Identification of Robust Protein Associations With COVID-19 Disease Based on Five Clinical Studies

Identification of soluble biomarkers that associate with distinct manifestations of long COVID

Long coronavirus disease (COVID) is a heterogeneous clinical condition of uncertain etiology triggered by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Here we used ultrasensitive approaches to profile the immune system and the plasma proteome in healthy convalescent individuals and individuals with long COVID, spanning geographically independent cohorts from Sweden and the United Kingdom. Symptomatic disease was not consistently associated with quantitative differences in immune cell lineage composition or antiviral T cell immunity. Healthy convalescent individuals nonetheless exhibited higher titers of neutralizing antibodies against SARS-CoV-2 than individuals with long COVID, and extensive phenotypic analyses revealed a subtle increase in the expression of some co-inhibitory receptors, most notably PD-1 and TIM-3, among SARS-CoV-2 nonspike-specific CD8+ T cells in individuals with long COVID. We further identified a shared plasma biomarker signature of disease linking breathlessness with apoptotic inflammatory networks centered on various proteins, including CCL3, CD40, IKBKG, IL-18 and IRAK1, and dysregulated pathways associated with cell cycle progression, lung injury and platelet activation, which could potentially inform the diagnosis and treatment of long COVID.

Possible involvement of neuropeptide Y sub-receptor 1 (NPY-Y1) in the anti-viral response of SARS-CoV-2 infection in Syrian hamster

Co-administration of Molnupiravir and Remdesivir, treatments for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), inhibits viral replication and infectivity. Previous studies indicate that the neuropeptide Y sub-receptor 1 (NPY-Y1) is involved in influenza virus aggravation in mouse pulmonary phagocytes, but the exact mechanisms remain unclear. Understanding the NPY-Y1 receptor's involvement in influenza and SARS-CoV-2 in both mice and hamsters may help explore its potential as an indicator of viral infections and support the development of preventive care. This study examined the effects of Molnupiravir and Remdesivir on infected Syrian hamsters and the NPY pathway during SARS-CoV-2 infection. SARS-CoV-2 infection increased mRNA expression of NPY, NPY-Y1 receptors, and inflammatory cytokines and chemokines in hamster lungs. Co-administration of the drugs significantly reduced these expressions. Changes in NPY-Y1 receptor expression were correlated with NPY, IL-10, IL-12, and IFN-γ, implying a role in the antiviral response pathway. These findings highlight that changes in the mRNA expression levels of NPY and NPY-Y1 receptor are influenced by SARS-CoV-2 infection and that the antiviral drugs impact the NPY-NPY-Y1 receptor cascade. This implies the pathway's involvement in inflammatory responses during viral infection and its potential as a therapeutic target.

Plasma MERTK is causally associated with infection mortality

BACKGROUND

Infectious diseases are a major cause of mortality in spite of existing public health, anti-microbial and vaccine interventions. We aimed to define plasma proteomic associates of infection mortality and then apply Mendelian randomisation (MR) to yield biomarkers that may be causally associated.

METHODS

We used UK Biobank plasma proteomic data to associate 2923 plasma proteins with infection mortality before 31st December 2019 (240 events in 52,520 participants). Since many plasma proteins also predict non-infection mortality, we focussed on those associated with >1.5-fold risk of infection mortality in an analysis excluding survivors. Protein quantitative trait scores (pQTS) were then used to identify whether genetically predicted protein levels also associated with infection mortality. To conduct Two Sample MR, we performed a genome-wide association study (GWAS) of infection mortality using UK Biobank participants without plasma proteomic data (n = 363,953 including 984 infection deaths).

FINDINGS

After adjusting for clinical risk factors, 1142 plasma proteins were associated with risk of infection mortality (false discovery rate <0.05). 259 proteins were associated with >1.5-fold increased risk of infection versus non-infection mortality. Of these, we identified genetically predicted increasing MERTK concentration was associated with increased risk of infection mortality. MR supported a causal association between increasing plasma MERTK protein and infection mortality (odds ratio 1.46 per unit; 95% CI 1.15- 1.85; p = 0.002).

