Biology subjects

Yuan, K.

Publications and source records attributed to Yuan, K..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

A novel architecture of PT neuron-based corticothalamic connectivity in the auditory system

Largely topographical projections from different modules of the thalamus, such as the primary, secondary and association sensory thalamus, to hierarchically defined cortical areas have been recognized across sensory systems. However, how corticothalamic projections, which are believed to be crucial for the remarkable flexibility and precision exhibited by our sensory systems, are organized remained poorly understood compared with the thalamocortical counterpart. Here we report that, first, the primary auditory thalamus received direct inputs from cortical L5 neurons. Second, in contrast to the robust thalamocortical topography, L5 neurons in each of the primary, secondary and association auditory cortical regions project to each individual module of the auditory thalamus at the macroscale. Third, the association cortex provided the most L5 inputs to all thalamic modules followed by the secondary and primary auditory cortices. Lastly, L5 axon terminals were mainly varicosity-type and evenly distributed across thalamic modules, but those in the polymodal association module were the largest. Our data suggest that all the modules of the auditory thalamus may be under the modulation of common L5 inputs. This fully-connected-like corticothalamic architecture urges a revision of the traditional hierarchical model in the sensory systems.

neuroscience↗

bioRxiv2023

SARS-CoV-2's evolutionary capacity is mostly driven by host antiviral molecules

The COVID-19 pandemic has been characterised by sequential variant-specific waves shaped by viral, individual human and population factors. SARS-CoV-2 variants are defined by their unique combinations of mutations and there has been a clear adaptation to human infection since its emergence in 2019. Here we use machine learning models to identify shared signatures, i.e., common underlying mutational processes, and link these to the subset of mutations that define the variants of concern (VOCs). First, we examined the global SARS-CoV-2 genomes and associated metadata to determine how viral properties and public health measures have influenced the magnitude of waves, as measured by the number of infection cases, in different geographic locations using regression models. This analysis showed that, as expected, both public health measures and not virus properties alone are associated with the rise and fall of regional SARS-CoV-2 reported infection numbers. This impact varies geographically. We attribute this to intrinsic differences such as vaccine coverage, testing and sequencing capacity, and the effectiveness of government stringency. In terms of underlying evolutionary change, we used non-negative matrix factorisation to observe three distinct mutational signatures, unique in their substitution patterns and exposures from the SARS-CoV-2 genomes. Signatures 0, 1 and 3 were biased to C[->]T, T[->]C/A[->]G and G[->]T point mutations as would be expected of host antiviral molecules APOBEC, ADAR and ROS effects, respectively. We also observe a shift amidst the pandemic in relative mutational signature activity from predominantly APOBEC-like changes to an increasingly high proportion of changes consistent with ADAR editing. This could represent changes in how the virus and the host immune response interact, and indicates how SARS-CoV-2 may continue to accumulate mutations in the future. Linkage of the detected mutational signatures to the VOC defining amino acids substitutions indicates the majority of SARS-CoV-2s evolutionary capacity is likely to be associated with the action of host antiviral molecules rather than virus replication errors.

genomics↗

bioRxiv2023

Prediction of virus-host association using protein language models and multiple instance learning

Predicting virus-host associations is essential to determine the specific host species that viruses interact with, and discover if new viruses infect humans and animals. Currently, the host of the majority of viruses is unknown, particularly in microbiomes. To address this challenge, we introduce EvoMIL, a deep learning method that predicts the host species for viruses from viral sequences only. It also identifies important viral proteins that significantly contribute to host prediction. The method combines a pre-trained large protein language model (ESM) and attention-based multiple instance learning to allow protein-orientated predictions. Our results show that protein embeddings capture stronger predictive signals than sequence composition features, including amino acids, physiochemical properties, and DNA k-mers. In multi-host prediction tasks, EvoMIL achieves median F1 score improvements of 8.6%, 12.3%, and 4.1% in prokaryotic hosts, and 0.5%, 1.8% and 3% in eukaryotic hosts. EvoMIL binary classifiers achieve impressive AUC over 0.95 for all prokaryotic and range from roughly 0.8 to 0.9 for eukaryotic hosts. Furthermore, EvoMIL estimates the importance of single proteins in the prediction task and maps them to an embedding landscape of all viral proteins, where proteins with similar functions are distinctly clustered together, highlighting the ability of EvoMIL to capture key proteins in virus-host specificity. Author summaryBeing able to predict which viruses can infect which host species, and identifying the specific proteins that are involved in these interactions, are fundamental tasks in virology. Traditional methods for predicting these interactions rely on common manual features among proteins, overlooking the structure of the protein "language" encoded in individual proteins. We have developed a novel method that combines a protein language model and multiple instance learning to allow host prediction directly from protein sequences, without the need to extract manual features. This method significantly improved prediction accuracy and revealed key proteins involved in virus-host interactions.

