Biology subjects

Li, A.

Publications and source records attributed to Li, A..

At least 199 records · Page 11Linked to original sources

bioRxiv2022

Convergent impact of schizophrenia risk genes

Genetic studies of schizophrenia reveal a complex polygenic risk architecture comprised of hundreds of risk variants; most are common in the population at-large, non-coding, and act by genetically regulating the expression of one or more gene targets ("eGenes"). It remains unclear how genetic variants predicted to confer individually small effects combine to yield substantial clinical impacts in aggregate. Here, we demonstrate that eGenes have shared downstream transcriptomic effects ("convergence") that may underlie unexpected interactions ("non-additive effects") observed when eGenes are manipulated in combination. We apply a pooled CRISPR approach to perturb schizophrenia eGenes in human induced pluripotent stem cell-derived glutamatergic neurons. The strength and specificity of convergence increased between functionally similar eGenes. Predicting that convergence might impact additive relationships between risk loci when inherited together, we use an arrayed approach to explore bidirectional combinatorial perturbations of a partially overlapping set of fifteen schizophrenia eGenes. When specifically considering groups of synaptic or epigenetic eGenes, combinatorial eGene perturbations yield changes that are smaller than predicted by summing individual eGene effects ("sub-additive effects"). Moreover, convergent and non-additive downstream transcriptomic effects overlap, suggesting that functional redundancy of eGenes may be a major mechanism underlying non-additivity. Combinatorial perturbations result in outcomes that are not yet well-predicted by single eGene perturbations alone, indicating that the effects of polygenic risk cannot necessarily be extrapolated from experiments testing one risk gene at a time.

neuroscience↗

bioRxiv2022

Novel feature selection methods for construction of accurate epigenetic clocks

Epigenetic clocks allow the accurate prediction of age based on the methylation status of specific CpG sites in a variety of tissues. These predictive models can be used to distinguish the biological age of an organism from its chronological age, and are a powerful tool to measure the effectiveness of aging interventions. There is a growing need for methods to efficiently construct epigenetic clocks. The most common approach is to create clocks using elastic net regression modelling of all measured CpG sites, without first identifying specific features or CpGs of interest. The addition of feature selection approaches provides the opportunity to reduce the cost and time of clock development by decreasing the number of CpG sites included in clocks. Here, we apply both classic feature selection methods and novel combinatorial methods to the development of epigenetic clocks. We perform feature selection on the human whole blood methylation dataset of [~]470,000 CpG features published by Hannum and colleagues (2015). We develop clocks to predict age, using a variety of feature selection approaches, and all clocks have R2 correlation scores of greater than 0.73. The most predictive clock uses 35 CpG sites for a R2 correlation score of 0.87. The five most frequent sites across all clocks are also modelled to build a clock with a R2 correlation score of 0.83. These two clocks are validated on two external datasets where they maintain excellent predictive accuracy and outperform Hannum et als model in accuracy of age prediction despite using significantly less CpGs. We also identify the associated gene regulatory regions of these CpG sites, which may be possible targets for future aging studies. These novel feature selection algorithms will lower the number of sites needed to be sequenced to build clocks and allow conventionally expensive aging epigenetic studies to cost a fraction of what it would normally.

bioinformatics↗

bioRxiv2022

CRISPR-Detector: Fast and Accurate Detection, Visualization, and Annotation of Genome Wide Mutations Induced by Gene Editing Events

The leading edge of genome editing, driven by CRISPR/Cas technology, is revolutionizing biotechnologies. In pace with the burst of novel genome editing methods, bioinformatic tools to monitor the on/off-target events need to be more evolved as well. Existing tools suffer from limitations in speed and scalability, and they especially struggle with whole genome sequencing (WGS) data analysis which has the potential to detect off-target mutations at a genome-wide level via an unbiased manner. Here, we introduce our CRISPR-detector tool, which is a web-hosted or locally deployable pipeline with five key innovations: 1) optimized scalability allowing for WGS data analysis beyond BED (Browser Extensible Data) file-defined regions; 2) improved accuracy benefiting from haplotype-based variant calling to handle sequencing errors; 3) treated and control sample co-analysis to remove background variants existing prior to genome editing; 4) integrated structural variation (SV) calling; and 5) functional and clinical annotation of editing-induced mutations.

