RESUMEN
1.Severe acute respiratory distress syndrome (ARDS) during SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) infection, manifests as uncontrolled lung inflammation and systemic thrombosis with high mortality. Anti-viral drugs and monoclonal antibodies can reduce COVID-19 severity if administered in the early viremic phase, but treatments for later stage immuno-thrombotic syndrome and long COVID are limited. Serine protease inhibitors (SERPINS) regulate activated proteases during thrombotic, thrombolytic and immune responses. The myxoma poxvirus-derived Serp-1 protein is a secreted immunomodulatory serpin that targets activated coagulation and complement protease pathways as part of a self-defense strategy to combat viral clearance by the innate immune system. When purified and utilized as an anti-immune therapeutic, Serp-1 is effective as an anti-inflammatory drug in multiple animal models of inflammatory lung disease and vasculitis. Here, we describe systemic treatment with purified PEGylated Serp-1 (PEGSerp-1) as a therapy for immuno-thrombotic complications during ARDS. Treatment with PEGSerp-1 in two distinct mouse-adapted SARS-CoV-2 models in C57Bl/6 and BALB/c mice reduced lung and heart inflammation, with improved clinical outcomes. PEGSerp-1 significantly reduced M1 macrophage invasion in the lung and heart by modifying urokinase-type plasminogen activator receptor (uPAR) and complement membrane attack complex (MAC). Sequential changes in urokinase-type plasminogen activator receptor (uPAR) and serpin gene expression were observed in lung and heart with PEGSerp-1 treatment. PEGSerp-1 is a highly effective immune-modulator with therapeutic potential for treatment of severe viral ARDS with additional potential to reduce late SARS-CoV-2 complications related to immune-thrombotic events that persist during long COVID. SignificanceSevere acute respiratory distress syndrome (ARDS) in SARS-CoV-2 infection manifests as uncontrolled tissue inflammation and systemic thrombosis with high mortality. Anti-viral drugs and monoclonal antibodies reduce COVID-19 severity if administered early, but treatments for later stage immuno-thrombosis are limited. Serine protease inhibitors (SERPINS) regulate thrombotic, thrombolytic and complement pathways. We investigate here systemic treatment with purified poxvirus-derived PEGSerp-1 as a therapeutic for immuno-thrombotic complications in viral ARDS. PEGSerp-1 treatment in two mouse-adapted SARS-CoV-2 models (C57Bl/6 and BALB/c) significantly reduced lung and heart inflammation and improved clinical outcomes, with sequential changes in thrombolytic (uPAR) and complement expression. PEGSerp-1 is a highly effective immune-modulator with therapeutic potential for immune-thrombotic complications in severe viral ARDS and has potential benefit for long COVID.
RESUMEN
Back and forth transmission of SARS-CoV-2 between humans and animals may lead to wild reservoirs of virus that can endanger efforts toward long-term control of COVID-19 in people, and protecting vulnerable animal populations that are particularly susceptible to lethal disease. Predicting high risk host species is key to targeting field surveillance and lab experiments that validate host zoonotic potential. A major bottleneck to predicting animal hosts is the small number of species with available molecular information about the structure of ACE2, a key cellular receptor required for viral cell entry. We overcome this bottleneck by combining species ecological and biological traits with 3D modeling of virus and host cell protein interactions using machine learning methods. This approach enables predictions about the zoonotic capacity of SARS-CoV-2 for over 5,000 mammals -- an order of magnitude more species than previously possible. The high accuracy predictions achieved by this approach are strongly corroborated by in vivo empirical studies. We identify numerous common mammal species whose predicted zoonotic capacity and close proximity to humans may further enhance the risk of spillover and spillback transmission of SARS-CoV-2. Our results reveal high priority areas of geographic overlap between global COVID-19 hotspots and potential new mammal hosts of SARS-CoV-2. With molecular sequence data available for only a small fraction of potential host species, predictive modeling integrating data across multiple biological scales offers a conceptual advance that may expand our predictive capacity for zoonotic viruses with similarly unknown and potentially broad host ranges.
RESUMEN
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged from a zoonotic spill-over event and has led to a global pandemic. The public health response has been predominantly informed by surveillance of symptomatic individuals and contact tracing, with quarantine, and other preventive measures have then been applied to mitigate further spread. Non-traditional methods of surveillance such as genomic epidemiology and wastewater-based epidemiology (WBE) have also been leveraged during this pandemic. Genomic epidemiology uses high-throughput sequencing of SARS-CoV-2 genomes to inform local and international transmission events, as well as the diversity of circulating variants. WBE uses wastewater to analyse community spread, as it is known that SARS-CoV-2 is shed through bodily excretions. Since both symptomatic and asymptomatic individuals contribute to wastewater inputs, we hypothesized that the resultant pooled sample of population-wide excreta can provide a more comprehensive picture of SARS-CoV-2 genomic diversity circulating in a community than clinical testing and sequencing alone. In this study, we analysed 91 wastewater samples from 11 states in the USA, where the majority of samples represent Maricopa County, Arizona (USA). With the objective of assessing the viral diversity at a population scale, we undertook a single-nucleotide variant (SNV) analysis on data from 52 samples with >90% SARS-CoV-2 genome coverage of sequence reads, and compared these SNVs with those detected in genomes sequenced from clinical patients. We identified 7973 SNVs, of which 5680 were "novel" SNVs that had not yet been identified in the global clinical-derived data as of 17th June 2020 (the day after our last wastewater sampling date). However, between 17th of June 2020 and 20th November 2020, almost half of the SNVs have since been detected in clinical-derived data. Using the combination of SNVs present in each sample, we identified the more probable lineages present in that sample and compared them to lineages observed in North America prior to our sampling dates. The wastewater-derived SARS-CoV-2 sequence data indicates there were more lineages circulating across the sampled communities than represented in the clinical-derived data. Principal coordinate analyses identified patterns in population structure based on genetic variation within the sequenced samples, with clear trends associated with increased diversity likely due to a higher number of infected individuals relative to the sampling dates. We demonstrate that genetic correlation analysis combined with SNVs analysis using wastewater sampling can provide a comprehensive snapshot of the SARS-CoV-2 genetic population structure circulating within a community, which might not be observed if relying solely on clinical cases.
RESUMEN
On January 26 2020, the first Coronavirus Disease 2019 (COVID-19) case was reported in Arizona of an individual with travel history (3rd case in the US) (1). Here, we report on early SARS-CoV-2 sentinel surveillance in Tempe, Arizona (USA). Genomic characterization identified an isolate encoding a 27 amino acid in-frame deletion in accessory protein ORF7a, the ortholog of SARS-CoV immune antagonist ORF7a/X4.
