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1.
Sci Rep ; 11(1): 20638, 2021 10 19.
Article in English | MEDLINE | ID: covidwho-1475483

ABSTRACT

The COVID-19 pandemic is an unprecedented threat to humanity that has provoked global health concerns. Since the etiopathogenesis of this illness is not fully characterized, the prognostic factors enabling treatment decisions have not been well documented. Accurately predicting the progression of the disease would aid in appropriate patient categorization and thus help determine the best treatment option. Here, we have introduced a proteomic approach utilizing data-independent acquisition mass spectrometry (DIA-MS) to identify the serum proteins that are closely associated with COVID-19 prognosis. Twenty-seven proteins were differentially expressed between severely ill COVID-19 patients with an adverse or favorable prognosis. Ingenuity Pathway Analysis revealed that 15 of the 27 proteins might be regulated by cytokine signaling relevant to interleukin (IL)-1ß, IL-6, and tumor necrosis factor (TNF), and their differential expression was implicated in the systemic inflammatory response and in cardiovascular disorders. We further evaluated practical predictors of the clinical prognosis of severe COVID-19 patients. Subsequent ELISA assays revealed that CHI3L1 and IGFALS may serve as highly sensitive prognostic markers. Our findings can help formulate a diagnostic approach for accurately identifying COVID-19 patients with severe disease and for providing appropriate treatment based on their predicted prognosis.


Subject(s)
Biomarkers/blood , COVID-19 Serological Testing/methods , COVID-19/blood , Gene Expression Profiling , Proteomics/methods , Chitinase-3-Like Protein 1/metabolism , Enzyme-Linked Immunosorbent Assay , Gas Chromatography-Mass Spectrometry , Gene Expression Regulation , Humans , Inflammation , Interleukin-1beta/biosynthesis , Interleukin-6/biosynthesis , Prognosis , SARS-CoV-2 , Tumor Necrosis Factor-alpha/biosynthesis , Virus Diseases
2.
Cell Rep ; 37(2): 109806, 2021 10 12.
Article in English | MEDLINE | ID: covidwho-1466094

ABSTRACT

Tactical disruption of protein synthesis is an attractive therapeutic strategy, with the first-in-class eIF4A-targeting compound zotatifin in clinical evaluation for cancer and COVID-19. The full cellular impact and mechanisms of these potent molecules are undefined at a proteomic level. Here, we report mass spectrometry analysis of translational reprogramming by rocaglates, cap-dependent initiation disruptors that include zotatifin. We find effects to be far more complex than simple "translational inhibition" as currently defined. Translatome analysis by TMT-pSILAC (tandem mass tag-pulse stable isotope labeling with amino acids in cell culture mass spectrometry) reveals myriad upregulated proteins that drive hitherto unrecognized cytotoxic mechanisms, including GEF-H1-mediated anti-survival RHOA/JNK activation. Surprisingly, these responses are not replicated by eIF4A silencing, indicating a broader translational adaptation than currently understood. Translation machinery analysis by MATRIX (mass spectrometry analysis of active translation factors using ribosome density fractionation and isotopic labeling experiments) identifies rocaglate-specific dependence on specific translation factors including eEF1ε1 that drive translatome remodeling. Our proteome-level interrogation reveals that the complete cellular response to these historical "translation inhibitors" is mediated by comprehensive translational landscape remodeling.


Subject(s)
Protein Biosynthesis/drug effects , Protein Synthesis Inhibitors/pharmacology , Animals , Benzofurans/pharmacology , Cell Line, Tumor , Eukaryotic Initiation Factor-4A/drug effects , Eukaryotic Initiation Factor-4A/metabolism , Humans , Male , Mice , Mice, Inbred NOD , Primary Cell Culture , Protein Biosynthesis/physiology , Proteomics/methods , Ribosomes/metabolism , Transcriptome/drug effects , Transcriptome/genetics , Triterpenes/pharmacology
3.
Anal Bioanal Chem ; 413(29): 7305-7318, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1460297

