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Molecular & Cellular Proteomics

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Technological Innovation and Resources

A Meta-proteogenomic Approach to Peptide Identification Incorporating Assembly Uncertainty and Genomic Variation

View ORCID ProfileSujun Li, Haixu Tang and Yuzhen Ye  Correspondence email
Molecular & Cellular Proteomics August 9, 2019, First published on May 29, 2019, 18 (8 suppl 1) S183-S192; https://doi.org/10.1074/mcp.TIR118.001233
Sujun Li
School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN
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Haixu Tang
School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN
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Yuzhen Ye
School of Informatics, Computing and Engineering, Indiana University, Bloomington, IN
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  • For correspondence: yye@indiana.edu
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Graphical Abstract

Figure1
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Highlights

  • A novel meta-proteogenomic analysis pipeline integrating Graph2Pro and Var2Pep approaches.

  • Metaproteomic support of proteins with unknown functions.

  • Improved functional profiling of microbiomes using variant peptides.

Abstract

Matching metagenomic and/or metatranscriptomic data, currently often under-used, can be useful reference for metaproteomic tandem mass spectra (MS/MS) data analysis. Here we developed a software pipeline for identification of peptides and proteins from metaproteomic MS/MS data using proteins derived from matching metagenomic (and metatranscriptomic) data as the search database, based on two novel approaches Graph2Pro (published) and Var2Pep (new). Graph2Pro retains and uses uncertainties of metagenome assembly for reference-based MS/MS data analysis. Var2Pep considers the variations found in metagenomic/metatranscriptomic sequencing reads that are not retained in the assemblies (contigs). The new software pipeline provides one stop application of both tools, and it supports the use of metagenome assembly from commonly used assemblers including MegaHit and metaSPAdes. When tested on two collections of multi-omic microbiome data sets, our pipeline significantly improved the identification rate of the metaproteomic MS/MS spectra by about two folds, comparing to conventional contig- or read-based approaches (the Var2Pep alone identified 5.6% to 24.1% more unique peptides, depending on the data set). We also showed that identified variant peptides are important for functional profiling of microbiomes. All results suggested that it is important to take into consideration of the assembly uncertainties and genomic variants to facilitate metaproteomic MS/MS data interpretation.

  • Bioinformatics
  • Microbiome
  • Database design
  • Data evaluation
  • Bioinformatics software
  • assembly graph
  • genomic variation
  • metaproteomics

Footnotes

  • ↵* The NIH grants 1R01AI108888 and 1R01AI143254, and the Indiana University (IU) Precision Health Initiative (PHI).

  • ↵Embedded Image This article contains supplemental Figures.

  • Received November 21, 2018.
  • Revision received April 25, 2019.
  • © 2019 Li et al.

Published under exclusive license by The American Society for Biochemistry and Molecular Biology, Inc.

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A Meta-proteogenomic Approach to Peptide Identification Incorporating Assembly Uncertainty and Genomic Variation
Sujun Li, Haixu Tang, Yuzhen Ye
Molecular & Cellular Proteomics August 9, 2019, First published on May 29, 2019, 18 (8 suppl 1) S183-S192; DOI: 10.1074/mcp.TIR118.001233

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A Meta-proteogenomic Approach to Peptide Identification Incorporating Assembly Uncertainty and Genomic Variation
Sujun Li, Haixu Tang, Yuzhen Ye
Molecular & Cellular Proteomics August 9, 2019, First published on May 29, 2019, 18 (8 suppl 1) S183-S192; DOI: 10.1074/mcp.TIR118.001233
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Molecular & Cellular Proteomics: 18 (8 suppl 1)
Molecular & Cellular Proteomics
Vol. 18, Issue 8 suppl 1
9 Aug 2019
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