Co-infecting pathogens and the microbiome from SARS-CoV-2 positive and negative samples

By Neha MathurDec 6 2022Reviewed by Danielle Ellis, B.Sc. In a recent study published in PLOS ONE, researchers evaluated co-infections in severe acute respiratory syndrome coronavirus 2 -infected patients. Additionally, they explored the differences in microbial profiles of SARS-CoV-2-positive and SARS-CoV-2-negative samples.

These studies primarily used real-time reverse transcriptase-polymerase chain reaction assays to detect co-infecting pathogens. Given the limited sensitivity of PCR assays, detection of co-infections remained limited to known or suspected targets. The team used version seven of the Lawrence Livermore Microbial Detection Array , a broad-spectrum microbial detection platform, for analyzing the collected samples. This platform quickly processed up to 96 clinical samples simultaneously. It could detect more than 12,000 microbial species through its deoxyribonucleic acid probes, including 4219 viral, 5367 bacterial, and 265 fungal species. Further, it could detect 117 protozoa and 293 archaebacteria.

Related StoriesAlso, it detected Haemophilus influenzae in eight of 101 SARS-CoV-2 positive samples. A meta-analysis by Lansbury et al. found the most common bacterial co-infections were due to Pseudomonas aeruginosa, Mycoplasma pneumonia, and Haemophilus influenzae. Additionally, they identified respiratory syncytial virus and influenza A as the most frequent co-infecting viruses. They reviewed 30 studies covering 3,834 patients published between January and April 2020.

Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes, and Fusobacteria comprised 98% of the sequences detected by 16S rRNA sequence analysis. The 16S rRNA analysis for amplicon sequence variants showed that the nasal microbial profile was very individualized. While ASVs within the Moraxellaceae and Corynebacteriaceae had a higher prevalence in the SARS-CoV-2 positive samples, those within the Pasturellaceae and Streptococcaceae had a lower abundance.

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