ABSTRACT

The spike protein of SARS-CoV-2, the virus responsible for the global pandemic of COVID-19, is an abundant, heavily glycosylated surface protein that plays a key role in receptor binding and host cell fusion, and is the focus of all current vaccine development efforts. Variants of concern are now circulating worldwide that exhibit mutations in the spike protein. Protein sequence and glycosylation variations of the spike may affect viral fitness, antigenicity, and immune evasion. Global surveillance of the virus currently involves genome sequencing, but tracking emerging variants should include quantitative measurement of changes in site-specific glycosylation as well. In this work, we used data-dependent acquisition (DDA) and data-independent acquisition (DIA) mass spectrometry to quantitatively characterize the five N-linked glycosylation sites of the glycoprotein standard alpha-1-acid glycoprotein (AGP), as well as the 22 sites of the SARS-CoV-2 spike protein. We found that DIA compared favorably to DDA in sensitivity, resulting in more assignments of low-abundance glycopeptides. However, the reproducibility across replicates of DIA-identified glycopeptides was lower than that of DDA, possibly due to the difficulty of reliably assigning low-abundance glycopeptides confidently. The differences in the data acquired between the two methods suggest that DIA outperforms DDA in terms of glycoprotein coverage but that overall performance is a balance of sensitivity, selectivity, and statistical confidence in glycoproteomics. We assert that these analytical and bioinformatics methods for assigning and quantifying glycoforms would benefit the process of tracking viral variants as well as for vaccine development.


Subject(s)
Glycomics/methods , Mass Spectrometry/methods , Proteomics/methods , SARS-CoV-2/metabolism , Spike Glycoprotein, Coronavirus/chemistry , COVID-19/virology , Glycosylation , Humans , Limit of Detection , Reproducibility of Results , Spike Glycoprotein, Coronavirus/metabolism
4.
Cell Rep ; 37(3): 109839, 2021 10 19.
Article in English | MEDLINE | ID: covidwho-1439921

ABSTRACT

MicroRNAs (miRNAs) are small non-coding RNAs involved in post-transcriptional gene regulation that have a major impact on many diseases and provide an exciting avenue toward antiviral therapeutics. From patient transcriptomic data, we determined that a circulating miRNA, miR-2392, is directly involved with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) machinery during host infection. Specifically, we show that miR-2392 is key in driving downstream suppression of mitochondrial gene expression, increasing inflammation, glycolysis, and hypoxia, as well as promoting many symptoms associated with coronavirus disease 2019 (COVID-19) infection. We demonstrate that miR-2392 is present in the blood and urine of patients positive for COVID-19 but is not present in patients negative for COVID-19. These findings indicate the potential for developing a minimally invasive COVID-19 detection method. Lastly, using in vitro human and in vivo hamster models, we design a miRNA-based antiviral therapeutic that targets miR-2392, significantly reduces SARS-CoV-2 viability in hamsters, and may potentially inhibit a COVID-19 disease state in humans.


Subject(s)
COVID-19/genetics , COVID-19/immunology , MicroRNAs/genetics , SARS-CoV-2/genetics , Adult , Aged , Aged, 80 and over , Animals , Antiviral Agents/pharmacology , Biomarkers/metabolism , COVID-19/drug therapy , Cricetinae , Female , Ferrets , Gene Expression Regulation , Glycolysis , Healthy Volunteers , Humans , Hypoxia , Inflammation , Male , Mice , Middle Aged , Proteomics/methods , ROC Curve , Rats
5.
J Proteome Res ; 20(2): 1415-1423, 2021 02 05.
Article in English | MEDLINE | ID: covidwho-1387126

ABSTRACT

The utility of low sample volume in vitro diagnostic (IVDr) proton nuclear magnetic resonance (1H NMR) spectroscopic experiments on blood plasma for information recovery from limited availability or high value samples was exemplified using plasma from patients with SARS-CoV-2 infection and normal controls. 1H NMR spectra were obtained using solvent-suppressed 1D, spin-echo (CPMG), and 2-dimensional J-resolved (JRES) spectroscopy using both 3 mm outer diameter SampleJet NMR tubes (100 µL plasma) and 5 mm SampleJet NMR tubes (300 µL plasma) under in vitro diagnostic conditions. We noted near identical diagnostic models in both standard and low volume IVDr lipoprotein analysis (measuring 112 lipoprotein parameters) with a comparison of the two tubes yielding R2 values ranging between 0.82 and 0.99 for the 40 paired lipoprotein parameters samples. Lipoprotein measurements for the 3 mm tubes were achieved without time penalty over the 5 mm tubes as defined by biomarker recovery for SARS-CoV-2. Overall, biomarker pattern recovery for the lipoproteins was extremely similar, but there were some small positive offsets in the linear equations for several variables due to small shimming artifacts, but there was minimal degradation of the biological information. For the standard untargeted 1D, CPMG, and JRES NMR experiments on the same samples, the reduced signal-to-noise was more constraining and required greater scanning times to achieve similar differential diagnostic performance (15 min per sample per experiment for 3 mm 1D and CPMG, compared to 4 min for the 5 mm tubes). We conclude that the 3 mm IVDr method is fit-for-purpose for quantitative lipoprotein measurements, allowing the preparation of smaller volumes for high value or limited volume samples that is common in clinical studies. If there are no analytical time constraints, the lower volume experiments are equally informative for untargeted profiling.


