Biochemical, Biophysical, and Immunological Characterization of Respiratory Secretions in Severe SARS-CoV-2 (COVID-19) Infections

Thick, viscous respiratory secretions are a major pathogenic feature of COVID-19 disease, but the composition and physical properties of these secretions are poorly understood. We characterized the composition and rheological properties (i.e. resistance to flow) of respiratory secretions collected from intubated COVID-19 patients. We find the percent solids and protein content are greatly elevated in COVID-19 compared to heathy control samples and closely resemble levels seen in cystic fibrosis, a genetic disease known for thick, tenacious respiratory secretions. DNA and hyaluronan (HA) are major components of respiratory secretions in COVID-19 and are likewise abundant in cadaveric lung tissues from these patients. COVID-19 secretions exhibit heterogeneous rheological behaviors with thicker samples showing increased sensitivity to DNase and hyaluronidase treatment. In histologic sections from these same patients, we observe increased accumulation of HA and the hyaladherin versican but reduced tumor necrosis factor-stimulated gene-6 (TSG6) staining, consistent with the inflammatory nature of these secretions. Finally, we observed diminished type I interferon and enhanced inflammatory cytokines in these secretions. Overall, our studies indicate that increases in HA and DNA in COVID-19 respiratory secretion samples correlate with enhanced inflammatory burden and suggest that DNA and HA may be viable therapeutic targets in COVID-19 infection.

Detection of bacterial co-infections and prediction of fatal outcomes in COVID-19 patients presenting to the emergency department using a 29 mRNA host response classifier.

ObjectiveClinicians in the emergency department (ED) face challenges in concurrently assessing patients with suspected COVID-19 infection, detecting bacterial co-infection, and determining illness severity since current practices require separate workflows. Here we explore the accuracy of the IMX-BVN-3/IMX-SEV-3 29 mRNA host response classifiers in simultaneously detecting SARS-CoV-2 infection, bacterial co-infections, and predicting clinical severity of COVID-19. Methods161 patients with PCR-confirmed COVID-19 (52.2% female, median age 50.0 years, 51% hospitalized, 5.6% deaths) were enrolled at the Stanford Hospital ED. RNA was extracted (2.5 mL whole blood in PAXgene Blood RNA) and 29 host mRNAs in response to the infection were quantified using Nanostring nCounter. ResultsThe IMX-BVN-3 classifier identified SARS-CoV-2 infection in 151 patients with a sensitivity of 93.8%. Six of 10 patients undetected by the classifier had positive COVID tests more than 9 days prior to enrolment and the remaining oscillated between positive and negative results in subsequent tests. The classifier also predicted that 6 (3.7%) patients had a bacterial co-infection. Clinical adjudication confirmed that 5/6 (83.3%) of the patients had bacterial infections, i.e. Clostridioides difficile colitis (n=1), urinary tract infection (n=1), and clinically diagnosed bacterial infections (n=3) for a specificity of 99.4%. 2/101 (2.8%) patients in the IMX-SEV-3 Low and 7/60 (11.7%) in the Moderate severity classifications died within thirty days of enrollment. ConclusionsIMX-BVN-3/IMX-SEV-3 classifiers accurately identified patients with COVID-19, bacterial co-infections, and predicted patients risk of death. A point-of-care version of these classifiers, under development, could improve ED patient management including more accurate treatment decisions and optimized resource utilization.

Association Between SARS-CoV-2 RNAemia and Post-Acute Sequelae of COVID-19.

Determinants of Post-Acute Sequelae of COVID-19 are not known. Here we show that 75% of patients with viral RNA in blood (RNAemia) at presentation were symptomatic in the post-acute phase. RNAemia at presentation successfully predicted PASC, independent of patient demographics, initial disease severity, and length of symptoms.

Intramuscular SARS-CoV-2 vaccines elicit varying degrees of plasma and salivary antibody responses as compared to natural infection

Vaccination induced antibody and T-cell immune responses are important for systemic protection from COVID-19. Because SARS-CoV-2 infects and is transmitted by oral-pharyngeal mucosa, we wished to test mucosal antibodies elicited by natural infection or intramuscular vaccine injection. In a non-randomized observational study, we measured antibodies against the SARS-CoV-2 RBD in plasma and saliva from convalescent or vaccinated individuals and tested their neutralizing potential using a replication competent rVSV-eGFP-SARS-CoV-2. We found IgG and IgA anti-RBD antibodies as well as neutralizing activity in convalescent plasma and saliva. Two doses of mRNA vaccination (BNT162b2 or mRNA-1273) induced high levels of IgG anti-RBD in saliva, a subset of whom also had IgA, and significant neutralizing activity. We detected anti-RBD IgG and IgA with significant neutralizing potential in the plasma of single dose Ad26.COV2.S vaccinated individuals, and we detected slight amounts of anti-RBD antibodies in matched saliva. The role of salivary antibodies in protection against SARS-CoV-2 infection is unknown and merits further investigation. This study was not designed to, nor did it study the full kinetics of the antibody response or protection from infection, nor did it address variants of SARS-CoV-2.

