Proteomic Signature of Host Response to SARS-CoV-2 Infection in the Nasopharynx

DNA methylation changes during acute COVID-19 are associated with long-term transcriptional dysregulation in patients' airway epithelial cells

Molecular changes underlying the persistent health effects after SARS-CoV-2 infection remain poorly understood. To discern the gene regulatory landscape in the upper respiratory tract of COVID-19 patients, we performed enzymatic DNA methylome and single-cell RNA sequencing in nasal cells of COVID-19 patients (n = 19, scRNA-seq n = 14) and controls (n = 14, scRNA-seq n = 10). In addition, we resampled a subset of these patients for transcriptome analyses at 3 (n = 7) and 12 months (n = 5) post infection and followed the expression of differentially regulated genes over time. Genome-wide DNA methylation analysis revealed 3112 differentially methylated regions between COVID-19 patients and controls. Hypomethylated regions affected immune regulatory genes, while hypermethylated regions were associated with genes governing ciliary function. These genes were not only downregulated in the acute phase of the disease but sustained repressed up to 12 months post infection in ciliated cells. Validation in an independent cohort collected 6 months post infection (n  = 15) indicated symptom-dependent transcriptional repression of ciliary genes. We therefore propose that hypermethylation observed in the acute phase may exert a long-term effect on gene expression, possibly contributing to post-acute COVID-19 sequelae.

Dynamic Gene Attention Focus (DyGAF): Enhancing Biomarker Identification Through Dual-Model Attention Networks

The DyGAF model, which stands for Dynamic Gene Attention Focus, is specifically designed and tailored to address the challenges in biomarker detection, progression reporting of pathogen infection, and disease diagnostics. The DyGAF model introduced a novel dual-model attention-based mechanism within neural networks, combined with machine learning algorithms to enhance the process of biomarker identification. The model transcended traditional diagnostic approaches by meticulously analyzing gene expression data. DyGAF not only identified but also ranked genes based on their significance, revealing a comprehensive list of the top genes essential for disease detection and prognosis. In addition, KEGG pathways, Wiki Pathways, and Gene Ontology-based analyses provided a multileveled evaluation of the genes' roles. In our analyses, we tailored COVID-19 gene expression profile from nasopharyngeal swabs that offer a more nuanced view of the intricate interplay between the host and the virus. The genes ranked by the DyGAF model were compared against those selected by differential expression analysis and random forest feature selection methods for further validation of our model. DyGAF demonstrated its prowess in identifying important biomarkers that could enrich gene ontologies and pathways crucial for elucidating the pathogenesis of COVID-19. Furthermore, DyGAF was also employed for diagnosing COVID-19 patients by classifying gene-expression profiles with an accuracy of 94.23%. Benchmarking against other conventional models revealed DyGAF's superior performance, highlighting its effectiveness in identifying and categorizing COVID-19 cases. In summary, DyGAF model represents a significant advancement in genomic research, providing a more comprehensive and precise tool for identifying key genetic markers and unraveling the complex biological insights of a disease. The DyGAF model is available as a software package at the following link: https://github.com/hiddenntreasure/DyGAF.

Cytosolic nucleic acid sensing as driver of critical illness: mechanisms and advances in therapy

Nucleic acids from both self- and non-self-sources act as vital danger signals that trigger immune responses. Critical illnesses such as acute respiratory distress syndrome, sepsis, trauma and ischemia lead to the aberrant cytosolic accumulation and massive release of nucleic acids that are detected by antiviral innate immune receptors in the endosome or cytosol. Activation of receptors for deoxyribonucleic acids and ribonucleic acids triggers inflammation, a major contributor to morbidity and mortality in critically ill patients. In the past decade, there has been growing recognition of the therapeutic potential of targeting nucleic acid sensing in critical care. This review summarizes current knowledge of nucleic acid sensing in acute respiratory distress syndrome, sepsis, trauma and ischemia. Given the extensive research on nucleic acid sensing in common pathological conditions like cancer, autoimmune disorders, metabolic disorders and aging, we provide a comprehensive summary of nucleic acid sensing beyond critical illness to offer insights that may inform its role in critical conditions. Additionally, we discuss potential therapeutic strategies that specifically target nucleic acid sensing. By examining nucleic acid sources, sensor activation and function, as well as the impact of regulating these pathways across various acute diseases, we highlight the driving role of nucleic acid sensing in critical illness.

SARS-CoV-2 disrupts host gene networks: Unveiling key hub genes as potential therapeutic targets for COVID-19 management

PURPOSE

Although the end of COVID-19 as a public health emergency was declared on May 2023, still new cases of the infection are reported and the risk remains of new variants emerging that may cause new surges in cases and deaths. While clinical symptoms have been rapidly defined worldwide, the basic body responses and pathogenetic mechanisms acting in patients with SARS-CoV-2 infection over time until recovery or death require further investigation. The understanding of the molecular mechanisms underlying the development and course of the disease is essential in designing effective preventive and therapeutic approaches, and ultimately reducing mortality and disease spreading.

