Medical Research Council of South Africa.

Influenza pandemics require that a virus containing a hemagglutinin (HA) surface antigen previously unseen by a majority of the population becomes airborne-transmissible between humans. Although the HA protein is central to the emergence of a pandemic influenza virus, its required molecular properties for sustained transmission between humans are poorly defined. During virus entry, the HA protein binds receptors and is triggered by low pH in the endosome to cause membrane fusion; during egress, HA contributes to virus assembly and morphology. In 2009, a swine influenza virus (pH1N1) jumped to humans and spread globally. Here we link the pandemic potential of pH1N1 to its HA acid stability, or the pH at which this one-time-use nanomachine is either triggered to cause fusion or becomes inactivated in the absence of a target membrane. In surveillance isolates, our data show HA activation pH values decreased during the evolution of H1N1 from precursors in swine (pH 5.5–6.0), to early 2009 human cases (pH 5.5), and then to later human isolates (pH 5.2–5.4). A loss-of-function pH1N1 virus with a destabilizing HA1-Y17H mutation (pH 6.0) was less pathogenic in mice and ferrets, less transmissible by contact, and no longer airborne-transmissible. A ferret-adapted revertant (HA1-H17Y/HA2-R106K) regained airborne transmissibility by stabilizing HA to an activation pH of 5.3, similar to that of human-adapted isolates from late 2009–2014. Overall, these studies reveal that a stable HA (activation pH ≤ 5.5) is necessary for pH1N1 influenza virus pathogenicity and airborne transmissibility in ferrets and is associated with pandemic potential in humans.

Metagenomic next-generation sequencing (mNGS) offers an agnostic approach for emerging pathogen detection directly from clinical specimens. In contrast to targeted methods, mNGS also provides valuable information on the composition of the microbiome and might uncover coinfections that may associate with disease progression and impact prognosis. To evaluate the use of mNGS for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and/or other infecting pathogens, we applied direct Oxford Nanopore long-read third-generation metatranscriptomic and metagenomic sequencing. Nasopharyngeal (NP) swab specimens from 50 patients under investigation for CoV disease 2019 (COVID-19) were sequenced, and the data were analyzed by the CosmosID bioinformatics platform. Further, we characterized coinfections and the microbiome associated with a four-point severity index. SARS-CoV-2 was identified in 77.5% (31/40) of samples positive by RT-PCR, correlating with lower cycle threshold (Ct) values and fewer days from symptom onset. At the time of sampling, possible bacterial or viral coinfections were detected in 12.5% of SARS-CoV-2-positive specimens. A decrease in microbial diversity was observed among COVID-19-confirmed patients (Shannon diversity index, P = 0.0082; Chao richness estimate, P = 0.0097; Simpson diversity index, P = 0.018), and differences in microbial communities were linked to disease severity (P = 0.022). Furthermore, statistically significant shifts in the microbiome were identified among SARS-CoV-2-positive and -negative patients, in the latter of whom a higher abundance of Propionibacteriaceae (P = 0.028) and a reduction in the abundance of Corynebacterium accolens (P = 0.025) were observed. Our study corroborates the growing evidence that increased SARS-CoV-2 RNA detection from NP swabs is associated with the early stages rather than the severity of COVID-19. Further, we demonstrate that SARS-CoV-2 causes a significant change in the respiratory microbiome. This work illustrates the utility of mNGS for the detection of SARS-CoV-2, for diagnosing coinfections without viral target enrichment or amplification, and for the analysis of the respiratory microbiome. IMPORTANCE SARS-CoV-2 has presented a rapidly accelerating global public health crisis. The ability to detect and analyze viral RNA from minimally invasive patient specimens is critical to the public health response. Metagenomic next-generation sequencing (mNGS) offers an opportunity to detect SARS-CoV-2 from nasopharyngeal (NP) swabs. This approach also provides information on the composition of the respiratory microbiome and its relationship to coinfections or the presence of other organisms that may impact SARS-CoV-2 disease progression and prognosis. Here, using direct Oxford Nanopore long-read third-generation metatranscriptomic and metagenomic sequencing of NP swab specimens from 50 patients under investigation for COVID-19, we detected SARS-CoV-2 sequences by applying the CosmosID bioinformatics platform. Further, we characterized coinfections and detected a decrease in the diversity of the microbiomes in these patients. Statistically significant shifts in the microbiome were identified among COVID-19-positive and -negative patients, in the latter of whom a higher abundance of Propionibacteriaceae and a reduction in the abundance of Corynebacterium accolens were observed. Our study also corroborates the growing evidence that increased SARS-CoV-2 RNA detection from NP swabs is associated with the early stages of disease rather than with severity of disease. This work illustrates the utility of mNGS for the detection and analysis of SARS-CoV-2 from NP swabs without viral target enrichment or amplification and for the analysis of the respiratory microbiome.

The dynamics of SARS-CoV-2 replication and shedding in humans remain poorly understood. We captured the dynamics of infectious virus and viral RNA shedding during acute infection through daily longitudinal sampling of 60 individuals for up to 14 days. By fitting mechanistic models, we directly estimated viral expansion and clearance rates, and overall infectiousness for each individual. Significant person-to-person variation in infectious virus shedding suggests that individual-level heterogeneity in viral dynamics contributes to superspreading. Viral genome loads often peaked days earlier in saliva than in nasal swabs, indicating strong tissue compartmentalization and suggesting that saliva may serve as a superior sampling site for early detection of infection. Viral loads and clearance kinetics of Alpha (B.1.1.7) and previously circulating non-variant of concern viruses were mostly indistinguishable, indicating that the enhanced transmissibility of this variant cannot be simply explained by higher viral loads or delayed clearance. These results provide a high-resolution portrait of SARS-CoV-2 infection dynamics and implicate individual-level heterogeneity in infectiousness in superspreading.