Team:USP-UNESP-Brazil/Project
From 2012.igem.org
Network
Overall project
Our group purpose is to discover and develop new ways of hacking and modifying biological systems. We developed two projects, which aims are to introduce new properties in a system and to gain control over the information processing. The first one hacks the way of transforming cells. It inserts and express any protein inside E. coliand only uses two steps: PCR and transformation. The Cre recombinase action over a target gene (ORF - open reading frame) flanked by loxP modified sites, allows its insertion in a plasmid (Plug&Play Machine). The receptor plasmid posses all the necessary protein expression machinery. The second project is a way to build a bacteria network with memory capacity, which works as a Hopfield Network. This network could, by means of quorum sensing, recognize a given pattern (input), process the pattern and reach an output state. The output depends on two possibilities already imprinted in the memory of the bacteria community.
Plug&Play Plasmid
Aware of the necessity of techniques to produce biological standardize parts in a high throughput manner, we developed a project that aims to build a machine, called Plug&Play, that express any protein using the Cre-Recombinase system. For this purpose, we designed a plasmid that has a mutated recombination site (lox71) recognize by the Cre-recombinase, in which the desired ORF (open reading frame) is going to be inserted, upstream the insertion site is located a promoter ready to transcript the gene into the desire protein. The plasmid has also a resistance gene to ampicillin that maintain it inside the cell as long as the antibiotic is applied in the culture medium. This is a high throughput system for expressing proteins that allows putative (or new build) genes prospection, which is mean to be an open source tool.
Associative Memory Network Using Bacteria
Memory storage in biological systems has a critical role in biotechnology development. A systemic way of storing a specific memory that can be recovered and used at any moment has been studied in several experiments and mathematical models involving neural networks. One of these models, known as “Hopfield Network”, considers the memory storage as a neurons association that share a characteristic pattern of “communication intensity” – the “measure unity” of a neuron network . This model is notorious for allowing systems to recognize patterns.
In this project we propose to build a communication network using E.coli populations with associative memory that behaves like a Hopfield Model. Modified E.coli populations will be generated and physically isolated from each other, the communication will happen through Quorum Sensing Substances (QSS). These QSS will produce inhibition or excitation of the pre-determined populations, the amount of excitation will be measure using GFP fluorescent. The objective is to achieve a specific complete pattern represented by excited and inhibited populations by means of the interactions between the bacteria populations that processed a given incomplete pattern. The network will recognize this pattern and choose between two systemic memories already inserted using biobricks.