Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease

MSystems
Robert H MillsDavid J Gonzalez

Abstract

Although genetic approaches are the standard in microbiome analysis, proteome-level information is largely absent. This discrepancy warrants a better understanding of the relationship between gene copy number and protein abundance, as this is crucial information for inferring protein-level changes from metagenomic data. As it remains unknown how metaproteomic systems evolve during dynamic disease states, we leveraged a 4.5-year fecal time series using samples from a single patient with colonic Crohn's disease. Utilizing multiplexed quantitative proteomics and shotgun metagenomic sequencing of eight time points in technical triplicate, we quantified over 29,000 protein groups and 110,000 genes and compared them to five protein biomarkers of disease activity. Broad-scale observations were consistent between data types, including overall clustering by principal-coordinate analysis and fluctuations in Gene Ontology terms related to Crohn's disease. Through linear regression, we determined genes and proteins fluctuating in conjunction with inflammatory metrics. We discovered conserved taxonomic differences relevant to Crohn's disease, including a negative association of Faecalibacterium and a positive association of Escherichia with...Continue Reading

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Citations

Jul 3, 2019·Molecular & Cellular Proteomics : MCP·Hao Q TranAndrew T Gewirtz
May 7, 2020·Microbiome·Kenzie D BirseGrace Aldrovandi
Jul 2, 2020·MSystems·Carlos G GonzalezJoshua E Elias
May 7, 2020·Metabolites·Kathleen A Lee-SarwarScott T Weiss
Sep 1, 2019·Molecular & Cellular Proteomics : MCP·Hao Q TranAndrew T Gewirtz

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Datasets Mentioned

BETA
PRJEB28712

Software Mentioned

Diamond
pDB
Prodigal
Procrustes
scipy
Salmon
Proteome Discoverer
Integrated Gene Catalog [
Sequest
MEGAHIT

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