bioinformatics↗

bioRxiv2023

Exposure to high-sugar diet induces transgenerational changes in sweet sensitivity and feeding behavior via H3K27me3 reprogramming

Human health is facing a host of new threats linked to unbalanced diets, including high sugar diet (HSD), which contributes to the development of both metabolic and behavioral disorders. Studies have shown that diet-induced metabolic dysfunctions can transmit to multiple generations of offspring and exert long-lasting health burden. Meanwhile, whether and how diet-induced behavioral abnormalities can be transmitted to the offspring remain largely unclear. Here, we showed that ancestral HSD exposure suppressed sweet sensitivity and feeding behavior in the offspring in Drosophila. These behavioral deficits were transmitted through the maternal germline and companied by the enhancement of H3K27me3 modifications. PCL-PRC2 complex, a major driver of H3K27 trimethylation, was upregulated by ancestral HSD exposure, and disrupting its activity eliminated the transgenerational inheritance of sweet sensitivity and feeding behavior deficits. Elevated H3K27me3 inhibited the expression of a transcriptional factor Cad and suppressed sweet sensitivity of the sweet-sensing gustatory neurons, reshaping the sweet perception and feeding behavior of the offspring. Taken together, we uncovered a novel molecular mechanism underlying behavioral abnormalities across multiple generations of offspring upon ancestral HSD exposure, which would contribute to the further understanding of long-term health risk of unbalanced diet.

neuroscience↗

bioRxiv2023

Exploration of the Link Between COVID-19 and Alcoholic Hepatitis from the Perspective of Bioinformatics and Systems Biology

ObjectiveSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been suggested to purpose threats to health of mankind. Alcoholic hepatitis (AH) is a life-threatening acute and chronic liver failure that takes place in sufferers who drink excessively. During the epidemic, AH has an increasing incidence of severe illness and mortality. However, for these two diseases, the intrinsic relationship of molecular pathogenesis, as well as common therapeutic strategies are still poorly understood. MethodsThe transcriptome of the COVID-19 and AH has been compared to obtain the altered genes and hub genes were screened out through protein-protein interaction (PPI) network analysis. Via gene ontology (GO), pathway enrichment and transcription regulator analysis, a deeper appreciation of the interplay mechanism between hub genes were established. ResultsWith 181 common differentially expressed genes (DEGs) of AH and COVID-19 were obtained, 10 hub genes were captured. Follow-up studies located that these 10 genes typically mediated the diseases occurrence by regulating the activities of the immune system. Other results suggest that the common pathways of the two ailments are enriched in regulating the function of immune cells and the release of immune molecules. ConclusionThis study reveals the common pathogenesis of COVID-19 and AH and assist to discover necessary therapeutic targets to combat the ongoing pandemic induced via SARS-CoV-2 infection and acquire promising remedy strategies for the two diseases.

bioinformatics↗

bioRxiv2023

Bioinformatics Approaches to Determine the Effect of SARS-CoV-2 Infection on Patients with Intrahepatic Cholangiocarcinoma

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causal agent of coronavirus disease 2019 (COVID-19), has infected millions of individuals throughout the world, which poses a serious threat to human health. COVID-19 is a systemic disease that affects tissues and organs, including the lung and liver. Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) are the most common liver cancer, and cancer patients are particularly at high risk of SARS-CoV-2 infection. The relationship between HCC and COVID-19 has been reported in previous studies, but ICC has been rare. With the methods of systems biology and bioinformatics, this study explored the link between COVID-19 and ICC. Transcriptional profiling of COVID-19 and ICC were obtained from the GEO database. A total of 70 common differentially expressed gene (DEGs) of both diseases were identified to investigate shared pathways. Then top-ranked 10 key DEGs (SCD, ACSL5, ACAT2, HSD17B4, ALDOA, ACSS1, ACADSB, CYP51A1, PSAT1, and HKDC1) were identified as hub genes by protein-protein interaction (PPI) network analysis. In addition, transcriptional regulatory networks regulating hub genes were revealed by hub Gene-transcription factor (TF) interaction analysis and hub gene-microRNA (miRNAs) interaction analysis. This study is expected to provide new references for future research and treatment of COVID-19 and ICC.