METHODS

The current investigation aimed to identify the key genes engaged in SARS-CoV-2 infection. To achieve this goal high-throughput RNA sequencing of peripheral blood samples collected from healthy donors and COVID-19 patients was performed. The resulting sequence data were processed using a wide range of bioinformatics tools to obtain detailed modifications within five transcriptomic phenomena: expression of genes and long non-coding RNAs, alternative splicing, allel-specific expression and circRNA production. The in silico procedure was completed with a functional analysis of the identified alterations.

RESULTS

The transcriptomic analysis revealed that SARS-CoV-2 has a significant impact on multiple genes encoding ribosomal proteins (RPs). Results show that these genes differ not only in terms of expression but also manifest biases in alternative splicing and ASE ratios. The integrated functional analysis exposed that RPs mostly affected pathways and processes related to infection-COVID-19 and NOD-like receptor signaling pathway, SARS-CoV-2-host interactions and response to the virus. Furthermore, our results linked the multiple intronic ASE variants and exonic circular RNA differentiations with SARS-CoV-2 infection, suggesting that these molecular events play a crucial role in mRNA maturation and transcription during COVID-19 disease.

CONCLUSIONS

By elucidating the genetic mechanisms induced by the virus, the current research provides significant information that can be employed to create new targeted therapeutic strategies for future research and treatment related to COVID-19. Moreover, the findings highlight potentially promising therapeutic biomarkers for early risk assessment of critically ill patients.

Brain-wide alterations revealed by spatial transcriptomics and proteomics in COVID-19 infection

Understanding the pathophysiology of neurological symptoms observed after severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection is essential to optimizing outcomes and therapeutics. To date, small sample sizes and narrow molecular profiling have limited the generalizability of findings. In this study, we profiled multiple cortical and subcortical regions in postmortem brains of patients with coronavirus disease 2019 (COVID-19) and controls with matched pulmonary pathology (total n = 42) using spatial transcriptomics, bulk gene expression and proteomics. We observed a multi-regional antiviral response without direct active SARS-CoV2 infection. We identified dysregulation of mitochondrial and synaptic pathways in deep-layer excitatory neurons and upregulation of neuroinflammation in glia, consistent across both mRNA and protein. Remarkably, these alterations overlapped substantially with changes in age-related neurodegenerative diseases, including Parkinson's disease and Alzheimer's disease. Our work, combining multiple experimental and analytical methods, demonstrates the brain-wide impact of severe acute/subacute COVID-19, involving both cortical and subcortical regions, shedding light on potential therapeutic targets within pathways typically associated with pathological aging and neurodegeneration.

Interferon-stimulated genes and their antiviral activity against SARS-CoV-2

The coronavirus disease 2019 (COVID-19) pandemic remains an international health problem caused by the recent emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As of May 2024, SARS-CoV-2 has caused more than 775 million cases and over 7 million deaths globally. Despite current vaccination programs, infections are still rapidly increasing, mainly due to the appearance and spread of new variants, variations in immunization rates, and limitations of current vaccines in preventing transmission. This underscores the need for pan-variant antivirals and treatments. The interferon (IFN) system is a critical element of the innate immune response and serves as a frontline defense against viruses. It induces a generalized antiviral state by transiently upregulating hundreds of IFN-stimulated genes (ISGs). To gain a deeper comprehension of the innate immune response to SARS-CoV-2, its connection to COVID-19 pathogenesis, and the potential therapeutic implications, this review provides a detailed overview of fundamental aspects of the diverse ISGs identified for their antiviral properties against SARS-CoV-2. It emphasizes the importance of these proteins in controlling viral replication and spread. Furthermore, we explore methodological approaches for the identification of ISGs and conduct a comparative analysis with other viruses. Deciphering the roles of ISGs and their interactions with viral pathogens can help identify novel targets for antiviral therapies and enhance our preparedness to confront current and future viral threats.

SARS-CoV-2 and UPS with potentials for therapeutic interventions

The Ubiquitin proteasome system (UPS), an essential eukaryotic/host/cellular post-translational modification (PTM), plays a critical role in the regulation of diverse cellular functions including regulation of protein stability, immune signaling, antiviral activity, as well as virus replication. Although UPS regulation of viral proteins may be utilized by the host as a defense mechanism to invade viruses, viruses may have adapted to take advantage of the host UPS. This system can be manipulated by viruses such as the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) to stimulate various steps of the viral replication cycle and facilitate pathogenesis, thereby causing the respiratory disease COVID-19. Many SARS-CoV-2 encoded proteins including open reading frame 3a (ORF3a), ORF6, ORF7a, ORF9b, and ORF10 interact with the host's UPS machinery, influencing host immune signaling and apoptosis. Moreover, SARS-CoV-2 encoded papain-like protease (PLpro) interferes with the host UPS to facilitate viral replication and to evade the host's immune system. These alterations in SARS-CoV-2 infected cells have been revealed by various proteomic studies, suggesting potential targets for clinical treatment. To provide insight into the underlying causes of COVID-19 and suggest possible directions for therapeutic interventions, this paper reviews the intricate relationship between SARS-CoV-2 and UPS. Promising treatment strategies are also investigated in this paper including targeting PLpro with zinc-ejector drugs, as well as targeting viral non-structural protein (nsp12) via heat treatment associated ubiquitin-mediated proteasomal degradation to reduce viral pathogenesis.