bioinformatics↗

bioRxiv2022

Aucubin promoted neuron functional recovery by suppressing inflammation and neuronal apoptosis in a spinal cord injury model

Spinal cord injury (SCI) can cause severe motor impairment. Post-SCI treatment has focused primarily on secondary injury, with neuroinflammation and neuronal apoptosis as the primary therapeutic targets. Aucubin (Au), a Chinese herbal medicine, exerts anti-inflammatory and neuroprotective effects. The therapeutic effects of Au in SCI have not been reported. We showed that Au can promote functional recovery after SCI. Recovery may occur through the toll-like receptor 4 (TLR4)/nuclear factor kappa B (NF-{kappa}B) pathway to promote M2/M1 polarization in microglia and inhibit mitochondrial dysfunction to reduce neuronal apoptosis. These biochemical changes result in reduced secondary injury and facilitate axon regeneration. Therefore, Au may be a promising post-SCI therapeutic medication.

cell biology↗

bioRxiv2022

JWA deficiency accelerates aging through disrupting intestinal epithelial homeostasis via Notch1/PPARγ/Stat5 axis

Aging usually suppresses the renewal and regeneration of intestinal epithelium. The imbalance of intestinal epithelial homeostasis may also be a promoter for aging. JWA responds to oxidative stress and repairs damaged DNA; it participates in multiple cellular processes like cell proliferation and differentiation. Here we identified JWA as a new aging-associated gene, whose deletion-accelerated aging in mice was related to intestinal epithelium atrophy. We further knocked out intestinal epithelial JWA and found it disrupted intestinal epithelial homeostasis, thus promoting aging in mice. Mechanistically, we discovered that JWA deficiency promoted Notch1 ubiquitination degradation via ERK/Fbxw7 cascade and interfered with the PPAR{gamma}/Stat5 signal axis. This reduced the intestinal stem cell function and altered the intestinal epithelial cell lineage distribution, finally suppressing the renewal and regeneration of intestinal epithelium. Our results demonstrated that JWA is a new aging-associated gene essential for the renewal and regeneration of intestinal epithelium. We also provide a new idea that maintaining intestinal epithelial homeostasis may be a potential anti-aging strategy in humans or mammals.

developmental biology↗

bioRxiv2022

Real-time dynamic single-molecule protein sequencing on an integrated semiconductor device

Proteins are the main structural and functional components of cells, and their dynamic regulation and post-translational modifications (PTMs) underlie cellular phenotypes. Next-generation DNA sequencing technologies have revolutionized our understanding of heredity and gene regulation, but the complex and dynamic states of cells are not fully captured by the genome and transcriptome. Sensitive measurements of the proteome are needed to fully understand biological processes and changes to the proteome that occur in disease states. Studies of the proteome would benefit greatly from methods to directly sequence and digitally quantify proteins and detect PTMs with single-molecule sensitivity and precision. However current methods for studying the proteome lag behind DNA sequencing in throughput, sensitivity, and accessibility due to the complexity and dynamic range of the proteome, the chemical properties of proteins, and the inability to amplify proteins. Here, we demonstrate single-molecule protein sequencing on a compact benchtop instrument using a dynamic sequencing by stepwise degradation approach in which single surface-immobilized peptide molecules are probed in real-time by a mixture of dye-labeled N-terminal amino acid recognizers and simultaneously cleaved by aminopeptidases. By measuring fluorescence intensity, lifetime, and binding kinetics of recognizers on an integrated semiconductor chip we are able to annotate amino acids and identify the peptide sequence. We describe the expansion of the number of recognizable amino acids and demonstrate the kinetic principles that allow individual recognizers to identify multiple amino acids in a highly information-rich manner that is sensitive to adjacent residues. Furthermore, we demonstrate that our method is compatible with both synthetic and natural peptides, and capable of detecting single amino acid changes and PTMs. We anticipate that with further development our protein sequencing method will offer a sensitive, scalable, and accessible platform for studies of the proteome.

