Team:Arizona State/FieldApplications

From 2012.igem.org

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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.
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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.
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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 <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).
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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 <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).
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Revision as of 16:19, 21 October 2012

Escherichia Coli Case Studies


Timeline of an outbreak:


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 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. 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.


Finding the source of an outbreak?


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).


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?


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.


How many tests should be done for an outbreak?


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).


What are the current practices?


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.


How does the biosensor improve sanitation?

Why is there a need for a real time/faster response for the biosensor needed?


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.