Metaproteomic analysis of nasopharyngeal swab samples to identify microbial peptides and potential co-infection status in COVID-19 patients

Abstract

AbstractRespiratory infections disrupt the microbiota in the upper respiratory tract (URT), putting patients at a risk for subsequent infections. During the pandemic, cases of COVID-19 were aggravated by secondary infections because of impaired immunity and medical interventions, which was clearly evident in the second wave of COVID-19 in India. The potential dangers and clinical difficulties of bacterial and fungal secondary infections in COVID-19 patients necessitate microbial exploration of the URT. In this regard, mass spectrometry (MS)-based proteome data of nasopharyngeal swab samples from COVID-19 patients was used to investigate the metaproteome. The MS datasets were searched against a comprehensive protein sequence database of common URT pathogens using multiple search platforms (MaxQuant, MSFragger, and Search GUI/PeptideShaker). The detected microbial peptides were verified using PepQuery, which analyses peptide-spectrum pairs to give statistical output for determining confident microbial peptides. Finally, a protein sequence database was generated using the list of verified microbial peptides for identification and quantitation of microbial peptides and proteins, respectively. The taxonomic analysis of the detected peptides revealed several opportunistic pathogens likeStreptococcus pneumoniae, Rhizopus microsporus, Clavispora lusitaniae, andSyncephalastrum racemosumamong others. Using parallel reaction monitoring (PRM), we validated a few identified microbial peptides in clinical samples. The analysis also revealed proteins belonging to species likePseudomonas fluorescens, Enterobacter, andClostridiumto be up-regulated in severe COVID-19 samples. Thus, MS can serve as a powerful tool for untargeted detection of a wide range of microorganisms. Metaproteomic analysis in COVID-19 patients for early identification and characterisation of co-infecting microorganisms can significantly impact the diagnosis and treatment of patients.