ArticleApplied and environmental microbiology2007
Multivariate analysis of complex DNA sequence electropherograms for high-throughput quantitative analysis of mixed microbial populations.
Article in Applied and environmental microbiology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Inferring microbial interaction network from microbiome data using RMN algorithm.BMC systems biology · 2015Article
- Shifts in the Midgut/Pyloric Microbiota Composition within a Honey Bee Apiary throughout a Season.Microbes and environments · 2015Article
- Base-calling algorithm with vocabulary (BCV) method for analyzing population sequencing chromatograms.PloS one · 2013Article
- Long-term nitrogen amendment alters the diversity and assemblage of soil bacterial communities in tallgrass prairie.PloS one · 2013Article
- Article
- Abrupt temporal fluctuations in the chicken fecal microbiota are explained by its gastrointestinal origin.Applied and environmental microbiology · 2012Article
- Probiotics, symptoms, and gut microbiota: what are the relations? A randomized controlled trial in subjects with irritable bowel syndrome.Gastroenterology research and practice · 2012Article
- Statistical assessment of variability of terminal restriction fragment length polymorphism analysis applied to complex microbial communities.Applied and environmental microbiology · 2009Article
- Quantitative Single-letter Sequencing: a method for simultaneously monitoring numerous known allelic variants in single DNA samples.BMC genomics · 2008Article
- Co-infection dynamics of a major food-borne zoonotic pathogen in chicken.PLoS pathogens · 2007Article
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Authors and funding
6 authors.
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Abstract
High-throughput quantification of genetically coherent units (GCUs) is essential for deciphering population dynamics and species interactions within a community of microbes. Current techniques for microbial community analyses are, however, not suitable for this kind of high-throughput application. Here, we demonstrate the use of multivariate statistical analysis of complex DNA sequence electropherograms for the effective and accurate estimation of relative genotype abundance in cell samples from mixed microbial populations. The procedure is no more labor-intensive than standard automated DNA sequencing and provides a very effective means of quantitative data acquisition from experimental microbial communities. We present results with the Campylobacter jejuni strain-specific marker gene gltA, as well as the 16S rRNA gene, which is a universal marker across bacterial assemblages. The statistical models computed for these genes are applied to genetic data from two different experimental settings, namely, a chicken infection model and a multispecies anaerobic fermentation model, demonstrating collection of time series data from model bacterial communities. The method presented here is, however, applicable to any experimental scenario where the interest is quantification of GCUs in genetically heterogeneous DNA samples.
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