bioinformatics↗

bioRxiv2022

Polygenic prediction across populations is influenced by ancestry, genetic architecture, and methodology

Polygenic risk scores (PRS) developed from multi-ancestry genome-wide association studies (GWAS), PRSmulti, hold promise for improving PRS accuracy and generalizability across populations. To establish best practices for leveraging the increasing diversity of genomic studies, we investigated how various factors affect the performance of PRSmulti compared to PRS constructed from single-ancestry GWAS (PRSsingle). Through extensive simulations and empirical analyses, we showed that PRSmulti overall outperformed PRSsingle in understudied populations, except when the understudied population represented a small proportion of the multi-ancestry GWAS. Notably, for traits with large-effect ancestry-enriched variants, such as mean corpuscular volume, using substantially fewer samples from Biobank Japan achieved comparable accuracies to a much larger European cohort. Furthermore, integrating PRS based on local ancestry-informed GWAS and large-scale European-based PRS improved predictive performance in understudied African populations, especially for less polygenic traits with large ancestry-enriched variants. Our work highlights the importance of diversifying genomic studies to achieve equitable PRS performance across ancestral populations and provides guidance for developing PRS from multiple studies.

genomics↗

bioRxiv2022

TF-Prioritizer: a java pipeline to prioritize condition-specific transcription factors

BackgroundEukaryotic gene expression is controlled by cis-regulatory elements (CREs), including promoters and enhancers, which are bound by transcription factors (TFs). Differential expression of TFs and their binding affinity at putative CREs determine tissue- and developmental-specific transcriptional activity. Consolidating genomic data sets can offer further insights into the accessibility of CREs, TF activity, and, thus, gene regulation. However, the integration and analysis of multi-modal data sets are hampered by considerable technical challenges. While methods for highlighting differential TF activity from combined chromatin state data (e.g., ChIP-seq, ATAC-seq, or DNase-seq) and RNA-seq data exist, they do not offer convenient usability, have limited support for large-scale data processing, and provide only minimal functionality for visually interpreting results. ResultsWe developed TF-Prioritizer, an automated pipeline that prioritizes condition-specific TFs from multi-modal data and generates an interactive web report. We demonstrated its potential by identifying known TFs along with their target genes, as well as previously unreported TFs active in lactating mouse mammary glands. Additionally, we studied a variety of ENCODE data sets for cell lines K562 and MCF-7, including twelve histone modification ChIP-seq as well as ATAC-seq and DNase-seq datasets, where we observe and discuss assay-specific differences. ConclusionTF-Prioritizer accepts ATAC-seq, DNase-seq, or ChIP-seq and RNA-seq data as input and identifies TFs with differential activity, thus offering an understanding of genome-wide gene regulation, potential pathogenesis, and therapeutic targets in biomedical research.

bioinformatics↗

bioRxiv2022

Protein Language Model Predicts Mutation Pathogenicity and Clinical Prognosis

Accurately predicting the effects of mutations in cancer has the potential to improve existing treatments and identify novel therapeutic targets. In this paper, we evidence for the first time that the large-scale pre-trained protein language models (PPLMs) are zero-shot predictors for two clinically relevant tasks: identifying diseasecausing mutations and predicting patient survival rate. Then we benchmark a series of state-of-the-art (SOTA) PPLMs on 2279 protein variants across 20 cancer-related genes. Our empirical results show that the PPLMs outperform the SOTA baseline, EVE [1], trained on multiple sequence alignment (MSA) data. We also demonstrate that the evolutionary index score, generated from the PPLMs softmax layer, is good indicator for both mutation pathogenicity and patient survival rate. Our paper has taken a key step toward the clinical utility of large-scale PPLMs.

