />
<p><br />
In order to implement the biosensor correctly, it is imperative to find data about how E.coli outbreaks progressed. Last year, there was on outbreak of E.coli O104:H4 in Germany. It was first detected in early May of 2011, by causing an increased frequency of hemolytic uremic syndrome (Rohde). As the E.coli outbreak continued to spread, traces of E.coli were present in different foods. According to Dr. Rohde in the Open-Source Genomic Analysis of Shiga-Toxin-Producing E.coli O104:H4 case study, the genomic events began with how the E.coli phenotype was determined (Rohde). It wasn’t until five days after the first detection of the E.coli did lab work begin (Rohde). Although this case study reference is a food E.coli outbreak, it continued to grow in size as more food was found to be contaminated. This scenario is similar to a water based E.coli outbreak because typically in larger outbreaks it will affect more than one geographic area. Using this timeline as an example, between the first detection of the outbreak to the E.coli phenotype being determined, it was a period of three weeks. <br />
<br />
According to research, detection of the pathogen took a very small amount of time compared to determining the phenotype of the pathogen (Rohde). At this point in time there would have been many sick patients and potentially deaths depending on the severity of the outbreak. With our biosensor, this time could be dramatically reduced. Our biosensor could detect ideally any pathogen of interest. In a hypothetical situation, a potential timeline would be that the water would be tested the day a potential contamination would occur. This contamination could come from heavy rain, flooding, development of a new community, natural disaster, etc. Within minutes of the test being initiated, a pathogen would be able to be detected. This would greatly decrease the amount of locals that could get infected with the pathogen because a contamination warning would be implemented the same day. According to current practices and timelines, a water contamination warning would not be able to go out until two days after the pathogen was detected (Pitkanen). Our biosensor would reduce this time by turning days into minutes. By using the team’s biosensor, we are able to engineer our biosensor to a specific phenotype of pathogen. We would be able to do this onsite or have our biosensor pre-designed before its implemented. This would eliminate expensive lab experiments and time by already having the phenotype of the pathogen determined. <br />
<br />
</p><br />
<br /><br />
<br />
<h2> Finding the source of an outbreak? </h2><br />
<br />
<p><br />
According to the Center of Disease Control and Prevention, a waterborne outbreak is a cluster of two or more infections caused by the same agent(s) and linked to the same water exposure (Centers for Disease Control and Prevention). Outbreaks can be caused by water contaminated with pathogens, chemicals, or toxins which can be spread through ingestion of, contact with, or breathing contaminated water (Centers for Disease Control and Prevention). Though many of these infections occur in developing countries with lower levels of sanitation and less public health awareness, outbreaks have occurred in developed countries such as the United States and Canada (Shannon).For example, in Denmark there was an outbreak of Campylobacter jejuni that happened between the years 1995-1996 (Engberg). This bacterium is similar to E.coli in that it behaves very similar. Campylobacter jejuni is the most commonly reported bacterial cause of diarrhea in humans in developing countries (Engberg).<br />
<br />
In December of 1995, a procedure was performed to test the amount of nitrate in the ground water. In the process of testing this, a sewage pipe was damaged and then leaked into the ground water supply. It took over a month for the water pump to be turned off from the initial point of contamination (Engberg). For this particular case, a very high coliform count was found in the infected water. “A coliform count is a water contamination test, counting colonies of coliform-bacteria Escherichia coli (E. coli) per 100 milliliter of water. The counted result is expressed as ‘Coliform Microbial Density’ and indicates the extent of fecal matter present (The Law Dictionary). <br />
<br />
The Environmental Protection Agency, instituted regulations for beaches and recreational waters to ensure that people who came into contact with bodies of water would not become ill. These regulations stated that for freshwater the present single-sample advisory limits are 235 CFU/100 ml for E. coli (Kinzelman). “According to common water quality standards, recreational (fishing and boating) water can have no more than 1000 colonies. Drinking water must be completely free from any colonies, bathing and swimming pool water can have no more than 200 colonies” (The Law Dictionary). In Canada, before water can be re-used, it must go through treatments to eliminate pathogens or particles. It is under normal operating conditions, the efficiency of pathogen removal is measured in the final effluent. This accounts for the amount of wastewater being treated for the removal of pathogens. Under the guidelines issued by Environment Canada, fecal coliforms in final effluents are limited to 400 CFU per 100 mL after disinfection (Shannon). It is at these concentrations which can be harmful to human populations. With the use of our biosensor we would be able to test any water sources to see if pathogens were present. Our biosensor is both portable and efficient, which would allow for finding the source of an outbreak much easier. <br />
<br />
</p><br />
<br /><br />
<br />
<h2> What if the <i>E.coli</i> strain mutated or the <i>E.coli</i> was undetectable?</h2><br />
<h4>What are the chances of a mutation occurring or what should be done if a mutation occurs? </h4><br />
<br />
<p><br />
Currently there is a controversial hypothesis that although E.coli can be detected it is viable but its non-culturable (Bogosian). This topic pertains to our biosensor because there could be pathogens present in water, but not enough to cause an outbreak. This holds true for any bacteria that cannot be cultured by standard methods. A culturable bacterium is inoculated into a sterile microcosm, most commonly seawater or river water, and incubated for a number of days with regular monitoring (Bogosian). This would affect the timeline of an outbreak as well as infect more people with contaminated water. This poses as an obvious public health issue for developing nations who do not have the equipment or technology for this kind of situation. Thus far it has been shown that although this poses as a health risk, it has only been attributed to 22 deaths and 104 total cases in the United States in the last 70 years (Bogosian). It has been shown that although the E.coli is present, the cells actually die off based on their living conditions. A study was conducted to determine if changes in cell populations were due to cell death or to the cells developing into the non-culturable state (Bogosian). This proved to be very useful because the study tested what kinds of environment the E.coli cells would either decline in their populations or thrive to cause an outbreak. The conclusion the E.coli cells did not thrive in non-sterile environments (Bogosian). This proves that when an E.coli outbreak occurs it will be because the cells are in an optimum environment where they are able to grow readily. Although E.coli can be present in water does not mean an outbreak will occur. Our biosensor would ideally be able to detect these pathogens no matter how many colonies were present. Although an outbreak may not occur, the water could still be monitored more closely to prevent an outbreak. <br />
</p><br />
<br /><br />
<br />
<h2> How many tests should be done for an outbreak? </h2><br />
<br />
<p><br />
In each of the case studies that were researched, it became apparent that each outbreak has its own characteristics. For example, in 2011, there was an outbreak that took place in Germany where there was a very high incidence in adults, especially women (Rohde). Since each outbreak is unique in its own way, it is difficult to determine how many tests should be done to determine the severity of the outbreak. According to case study about an outbreak that took place in Alpine, Wyoming, physicians began seeing more patients with bloody diarrhea (Olsen). More cases began showing up not only in Wyoming, but also Utah and Washington (Olsen). During the lab investigation of this outbreak, serum was tested from town residents to check for IgM antibodies to the O157 lipopolysaccharides (Olsen). Prior to the outbreak, the Alpine municipal water system was tested multiple times each month for coliform counts. In this case, they were positive results for E.coli in April, May, and June of that year (Olsen). It was in late June that the outbreak occurred, and by middle of July they had found the source of this occurrence. Once the outbreak was detected, stool samples from infected patients were then sent to a lab for further testing. From the time that the outbreak began to the time that the source was found was about 3-4 weeks (Olsen). During this time, tests were being done by multiple agencies such as the Wyoming State laboratory and the Utah Department of Health State Laboratory (Olsen). Using the biosensor that our team has developed, the severity of the outbreak would be extremely decreased. Although regular water samples are taken, once the water tested positive for pathogens, water contamination warnings should have been implemented in ensure that an outbreak was minimalized. With the biosensor designed by the ASU iGEM team, our biosensor would be pathogen specific to detect whether that pathogen is present or not in water. Our biosensor would be able detect pathogens in water within minutes of running the experiment. This would greatly decrease the amount of people that potentially could get sick. <br />
</p><br />
<br /><br />
<br />
<h2> What are the current practices? </h2><br />
<br />
<p><br />
E.coli outbreaks have been known to occur in different sources, such as food, water, and plants. It has been shown that before an outbreak takes place in water, there are typically signs that E.coli is present (Olsen). This is because before an outbreak can occur the cells must be able to survive in their environment. In recent case studies it has been found that although E.coli was found to be present in the water supply, although the amount of E.coli was insufficient. It was not until after an outbreak occurred and patients began having symptoms did the amount of E.coli becomes a problem. Once the E.coli outbreak has occurred, it will usually take a few weeks to run tests. These experiments can be determining the phenotype of E.coli or just to determine how many people could potentially be affected by the outbreak. It is quite common during E.coli water outbreaks for the cohort case studies to take place. These studies determine the statistical analysis of the outbreak, where the analysts can see how the outbreak progressed with how many people it infected (Olsen). When E.coli is present in other sources such as food and plants, it is usually not known that this is the source until after the outbreak has already occurred. The biosensor developed by the ASU team, eliminated many of these issues. By engineering the biosensor to already be pathogen specific, it decreases the amount of time to determine what the pathogen. The efficiency of our biosensor allows for the efforts the community to then be focused on water purification, instead of waiting for lab results. <br />
</p><br />
<br /><br />
<br />
<h2> How does the biosensor improve sanitation?</h2><br />
<h4> Why is there a need for a real time/faster response for the biosensor needed? </h4><br />
<br />
<p>Improving sanitation and hygiene of water has been one of the primary goals for Arizona State’s iGEM team. As a result of producing a biosensor to detect pathogens, it has the ability to not only prevent outbreaks from occurring but also to minimize them. Our biosensor has the ability to be used to detect different kinds of pathogens. This is very useful because if an outbreak were to occur, the amount of time in spending on determining the phenotype of the pathogen can then be spent on eliminating it from water sources. This is another reason why our biosensor can be so effective by being able to detect specific pathogens, but it is also able to give you the answers in real time. This eliminates even more time in the process of determining the pathogen. By being able to prevent an outbreak from occurring, we would be able to improve the sanitation of water, especially in developing countries. It is in developing nations where the outbreaks are the most prevalent. Our biosensor was designed to be easy to use and efficient. This would allow for it to be portable to test many different kinds of water sources. The more our biosensor is used, the more safety and sanitation would be improved. <br />
</p><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ReferencesTeam:Arizona State/References2012-10-26T22:51:51Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1>References</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<h2>Streptavidin</h2><br />
<br />
<p><br />
<ul><br />
<li><br />
Laitinen, O. H., V. P. Hytönen, H. R. Nordlund, and M. S. Kulomaa. "Genetically Engineered Avidins and Streptavidins." Cellular and Molecular Life Sciences 63.24 (2006): 2992-3017. Print.<br />
</li><br />
<li><br />
Szafranski, Przemyslaw, Charlene M. Mello, Takeshi Sano, Cassandra L. Smith, David L. Kaplan, and Charles R. Cantor. "A New Approach for Containment of Microorganisms: Dual Control of Streptavidin Expression by Antisense RNA and the T7 Transcription System." Applied Biological Sciences 94 (1997): 1059-063. Print.<br />
</li><br />
</ul><br />
</p><br />
<br />
<h2>Topoisomerase</h2><br />
<br />
<p><br />
<ul><br />
<li><br />
Hwang, Y., N. Minkah, K. Perry, G. D. Van Duyne, and F. D. Bushman. "Regulation of Catalysis by the Smallpox Virus Topoisomerase." Journal of Biological Chemistry 281.49 (2006): 38052-8060. Print. <br />
</li><br />
<li><br />
Sekiguchi, JoAnn, and Stewart Shuman. "Requirements for Noncovalent Binding of Vaccinia Topoisomerase I to Duplex DNA." Nucleic Acids Research 22.24 (1994): 5360-365. Print.<br />
</li><br />
<li><br />
Shuman, S. "Recombination Mediated by Vaccinia Virus DNA Topoisomerase I in Escherichia Coli Is Sequence Specific." Proceedings of the National Academy of Sciences 88.22 (1991): 10104-0108. Print. <br />
</li><br />
<li><br />
Shuman, Steward. "Site-specific Interaction of Vaccinia Virus Topoisomerase WI Ith Duplex DNA." The Journal of Biological Chemistry 266.17 (1991): 11372-1379. Print. <br />
</li><br />
</ul><br />
</p><br />
<br />
<h2>Human Practices</h2><br />
<br />
<p><br />
<ul><br />
<li><br />
Arora, Kavita, Subhash Chand, and B. D. Malhotra. "Recent Developments in Bio-molecular Techniques for Food Pathogens." Analytica Chimica Acta (2006): 259-74. Web. <br />
</li><br />
<li><br />
Bai, Sulan, Jinyi Zhao, Yaochuan Zhang, Wensheng Huang, Shi Xu, Haodong Chen, Liu-Min Fan, Ying Chen, and Xing Wang Deng. "Rapid and Reliable Detection of 11 Food-borne Pathogens Using Thin-film Biosensor Chips." Applied Microbiology and Biotechnology 86.3 (2010): 983-90. Print. <br />
</li><br />
<li><br />
Beatty, Mark. "Clinical Infectious Diseases." Epidemic Diarrhea Due to Enterotoxigenic Escherichia Coli. N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://cid.oxfordjournals.org/content/42/3/329.full">http://cid.oxfordjournals.org/content/42/3/329.full</a><br />
&gt;.<br />
</li><br />
<li><br />
Bogosian, Gregg. "American Society for MicrobiologyApplied and Environmental Microbiology." Death of the Escherichia Coli K-12 Strain W3110 in Soil and Water. N.p., 11 June 1996. Web. 03 Oct. 2012. &lt;<br />
<a href="http://aem.asm.org/content/62/11/4114.full.pdf html">http://aem.asm.org/content/62/11/4114.full.pdf</a><br />
&gt; html.<br />
</li><br />
<li><br />
Cairncross, Sandy, Caroline Hunt, Sophie Boisson, Kristof Bostoen, Val Curtis, Isaac CH Fung, and Wolf-Peter Smidth. "Water, Sanitation, and Hygiene of Diarrhoea." International Journal of Epidemiology 39 (2010): 193-205. Print. <br />
</li><br />
<li><br />
Carothers, Thomas. "Revitalizing Democracy Assistance: The Challenge of USAID -Carnegie Endowment for International Peace." Carnegie Endowment for International Peace. N.p., n.d. Web. 24 Oct. 2012. <http://www.carnegieendowment.org/2009/10/27/revitalizing-democracy-assistance-challenge-of-usaid/3hc>.<br />
