Bacterial Sub-Populations

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Summary: Researchers in Dr. Alfred Spormann’s lab have developed a qPCR platform to identify organohalogen-respiring bacteria subpopulations from a complex environment for bioremediation purposes. The bioremediation of groundwater aquifers and sediments contaminated with chlorinated hydrocarbons depend on microorganisms such as organohalogen-respiring bacteria. Successfully managing bioremediation requires understanding the microbial community present to predict and control its ecological responses. A variety of techniques have been developed to identify and differentiate closely related but distinct organohalogen-respiring bacteria. However, due to requirements for large amounts of DNA, high cost and sensitivity constraints, these techniques have not been widely applied in full scale field studies. To overcome these limitations, the inventors have developed this qPCR platform which identifies distinct subpopulations of organohalogen-respiring bacteria. The qPCR assays can be run in parallel at a single reaction condition in a nanoliter qPCR instrument to screen DNA recovered from bioreactors or sites contaminated with chlorinated hydrocarbons. The technology may be used to estimate the diversity and abundance of organohalogen-respiring bacterial populations and their response to natural or engineered perturbations to achieve successful biochemical pollution removal.   Applications: Bioremediation of contaminated sites Characterize native or introduced organohalogen-respiring bacterial populations and their response to biostimulation, bioaugmentation or natural attenuation Bioreactors Engineering bacterial consortia for optimal bioaugmentation of a contaminated site Reactor monitoring: ensure bacterial population structure is maintained for consistent reactor performance   Advantages: Rapid: screen 50 gene targets in under 2 hours High sensitivity with minimal DNA input: allows direct screening of un-amplified DNA isolated from contaminated site environment Cost-effective: per-sample cost is less than 50 dollars allowing for high temporal or spatial resolutions sampling Robust to mutations present in natural bacterial populations: multiple conserved loci are screened in each gene target Permits low complexity data analysis compared to bioinformatics intensive alternatives