Metatranscriptomics to characterize respiratory virome, microbiome, and host response directly from clinical samples.

We developed a metatranscriptomics method that can simultaneously capture the respiratory virome, microbiome, and host response directly from low biomass samples. Using nasal swab samples, we capture RNA virome with sufficient sequencing depth required to assemble complete genomes. We find a surprisingly high frequency of respiratory syncytial virus (RSV) and coronavirus (CoV) in healthy children, and a high frequency of RSV-A and RSV-B co-detections in children with symptomatic RSV. In addition, we have identified commensal and pathogenic bacteria and fungi at the species level. Functional analysis revealed that H. influenzae was highly active in symptomatic RSV subjects. The host nasal transcriptome reveled upregulation of the innate immune system, anti-viral response and inflammasome pathway, and downregulation of fatty acid pathways in children with symptomatic RSV. Overall, we demonstrate that our method is broadly applicable to infer the transcriptome landscape of an infected system, surveil respiratory infections, and to sequence RNA viruses directly from clinical samples.

Upper respiratory tract microbiota dynamics following COVID-19 in adults.

To date, little is known about the effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for the coronavirus disease 2019 (COVID-19) pandemic, on the upper respiratory tract (URT) microbiota over time. To fill this knowledge gap, we used 16S ribosomal RNA gene sequencing to characterize the URT microbiota in 48 adults, including (1) 24 participants with mild-to-moderate COVID-19 who had serial mid-turbinate swabs collected up to 21 days after enrolment and (2) 24 asymptomatic, uninfected controls who had mid-turbinate swabs collected at enrolment only. To compare the URT microbiota between groups in a comprehensive manner, different types of statistical analyses that are frequently employed in microbial ecology were used, including ⍺-diversity, ß-diversity and differential abundance analyses. Final statistical models included age, sex and the presence of at least one comorbidity as covariates. The median age of all participants was 34.00 (interquartile range=28.75-46.50) years. In comparison to samples from controls, those from participants with COVID-19 had a lower observed species index at day 21 (linear regression coefficient=-13.30; 95 % CI=-21.72 to -4.88; q=0.02). In addition, the Jaccard index was significantly different between samples from participants with COVID-19 and those from controls at all study time points (PERMANOVA q<0.05 for all comparisons). The abundance of three amplicon sequence variants (ASVs) (one Corynebacterium ASV, Frederiksenia canicola, and one Lactobacillus ASV) were decreased in samples from participants with COVID-19 at all seven study time points, whereas the abundance of one ASV (from the family Neisseriaceae) was increased in samples from participants with COVID-19 at five (71.43 %) of the seven study time points. Our results suggest that mild-to-moderate COVID-19 can lead to alterations of the URT microbiota that persist for several weeks after the initial infection.

Mucosal Gene Expression in Response to SARS-CoV-2 Is Associated with Viral Load.

Little is known about the relationships between symptomatic early severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load and upper airway mucosal gene expression and immune response. To examine the association of symptomatic SARS-CoV-2 early viral load with upper airway mucosal gene expression, we profiled the host mucosal transcriptome from nasopharyngeal swab samples from 68 adults with symptomatic, mild-to-moderate coronavirus disease 19 (COVID-19). We measured SARS-CoV-2 viral load using reverse transcription-quantitative PCR (RT-qPCR). We then examined the association of SARS-CoV-2 viral load with upper airway mucosal immune response. We detected SARS-CoV-2 in all samples and recovered >80% of the genome from 95% of the samples from symptomatic COVID-19 adults. The respiratory virome was dominated by SARS-CoV-2, with limited codetection of other respiratory viruses, with the human Rhinovirus C being identified in 4 (6%) samples. This limited codetection of other respiratory viral pathogens may be due to the implementation of public health measures, like social distancing and masking practices. We observed a significant positive correlation between SARS-CoV-2 viral load and interferon signaling (OAS2, OAS3, IFIT1, UPS18, ISG15, ISG20, IFITM1, and OASL), chemokine signaling (CXCL10 and CXCL11), and adaptive immune system (IFITM1, CD300E, and SIGLEC1) genes in symptomatic, mild-to-moderate COVID-19 adults, when adjusting for age, sex, and race. Interestingly, the expression levels of most of these genes plateaued at a cycle threshold (CT) value of ~25. Overall, our data show that the early nasal mucosal immune response to SARS-CoV-2 infection is viral load dependent, potentially modifying COVID-19 outcomes. IMPORTANCE Several prior studies have shown that SARS-CoV-2 viral load can predict the likelihood of disease spread and severity. A higher detectable SARS-CoV-2 plasma viral load was associated with worse respiratory disease severity. However, the relationship between SARS-CoV-2 viral load, airway mucosal gene expression, and immune response remains elusive. We profiled the nasal mucosal transcriptome from nasal samples collected from adults infected with SARS-CoV-2 during spring 2020 with mild-to-moderate symptoms using a comprehensive metatranscriptomics method. We observed a positive correlation between SARS-CoV-2 viral load, interferon signaling, chemokine signaling, and adaptive immune system in adults with COVID-19. Our data suggest that early nasal mucosal immune response to SARS-CoV-2 infection was viral load dependent and may modify COVID-19 outcomes.

Ligation-based assay for variant typing without sequencing: Application to SARS-CoV-2 variants of concern.

