An attenuated vaccinia vaccine encoding the severe acute respiratory syndrome coronavirus-2 spike protein elicits broad and durable immune responses, and protects cynomolgus macaques and human angiotensin-converting enzyme 2 transgenic mice from severe acute respiratory syndrome coronavirus-2 and its variants.

As long as the coronavirus disease-2019 (COVID-19) pandemic continues, new variants of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) with altered antigenicity will emerge. The development of vaccines that elicit robust, broad, and durable protection against SARS-CoV-2 variants is urgently required. We have developed a vaccine consisting of the attenuated vaccinia virus Dairen-I (DIs) strain platform carrying the SARS-CoV-2 S gene (rDIs-S). rDIs-S induced neutralizing antibody and T-lymphocyte responses in cynomolgus macaques and human angiotensin-converting enzyme 2 (hACE2) transgenic mice, and the mouse model showed broad protection against SARS-CoV-2 isolates ranging from the early-pandemic strain (WK-521) to the recent Omicron BA.1 variant (TY38-873). Using a tandem mass tag (TMT)-based quantitative proteomic analysis of lung homogenates from hACE2 transgenic mice, we found that, among mice subjected to challenge infection with WK-521, vaccination with rDIs-S prevented protein expression related to the severe pathogenic effects of SARS-CoV-2 infection (tissue destruction, inflammation, coagulation, fibrosis, and angiogenesis) and restored protein expression related to immune responses (antigen presentation and cellular response to stress). Furthermore, long-term studies in mice showed that vaccination with rDIs-S maintains S protein-specific antibody titers for at least 6 months after a first vaccination. Thus, rDIs-S appears to provide broad and durable protective immunity against SARS-CoV-2, including current variants such as Omicron BA.1 and possibly future variants.

Profiling SARS-CoV-2 Infection by High-Throughput Shotgun Proteomics.

A comprehensive cartography of viral and host proteins expressed during the different stages of SARS-CoV-2 infection is key to decipher the molecular mechanisms of pathogenesis. For the most detailed analysis, proteins should be first purified and then proteolyzed with trypsin in the presence of detergents. The resulting peptide mixtures are resolved by reverse phase ultrahigh pressure liquid chromatography and then identified by a high-resolution tandem mass spectrometer. The thousands of spectra acquired for each fraction can then be assigned to peptide sequences using a relevant protein sequence database, comprising viral and host proteins and potential contaminants from the growth medium or from the operator. The peptides are evidencing proteins and their intensities are used to infer the abundance of their corresponding proteins. Data analysis allows for highlighting the viral and host proteins dynamics. Here, we describe the sample preparation method adapted to profile SARS-CoV-2 -infected cell models, the shotgun proteomics pipeline to record experimental data, and the workflow for data interpretation to analyze infection-induced proteomic changes in a time-resolved manner.

Longitudinal Plasma Proteomics Analysis Reveals Novel Candidate Biomarkers in Acute COVID-19.

The host response to COVID-19 pathophysiology over the first few days of infection remains largely unclear, especially the mechanisms in the blood compartment. We report on a longitudinal proteomic analysis of acute-phase COVID-19 patients, for which we used blood plasma, multiple reaction monitoring with internal standards, and data-independent acquisition. We measured samples on admission for 49 patients, of which 21 had additional samples on days 2, 4, 7, and 14 after admission. We also measured 30 externally obtained samples from healthy individuals for comparison at baseline. The 31 proteins differentiated in abundance between acute COVID-19 patients and healthy controls belonged to acute inflammatory response, complement activation, regulation of inflammatory response, and regulation of protein activation cascade. The longitudinal analysis showed distinct profiles revealing increased levels of multiple lipid-associated functions, a rapid decrease followed by recovery for complement activation, humoral immune response, and acute inflammatory response-related proteins, and level fluctuation in the regulation of smooth muscle cell proliferation, secretory mechanisms, and platelet degranulation. Three proteins were differentiated between survivors and nonsurvivors. Finally, increased levels of fructose-bisphosphate aldolase B were determined in patients with exposure to angiotensin receptor blockers versus decreased levels in those exposed to angiotensin-converting enzyme inhibitors. Data are available via ProteomeXchange PXD029437.

HDL proteome remodeling associates with COVID-19 severity.

BACKGROUND: Besides the well-accepted role in lipid metabolism, high-density lipoprotein (HDL) also seems to participate in host immune response against infectious diseases. OBJECTIVE: We used a quantitative proteomic approach to test the hypothesis that alterations in HDL proteome associate with severity of Coronavirus disease 2019 (COVID-19). METHODS: Based on clinical criteria, subjects (n=41) diagnosed with COVID-19 were divided into two groups: a group of subjects presenting mild symptoms and a second group displaying severe symptoms and requiring hospitalization. Using a proteomic approach, we quantified the levels of 29 proteins in HDL particles derived from these subjects. RESULTS: We showed that the levels of serum amyloid A 1 and 2 (SAA1 and SAA2, respectively), pulmonary surfactant-associated protein B (SFTPB), apolipoprotein F (APOF), and inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4) were increased by more than 50% in hospitalized patients, independently of sex, HDL-C or triglycerides when comparing with subjects presenting only mild symptoms. Altered HDL proteins were able to classify COVID-19 subjects according to the severity of the disease (error rate 4.9%). Moreover, apolipoprotein M (APOM) in HDL was inversely associated with odds of death due to COVID-19 complications (odds ratio [OR] per 1-SD increase in APOM was 0.27, with 95% confidence interval [CI] of 0.07 to 0.72, P=0.007). CONCLUSION: Our results point to a profound inflammatory remodeling of HDL proteome tracking with severity of COVID-19 infection. They also raise the possibility that HDL particles could play an important role in infectious diseases.