biophysics↗

bioRxiv2021

A human monoclonal antibody potently pan-neutralizes SARS-CoV-2 VOCs by targeting RBD invariant sites

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of novel corona virus disease (COVID-19). The neutralizing monoclonal antibodies (mAbs) targeting the receptor binding domain (RBD) of SARS-CoV-2 are among the most promising strategies to prevent and treat COVID-19. However, SARS-CoV-2 variants of concern (VOCs) profoundly reduced the efficacies of most of mAbs and vaccines approved for clinical use. Herein, we demonstrated mAb 35B5 efficiently neutralizes both wild-type (WT) SARS-CoV-2 and VOCs, including B.1.617.2 (delta) variant, in vitro and in vivo. Cryo-electron microscopy (cryo-EM) revealed that 35B5 neutralizes SARS-CoV-2 by targeting a unique epitope that avoids the prevailing mutation sites on RBD identified in circulating VOCs, providing the molecular basis for its pan-neutralizing efficacy. The 35B5-binding epitope could also be exploited for the rational design of a universal SARS-CoV-2 vaccine.

immunology↗

bioRxiv2021

In vitro and in vivo CRISPR-Cas9 screens reveal drivers of aging in neural stem cells of the brain

Aging impairs the ability of neural stem cells to transition from quiescence to activation (proliferation) in the adult mammalian brain. Neural stem cell (NSC) functional decline results in decreased production of new neurons and defective regeneration upon injury during aging1-9, and this is exacerbated in Alzheimers disease10. Many genes are upregulated with age in NSCs3, 11-13, and the knockout of some of these boosts old NSC activation and rejuvenates aspects of old brain function14-18. But systematic functional testing of genes in old NSCs - and more generally in old cells - has not been done. This has been a major limiting factor in identifying the most promising rejuvenation interventions. Here we develop in vitro and in vivo high-throughput CRISPR-Cas9 screening platforms to systematically uncover gene knockouts that boost NSC activation in old mice. Our genome-wide screening pipeline in primary cultures of young and old NSCs identifies over 300 gene knockouts that specifically restore old NSC activation. Interestingly, the top gene knockouts are involved in glucose import, cilium organization and ribonucleoprotein structures. To determine which gene knockouts have a rejuvenating effect for the aging brain, we establish a scalable CRISPR-Cas9 screening platform in vivo in old mice. Of the 50 gene knockouts we tested in vivo, 23 boost old NSC activation and production of new neurons in old brains. Notably, the knockout of Slc2a4, which encodes for the GLUT4 glucose transporter, is a top rejuvenating intervention for old NSCs. GLUT4 protein expression increases in the stem cell niche during aging, and we show that old NSCs indeed uptake [~]2-fold more glucose than their young counterparts. Transient glucose starvation increases the ability of old NSCs to activate, which is not further improved by knockout of Slc2a4/GLUT4. Together, these results indicate that a shift in glucose uptake contributes to the decline in NSC activation with age, but that it can be reversed by genetic or external interventions. Importantly, our work provides scalable platforms to systematically identify genetic interventions that boost old NSC function, including in vivo in old brains, with important implications for regenerative and cognitive decline during aging.

neuroscience↗

bioRxiv2021

A chemical method to sequence 5-formylcytosine on RNA

Epitranscriptomic RNA modifications can regulate biological processes, but there remains a major gap in our ability to identify and measure individual modifications at nucleotide resolution. Here we present Mal-Seq, a chemical method to sequence 5-formylcytosine (f5C) modifications on RNA based upon selective and efficient malononitrile-mediated labeling of f5C residues to generate adducts that are read as C-to-T mutations upon reverse transcription and PCR amplification. We apply Mal-Seq to characterize the prevalence of f5C at the wobble position of mt-tRNA(Met) in different organisms and tissue types and find that high-level f5C modification is present in mammals but lacking in lower eukaryotes. Our work sheds light on mitochondrial tRNA modifications throughout eukaryotic evolution and provides a general platform for characterizing the f5C epitranscriptome.

biochemistry↗

bioRxiv2021

Hypertonic saline and aprotinin based blockage of SARS-CoV-2 specific furin site cleavage by inhibition of nasal protease activity