</li><br />
<li><br />
"Coliform Count." Business Dictionary. N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://www.businessdictionary.com/definition/coliform-count.html">http://www.businessdictionary.com/definition/coliform-count.html</a><br />
&gt;.<br />
</li><br />
<li><br />
De Boer, Enne, and Rijkelt R. Beumer. "Methodology for Detection and Typing of Foodborne Microorganisms." International Journal of Food Microbiology (1999): 119-30. Web. <br />
</li><br />
<li><br />
Engberg, Jørgen. "Water-borne Campylobacter Jejuni Infection in a Danish Town-a 6-week Continuous Source Outbreak." Wiley-Online Library. N.p., 27 Oct. 2008. Web. 03 Oct. 2012. &lt;<br />
<a href="http://onlinelibrary.wiley.com/doi/10.1111/j.1469-0691.1998.tb00348.x/full">http://onlinelibrary.wiley.com/doi/10.1111/j.1469-0691.1998.tb00348.x/full</a><br />
&gt;.<br />
</li><br />
<li><br />
England, Roger. “The Fight Against AIDS in the Larger Context: the end of ‘AIDS exceptionalism’.” UNU-Cornell Africa Series Symposium: The social and economic dimensions of HIV/AIDS in Africa. New York, September 9, 2008. <br />
</li><br />
<li><br />
Hunter, Paul, Paul Jagals, and Katherine Pond. Valuing Water, Valuing Livelihoods. Ed. John Cameron. London: IWA, 2011. Web.<br />
</li><br />
<li><br />
Johansson, Emily W., and Tessa Wardlaw. Diarrhoea: Why Children Are Still Dying and What Can Be Done. Publication. World Health Organization, 2009. Web. <br />
</li><br />
<li><br />
McMeekin, T.a., C. Hill, M. Wagner, A. Dahl, and T. Ross. "Ecophysiology of Food-borne Pathogens: Essential Knowledge to Improve Food Safety." International Journal of Food Microbiology 139 (2010): S64-78. Print. <br />
</li><br />
<li><br />
Mellmann, Alexander. "Prospective Genomic Characterization of the German Enterohemorrhagic Escherichia Coli O104:H4 Outbreak by Rapid Next Generation Sequencing Technology." PLOS ONE:. N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0022751?imageURI=info:doi/10.1371/journal.pone.0022751.g001">http://www.plosone.org/article/info:doi/10.1371/journal.pone.0022751?imageURI=info:doi/10.1371/journal.pone.0022751.g001</a><br />
&gt;.<br />
</li><br />
<li><br />
Newkirk, Brian J. "Turning Quicksand into Bedrock: Understanding the Dynamic Effects of Disease-focused Global Health Aid on Health Systems." Harvard-MIT Division of Health Sciences and Technology (2009): 1-90. Web.<br />
</li><br />
<li><br />
Olsen, Sonja J., Gayle Miller, Thomas Breuer, Malinda Kennedy, Charles Higgins, Jim Walford, Gary McKee, Kim Fox, William Bibb, and Paul Mead. "Abstract." National Center for Biotechnology Information. U.S. National Library of Medicine, 21 Sept. 0005. Web. 03 Oct. 2012. &lt;<br />
<a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2730238/">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2730238/</a><br />
&gt;.<br />
</li><br />
<li><br />
Palchetti, Ilaria, and Marco Mascini. "Electroanalytical Biosensors and Their Potential for Food Pathogen and Toxin Detection." Review. 8 Jan. 2008. Print. <br />
</li><br />
<li><br />
Rohde, Holger, MD. "The New England Journal of Medicine." Open-Source Genomic Analysis of Shiga-Toxinâ Producing E. Coli O104:H4 âNEJM. N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://www.nejm.org/doi/full/10.1056/nejmoa1107643">http://www.nejm.org/doi/full/10.1056/nejmoa1107643</a><br />
&gt;.<br />
</li><br />
<li><br />
Swerdlow DL. "Waterborne Outbreak in Missouri of Escherichia Coli O157:H7 Associated with Bloody Diarrhea and Death." A Waterborne Outbreak in Missouri of Escherichia Coli O157:H7 Associated with Bloody Diarrhea... N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://ukpmc.ac.uk/abstract/MED/1416555/reload=0;jsessionid=485eElQK2FrO5B4oKFQ1.0">http://ukpmc.ac.uk/abstract/MED/1416555/reload=0;jsessionid=485eElQK2FrO5B4oKFQ1.0</a><br />
&gt;.<br />
</li><br />
<li><br />
"THE DUAL-USE DILEMMA." Parliamentary Office of Science and Technology 340 (2009): n. pag. Print.<br />
</li><br />
<li><br />
"Water-related Diseases." World Health Organization. Web. 02 Oct. 2012. &lt;<br />
<a href="http://www.who.int/water_sanitation_health/diseases/diarrhoea/en/">http://www.who.int/water_sanitation_health/diseases/diarrhoea/en/</a><br />
&gt;. <br />
</li><br />
<li><br />
World Health Organization and UNICEF. Progress of Sanitation and Drinking Water. World Health Organization and UNICEF, 2010. Print. <br />
</li><br />
<li><br />
World Health Organization. Emerging Issues in Water and Infectious Disease. World Health Organization, 2003. Print. <br />
</li><br />
<li><br />
World Health Organization. Guidelines for the Control of Shigellosis, including Epidemics Due to Shigallea Dysenteriae. Geneva: World Health Organization, 2005. Print. <br />
</li><br />
<li><br />
World Health Organization. Water Safety Plan Manual. Geneva: World Health Organization, 2009. Print.<br />
</li><br />
</ul><br />
</p><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ReferencesTeam:Arizona State/References2012-10-26T22:48:33Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1>References</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<h2>Streptavidin</h2><br />
<br />
<p><br />
<ul><br />
<li><br />
Laitinen, O. H., V. P. Hytönen, H. R. Nordlund, and M. S. Kulomaa. "Genetically Engineered Avidins and Streptavidins." Cellular and Molecular Life Sciences 63.24 (2006): 2992-3017. Print.<br />
</li><br />
<li><br />
Szafranski, Przemyslaw, Charlene M. Mello, Takeshi Sano, Cassandra L. Smith, David L. Kaplan, and Charles R. Cantor. "A New Approach for Containment of Microorganisms: Dual Control of Streptavidin Expression by Antisense RNA and the T7 Transcription System." Applied Biological Sciences 94 (1997): 1059-063. Print.<br />
</li><br />
</ul><br />
</p><br />
<br />
<h2>Topoisomerase</h2><br />
<br />
<p><br />
<ul><br />
<li><br />
Hwang, Y., N. Minkah, K. Perry, G. D. Van Duyne, and F. D. Bushman. "Regulation of Catalysis by the Smallpox Virus Topoisomerase." Journal of Biological Chemistry 281.49 (2006): 38052-8060. Print. <br />
</li><br />
<li><br />
Sekiguchi, JoAnn, and Stewart Shuman. "Requirements for Noncovalent Binding of Vaccinia Topoisomerase I to Duplex DNA." Nucleic Acids Research 22.24 (1994): 5360-365. Print.<br />
</li><br />
<li><br />
Shuman, S. "Recombination Mediated by Vaccinia Virus DNA Topoisomerase I in Escherichia Coli Is Sequence Specific." Proceedings of the National Academy of Sciences 88.22 (1991): 10104-0108. Print. <br />
</li><br />
<li><br />
Shuman, Steward. "Site-specific Interaction of Vaccinia Virus Topoisomerase WI Ith Duplex DNA." The Journal of Biological Chemistry 266.17 (1991): 11372-1379. Print. <br />
</li><br />
</ul><br />
</p><br />
<br />
<h2>Human Practices</h2><br />
<br />
<p><br />
<ul><br />
<li><br />
Arora, Kavita, Subhash Chand, and B. D. Malhotra. "Recent Developments in Bio-molecular Techniques for Food Pathogens." Analytica Chimica Acta (2006): 259-74. Web. <br />
</li><br />
<li><br />
Bai, Sulan, Jinyi Zhao, Yaochuan Zhang, Wensheng Huang, Shi Xu, Haodong Chen, Liu-Min Fan, Ying Chen, and Xing Wang Deng. "Rapid and Reliable Detection of 11 Food-borne Pathogens Using Thin-film Biosensor Chips." Applied Microbiology and Biotechnology 86.3 (2010): 983-90. Print. <br />
</li><br />
<li><br />
Beatty, Mark. "Clinical Infectious Diseases." Epidemic Diarrhea Due to Enterotoxigenic Escherichia Coli. N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://cid.oxfordjournals.org/content/42/3/329.full">http://cid.oxfordjournals.org/content/42/3/329.full</a><br />
&gt;.<br />
</li><br />
<li><br />
Bogosian, Gregg. "American Society for MicrobiologyApplied and Environmental Microbiology." Death of the Escherichia Coli K-12 Strain W3110 in Soil and Water. N.p., 11 June 1996. Web. 03 Oct. 2012. &lt;<br />
<a href="http://aem.asm.org/content/62/11/4114.full.pdf html">http://aem.asm.org/content/62/11/4114.full.pdf</a><br />
&gt; html.<br />
</li><br />
<li><br />
Cairncross, Sandy, Caroline Hunt, Sophie Boisson, Kristof Bostoen, Val Curtis, Isaac CH Fung, and Wolf-Peter Smidth. "Water, Sanitation, and Hygiene of Diarrhoea." International Journal of Epidemiology 39 (2010): 193-205. Print. <br />
</li><br />
<li><br />
Carothers, Thomas. "Revitalizing Democracy Assistance: The Challenge of USAID -Carnegie Endowment for International Peace." Carnegie Endowment for International Peace. N.p., n.d. Web. 24 Oct. 2012. <http://www.carnegieendowment.org/2009/10/27/revitalizing-democracy-assistance-challenge-of-usaid/3hc>.<br />
</li><br />
<li><br />
"Coliform Count." Business Dictionary. N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://www.businessdictionary.com/definition/coliform-count.html">http://www.businessdictionary.com/definition/coliform-count.html</a><br />
&gt;.<br />
</li><br />
<li><br />
De Boer, Enne, and Rijkelt R. Beumer. "Methodology for Detection and Typing of Foodborne Microorganisms." International Journal of Food Microbiology (1999): 119-30. Web. <br />
</li><br />
<li><br />
Engberg, Jørgen. "Water-borne Campylobacter Jejuni Infection in a Danish Town-a 6-week Continuous Source Outbreak." Wiley-Online Library. N.p., 27 Oct. 2008. Web. 03 Oct. 2012. &lt;<br />
<a href="http://onlinelibrary.wiley.com/doi/10.1111/j.1469-0691.1998.tb00348.x/full">http://onlinelibrary.wiley.com/doi/10.1111/j.1469-0691.1998.tb00348.x/full</a><br />
&gt;.<br />
</li><br />
<li><br />
Hunter, Paul, Paul Jagals, and Katherine Pond. Valuing Water, Valuing Livelihoods. Ed. John Cameron. London: IWA, 2011. Web.<br />
</li><br />
<li><br />
Johansson, Emily W., and Tessa Wardlaw. Diarrhoea: Why Children Are Still Dying and What Can Be Done. Publication. World Health Organization, 2009. Web. <br />
</li><br />
<li><br />
McMeekin, T.a., C. Hill, M. Wagner, A. Dahl, and T. Ross. "Ecophysiology of Food-borne Pathogens: Essential Knowledge to Improve Food Safety." International Journal of Food Microbiology 139 (2010): S64-78. Print. <br />
</li><br />
<li><br />
Mellmann, Alexander. "Prospective Genomic Characterization of the German Enterohemorrhagic Escherichia Coli O104:H4 Outbreak by Rapid Next Generation Sequencing Technology." PLOS ONE:. N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0022751?imageURI=info:doi/10.1371/journal.pone.0022751.g001">http://www.plosone.org/article/info:doi/10.1371/journal.pone.0022751?imageURI=info:doi/10.1371/journal.pone.0022751.g001</a><br />
&gt;.<br />
</li><br />
<li><br />
Olsen, Sonja J., Gayle Miller, Thomas Breuer, Malinda Kennedy, Charles Higgins, Jim Walford, Gary McKee, Kim Fox, William Bibb, and Paul Mead. "Abstract." National Center for Biotechnology Information. U.S. National Library of Medicine, 21 Sept. 0005. Web. 03 Oct. 2012. &lt;<br />
<a href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2730238/">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2730238/</a><br />
&gt;.<br />
</li><br />
<li><br />
Palchetti, Ilaria, and Marco Mascini. "Electroanalytical Biosensors and Their Potential for Food Pathogen and Toxin Detection." Review. 8 Jan. 2008. Print. <br />
</li><br />
<li><br />
Rohde, Holger, MD. "The New England Journal of Medicine." Open-Source Genomic Analysis of Shiga-Toxinâ Producing E. Coli O104:H4 âNEJM. N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://www.nejm.org/doi/full/10.1056/nejmoa1107643">http://www.nejm.org/doi/full/10.1056/nejmoa1107643</a><br />
&gt;.<br />
</li><br />
<li><br />
Swerdlow DL. "Waterborne Outbreak in Missouri of Escherichia Coli O157:H7 Associated with Bloody Diarrhea and Death." A Waterborne Outbreak in Missouri of Escherichia Coli O157:H7 Associated with Bloody Diarrhea... N.p., n.d. Web. 03 Oct. 2012. &lt;<br />
<a href="http://ukpmc.ac.uk/abstract/MED/1416555/reload=0;jsessionid=485eElQK2FrO5B4oKFQ1.0">http://ukpmc.ac.uk/abstract/MED/1416555/reload=0;jsessionid=485eElQK2FrO5B4oKFQ1.0</a><br />
&gt;.<br />
</li><br />
<li><br />
"Water-related Diseases." World Health Organization. Web. 02 Oct. 2012. &lt;<br />
<a href="http://www.who.int/water_sanitation_health/diseases/diarrhoea/en/">http://www.who.int/water_sanitation_health/diseases/diarrhoea/en/</a><br />
&gt;. <br />
</li><br />
<li><br />
World Health Organization and UNICEF. Progress of Sanitation and Drinking Water. World Health Organization and UNICEF, 2010. Print. <br />
</li><br />
<li><br />
World Health Organization. Emerging Issues in Water and Infectious Disease. World Health Organization, 2003. Print. <br />
</li><br />
<li><br />
World Health Organization. Guidelines for the Control of Shigellosis, including Epidemics Due to Shigallea Dysenteriae. Geneva: World Health Organization, 2005. Print. <br />
</li><br />
<li><br />
World Health Organization. Water Safety Plan Manual. Geneva: World Health Organization, 2009. Print.<br />
</li><br />
</ul><br />
</p><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/Ethical_ConditionsTeam:Arizona State/Ethical Conditions2012-10-26T22:44:03Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<h1>Knowledge Sharing</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
This biosensor has the ability to change the lives of people in developing nations. The biosensor allows communities to detect the quality of the water supply. Knowing when the water is contaminated can stop people from consuming dirty water. The ethical dilemma arises when, after testing the water and determining that the supply is contaminated, the community cannot treat the water. Is it ethical to present information to a population that does not have the resources available to address the problem? <br />
<br />
<br />
Sharing information about a contaminated water supply in a community can create problems. Addressing one side of the ethical dilemma, providing a community with the awareness of contaminated water and thus possible illness may be knowledge that the community does not want. Without the tools necessary to clean the water, notifying communities of a contaminated water source may seem futile. The awareness may be perceived by the community as a means of oppression: an external influence comes in to a village, diagnoses a problem, and then departs leaving the community members to address a problem that is not within their means to address. Water is an intrinsic need; humans depend on it. Coming into a community and then determining that water is contaminated can be perceived as a disruptive force. The community is told that the water is not good to consume, but with the inability to treat the water individuals are left using contaminated water. Problems may arise when sharing information with a community that is unable to solve the problem as the knowledge may be futile and can also act as a disruptive force. <br />
<br />
<br />
Providing knowledge, however, can benefit a community in numerous ways. First and foremost, the knowledge of contaminated water provides a community with the power of making a decision. The community must become involved in the decision-making process, deciding which actions to take and how to expend accessible resources. Knowledge of contamination allows community members to take immediate steps. Such steps can be rudimentary measures, such as boiling or chlorination treatments. In each situation, using their own culture and morality, a community can decide what to do. Knowledge of contamination provides a community with the power of choice. The biosensor is preventative; it provides knowledge. This awareness allows action, and decision making, which is empowering. The argument that a community should remain in the darkness if action cannot be taken is an argument for passivity. <br />
<br />
<br />
The ASU iGEM team has decided that the decision to share knowledge of a contaminated water source with a community that may not have the necessary resources is ethical. Awareness of the issue leads to action and decision-making, which leads to empowerment. The ASU iGEM team wants to empower communities in developing countries.<br />
<br />
<br />
<h1>Policy Implications</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
One of the main focuses of the ASU iGEM team is being able to design effective methods for how our biosensor could be implemented. When designing our biosensor, it was important that other countries would be able to use our device with ease. If our project was able to be used in developing countries how would this affect their healthcare? What kinds of implications would our biosensor have on the communities where our biosensor was used? These are important policy and ethical implications that need to be discussed in order for our biosensor to be used effectively. <br />
<br />
<br />
