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Metaproteomics as a tool for studying the protein landscape of human-gut bacterial species
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Abstract
Host-microbiome interactions and the microbial community have broad impact in human health and diseases. Most microbiome based studies are performed at the genome level based on next-generation sequencing techniques, but metaproteomics is emerging as a powerful technique to study microbiome functional activity by characterizing the complex and dynamic composition of microbial proteins. We conducted a large-scale survey of human gut microbiome metaproteomic data to identify generalist species that are ubiquitously expressed across all samples and specialists that are highly expressed in a small subset of samples associated with a certain phenotype. We were able to utilize the metaproteomic mass spectrometry data to reveal the protein landscapes of these species, which enables the characterization of the expression levels of proteins of different functions and underlying regulatory mechanisms, such as operons. Finally, we were able to recover a large number of open reading frames (ORFs) with spectral support, which were missed by
de novo
protein-coding gene predictors. We showed that a majority of the rescued ORFs overlapped with
de novo
predicted proteincoding genes, but on opposite strands or on different frames. Together, these demonstrate applications of metaproteomics for the characterization of important gut bacterial species. Results are available for public access at
https://omics.informatics.indiana.edu/GutBac
.
Author summary
Many reference genomes for studying human gut microbiome are available, but knowledge about how microbial organisms work is limited. Identification of proteins at individual species or community level provides direct insight into the functionality of microbial organisms. By analyzing more than a thousand metaproteomics datasets, we examined protein landscapes of more than two thousands of microbial species that may be important to human health and diseases. This work demonstrated new applications of metaproteomic datasets for studying individual genomes. We made the analysis results available through the GutBac website, which we believe will become a resource for studying microbial species important for human health and diseases.
Title: Metaproteomics as a tool for studying the protein landscape of human-gut bacterial species
Description:
Abstract
Host-microbiome interactions and the microbial community have broad impact in human health and diseases.
Most microbiome based studies are performed at the genome level based on next-generation sequencing techniques, but metaproteomics is emerging as a powerful technique to study microbiome functional activity by characterizing the complex and dynamic composition of microbial proteins.
We conducted a large-scale survey of human gut microbiome metaproteomic data to identify generalist species that are ubiquitously expressed across all samples and specialists that are highly expressed in a small subset of samples associated with a certain phenotype.
We were able to utilize the metaproteomic mass spectrometry data to reveal the protein landscapes of these species, which enables the characterization of the expression levels of proteins of different functions and underlying regulatory mechanisms, such as operons.
Finally, we were able to recover a large number of open reading frames (ORFs) with spectral support, which were missed by
de novo
protein-coding gene predictors.
We showed that a majority of the rescued ORFs overlapped with
de novo
predicted proteincoding genes, but on opposite strands or on different frames.
Together, these demonstrate applications of metaproteomics for the characterization of important gut bacterial species.
Results are available for public access at
https://omics.
informatics.
indiana.
edu/GutBac
.
Author summary
Many reference genomes for studying human gut microbiome are available, but knowledge about how microbial organisms work is limited.
Identification of proteins at individual species or community level provides direct insight into the functionality of microbial organisms.
By analyzing more than a thousand metaproteomics datasets, we examined protein landscapes of more than two thousands of microbial species that may be important to human health and diseases.
This work demonstrated new applications of metaproteomic datasets for studying individual genomes.
We made the analysis results available through the GutBac website, which we believe will become a resource for studying microbial species important for human health and diseases.
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