bioinformatics↗

bioRxiv2022

Aortic Shape Space Topology

Clinical imaging modalities are a mainstay of modern disease management, but the full utilization of imaging-based data remains elusive. Aortic disease is defined by anatomic scalars quantifying aortic size, even though aortic disease progression initiates complex shape changes. We present an imaging-based geometric descriptor, inspired by fundamental ideas from topology and soft-matter physics that captures dynamic shape evolution. The aorta is reduced to a two-dimensional mathematical surface in space whose geometry is fully characterized by the local principal curvatures. Disease causes deviation from the smooth bent cylindrical shape of normal aortas, leading to a family of highly heterogeneous surfaces of varying shapes and sizes. To deconvolute changes in shape from size, the shape is characterized using integrated Gaussian curvature or total curvature. The fluctuation in total curvature ({delta}K) across aortic surfaces captures heterogeneous morphologic evolution by characterizing local shape changes. We discover that aortic morphology evolves with a power-law defined behavior with rapidly increasing{delta} K forming the hallmark of aortic disease. Divergent{delta} K is seen for highly diseased aortas indicative of impending topologic catastrophe or aortic rupture. We also show that aortic size (surface area or enclosed aortic volume) scales as a generalized cylinder for all shapes. Classification accuracy for predicting aortic disease state (normal, diseased with successful surgery, and diseased with failed surgical outcomes) is 92.8 {+/-}1.7%. The analysis of{delta} K can be applied on any three-dimensional geometric structure and thus may be extended to other clinical problems of characterizing disease through captured anatomic changes.

bioengineering↗

bioRxiv2022

A mutant bacterial O-GlcNAcase visualizes a progressive decline of protein O-GlcNAcylation in early Drosophila embryos critical for neurodevelopment

Protein O-GlcNAcylation, a monosaccharide posttranslational modification maintained by two evolutionarily conserved enzymes, O-GlcNAc transferase (OGT) and O-GlcNAcase (OGA), is a major nutrient sensor integrating key metabolic pathways. While mutations in OGT have recently been associated with neurodevelopmental disorders, the dynamics and function of protein O-GlcNAcylation during early embryogenesis remain elusive. Here we develop a new fluorescent probe to visualize O-GlcNAcylation levels in live Drosophila early embryos. Our study shows that protein O-GlcNAcylation declines as the embryos develop to the mid-blastula transition when the facultative heterochromatin makes its first appearance. Lowering O-GlcNAcylation levels by exogenous OGA activity promotes the polycomb group O-GlcNAc protein Polyhomeotic (Ph) to form nuclear foci and K27 trimethylation of histone H3. This enhanced facultative heterochromatin formation fine-tunes the expression of several neurodevelopmental genes including short of gastrulation (sog). We provide evidence that perturbation of O-GlcNAcylation during early embryogenesis affects learning ability in adulthood, highlighting the importance of O-GlcNAcylation homeostasis for the development of the nervous system.

developmental biology↗

bioRxiv2022

A non-lemniscal thalamic interface connecting alerting sensory cues to internal states in mice

Alterations in internal states, such as elevated arousal level and increased anxiety or fear, triggered by alerting environmental cues are required for behavioral state transitions promoting survival. However, the specific brain region that plays an interfacing role between alerting stimuli and internal states remains to be identified. Here, we report that the medial sector of the auditory thalamus (ATm), which consists of a group of non-lemniscal thalamic nuclei, can fulfill this function. VGluT2-expressing ATm (ATmVGluT2+) neurons receive direct and strong inputs from both visual and auditory midbrain regions, and project to multiple downstream structures critically involved in brain state regulation. Their activity was correlated with, and indispensable for, both blue light- and sound-induced NREM sleep-to-Wake transition, and their arousing effects were mainly mediated by, but not limited to, the temporal association cortices. ATmVGluT2+ neuron activation in awake behaving mice induced pupil dilation and behavioral responses suggestive of anxiety. Blocking the neurotransmitter release of ATmVGluT2+ neurons receiving auditory inputs selectively abolished loud noise-triggered escape behavior but not locomotion. Thus, the ATm is an interface in mouse brain that can transform alerting environmental cues into internal arousal and emotional state alterations that promote survival.

neuroscience↗

bioRxiv2021

Acute SARS-CoV-2 infection in pregnancy is associated with placental ACE-2 shedding

Human placental tissues have variable rates of SARS-CoV-2 invasion resulting in consistently low rates of fetal transmission suggesting a unique physiologic blockade against SARS-CoV-2. Angiotensin-converting enzyme (ACE)-2, the main receptor for SARS-CoV-2, is expressed as cell surface and soluble forms regulated by a metalloprotease cleavage enzyme, ADAM17. ACE-2 is expressed in the human placenta, but the regulation of placental ACE-2 expression in relation to timing of maternal SARS-CoV-2 infection in pregnancy is not well understood. In this study, we evaluated ACE-2 expression, ADAM17 activity and serum ACE-2 abundance in a cohort of matched villous placental and maternal serum samples from Control pregnancies (SARS-CoV-2 negative, n=8) and pregnancies affected by symptomatic maternal SARS-CoV-2 infections in the 2nd trimester ("2ndTri COVID", n=8) and 3rd trimester ("3rdTri COVID", n=8). In 3rdTri COVID as compared to control and 2ndTri-COVID villous placental tissues ACE-2 mRNA expression was remarkably elevated, however, ACE-2 protein expression was significantly decreased with a parallel increase in ADAM17 activity. Soluble ACE-2 was also significantly increased in the maternal serum from 3rdTri COVID infections as compared to control and 2ndTri-COVID pregnancies. These data suggest that in acute maternal SARS-CoV-2 infections, decreased placental ACE-2 protein may be the result of ACE-2 shedding. Overall, this work highlights the importance of ACE-2 for ongoing studies on SARS-CoV-2 responses at the maternal-fetal interface.