About $14 billion dollars a year are spent by Western countries that provide healthcare interventions to prevent and cure illness in developing countries (England 2008). The way that these governments distribute this money is via two different methods. The first method is called “horizontal aid” which seeks to distribute money to improve the overall healthcare system within a country (Newkirk 2008). The second method is “vertical aid” which also seeks to target specific diseases of interest (Newkirk 2008).The “horizontal aid” option incorporates the entire infrastructure of the country which should be improved. The drawback to implementing the ASU biosensor in tandem is that the entire implementation process could take much longer. When integrating this new technology, like a biosensor, with an already established healthcare system, developing countries will require that it meets the needs of their people. In some cases this requires expanding the country’s healthcare system to incorporate the new technology.<br />
<br />
<br />
The technology being under control of the government runs the risk of the “dual-use dilemma”. This is where the government can abuse or misuse their control of the technology (POST 2009). An example of this would be if the government prevented which areas of the country would have access to the technology or to charge an exorbitant fee to use the technology. This would be a means to expand their control. Ultimately all of these issues kill the effectiveness of the technology as it prevents long-term deployment of the technology, meaning that any benefits from actually creating it may be short-lived. <br />
<br />
<br />
In order for the ASU biosensor to be implemented correctly, our team would rely on non-governmental organizations (NGO). These kinds of organizations are put into place to work independently of the government. This would be a solution to eliminate corrupt government involvement. First, the biosensor can be vertically distributed by NGOs as this represents the most effective strategy to getting it to countries and regions throughout the world. Second, the aid approach must prioritize the needs of the recipients over the needs of the donor organizations. By giving priority to those who are in need, it would encourage local ownership of the device whereby the political and local attitudes will be for the technology versus against it (Newkirk 2008). This can be effective in overcoming generic narratives that state the technology is more of an imposition than an actual need. This would also allow for the technology to be deployed more effectively as it responds to the needs of the recipients and quickly adapts to them (Newkirk 2008). <br />
<br />
<br />
Long term, the goal is to have the ASU biosensor become an effective tool for the developing country to use regularly. This would require government officials to create a sustainable, long-term infrastructure that would allow for an adequate prevention and care system. This approach would be most effective in both the long and short term because the NGOs can set up infrastructure in the intermediary to effectively combat the outbreak, while the government creates their regulations to implement our biosensor. The policy effort behind implementation has to include engagement with the local government whereby political goodwill will be generated for the technology versus against it. This is essential to not only preventing political backlash but also resolving any possible concerns regarding the “dual-use dilemma.”</div>Aispashttp://2012.igem.org/Team:Arizona_State/Ethical_ConditionsTeam:Arizona State/Ethical Conditions2012-10-26T22:43:09Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<h1>Knowledge Sharing</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
This biosensor has the ability to change the lives of people in developing nations. The biosensor allows communities to detect the quality of the water supply. Knowing when the water is contaminated can stop people from consuming dirty water. The ethical dilemma arises when, after testing the water and determining that the supply is contaminated, the community cannot treat the water. Is it ethical to present information to a population that does not have the resources available to address the problem? <br />
<br />
<br />
Sharing information about a contaminated water supply in a community can create problems. Addressing one side of the ethical dilemma, providing a community with the awareness of contaminated water and thus possible illness may be knowledge that the community does not want. Without the tools necessary to clean the water, notifying communities of a contaminated water source may seem futile. The awareness may be perceived by the community as a means of oppression: an external influence comes in to a village, diagnoses a problem, and then departs leaving the community members to address a problem that is not within their means to address. Water is an intrinsic need; humans depend on it. Coming into a community and then determining that water is contaminated can be perceived as a disruptive force. The community is told that the water is not good to consume, but with the inability to treat the water individuals are left using contaminated water. Problems may arise when sharing information with a community that is unable to solve the problem as the knowledge may be futile and can also act as a disruptive force. <br />
<br />
<br />
Providing knowledge, however, can benefit a community in numerous ways. First and foremost, the knowledge of contaminated water provides a community with the power of making a decision. The community must become involved in the decision-making process, deciding which actions to take and how to expend accessible resources. Knowledge of contamination allows community members to take immediate steps. Such steps can be rudimentary measures, such as boiling or chlorination treatments. In each situation, using their own culture and morality, a community can decide what to do. Knowledge of contamination provides a community with the power of choice. The biosensor is preventative; it provides knowledge. This awareness allows action, and decision making, which is empowering. The argument that a community should remain in the darkness if action cannot be taken is an argument for passivity. <br />
<br />
<br />
The ASU iGEM team has decided that the decision to share knowledge of a contaminated water source with a community that may not have the necessary resources is ethical. Awareness of the issue leads to action and decision-making, which leads to empowerment. The ASU iGEM team wants to empower communities in developing countries.<br />
<br />
<h1>Policy Implications</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
One of the main focuses of the ASU iGEM team is being able to design effective methods for how our biosensor could be implemented. When designing our biosensor, it was important that other countries would be able to use our device with ease. If our project was able to be used in developing countries how would this affect their healthcare? What kinds of implications would our biosensor have on the communities where our biosensor was used? These are important policy and ethical implications that need to be discussed in order for our biosensor to be used effectively. <br />
<br />
About $14 billion dollars a year are spent by Western countries that provide healthcare interventions to prevent and cure illness in developing countries (England 2008). The way that these governments distribute this money is via two different methods. The first method is called “horizontal aid” which seeks to distribute money to improve the overall healthcare system within a country (Newkirk 2008). The second method is “vertical aid” which also seeks to target specific diseases of interest (Newkirk 2008).The “horizontal aid” option incorporates the entire infrastructure of the country which should be improved. The drawback to implementing the ASU biosensor in tandem is that the entire implementation process could take much longer. When integrating this new technology, like a biosensor, with an already established healthcare system, developing countries will require that it meets the needs of their people. In some cases this requires expanding the country’s healthcare system to incorporate the new technology.<br />
<br />
The technology being under control of the government runs the risk of the “dual-use dilemma”. This is where the government can abuse or misuse their control of the technology (POST 2009). An example of this would be if the government prevented which areas of the country would have access to the technology or to charge an exorbitant fee to use the technology. This would be a means to expand their control. Ultimately all of these issues kill the effectiveness of the technology as it prevents long-term deployment of the technology, meaning that any benefits from actually creating it may be short-lived. <br />
<br />
In order for the ASU biosensor to be implemented correctly, our team would rely on non-governmental organizations (NGO). These kinds of organizations are put into place to work independently of the government. This would be a solution to eliminate corrupt government involvement. First, the biosensor can be vertically distributed by NGOs as this represents the most effective strategy to getting it to countries and regions throughout the world. Second, the aid approach must prioritize the needs of the recipients over the needs of the donor organizations. By giving priority to those who are in need, it would encourage local ownership of the device whereby the political and local attitudes will be for the technology versus against it (Newkirk 2008). This can be effective in overcoming generic narratives that state the technology is more of an imposition than an actual need. This would also allow for the technology to be deployed more effectively as it responds to the needs of the recipients and quickly adapts to them (Newkirk 2008). <br />
<br />
Long term, the goal is to have the ASU biosensor become an effective tool for the developing country to use regularly. This would require government officials to create a sustainable, long-term infrastructure that would allow for an adequate prevention and care system. This approach would be most effective in both the long and short term because the NGOs can set up infrastructure in the intermediary to effectively combat the outbreak, while the government creates their regulations to implement our biosensor. The policy effort behind implementation has to include engagement with the local government whereby political goodwill will be generated for the technology versus against it. This is essential to not only preventing political backlash but also resolving any possible concerns regarding the “dual-use dilemma.”</div>Aispashttp://2012.igem.org/Team:Arizona_State/FieldApplicationsTeam:Arizona State/FieldApplications2012-10-21T16:20:06Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1><i>Escherichia Coli</i> Case Studies</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<h2> Timeline of an outbreak: </h2><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
In order to implement the biosensor correctly, it is imperative to find data about how <i>E.coli</i> outbreaks progressed. Last year for example, there was on outbreak of <i>E.coli</i> O104:H4 in Germany. It was first detected in early May of 2011, by causing an increased frequency of hemolytic uremic syndrome (Rohde). As the <i>E.coli</i> outbreak continued to spread, traces of <i>E.coli</i> were present in different foods. According to Dr. Rohde in the Open-Source Genomic Analysis of Shiga-Toxin-Producing <i>E.coli</i> O104:H4 case study, the genomic events began with how the <i>E.coli</i> phenotype being determined (Rohde). It wasn’t until five days after the first detection of the <i>E.coli</i> did lab work begin (Rohde). Although this case study reference is a food <i>E.coli</i> outbreak, it continued to grow in size as more food was found to be contaminated. This scenario is similar to a water based <i>E.coli</i> outbreak because typically in larger outbreaks it will affect more than one geographic area. Using this timeline as an example, between the first detection of the outbreak to the <i>E.coli</i> phenotype being determined, it was a period of three weeks. According to research, detection of the pathogen took a very small amount of time compared to determining the phenotype of the pathogen (Rohde). At this point in time there would have been many sick patients and even potentially deaths depending on the severity of the outbreak. With our biosensor, this time could be dramatically reduced. Our biosensor could detect ideally any pathogen of interest.<br />
</p><br />
<br /><br />
<br />
<h2> Finding the source of an outbreak? </h2><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
As defined an outbreak is an occurrence of disease greater than would otherwise be expected at a particular time and place (Business Dictionary). For an <i>E.coli</i> outbreak it is most common to see outbreaks take place when fecal matter is mixed in with the primary supply of water or in food. This is more common in developing countries that in more established countries such as most of Europe and the United States, although occurrences still take place in these areas. For example in Denmark, there was an outbreak of <i>Campylobacter jejuni</i> that happened between 1995-1996 (Engberg). This bacteria is similar to <i>E.coli</i> in that it behaves very similar. <i>Campylobacter jejuni</i> is the most commonly reported bacterial cause of diarrhea in humans in developing countries (Engberg). In December of 1995, a control procedure was performed to test the amount of nitrate in the ground water. In the process of testing this, a sewage pipe was damaged and then leaked into the ground water supply. It took over a month for the water pump to be turned off from the initial point of contamination (Engberg). For this particular case, a very high coliform count was found in the infected water. “A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria <i>Escherichia coli</i> (<i>E.coli</i>) per 100 milliliter of water is counted. The result is expressed as “Coliform Microbial Density” and indicates the extent of fecal matter present in it. According to common water quality standards water can have about 200 colonies, and about 1000 in recreational water” (Business Dictionary). An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen).<br />
</p><br />
<br /><br />
<br />
<h2> What if the <i>E.coli</i> strain mutated or the <i>E.coli</i> was undetectable?</h2><br />
<h4>What are the chances of a mutation occurring or what should be done if a mutation occurs? </h4><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
Currently there is a controversial hypothesis that although <i>E.coli</i> can be detected it is viable but its non-culturable (Bogosian). This holds true for any bacteria that cannot be cultured by standard methods. A culturable bacterium is inoculated into a sterile microcosm, most commonly seawater or river water, and incubated for a number of days with regular monitoring (Bogosian). This would affect the timeline of an outbreak as well as infect more people with contaminated water. This poses as an obvious public health issue for developing nations who do not have the equipment or technology for this kind of situation. Thus far it has been shown that although this poses as a health risk, it has only been attributed to 22 deaths and 104 total cases in the United States in the last 70 years (Bgosian). It has been shown that although the <i>E.coli</i> are present, the cells actually die off based on their living conditions. A study was conducted to determine if changes in cell populations were due to cell death or to the cells developing into the non-culturable state (Bogosian). This proved to be very useful because the study tested what kinds of environment the <i>E.coli</i> cells would either decline in their populations or thrive to cause an outbreak. The conclusion that <i>E.coli</i> cells did not thrive in non-sterile environments (Bogosian). This proves that when an <i>E.coli</i> outbreak occurs it will be because the cells are in an optimum environment where they are able to grow readily. Although <i>E.coli</i> can be present in water does not mean an outbreak will occur. <br />
</p><br />
<br /><br />
<br />
<h2> How many tests should be done for an outbreak? </h2><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
