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.

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.

Molecular signature of postmortem lung tissue from COVID-19 patients suggests distinct trajectories driving mortality.

To elucidate the molecular mechanisms that manifest lung abnormalities during severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, we performed whole-transcriptome sequencing of lung autopsies from 31 patients with severe COVID-19 and ten uninfected controls. Using metatranscriptomics, we identified the existence of two distinct molecular signatures of lethal COVID-19. The dominant 'classical' signature (n=23) showed upregulation of the unfolded protein response, steroid biosynthesis and complement activation, supported by massive metabolic reprogramming leading to characteristic lung damage. The rarer signature (n=8) that potentially represents 'cytokine release syndrome' (CRS) showed upregulation of cytokines such as IL1 and CCL19, but absence of complement activation. We found that a majority of patients cleared SARS-CoV-2 infection, but they suffered from acute dysbiosis with characteristic enrichment of opportunistic pathogens such as Staphylococcus cohnii in 'classical' patients and Pasteurella multocida in CRS patients. Our results suggest two distinct models of lung pathology in severe COVID-19 patients, which can be identified through complement activation, presence of specific cytokines and characteristic microbiome. These findings can be used to design personalized therapy using in silico identified drug molecules or in mitigating specific secondary infections.

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.

Generation of a Novel SARS-CoV-2 Sub-genomic RNA Due to the R203K/G204R Variant in Nucleocapsid: Homologous Recombination has Potential to Change SARS-CoV-2 at Both Protein and RNA Level.

BACKGROUND: Genetic variations across the SARS-CoV-2 genome may influence transmissibility of the virus and the host's anti-viral immune response, in turn affecting the frequency of variants over time. In this study, we examined the adjacent amino acid polymorphisms in the nucleocapsid (R203K/G204R) of SARS-CoV-2 that arose on the background of the spike D614G change and describe how strains harboring these changes became dominant circulating strains globally. METHODS: Deep-sequencing data of SARS-CoV-2 from public databases and from clinical samples were analyzed to identify and map genetic variants and sub-genomic RNA transcripts across the genome. Results: Sequence analysis suggests that the 3 adjacent nucleotide changes that result in the K203/R204 variant have arisen by homologous recombination from the core sequence of the leader transcription-regulating sequence (TRS) rather than by stepwise mutation. The resulting sequence changes generate a novel sub-genomic RNA transcript for the C-terminal dimerization domain of nucleocapsid. Deep-sequencing data from 981 clinical samples confirmed the presence of the novel TRS-CS-dimerization domain RNA in individuals with the K203/R204 variant. Quantification of sub-genomic RNA indicates that viruses with the K203/R204 variant may also have increased expression of sub-genomic RNA from other open reading frames. CONCLUSIONS: The finding that homologous recombination from the TRS may have occurred since the introduction of SARS-CoV-2 in humans, resulting in both coding changes and novel sub-genomic RNA transcripts, suggests this as a mechanism for diversification and adaptation within its new host.