Subject(s)
COVID-19/diagnosis , Lipoproteins/metabolism , Metabolomics/methods , Proteomics/methods , Proton Magnetic Resonance Spectroscopy/methods , SARS-CoV-2/metabolism , Adult , Aged , Biomarkers/blood , Biomarkers/metabolism , COVID-19/blood , COVID-19/virology , Female , Humans , Lipoproteins/blood , Male , Middle Aged , Protein Interaction Maps , SARS-CoV-2/physiology
6.
Proteomics ; 21(10): e2000279, 2021 05.
Article in English | MEDLINE | ID: covidwho-1384282

ABSTRACT

While protein-protein interaction is the first step of the SARS-CoV-2 infection, recent comparative proteomic profiling enabled the identification of over 11,000 protein dynamics, thus providing a comprehensive reflection of the molecular mechanisms underlying the cellular system in response to viral infection. Here we summarize and rationalize the results obtained by various mass spectrometry (MS)-based proteomic approaches applied to the functional characterization of proteins and pathways associated with SARS-CoV-2-mediated infections in humans. Comparative analysis of cell-lines versus tissue samples indicates that our knowledge in proteome profile alternation in response to SARS-CoV-2 infection is still incomplete and the tissue-specific response to SARS-CoV-2 infection can probably not be recapitulated efficiently by in vitro experiments. However, regardless of the viral infection period, sample types, and experimental strategies, a thorough cross-comparison of the recently published proteome, phosphoproteome, and interactome datasets led to the identification of a common set of proteins and kinases associated with PI3K-Akt, EGFR, MAPK, Rap1, and AMPK signaling pathways. Ephrin receptor A2 (EPHA2) was identified by 11 studies including all proteomic platforms, suggesting it as a potential future target for SARS-CoV-2 infection mechanisms and the development of new therapeutic strategies. We further discuss the potentials of future proteomics strategies for identifying prognostic SARS-CoV-2 responsive age-, gender-dependent, tissue-specific protein targets.


Subject(s)
COVID-19/metabolism , Host-Pathogen Interactions , Mass Spectrometry/methods , Proteomics/methods , SARS-CoV-2/physiology , Animals , COVID-19/diagnosis , COVID-19/pathology , Humans , Protein Interaction Mapping/methods , Protein Interaction Maps , Protein Kinases/analysis , Protein Kinases/metabolism , Protein Processing, Post-Translational , Proteome/analysis , Proteome/metabolism , Receptor, EphA2/analysis , Receptor, EphA2/metabolism , Signal Transduction
7.
Proteomics ; 21(7-8): e2000226, 2021 04.
Article in English | MEDLINE | ID: covidwho-1384280

ABSTRACT

A major part of the analysis of parallel reaction monitoring (PRM) data is the comparison of observed fragment ion intensities to a library spectrum. Classically, these libraries are generated by data-dependent acquisition (DDA). Here, we test Prosit, a published deep neural network algorithm, for its applicability in predicting spectral libraries for PRM. For this purpose, we targeted 1529 precursors derived from synthetic viral peptides and analyzed the data with Prosit and DDA-derived libraries. Viral peptides were chosen as an example, because virology is an area where in silico library generation could significantly improve PRM assay design. With both libraries a total of 1174 precursors were identified. Notably, compared to the DDA-derived library, we could identify 101 more precursors by using the Prosit-derived library. Additionally, we show that Prosit can be applied to predict tandem mass spectra of synthetic viral peptides with different collision energies. Finally, we used a spectral library predicted by Prosit and a DDA library to identify SARS-CoV-2 peptides from a simulated oropharyngeal swab demonstrating that both libraries are suited for peptide identification by PRM. Summarized, Prosit-derived viral spectral libraries predicted in silico can be used for PRM data analysis, making DDA analysis for library generation partially redundant in the future.