Proteomic Analysis Identifies Prolonged Disturbances in Pathways Related to Cholesterol Metabolism and Myocardium Function in the COVID-19 Recovery Stage.

The COVID-19 pandemic has become a worldwide health crisis. So far, most studies have focused on the epidemiology and pathogenesis of this infectious disease. Little attention has been given to the disease sequelae in patients recovering from COVID-19, and nothing is known about the mechanisms underlying these sequelae. Herein, we profiled the serum proteome of a cohort of COVID-19 patients in the disease onset and recovery stages. Based on the close integration of our proteomic analysis with clinical data, we propose that COVID-19 is associated with prolonged disorders in cholesterol metabolism and myocardium, even in the recovery stage. We identify potential biomarkers for these disorders. Moreover, severely affected patients presented more serious disturbances in these pathways. Our findings potentially support clinical decision-making to improve the prognosis and treatment of patients.

Virus systems biology: Proteomics profiling of dynamic protein networks during infection.

The host cell proteome undergoes a variety of dynamic changes during viral infection, elicited by the virus itself or host cell defense mechanisms. Studying these changes on a global scale by integrating functional and physical interactions within protein networks during infection is an important tool to understand pathology. Indeed, proteomics studies dissecting protein signaling cascades and interaction networks upon infection showed how global information can significantly improve understanding of disease mechanisms of diverse viral infections. Here, we summarize and give examples of different experimental designs, proteomics approaches and bioinformatics analyses that allow profiling proteome changes and host-pathogen interactions to gain a molecular systems view of viral infection.

Utility of Proteomics in Emerging and Re-Emerging Infectious Diseases Caused by RNA Viruses.

Emerging and re-emerging infectious diseases due to RNA viruses cause major negative consequences for the quality of life, public health, and overall economic development. Most of the RNA viruses causing illnesses in humans are of zoonotic origin. Zoonotic viruses can directly be transferred from animals to humans through adaptation, followed by human-to-human transmission, such as in human immunodeficiency virus (HIV), severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), and, more recently, SARS coronavirus 2 (SARS-CoV-2), or they can be transferred through insects or vectors, as in the case of Crimean-Congo hemorrhagic fever virus (CCHFV), Zika virus (ZIKV), and dengue virus (DENV). At the present, there are no vaccines or antiviral compounds against most of these viruses. Because proteins possess a vast array of functions in all known biological systems, proteomics-based strategies can provide important insights into the investigation of disease pathogenesis and the identification of promising antiviral drug targets during an epidemic or pandemic. Mass spectrometry technology has provided the capacity required for the precise identification and the sensitive and high-throughput analysis of proteins on a large scale and has contributed greatly to unravelling key protein-protein interactions, discovering signaling networks, and understanding disease mechanisms. In this Review, we present an account of quantitative proteomics and its application in some prominent recent examples of emerging and re-emerging RNA virus diseases like HIV-1, CCHFV, ZIKV, and DENV, with more detail with respect to coronaviruses (MERS-CoV and SARS-CoV) as well as the recent SARS-CoV-2 pandemic.

Proteomic characteristics of bronchoalveolar lavage fluid in critical COVID-19 patients.

Up to 10-20% of patients with coronavirus disease 2019 (COVID-19) develop a severe pulmonary disease due to immune dysfunction and cytokine dysregulation. However, the extracellular proteomic characteristics in respiratory tract of these critical COVID-19 patients still remain to be investigated. In the present study, we performed a quantitative proteomic analysis of the bronchoalveolar lavage fluid (BALF) from patients with critical COVID-19 and from non-COVID-19 controls. Our study identified 358 differentially expressed BALF proteins (P < 0.05), among which 41 were significantly changed after using the Benjamini-Hochberg correction (q < 0.05). The up-regulated signaling was found to be mainly involved in inflammatory signaling and response to oxidative stress. A series of increased extracellular factors including Tenascin-C (TNC), Mucin-1 (KL-6 or MUC1), Lipocalin-2 (LCN2), periostin (POSTN), Chitinase 3-like 1 (CHI3L1 or YKL40), and S100A12, and the antigens including lymphocyte antigen 6D/E48 antigen (LY6D), CD9 antigen, CD177 antigen, and prostate stem cell antigen (PSCA) were identified, among which the proinflammatory factors TNC and KL-6 were further validated in serum of another thirty-nine COVID-19 patients and healthy controls, showing high potentials of being biomarkers or therapeutic candidates for COVID-19. This BALF proteome associated with COVID-19 would also be a valuable resource for researches on anti-inflammatory medication and understanding the molecular mechanisms of host response. DATABASE: Proteomic raw data are available in ProteomeXchange (http://proteomecentral.proteomexchange.org) under the accession number PXD022085, and in iProX (www.iprox.org) under the accession number IPX0002429000.