Multi-omic profiling reveals widespread dysregulation of innate immunity and hematopoiesis in COVID-19

Our understanding of protective vs. pathologic immune responses to SARS-CoV-2, the virus that causes Coronavirus disease 2019 (COVID-19), is limited by inadequate profiling of patients at the extremes of the disease severity spectrum. Here, we performed multi-omic single-cell immune profiling of 64 COVID-19 patients across the full range of disease severity, from outpatients with mild disease to fatal cases. Our transcriptomic, epigenomic, and proteomic analyses reveal widespread dysfunction of peripheral innate immunity in severe and fatal COVID-19, with the most profound disturbances including a prominent neutrophil hyperactivation signature and monocytes with anti-inflammatory features. We further demonstrate that emergency myelopoiesis is a prominent feature of fatal COVID-19. Collectively, our results reveal disease severity-associated immune phenotypes in COVID-19 and identify pathogenesis-associated pathways that are potential targets for therapeutic intervention. One Sentence SummarySingle-cell profiling demonstrates multifarious dysregulation of innate immune phenotype associated with COVID-19 severity.

SARS-CoV-2 RNAaemia predicts clinical deterioration and extrapulmonary complications from COVID-19.

BackgroundThe determinants of COVID-19 disease severity and extrapulmonary complications (EPCs) are poorly understood. We characterise the relationships between SARS-CoV-2 RNAaemia and disease severity, clinical deterioration, and specific EPCs. MethodsWe used quantitative (qPCR) and digital (dPCR) PCR to quantify SARS-CoV-2 RNA from nasopharyngeal swabs and plasma in 191 patients presenting to the Emergency Department (ED) with COVID-19. We recorded patient symptoms, laboratory markers, and clinical outcomes, with a focus on oxygen requirements over time. We collected longitudinal plasma samples from a subset of patients. We characterised the role of RNAaemia in predicting clinical severity and EPCs using elastic net regression. Findings23{middle dot}0% (44/191) of SARS-CoV-2 positive patients had viral RNA detected in plasma by dPCR, compared to 1{middle dot}4% (2/147) by qPCR. Most patients with serial measurements had undetectable RNAaemia 10 days after onset of symptoms, but took 16 days to reach maximum severity, and 33 days for symptoms to resolve. Initially RNAaemic patients were more likely to manifest severe disease (OR 6{middle dot}72 [95% CI, 2{middle dot}45 - 19{middle dot}79]), worsening of disease severity (OR 2{middle dot}43 [95% CI, 1{middle dot}07 - 5{middle dot}38]), and EPCs (OR 2{middle dot}81 [95% CI, 1{middle dot}26 - 6{middle dot}36]). RNA load correlated with maximum severity (r = 0{middle dot}47 [95% CI, 0{middle dot}20 - 0{middle dot}67]). InterpretationdPCR is more sensitive than qPCR for the detection of SARS-CoV-2 RNAaemia, which is a robust predictor of eventual COVID-19 severity and oxygen requirements, as well as EPCs. Since many COVID-19 therapies are initiated on the basis of oxygen requirements, RNAaemia on presentation might serve to direct early initiation of appropriate therapies for the patients most likely to deteriorate. FundingNIH/NIAID (Grants R01A153133, R01AI137272, and 3U19AI057229 - 17W1 COVID SUPP #2) and a donation from Eva Grove. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSThe varied clinical manifestations of COVID-19 have directed attention to the distribution of SARS-CoV-2 in the body. Although most concentrated and tested for in the nasopharynx, SARS-CoV-2 RNA has been found in blood, stool, and numerous tissues, raising questions about dissemination of viral RNA throughout the body, and the role of this process in disease severity and extrapulmonary complications. Recent studies have detected low levels of SARS-CoV-2 RNA in blood using either quantitative reverse transcriptase real-time PCR (qPCR) or droplet digital PCR (dPCR), and have associated RNAaemia with disease severity and biomarkers of dysregulated immune response. Added value of this studyWe quantified SARS-CoV-2 RNA in the nasopharynx and plasma of patients presenting to the Emergency Department with COVID-19, and found an array-based dPCR platform to be markedly more sensitive than qPCR for detection of SARS-CoV-2 RNA, with a simplified workflow well-suited to clinical adoption. We collected serial plasma samples during patients course of illness, and showed that SARS-CoV-2 RNAaemia peaks early, while clinical condition often continues to worsen. Our findings confirm the association between RNAaemia and disease severity, and additionally demonstrate a role for RNAaemia in predicting future deterioration and specific extrapulmonary complications. Implications of all the available evidenceVariation in SARS-CoV-2 RNAaemia may help explain disparities in disease severity and extrapulmonary complications from COVID-19. Testing for RNAaemia with dPCR early in the course of illness may help guide patient triage and management.