SARS-CoV-2 enters into the human body mainly through the nasal epithelial cells. Cell entry of SARS-CoV-2 needs to be pre-activated by S1/S2 boundary furin motif cleavage by furin and/or relevant proteases. It is important to locally block SARS-CoV-2 S1/S2 site cleavage caused by furin and other relevant protease activity in the nasal cavity. We tested hypertonic saline and aprotinin-based blockage of SARS-CoV-2 specific furin site cleavage by furin, trypsin and nasal swab samples containing nasal proteases. Our results show that saline and aprotinin block SARS-Cov-2 specific furin site cleavage and that a saline and aprotinin combination could significantly reduce SARS-Cov-2 wild-type and P681R mutant furin site cleavage by inhibition of nasal protease activity.

pharmacology and toxicology↗

bioRxiv2021

Source-sink connectivity: a novel resting-state EEG marker of the epileptogenic zone

Over 15 million epilepsy patients worldwide have drug-resistant epilepsy (DRE). Successful surgery is a standard of care treatment for DRE but can only be achieved through complete resection or disconnection of the epileptogenic zone (EZ), the brain region(s) where seizures originate. Surgical success rates vary between 20-80% because no clinically validated biological markers of the EZ exist. Localizing the EZ is a costly and time-consuming process beginning with non-invasive neuroimaging and often followed by days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity (e.g., low-voltage high frequency activity) on individual channels occurring immediately before seizures or spikes that occur on interictal iEEG (i.e., between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in EZ localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients. Intracranial EEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aim to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the EZ. We hypothesize that when a patient is not clinically seizing, it is because the EZ is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighboring nodes ("sources") and the inhibited nodes themselves ("sinks"). Specifically, patient-specific dynamical network models (DNMs) were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics (SSMs). We validated the SSMs in a retrospective analysis of 65 patients by using the SSMs of the annotated EZ to predict surgical outcomes. The SSMs predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians predictions (surgical success rate of this dataset). In failed outcomes, we identified regions of the brain with high SSMs that were untreated. When compared to high frequency oscillations, the most commonly proposed interictal iEEG feature for EZ localization, SSMs outperformed in predictive power (by a factor of 1.2) suggesting SSMs may be an interictal iEEG fingerprint of the EZ.

bioengineering↗

bioRxiv2021

Effects of dual deletion of glnR and mtrA on expression of nitrogen metabolism genes in Streptomyces venezuelae

GlnR activates nitrogen metabolism genes under nitrogen-limited conditions whereas MtrA represses these genes under nutrient-rich conditions in Streptomyces. In this study, we compared the transcription patterns of nitrogen metabolism genes in a double deletion mutant ({Delta}mtrA-glnR) lacking both mtrA and glnR and in mutants lacking either mtrA ({Delta}mtrA) or glnR ({Delta}glnR). The nitrogen metabolism genes were expressed similarly in {Delta}mtrA-glnR and {Delta}glnR under both nitrogen-limited and nutrient-rich conditions, with patterns distinctly different from that of {Delta}mtrA, suggesting a decisive role for GlnR in the control of nitrogen metabolism genes and further suggesting that regulation of these genes by MtrA is GlnR-dependent. MtrA and GlnR utilize the same binding sites upstream of nitrogen metabolism genes, and we showed stronger in vivo binding of MtrA to these sites under nutrient-rich conditions and of GlnR under nitrogen-limited conditions, consistent with the higher levels of MtrA or GlnR under those respective conditions. In addition, we showed that both mtrA and glnR are auto-regulatory. Our study provides new insights into the regulation of nitrogen metabolism genes in Streptomyces.