In each of the case studies that were researched, it became apparent quickly that each outbreak has its own characteristics. For example, in 2011, there was an outbreak that took place in Germany where there was a very high incidence in adults, especially women (Rohde). There can also be instances where the outbreak is more toxic to visitors compared to residents or could affect children more so than adults. Since each outbreak is unique in its own way, it is difficult to determine how many tests should be done to determine the severity of the outbreak. According to case study about an outbreak that took place in Alpine, Wyoming, physicians began seeing more patients with bloody diarrhea (Olsen). More cases began showing up in not only Wyoming but also Utah and Washington (Olsen). During the lab investigation of this outbreak, serum was tested from town residents to check for IgM antibodies to the O157 lipopolysaccharides (Olsen). An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen). Prior to the outbreak, the Alpine municipal water system was tested multiple times each month for coliform counts. In this case, they were positive results for <i>E.coli</i> in April, May and June of that year (Olsen). It was in late June that the outbreak occurred, and by middle of July they had found the source of this occurrence. Once the outbreak was detected, stool samples from infected patients were then sent to a lab for further testing. In total, from the time that the outbreak began to the time that the source was found, took about 3-4 weeks (Olsen). During this time, tests were being done by multiple agencies such as the Wyoming State laboratory, and the Utah Department of Health State Laboratory (Olsen). <br />
</p><br />
<br /><br />
<br />
<h2> What are the current practices? </h2><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
<i>E.coli</i> outbreaks have been known to occur in many different sources, such as food, water, and plants. It has been shown that before an outbreak takes place in water, there are typically signs that <i>E.coli</i> is present (Olsen). This is because before an outbreak can occur the cells must be able to survive in their environment. In recent case studies it has been found that although <i>E.coli</i> were found to be present in the water supply, although the amount of <i>E.coli</i> was insufficient. It was not until after an outbreak occurred and patients began having symptoms did the amount of <i>E.coli</i> become a problem. Once the <i>E.coli</i> outbreak has occurred, it will usually take a few weeks to run tests. These experiments can be determining the phenotype of <i>E.coli</i> or just to determine how many people could potentially be affected by the outbreak. It is quite common during <i>E.coli</i> water outbreaks for the cohort case studies to take place. These studies determine the statistical analysis of the outbreak, where the analysts can see how the outbreak progressed with how many people it infected (Olsen). When <i>E.coli</i> are present in other sources such as food and plants, it is usually not known that this is the source until after the outbreak has already occurred. <br />
</p><br />
<br /><br />
<br />
<h2> How does the biosensor improve sanitation?</h2><br />
<h4> Why is there a need for a real time/faster response for the biosensor needed? </h4><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
Improving sanitation and hygiene of water has been one of the primary goals for Arizona State’s iGEM team. As a result of producing a biosensor to detect pathogens, it has the ability to not only prevent outbreaks from occurring but also to minimize them. Our biosensor has the ability to be used to detect different kinds of pathogens. This is very useful because if an outbreak were to occur, the amount of time in spending on determining the phenotype of the pathogen, can then be spent on eliminating it from water sources. This is another reason why our biosensor can be so effective by being able to detect specific pathogens, but it is also able to give you the answers in real time. This eliminates even more time in the process of determining the pathogen. By being able to prevent an outbreak from occurring, we would be able to improve the sanitation of water, especially in developing countries. It is in developing nations where the outbreaks are the most prevalent.<br />
</p><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/FieldApplicationsTeam:Arizona State/FieldApplications2012-10-21T16:19:14Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1><i>Escherichia Coli</i> Case Studies</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<h2> Timeline of an outbreak: </h2><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
In order to implement the biosensor correctly, it is imperative to find data about how <i>E.coli</i> outbreaks progressed. Last year for example, there was on outbreak of <i>E.coli</i> O104:H4 in Germany. It was first detected in early May of 2011, by causing an increased frequency of hemolytic uremic syndrome (Rohde). As the <i>E.coli</i> outbreak continued to spread, traces of <i>E.coli</i> were present in different foods. According to Dr. Rohde in the Open-Source Genomic Analysis of Shiga-Toxin-Producing <i>E.coli</i> O104:H4 case study, the genomic events began with how the <i>E.coli</i> phenotype being determined (Rohde). It wasn’t until five days after the first detection of the <i>E.coli</i> did lab work begin (Rohde). Although this case study reference is a food <i>E.coli</i> outbreak, it continued to grow in size as more food was found to be contaminated. This scenario is similar to a water based <i>E.coli</i> outbreak because typically in larger outbreaks it will affect more than one geographic area. Using this timeline as an example, between the first detection of the outbreak to the <i>E.coli</i> phenotype being determined, it was a period of three weeks. According to research, detection of the pathogen took a very small amount of time compared to determining the phenotype of the pathogen (Rohde). At this point in time there would have been many sick patients and even potentially deaths depending on the severity of the outbreak. With our biosensor, this time could be dramatically reduced. Our biosensor could detect ideally any pathogen of interest.<br />
</p><br />
<br /><br />
<br />
<h2> Finding the source of an outbreak? </h2><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
As defined an outbreak is an occurrence of disease greater than would otherwise be expected at a particular time and place (Business Dictionary). For an <i>E.coli</i> outbreak it is most common to see outbreaks take place when fecal matter is mixed in with the primary supply of water or in food. This is more common in developing countries that in more established countries such as most of Europe and the United States, although occurrences still take place in these areas. For example in Denmark, there was an outbreak of <i>Campylobacter jejuni</i> that happened between 1995-1996 (Engberg). This bacteria is similar to <i>E.coli</i> in that it behaves very similar. <i>Campylobacter jejuni</i> is the most commonly reported bacterial cause of diarrhea in humans in developing countries (Engberg). In December of 1995, a control procedure was performed to test the amount of nitrate in the ground water. In the process of testing this, a sewage pipe was damaged and then leaked into the ground water supply. It took over a month for the water pump to be turned off from the initial point of contamination (Engberg). For this particular case, a very high coliform count was found in the infected water. “A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria <i>Escherichia coli</i> (<i>E.coli</i>) per 100 milliliter of water is counted. The result is expressed as “Coliform Microbial Density” and indicates the extent of fecal matter present in it. According to common water quality standards water can have about 200 colonies, and about 1000 in recreational water” (Business Dictionary). An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen).<br />
</p><br />
<br /><br />
<br />
<h2> What if the E-coli strain mutated or the E-coli was undetectable?</h2><br />
<h4>What are the chances of a mutation occurring or what should be done if a mutation occurs? </h4><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
Currently there is a controversial hypothesis that although <i>E.coli</i> can be detected it is viable but its non-culturable (Bogosian). This holds true for any bacteria that cannot be cultured by standard methods. A culturable bacterium is inoculated into a sterile microcosm, most commonly seawater or river water, and incubated for a number of days with regular monitoring (Bogosian). This would affect the timeline of an outbreak as well as infect more people with contaminated water. This poses as an obvious public health issue for developing nations who do not have the equipment or technology for this kind of situation. Thus far it has been shown that although this poses as a health risk, it has only been attributed to 22 deaths and 104 total cases in the United States in the last 70 years (Bgosian). It has been shown that although the <i>E.coli</i> are present, the cells actually die off based on their living conditions. A study was conducted to determine if changes in cell populations were due to cell death or to the cells developing into the non-culturable state (Bogosian). This proved to be very useful because the study tested what kinds of environment the <i>E.coli</i> cells would either decline in their populations or thrive to cause an outbreak. The conclusion that <i>E.coli</i> cells did not thrive in non-sterile environments (Bogosian). This proves that when an <i>E.coli</i> outbreak occurs it will be because the cells are in an optimum environment where they are able to grow readily. Although <i>E.coli</i> can be present in water does not mean an outbreak will occur. <br />
</p><br />
<br /><br />
<br />
<h2> How many tests should be done for an outbreak? </h2><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
In each of the case studies that were researched, it became apparent quickly that each outbreak has its own characteristics. For example, in 2011, there was an outbreak that took place in Germany where there was a very high incidence in adults, especially women (Rohde). There can also be instances where the outbreak is more toxic to visitors compared to residents or could affect children more so than adults. Since each outbreak is unique in its own way, it is difficult to determine how many tests should be done to determine the severity of the outbreak. According to case study about an outbreak that took place in Alpine, Wyoming, physicians began seeing more patients with bloody diarrhea (Olsen). More cases began showing up in not only Wyoming but also Utah and Washington (Olsen). During the lab investigation of this outbreak, serum was tested from town residents to check for IgM antibodies to the O157 lipopolysaccharides (Olsen). An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen). Prior to the outbreak, the Alpine municipal water system was tested multiple times each month for coliform counts. In this case, they were positive results for <i>E.coli</i> in April, May and June of that year (Olsen). It was in late June that the outbreak occurred, and by middle of July they had found the source of this occurrence. Once the outbreak was detected, stool samples from infected patients were then sent to a lab for further testing. In total, from the time that the outbreak began to the time that the source was found, took about 3-4 weeks (Olsen). During this time, tests were being done by multiple agencies such as the Wyoming State laboratory, and the Utah Department of Health State Laboratory (Olsen). <br />
</p><br />
<br /><br />
<br />
<h2> What are the current practices? </h2><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
<i>E.coli</i> outbreaks have been known to occur in many different sources, such as food, water, and plants. It has been shown that before an outbreak takes place in water, there are typically signs that <i>E.coli</i> is present (Olsen). This is because before an outbreak can occur the cells must be able to survive in their environment. In recent case studies it has been found that although <i>E.coli</i> were found to be present in the water supply, although the amount of <i>E.coli</i> was insufficient. It was not until after an outbreak occurred and patients began having symptoms did the amount of <i>E.coli</i> become a problem. Once the <i>E.coli</i> outbreak has occurred, it will usually take a few weeks to run tests. These experiments can be determining the phenotype of <i>E.coli</i> or just to determine how many people could potentially be affected by the outbreak. It is quite common during <i>E.coli</i> water outbreaks for the cohort case studies to take place. These studies determine the statistical analysis of the outbreak, where the analysts can see how the outbreak progressed with how many people it infected (Olsen). When <i>E.coli</i> are present in other sources such as food and plants, it is usually not known that this is the source until after the outbreak has already occurred. <br />
</p><br />
<br /><br />
<br />
<h2> How does the biosensor improve sanitation?</h2><br />
<h4> Why is there a need for a real time/faster response for the biosensor needed? </h4><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
Improving sanitation and hygiene of water has been one of the primary goals for Arizona State’s iGEM team. As a result of producing a biosensor to detect pathogens, it has the ability to not only prevent outbreaks from occurring but also to minimize them. Our biosensor has the ability to be used to detect different kinds of pathogens. This is very useful because if an outbreak were to occur, the amount of time in spending on determining the phenotype of the pathogen, can then be spent on eliminating it from water sources. This is another reason why our biosensor can be so effective by being able to detect specific pathogens, but it is also able to give you the answers in real time. This eliminates even more time in the process of determining the pathogen. By being able to prevent an outbreak from occurring, we would be able to improve the sanitation of water, especially in developing countries. It is in developing nations where the outbreaks are the most prevalent.<br />
</p><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/FieldApplicationsTeam:Arizona State/FieldApplications2012-10-21T16:15:09Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1><i>Escherichia Coli</i> Case Studies</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<h2> Timeline of an outbreak: </h2><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
In order to implement the biosensor correctly, it is imperative to find data about how <i>E.coli</i> outbreaks progressed. Last year for example, there was on outbreak of <i>E.coli</i> O104:H4 in Germany. It was first detected in early May of 2011, by causing an increased frequency of hemolytic uremic syndrome (Rohde). As the <i>E.coli</i> outbreak continued to spread, traces of <i>E.coli</i> were present in different foods. According to Dr. Rohde in the Open-Source Genomic Analysis of Shiga-Toxin-Producing <i>E.coli</i> O104:H4 case study, the genomic events began with how the <i>E.coli</i> phenotype being determined (Rohde). It wasn’t until five days after the first detection of the <i>E.coli</i> did lab work begin (Rohde). Although this case study reference is a food <i>E.coli</i> outbreak, it continued to grow in size as more food was found to be contaminated. This scenrario is similar to a water based <i>E.coli</i> outbreak because typically in larger outbreaks it will affect more than one geographic area. Using this timeline as an example, between the first detection of the outbreak to the <i>E.coli</i> phenotype being determined, it was a period of three weeks. According to research, detection of the pathogen took a very small amount of time compared to determining the phenotype of the pathogen (Rohde). At this point in time there would have been many sick patients and even potentially deaths depending on the severity of the outbreak. With our biosensor, this time could be dramatically reduced. Our biosensor could detect ideally any pathogen of interest.<br />
</p><br />
<br /><br />
<br />
<h2> Finding the source of an outbreak? </h2><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
