Function is What Counts: How Microbial Community Complexity Affects Species, Proteome and Pathway Coverage in Metaproteomics
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: Metaproteomics is an established method to obtain a comprehensive taxonomic and functional view of microbial communities. After more than a decade, we are now able to describe the promise, reality, and perspectives of metaproteomics and provide useful information about the choice of method, applications, and potential improvement strategies.: In this article, we will discuss current challenges of species and proteome coverage, and also highlight functional aspects of metaproteomics analysis of microbial communities with different levels of complexity. To do this, we re-analyzed data from microbial communities with low to high complexity (8, 72, 200 and >300 species). High species diversity leads to a reduced number of protein group identifications in a complex community, and thus the number of species resolved is underestimated. Ultimately, low abundance species remain undiscovered in complex communities. However, we observed that the main functional categories were better represented within complex microbiomes when compared to species coverage.: Our findings showed that even with low species coverage, metaproteomics has the potential to reveal habitat-specific functional features. Finally, we exploit this information to highlight future research avenues that are urgently needed to enhance our understanding of taxonomic composition and functions of complex microbiomes.
[Microbial metaproteomics--From sample processing to data acquisition and analysis].
Wu E, Qiao L Se Pu. 2024; 42(7):658-668.
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The Landscape and Perspectives of the Human Gut Metaproteomics.
Sun Z, Ning Z, Figeys D Mol Cell Proteomics. 2024; 23(5):100763.
PMID: 38608842 PMC: 11098955. DOI: 10.1016/j.mcpro.2024.100763.
Castaneda-Monsalve V, Frohlich L, Haange S, Nabhan Homsi M, Rolle-Kampczyk U, Fu Q Front Microbiol. 2024; 15:1349367.
PMID: 38444810 PMC: 10912515. DOI: 10.3389/fmicb.2024.1349367.
Metaproteomics to understand how microbiota function: The crystal ball predicts a promising future.
Armengaud J Environ Microbiol. 2022; 25(1):115-125.
PMID: 36209500 PMC: 10091800. DOI: 10.1111/1462-2920.16238.
Ecosystem-specific microbiota and microbiome databases in the era of big data.
Lobanov V, Gobet A, Joyce A Environ Microbiome. 2022; 17(1):37.
PMID: 35842686 PMC: 9287977. DOI: 10.1186/s40793-022-00433-1.