SARS-CoV-2 mitochondrial metabolic and epigenomic reprogramming in COVID-19

To determine the effects of SARS-CoV-2 infection on cellular metabolism, we conducted an exhaustive survey of the cellular metabolic pathways modulated by SARS-CoV-2 infection and confirmed their importance for SARS-CoV-2 propagation by cataloging the effects of specific pathway inhibitors. This revealed that SARS-CoV-2 strongly inhibits mitochondrial oxidative phosphorylation (OXPHOS) resulting in increased mitochondrial reactive oxygen species (mROS) production. The elevated mROS stabilizes HIF-1α which redirects carbon molecules from mitochondrial oxidation through glycolysis and the pentose phosphate pathway (PPP) to provide substrates for viral biogenesis. mROS also induces the release of mitochondrial DNA (mtDNA) which activates innate immunity. The restructuring of cellular energy metabolism is mediated in part by SARS-CoV-2 Orf8 and Orf10 whose expression restructures nuclear DNA (nDNA) and mtDNA OXPHOS gene expression. These viral proteins likely alter the epigenome, either by directly altering histone modifications or by modulating mitochondrial metabolite substrates of epigenome modification enzymes, potentially silencing OXPHOS gene expression and contributing to long-COVID.

A complement C4-derived glycopeptide is a biomarker for PMM2-CDG

BACKGROUNDDiagnosis of PMM2-CDG, the most common congenital disorder of glycosylation (CDG), relies on measuring carbohydrate-deficient transferrin (CDT) and genetic testing. CDT tests have false negatives and may normalize with age. Site-specific changes in protein N-glycosylation have not been reported in sera in PMM2-CDG.METHODSUsing multistep mass spectrometry-based N-glycoproteomics, we analyzed sera from 72 individuals to discover and validate glycopeptide alterations. We performed comprehensive tandem mass tag-based discovery experiments in well-characterized patients and controls. Next, we developed a method for rapid profiling of additional samples. Finally, targeted mass spectrometry was used for validation in an independent set of samples in a blinded fashion.RESULTSOf the 3,342 N-glycopeptides identified, patients exhibited decrease in complex-type N-glycans and increase in truncated, mannose-rich, and hybrid species. We identified a glycopeptide from complement C4 carrying the glycan Man5GlcNAc2, which was not detected in controls, in 5 patients with normal CDT results, including 1 after liver transplant and 2 with a known genetic variant associated with mild disease, indicating greater sensitivity than CDT. It was detected by targeted analysis in 2 individuals with variants of uncertain significance in PMM2.CONCLUSIONComplement C4-derived Man5GlcNAc2 glycopeptide could be a biomarker for accurate diagnosis and therapeutic monitoring of patients with PMM2-CDG and other CDGs.FUNDINGU54NS115198 (Frontiers in Congenital Disorders of Glycosylation: NINDS; NCATS; Eunice Kennedy Shriver NICHD; Rare Disorders Consortium Disease Network); K08NS118119 (NINDS); Minnesota Partnership for Biotechnology and Medical Genomics; Rocket Fund; R01DK099551 (NIDDK); Mayo Clinic DERIVE Office; Mayo Clinic Center for Biomedical Discovery; IA/CRC/20/1/600002 (Center for Rare Disease Diagnosis, Research and Training; DBT/Wellcome Trust India Alliance).

Protein Quality Control Systems and ER Stress as Key Players in SARS-CoV-2-Induced Neurodegeneration

The COVID-19 pandemic has brought to the forefront the intricate relationship between SARS-CoV-2 and its impact on neurological complications, including potential links to neurodegenerative processes, characterized by a dysfunction of the protein quality control systems and ER stress. This review article explores the role of protein quality control systems, such as the Unfolded Protein Response (UPR), the Endoplasmic Reticulum-Associated Degradation (ERAD), the Ubiquitin-Proteasome System (UPS), autophagy and the molecular chaperones, in SARS-CoV-2 infection. Our hypothesis suggests that SARS-CoV-2 produces ER stress and exploits the protein quality control systems, leading to a disruption in proteostasis that cannot be solved by the host cell. This disruption culminates in cell death and may represent a link between SARS-CoV-2 and neurodegeneration.

Proteomics-based mass spectrometry profiling of SARS-CoV-2 infection from human nasopharyngeal samples

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the on-going global pandemic of coronavirus disease 2019 (COVID-19) that continues to pose a significant threat to public health worldwide. SARS-CoV-2 encodes four structural proteins namely membrane, nucleocapsid, spike, and envelope proteins that play essential roles in viral entry, fusion, and attachment to the host cell. Extensively glycosylated spike protein efficiently binds to the host angiotensin-converting enzyme 2 initiating viral entry and pathogenesis. Reverse transcriptase polymerase chain reaction on nasopharyngeal swab is the preferred method of sample collection and viral detection because it is a rapid, specific, and high-throughput technique. Alternate strategies such as proteomics and glycoproteomics-based mass spectrometry enable a more detailed and holistic view of the viral proteins and host-pathogen interactions and help in detection of potential disease markers. In this review, we highlight the use of mass spectrometry methods to profile the SARS-CoV-2 proteome from clinical nasopharyngeal swab samples. We also highlight the necessity for a comprehensive glycoproteomics mapping of SARS-CoV-2 from biological complex matrices to identify potential COVID-19 markers.