microbiology↗

bioRxiv2021

Reprogramming the neuroblastoma epigenome with a mitochondrial uncoupler

Dysregulated DNA methylation is associated with poor prognosis in cancer patients, promoting tumorigenesis and therapeutic resistance1. DNA methyltransferase inhibitors (DNMTi) reduce DNA methylation and promote cancer cell differentiation, with two DNMTi already approved for cancer treatment2. However, these drugs rely on cell division to dilute existing methylation, thus the demethylation effects are achieved in a passive manner, limiting their application in slow-proliferating tumor cells. In this study we use a mitochondrial uncoupler, niclosamide ethanolamine (NEN), to actively achieve global DNA demethylation. NEN treatment promotes DNA demethylation by activating electron transport chain (ETC) to produce -ketoglutarate (-KG), a substrate for the DNA demethylase TET. In addition, NEN inhibits reductive carboxylation, a key metabolic pathway to support growth of cancer cells with defective mitochondria or under hypoxia. Importantly, NEN treatment reduces 2-hydroxyglutarate (2-HG) generation and blocks DNA hypermethylation under hypoxia. Together, these metabolic reprogramming effects of NEN actively alter the global DNA methylation landscape and promote neuroblastoma differentiation. These results not only support Warburgs original hypothesis that inhibition of ETC causes cell de-differentiation and tumorigenesis, but also suggest that mitochondrial uncoupling is an effective metabolic and epigenetic intervention that remodels the tumor epigenome for better prognosis.

cancer biology↗

bioRxiv2021

Spatio-temporal feature based deep neural network for cell lineage analysis in microscopy images

BackgroundTime-lapse microscopy has been widely used in biomedical experiments because it can visualize the molecular activities of living cells in real time. However, biomedical researchers are still conducting cell lineage analysis manually. Developing automatic lineage tracing algorithms is a challenging task. In the past two decades, deep neural networks (DNNs) became have shown outstanding performance on computer vision tasks. They can learn complex visual features, capture long-range temporal dependencies, and have the potential to be used for automatic cell lineage analysis. MethodsIn this study, we propose a multi-task spatio-temporal feature based deep neural network for cell lineages analysis (Cell-STN). The Cell-STN extracts spatio-temporal features from microscopy image sequences by leveraging our convolutional long short-term memory based core block. And the proposed Cell-STN utilized a task specific network to predict the cell location, the mitosis event, and the apoptosis event in a multi-task manner. ResultsWe evaluated the Cell-STN on three in-house datasets (MCF7, U2OS, and HCT116) and one public dataset (Fluo-N2DL-HeLa). For cell tracking, we used peak-wise precision, track-wise precision, end-peak precision, and spatial distance as metrics. The overall results showed the Cell-STN models outperform other state-of-the-art cell trackers. For mitosis and apoptosis tasks, we used accuracy, F1-score, temporal distance, and spatial distance as metrics. The Cell-STN models achieved the highest performance on all datasets. ConclusionThis study presented a novel DNNs approach for cell lineage analysis in microscopy images. The Cell-STN showed outstanding performance on the four datasets. Additionally, the Cell-STN required minimal training data and can be adapted to new biological event detection tasks by appending task-specific layers. This algorithm has the potential to be used in real-world biomedical research.

bioinformatics↗

bioRxiv2021

Single-shot rAAV5-based Vaccine Provides Long-term Protective Immunity against SARS-CoV-2 and Its Variants

The COVID-19 pandemic and the SARS-CoV-2 with its variants have posed unprecedented challenges worldwide. Existing vaccines have limited effectiveness against the SARS-CoV-2 variants. Therefore, novel vaccines to match current mutated viral lineages with long-term protective immunity are urgently in demand. In the current study, we for the first time designed a recombinant Adeno-Associated Virus 5 (rAAV5)-based vaccine named as rAAV-COVID-19 vaccine (Covacinplus) by using RBD-plus of spike protein with both the single-stranded and the self-complementary AAV5 delivering vectors (ssAAV5 and scAAAV5), which provides excellent protection from SARS-CoV-2 infection. A single dose vaccination induced the strong immune response against SARS-CoV-2. The induced neutralizing antibodies (NAs) titers were maintained at a high peak level of over 1:1024 even after more than one year of injection and accompanied with functional T-cells responses in mice. Importantly, both ssAAV- and scAAV-based RBD-plus vaccines exhibited high levels of serum NAs against current circulating variants including variants Alpha, Beta, Gamma and Delta. SARS-CoV-2 virus challenge test showed that ssAAV5-RBD-plus vaccine protected both young and old age mice from SARS-CoV-2 infection in the upper and the lower respiratory tracts. Moreover, whole genome sequencing demonstrated that AAV vector DNA sequences were not found in the genome of the vaccinated mice after one year vaccination, demonstrating excellent safety of the vaccine. Taken together, this study suggests that rAAV5-based vaccine is powerful against SARS-CoV-2 and its variants with long-term protective immunity and excellent safety, which has great potential for development into prophylactic vaccination in human to end this global pandemic.