pathology↗

bioRxiv2021

Elevated transcriptional pausing of RNA polymerase II underlies acquired resistance to radiotherapy

As the mainstay modality for many malignancies, particularly inoperable solid tumors such as nasopharyngeal carcinoma (NPC), ionizing radiation (IR) induces a variety of lesions in genomic DNA, evoking a multipronged DNA damage response to interrupt many cellular processes including transcription. The turbulence in transcription, depending on the nature of DNA lesions, encompasses local blockage of RNA polymerase II (RNAPII) near the damage sites, as well as a less understood genome-wide alteration. How the transcriptional change influences the effectiveness of radiotherapy remains unclear. Using a panel of NPC and lung cancer cell lines, we observe increased phosphorylation at serine 5 (pS5) of the RNAPII after IR, indicating an accumulation of paused RNAPII. Remarkably, a similar increase of pS5 is seen in IR-resistant cells. ChIP-seq analysis of RNAPII distribution confirms this increased pausing both in IR-treated and IR-resistant NPC cells, notably on genes involved in radiation response and cell cycle. Accordingly, many of these genes show downregulated transcripts abundance in IR-resistant cells, and individual knockdown some of them such as TP53 and NEK7 endows NPC cells with varying degrees of IR-resistance. Decreasing pS5 of RNAPII and hence tuning down transcriptional pausing by inhibiting CDK7 reverses IR-resistance both in cell culture and xenograft models. Our results therefore uncover an unexpected link between elevated transcriptional pausing and IR-resistance. Given the recurrent NPC tissues display a steady increase in pS5 compared to the paired primary tissues, we suggest that CDK7 inhibitors can be used in combination with radiotherapy to increase sensitivity and thwart resistance.

cancer biology↗

bioRxiv2021

Clock genes Period1 and Period2 in the hippocampal CA1 mediate depression-like behaviors and rapid antidepressant response

Accumulated reports have indicated that circadian rhythm is closely related to the pathogenesis of major depressive disorder (MDD). Recently, adenosine has been identified to modulate circadian clock via adenosine A1 and A2A receptor signaling pathways. Cyclic AMP-response element binding protein (CREB) is a convergent point that plays a critical role in the pathogenesis of depression and is a downstream molecule of adenosine A1 receptor signaling pathway as an endpoint that can regulate the expression of circadian genes Period1 (Per1) and Period2 (Per2). However, whether Per mediates the development of MDD via CREB has not been elucidated. We used chronic unpredictable stress (CUS) to induce depression-like behaviors and found that it could induce decrease in p-CREB and PER1 levels in the hippocampal CA1 region in rats. Both depression-like behaviors and the decreased protein levels could be rapidly rescued by the administration of adenosine A1 receptor agonist 2-Choro-N6-cyclopentyladenosine (CCPA). Furthermore, knockdown of Per1 in hippocampal CA1 region could also induce depression-like behaviors, which could also be rescued by CCPA. Interestingly, Per2 knockdown in hippocampal CA1 region resulted in potential antidepressant-like effect. In addition, knockout of CRE sequence in the promoter regions of either Per1 or Per2 led to depression-like behaviors, which could not be rescued by CCPA. These results indicated that clock genes Per1 and Per2 play critical roles in the pathophysiology of depression and CRE sequences in the promoter regions of Per1 and Per2 may be a critical antidepressant target. HighlightsO_LICUS induces both depression-like behaviors and decreases in the expression of p-CREB and PER1 levels in the hippocampal CA1 region in rats, which can be rapidly rescued by 2-Choro-N6-cyclopentyladenosine (CCPA). C_LIO_LIKnockdown of clock gene Per1 in the hippocampal CA1 brain region leads to depression-like behaviors in rats, which can be also rescued by CCPA. C_LIO_LIKnockdown of clock gene Per2 in the hippocampal CA1 brain region may have potential antidepressant-like effect. C_LIO_LIKnockout of the CRE sequence on the promoter region of the clock genes Per1 and Per2 produces depression-like behaviors, which cannot be rescued by CCPA. C_LI

neuroscience↗

bioRxiv2021

ARID1A loss derepresses human endogenous retrovirus-H to modulate BRD4-dependent transcription