CONCLUSION

Plasma MERTK is causally associated with infection mortality and warrants exploration as a potential therapeutic target.

Assessment of immune responses to a Comirnaty® booster following CoronaVac® vaccination in healthcare workers

BACKGROUND

The immunological response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and immunisation is variable.

OBJECTIVES

To describe the humoral immune response by correlating IgA and IgG antibodies with NAbs titration following CoronaVac® immunisation and an mRNA (Comirnaty®) booster among healthcare workers (HCWs) and to compare the cytokine and interleukin profiles between HCWs vaccinated with CoronaVac and coronavirus disease 2019 (COVID-19) infected patients.

METHODS

Samples from 133 HCWs collected at 20 (T1) and 90 (T2) days after CoronaVac immunisation and 15 (T3) days after a booster dose with the Comirnaty vaccine were analysed for IgA and IgG EIA and neutralisation assay. Cytokine levels from vaccinated individuals at T1 day and COVID-19 patients were compared.

FINDINGS

Neutralising antibodies (NAbs) were observed in 81.7% of participants at T1, but only 49.2% maintained detectable NAbs after 90 days. The booster dose increased NAbs response in all participants. The cytokines with the highest levels post-vaccination were IL-6 and MCP-1. The MCP-1, IL-18, and IFN- γ levels were higher in COVID-19 patients than in vaccinated HCWs, while IL-22 levels increased in the vaccinated HCWs group.

MAIN CONCLUSIONS

The neutralisation titres in the T2 samples decreased, and antibody levels detected at T2 showed a more significant reduction than the neutralisation. The higher IL-22 expression in immunised individuals compared to those with COVID-19 suggests that IL-22 may be beneficial in protecting against severe disease.

Methods and clinical biomarker discovery for targeted proteomics using Olink technology

PURPOSE

This paper is to offer insights for designing research utilizing Olink technology to identify biomarkers and potential therapeutic targets for disease treatment.

EXPERIMENTAL DESIGN

We discusses the application of Olink technology in oncology, cardiovascular, respiratory and immune-related diseases, and Outlines the advantages and limitations of Olink technology.

RESULTS

Olink technology simplifies the search for therapeutic targets, advances proteomics research, reveals the pathogenesis of diseases, and ultimately helps patients develop precision treatments.

CONCLUSIONS

Although proteomics technology has been rapidly developed in recent years, each method has its own disadvantages, so in the future research, more methods should be selected for combined application to verify each other.

Network-based integrative multi-omics approach reveals biosignatures specific to COVID-19 disease phases

Background

COVID-19 disease is characterized by a spectrum of disease phases (mild, moderate, and severe). Each disease phase is marked by changes in omics profiles with corresponding changes in the expression of features (biosignatures). However, integrative analysis of multiple omics data from different experiments across studies to investigate biosignatures at various disease phases is limited. Exploring an integrative multi-omics profile analysis through a network approach could be used to determine biosignatures associated with specific disease phases and enable the examination of the relationships between the biosignatures.

Aim

To identify and characterize biosignatures underlying various COVID-19 disease phases in an integrative multi-omics data analysis.

Method

We leveraged a multi-omics network-based approach to integrate transcriptomics, metabolomics, proteomics, and lipidomics data. The World Health Organization Ordinal Scale WHO Ordinal Scale was used as a disease severity reference to harmonize COVID-19 patient metadata across two studies with independent data. A unified COVID-19 knowledge graph was constructed by assembling a disease-specific interactome from the literature and databases. Disease-state specific omics-graphs were constructed by integrating multi-omics data with the unified COVID-19 knowledge graph. We expanded on the network layers of multiXrank, a random walk with restart on multilayer network algorithm, to explore disease state omics-specific graphs and perform enrichment analysis.