CoVProt: Toward a Mass Spectrometry Data Portal for COVID-19 Proteomics Research and Development

The coronavirus disease 2019 (COVID-19) pandemic has wreaked havoc globally. Beyond the pandemic, the long-term effects of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in multiple organ systems are yet to be deciphered. This calls for continued systems science research. Moreover, the host response to SARS-CoV-2 varies person-to-person and gives rise to different degrees of morbidity and mortality. Mass spectrometry (MS) has been a proven asset in studies of the SARS-CoV-2 from an omics systems science lens. To strengthen the proteomics research dedicated to COVID-19, we introduce here a web-based portal, CoVProt. The portal is work in progress and aims for a comprehensive curation of MS-based proteomics data of COVID-19 clinical samples for deep proteomic investigations, data visualization, and easy data accessibility for life sciences innovations and planetary health research community. Currently, CoVProt contains information on 2725 different proteins and 37,125 different peptides from six data sets covering a total of 202 clinical samples. Moreover, all pertinent data sets extracted from the literature have been reanalyzed using a common analysis pipeline developed by combining multiple tools. Going forward, we anticipate that the CoVProt portal will also provide access to the clinical parameters of the patients. The CoVProt (v1.0) portal addresses an existing significant gap to study COVID-19 host proteomics, which, to the best of our knowledge, is the first effort in this direction. We believe that CoVProt is poised to make contributions as a community resource for proteomic applications and aims to broadly support clinical studies to facilitate the discovery of COVID-19 biomarkers and therapeutics with translational potential.

Leishmania infection upregulates and engages host macrophage Argonaute 1, and system-wide proteomics reveals Argonaute 1-dependent host response

Leishmania donovani, an intracellular protozoan parasite, is the causative agent of visceral leishmaniasis, the most severe form of leishmaniasis in humans. It is becoming increasingly clear that several intracellular pathogens target host cell RNA interference (RNAi) pathways to promote their survival. Complexes of Argonaute proteins with small RNAs are core components of the RNAi. In this study, we investigated the potential role of host macrophage Argonautes in Leishmania pathogenesis. Using Western blot analysis of Leishmania donovani-infected macrophages, we show here that Leishmania infection selectively increased the abundance of host Argonaute 1 (Ago1). This increased abundance of Ago1 in infected cells also resulted in higher levels of Ago1 in active Ago-complexes, suggesting the preferred use of Ago1 in RNAi in Leishmania-infected cells. This analysis used a short trinucleotide repeat containing 6 (TNRC6)/glycine-tryptophan repeat protein (GW182) protein-derived peptide fused to Glutathione S-transferase as an affinity matrix to capture mature Ago-small RNAs complexes from the cytosol of non-infected and Leishmania-infected cells. Furthermore, Ago1 silencing significantly reduced intracellular survival of Leishmania, demonstrating that Ago1 is essential for Leishmania pathogenesis. To investigate the role of host Ago1 in Leishmania pathogenesis, a quantitative whole proteome approach was employed, which showed that expression of several previously reported Leishmania pathogenesis-related proteins was dependent on the level of macrophage Ago1. Together, these findings identify Ago1 as the preferred Argonaute of RNAi machinery in infected cells and a novel and essential virulence factor by proxy that promotes Leishmania survival.

Investigation of the Host Kinome Response to Coronavirus Infection Reveals PI3K/mTOR Inhibitors as Betacoronavirus Antivirals

Host kinases play essential roles in the host cell cycle, innate immune signaling, the stress response to viral infection, and inflammation. Previous work has demonstrated that coronaviruses specifically target kinase cascades to subvert host cell responses to infection and rely upon host kinase activity to phosphorylate viral proteins to enhance replication. Given the number of kinase inhibitors that are already FDA approved to treat cancers, fibrosis, and other human disease, they represent an attractive class of compounds to repurpose for host-targeted therapies against emerging coronavirus infections. To further understand the host kinome response to betacoronavirus infection, we employed multiplex inhibitory bead mass spectrometry (MIB-MS) following MERS-CoV and SARS-CoV-2 infection of human lung epithelial cell lines. Our MIB-MS analyses revealed activation of mTOR and MAPK signaling following MERS-CoV and SARS-CoV-2 infection, respectively. SARS-CoV-2 host kinome responses were further characterized using paired phosphoproteomics, which identified activation of MAPK, PI3K, and mTOR signaling. Through chemogenomic screening, we found that clinically relevant PI3K/mTOR inhibitors were able to inhibit coronavirus replication at nanomolar concentrations similar to direct-acting antivirals. This study lays the groundwork for identifying broad-acting, host-targeted therapies to reduce betacoronavirus replication that can be rapidly repurposed during future outbreaks and epidemics. The proteomics, phosphoproteomics, and MIB-MS datasets generated in this study are available in the Proteomics Identification Database (PRIDE) repository under project identifiers PXD040897 and PXD040901.