The transposable elements (TEs) through evolutionary exaptation have become an integral part of human genome, offering ample regulatory sequences and shaping chromatin 3D architecture. While the functional impacts of TE-derived sequences on early embryogenesis are recognized, their role in malignancy has only started to emerge. Here we show that many TEs, especially the pluripotency-related endogenous retrovirus H (HERVH), are abnormally activated in colorectal cancer (CRC) samples. The transcriptional upregulation of HERVH is associated with mutations of several tumor suppressors including ARID1A. Knockout of ARID1A in CRC cells leads to increased accessibility at HERVH loci and enhanced transcription, which is dependent on ARID1B. Suppression of HERVH in CRC cells and patient-derived organoids impairs tumor growth. Mechanistically, HERVH transcripts colocalize with nuclear BRD4 foci, modulate their dynamics, and co-regulate many target genes. Altogether, we uncover a critical role for ARID1A in restraining HERVH, which can promote tumorigenesis by stimulating BRD4-dependent transcription when ARID1A is mutated.

cancer biology↗

bioRxiv2021

The Oncoprotein BCL6 Enables Cancer Cells to Evade Genotoxic Stress

Genotoxic agents remain the mainstay of cancer treatment. Unfortunately, the clinical benefits are often countered by a rapid tumor adaptive response. Here, we report that the oncoprotein B cell lymphoma 6 (BCL6) is a core component that confers tumor adaptive resistance to genotoxic stress. Multiple genotoxic agents promoted BCL6 transactivation, which was positively correlated with a weakened therapeutic efficacy and a worse clinical outcome. Mechanistically, we discovered that treatment with the genotoxic agent etoposide led to the transcriptional reprogramming of multiple pro-inflammatory cytokines, among which the interferon- and interferon-{gamma} responses were selectively and substantially enriched in resistant cells. Our results further revealed that the activation of interferon/signal transducer and activator of transcription 1 axis directly upregulated BCL6 expression. The increased expression of BCL6 further repressed the tumor suppressor PTEN and consequently enabled resistant cancer cell survival. Accordingly, targeted inhibition of BCL6 remarkably enhanced etoposide-triggered DNA damage and apoptosis both in vitro and in vivo. Our findings highlight the importance of BCL6 signaling in conquering tumor tolerance to genotoxic stress, further establishing a rationale for a combined approach with genotoxic agents and BCL6-targeted therapy.

cancer biology↗

bioRxiv2021

Variable Induction of Pro-inflammatory Cytokines by Commercial SARS CoV-2 Spike Protein Reagents: Potential Impacts of LPS on In Vitro Modeling and Pathogenic Mechanisms In Vivo

Proinflammatory cytokine production following infection with severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) is associated with poor clinical outcomes. Like SARS CoV-1, SARS CoV-2 enters host cells via its spike protein, which attaches to angiotensin-converting enzyme 2 (ACE2). As SARS CoV-1 spike protein is reported to induce cytokine production, we hypothesized that this pathway could be a shared mechanism underlying pathogenic immune responses. We herein compared the capabilities of Middle East Respiratory Syndrome (MERS), SARS CoV-1 and SARS CoV-2 spike proteins to induce cytokine expression in human peripheral blood mononuclear cells (PBMC). We observed that only specific commercial lots of SARS CoV-2 induce cytokine production. Surprisingly, recombinant SARS CoV-2 spike proteins from different vendors and batches exhibited different patterns of cytokine induction, and these activities were not inhibited by blockade of spike protein-ACE2 binding using either soluble ACE2 or neutralizing anti-S1 antibody. Moreover, commercial spike protein reagents contained varying levels of endotoxin, which correlated directly with their abilities to induce cytokine production. The lipopolysaccharide (LPS) inhibitor, polymyxin B, blocked this cytokine induction activity. In addition, SARS CoV-2 spike protein avidly bound soluble LPS in vitro, rendering it a cytokine inducer. These results not only suggest caution in monitoring the purity of SARS CoV-2 spike protein reagents, but they indicate the possibility that interactions of SARS CoV-2 spike protein with LPS from commensal bacteria in virally infected mucosal tissues could promote pathogenic inflammatory cytokine production.

microbiology↗