Subject(s)
COVID-19/virology , Proteomics/methods , SARS-CoV-2/chemistry , Viral Proteins/analysis , Amino Acid Sequence , Humans , Neural Networks, Computer , Peptide Library , Peptides/analysis , Tandem Mass Spectrometry/methods
8.
Sci Rep ; 11(1): 6621, 2021 03 23.
Article in English | MEDLINE | ID: covidwho-1387468

ABSTRACT

The human bronchial epithelium is the first line of defense against atmospheric particles, pollutants, and respiratory pathogens such as the novel SARS-CoV-2. The epithelial cells form a tight barrier and secrete proteins that are major components of the mucosal immune response. Functional in vitro models of the human lung are essential for screening the epithelial response and assessing the toxicity and barrier crossing of drugs, inhaled particles, and pollutants. However, there is a lack of models to investigate the effect of chronic exposure without resorting to animal testing. Here, we developed a 3D model of the human bronchial epithelium using Calu-3 cell line and demonstrated its viability and functionality for 21 days without subculturing. We investigated the effect of reduced Fetal Bovine Serum supplementation in the basal medium and defined the minimal supplementation needed to maintain a functional epithelium, so that the amount of exogenous serum proteins could be reduced during drug testing. The long-term evolution of the epithelial cell secretome was fully characterized by quantitative mass spectrometry in two preclinical models using Calu-3 or primary NHBE cells. 408 common secreted proteins were identified while significant differences in protein abundance were observed with time, suggesting that 7-10 days are necessary to establish a mature secretome in the Calu-3 model. The associated Reactome pathways highlight the role of the secreted proteins in the immune response of the bronchial epithelium. We suggest this preclinical 3D model can be used to evaluate the long-term toxicity of drugs or particles on the human bronchial epithelium, and subsequently to investigate their effect on the epithelial cell secretions.


Subject(s)
Epithelial Cells/metabolism , Proteome/analysis , Proteomics/methods , Angiotensin-Converting Enzyme 2/metabolism , Bronchi/cytology , COVID-19/pathology , COVID-19/virology , Cell Culture Techniques , Cell Line , Culture Media/chemistry , Epithelial Cells/cytology , Humans , Mass Spectrometry , Models, Biological , Principal Component Analysis , SARS-CoV-2/isolation & purification , SARS-CoV-2/physiology
9.
J Proteome Res ; 19(11): 4398-4406, 2020 11 06.
Article in English | MEDLINE | ID: covidwho-1387124

ABSTRACT

Presentation of antigenic peptides by MHCI is central to cellular immune responses against viral pathogens. While adaptive immune responses versus SARS-CoV-2 can be of critical importance to both recovery and vaccine efficacy, how protein antigens from this pathogen are processed to generate antigenic peptides is largely unknown. Here, we analyzed the proteolytic processing of overlapping precursor peptides spanning the entire sequence of the S1 spike glycoprotein of SARS-CoV-2, by three key enzymes that generate antigenic peptides, aminopeptidases ERAP1, ERAP2, and IRAP. All enzymes generated shorter peptides with sequences suitable for binding onto HLA alleles, but with distinct specificity fingerprints. ERAP1 was the most efficient in generating peptides 8-11 residues long, the optimal length for HLA binding, while IRAP was the least efficient. The combination of ERAP1 with ERAP2 greatly limited the variability of peptide sequences produced. Less than 7% of computationally predicted epitopes were found to be produced experimentally, suggesting that aminopeptidase processing may constitute a significant filter to epitope presentation. These experimentally generated putative epitopes could be prioritized for SARS-CoV-2 immunogenicity studies and vaccine design. We furthermore propose that this in vitro trimming approach could constitute a general filtering method to enhance the prediction robustness for viral antigenic epitopes.


