Improving Microbiome Science by Modeling the Measurement Process

PROJECT SUMMARY/ABSTRACT - Callahan, Benjamin The Callahan laboratory develops quantitative and computational methods that improve the precision, accuracy and reproducibility of microbiome measurement methods, and implements those methods in open-source and actively supported software. The Callahan laboratory collaborates with other research groups to investigate the role of host-associated microbial communities in various health problems, with particular emphasis on predicting preterm birth and reducing the spread of antimicrobial resistance. High throughput methods to measure whole microbial communities without the need for culture have revolutionized microbiome science. Most prominent amongst a growing suite of “omics” methods are those based on high-throughput sequencing: amplicon sequencing and metagenomics. However, while these sequencing-based measurement methods are powerful, they suffer from imperfections and flaws that limit their application in some sample types and can lead to incorrect conclusions. Over the next five years we intend to build new capabilities for measuring microbiomes embedded in high-DNA backgrounds by creating new computational methods for long-read amplicon sequencing. If successful, this will provide microbiome scientists a measurement method with sub-species resolution that can be inexpensively applied to difficult sample types like tissue biopsies. We also intend to build new software and methods that correct the bias inherent in microbiome sequencing measurements. Because different microbial taxa are detected more (or less) efficiently than others, and this detection efficiency depends on experimental details, the abundances of microbes measured by sequencing deviate from the true abundances. If successful, our new work will use measurements of reference materials to correct that deviation and recover the true microbial abundances. By focusing on proteins (the working molecules of life) rather than DNA (the plans of life), metaproteomics brings microbiome measurement closer to actual activity and function. Rapid recent advances in mass spectrometry technology has made metaproteomics more accessible and competitive with sequencing-based methods, but associated computational and statistical methods are still catching up to these changes. Over the next five years, we will leverage a new set of reference samples to evaluate metaproteomics measurements and analysis methods, providing guidance on optimal choices and as needed developing new methods. If successful, this work will improve the capabilities available to microbiome scientists for studying microbiomes at the molecular level closest to their function.