Evidence map›Paper›PMID 33795009›Full record

ArticleMicrobiome2021

Using high-abundance proteins as guides for fast and effective peptide/protein identification from human gut metaproteomic data.

Moses Stamboulian, Sujun Li, Yuzhen Ye

Abstract readVideo-Audio Media
In one paragraph

Article in Microbiome, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. GroEL-Proteotyping of Bacterial Communities Using Tandem Mass Spectrometry.International journal of molecular sciences · 2023
    Article
  9. Article
  10. Article
  11. Article
  12. Gut Microbiome Proteomics in Food Allergies.International journal of molecular sciences · 2023
    Review
  13. Article
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Moses StamboulianLuddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN, 47408, United States.
Sujun LiLuddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN, 47408, United States.
Yuzhen YeLuddy School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN, 47408, United States. yye@indiana.edu.ORCID 0000-0003-3707-3185

Funding

Graph-centric approaches to metatranscriptomic and metaproteomic data analysisR01AI108888 · NIAID · TRUSTEES OF INDIANA UNIVERSITY · PI YE, YUZHEN · 2014 to 2017
$1.4M
Subtractive assembly approaches for inferring disease-associated microbial genes and pathways from microbiome sequencing dataR01AI143254 · NIAID · TRUSTEES OF INDIANA UNIVERSITY · PI YE, YUZHEN · 2019 to 2023
$1.1M
NIAID NIH HHS R01 AI108888NIAID NIH HHS R01 AI143254
6 · The paper itself

Abstract

backgroundA few recent large efforts significantly expanded the collection of human-associated bacterial genomes, which now contains thousands of entities including reference complete/draft genomes and metagenome assembled genomes (MAGs). These genomes provide useful resource for studying the functionality of the human-associated microbiome and their relationship with human health and diseases. One application of these genomes is to provide a universal reference for database search in metaproteomic studies, when matched metagenomic/metatranscriptomic data are unavailable. However, a greater collection of reference genomes may not necessarily result in better peptide/protein identification because the increase of search space often leads to fewer spectrum-peptide matches, not to mention the drastic increase of computation time. Video Abstract

methodsHere, we present a new approach that uses two steps to optimize the use of the reference genomes and MAGs as the universal reference for human gut metaproteomic MS/MS data analysis. The first step is to use only the high-abundance proteins (HAPs) (i.e., ribosomal proteins and elongation factors) for metaproteomic MS/MS database search and, based on the identification results, to derive the taxonomic composition of the underlying microbial community. The second step is to expand the search database by including all proteins from identified abundant species. We call our approach HAPiID (HAPs guided metaproteomics IDentification).

resultsWe tested our approach using human gut metaproteomic datasets from a previous study and compared it to the state-of-the-art reference database search method MetaPro-IQ for metaproteomic identification in studying human gut microbiota. Our results show that our two-steps method not only performed significantly faster but also was able to identify more peptides. We further demonstrated the application of HAPiID to revealing protein profiles of individual human-associated bacterial species, one or a few species at a time, using metaproteomic data.

conclusionsThe HAP guided profiling approach presents a novel effective way for constructing target database for metaproteomic data analysis. The HAPiID pipeline built upon this approach provides a universal tool for analyzing human gut-associated metaproteomic data.

Indexed as

Gastrointestinal MicrobiomeHumansMetagenomicsPeptidesProteomicsTandem Mass SpectrometryPeptidesExpanded target databaseHigh-abundance protein (HAP)Human gut metaproteomicsSample profilingSpectra search

Identifiers

PMID33795009
PMCPMC8017886

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.