Thuy-Boun PS, Mehta S, Gruening B, McGowan T, Nguyen A, Rajczewski A, Johnson JE, Griffin TJ, Wolan DW, Jagtap PD. Metaproteomics Analysis of SARS-CoV-2-Infected Patient Samples Reveals Presence of Potential Coinfecting Microorganisms.
J Proteome Res 2021;
20:1451-1454. [PMID:
33393790 PMCID:
PMC7805602 DOI:
10.1021/acs.jproteome.0c00822]
[Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Indexed: 01/06/2023]
Abstract
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.
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