BACKGROUND: COVID-19 prevalence has remained high throughout the pandemic with intermittent surges, due largely to the emergence of genetic variants, demonstrating the need for more accessible sequencing technologies for strain typing. METHODS: A ligation-based typing assay was developed to detect known variants of severe acute respiratory syndrome virus 2 (SARS-CoV-2) by identifying the presence of characteristic single-nucleotide polymorphisms (SNPs). General principles for extending the strategy to new variants and alternate diseases with SNPs of interest are described. Of note, this strategy leverages commercially available reagents for assay preparation, as well as standard real-time polymerase chain reaction (PCR) instrumentation for assay performance. RESULTS: The assay demonstrated a combined sensitivity and specificity of 96.6% and 99.5%, respectively, for the classification of 88 clinical samples of the Alpha, Delta, and Omicron variants relative to the gold standard of viral genome sequencing. It achieved an average limit of detection of 7.4 × 104 genome copies/mL in contrived nasopharyngeal samples. The ligation-based strategy performed robustly in the presence of additional polymorphisms in the targeted regions of interest as shown by the sequence alignment of clinical samples. CONCLUSIONS: The assay demonstrates the potential for robust variant typing with performance comparable with next-generation sequencing without the need for the time delays and resources required for sequencing. The reduced resource dependency and generalizability could expand access to variant classification information for pandemic surveillance.

COVID-19 severity from Omicron and Delta SARS-CoV-2 variants.

The Omicron variant of SARS-CoV-2 achieved worldwide dominance in late 2021. Early work suggests that infections caused by the Omicron variant may be less severe than those caused by the Delta variant. We sought to compare clinical outcomes of infections caused by these two strains, confirmed by whole genome sequencing, over a short period of time, from respiratory samples collected from SARS-CoV-2 positive patients at a large medical center. We found that infections caused by the Omicron variant caused significantly less morbidity, including admission to the hospital and requirement for oxygen supplementation, and significantly less mortality than those caused by the Delta variant.

Severe COVID-19 Is Associated With an Altered Upper Respiratory Tract Microbiome.

Background: The upper respiratory tract (URT) is the portal of entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and SARS-CoV-2 likely interacts with the URT microbiome. However, understanding of the associations between the URT microbiome and the severity of coronavirus disease 2019 (COVID-19) is still limited. Objective: Our primary objective was to identify URT microbiome signature/s that consistently changed over a spectrum of COVID-19 severity. Methods: Using data from 103 adult participants from two cities in the United States, we compared the bacterial load and the URT microbiome between five groups: 20 asymptomatic SARS-CoV-2-negative participants, 27 participants with mild COVID-19, 28 participants with moderate COVID-19, 15 hospitalized patients with severe COVID-19, and 13 hospitalized patients in the ICU with very severe COVID-19. Results: URT bacterial load, bacterial richness, and within-group microbiome composition dissimilarity consistently increased as COVID-19 severity increased, while the relative abundance of an amplicon sequence variant (ASV), Corynebacterium_unclassified.ASV0002, consistently decreased as COVID-19 severity increased. Conclusions: We observed that the URT microbiome composition significantly changed as COVID-19 severity increased. The URT microbiome could potentially predict which patients may be more likely to progress to severe disease or be modified to decrease severity. However, further research in additional longitudinal cohorts is needed to better understand how the microbiome affects COVID-19 severity.

SARS-CoV-2 infection and viral load are associated with the upper respiratory tract microbiome.

BACKGROUND: Little is known about the relationships between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the respiratory virus responsible for the ongoing coronavirus disease 2019 (COVID-19) pandemic, and the upper respiratory tract (URT) microbiome. OBJECTIVE: We sought to compare the URT microbiome between SARS-CoV-2-infected and -uninfected adults and to examine the association of SARS-CoV-2 viral load with the URT microbiome during COVID-19. METHODS: We characterized the URT microbiome using 16S ribosomal RNA sequencing in 59 adults (38 with confirmed, symptomatic, mild to moderate COVID-19 and 21 asymptomatic, uninfected controls). In those with COVID-19, we measured SARS-CoV-2 viral load using quantitative reverse transcription PCR. We then examined the association of SARS-CoV-2 infection status and its viral load with the ⍺-diversity, ß-diversity, and abundance of bacterial taxa of the URT microbiome. Our main models were all adjusted for age and sex. RESULTS: The observed species index was significantly higher in SARS-CoV-2-infected than in -uninfected adults (ß linear regression coefficient = 7.53; 95% CI, 0.17-14.89; P = .045). In differential abundance testing, 9 amplicon sequence variants were significantly different in both of our comparisons, with Peptoniphilus lacrimalis, Campylobacter hominis, Prevotella 9 copri, and an Anaerococcus unclassified amplicon sequence variant being more abundant in those with SARS-CoV-2 infection and in those with high viral load during COVID-19, whereas Corynebacterium unclassified, Staphylococcus haemolyticus, Prevotella disiens, and 2 Corynebacterium_1 unclassified amplicon sequence variants were more abundant in those without SARS-CoV-2 infection and in those with low viral load during COVID-19. CONCLUSIONS: Our findings suggest complex associations between SARS-CoV-2 and the URT microbiome in adults. Future studies are needed to examine how these viral-bacterial interactions can impact the clinical progression, severity, and recovery of COVID-19.