Automated Sample Preparation Workflow for Tandem Mass Tag-Based Proteomics

Although tandem mass tag (TMT)-based isobaric labeling has become a powerful approach for multiplexed protein quantitation, automating the workflow for this technique has not been easy to achieve for widespread adoption. This is because preparation of TMT-labeled peptide samples involves multiple steps ranging from protein extraction, denaturation, reduction, and alkylation to tryptic digestion, desalting, labeling, and cleanup, all of which require a high level of proficiency. The variability resulting from multiple processing steps is inherently problematic, especially with large-scale clinical studies that involve hundreds of samples where reproducibility is critical for quantitation. Here, we sought to compare the performance of a recently introduced platform, AccelerOme, for an automated proteomic workflow employing TMT labeling with the manual processing of samples. Cell pellets were prepared and subjected to a 16-plex experiment using an automated platform and a conventional manual protocol. Single-shot liquid chromatography with tandem mass spectrometry analysis revealed a higher number of proteins and peptides identified using the automated platform. Efficiency of tryptic digestion, alkylation, and TMT labeling were similar in both manual and automated processes. In addition, comparison of quantitation accuracy and precision showed similar performance in an automated workflow compared to manual sample preparation by an expert. Overall, we demonstrated that the automated platform performs at a level similar to a manual process performed by an expert for TMT-based proteomics. We anticipate that this automated workflow will increasingly replace manual pipelines and has the potential to be applied to large-scale TMT-based studies, providing robust results and high sample throughput.

Mass spectrometry-based proteomic profiling of sonicate fluid differentiates Staphylococcus aureus periprosthetic joint infection from non-infectious failure: A pilot study

PURPOSE

This pilot study aimed to use proteomic profiling of sonicate fluid samples to compare host response during Staphylococcus aureus-associated periprosthetic joint infection (PJI) and non-infected arthroplasty failure (NIAF) and identify potential novel biomarkers differentiating the two.

EXPERIMENTAL DESIGN

In this pilot study, eight sonicate fluid samples (four from NIAF and four from S. aureus PJI) were studied. Samples were reduced, alkylated, and trypsinized overnight, followed by analysis using liquid chromatography-tandem mass spectrometry (LC-MS/MS) on a high-resolution Orbitrap Eclipse mass spectrometer. MaxQuant software suite was used for protein identification, filtering, and label-free quantitation.

RESULTS

Principal component analysis of the identified proteins clearly separated S. aureus PJI and NIAF samples. Overall, 810 proteins were identified based on their detection in at least three out of four samples from each group; 35 statistically significant differentially abundant proteins (DAPs) were found (two-sample t-test p-values ≤0.05 and log2 fold-change values ≥2 or ≤-2). Gene ontology pathway analysis found that microbial defense responses, specifically those related to neutrophil activation, to be increased in S. aureus PJI compared to NIAF samples.

CONCLUSION AND CLINICAL RELEVANCE

Proteomic profiling of sonicate fluid using LC-MS/MS differentiated S. aureus PJI and NIAF in this pilot study. Further work is needed using a larger sample size and including non-S. aureus PJI and a diversty of NIAF-types.

COVIDpro: Database for Mining Protein Dysregulation in Patients with COVID-19

The ongoing pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 still has limited treatment options. Our understanding of the molecular dysregulations that occur in response to infection remains incomplete. We developed a web application COVIDpro (https://www.guomics.com/covidPro/) that includes proteomics data obtained from 41 original studies conducted in 32 hospitals worldwide, involving 3077 patients and covering 19 types of clinical specimens, predominantly plasma and serum. The data set encompasses 53 protein expression matrices, comprising a total of 5434 samples and 14,403 unique proteins. We identified a panel of proteins that exhibit significant dysregulation, enabling the classification of COVID-19 patients into severe and non-severe disease categories. The proteomic signatures achieved promising results in distinguishing severe cases, with a mean area under the curve of 0.87 and accuracy of 0.80 across five independent test sets. COVIDpro serves as a valuable resource for testing hypotheses and exploring potential targets for novel treatments in COVID-19 patients.

