Details

Autor(en) / Beteiligte

• Li, Leyuan
• Figeys, Daniel

Titel

Proteomics and Metaproteomics Add Functional, Taxonomic and Biomass Dimensions to Modeling the Ecosystem at the Mucosal-luminal Interface

Ist Teil von

• Molecular & cellular proteomics, 2020-09, Vol.19 (9), p.1409-1417

Ort / Verlag

United States: Elsevier Inc

Erscheinungsjahr

2020

Quelle

MEDLINE

Beschreibungen/Notizen

• Proteomics and metaproteomics are important tools for studying the spatiotemporal heterogeneous ecosystem in our gut. We review strategies and their applications to gut ecology studies, such as building a dynamical model of the MLI. [Display omitted] Highlights •The gut mucosal-luminal interface is a spatiotemporal heterogeneous ecosystem.•Proteomics and metaproteomics are tools to study the host and microbiome functionality.•Insights into functional diversity, biomass, and matter flow can be obtained.•Such data can be complementary inputs for building ecology models of the microbiome. Recent efforts in gut microbiome studies have highlighted the importance of explicitly describing the ecological processes beyond correlative analysis. However, we are still at the early stage of understanding the organizational principles of the gut ecosystem, partially because of the limited information provided by currently used analytical tools in ecological modeling practices. Proteomics and metaproteomics can provide a number of insights for ecological studies, including biomass, matter and energy flow, and functional diversity. In this Mini Review, we discuss proteomics and metaproteomics-based experimental strategies that can contribute to studying the ecology, in particular at the mucosal-luminal interface (MLI) where the direct host-microbiome interaction happens. These strategies include isolation protocols for different MLI components, enrichment methods to obtain designated array of proteins, probing for specific pathways, and isotopic labeling for tracking nutrient flow. Integration of these technologies can generate spatiotemporal and site-specific biological information that supports mathematical modeling of the ecosystem at the MLI.