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

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...

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Autores principales:	Robert H. Mills, Yoshiki Vázquez-Baeza, Qiyun Zhu, Lingjing Jiang, James Gaffney, Greg Humphrey, Larry Smarr, Rob Knight, David J. Gonzalez
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2019
Materias:	colonic Crohn's disease inflammatory bowel disease metagenomics metaproteomics microbiome multiomics Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/b907b7cb9f5d4918b7ae946feea99386
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spelling	oai:doaj.org-article:b907b7cb9f5d4918b7ae946feea993862021-12-02T18:39:15ZEvaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease10.1128/mSystems.00337-182379-5077https://doaj.org/article/b907b7cb9f5d4918b7ae946feea993862019-02-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00337-18https://doaj.org/toc/2379-5077ABSTRACT 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 calprotectin. Despite concordant associations of genera, the specific genes correlated with these metrics were drastically different between metagenomic and metaproteomic data sets. This resulted in the generation of unique functional interpretations dependent on the data type, with metaproteome evidence for previously investigated mechanisms of dysbiosis. An example of one such mechanism was a connection between urease enzymes, amino acid metabolism, and the local inflammation state within the patient. This proof-of-concept approach prompts further investigation of the metaproteome and its relationship with the metagenome in biologically complex systems such as the microbiome. IMPORTANCE A majority of current microbiome research relies heavily on DNA analysis. However, as the field moves toward understanding the microbial functions related to healthy and disease states, it is critical to evaluate how changes in DNA relate to changes in proteins, which are functional units of the genome. This study tracked the abundance of genes and proteins as they fluctuated during various inflammatory states in a 4.5-year study of a patient with colonic Crohn’s disease. Our results indicate that despite a low level of correlation, taxonomic associations were consistent in the two data types. While there was overlap of the data types, several associations were uniquely discovered by analyzing the metaproteome component. This case study provides unique and important insights into the fundamental relationship between the genes and proteins of a single individual’s fecal microbiome associated with clinical consequences.Robert H. MillsYoshiki Vázquez-BaezaQiyun ZhuLingjing JiangJames GaffneyGreg HumphreyLarry SmarrRob KnightDavid J. GonzalezAmerican Society for Microbiologyarticlecolonic Crohn's diseaseinflammatory bowel diseasemetagenomicsmetaproteomicsmicrobiomemultiomicsMicrobiologyQR1-502ENmSystems, Vol 4, Iss 1 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	colonic Crohn's disease inflammatory bowel disease metagenomics metaproteomics microbiome multiomics Microbiology QR1-502
spellingShingle	colonic Crohn's disease inflammatory bowel disease metagenomics metaproteomics microbiome multiomics Microbiology QR1-502 Robert H. Mills Yoshiki Vázquez-Baeza Qiyun Zhu Lingjing Jiang James Gaffney Greg Humphrey Larry Smarr Rob Knight David J. Gonzalez Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease
description	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 calprotectin. Despite concordant associations of genera, the specific genes correlated with these metrics were drastically different between metagenomic and metaproteomic data sets. This resulted in the generation of unique functional interpretations dependent on the data type, with metaproteome evidence for previously investigated mechanisms of dysbiosis. An example of one such mechanism was a connection between urease enzymes, amino acid metabolism, and the local inflammation state within the patient. This proof-of-concept approach prompts further investigation of the metaproteome and its relationship with the metagenome in biologically complex systems such as the microbiome. IMPORTANCE A majority of current microbiome research relies heavily on DNA analysis. However, as the field moves toward understanding the microbial functions related to healthy and disease states, it is critical to evaluate how changes in DNA relate to changes in proteins, which are functional units of the genome. This study tracked the abundance of genes and proteins as they fluctuated during various inflammatory states in a 4.5-year study of a patient with colonic Crohn’s disease. Our results indicate that despite a low level of correlation, taxonomic associations were consistent in the two data types. While there was overlap of the data types, several associations were uniquely discovered by analyzing the metaproteome component. This case study provides unique and important insights into the fundamental relationship between the genes and proteins of a single individual’s fecal microbiome associated with clinical consequences.
format	article
author	Robert H. Mills Yoshiki Vázquez-Baeza Qiyun Zhu Lingjing Jiang James Gaffney Greg Humphrey Larry Smarr Rob Knight David J. Gonzalez
author_facet	Robert H. Mills Yoshiki Vázquez-Baeza Qiyun Zhu Lingjing Jiang James Gaffney Greg Humphrey Larry Smarr Rob Knight David J. Gonzalez
author_sort	Robert H. Mills
title	Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease
title_short	Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease
title_full	Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease
title_fullStr	Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease
title_full_unstemmed	Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease
title_sort	evaluating metagenomic prediction of the metaproteome in a 4.5-year study of a patient with crohn's disease
publisher	American Society for Microbiology
publishDate	2019
url	https://doaj.org/article/b907b7cb9f5d4918b7ae946feea99386
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Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease

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