Results

Network analysis revealed the biosignatures involved in inducing chemokines and inflammatory responses as hubs in the severe and moderate disease phases. We observed distinct biosignatures between severe and moderate disease phases as compared to mild-moderate and mild-severe disease phases. Mild COVID-19 cases were characterized by a unique biosignature comprising C-C Motif Chemokine Ligand 4 (CCL4), and Interferon Regulatory Factor 1 (IRF1). Hepatocyte Growth Factor (HGF), Matrix Metallopeptidase 12 (MMP12), Interleukin 10 (IL10), Nuclear Factor Kappa B Subunit 1 (NFKB1), and suberoylcarnitine form hubs in the omics network that characterizes the moderate disease state. The severe cases were marked by biosignatures such as Signal Transducer and Activator of Transcription 1 (STAT1), Superoxide Dismutase 2 (SOD2), HGF, taurine, lysophosphatidylcholine, diacylglycerol, triglycerides, and sphingomyelin that characterize the disease state.

Conclusion

This study identified both biosignatures of different omics types enriched in disease-related pathways and their associated interactions (such as protein-protein, protein-transcript, protein-metabolite, transcript-metabolite, and lipid-lipid interactions) that are unique to mild, moderate, and severe COVID-19 disease states. These biosignatures include molecular features that underlie the observed clinical heterogeneity of COVID-19 and emphasize the need for disease-phase-specific treatment strategies. The approach implemented here can be used to find associations between transcripts, proteins, lipids, and metabolites in other diseases.

Proteome profiling of home-sampled dried blood spots reveals proteins of SARS-CoV-2 infections

BACKGROUND

Self-sampling of dried blood spots (DBS) offers new routes to gather valuable health-related information from the general population. Yet, the utility of using deep proteome profiling from home-sampled DBS to obtain clinically relevant insights about SARS-CoV-2 infections remains largely unexplored.

METHODS

Our study involved 228 individuals from the general Swedish population who used a volumetric DBS sampling device and completed questionnaires at home during spring 2020 and summer 2021. Using multi-analyte COVID-19 serology, we stratified the donors by their response phenotypes, divided them into three study sets, and analyzed 276 proteins by proximity extension assays (PEA). After normalizing the data to account for variances in layman-collected samples, we investigated the association of DBS proteomes with serology and self-reported information.

RESULTS

Our three studies display highly consistent variance of protein levels and share associations of proteins with sex (e.g., MMP3) and age (e.g., GDF-15). Studying seropositive (IgG+) and seronegative (IgG-) donors from the first pandemic wave reveals a network of proteins reflecting immunity, inflammation, coagulation, and stress response. A comparison of the early-infection phase (IgM+IgG-) with the post-infection phase (IgM-IgG+) indicates several proteins from the respiratory system. In DBS from the later pandemic wave, we find that levels of a virus receptor on B-cells differ between seropositive (IgG+) and seronegative (IgG-) donors.

CONCLUSIONS

Proteome analysis of volumetric self-sampled DBS facilitates precise analysis of clinically relevant proteins, including those secreted into the circulation or found on blood cells, augmenting previous COVID-19 reports with clinical blood collections. Our population surveys support the usefulness of DBS, underscoring the role of timing the sample collection to complement clinical and precision health monitoring initiatives.

Disease-specific plasma protein profiles in patients with fever after traveling to tropical areas

Fever is common among individuals seeking healthcare after traveling to tropical regions. Despite the association with potentially severe disease, the etiology is often not determined. Plasma protein patterns can be informative to understand the host response to infection and can potentially indicate the pathogen causing the disease. In this study, we measured 49 proteins in the plasma of 124 patients with fever after travel to tropical or subtropical regions. The patients had confirmed diagnoses of either malaria, dengue fever, influenza, bacterial respiratory tract infection, or bacterial gastroenteritis, representing the most common etiologies. We used multivariate and machine learning methods to identify combinations of proteins that contributed to distinguishing infected patients from healthy controls, and each other. Malaria displayed the most unique protein signature, indicating a strong immunoregulatory response with high levels of IL10, sTNFRI and II, and sCD25 but low levels of sCD40L. In contrast, bacterial gastroenteritis had high levels of sCD40L, APRIL, and IFN-γ, while dengue was the only infection with elevated IFN-α2. These results suggest that characterization of the inflammatory profile of individuals with fever can help to identify disease-specific host responses, which in turn can be used to guide future research on diagnostic strategies and therapeutic interventions.

