(564b) Freq-Seq: A Method for Rapid, Cost-Effective Allele Frequency Determination in Microbial Populations

Understanding evolutionary dynamics in microbial systems requires the ability to accurately follow allele frequencies in populations through time. Established methods such as quantitative Sanger sequencing, restriction fragment length polymorphism (RFLP), quantitative PCR (qPCR) and mass spectrometry-based methods (SEQUENOM) provide an array of strategies to interrogate allele frequencies. But these methods are inhibited by both their ease and/or cost of implementation, as well as their respective detection limits. An alternative strategy has been to rely on next generation meta-sequencing of microbial populations to infer relative frequencies of pertinent genotypes. The primary drawbacks to this approach are the lack of uniform sequencing depth required to make quantitative diagnoses of low frequency mutations and inability to perform large scale sample multiplexing.

In contrast, we present a rapid, cost-effective strategy for localized allele frequency detection using the Illumina HiSeq and Genome Analyzer next-generation sequencing platforms called Freq-Seq. The Freq-Seq method utilizes two rounds of PCR using inexpensive user-designed oligonucleotides and a bar-coded adapter system that can be produced in-house at low cost. Likewise, we have developed custom analysis software allowing users to easily extract and interpret experimental results. Both the Freq-Seq allele frequency detection adapter kit and open-source software are now publically available.  

We validate and demonstrate the utility of the Freq-Seq system by determining the order of emergence and frequency of beneficial alleles that arose as a microbial population adapted to an engineered metabolic pathway. Our data show that Freq-Seq is capable of detecting allele frequencies accurately below 1% abundance. Likewise, the evolutionary dynamics observed via Freq-Seq allowed us to uncover the existence of large-scale clonal interference during the early stages of adaptation. These results suggest the utility of Freq-Seq as an accessible and cost-effective diagnostic tool in determining the genetic composition of microbial processes and communities.