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Christopher Quince

Publications and source records attributed to Christopher Quince.

2 recordsLinked to original sources

De novo extraction of microbial strains from metagenomes reveals intra-species niche partitioning

BackgroundWe introduce DESMAN for De novo Extraction of Strains from MetAgeNomes. Metagenome sequencing generates short reads from throughout the genomes of a microbial community. Increasingly large, multi-sample metagenomes, stratified in space and time are being generated from communities with thousands of species. Repeats result in fragmentary co-assemblies with potentially millions of contigs. Contigs can be binned into metagenome assembled genomes (MAGs) but strain level variation will remain. DESMAN identifies variants on core genes, then uses co-occurrence across samples to link variants into strain sequences and abundance profiles. These strain profiles are then searched for on non-core genes to determine the accessory genes present in each strain.\n\nResultsWe validated DESMAN on a synthetic twenty genome community with 64 samples. We could resolve the five E. coli strains present with 99.58% accuracy across core gene variable sites and their gene complement with 95.7% accuracy. Similarly, on real fecal metagenomes from the 2011 E. coli (STEC) O104:H4 outbreak, the outbreak strain was reconstructed with 99.8% core sequence accuracy. Application to an anaerobic digester metagenome time series reveals that strain level variation is endemic with 16 out of 26 MAGs (61.5%) examined exhibiting two strains. In almost all cases the strain proportions were not statistically different between replicate reactors, suggesting intra-species niche partitioning. The only exception being when the two strains had almost identical gene complement and, hence, functional capability.\n\nConclusionsDESMAN will provide a provide a powerful tool for de novo resolution of fine-scale variation in microbial communities. It is available as open source software from https://github.com/chrisquince/DESMAN.

Bioinformatics

Simera: Modelling the PCR Process to Simulate Realistic Chimera Formation

Polymerase Chain Reaction (PCR) is the principal method of amplifying target DNA regions and, as such, is of great importance when performing microbial diversity studies. An unfortunate side effect of PCR is the formation of unwanted byproducts such as chimeras. The main goal of the work covered in this article is the development of an algorithm that simulates realistic chimeras for use in the evaluation of chimera detection software and for investigations into the accuracy of community structure analyses. Experimental data has helped to identify factors which may cause the formation of chimeras and has provided evidence of how influential these factors can be. This article makes use of some of this evidence in order to build a model with which to simulate the PCR process. This model helps to better explain the formation of chimeras and is therefore able to provide aid to future studies that intend to use PCR.

Bioinformatics