Cross-Platform Comparison of Highly Sensitive Immunoassays for Inflammatory Markers in a COVID-19 Cohort

A variety of commercial platforms are available for the simultaneous detection of multiple cytokines and associated proteins, often employing Ab pairs to capture and detect target proteins. In this study, we comprehensively evaluated the performance of three distinct platforms: the fluorescent bead-based Luminex assay, the proximity extension-based Olink assay, and a novel proximity ligation assay platform known as Alamar NULISAseq. These assessments were conducted on human serum samples from the National Institutes of Health IMPACC study, with a focus on three essential performance metrics: detectability, correlation, and differential expression. Our results reveal several key findings. First, the Alamar platform demonstrated the highest overall detectability, followed by Olink and then Luminex. Second, the correlation of protein measurements between the Alamar and Olink platforms tended to be stronger than the correlation of either of these platforms with Luminex. Third, we observed that detectability differences across the platforms often translated to differences in differential expression findings, although high detectability did not guarantee the ability to identify meaningful biological differences. Our study provides valuable insights into the comparative performance of these assays, enhancing our understanding of their strengths and limitations when assessing complex biological samples, as exemplified by the sera from this COVID-19 cohort.

Proteomic profiling identifies biomarkers of COVID-19 severity

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

Macrophage Activation Syndrome in the Setting of Rheumatic Diseases

Patients with established rheumatic disorders may develop complications of macrophage activation syndrome due to severe flares of the underlying disease (adult-onset Still's disease, SLE); however, in most other rheumatic disorders, MAS develops in association with identified viral or other infectious triggers. It is therefore important to pursue appropriate studies to identify potential infectious triggers in rheumatic disease patients who develop MAS. Management is best directed toward treatment of the triggering infections and combinations of high-dose corticosteroids, calcineurin inhibitors, and biologic therapies targeting IL-1 and/or IL-6 to suppress the associated cytokine storm.

NULISA: a proteomic liquid biopsy platform with attomolar sensitivity and high multiplexing

The blood proteome holds great promise for precision medicine but poses substantial challenges due to the low abundance of most plasma proteins and the vast dynamic range of the plasma proteome. Here we address these challenges with NUcleic acid Linked Immuno-Sandwich Assay (NULISA™), which improves the sensitivity of traditional proximity ligation assays by ~10,000-fold to attomolar level, by suppressing assay background via a dual capture and release mechanism built into oligonucleotide-conjugated antibodies. Highly multiplexed quantification of both low- and high-abundance proteins spanning a wide dynamic range is achieved by attenuating signals from abundant targets with unconjugated antibodies and next-generation sequencing of barcoded reporter DNA. A 200-plex NULISA containing 124 cytokines and chemokines and other proteins demonstrates superior sensitivity to a proximity extension assay in detecting biologically important low-abundance biomarkers in patients with autoimmune diseases and COVID-19. Fully automated NULISA makes broad and in-depth proteomic analysis easily accessible for research and diagnostic applications.

Cross-platform comparison of highly-sensitive immunoassays for inflammatory markers in a COVID-19 cohort 1

A variety of commercial platforms are available for the simultaneous detection of multiple cytokines and associated proteins, often employing antibody pairs to capture and detect target proteins. In this study, we comprehensively evaluated the performance of three distinct platforms: the fluorescent bead-based Luminex assay, the proximity extension-based Olink assay, and a novel proximity ligation assay platform known as Alamar NULISAseq. These assessments were conducted on serum samples from the NIH IMPACC study, with a focus on three essential performance metrics: detectability, correlation, and differential expression. Our results reveal several key findings. Firstly, the Alamar platform demonstrated the highest overall detectability, followed by Olink and then Luminex. Secondly, the correlation of protein measurements between the Alamar and Olink platforms tended to be stronger than the correlation of either of these platforms with Luminex. Thirdly, we observed that detectability differences across the platforms often translated to differences in differential expression findings, although high detectability did not guarantee the ability to identify meaningful biological differences. Our study provides valuable insights into the comparative performance of these assays, enhancing our understanding of their strengths and limitations when assessing complex biological samples, as exemplified by the sera from this COVID-19 cohort.

