MixOmics Integration of Biological Datasets Identifies Highly Correlated Key Variables of COVID-19 severity. (preprint)

Background: Despite several years since the COVID-19 pandemic was declared, challenges remain in understanding the factors that can predict the severity of COVID-19 disease and complications of SARS-CoV-2 infection. While many large-scale Multiomic datasets have been published, integration of these datasets has the potential to substantially increase the biological insight gained allowing a more complex comprehension of the disease pathogenesis. Such insight may improve our ability to predict disease progression, detect severe cases more rapidly and develop effective therapeutics. Methods: In this study we have applied an innovative machine learning algorithm to delineate COVID-severity based on integration of paired samples of proteomic and transcriptomic data from a small cohort of patients testing positive for SARS-CoV-2 infection with differential disease severity. Targeted plasma proteomics and an onco-immune targeted transcriptomic panel was performed on sequential samples from a cohort of 23 severe, 21 moderate and 10 mild COVID-19 patients. We applied DIABLO, a new integrative method, to identify multi-omics biomarker panels that can discriminate between multiple phenotypic groups, such as the varied severity of disease in COVID-19 patients. Results: As COVID-19 severity is known among our sample group, we can train models using this as the outcome variable and calculate features that are important predictors of severe disease. In this study, we detect highly correlated key variables of severe COVID-19 using transcriptomic discriminant analysis and multi-omics integration methods. Conclusions: This approach highlights the power of data integration from a small cohort of patients offering a better biological understanding of the molecular mechanisms driving COVID-19 severity and an opportunity to improve prediction of disease trajectories and targeted therapeutics.

Proteomic profiling identifies biomarkers of COVID-19 severity (preprint)

SARS-CoV-2 infection remains a major public health concern, particularly for the aged and those individuals with co-morbidities at risk for developing severe COVID-19. Understanding the pathogenesis and biomarkers associated with responses to SARS-CoV-2 infection remain critical components in developing effective therapeutic approaches, especially in cases of severe and long-COVID-19. In this study blood plasma protein expression was compared in subjects with mild, moderate, and severe COVID-19 disease. Evaluation of an inflammatory protein panel confirms upregulation of proteins including TNF{beta}, IL-6, IL-8, IL-12, already associated with severe cytokine storm and progression to severe COVID-19. Importantly, we identify several proteins not yet associated with COVID-19 disease, including mesothelin (MSLN), that are expressed at significantly higher levels in severe COVID-19 subjects. In addition, we find a subset of markers associated with T-cell and dendritic cell responses to viral infection that are significantly higher in mild cases and decrease in expression as severity of COVID-19 increases, suggesting that an immediate and effective activation of T-cells is critical in modulating disease progression. Together, our findings identify new targets for further investigation as therapeutic approaches for the treatment of SARS-CoV-2 infection and prevention of complications of severe COVID-19.

Neutrophil-epithelial interactions augment infectivity and pro-inflammatory responses to SARS-CoV-2 infection (preprint)

In response to viral infection, neutrophils release inflammatory mediators as part of the innate immune response, contributing to pathogen clearance through virus internalization and killing. Pre-existing co-morbidities, correlating to incidence of severe COVID-19, are associated with chronic airway neutrophilia and examination of COVID-19 lung tissue revealed a series of epithelial pathologies associated with infiltration and activation of neutrophils. To determine the impact of neutrophil-epithelial interactions on the infectivity and inflammatory response to SARS-CoV-2 infection, we developed a co-culture model of airway neutrophilia. We discovered that SARS-CoV-2 infection of the airway epithelium alone does not result in a notable release of pro-inflammatory cytokines, however in the presence of neutrophils, the inflammatory response is both polarized and significantly augmented, epithelial barrier integrity in impaired and viral load of the airway epithelium increased. This study reveals a key role for neutrophil-epithelial interactions in determining inflammation, infectivity, and outcomes in response to SARS-CoV-2 infection. HighlightsO_LIWe have developed a model to study neutrophil-epithelial interactions which better reflects the in vivo situation than monocultures C_LIO_LINeutrophils significantly augment SARS-CoV-2 mediated, pro-inflammatory cytokine release from the epithelium indicating a key interaction C_LIO_LISARS-CoV-2 infection leads to a polarized inflammatory response in differentiated airway epithelium C_LIO_LIDisruption of the epithelial barrier via addition of neutrophils or cytokines leads to increased infection C_LIO_LIStudy reveals a key role for neutrophil-epithelial interactions in determining outcome/infectivity C_LI

The D614G mutation in the SARS-CoV2 Spike protein increases infectivity in an ACE2 receptor dependent manner (preprint)

The SARS-CoV2 coronavirus responsible for the current COVID19 pandemic has been reported to have a relatively low mutation rate. Nevertheless, a few prevalent variants have arisen that give the appearance of undergoing positive selection as they are becoming increasingly widespread over time. Most prominent among these is the D614G amino acid substitution in the SARS-CoV2 Spike protein, which mediates viral entry. The D614G substitution, however, is in linkage disequilibrium with the ORF1b P314L mutation where both mutations almost invariably co-occur, making functional inferences problematic. In addition, the possibility of repeated new introductions of the mutant strain does not allow one to distinguish between a founder effect and an intrinsic genetic property of the virus. Here, we synthesized and expressed the WT and D614G variant SARS-Cov2 Spike protein, and report that using a SARS-CoV2 Spike protein pseudotyped lentiviral vector we observe that the D614G variant Spike has >1/2 log10 increased infectivity in human cells expressing the human ACE2 protein as the viral receptor. The increased binding/fusion activity of the D614G Spike protein was corroborated in a cell fusion assay using Spike and ACE2 proteins expressed in different cells. These results are consistent with the possibility that the Spike D614G mutant increases the infectivity of SARS-CoV2.