Quantitative proteomics reveals a broad-spectrum antiviral property of ivermectin, benefiting for COVID-19 treatment.

Viruses such as human cytomegalovirus (HCMV), human papillomavirus (HPV), Epstein-Barr virus (EBV), human immunodeficiency virus (HIV), and coronavirus (severe acute respiratory syndrome coronavirus 2 [SARS-CoV-2]) represent a great burden to human health worldwide. FDA-approved anti-parasite drug ivermectin is also an antibacterial, antiviral, and anticancer agent, which offers more potentiality to improve global public health, and it can effectively inhibit the replication of SARS-CoV-2 in vitro. This study sought to identify ivermectin-related virus infection pathway alterations in human ovarian cancer cells. Stable isotope labeling by amino acids in cell culture (SILAC) quantitative proteomics was used to analyze human ovarian cancer cells TOV-21G treated with and without ivermectin (20 µmol/L) for 24 h, which identified 4447 ivermectin-related proteins in ovarian cancer cells. Pathway network analysis revealed four statistically significant antiviral pathways, including HCMV, HPV, EBV, and HIV1 infection pathways. Interestingly, compared with the reported 284 SARS-CoV-2/COVID-19-related genes from GencLip3, we identified 52 SARS-CoV-2/COVID-19-related protein alterations when treated with and without ivermectin. Protein-protein network (PPI) was constructed based on the interactions between 284 SARS-CoV-2/COVID-19-related genes and between 52 SARS-CoV-2/COVID-19-related proteins regulated by ivermectin. Molecular complex detection analysis of PPI network identified three hub modules, including cytokines and growth factor family, MAP kinase and G-protein family, and HLA class proteins. Gene Ontology analysis revealed 10 statistically significant cellular components, 13 molecular functions, and 11 biological processes. These findings demonstrate the broad-spectrum antiviral property of ivermectin benefiting for COVID-19 treatment in the context of predictive, preventive, and personalized medicine in virus-related diseases.

Update on Proteomic approaches to uncovering virus-induced protein alterations and virus -host protein interactions during the progression of viral infection.

INTRODUCTION: Viruses induce profound changes in the cells they infect. Understanding these perturbations will assist in designing better therapeutics to combat viral infection. System-based proteomic assays now provide unprecedented opportunity to monitor large numbers of cellular proteins. AREAS COVERED: This review will describe various quantitative and functional mass spectrometry-based methods, and complementary non-mass spectrometry-based methods, such as aptamer profiling and proximity extension assays, and examples of how each are used to delineate how viruses affect host cells, identify which viral proteins interact with which cellular proteins, and how these change during the course of a viral infection. PubMed was searched multiple times prior to manuscript submissions and revisions, using virus, viral, proteomics; in combination with each keyword. The most recent examples of published works from each search were then analyzed. EXPERT OPINION: There has been exponential growth in numbers and types of proteomic analyses in recent years. Continued development of reagents that allow increased multiplexing and deeper proteomic probing of the cell, at quantitative and functional levels, enhancements that target more important protein modifications, and improved bioinformatics software tools and pathway prediction algorithms will accelerate this growth and usher in a new era of host proteome understanding.

Quantitative proteomic dataset from oro- and naso-pharyngeal swabs used for COVID-19 diagnosis: Detection of viral proteins and host's biological processes altered by the infection.

Since January 2020, the world is facing the COVID-19 pandemic caused by SARS-CoV-2. In a big effort to cope with this outbreak, two Uruguayan institutions, Institut Pasteur de Montevideo and Universidad de la República, have developed and implemented a diagnosis pipeline based on qRT-PCR using entirely local resources. In this context, we performed comparative quantitative proteomic analysis from oro- and naso-pharyngeal swabs used for diagnosis. Tryptic peptides obtained from five positive and five negative samples were analysed by nano-LC-MS/MS using a Q-Exactive Plus mass spectrometer. Data analysis was performed using PatternLab for Proteomics software. From all SARS-CoV-2 positive swabs we were able to detect peptides of the SARS-CoV-2 nucleoprotein that encapsulates and protect the RNA genome. Additionally, we detected an average of 1100 human proteins from each sample. The most abundant proteins exclusively detected in positive swabs were "Guanylate-binding protein 1", "Tapasin" and "HLA class II histocompatibility antigen DR beta chain". The biological processes overrepresented in infected host cells were "SRP-dependent cotranslational protein targeting to membrane", "nuclear-transcribed mRNA catabolic process, nonsense-mediated decay", "viral transcription" and "translational initiation". Data is available via ProteomeXchange with identifier PXD020394. We expect that this data can contribute to the future development of mass spectrometry based approaches for COVID-19 diagnosis. Also, we share this preliminary proteomic characterization concerning the host response to infection for its reuse in basic investigation.