Subject(s)
Aminopeptidases/metabolism , Antigens, Viral , Epitopes , Spike Glycoprotein, Coronavirus , Antigens, Viral/chemistry , Antigens, Viral/metabolism , Chromatography, Liquid , Epitopes/chemistry , Epitopes/metabolism , HEK293 Cells , HLA Antigens/chemistry , HLA Antigens/metabolism , Humans , Peptides/analysis , Peptides/chemistry , Peptides/metabolism , Proteomics/methods , Spike Glycoprotein, Coronavirus/chemistry , Spike Glycoprotein, Coronavirus/metabolism , Tandem Mass Spectrometry
10.
BMC Bioinformatics ; 21(Suppl 17): 484, 2020 Dec 14.
Article in English | MEDLINE | ID: covidwho-1388725

ABSTRACT

BACKGROUND: We previously introduced PCPS (Proteasome Cleavage Prediction Server), a web-based tool to predict proteasome cleavage sites using n-grams. Here, we evaluated the ability of PCPS immunoproteasome cleavage model to discriminate CD8+ T cell epitopes. RESULTS: We first assembled an epitope dataset consisting of 844 unique virus-specific CD8+ T cell epitopes and their source proteins. We then analyzed cleavage predictions by PCPS immunoproteasome cleavage model on this dataset and compared them with those provided by a related method implemented by NetChop web server. PCPS was clearly superior to NetChop in term of sensitivity (0.89 vs. 0.79) but somewhat inferior with regard to specificity (0.55 vs. 0.60). Judging by the Mathew's Correlation Coefficient, PCPS predictions were overall superior to those provided by NetChop (0.46 vs. 0.39). We next analyzed the power of C-terminal cleavage predictions provided by the same PCPS model to discriminate CD8+ T cell epitopes, finding that they could be discriminated from random peptides with an accuracy of 0.74. Following these results, we tuned the PCPS web server to predict CD8+ T cell epitopes and predicted the entire SARS-CoV-2 epitope space. CONCLUSIONS: We report an improved version of PCPS named iPCPS for predicting proteasome cleavage sites and peptides with CD8+ T cell epitope features. iPCPS is available for free public use at https://imed.med.ucm.es/Tools/pcps/ .


Subject(s)
Epitopes, T-Lymphocyte , Proteasome Endopeptidase Complex/metabolism , Proteomics/methods , SARS-CoV-2 , Viral Proteins , COVID-19/virology , Epitopes, T-Lymphocyte/chemistry , Epitopes, T-Lymphocyte/metabolism , Humans , Peptides/chemistry , Peptides/metabolism , SARS-CoV-2/chemistry , SARS-CoV-2/metabolism , Software , Viral Proteins/chemistry , Viral Proteins/metabolism
11.
Molecules ; 26(16)2021 Aug 06.
Article in English | MEDLINE | ID: covidwho-1362397

ABSTRACT

Protein glycosylation that mediates interactions among viral proteins, host receptors, and immune molecules is an important consideration for predicting viral antigenicity. Viral spike proteins, the proteins responsible for host cell invasion, are especially important to be examined. However, there is a lack of consensus within the field of glycoproteomics regarding identification strategy and false discovery rate (FDR) calculation that impedes our examinations. As a case study in the overlap between software, here as a case study, we examine recently published SARS-CoV-2 glycoprotein datasets with four glycoproteomics identification software with their recommended protocols: GlycReSoft, Byonic, pGlyco2, and MSFragger-Glyco. These software use different Target-Decoy Analysis (TDA) forms to estimate FDR and have different database-oriented search methods with varying degrees of quantification capabilities. Instead of an ideal overlap between software, we observed different sets of identifications with the intersection. When clustering by glycopeptide identifications, we see higher degrees of relatedness within software than within glycosites. Taking the consensus between results yields a conservative and non-informative conclusion as we lose identifications in the desire for caution; these non-consensus identifications are often lower abundance and, therefore, more susceptible to nuanced changes. We conclude that present glycoproteomics softwares are not directly comparable, and that methods are needed to assess their overall results and FDR estimation performance. Once such tools are developed, it will be possible to improve FDR methods and quantify complex glycoproteomes with acceptable confidence, rather than potentially misleading broad strokes.