Analysis of inflammatory protein profiles in the circulation of COVID-19 patients identifies patients with severe disease phenotypes

BACKGROUND

The coronavirus disease (COVID-19) caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) can present with a broad range of clinical manifestations, ranging from asymptomatic to severe multiple organ failure. The severity of the disease can vary depending on factors such as age, sex, ethnicity, and pre-existing medical conditions. Despite multiple efforts to identify reliable prognostic factors and biomarkers, the predictive capacity of these markers for clinical outcomes remains poor. Circulating proteins, which reflect the active mechanisms in an individual, can be easily measured in clinical practice and therefore may be useful as biomarkers for COVID-19 disease severity. In this study, we sought to identify protein biomarkers and endotypes for COVID-19 severity and evaluate their reproducibility in an independent cohort.

METHODS

We investigated a cohort of 153 Greek patients with confirmed SARS-CoV-2 infection in which plasma protein levels were measured using the Olink Explore 1536 panel, which consists of 1472 proteins. We compared the protein profiles from severe and moderate COVID-19 patients to identify proteins associated with disease severity. To evaluate the reproducibility of our findings, we compared the protein profiles of 174 patients with comparable COVID-19 severities in a US COVID-19 cohort to identify proteins consistently correlated with COVID-19 severity in both groups.

RESULTS

We identified 218 differentially regulated proteins associated with severity, 20 proteins were also replicated in an external cohort which we used for validation. Moreover, we performed unsupervised clustering of patients based on 97 proteins with the highest log2 fold changes in order to identify COVID-19 endotypes. Clustering of patients based on differentially regulated proteins revealed the presence of three clinical endotypes. While endotypes 2 and 3 were enriched for severe COVID-19 patients, endotypes 3 represented the most severe form of the disease.

CONCLUSIONS

These results suggest that identified circulating proteins may be useful for identifying COVID-19 patients with worse outcomes, and this potential utility may extend to other populations.

TRIAL REGISTRATION

NCT04357366.

Auto-immunoproteomics analysis of COVID-19 ICU patients revealed increased levels of autoantibodies related to the male reproductive system

Background: Coronavirus disease (COVID-19) manifests many clinical symptoms, including an exacerbated immune response and cytokine storm. Autoantibodies in COVID-19 may have severe prodromal effects that are poorly understood. The interaction between these autoantibodies and self-antigens can result in systemic inflammation and organ dysfunction. However, the role of autoantibodies in COVID-19 complications has yet to be fully understood. Methods: The current investigation screened two independent cohorts of 97 COVID-19 patients [discovery (Disc) cohort from Qatar (case = 49 vs. control = 48) and replication (Rep) cohort from New York (case = 48 vs. control = 28)] utilizing high-throughput KoRectly Expressed (KREX) Immunome protein-array technology. Total IgG autoantibody responses were evaluated against 1,318 correctly folded and full-length human proteins. Samples were randomly applied on the precoated microarray slides for 2 h. Cy3-labeled secondary antibodies were used to detect IgG autoantibody response. Slides were scanned at a fixed gain setting using the Agilent fluorescence microarray scanner, generating a 16-bit TIFF file. Group comparisons were performed using a linear model and Fisher's exact test. Differentially expressed proteins were used for KEGG and WIKIpathway annotation to determine pathways in which the proteins of interest were significantly over-represented. Results and conclusion: Autoantibody responses to 57 proteins were significantly altered in the COVID-19 Disc cohort compared to healthy controls (p ≤ 0.05). The Rep cohort had altered autoantibody responses against 26 proteins compared to non-COVID-19 ICU patients who served as controls. Both cohorts showed substantial similarities (r 2 = 0.73) and exhibited higher autoantibody responses to numerous transcription factors, immunomodulatory proteins, and human disease markers. Analysis of the combined cohorts revealed elevated autoantibody responses against SPANXN4, STK25, ATF4, PRKD2, and CHMP3 proteins in COVID-19 patients. The sequences for SPANXN4 and STK25 were cross-validated using sequence alignment tools. ELISA and Western blot further verified the autoantigen-autoantibody response of SPANXN4. SPANXN4 is essential for spermiogenesis and male fertility, which may predict a potential role for this protein in COVID-19-associated male reproductive tract complications, and warrants further research.