As defined an outbreak is an occurrence of disease greater than would otherwise be expected at a particular time and place (Business Dictionary). For an <i>E.coli</i> outbreak it is most common to see outbreaks take place when fecal matter is mixed in with the primary supply of water or in food. This is more common in developing countries that in more established countries such as most of Europe and the United States, although occurrences still take place in these areas. For example in Denmark, there was an outbreak of Campylobacter jejuni that happened between 1995-1996 (Engberg). This bacteria is similar to <i>E.coli</i> in that it behaves very similar. Campylobacter jejuni is the most commonly reported bacterial cause of diarrhea in humans in developing countries (Engberg). In December of 1995, a control procedure was performed to test the amount of nitrate in the ground water. In the process of testing this, a sewage pipe was damaged and then leaked into the ground water supply. It took over a month for the water pump to be turned off from the initial point of contamination (Engberg). For this particular case, a very high coliform count was found in the infected water. “A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria <i>Escherichia coli</i> (<i>E.coli</i>) per 100 milliliter of water is counted. The result is expressed as “Coliform Microbial Density” and indicates the extent of fecal matter present in it. According to common water quality standards water can have about 200 colonies, and about 1000 in recreational water” (Business Dictionary). An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen).<br />
</p><br />
<br /><br />
<br />
<h2> What if the E-coli strain mutated or the E-coli was undetectable?</h2><br />
<h4>What are the chances of a mutation occurring or what should be done if a mutation occurs? </h4><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
Currently there is a controversial hypothesis that although <i>E.coli</i> can be detected it is viable but its non-culturable (Bogosian). This holds true for any bacteria that cannot be cultured by standard methods. A culturable bacterium is inoculated into a sterile microcosm, most commonly seawater or river water, and incubated for a number of days with regular monitoring (Bogosian). This would affect the timeline of an outbreak as well as infect more people with contaminated water. This poses as an obvious public health issue for developing nations who do not have the equipment or technology for this kind of situation. Thus far it has been shown that although this poses as a health risk, it has only been attributed to 22 deaths and 104 total cases in the United States in the last 70 years (Bgosian). It has been shown that although the <i>E.coli</i> are present, the cells actually die off based on their living conditions. A study was conducted to determine if changes in cell populations were due to cell death or to the cells developing into the non-culturable state (Bogosian). This proved to be very useful because the study tested what kinds of environment the <i>E.coli</i> cells would either decline in their populations or thrive to cause an outbreak. The conclusion that <i>E.coli</i> cells did not thrive in non-sterile environments (Bogosian). This proves that when an <i>E.coli</i> outbreak occurs it will be because the cells are in an optimum environment where they are able to grow readily. Although <i>E.coli</i> can be present in water does not mean an outbreak will occur. <br />
</p><br />
<br /><br />
<br />
<h2> How many tests should be done for an outbreak? </h2><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
In each of the case studies that were researched, it became apparent quickly that each outbreak has its own characteristics. For example, in 2011, there was an outbreak that took place in Germany where there was a very high incidence in adults, especially women (Rohde). There can also be instances where the outbreak is more toxic to visitors compared to residents or could affect children more so than adults. Since each outbreak is unique in its own way, it is difficult to determine how many tests should be done to determine the severity of the outbreak. According to case study about an outbreak that took place in Alpine, Wyoming, physicians began seeing more patients with bloody diarrhea (Olsen). More cases began showing up in not only Wyoming but also Utah and Washington (Olsen). During the lab investigation of this outbreak, serum was tested from town residents to check for IgM antibodies to the O157 lipopolysaccharides (Olsen). An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen). Prior to the outbreak, the Alpine municipal water system was tested multiple times each month for coliform counts. In this case, they were positive results for <i>E.coli</i> in April, May and June of that year (Olsen). It was in late June that the outbreak occurred, and by middle of July they had found the source of this occurrence. Once the outbreak was detected, stool samples from infected patients were then sent to a lab for further testing. In total, from the time that the outbreak began to the time that the source was found, took about 3-4 weeks (Olsen). During this time, tests were being done by multiple agencies such as the Wyoming State laboratory, and the Utah Department of Health State Laboratory (Olsen). <br />
</p><br />
<br /><br />
<br />
<h2> What are the current practices? </h2><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
<i>E.coli</i> outbreaks have been known to occur in many different sources, such as food, water, and plants. It has been shown that before an outbreak takes place in water, there are typically signs that <i>E.coli</i> is present (Olsen). This is because before an outbreak can occur the cells must be able to survive in their environment. In recent case studies it has been found that although <i>E.coli</i> were found to be present in the water supply, although the amount of <i>E.coli</i> was insufficient. It was not until after an outbreak occurred and patients began having symptoms did the amount of <i>E.coli</i> become a problem. Once the <i>E.coli</i> outbreak has occurred, it will usually take a few weeks to run tests. These experiments can be determining the phenotype of <i>E.coli</i> or just to determine how many people could potentially be affected by the outbreak. It is quite common during <i>E.coli</i> water outbreaks for the cohort case studies to take place. These studies determine the statistical analysis of the outbreak, where the analysts can see how the outbreak progressed with how many people it infected (Olsen). When <i>E.coli</i> are present in other sources such as food and plants, it is usually not known that this is the source until after the outbreak has already occurred. <br />
</p><br />
<br /><br />
<br />
<h2> How does the biosensor improve sanitation?</h2><br />
<h4> Why is there a need for a real time/faster response for the biosensor needed? </h4><br />
<hr style="color: #800000; height:3px;" /><br />
<p><br />
Improving sanitation and hygiene of water has been one of the primary goals for Arizona State’s iGEM team. As a result of producing a biosensor to detect pathogens, it has the ability to not only prevent outbreaks from occurring but also to minimize them. Our biosensor has the ability to be used to detect different kinds of pathogens. This is very useful because if an outbreak were to occur, the amount of time in spending on determining the phenotype of the pathogen, can then be spent on eliminating it from water sources. This is another reason why our biosensor can be so effective by being able to detect specific pathogens, but it is also able to give you the answers in real time. This eliminates even more time in the process of determining the pathogen. By being able to prevent an outbreak from occurring, we would be able to improve the sanitation of water, especially in developing countries. It is in developing nations where the outbreaks are the most prevalent.<br />
</p><br />
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</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/Chimeric_ReporterTeam:Arizona State/Chimeric Reporter2012-10-04T04:04:05Z<p>Aispas: </p>
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<h1>DNA-Protein Chimera Biosensor</h1><br />
<h2>Overview</h2><br />
<p><br />
There are various biosensors on the market but the state of the art technology is based upon Polymerase Chain Reaction and nanotechnology, which involves gold plated probes and requires specialized skills to use. Despite the extreme accuracy of the device, the affordability, and longer diagnostic time has made the technology scarce in the field. In order to make biosensing technology more accessible to those with few resources and the greatest need, the team worked on generating a cost effective, highly accurate and user-friendly organic biosensor. The components of the sensor will be produced in non-pathogenic <i>E. coli</i>. The sensor is made up of a protein head and DNA tail. The protein head is an enzyme that turns a colorless substrate (X-gal) blue. The enzyme is split in half, so that when the sensor is dissolved in water it cannot produce blue color. When pathogenic target DNA is present, two DNA sensor tails bind the target, the split enzyme assembles, and blue color is produced. Color provides a user-friendly output that is familiar to non-skilled users. <br />
</p><br />
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<h2>Streptavidin</h2><br />
<p><br />
Purified and extracted from the bacteria Streptomyces avidinii, Streptavidin posses a high binding affinity for biotin, with a dissociation constant of 10^-14–10^–16 M ( Laitinen et al.). With such high dissociation constant, the bonding of streptavidin to biotin is considered as one of the strongest non covalent bonding in nature. Due to its high binding affinity to biotin, streptavidin serves as one of the major component of this project. <br />
</p><br />
<p><br />
As a proof of concept for our design, our team designed and assembled fusions of streptavidin (strep) and the split beta-galactosidase (bgal) fragments. Because of streptavidin's high biotin binding affinity, it will allow our fusion proteins to easily bind onto the ends of biotinylated DNA fragments.<br />
</p><br />
<p><br />
<br />
The addition of a poly-histidine tag (His-tag) makes it possible to generate the fusion proteins in E. Coli, then isolate and purify them using a nickle binding column. Mixtures of His-purified strep-tagged bgal fragments and single stranded biotinylated DNA will generate DNA-Protein Chimera 'probes' as the streptavidin binds to the biotinylated end of the DNA. <br />
</p><br />
<p><br />
<br />
By creating probes using complementary strands of DNA of varying lengths, we can confirm that DNA-Protein Chimeric probes generated in E. Coli will create a colorimetric response when kept in close proximity. This will allow us to characterize the behavior of split bgal fusion probes as a function of the distance that they are separated - which can be controlled by altering the length of the ssDNA, or by creating two probes that bind to the same template ssDNA at different sites separated by a variable length.<br />
</p><br />
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<h2>Topoisomerase</h2><br />
<p><br />
<img src="https://static.igem.org/mediawiki/2012/8/8f/TopoDiagram.png" width="800" height="500"><br />
</p><br />
<p><br />
The wild type form of topoisomerase binds to the DNA sequence (YCCTT) in E. Coli. It regulates the winding of the DNA by making a nick after the second T. This allows for the rotation of the strands to relieve torsional stress. Afterwards, the DNA strands are religated. In 2006, Bushman et al. have shown that the smallpox topoisomerase double cysteine mutant D168A mutates the tyrosine responsible for covalent bonding to the 5’ phosphate at the DNA nicking. This mutant form prevents religation, and thus causes the majority of the DNA to stay in the covalently bonded complex.<br />
</p><br />
<h2>Design Scheme</h2><br />
<p><br />
In our design, we plan to use topoisomerase to nick a specific covalently bonded sequence and peel off a section of single stranded DNA. We have designed a template plasmid that includes tandem YCCTT recognition sites with template strand in between, and is complementary to a section of coding sequence of GFP. By inducing topoisomerase/split bgal fusion protein expression, we will be able to generate Chimeric probes <i>in vivo</i> that can be easily His-tag purified and tested. We plan to use a KEIO strain with one copy of this coding sequence in the <i>E. Coli</i> genome in order to test the function of our chimeric probes on cell lysates and mock water samples.<br />
</p><br />
<h2>Reporter System</h2><br />
<p><br />
Basilion et al. from Case Western in 2010 have shown that they were able to make a split beta-galactosidase complementation assay with relatively reliable assay results In the assay, alpha-4/omega, which has a higher specificity, is the most successful split beta galactosidase assay. It is thus used to eliminate false positive. Additionally, we are adapting alpha and 1-omega, which is less specific but has a higher signal, for the same protocol to eliminate false negative.<br />
</p><br />
<p><br />
Basilion et al. also demonstrated success in creating fusion proteins with a split-beta galactosidase fragment and antibody specific to their target. Modifying this, we plan to make a fusion of our mutant topoisomerase and our split-beta galactosidase fragments. This effectively creates a probe that when assembled contains topoisomerase bound both to a single stranded DNA hybridization probe and a split-beta galactosidase fragment. By incubating the two probes that recognize adjacent DNA sequences, we can test for the presence of DNA sequences in a bacterial genome.<br />
</p></div>Aispashttp://2012.igem.org/Team:Arizona_StateTeam:Arizona State2012-10-04T04:00:21Z<p>Aispas: </p>
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<h1>Project Overview</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<p><br />
Arizona State's 2012 iGEM project aims to develop a portable water-borne pathogen biosensor feasible for real-time field application. To achieve both specificity and portability, the team is constructing two biosensors, each capable of detecting a specific pathogenic marker in water-borne bacteria. The first system, a split-enzyme engineered fusion protein, selectively binds to pathogen membranes in water samples and induces a colorimetric response. The second system will detect specific DNA sequences in pathogenic bacteria and activate a similar colorimetric change. The advantage of this design over previous designs in the field lies in the cheap production of probes and the enzymatic chain reaction. In this way, samples can be tested in the field with minimal cost and high sensitivity.<br />
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</p><br />
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<h1>Abstract</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<p><br />
Diarrheic pathogens including <i>E.coli</i> O157:H7 serotype, <i>Campylobacter</i>, <i>Shigella</i>, and <i>Salmonella</i> often contaminate drinking water supplies in developing nations and are responsible for approximately 1.5 million worldwide annual deaths. Current technologies for detection of bacteria include DNA hybridization FRET signaling, electrical detection via immobilized antimicrobial peptides, and PCR amplification followed by gel visualization. Our method of bacterial detection fills a niche in biosensor technology. Our design implies lower costs, higher portability, and a more rapid signal output than most bacterial biosensors. Additionally, our interchangeable DNA probe confers modularity, allowing for a range of bacterial detection. Using a novel split beta-galactosidase complementation assay, we have designed three unique chimeric proteins that recognize and bind to specific pathogenic markers and create a functioning beta-galactosidase enzyme. This functioning enzyme unit then cleaves X-gal and produces a colorimetric output signal. Our research demonstrates success in initial stages of chimeric protein assembly. <br />
</p><br />
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<b>Contact Us</b><br />
<br /><br />
Arizona State University<br />
<br /><br />
ECG 334, PO BOX 9709<br />
<br /><br />
Tempe, Arizona 85287<br />
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{{:Team:Arizona_State/sitemap}}</div>Aispashttp://2012.igem.org/Team:Arizona_StateTeam:Arizona State2012-10-04T03:59:42Z<p>Aispas: </p>
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<br />
<body><br />
<h1>Project Overview</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<p><br />