Subject(s)
Algorithms , Glycopeptides/analysis , Glycoproteins/analysis , COVID-19/metabolism , Databases, Protein , Glycopeptides/chemistry , Glycoproteins/chemistry , Glycosylation , Humans , Proteomics/methods , Proteomics/standards , SARS-CoV-2/metabolism , Software , Spike Glycoprotein, Coronavirus/analysis , Spike Glycoprotein, Coronavirus/chemistry , Tandem Mass Spectrometry/methods , Viral Fusion Proteins/analysis , Viral Fusion Proteins/chemistry
12.
Cell Death Dis ; 12(8): 788, 2021 08 12.
Article in English | MEDLINE | ID: covidwho-1356553

ABSTRACT

In the last months, many studies have clearly described several mechanisms of SARS-CoV-2 infection at cell and tissue level, but the mechanisms of interaction between host and SARS-CoV-2, determining the grade of COVID-19 severity, are still unknown. We provide a network analysis on protein-protein interactions (PPI) between viral and host proteins to better identify host biological responses, induced by both whole proteome of SARS-CoV-2 and specific viral proteins. A host-virus interactome was inferred, applying an explorative algorithm (Random Walk with Restart, RWR) triggered by 28 proteins of SARS-CoV-2. The analysis of PPI allowed to estimate the distribution of SARS-CoV-2 proteins in the host cell. Interactome built around one single viral protein allowed to define a different response, underlining as ORF8 and ORF3a modulated cardiovascular diseases and pro-inflammatory pathways, respectively. Finally, the network-based approach highlighted a possible direct action of ORF3a and NS7b to enhancing Bradykinin Storm. This network-based representation of SARS-CoV-2 infection could be a framework for pathogenic evaluation of specific clinical outcomes. We identified possible host responses induced by specific proteins of SARS-CoV-2, underlining the important role of specific viral accessory proteins in pathogenic phenotypes of severe COVID-19 patients.


Subject(s)
COVID-19/metabolism , COVID-19/virology , SARS-CoV-2/metabolism , Host Microbial Interactions , Immunity/immunology , Protein Interaction Maps/physiology , Proteome , Proteomics/methods , SARS-CoV-2/pathogenicity , Severity of Illness Index , Viral Proteins/metabolism , Viral Regulatory and Accessory Proteins/metabolism
13.
Sci Immunol ; 6(62)2021 08 10.
Article in English | MEDLINE | ID: covidwho-1352518

ABSTRACT

The IMmunoPhenotyping Assessment in a COVID-19 Cohort (IMPACC) is a prospective longitudinal study designed to enroll 1000 hospitalized patients with COVID-19 (NCT04378777). IMPACC collects detailed clinical, laboratory and radiographic data along with longitudinal biologic sampling of blood and respiratory secretions for in depth testing. Clinical and lab data are integrated to identify immunologic, virologic, proteomic, metabolomic and genomic features of COVID-19-related susceptibility, severity and disease progression. The goals of IMPACC are to better understand the contributions of pathogen dynamics and host immune responses to the severity and course of COVID-19 and to generate hypotheses for identification of biomarkers and effective therapeutics, including optimal timing of such interventions. In this report we summarize the IMPACC study design and protocols including clinical criteria and recruitment, multi-site standardized sample collection and processing, virologic and immunologic assays, harmonization of assay protocols, high-level analyses and the data sharing plans.


Subject(s)
Biomarkers , COVID-19/immunology , COVID-19/virology , Immunophenotyping , SARS-CoV-2/immunology , Biomarkers/blood , COVID-19/diagnosis , COVID-19/epidemiology , Computational Biology/methods , Data Analysis , Gene Expression Profiling , Hospitalization , Humans , Longitudinal Studies , Molecular Diagnostic Techniques/methods , Prospective Studies , Proteomics/methods , United States/epidemiology
14.
Theranostics ; 11(16): 8008-8026, 2021.
Article in English | MEDLINE | ID: covidwho-1337803

ABSTRACT

Rationale: Children usually develop less severe symptoms responding to Coronavirus Disease 2019 (COVID-19) than adults. However, little is known about the molecular alterations and pathogenesis of COVID-19 in children. Methods: We conducted plasma proteomic and metabolomic profilings of the blood samples of a cohort containing 18 COVID-19-children with mild symptoms and 12 healthy children, which were enrolled from hospital admissions and outpatients, respectively. Statistical analyses were performed to identify molecules specifically altered in COVID-19-children. We also developed a machine learning-based pipeline named inference of biomolecular combinations with minimal bias (iBM) to prioritize proteins and metabolites strongly altered in COVID-19-children, and experimentally validated the predictions. Results: By comparing to the multi-omic data in adults, we identified 44 proteins and 249 metabolites differentially altered in COVID-19-children against healthy children or COVID-19-adults. Further analyses demonstrated that both deteriorative immune response/inflammation processes and protective antioxidant or anti-inflammatory processes were markedly induced in COVID-19-children. Using iBM, we prioritized two combinations that contained 5 proteins and 5 metabolites, respectively, each exhibiting a total area under curve (AUC) value of 100% to accurately distinguish COVID-19-children from healthy children or COVID-19-adults. Further experiments validated that all the 5 proteins were up-regulated upon coronavirus infection. Interestingly, we found that the prioritized metabolites inhibited the expression of pro-inflammatory factors, and two of them, methylmalonic acid (MMA) and mannitol, also suppressed coronaviral replication, implying a protective role of these metabolites in COVID-19-children. Conclusion: The finding of a strong antagonism of deteriorative and protective effects provided new insights on the mechanism and pathogenesis of COVID-19 in children that mostly underwent mild symptoms. The identified metabolites strongly altered in COVID-19-children could serve as potential therapeutic agents of COVID-19.