Hyaluronan is abundant in COVID-19 respiratory secretions

Thick, viscous respiratory secretions are a major pathogenic feature of COVID-19 disease, but the composition and physical properties of these secretions are poorly understood. We characterized the composition and rheological properties (i.e. resistance to flow) of respiratory secretions collected from intubated COVID-19 patients. We found the percent solids and protein content are all greatly elevated in COVID-19 compared to heathy control samples and closely resemble levels seen in cystic fibrosis (CF), a genetic disease known for thick, tenacious respiratory secretions. DNA and hyaluronan are major components of respiratory secretions in COVID-19 and are likewise abundant in cadaveric lung tissues from these patients. COVID-19 secretions exhibited heterogeneous rheological behaviors with thicker samples showing increased sensitivity to DNase and hyaluronidase treatment. These results highlight the dramatic biophysical properties of COVID-19 respiratory secretions and suggest that DNA and hyaluronan may be viable therapeutic targets in COVID-19 infection.

Origin of Novel Coronavirus (COVID-19): A Computational Biology Study using Artificial Intelligence

Origin of the COVID-19 virus (SARS-CoV-2) has been intensely debated in the scientific community since the first infected cases were detected in December 2019. The disease has caused a global pandemic, leading to deaths of thousands of people across the world and thus finding origin of this novel coronavirus is important in responding and controlling the pandemic. Recent research results suggest that bats or pangolins might be the hosts for SARS-CoV-2 based on comparative studies using its genomic sequences. This paper investigates the SARS-CoV-2 origin by using artificial intelligence (AI) and raw genomic sequences of the virus. More than 300 genome sequences of COVID-19 infected cases collected from different countries are explored and analysed using unsupervised clustering methods. The results obtained from various AI-enabled experiments using clustering algorithms demonstrate that all examined SARS-CoV-2 genomes belong to a cluster that also contains bat and pangolin coronavirus genomes. This provides evidence strongly supporting scientific hypotheses that bats and pangolins are probable hosts for SARS-CoV-2. At the whole genome analysis level, our findings also indicate that bats are more likely the hosts for the COVID-19 virus than pangolins.

Accumulation of genome-specific transcripts, transcription factors and phytohormonal regulators during early stages of fiber cell development in allotetraploid cotton.

Gene expression during the early stages of fiber cell development and in allopolyploid crops is poorly understood. Here we report computational and expression analyses of 32 789 high-quality ESTs derived from Gossypium hirsutum L. Texas Marker-1 (TM-1) immature ovules (GH_TMO). The ESTs were assembled into 8540 unique sequences including 4036 tentative consensus sequences (TCs) and 4504 singletons, representing approximately 15% of the unique sequences in the cotton EST collection. Compared with approximately 178 000 existing ESTs derived from elongating fibers and non-fiber tissues, GH_TMO ESTs showed a significant increase in the percentage of genes encoding putative transcription factors such as MYB and WRKY and genes encoding predicted proteins involved in auxin, brassinosteroid (BR), gibberellic acid (GA), abscisic acid (ABA) and ethylene signaling pathways. Cotton homologs related to MIXTA, MYB5, GL2 and eight genes in the auxin, BR, GA and ethylene pathways were induced during fiber cell initiation but repressed in the naked seed mutant (N1N1) that is impaired in fiber formation. The data agree with the known roles of MYB and WRKY transcription factors in Arabidopsis leaf trichome development and the well-documented phytohormonal effects on fiber cell development in immature cotton ovules cultured in vitro. Moreover, the phytohormonal pathway-related genes were induced prior to the activation of MYB-like genes, suggesting an important role of phytohormones in cell fate determination. Significantly, AA sub-genome ESTs of all functional classifications including cell-cycle control and transcription factor activity were selectively enriched in G. hirsutum L., an allotetraploid derived from polyploidization between AA and DD genome species, a result consistent with the production of long lint fibers in AA genome species. These results suggest general roles for genome-specific, phytohormonal and transcriptional gene regulation during the early stages of fiber cell development in cotton allopolyploids.