Role of E3 ubiquitin ligases and deubiquitinating enzymes in SARS-CoV-2 infection

Ever since its emergence in 2019, COVID-19 has rapidly disseminated worldwide, engendering a pervasive pandemic that has profoundly impacted healthcare systems and the socio-economic milieu. A plethora of studies has been conducted targeting its pathogenic virus, SARS-CoV-2, to find ways to combat COVID-19. The ubiquitin-proteasome system (UPS) is widely recognized as a crucial mechanism that regulates human biological activities by maintaining protein homeostasis. Within the UPS, the ubiquitination and deubiquitination, two reversible modifications, of substrate proteins have been extensively studied and implicated in the pathogenesis of SARS-CoV-2. The regulation of E3 ubiquitin ligases and DUBs(Deubiquitinating enzymes), which are key enzymes involved in the two modification processes, determines the fate of substrate proteins. Proteins associated with the pathogenesis of SARS-CoV-2 may be retained, degraded, or even activated, thus affecting the ultimate outcome of the confrontation between SARS-CoV-2 and the host. In other words, the clash between SARS-CoV-2 and the host can be viewed as a battle for dominance over E3 ubiquitin ligases and DUBs, from the standpoint of ubiquitin modification regulation. This review primarily aims to clarify the mechanisms by which the virus utilizes host E3 ubiquitin ligases and DUBs, along with its own viral proteins that have similar enzyme activities, to facilitate invasion, replication, escape, and inflammation. We believe that gaining a better understanding of the role of E3 ubiquitin ligases and DUBs in COVID-19 can offer novel and valuable insights for developing antiviral therapies.

Quantification of host proteomic responses to genotype 4 hepatitis E virus replication facilitated by pregnancy serum

BACKGROUND

Hepatitis E virus (HEV) infection is a common cause of acute hepatitis worldwide and causes approximately 30% case fatality rate among pregnant women. Pregnancy serum (PS), which contains a high concentration of estradiol, facilitates HEV replication in vitro through the suppression of the PI3K-AKT-mTOR and cAMPK-PKA-CREB signaling pathways. However, the proteomics of the complex host responses to HEV infection, especially how PS facilitates viral replication, remains unclear.

METHODS

In this study, the differences in the proteomics of HEV-infected HepG2 cells supplemented with fetal bovine serum (FBS) from those of HEV-infected HepG2 cells supplemented with serum from women in their third trimester of pregnancy were quantified by using isobaric tags for relative and absolute quantification technology.

RESULTS

A total of 1511 proteins were identified, among which 548 were defined as differentially expressed proteins (DEPs). HEV-infected cells supplemented with PS exhibited the most significant changes at the protein level. A total of 328 DEPs, including 66 up-regulated and 262 down-regulated proteins, were identified in HEV-infected cells supplemented with FBS, whereas 264 DEPs, including 201 up-regulated and 63 down-regulated proteins, were found in HEV-infected cells supplemented with PS. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that in HEV-infected cells, PS supplementation adjusted more host genes and signaling pathways than FBS supplementation. The DEPs involved in virus-host interaction participated in complex interactions, especially a large number of immune-related protein emerged in HEV-infected cells supplemented with PS. Three significant or interesting proteins, including filamin-A, thioredoxin, and cytochrome c, in HEV-infected cells were functionally verified.

CONCLUSIONS

The results of this study provide new and comprehensive insight for exploring virus-host interactions and will benefit future studies on the pathogenesis of HEV in pregnant women.

Proteomic Investigation of COVID-19 Severity During the Tsunamic Second Wave in Mumbai

Maharashtra was severely affected during the noxious second wave of COVID-19, with the highest number of cases recorded across India. The emergence of new symptoms and dysregulation of multiple organs resulted in high disease severity during the second wave which led to increased difficulties in understanding the molecular mechanisms behind the disease pathology. Exploring the underlying factors can help to relieve the burden on the medical communities to some extent by prioritizing the patients and, at the same time, opening avenues for improved treatments. In the current study, we have performed a mass-spectrometry-based proteomic analysis to investigate the disease pathology using nasopharyngeal swab samples collected from the COVID-19 patients in the Mumbai region of Maharashtra over the period of March-June 2021, the peak of the second wave. A total of 59 patients, including 32 non-severe and 27 severe cases, were considered for this proteomic study. We identified 23 differentially regulated proteins in severe patients as a host response to infection. In addition to the previously identified innate mechanisms of neutrophil and platelet degranulation, this study revealed significant alterations of anti-microbial peptide pathways in severe conditions, illustrating its role in the severity of the infectious strain of COVID-19 during the second wave. Furthermore, myeloperoxidase, cathepsin G, and profilin-1 were identified as potential therapeutic targets of the FDA-approved drugs dabrafenib, ZINC4097343, and ritonavir. This study has enlightened the role of the anti-microbial peptide pathway associated with the second wave in India and proposed its importance in potential therapeutics for COVID-19.

Multi-OMICs landscape of SARS-CoV-2-induced host responses in human lung epithelial cells

COVID-19 pandemic continues to remain a global health concern owing to the emergence of newer variants. Several multi-Omics studies have produced extensive evidence on host-pathogen interactions and potential therapeutic targets. Nonetheless, an increased understanding of host signaling networks regulated by post-translational modifications and their ensuing effect on the cellular dynamics is critical to expanding the current knowledge on SARS-CoV-2 infections. Through an unbiased transcriptomics, proteomics, acetylomics, phosphoproteomics, and exometabolome analysis of a lung-derived human cell line, we show that SARS-CoV-2 Norway/Trondheim-S15 strain induces time-dependent alterations in the induction of type I IFN response, activation of DNA damage response, dysregulated Hippo signaling, among others. We identified interplay of phosphorylation and acetylation dynamics on host proteins and its effect on the altered release of metabolites, especially organic acids and ketone bodies. Together, our findings serve as a resource of potential targets that can aid in designing novel host-directed therapeutic strategies.