NULISA: a novel proteomic liquid biopsy platform with attomolar sensitivity and high multiplexing

The blood proteome holds great promise for precision medicine but poses substantial challenges due to the low abundance of most plasma proteins and the vast dynamic range across the proteome. We report a novel proteomic technology - NUcleic acid Linked Immuno-Sandwich Assay (NULISA™) - that incorporates a dual capture and release mechanism to suppress the assay background and improves the sensitivity of the proximity ligation assay by over 10,000-fold to the attomolar level. It utilizes pairs of antibodies conjugated to DNA oligonucleotides that enable immunocomplex purification and generate reporter DNA containing target- and sample-specific barcodes for a next-generation sequencing-based, highly multiplexed readout. A 200-plex NULISA targeting 124 cytokines and chemokines and 80 other immune response-related proteins demonstrated superior sensitivity for detecting low-abundance proteins and high concordance with other immunoassays. The ultrahigh sensitivity allowed the detection of previously difficult-to-detect, but biologically important, low-abundance biomarkers in patients with autoimmune diseases and COVID-19. Fully automated NULISA addresses longstanding challenges in proteomic analysis of liquid biopsies and makes broad and in-depth proteomic analysis accessible to the general research community and future diagnostic applications.

Interferon gamma-1b for the prevention of hospital-acquired pneumonia in critically ill patients: a phase 2, placebo-controlled randomized clinical trial

PURPOSE

We aimed to determine whether interferon gamma-1b prevents hospital-acquired pneumonia in mechanically ventilated patients.

METHODS

In a multicenter, placebo-controlled, randomized trial conducted in 11 European hospitals, we randomly assigned critically ill adults, with one or more acute organ failures, under mechanical ventilation to receive interferon gamma-1b (100 µg every 48 h from day 1 to 9) or placebo (following the same regimen). The primary outcome was a composite of hospital-acquired pneumonia or all-cause mortality on day 28. The planned sample size was 200 with interim safety analyses after enrolling 50 and 100 patients.

RESULTS

The study was discontinued after the second safety analysis for potential harm with interferon gamma-1b, and the follow-up was completed in June 2022. Among 109 randomized patients (median age, 57 (41-66) years; 37 (33.9%) women; all included in France), 108 (99%) completed the trial. Twenty-eight days after inclusion, 26 of 55 participants (47.3%) in the interferon-gamma group and 16 of 53 (30.2%) in the placebo group had hospital-acquired pneumonia or died (adjusted hazard ratio (HR) 1.76, 95% confidence interval (CI) 0.94-3.29; P = 0.08). Serious adverse events were reported in 24 of 55 participants (43.6%) in the interferon-gamma group and 17 of 54 (31.5%) in the placebo group (P = 0.19). In an exploratory analysis, we found that hospital-acquired pneumonia developed in a subgroup of patients with decreased CCL17 response to interferon-gamma treatment.

CONCLUSIONS

Among mechanically ventilated patients with acute organ failure, treatment with interferon gamma-1b compared with placebo did not significantly reduce the incidence of hospital-acquired pneumonia or death on day 28. Furthermore, the trial was discontinued early due to safety concerns about interferon gamma-1b treatment.

