Metaproteomics Analysis of SARS-CoV-2-Infected Patient Samples Reveals Presence of Potential Coinfecting Microorganisms

Peter S. Thuy-Boun, Subina Mehta, Bjoern Gruening, Thomas McGowan, An Nguyen, Andrew T. Rajczewski, James E Johnson, Timothy J. Griffin, Dennis W. Wolan, Pratik D. Jagtap

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


In this Letter, we reanalyze published mass spectrometry data sets of clinical samples with a focus on determining the coinfection status of individuals infected with SARS-CoV-2 coronavirus. We demonstrate the use of ComPIL 2.0 software along with a metaproteomics workflow within the Galaxy platform to detect cohabitating potential pathogens in COVID-19 patients using mass spectrometry-based analysis. From a sample collected from gargling solutions, we detected Streptococcus pneumoniae (opportunistic and multidrug-resistant pathogen) and Lactobacillus rhamnosus (a probiotic component) along with SARS-Cov-2. We could also detect Pseudomonas sps. Bc-h from COVID-19 positive samples and Acinetobacter ursingii and Pseudomonas monteilii from COVID-19 negative samples collected from oro- and nasopharyngeal samples. We believe that the early detection and characterization of coinfections by using metaproteomics from COVID-19 patients will potentially impact the diagnosis and treatment of patients affected by SARS-CoV-2 infection.

Original languageEnglish (US)
Pages (from-to)1451-1454
Number of pages4
JournalJournal of Proteome Research
Issue number2
StatePublished - Feb 5 2021

Bibliographical note

Publisher Copyright:
© 2021 American Chemical Society.

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.


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