For decades, multiple varieties of antibiotics have been used for therapeutic purposes and across industries such as agriculture and animal husbandry. However, in recent times both the use and inadvertent misuse of antibiotics have led to the advent of multi-drug-resistant strains. Phage therapy, which was thought to be the best solution, is also failing due to CRISPR and other innate bacterial defences. Development of newer antibiotics is slow and unreliable as it depends mainly on modifying the existing antibiotics.
We at iGEM IISER Tirupati aspire to lessen the burden that is Antimicrobial Resistance (AMR) by controlling antibiotic pollution. We plan to achieve this by engineering an E. coli, giving it antibiotic degrading capabilities, and releasing the cell lysate of said E. coli on farm excreta so that it can degrade the excess antibiotic in the excreta prior to its release to the environment. The cell lysate, rich in the antibiotic degrading protein, is expected to degrade the antibiotics below the Predicted No Effect Concentration (PNEC) level. Thus, instead of curing AMR, we prevent it in the first place. Use of a tightly regulated ‘kill switch’ with DNA degrading enzyme alongside the use of cell lysate ensures high biosafety, limiting the flow of DNA of our GMO into the environment. Even though we plan to show a proof of concept through the degradation of sulphonamides, this can be extended for bioremediation of a range of antibiotics by switching the antibiotic degrading genes involved and with certain simpler optimizations.
Below are a few figures that provide an insight into the effect of antibiotics on the growth rate of bacteria.
Figure 1: Schematic representation of growth rates as a function of antibiotic concentration. Green indicates a concentration interval where the susceptible strain (blue line) will outcompete the resistant strain (red line). Orange (sub-MIC selective window) and red (traditional mutant selective window) indicate concentration intervals where the resistant strain will outcompete the susceptible strain. MICsusc = minimal inhibitory concentration of the susceptible strain, MICres = minimal inhibitory concentration of the resistant strain and MSC = minimal selective concentration.
Adapted from: Gullberg E, Cao S, Berg OG, Ilbäck C, Sandegren L, Hughes D, Andersson DI. Selection of resistant bacteria at very low antibiotic concentrations. PLoS Pathog. 2011 Jul;7(7):e1002158. doi: 10.1371/journal.ppat.1002158. Epub 2011 Jul 21. PMID: 21811410; PMCID: PMC3141051.
Figure 2: (A) Growth rates of resistant (blue) and sensitive (red) bacteria as a function of antibiotic concentration. Free of the metabolic cost associated with resistance, sensitive cells grow faster than resistant cells (γS>γR) at antibiotic concentrations below the MIC of the sensitive bacteria. Above the MIC, sensitive cells die at a rate of γD. (D) The equilibrium-resistant fraction as a function of the antibiotic concentration and the initial cell density. According to this model, coexistence between resistant and sensitive cells is possible at antibiotic concentrations above the MIC of sensitive cells.
Adapted from: Yurtsev EA, Chao HX, Datta MS, Artemova T, Gore J. Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids. Mol Syst Biol. 2013 Aug 6;9:683. doi: 10.1038/msb.2013.39. PMID: 23917989; PMCID: PMC3779801.