immunology↗

bioRxiv2021

Cornering an Ever-Evolving Coronavirus: TATX-03, a fully human synergistic multi-antibody cocktail targeting the SARS-CoV-2 Spike Protein with in vivo efficacy

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created an ongoing global human health crisis and will likely become endemic, requiring novel sustainable therapeutic strategies. We report on the discovery of a fully human multi-antibody cocktail (TATX-03) targeting diversified non-overlapping epitopes on the SARS-CoV-2 spike protein that suppressed replication-competent viral titers to undetectable levels in the lungs of SARS-CoV-2 challenged hamsters upon both prophylactic and therapeutic administration. While monotherapy with two of the individual cocktail components also showed clear in vivo protection, neither recapitulated the efficacy of TATX-03. This synergistic effect was further supported by examining in vivo efficacy of these individual antibodies and corresponding combination therapy at a lower dose. Furthermore, in vitro screenings using VSV-particles pseudo-typed with spike proteins representing the SARS-CoV-2 variants of concern Alpha, Beta, and Delta showed that TATX-03 maintained its neutralization potency. These results merit further development of TATX-03 as a potential therapy for SARS-CoV-2 infection with resistance to mutagenic escape.

immunology↗

bioRxiv2021

Probing molecular specificity with deep sequencing and biophysically interpretable machine learning

Quantifying sequence-specific protein-ligand interactions is critical for understanding and exploiting numerous cellular processes, including gene regulation and signal transduction. Next-generation sequencing (NGS) based assays are increasingly being used to profile these interactions with high-throughput. However, these assays do not provide the biophysical parameters that have long been used to uncover the quantitative rules underlying sequence recognition. We developed a highly flexible machine learning framework, called ProBound, to define sequence recognition in terms of biophysical parameters based on NGS data. ProBound quantifies transcription factor (TF) behavior with models that accurately predict binding affinity over a range exceeding that of previous resources, captures the impact of DNA modifications and conformational flexibility of multi-TF complexes, and infers specificity directly from in vivo data such as ChIP-seq without peak calling. When coupled with a new assay called Kd-seq, it determines the absolute affinity of protein-ligand interactions. It can also profile the kinetics of kinase-substrate interactions. By constructing a biophysically robust foundation for profiling sequence recognition, ProBound opens up new avenues for decoding biological networks and rationally engineering protein-ligand interactions.

genomics↗

bioRxiv2021

FXa cleaves the SARS-CoV-2 spike protein and blocks cell entry to protect against infection with inferior effects in B.1.1.7 variant

The ongoing coronavirus disease 2019 (COVID-19) pandemic is caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Human natural defense mechanisms against SARS-CoV-2 are largely unknown. Serine proteases (SPs) including furin and TMPRSS2 cleave SARS-CoV-2 spike protein, facilitating viral entry. Here, we show that FXa, a SP for blood coagulation, is upregulated in COVID-19 patients compared to non-COVID-19 donors and exerts anti-viral activity. Mechanistically, FXa cleaves the SARS-CoV-2 spike protein, which prevents its binding to ACE2, and thus blocks viral entry. Furthermore, the variant B.1.1.7 with several mutations is dramatically resistant to the anti-viral effect of FXa compared to wild-type SARA-CoV-2 in vivo and in vitro. The anti-coagulant rivaroxaban directly inhibits FXa and facilitates viral entry, whereas the indirect inhibitor fondaparinux does not. In a lethal humanized hACE2 mouse model of SARS-CoV-2, FXa prolonged survival while combination with rivaroxaban but not fondaparinux abrogated this protection. These preclinical results identify a previously unknown SP function and associated anti-viral host defense mechanism and suggest caution in considering direct inhibitors for prevention or treatment of thrombotic complications in COVID-19 patients.

microbiology↗