Arizona State's 2012 iGEM project aims to develop a portable water-borne pathogen biosensor feasible for real-time field application. To achieve both specificity and portability, the team is constructing two biosensors, each capable of detecting a specific pathogenic marker in water-borne bacteria. The first system, a split-enzyme engineered fusion protein, selectively binds to pathogen membranes in water samples and induces a colorimetric response. The second system will detect specific DNA sequences in pathogenic bacteria and activate a similar colorimetric change. The advantage of this design over previous designs in the field lies in the cheap production of probes and the enzymatic chain reaction. In this way, samples can be tested in the field with minimal cost and high sensitivity.<br />
<br />
</p><br />
<br />
<br />
<br />
<h1>Abstract</h1><br />
<hr style="color: #800000; height:3px;" /><br />
<br />
<p><br />
Diarrheic pathogens including <i>E.coli</i> O157:H7 serotype, <i>Campylobacter</i>, <i>Shigella</i>, and <i>Salmonella</i> often contaminate drinking water supplies in developing nations and are responsible for approximately 1.5 million worldwide annual deaths. Current technologies for detection of bacteria include DNA hybridization FRET signaling, electrical detection via immobilized antimicrobial peptides, and PCR amplification followed by gel visualization. Our method of bacterial detection fills a niche in biosensor technology. Our design implies lower costs, higher portability, and a more rapid signal output than most bacterial biosensors. Additionally, our interchangeable DNA probe confers modularity, allowing for a range of bacterial detection. Using a novel split beta-galactosidase complementation assay, we have designed three unique chimeric proteins that recognize and bind to specific pathogenic markers and create a functioning beta-galactosidase enzyme. This functioning enzyme unit then cleaves x-gal and produces a colorimetric output signal. Our research demonstrates success in initial stages of chimeric protein assembly. <br />
</p><br />
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<hr style="color: #800000; height:3px;" /><br />
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<br /><br />
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<div align="center"><br />
<b>Contact Us</b><br />
<br /><br />
Arizona State University<br />
<br /><br />
ECG 334, PO BOX 9709<br />
<br /><br />
Tempe, Arizona 85287<br />
</div><br />
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</body><br />
</html><br />
{{:Team:Arizona_State/Template:twitter}}<br />
{{:Team:Arizona_State/sitemap}}</div>Aispashttp://2012.igem.org/Team:Arizona_State/DataTeam:Arizona State/Data2012-10-04T03:57:33Z<p>Aispas: </p>
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<h1>Data</h1><br />
<h2>Topoisomerase-based DNA Biosensor</h2><br />
<p><br />
<img src="https://static.igem.org/mediawiki/2012/8/8f/TopoDiagram.png" width="800" height="500"><br />
</p><br />
<h3>Data For Our New Favorite Parts</h3><br />
<p><br />
<a href="http://partsregistry.org/Part:BBa_K891234">D168A Double Cysteine Mutant of Smallpox Topoisomerase, BBa_K891234</a><br />
</p><br />
<p><br />
This mutant version of topoisomerase recognizes the YCCTT motif in dsDNA. It cleaves after the last T in this motif, making a single stranded nick, and covalently binds to the 3' phosphate on that thymine.<br />
</p><br />
<p><br />
<a href="http://partsregistry.org/Part:BBa_K891000">GFPT1, BBa_K891000</a><br />
</p><br />
<p><br />
This part should be paired with GFPT2. This part codes for a 20bp sequence that is complementary to a portion of the genomic GFP coding sequence in <i>E.coli</i> Keio strains.<br />
</p><br />
<p><br />
<a href="http://partsregistry.org/Part:BBa_K891999">GFPT2, BBa_K891999</a><br />
</p><br />
<p><br />
This part should be paired with GFPT1. This part codes for a 20bp sequence that is complementary to a portion of the genomic GFP coding sequence that comes after the GFPT1 binding site in <i>E.coli</i> Keio strains.<br />
</p><br />
<h2>Split Beta-Galactosidase Reporter System</h2><br />
<p><br />
Tested alpha fragment of beta-galactosidase for complementation with the omega fragment in vivo. A construct consisting of Streptavadin-Linker-Alpha fragment was transformed into BL21(DE3) <i>E.coli</i> cells that naturally express the omega fragment of beta-galactosidase. Quadrant streak plate in the presence of X-gal produced dark blue colonies. These results illustrate alpha-omega complementation <i>in vivo</i>. In vivo complementation indicates the ability of the two fragments to fuse into a functional beta-galactosidase unit, indicating that the split beta-galactosidase reporter system module of the biosensor was constructed and can be implemented successfully.<br />
</p><br />
<p><br />
<b>Notably, our data shows that the alpha fragment of beta-galactosidase was still able to complementarily bind to the omega fragment and produce a functional unit while linked to streptavidin, a toxic protein due to its high affinity towards biotin, an essential cofactor for fatty acid synthesis, valine synthesis, and gluconeogenesis. This indicates that the split beta-galactosidase reporter system can still be produced under harsh conditions and within a fusion protein construct. This parallels the conditions that we expect our probe to mature in, given that the beta-galactosidase fragments will also be fused to topoisomerase, which is also a toxic protein that binds DNA. This provides a proof-of-concept for the DNA-based biosensor, given that both modules of the final biosensor design work as expected.</b><br />
</p><br />
<h4>After 6 Hours</h4><br />
<p><br />
<img src="https://static.igem.org/mediawiki/2012/8/81/ASUiGEM2012_24hrbgal.png" width="400" length="400"><br />
</p><br />
<h4>After 12 Hours</h4><br />
<p><br />
<br />
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<div id='header' align="center"><br />
<table width="950"><br />
<tr><br />
<td><br />
<img src="https://static.igem.org/mediawiki/2012/0/0e/ASUiGEM2012_48hrbgal.png" width="400" height="400"></td><br />
<td><br />
<br />
<img src="https://static.igem.org/mediawiki/2012/7/75/ASUiGEM2012_48hrbgal2.png" align="right" width="400" height="400"><br />
</tr><br />
<tr><br />
</td><br />
<td><br />
<img src="https://static.igem.org/mediawiki/2012/3/38/ASUiGEM2012_48hrbgal3.png" width="400" height="400"><br />
</td><br />
<td><br />
<img src="https://static.igem.org/mediawiki/2012/a/a0/ASUiGEM2012_48hrbgal4.png" align="right" width="400" height="400"><br />
</td><br />
</table><br />
</div><br />
<br />
</p><br />
<h4>Current Research</h4><br />
<p><br />
Current testing with the split beta-galactosidase system includes time-interval testing of colorimetric response, including quantitative measurements of beta-galactosidase concentration over time, omega fragment negative control testing, and in vitro testing of the alpha and omega fragments linked to streptavadin and Magainin.<br />
</p><br />
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</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ProblemTeam:Arizona State/Problem2012-10-04T03:46:26Z<p>Aispas: </p>
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<h1>Detailed Problem Description</h1><br />
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<hr style="color: #800000; height:3px;" /><br />
<h2>What is the problem we want to solve?</h2><br />
<br />
<p><br />
Viewed as a minor inconvenience in the developed world, diarrhea can be a death sentence in developing countries. Diarrhea can be life threatening as it causes severe dehydration as a result of extensive fluid loss. An estimated 2.0 billion cases of diarrhea occur each year amongst children under five years of age. Of these cases, 1.5 million children die. The major pathogens that most frequently cause acute childhood diarrhea cases are bacterial pathogens such as E. coli, Shigella, Campylobacter and Salmonella. The ASU iGEM team plans to develop an inexpensive way for communities to test the purity of water sources- and identify the specific pathogens in the water source- in efforts of reducing the incidence of childhood diarrhea and ultimately decreasing mortality rates. Existing biosensors for water-borne pathogens are either costly, unaccessible to developing countries, require large machinery to operate, difficult to use without training, and not very reliable. For example, immunoassays, which uses antibodies specific for certain antigens on pathogenic diarrhea, have a good turnaround time. However, not all antigens have available antibodies that can be used for detection, and those antibodies that are available can be very costly. <br />
</font><br />
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<hr style="color: #800000; height:3px;" /><br />
<h2>Quantitative considerations</h2><br />
<br />
<p>What concentration of pathogens causes sickness?</font><br />
<p>In determining what kinds of scenarios our biosensor would work in, a concentration had to be determined for what would be considered an outbreak. Based on research that was found for our project, patients' stool samples were tested for antibodies. An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen). <br />
<br /><br />
What specific design approaches did we take to try to reduce false positives, while making the biosensor effective?<br />
<p> A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria Escherichia coli (E.coli) per 100 milliliter of water is counted. The result is expressed as “Coliform Microbial Density” and indicates the extent of fecal matter present in it. According to common water quality standards water can have about 200 colonies, and about 1000 in recreational water” (Business Dictionary). <br />
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<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>Why are we doing this?</h2><br />
<br />
<p><br />
What do we hope to accomplish/want to figure out?<br />
<p><br />
For this project we are hoping to make our biosensor as user friendly and most cost effective product as possible. In the process in making this design we also wanted to address the results from using the biosensor. We wanted our project to give results in real time and be able to determine the phenotype of the potential pathogen. <br />
<br /><br />
Who are we doing this for? What do we care about? <br />
<p> This project is primarily based on its applications. We wanted to develop a low-cost biosensor that could be implemented in developing countries. This is because pathogenic bacteria causes diarrhea which is one of the world's leading global health issues. By designing our biosensor it would be a potential solution to this problem. <br />
<br />
<br /><br />
What is our ultimate goal?<br />
<p>Our ultimate goal for the project is to be able to see our biosensor used in developing nations. Ideally our biosensor would be able to be used as an early detection device in order to prevent future pathogenic outbreaks. This would be a solution to not only maintaining a healthy water supply but also to also improve the overall sanitation of developing nations. <br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ProblemTeam:Arizona State/Problem2012-10-04T03:44:38Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1>Detailed Problem Description</h1><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>What is the problem we want to solve?</h2><br />
<br />
<p><br />
Viewed as a minor inconvenience in the developed world, diarrhea can be a death sentence in developing countries. Diarrhea can be life threatening as it causes severe dehydration as a result of extensive fluid loss. An estimated 2.0 billion cases of diarrhea occur each year amongst children under five years of age. Of these cases, 1.5 million children die. The major pathogens that most frequently cause acute childhood diarrhea cases are bacterial pathogens such as E. coli, Shigella, Campylobacter and Salmonella. The ASU iGEM team plans to develop an inexpensive way for communities to test the purity of water sources- and identify the specific pathogens in the water source- in efforts of reducing the incidence of childhood diarrhea and ultimately decreasing mortality rates. Existing biosensors for water-borne pathogens are either costly, unaccessible to developing countries, require large machinery to operate, difficult to use without training, and not very reliable. For example, immunoassays, which uses antibodies specific for certain antigens on pathogenic diarrhea, have a good turnaround time. However, not all antigens have available antibodies that can be used for detection, and those antibodies that are available can be very costly. <br />
</font><br />
<br /><br />
<br /><br />
<br />
</p><br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>Quantitative considerations</h2><br />
<br />
<p>What concentration of pathogens causes sickness?</font><br />
<p>In determining what kinds of scenarios our biosensor would work in, a concentration had to be determined for what would be considered an outbreak. Based on research that was found for our project, patients' stool samples were tested for antibodies. An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen). <br />
<br /><br />
What specific design approaches did we take to try to reduce false positives, while making the biosensor effective?<br />
<p> A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria Escherichia coli (E.coli) per 100 milliliter of water is counted. The result is expressed as “Coliform Microbial Density” and indicates the extent of fecal matter present in it. According to common water quality standards water can have about 200 colonies, and about 1000 in recreational water” (Business Dictionary). <br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>Why are we doing this?</h2><br />
<br />
<p><br />
What do we hope to accomplish/want to figure out?<br />
<p><br />
For this project we are hoping to make our biosensor as user friendly and most cost effective product as possible. In the process in making this design we also wanted to address the results from using the biosensor. We wanted our project to give results in real time and be able to determine the phenotype of the potential pathogen. <br />
<br /><br />
Who are we doing this for? What do we care about? <br />
<p> This project is primarily based on its applications. We wanted to develop a low-cost biosensor that could be implemented in developing countries. This is because pathogenic bacteria causes diarrhea which is one of the world's leading global health issues. By designing our biosensor it would be a potential solution to this problem. <br />
<br />
<br /><br />
What is our ultimate goal?<br />
<p>Our ultimate goal for the project is to be able to see our biosensor used in developing nations. Ideally our biosensor would be able to be used as an early detection device in order to prevent future pathogenic outbreaks. This would be a solution to not only maintaining a healthy water supply but also to also improve the overall sanitation of developing nations. <br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2></h2><br />
<br />
<p><br />
<br />
How is this different compared what others have done?<br />
<br /><br />
</p><br />
<br /><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ProblemTeam:Arizona State/Problem2012-10-04T03:43:41Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1>Detailed Problem Description</h1><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>What is the problem we want to solve?</h2><br />
<br />
<p><br />
Viewed as a minor inconvenience in the developed world, diarrhea can be a death sentence in developing countries. Diarrhea can be life threatening as it causes severe dehydration as a result of extensive fluid loss. An estimated 2.0 billion cases of diarrhea occur each year amongst children under five years of age. Of these cases, 1.5 million children die. The major pathogens that most frequently cause acute childhood diarrhea cases are bacterial pathogens such as E. coli, Shigella, Campylobacter and Salmonella. The ASU iGEM team plans to develop an inexpensive way for communities to test the purity of water sources- and identify the specific pathogens in the water source- in efforts of reducing the incidence of childhood diarrhea and ultimately decreasing mortality rates. Existing biosensors for water-borne pathogens are either costly, unaccessible to developing countries, require large machinery to operate, difficult to use without training, and not very reliable. For example, immunoassays, which uses antibodies specific for certain antigens on pathogenic diarrhea, have a good turnaround time. However, not all antigens have available antibodies that can be used for detection, and those antibodies that are available can be very costly. <br />
</font><br />
<br /><br />
<br /><br />
<br />