Integrated bioinformatics analysis identifies shared immune changes between ischemic stroke and COVID 19

Although COVID-19 is primarily a respiratory disease, its neurological complications, such as ischemic stroke (IS), have aroused growing concerns and reports. However, the molecular mechanisms that underlie IS and COVID-19 are not well understood. Therefore, we implemented transcriptomic analysis from eight GEO datasets consist of 1191 samples to detect common pathways and molecular biomarkers in IS and COVID-19 that help understand the linkage between them. Differentially expressed genes (DEGs) were detected for IS and COVID-19 separately for finding shared mechanisms and we found that immune-related pathways were outlined with statistical significance. JAK2, which was identified as a hub gene, was supposed to be a potential therapeutic gene targets during the immunological process of COVID-19 and IS. Besides, we found a decrease in the proportion of CD8+ T and T helper 2 cells in the peripheral circulation of both COVID and IS patients, and NCR3 expression was significantly correlated with this change. In conclusion, we demonstrated that transcriptomic analyses reported in this study could make a deeper understanding of the common mechanism and might be promising for effective therapeutic for IS and COVID-19.

Divergent Cytokine and Chemokine Responses at Early Acute Simian Immunodeficiency Virus Infection Correlated with Virus Replication and CD4 T Cell Loss in a Rhesus Macaque Model

Cytokine and chemokine levels remain one of the significant predictive factors of HIV pathogenesis and disease outcome. Understanding the impact of cytokines and chemokines during early acute infection will help to recognize critical changes during HIV pathogenesis and might assist in establishing improved HIV treatment and prevention methods. Sixty-one cytokines and chemokines were evaluated in the plasma of an SIV-infected rhesus macaque model. A substantial change in 11 cytokines/growth factors and 9 chemokines were observed during acute infection. Almost all the cytokines/chemokines were below the baseline values for an initial couple of days of infection. We detected six important cytokines/chemokines, such as IL-18, IP-10, FLT3L, MCP-1, MCP-2, and MIP-3β, that can be used as biomarkers to predict the peripheral CD4+ T cell loss and increased viral replication during the acute SIV/HIV infection. Hence, regulating IL-18, IP-10, FLT3L, MCP-1, MCP-2, and MIP-3β expression might provide an antiviral response to combat acute SIV/HIV infection.

Serum Proteomic Analysis for New Types of Long-Term Persistent COVID-19 Patients in Wuhan

The emergence of a new type of COVID-19 patients, who were retested positive after hospital discharge with long-term persistent SARS-CoV-2 infection but without COVID-19 clinical symptoms (hereinafter, LTPPs), poses novel challenges to COVID-19 treatment and prevention. Why was there such a contradictory phenomenon in LTPPs? To explore the mechanism underlying this phenomenon, we performed quantitative proteomic analyses using the sera of 12 LTPPs (Wuhan Pulmonary Hospital), with the longest carrying history of 132 days, and mainly focused on 7 LTPPs without hypertension (LTPPs-NH). The results showed differential serum protein profiles between LTPPs/LTPPs-NH and health controls. Further analysis identified 174 differentially-expressed-proteins (DEPs) for LTPPs, and 165 DEPs for LTPPs-NH, most of which were shared. GO and KEGG analyses for these DEPs revealed significant enrichment of "coagulation" and "immune response" in both LTPPs and LTPPs-NH. A unity of contradictory genotypes in the 2 aspects were then observed: some DEPs showed the same dysregulated expressed trend as that previously reported for patients in the acute phase of COVID-19, which might be caused by long-term stimulation of persistent SARS-CoV-2 infection in LTPPs, further preventing them from complete elimination; in contrast, some DEPs showed the opposite expression trend in expression, so as to retain control of COVID-19 clinical symptoms in LTPPs. Overall, the contrary effects of these DEPs worked together to maintain the balance of LTPPs, further endowing their contradictory steady-state with long-term persistent SARS-CoV-2 infection but without symptoms. Additionally, our study revealed some potential therapeutic targets of COVID-19. Further studies on these are warranted. IMPORTANCE This study reported a new type of COVID-19 patients and explored the underlying molecular mechanism by quantitative proteomic analyses. DEPs were significantly enriched in "coagulation" and "immune response". Importantly, we identified 7 "coagulation system"- and 9 "immune response"-related DEPs, the expression levels of which were consistent with those previously reported for patients in the acute phase of COVID-19, which appeared to play a role in avoiding the complete elimination of SARS-CoV-2 in LTPPs. On the contrary, 6 "coagulation system"- and 5 "immune response"-related DEPs showed the opposite trend in expression. The 11 inconsistent serum proteins seem to play a key role in the fight against long-term persistent SARS-CoV-2 infection, further retaining control of COVID-19 clinical symptom of LTPPs. The 26 proteins can serve as potential therapeutic targets and are thus valuable for the treatment of LTPPs; further studies on them are warranted.

