A cross-sectional study on the nasopharyngeal microbiota of individuals with SARS-CoV-2 infection across three COVID-19 waves in India

BackgroundMultiple variants of the SARS-CoV-2 virus have plagued the world through successive waves of infection over the past three years. Independent research groups across geographies have shown that the microbiome composition in COVID-19 positive patients (CP) differs from that of COVID-19 negative individuals (CN). However, these observations were based on limited-sized sample-sets collected primarily from the early days of the pandemic. Here, we study the nasopharyngeal microbiota in COVID-19 patients, wherein the samples have been collected across the three COVID-19 waves witnessed in India, which were driven by different variants of concern.MethodsThe nasopharyngeal swabs were collected from 589 subjects providing samples for diagnostics purposes at the Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, India and subjected to 16s rRNA gene amplicon - based sequencing.FindingsWe found variations in the microbiota of symptomatic vs. asymptomatic COVID-19 patients. CP showed a marked shift in the microbial diversity and composition compared to CN, in a wave-dependent manner. Rickettsiaceae was the only family that was noted to be consistently depleted in CP samples across the waves. The genera Staphylococcus, Anhydrobacter, Thermus, and Aerococcus were observed to be highly abundant in the symptomatic CP patients when compared to the asymptomatic group. In general, we observed a decrease in the burden of opportunistic pathogens in the host microbiota during the later waves of infection.InterpretationTo our knowledge, this is the first analytical cross-sectional study of this scale, which was designed to understand the relation between the evolving nature of the virus and the changes in the human nasopharyngeal microbiota. Although no clear signatures were observed, this study shall pave the way for a better understanding of the disease pathophysiology and help gather preliminary evidence on whether interventions to the host microbiota can help in better protection or faster recovery

Sensory Protein Database

The resource provides the list of sensory proteins that have been used for distinguishing between metagenome samples from health and diseased individuals in the following study - "Sensing Host Health: Insights from Sensory Protein Signature of the Metagenome

Discriminating functional pathways (KEGG) between HC and FK samples.

<p>Discriminating functional pathways (KEGG) between HC and FK samples.</p

Bacteria-Fungi interaction network for the HC samples (based on correlation of genera-level abundance).

<p>The node sizes in the network correspond to their degree. The bacterial genera have been highlighted as red nodes, whereas the fungal genera have been highlighted as green nodes. The positive and negative correlations / interactions have been indicated with green edges and red edges respectively.</p

Bacteria-Fungi interaction network for the FK samples (based on correlation of genera-level abundance).

<p>The node sizes in the network correspond to their degree. The bacterial genera have been highlighted as red nodes, whereas the fungal genera have been highlighted as green nodes. The positive and negative correlations / interactions have been indicated with green edges and red edges respectively.</p

Taxonomic abundance of different bacterial phyla, across HC and FK samples.

<p>Only those phyla with > 1% mean abundance are depicted in the plot.</p

Box plots indicating relative abundance of different bacterial genera which exhibited significant (BH corrected P < 0.05) differential abundance across HC and FK samples.

<p>Differentially abundant genera having a median abundance > 0.1% in at least one group of samples has been depicted. Median abundances and interquartile ranges have been indicated in the plots.</p

Bacterial OTUs exhibiting significant (BH corrected P < 0.05) differential abundance across HC and FK samples.

<p>Bacterial OTUs exhibiting significant (BH corrected P < 0.05) differential abundance across HC and FK samples.</p

Alterations in the gut bacterial microbiome in fungal Keratitis patients

<div><p>Dysbiosis in the gut microbiome has been implicated in several diseases including auto-immune diseases, inflammatory diseases, cancers and mental disorders. Keratitis is an inflammatory disease of the eye significantly contributing to corneal blindness in the developing world. It would be worthwhile to investigate the possibility of dysbiosis in the gut microbiome being associated with Keratitis. Here, we have analyzed fungal and bacterial populations in stool samples through high-throughput sequencing of the ITS2 region for fungi and V3-V4 region of 16S rRNA gene for bacteria in healthy controls (HC, n = 31) and patients with fungal keratitis (FK, n = 32). <i>Candida albicans</i> (2 OTUs), <i>Aspergillus</i> (1 OTU) and 3 other denovo-OTUs were enriched in FK samples and an unclassified denovo-OTU was enriched in HC samples. However, the overall abundances of these ‘discriminatory’ OTUs were very low (< 0.001%) and not indicative of significant dysbiosis in the fungal community inhabiting the gut of FK patients. In contrast, the gut bacterial richness and diversity in FK patients was significantly decreased when compared to HC. 52 OTUs were significantly enriched in HC samples whereas only 5 OTUs in FK. The OTUs prominently enriched in HC were identified as <i>Faecalibacterium prausnitzii</i>, <i>Bifidobacterium adolescentis</i>, <i>Lachnospira</i>, <i>Mitsuokella multacida</i>, <i>Bacteroides plebeius</i>, <i>Megasphaera</i> and Lachnospiraceae. In FK samples, 5 OTUs affiliated to <i>Bacteroides fragilis</i>, <i>Dorea</i>, <i>Treponema</i>, Fusobacteriaceae, and Acidimicrobiales were significantly higher in abundance. The functional implications are that <i>Faecalibacterium prausnitzii</i>, an anti-inflammatory bacterium and <i>Megasphaera</i>, <i>Mitsuokella multacida</i> and <i>Lachnospira</i> are butyrate producers, which were enriched in HC patients, whereas <i>Treponema</i> and <i>Bacteroides fragilis</i>, which are pathogenic were abundant in FK patients, playing a potential pro-inflammatory role. Heatmap, PCoA plots and functional profiles further confirm the distinct patterns of gut bacterial composition in FK and HC samples. Our study demonstrates dysbiosis in the gut bacterial microbiomes of FK patients compared to HC. Further, based on inferred functions, it appears that dysbiosis in the gut of FK subjects is strongly associated with the disease phenotype with decrease in abundance of beneficial bacteria and increase in abundance of pro-inflammatory and pathogenic bacteria.</p></div