COVIDpro: Database for mining protein dysregulation in patients with COVID-19

Background

The ongoing pandemic of the coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) still has limited treatment options partially due to our incomplete understanding of the molecular dysregulations of the COVID-19 patients. We aimed to generate a repository and data analysis tools to examine the modulated proteins underlying COVID-19 patients for the discovery of potential therapeutic targets and diagnostic biomarkers.

Methods

We built a web server containing proteomic expression data from COVID-19 patients with a toolset for user-friendly data analysis and visualization. The web resource covers expert-curated proteomic data from COVID-19 patients published before May 2022. The data were collected from ProteomeXchange and from select publications via PubMed searches and aggregated into a comprehensive dataset. Protein expression by disease subgroups across projects was compared by examining differentially expressed proteins. We also visualize differentially expressed pathways and proteins. Moreover, circulating proteins that differentiated severe cases were nominated as predictive biomarkers.

Findings

We built and maintain a web server COVIDpro ( https://www.guomics.com/covidPro/ ) containing proteomics data generated by 41 original studies from 32 hospitals worldwide, with data from 3077 patients covering 19 types of clinical specimens, the majority from plasma and sera. 53 protein expression matrices were collected, for a total of 5434 samples and 14,403 unique proteins. Our analyses showed that the lipopolysaccharide-binding protein, as identified in the majority of the studies, was highly expressed in the blood samples of patients with severe disease. A panel of significantly dysregulated proteins was identified to separate patients with severe disease from non-severe disease. Classification of severe disease based on these proteomic signatures on five test sets reached a mean AUC of 0.87 and ACC of 0.80.

Interpretation

COVIDpro is an online database with an integrated analysis toolkit. It is a unique and valuable resource for testing hypotheses and identifying proteins or pathways that could be targeted by new treatments of COVID-19 patients.

Funding

National Key R&D Program of China: Key PDPM technologies (2021YFA1301602, 2021YFA1301601, 2021YFA1301603), Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars (LR19C050001), Hangzhou Agriculture and Society Advancement Program (20190101A04), National Natural Science Foundation of China (81972492) and National Science Fund for Young Scholars (21904107), National Resource for Network Biology (NRNB) from the National Institute of General Medical Sciences (NIGMS-P41 GM103504).

Research in context

Evidence before this study: Although an increasing number of therapies against COVID-19 are being developed, they are still insufficient, especially with the rise of new variants of concern. This is partially due to our incomplete understanding of the disease’s mechanisms. As data have been collected worldwide, several questions are now worth addressing via meta-analyses. Most COVID-19 drugs function by targeting or affecting proteins. Effectiveness and resistance to therapeutics can be effectively assessed via protein measurements. Empowered by mass spectrometry-based proteomics, protein expression has been characterized in a variety of patient specimens, including body fluids (e.g., serum, plasma, urea) and tissue (i.e., formalin-fixed and paraffin-embedded (FFPE)). We expert-curated proteomic expression data from COVID-19 patients published before May 2022, from the largest proteomic data repository ProteomeXhange as well as from literature search engines. Using this resource, a COVID-19 proteome meta-analysis could provide useful insights into the mechanisms of the disease and identify new potential drug targets.Added value of this study: We integrated many published datasets from patients with COVID-19 from 11 nations, with over 3000 patients and more than 5434 proteome measurements. We collected these datasets in an online database, and generated a toolbox to easily explore, analyze, and visualize the data. Next, we used the database and its associated toolbox to identify new proteins of diagnostic and therapeutic value for COVID-19 treatment. In particular, we identified a set of significantly dysregulated proteins for distinguishing severe from non-severe patients using serum samples.Implications of all the available evidence: COVIDpro will support the navigation and analysis of patterns of dysregulated proteins in various COVID-19 clinical specimens for identification and verification of protein biomarkers and potential therapeutic targets.

IL4I1 binds to TMPRSS13 and competes with SARS-CoV-2 spike

The secreted enzyme interleukin four-induced gene 1 (IL4I1) is involved in the negative control of the adaptive immune response. IL4I1 expression in human cancer is frequent and correlates with poor survival and resistance to immunotherapy. Nevertheless, its mechanism of action remains partially unknown. Here, we identified transmembrane serine protease 13 (TMPRSS13) as an immune cell-expressed surface protein that binds IL4I1. TMPRSS13 is a paralog of TMPRSS2, of which the protease activity participates in the cleavage of SARS-CoV-2 spike protein and facilitates virus induced-membrane fusion. We show that TMPRSS13 is expressed by human lymphocytes, monocytes and monocyte-derived macrophages, can cleave the spike protein and allow SARS-CoV-2 spike pseudotyped virus entry into cells. We identify regions of homology between IL4I1 and spike and demonstrate competition between the two proteins for TMPRSS13 binding. These findings may be relevant for both interfering with SARS-CoV-2 infection and limiting IL4I1-dependent immunosuppressive activity in cancer.