</p><br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>Quantitative considerations</h2><br />
<br />
<p>What concentration of pathogens causes sickness?</font><br />
<p>In determining what kinds of scenarios our biosensor would work in, a concentration had to be determined for what would be considered an outbreak. Based on research that was found for our project, patients' stool samples were tested for antibodies. An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen). <br />
<br /><br />
What specific design approaches did we take to try to reduce false positives, while making the biosensor effective?<br />
<p> A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria Escherichia coli (E.coli) per 100 milliliter of water is counted. The result is expressed as “Coliform Microbial Density” and indicates the extent of fecal matter present in it. According to common water quality standards water can have about 200 colonies, and about 1000 in recreational water” (Business Dictionary). <br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>Why are we doing this?</h2><br />
<br />
<p><br />
What do we hope to accomplish/want to figure out?<br />
<p><br />
For this project we are hoping to make our biosensor as user friendly and most cost effective product as possible. In the process in making this design we also wanted to address the results from using the biosensor. We wanted our project to give results in real time and be able to determine the phenotype of the potential pathogen. <br />
<br /><br />
Who are we doing this for? What do we care about? <br />
<p> This project is primarily based on its applications. We wanted to develop a low-cost biosensor that could be implemented in developing countries. This is because pathogenic bacteria causes diarrhea which is one of the world's leading global health issues. By designing our biosensor it would be a potential solution to this problem. <br />
<br />
<br /><br />
What is our ultimate goal?<br />
<p>Our ultimate goal for the project is to be able to see our biosensor used in developing nations. Ideally our biosensor would be able to be used as an early detection device in order to prevent future pathogenic outbreaks. This would be a solution to not only maintaining a healthy water supply but also to also improve the overall sanitation of developing nations. <br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2></h2><br />
<br />
<p><br />
<br /><br />
How is this different compared what others have done?<br />
<br /><br />
</p><br />
<br /><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ProblemTeam:Arizona State/Problem2012-10-04T03:35:15Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1>Detailed Problem Description</h1><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>What is the problem we want to solve?</h2><br />
<br />
<p><br />
Viewed as a minor inconvenience in the developed world, diarrhea can be a death sentence in developing countries. Diarrhea can be life threatening as it causes severe dehydration as a result of extensive fluid loss. An estimated 2.0 billion cases of diarrhea occur each year amongst children under five years of age. Of these cases, 1.5 million children die. The major pathogens that most frequently cause acute childhood diarrhea cases are bacterial pathogens such as E. coli, Shigella, Campylobacter and Salmonella. The ASU iGEM team plans to develop an inexpensive way for communities to test the purity of water sources- and identify the specific pathogens in the water source- in efforts of reducing the incidence of childhood diarrhea and ultimately decreasing mortality rates. Existing biosensors for water-borne pathogens are either costly, unaccessible to developing countries, require large machinery to operate, difficult to use without training, and not very reliable. For example, immunoassays, which uses antibodies specific for certain antigens on pathogenic diarrhea, have a good turnaround time. However, not all antigens have available antibodies that can be used for detection, and those antibodies that are available can be very costly. <br />
</font><br />
<br /><br />
<br /><br />
<br />
</p><br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>Quantitative considerations</h2><br />
<br />
<p>What concentration of pathogens causes sickness?</font><br />
<p>In determining what kinds of scenarios our biosensor would work in, a concentration had to be determined for what would be considered an outbreak. Based on research that was found for our project, patients' stool samples were tested for antibodies. An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen). <br />
<br /><br />
What specific design approaches did we take to try to reduce false positives, while making the biosensor effective?<br />
<p> A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria Escherichia coli (E.coli) per 100 milliliter of water is counted. The result is expressed as “Coliform Microbial Density” and indicates the extent of fecal matter present in it. According to common water quality standards water can have about 200 colonies, and about 1000 in recreational water” (Business Dictionary). <br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>Why are we doing this?</h2><br />
<br />
<p><br />
What do we hope to accomplish/want to figure out?<br />
<p><br />
For this project we are hoping to make our biosensor as user friendly and most cost effective product as possible. In the process in making this design we also wanted to address the results from using the biosensor. We wanted our project to give results in real time and be able to determine the phenotype of the potential pathogen. <br />
<br /><br />
Who are we doing this for? What do we care about? tie in to human practices and provide links<br />
<p> <br />
<br />
<br /><br />
...what is our ultimate goal?<br />
</p><br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>How we are doing it</h2><br />
<br />
<p><br />
...what are our methods?<br />
<br /><br />
...How is this different compared what others have done?<br />
<br /><br />
...what has already been tried?<br />
</p><br />
<br /><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ProblemTeam:Arizona State/Problem2012-10-04T03:34:13Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1>Detailed Problem Description</h1><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>What is the problem we want to solve?</h2><br />
<br />
<p><br />
Viewed as a minor inconvenience in the developed world, diarrhea can be a death sentence in developing countries. Diarrhea can be life threatening as it causes severe dehydration as a result of extensive fluid loss. An estimated 2.0 billion cases of diarrhea occur each year amongst children under five years of age. Of these cases, 1.5 million children die. The major pathogens that most frequently cause acute childhood diarrhea cases are bacterial pathogens such as E. coli, Shigella, Campylobacter and Salmonella. The ASU iGEM team plans to develop an inexpensive way for communities to test the purity of water sources- and identify the specific pathogens in the water source- in efforts of reducing the incidence of childhood diarrhea and ultimately decreasing mortality rates. Existing biosensors for water-borne pathogens are either costly, unaccessible to developing countries, require large machinery to operate, difficult to use without training, and not very reliable. For example, immunoassays, which uses antibodies specific for certain antigens on pathogenic diarrhea, have a good turnaround time. However, not all antigens have available antibodies that can be used for detection, and those antibodies that are available can be very costly. <br />
</font><br />
<br /><br />
<br /><br />
<br />
</p><br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>Quantitative considerations</h2><br />
<br />
<p>What concentration of pathogens causes sickness?</font><br />
<p>In determining what kinds of scenarios our biosensor would work in, a concentration had to be determined for what would be considered an outbreak. Based on research that was found for our project, patients' stool samples were tested for antibodies. An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen). <br />
<br /><br />
What specific design approaches did we take to try to reduce false positives, while making the biosensor effective?<br />
</p> A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria Escherichia coli (E.coli) per 100 milliliter of water is counted. The result is expressed as “Coliform Microbial Density” and indicates the extent of fecal matter present in it. According to common water quality standards water can have about 200 colonies, and about 1000 in recreational water” (Business Dictionary). <br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>Why are we doing this?</h2><br />
<br />
<p><br />
What do we hope to accomplish/want to figure out?<br />
<p><br />
For this project we are hoping to make our biosensor as user friendly and most cost effective product as possible. In the process in making this design we also wanted to address the results from using the biosensor. We wanted our project to give results in real time and be able to determine the phenotype of the potential pathogen. <br />
<br /><br />
Who are we doing this for? What do we care about? tie in to human practices and provide links<br />
<p> <br />
<br />
<br /><br />
...what is our ultimate goal?<br />
</p><br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>How we are doing it</h2><br />
<br />
<p><br />
...what are our methods?<br />
<br /><br />
...How is this different compared what others have done?<br />
<br /><br />
...what has already been tried?<br />
</p><br />
<br /><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ProblemTeam:Arizona State/Problem2012-10-04T03:33:17Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1>Detailed Problem Description</h1><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>What is the problem we want to solve?</h2><br />
<br />
<p><br />
Viewed as a minor inconvenience in the developed world, diarrhea can be a death sentence in developing countries. Diarrhea can be life threatening as it causes severe dehydration as a result of extensive fluid loss. An estimated 2.0 billion cases of diarrhea occur each year amongst children under five years of age. Of these cases, 1.5 million children die. The major pathogens that most frequently cause acute childhood diarrhea cases are bacterial pathogens such as E. coli, Shigella, Campylobacter and Salmonella. The ASU iGEM team plans to develop an inexpensive way for communities to test the purity of water sources- and identify the specific pathogens in the water source- in efforts of reducing the incidence of childhood diarrhea and ultimately decreasing mortality rates. Existing biosensors for water-borne pathogens are either costly, unaccessible to developing countries, require large machinery to operate, difficult to use without training, and not very reliable. For example, immunoassays, which uses antibodies specific for certain antigens on pathogenic diarrhea, have a good turnaround time. However, not all antigens have available antibodies that can be used for detection, and those antibodies that are available can be very costly. <br />
</font><br />
<br /><br />
<br /><br />
<br />
</p><br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>Quantitative considerations</h2><br />
<br />
<p>What concentration of pathogens causes sickness?</font><br />
<p>In determining what kinds of scenarios our biosensor would work in, a concentration had to be determined for what would be considered an outbreak. Based on research that was found for our project, patients' stool samples were tested for antibodies. An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen). <br />
<br /><br />
What specific design approaches did we take to try to reduce false positives, while making the biosensor effective?<br />
</p>A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria Escherichia coli (E.coli) per 100 milliliter of water is counted. The result is expressed as “Coliform Microbial Density” and indicates the extent of fecal matter present in it. According to common water quality standards water can have about 200 colonies, and about 1000 in recreational water” (Business Dictionary). <br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>Why are we doing this?</h2><br />
<br />
<p><br />
What do we hope to accomplish/want to figure out?<br />
<p><br />
For this project we are hoping to make our biosensor as user friendly and most cost effective product as possible. In the process in making this design we also wanted to address the results from using the biosensor. We wanted our project to give results in real time and be able to determine the phenotype of the potential pathogen. <br />
<br /><br />
Who are we doing this for? What do we care about? tie in to human practices and provide links<br />
<p> <br />
<br />
<br /><br />
...what is our ultimate goal?<br />
</p><br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>How we are doing it</h2><br />
<br />
<p><br />
...what are our methods?<br />
<br /><br />
...How is this different compared what others have done?<br />
<br /><br />
...what has already been tried?<br />
</p><br />
<br /><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ProblemTeam:Arizona State/Problem2012-10-04T03:32:04Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<html><br />
<body><br />
<h1>Detailed Problem Description</h1><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>What is the problem we want to solve?</h2><br />
<br />
<p><br />
Viewed as a minor inconvenience in the developed world, diarrhea can be a death sentence in developing countries. Diarrhea can be life threatening as it causes severe dehydration as a result of extensive fluid loss. An estimated 2.0 billion cases of diarrhea occur each year amongst children under five years of age. Of these cases, 1.5 million children die. The major pathogens that most frequently cause acute childhood diarrhea cases are bacterial pathogens such as E. coli, Shigella, Campylobacter and Salmonella. The ASU iGEM team plans to develop an inexpensive way for communities to test the purity of water sources- and identify the specific pathogens in the water source- in efforts of reducing the incidence of childhood diarrhea and ultimately decreasing mortality rates. Existing biosensors for water-borne pathogens are either costly, unaccessible to developing countries, require large machinery to operate, difficult to use without training, and not very reliable. For example, immunoassays, which uses antibodies specific for certain antigens on pathogenic diarrhea, have a good turnaround time. However, not all antigens have available antibodies that can be used for detection, and those antibodies that are available can be very costly. <br />
</font><br />
<br /><br />
<br /><br />
<br />
</p><br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>Quantitative considerations</h2><br />
<br />
<p>What concentration of pathogens causes sickness?</font><br />
<p>In determining what kinds of scenarios our biosensor would work in, a concentration had to be determined for what would be considered an outbreak. Based on research that was found for our project, patients' stool samples were tested for antibodies. An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen). <br />
<br /><br />
What specific design approaches did we take to try to reduce false positives, while making the biosensor effective?<br />
</p><br />
A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria Escherichia coli (E.coli) per 100 milliliter of water is counted. The result is expressed as “Coliform Microbial Density” and indicates the extent of fecal matter present in it. According to common water quality standards water can have about 200 colonies, and about 1000 in recreational water” (Business Dictionary). <br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>Why are we doing this?</h2><br />
<br />
<p><br />
What do we hope to accomplish/want to figure out?<br />
<p><br />
For this project we are hoping to make our biosensor as user friendly and most cost effective product as possible. In the process in making this design we also wanted to address the results from using the biosensor. We wanted our project to give results in real time and be able to determine the phenotype of the potential pathogen. <br />
<br /><br />
Who are we doing this for? What do we care about? tie in to human practices and provide links<br />
<p> <br />
<br />
<br /><br />
...what is our ultimate goal?<br />
</p><br />
<br /><br />
<br />
<hr style="color: #800000; height:3px;" /><br />
<h2>How we are doing it</h2><br />
<br />
<p><br />
