Rapid, Inexpensive Measurement of Synthetic Bacterial Community Composition by Sanger Sequencing of Amplicon Mixtures
Synthetic bacterial communities are powerful tools for studying microbial ecology and evolution, as they enable rapid iteration between controlled laboratory experiments and theoretical modeling. However, their utility is hampered by the lack of fast, inexpensive, and accurate methods for quantifyin...
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Published in | iScience Vol. 23; no. 3; p. 100915 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
United States
Elsevier Inc
27.03.2020
Elsevier |
Subjects | |
Online Access | Get full text |
ISSN | 2589-0042 2589-0042 |
DOI | 10.1016/j.isci.2020.100915 |
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Summary: | Synthetic bacterial communities are powerful tools for studying microbial ecology and evolution, as they enable rapid iteration between controlled laboratory experiments and theoretical modeling. However, their utility is hampered by the lack of fast, inexpensive, and accurate methods for quantifying bacterial community composition. Although next-generation amplicon sequencing can be very accurate, high costs (>$30 per sample) and turnaround times (>1 month) limit the nature and pace of experiments. Here, we quantify amplicon composition in synthetic bacterial communities through Sanger sequencing. We PCR amplify a universal marker gene, then we sequence this amplicon mixture in a single Sanger sequencing reaction. We then fit the “mixed” electropherogram with contributions from each community member as a linear combination of time-warped single-strain electropherograms, allowing us to estimate the fractional amplicon abundance of each strain within the community. This approach can provide results within one day and costs ∼$5 per sample.
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•Our method “CASEU” estimates amplicon composition from mixed Sanger electropherograms•CASEU uses a marker gene and is fast (1-day turnaround) and inexpensive ($5/sample)•CASEU is accurate to ±1% abundance in mock microbial communities with up to seven strains•CASEU is available as a free, open-source R package
Microbiology; Microbial Genetics; Bioinformatics; Sequence Analysis |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Lead Contact These authors contributed equally |
ISSN: | 2589-0042 2589-0042 |
DOI: | 10.1016/j.isci.2020.100915 |