Development of a multiomics model for identification of predictive biomarkers for COVID-19 severity: a retrospective cohort study

BACKGROUND

COVID-19 is a multi-system disorder with high variability in clinical outcomes among patients who are admitted to hospital. Although some cytokines such as interleukin (IL)-6 are believed to be associated with severity, there are no early biomarkers that can reliably predict patients who are more likely to have adverse outcomes. Thus, it is crucial to discover predictive markers of serious complications.

METHODS

In this retrospective cohort study, we analysed samples from 455 participants with COVID-19 who had had a positive SARS-CoV-2 RT-PCR result between April 14, 2020, and Dec 1, 2020 and who had visited one of three Mayo Clinic sites in the USA (Minnesota, Arizona, or Florida) in the same period. These participants were assigned to three subgroups depending on disease severity as defined by the WHO ordinal scale of clinical improvement (outpatient, severe, or critical). Our control cohort comprised of 182 anonymised age-matched and sex-matched plasma samples that were available from the Mayo Clinic Biorepository and banked before the COVID-19 pandemic. We did a deep profiling of circulatory cytokines and other proteins, lipids, and metabolites from both cohorts. Most patient samples were collected before, or around the time of, hospital admission, representing ideal samples for predictive biomarker discovery. We used proximity extension assays to quantify cytokines and circulatory proteins and tandem mass spectrometry to measure lipids and metabolites. Biomarker discovery was done by applying an AutoGluon-tabular classifier to a multiomics dataset, producing a stacked ensemble of cutting-edge machine learning algorithms. Global proteomics and glycoproteomics on a subset of patient samples with matched pre-COVID-19 plasma samples was also done.

FINDINGS

We quantified 1463 cytokines and circulatory proteins, along with 902 lipids and 1018 metabolites. By developing a machine-learning-based prediction model, a set of 102 biomarkers, which predicted severe and clinical COVID-19 outcomes better than the traditional set of cytokines, were discovered. These predictive biomarkers included several novel cytokines and other proteins, lipids, and metabolites. For example, altered amounts of C-type lectin domain family 6 member A (CLEC6A), ether phosphatidylethanolamine (P-18:1/18:1), and 2-hydroxydecanoate, as reported here, have not previously been associated with severity in COVID-19. Patient samples with matched pre-COVID-19 plasma samples showed similar trends in muti-omics signatures along with differences in glycoproteomics profile.

INTERPRETATION

A multiomic molecular signature in the plasma of patients with COVID-19 before being admitted to hospital can be exploited to predict a more severe course of disease. Machine learning approaches can be applied to highly complex and multidimensional profiling data to reveal novel signatures of clinical use. The absence of validation in an independent cohort remains a major limitation of the study.

FUNDING

Eric and Wendy Schmidt.

SARS-CoV-2-positive patients display considerable differences in proteome diversity in urine, nasopharyngeal, gargle solution and bronchoalveolar lavage fluid samples

Proteome profile changes post-severe acute respiratory syndrome coronavirus 2 (post-SARS-CoV-2) infection in different body sites of humans remains an active scientific investigation whose solutions stand a chance of providing more information on what constitutes SARS-CoV-2 pathogenesis. While proteomics has been used to understand SARS-CoV-2 pathogenesis, there are limited data about the status of proteome profile in different human body sites infected by the SARS-CoV-2 virus. To bridge this gap, our study aims to characterize the proteins secreted in urine, bronchoalveolar lavage fluid (BALF), gargle solution, and nasopharyngeal samples and assess the proteome differences in these body samples collected from SARS-CoV-2-positive patients. We downloaded publicly available proteomic data from (https://www.ebi.ac.uk/pride/). The data we downloaded had the following identifiers: (i) PXD019423, n = 3 from Charles Tanford Protein Center in Germany. (ii) IPX0002166000, n = 15 from Beijing Proteome Research Centre, China. (iii) IPX0002429000, n = 5 from Huazhong University of Science and Technology, China, and (iv) PXD022889, n = 18 from Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905 USA. MaxQuant was used for the human peptide spectral matching using human and SARS-CoV-2 proteome database which we downloaded from the UniProt database (access date 13^th October 2021). The individuals infected with SARS-CoV-2 viruses displayed a different proteome diversity from the different body sites we investigated. Overally, we identified 1809 proteins across the four sample types we compared. Urine and BALF samples had significantly more abundant SARS-CoV-2 proteins than the other body sites we compared. Urine samples had 257(33.7%) unique proteins, followed by nasopharyngeal with 250(32.8%) unique proteins. Gargle solution and BALF had 38(5%) and 73(9.6%) unique proteins respectively. Urine, gargle solution, nasopharyngeal, and bronchoalveolar lavage fluid samples have different protein diversity in individuals infected with SARS-CoV-2. Moreover, our data also demonstrated that a given body site is characterized by a unique set of proteins in SARS-CoV-2 seropositive individuals.