Increased mRNA Levels of ADAM17, IFITM3, and IFNE in Peripheral Blood Cells Are Present in Patients with Obesity and May Predict Severe COVID-19 Evolution

Gene expression patterns in blood cells from SARS-CoV-2 infected individuals with different clinical phenotypes and body mass index (BMI) could help to identify possible early prognosis factors for COVID-19. We recruited patients with COVID-19 admitted in Hospital Universitari Son Espases (HUSE) between March 2020 and November 2021, and control subjects. Peripheral blood cells (PBCs) and plasma samples were obtained on hospital admission. Gene expression of candidate transcriptomic biomarkers in PBCs were compared based on the patients’ clinical status (mild, severe and critical) and BMI range (normal weight, overweight, and obesity). mRNA levels of ADAM17, IFITM3, IL6, CXCL10, CXCL11, IFNG and TYK2 were increased in PBCs of COVID-19 patients (n = 73) compared with controls (n = 47), independently of sex. Increased expression of IFNE was observed in the male patients only. PBC mRNA levels of ADAM17, IFITM3, CXCL11, and CCR2 were higher in those patients that experienced a more serious evolution during hospitalization. ADAM17, IFITM3, IL6 and IFNE were more highly expressed in PBCs of patients with obesity. Interestingly, the expression pattern of ADAM17, IFITM3 and IFNE in PBCs was related to both the severity of COVID-19 evolution and obesity status, especially in the male patients. In conclusion, gene expression in PBCs can be useful for the prognosis of COVID-19 evolution.

Proteomic Approaches to Unravel Mechanisms of Antibiotic Resistance and Immune Evasion of Bacterial Pathogens

The profound effects of and distress caused by the global COVID-19 pandemic highlighted what has been known in the health sciences a long time ago: that bacteria, fungi, viruses, and parasites continue to present a major threat to human health. Infectious diseases remain the leading cause of death worldwide, with antibiotic resistance increasing exponentially due to a lack of new treatments. In addition to this, many pathogens share the common trait of having the ability to modulate, and escape from, the host immune response. The challenge in medical microbiology is to develop and apply new experimental approaches that allow for the identification of both the microbe and its drug susceptibility profile in a time-sensitive manner, as well as to elucidate their molecular mechanisms of survival and immunomodulation. Over the last three decades, proteomics has contributed to a better understanding of the underlying molecular mechanisms responsible for microbial drug resistance and pathogenicity. Proteomics has gained new momentum as a result of recent advances in mass spectrometry. Indeed, mass spectrometry-based biomedical research has been made possible thanks to technological advances in instrumentation capability and the continuous improvement of sample processing and workflows. For example, high-throughput applications such as SWATH or Trapped ion mobility enable the identification of thousands of proteins in a matter of minutes. This type of rapid, in-depth analysis, combined with other advanced, supportive applications such as data processing and artificial intelligence, presents a unique opportunity to translate knowledge-based findings into measurable impacts like new antimicrobial biomarkers and drug targets. In relation to the Research Topic “Proteomic Approaches to Unravel Mechanisms of Resistance and Immune Evasion of Bacterial Pathogens,” this review specifically seeks to highlight the synergies between the powerful fields of modern proteomics and microbiology, as well as bridging translational opportunities from biomedical research to clinical practice.