Difference between revisions of "Team:elan vital korea/Protocol"

What makes the problem more pressing is that the data isbased on the reports of clinical samples from
laboratories, “predominantly in hospital settings” (Antimicrobial Resistance: Global Report on
Surveillance 2014, WHO, 2014, p. 70), which means community-acquired (compared to health-care associated)
infections and uncomplicated infections are underrepresented.

Global Report on Surveillance 2014, WHO, 2014, p. 70), which means community-acquired (compared to health-care
associated) infections and uncomplicated infections are underrepresented.

Existing Methods Used for Detection

CDC’s efforts at outsmarting the antibiotic resistance focuses on 4 core actions: detect, respond, prevent
and discover. The project is called AR Initiative (Detect and Protect Against Antibiotic
Resistance Initiative), which is an integral part of the CDC strategy to target investment aimed at AR.
Among the AR initiative, detection is the first step that impacts the whole controlling process.
Detecting antibiotic resistance quickly and effectively is crucial for determination of the treatment methods
for different patients as well as for quarantines to prevent it from becoming epidemic.
Currently, several methods are used for the detection of the antibiotic resistance. Most common and traditional
method is using growth inhibition assays performed in broth or by agar disc diffusion.
For clinically critical bacteria, diagnostic laboratories perform phenotypic-based analyses using standardized
susceptibility testing methods, usually in accordance with the guidelines published by the Clinical
and Laboratory Standards Institute.

Using the culture-based approach, it can take 1—2 days to produce results for fast-growing bacteria such as
Escherichia coli orSalmonella, but several weeks for slow-growing bacteria such as Mycobacterium tuberculosis.
Moreover, culturing only works for a small fraction of microbes; although most pathogens can be cultured
relatively easily thanks to years of accumulated experimental experiences, the vast majority of microbes cannot
grow outside their host environment, including pathogens such as Chlamydia orTrypanosomes.

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Using newer molecular detection techniques for antibiotic resistance such as quantitative PCR (qPCR) or microarrays, we can determine
the presence of specific resistance genes within hours, and we obtain improved diagnosis results. However,
these culture-independent approaches target well-known and well-studied pathogens or resistance-causing genes only,
and cannot be easily used for broader spectrum screening.

CDC dramatically innovated the detection process by adopting the Advanced Molecular Detection (AMD), which combines the latest pathogen
identification technologies with bioinformatics and advanced epidemiology to more effectively understand, prevent and control infectious
diseases. Using those technologies, it is possible to rapidly look for a microbe's match among thousands of reference
samples in the microbe library. If no match is found, the whole genomic sequence
of the microbe's DNA code can be taken, then quickly analyzed using disease detective works and bioinformatics
to answer critical disease-response questions. However, this new method, while it sounds very interesting, is not to be
completed until 2020, and still requires incubation, as well as being expensive.

Our Hypothesis: Possibility of Using Quorum
Sensing for Early Detection

Our team, Elan Vital Korea, addressed the problem of rapidly detecting antibiotic-resistant bacteria. We were interested in
a rapid and efficient method of antibiotic resistance detection, and we believed that such a method could be engineered
using quorum sensing. Our hypothesis was that we would be able to use quorum sensing – a method bacteria
use to communicate with each other – to make the cells quickly report the existence of antibiotic-resistant bacteria

By quorum sensing, bacteria can perform many cooperative functions, such as biofilm formation, antibiotic production, motility,
swarming, virulence, and much more. While most quorum sensing takes place between bacteria of the same species, there are
cases of interspecies quorum sensing. Auto-inducers affect the gene expression of the bacteria once they reach
a certain concentration threshold. Bacteria using quorum sensing usually produce small amounts of
auto-inducers, so that the concentration of auto-inducers are affected by the concentration of the bacteria.
In other words, quorum sensing, in essence, regulates gene expression in response to cell density.
Using quorum sensing, bacteria are able to act in unison, as if they were a single organism.

Quorum sensing is widely used by various bacteria for various functions, so each uses a slightly different auto-inducer
so the signals are not mixed up. In general, gram-negative bacteria use a class of molecules called N-acyl
homoserine lactones, or AHL, while gram-positive bacteria use short processed polypeptides.

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For example, the picture below represents the quorum sensing mechanism in the bacteria vibrio fisheri. Vibrio fisheri is a bacteria
that produces bioluminescence, and is famous for revealing quorum sensing for the first time. Vibrio fisheri uses quorum sensing
to produce light in high cell density, and researchers first discovered quorum sensing from examining vibrio fisheri.

In vibrio fishri, quorum sensing involves LuxI and LuxR as well as AHL. LuxI is the protein that produces AHL, and LuxR forms a complex
with AHL to affect the regulation of genes. In this case, it produces luciferase, which produces bioluminescence. Furthermore, the process
also boosts the production of LuxI, which creates a positive feedback loop. This AHL-LuxR quorum sensing mechanism is one of the most well
known gram-negative quorum sensing pathways, and it can be
engineered to affect almost any coding sequence we like.

For the project, we have developed a reporter cell that expresses GFP in the presence of the QS signaling molecule acyl homoserine
lactone (AHL). Our test cells (which act as a simulation of antibiotic-resistant bacteria) express lactonase,
which breaks down AHL. In our experimental system, test cells should signify their presence by breaking down AHL and
preventing GFP expression in reporter cells.

Experiment: Process and Results

There are many ways of utilizing quorum sensing for medicinal use, and one of the most intuitive and most well-known methods is quorum quenching.

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Quorum quenching takes advantage of the fact that quorum sensing also plays a role in expressing virulence, and interferes with the quorum sensing that
produces virulence. There are many ways of utilizing quorum sensing for medicinal use, and one of the most intuitive and most well-known methods is quorum quenching.
Quorum quenching takes advantage of the fact that quorum sensing also plays a role in expressing virulence, and interferes with
the quorum sensing that produces virulence. However, for our project this year, we decided to focus on engineering a detection method for antibiotic resistance.
For the project, we created a test plasmid and a reporter plasmid. We then transformed competent E. coli with the plasmids to produce a
test cell and a reporter cell. As shown in the picture below, the test cell produces lactonase, which breaks down AHL, a common auto-inducer in
gram-negative bacteria. And the reporter cell produces GFP (or luciferase) which creates a visible difference that we can detect.
Both plasmids were engineered using the BioBrick DNA recombination process. With such a set up, it will be possible to detect the presence of the test cell, or lactonase.

For the confirmation of our hypothesis, we conducted some experiments. Ideally, mixing AHL with the test cell will break down the AHL. And, adding
the reporter after that will not result in any fluorescence. But, if we do the same process with the control bacteria instead of the test cell,
there will be fluorescence. As theorized, the control experiments produced fluorescence, but the experiments with the test cell produced no fluorescence.

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