...what are our methods?<br />
<br /><br />
...How is this different compared what others have done?<br />
<br /><br />
...what has already been tried?<br />
</p><br />
<br /><br />
<br />
</body><br />
</html></div>Aispashttp://2012.igem.org/Team:Arizona_State/ReferencesTeam:Arizona State/References2012-10-04T03:15:31Z<p>Aispas: </p>
<hr />
<div>{{:Team:Arizona_State/Template:Header}}<br />
<br />
<h2>Streptavidin</h2><br />
<ul><ul><br />
*Laitinen, O. H., V. P. Hytönen, H. R. Nordlund, and M. S. Kulomaa. "Genetically Engineered Avidins and Streptavidins." Cellular and Molecular Life Sciences 63.24 (2006): 2992-3017. Print.<br />
*Szafranski, Przemyslaw, Charlene M. Mello, Takeshi Sano, Cassandra L. Smith, David L. Kaplan, and Charles R. Cantor. "A New Approach for Containment of Microorganisms: Dual Control of Streptavidin Expression by Antisense RNA and the T7 Transcription System." Applied Biological Sciences 94 (1997): 1059-063. Print.<br />
<br />
</ul></ul><br />
<br />
<h2>Topoisomerase</h2><br />
<ul><ul><br />
*Hwang, Y., N. Minkah, K. Perry, G. D. Van Duyne, and F. D. Bushman. "Regulation of Catalysis by the Smallpox Virus Topoisomerase." Journal of Biological Chemistry 281.49 (2006): 38052-8060. Print. <br />
*Sekiguchi, JoAnn, and Stewart Shuman. "Requirements for Noncovalent Binding of Vaccinia Topoisomerase I to Duplex DNA." Nucleic Acids Research 22.24 (1994): 5360-365. Print.<br />
*Shuman, S. "Recombination Mediated by Vaccinia Virus DNA Topoisomerase I in Escherichia Coli Is Sequence Specific." Proceedings of the National Academy of Sciences 88.22 (1991): 10104-0108. Print. <br />
*Shuman, Steward. "Site-specific Interaction of Vaccinia Virus Topoisomerase WI Ith Duplex DNA." The Journal of Biological Chemistry 266.17 (1991): 11372-1379. Print. <br />
</ul></ul><br />
<br />
<h2>Human Practices</h2><br />
<ul><ul><br />
*Arora, Kavita, Subhash Chand, and B. D. Malhotra. "Recent Developments in Bio-molecular Techniques for Food Pathogens." Analytica Chimica Acta (2006): 259-74. Web. <br />
<br />
*Bai, Sulan, Jinyi Zhao, Yaochuan Zhang, Wensheng Huang, Shi Xu, Haodong Chen, Liu-Min Fan, Ying Chen, and Xing Wang Deng. "Rapid and Reliable Detection of 11 Food-borne Pathogens Using Thin-film Biosensor Chips." Applied Microbiology and Biotechnology 86.3 (2010): 983-90. Print. <br />
<br />
*Beatty, Mark. "Clinical Infectious Diseases." Epidemic Diarrhea Due to Enterotoxigenic Escherichia Coli. N.p., n.d. Web. 03 Oct. 2012. <http://cid.oxfordjournals.org/content/42/3/329.full>.<br />
<br />
*Bogosian, Gregg. "American Society for MicrobiologyApplied and Environmental Microbiology." Death of the Escherichia Coli K-12 Strain W3110 in Soil and Water. N.p., 11 June 1996. Web. 03 Oct. 2012. <http://aem.asm.org/content/62/11/4114.full.pdf html>.<br />
<br />
*Cairncross, Sandy, Caroline Hunt, Sophie Boisson, Kristof Bostoen, Val Curtis, Isaac CH Fung, and Wolf-Peter Smidth. "Water, Sanitation, and Hygiene of Diarrhoea." International Journal of Epidemiology 39 (2010): 193-205. Print. <br />
<br />
*"Coliform Count." Business Dictionary. N.p., n.d. Web. 03 Oct. 2012. <http://www.businessdictionary.com/definition/coliform-count.html>.<br />
<br />
*De Boer, Enne, and Rijkelt R. Beumer. "Methodology for Detection and Typing of Foodborne Microorganisms." International Journal of Food Microbiology (1999): 119-30. Web. <br />
<br />
*Engberg, Jørgen. "Water-borne Campylobacter Jejuni Infection in a Danish Town-a 6-week Continuous Source Outbreak." Wiley-Online Library. N.p., 27 Oct. 2008. Web. 03 Oct. 2012. <http://onlinelibrary.wiley.com/doi/10.1111/j.1469-0691.1998.tb00348.x/full>.<br />
<br />
*Hunter, Paul, Paul Jagals, and Katherine Pond. Valuing Water, Valuing Livelihoods. Ed. John Cameron. London: IWA, 2011. Web.<br />
<br />
*Johansson, Emily W., and Tessa Wardlaw. Diarrhoea: Why Children Are Still Dying and What Can Be Done. Publication. World Health Organization, 2009. Web. <br />
<br />
*McMeekin, T.a., C. Hill, M. Wagner, A. Dahl, and T. Ross. "Ecophysiology of Food-borne Pathogens: Essential Knowledge to Improve Food Safety." International Journal of Food Microbiology 139 (2010): S64-78. Print. <br />
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*Mellmann, Alexander. "Prospective Genomic Characterization of the German Enterohemorrhagic Escherichia Coli O104:H4 Outbreak by Rapid Next Generation Sequencing Technology." PLOS ONE:. N.p., n.d. Web. 03 Oct. 2012. <http://www.plosone.org/article/info:doi/10.1371/journal.pone.0022751?imageURI=info:doi/10.1371/journal.pone.0022751.g001>.<br />
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*Olsen, Sonja J., Gayle Miller, Thomas Breuer, Malinda Kennedy, Charles Higgins, Jim Walford, Gary McKee, Kim Fox, William Bibb, and Paul Mead. "Abstract." National Center for Biotechnology Information. U.S. National Library of Medicine, 21 Sept. 0005. Web. 03 Oct. 2012. <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2730238/>.<br />
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*Palchetti, Ilaria, and Marco Mascini. "Electroanalytical Biosensors and Their Potential for Food Pathogen and Toxin Detection." Review. 8 Jan. 2008. Print. <br />
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*Rohde, Holger, MD. "The New England Journal of Medicine." Open-Source Genomic Analysis of Shiga-Toxinâ Producing E. Coli O104:H4 âNEJM. N.p., n.d. Web. 03 Oct. 2012. <http://www.nejm.org/doi/full/10.1056/nejmoa1107643>.<br />
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*Swerdlow DL. "Waterborne Outbreak in Missouri of Escherichia Coli O157:H7 Associated with Bloody Diarrhea and Death." A Waterborne Outbreak in Missouri of Escherichia Coli O157:H7 Associated with Bloody Diarrhea... N.p., n.d. Web. 03 Oct. 2012. <http://ukpmc.ac.uk/abstract/ MED/1416555/reload=0;jsessionid=485eElQK2FrO5B4oKFQ1.0>.<br />
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*"Water-related Diseases." World Health Organization. Web. 02 Oct. 2012. <http://www.who.int/water_sanitation_health/diseases/diarrhoea/en/>. <br />
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*World Health Organization and UNICEF. Progress of Sanitation and Drinking Water. World Health Organization and UNICEF, 2010. Print. <br />
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*World Health Organization. Emerging Issues in Water and Infectious Disease. World Health Organization, 2003. Print. <br />
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*World Health Organization. Guidelines for the Control of Shigellosis, including Epidemics Due to Shigallea Dysenteriae. Geneva: World Health Organization, 2005. Print. <br />
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*World Health Organization. Water Safety Plan Manual. Geneva: World Health Organization, 2009. Print.<br />
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<h1 style="font-family:Helvetica;color:maroon;" align="left">Case Studies Specific to E. Coli</h1><br />
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<b> Timeline of an outbreak: </b><br />
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In order to implement the biosensor correctly, it is imperative to find data about how E-coli outbreaks progressed. Last year for example, there was on outbreak of E-coli O104:H4 in Germany. It was first detected in early May of 2011, by causing an increased frequency of hemolytic uremic syndrome (Rohde). As the E-coli outbreak continued to spread, traces of E-coli were present in different foods. According to Dr. Rohde in the Open-Source Genomic Analysis of Shiga-Toxin-Producing E.coli O104:H4 case study, the genomic events began with how the E-coli phenotype being determined (Rohde). It wasn’t until five days after the first detection of the E-coli did lab work begin (Rohde). Although this case study reference is a food E-coli outbreak, it continued to grow in size as more food was found to be contaminated. This scenrario is similar to a water based E-coli outbreak because typically in larger outbreaks it will affect more than one geographic area. Using this timeline as an example, between the first detection of the outbreak to the E-coli phenotype being determined, it was a period of three weeks. According to research, detection of the pathogen took a very small amount of time compared to determining the phenotype of the pathogen (Rohde). At this point in time there would have been many sick patients and even potentially deaths depending on the severity of the outbreak. With our biosensor, this time could be dramatically reduced. Our biosensor could detect ideally any pathogen of interest.<br />
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<b> Finding the source of an outbreak? </b><br />
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As defined an outbreak is an occurrence of disease greater than would otherwise be expected at a particular time and place (Business Dictionary). For an E-coli outbreak it is most common to see outbreaks take place when fecal matter is mixed in with the primary supply of water or in food. This is more common in developing countries that in more established countries such as most of Europe and the United States, although occurrences still take place in these areas. For example in Denmark, there was an outbreak of Campylobacter jejuni that happened between 1995-1996 (Engberg). This bacteria is similar to E-coli in that it behaves very similar. Campylobacter jejuni is the most commonly reported bacterial cause of diarrhea in humans in developing countries (Engberg). In December of 1995, a control procedure was performed to test the amount of nitrate in the ground water. In the process of testing this, a sewage pipe was damaged and then leaked into the ground water supply. It took over a month for the water pump to be turned off from the initial point of contamination (Engberg). For this particular case, a very high coliform count was found in the infected water. “A coliform count is defined as a test of water contamination in which the number of the colonies of coliform-bacteria Escherichia coli (E.coli) per 100 milliliter of water is counted. The result is expressed as “Coliform Microbial Density” and indicates the extent of fecal matter present in it. According to common water quality standards water can have about 200 colonies, and about 1000 in recreational water” (Business Dictionary). An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen).<br />
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<b> What if the E-coli strain mutated or the E-coli was undetectable? What are the chances of a mutation occurring or what should be done if a mutation occurs? </b><br />
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Currently there is a controversial hypothesis that although e coli can be detected it is viable but its non-culturable (Bogosian). This holds true for any bacteria that cannot be cultured by standard methods. A culturable bacterium is inoculated into a sterile microcosm, most commonly seawater or river water, and incubated for a number of days with regular monitoring (Bogosian). This would affect the timeline of an outbreak as well as infect more people with contaminated water. This poses as an obvious public health issue for developing nations who do not have the equipment or technology for this kind of situation. Thus far it has been shown that although this poses as a health risk, it has only been attributed to 22 deaths and 104 total cases in the United States in the last 70 years (Bgosian). It has been shown that although the E-coli are present, the cells actually die off based on their living conditions. A study was conducted to determine if changes in cell populations were due to cell death or to the cells developing into the non-culturable state (Bogosian). This proved to be very useful because the study tested what kinds of environment the E-coli cells would either decline in their populations or thrive to cause an outbreak. The conclusion that E-coli cells did not thrive in non-sterile environments (Bogosian). This proves that when an E-coli outbreak occurs it will be because the cells are in an optimum environment where they are able to grow readily. Although E-coli can be present in water does not mean an outbreak will occur. <br />
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<b> How many tests should be done for an outbreak? </b><br />
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In each of the case studies that were researched, it became apparent quickly that each outbreak has its own characteristics. For example, in 2011, there was an outbreak that took place in Germany where there was a very high incidence in adults, especially women (Rohde). There can also be instances where the outbreak is more toxic to visitors compared to residents or could affect children more so than adults. Since each outbreak is unique in its own way, it is difficult to determine how many tests should be done to determine the severity of the outbreak. According to case study about an outbreak that took place in Alpine, Wyoming, physicians began seeing more patients with bloody diarrhea (Olsen). More cases began showing up in not only Wyoming but also Utah and Washington (Olsen). During the lab investigation of this outbreak, serum was tested from town residents to check for IgM antibodies to the O157 lipopolysaccharides (Olsen). An antibody >1:320 for IgM or >1:160 for IgG was considered positive (Olsen). Prior to the outbreak, the Alpine municipal water system was tested multiple times each month for coliform counts. In this case, they were positive results for E-coli in April, May and June of that year (Olsen). It was in late June that the outbreak occurred, and by middle of July they had found the source of this occurrence. Once the outbreak was detected, stool samples from infected patients were then sent to a lab for further testing. In total, from the time that the outbreak began to the time that the source was found, took about 3-4 weeks (Olsen). During this time, tests were being done by multiple agencies such as the Wyoming State laboratory, and the Utah Department of Health State Laboratory (Olsen). <br />
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<b> What are the current practices? </b><br />
E-coli outbreaks have been known to occur in many different sources, such as food, water, and plants. It has been shown that before an outbreak takes place in water, there are typically signs that E-coli is present (Olsen). This is because before an outbreak can occur the cells must be able to survive in their environment. In recent case studies it has been found that although E-coli were found to be present in the water supply, although the amount of E-coli was insufficient. It was not until after an outbreak occurred and patients began having symptoms did the amount of E-coli become a problem. Once the E-coli outbreak has occurred, it will usually take a few weeks to run tests. These experiments can be determining the phenotype of E-coli or just to determine how many people could potentially be affected by the outbreak. It is quite common during E-coli water outbreaks for the cohort case studies to take place. These studies determine the statistical analysis of the outbreak, where the analysts can see how the outbreak progressed with how many people it infected (Olsen). When E-coli are present in other sources such as food and plants, it is usually not known that this is the source until after the outbreak has already occurred. <br />
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<b> How does the biosensor improve sanitation? Why is there a need for a real time/faster response for the biosensor needed? </b><br />
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Improving sanitation and hygiene of water has been one of the primary goals for Arizona State’s iGEM team. As a result of producing a biosensor to detect pathogens, it has the ability to not only prevent outbreaks from occurring but also to minimize them. Our biosensor has the ability to be used to detect different kinds of pathogens. This is very useful because if an outbreak were to occur, the amount of time in spending on determining the phenotype of the pathogen, can then be spent on eliminating it from water sources. This is another reason why our biosensor can be so effective by being able to detect specific pathogens, but it is also able to give you the answers in real time. This eliminates even more time in the process of determining the pathogen. By being able to prevent an outbreak from occurring, we would be able to improve the sanitation of water, especially in developing countries. It is in developing nations where the outbreaks are the most prevalent.</div>Aispas