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Mack, D. R.

Publications and source records attributed to Mack, D. R..

2 recordsLinked to original sources

Revealing Protein-Level Functional Redundancy in the Human Gut Microbiome using Ultra-deep Metaproteomics

Functional redundancy is a key property of ecosystems and represents the fact that phylogenetically unrelated taxa can play similar functional roles within an ecosystem. The redundancy of potential functions of human microbiome has been recently quantified using metagenomics data. Yet, the redundancy of functions which are actually expressed within the human microbiome remains largely unexplored. Here, we quantify the protein-level functional redundancy in the human gut microbiome using metaproteomics and network approaches. In particular, our ultra-deep metaproteomics approach revealed high protein-level functional redundancy and high nestedness in proteomic content networks - bipartite graphs that connect taxa with their expressed functions. We further examined multiple metaproteomics datasets and showed that various environmental factors, including individuality, biogeography, xenobiotics, and disease, significantly altered the protein-level functional redundancy. Finally, by projecting the bipartite proteomic content networks into unipartite weighted genus networks, functional hub genera across individual microbiomes were discovered, suggesting that there may be a universal principle of functional organization in microbiome assembly. HighlightsO_LIUltra-deep metaproteomics reveals high protein-level functional redundancy in the human gut microbiome C_LIO_LIWithin-sample proteomic content networks display universal topology C_LIO_LIVarious environmental factors influence the redundancy of expressed functions C_LIO_LIFunctional hub genera are present across different datasets C_LI

systems biology↗

Stratification of Risk of Progression to Colectomy in Ulcerative Colitis using Measured and Predicted Gene Expression

An important goal of clinical genomics is to be able to estimate the risk of adverse disease outcomes. Between 5% and 10% of ulcerative colitis (UC) patients require colectomy within five years of diagnosis, but polygenic risk scores (PRS) utilizing findings from GWAS are unable to provide meaningful prediction of this adverse status. By contrast, in Crohns disease, gene expression profiling of GWAS-significant genes does provide some stratification of risk of progression to complicated disease in the form of a Transcriptional Risk Score (TRS). Here we demonstrate that both measured (TRS) and polygenic predicted gene expression (PPTRS) identify UC patients at 5-fold elevated risk of colectomy with data from the PROTECT clinical trial and UK Biobank population cohort studies, independently replicated in an NIDDK-IBDGC dataset. Prediction of gene expression from relatively small transcriptome datasets can thus be used in conjunction with transcriptome-wide association studies to stratify risk of disease complications.

genetics↗