Subject(s)
COVID-19/blood , COVID-19/virology , Adult , COVID-19/epidemiology , COVID-19/immunology , Child , Child, Preschool , China/epidemiology , Female , Hospitalization , Humans , Male , Metabolomics/methods , Middle Aged , Proteomics/methods , SARS-CoV-2/isolation & purification
15.
Life Sci Alliance ; 4(8)2021 08.
Article in English | MEDLINE | ID: covidwho-1282795

ABSTRACT

SARS-CoV-2 infection poses a global health crisis. In parallel with the ongoing world effort to identify therapeutic solutions, there is a critical need for improvement in the prognosis of COVID-19. Here, we report plasma proteome fingerprinting that predict high (hospitalized) and low-risk (outpatients) cases of COVID-19 identified by a platform that combines machine learning with matrix-assisted laser desorption ionization mass spectrometry analysis. Sample preparation, MS, and data analysis parameters were optimized to achieve an overall accuracy of 92%, sensitivity of 93%, and specificity of 92% in dataset without feature selection. We identified two distinct regions in the MALDI-TOF profile belonging to the same proteoforms. A combination of SDS-PAGE and quantitative bottom-up proteomic analysis allowed the identification of intact and truncated forms of serum amyloid A-1 and A-2 proteins, both already described as biomarkers for viral infections in the acute phase. Unbiased discrimination of high- and low-risk COVID-19 patients using a technology that is currently in clinical use may have a prompt application in the noninvasive prognosis of COVID-19. Further validation will consolidate its clinical utility.


Subject(s)
COVID-19/diagnosis , Machine Learning , Proteome/metabolism , Proteomics/methods , SARS-CoV-2/metabolism , Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methods , Adult , Aged , Biomarkers/blood , COVID-19/epidemiology , COVID-19/virology , Female , Humans , Male , Middle Aged , Pandemics , Prognosis , Reproducibility of Results , SARS-CoV-2/physiology , Sensitivity and Specificity , Serum Amyloid A Protein/analysis
17.
Molecules ; 26(11)2021 Jun 02.
Article in English | MEDLINE | ID: covidwho-1273485

ABSTRACT

The human testis and epididymis play critical roles in male fertility, including the spermatogenesis process, sperm storage, and maturation. However, the unique functions of the two organs had not been systematically studied. Herein, we provide a systematic and comprehensive multi-omics study between testis and epididymis. RNA-Seq profiling detected and quantified 19,653 in the testis and 18,407 in the epididymis. Proteomic profiling resulted in the identification of a total of 11,024 and 10,386 proteins in the testis and epididymis, respectively, including 110 proteins that previously have been classified as MPs (missing proteins). Furthermore, Five MPs expressed in testis were validated by the MRM method. Subsequently, multi-omcis between testis and epididymis were performed, including biological functions and pathways of DEGs (Differentially Expressed Genes) in each group, revealing that those differences were related to spermatogenesis, male gamete generation, as well as reproduction. In conclusion, this study can help us find the expression regularity of missing protein and help related scientists understand the physiological functions of testis and epididymis more deeply.


Subject(s)
Epididymis/chemistry , Gene Expression Profiling/methods , Protein Interaction Maps , Proteomics/methods , Testis/chemistry , Chromatography, Liquid , Gene Expression Regulation , Gene Regulatory Networks , High-Throughput Nucleotide Sequencing , Humans , Male , Mutation , Organ Specificity , Sequence Analysis, RNA , Spermatogenesis , Tandem Mass Spectrometry
18.
J Am Soc Mass Spectrom ; 32(7): 1618-1630, 2021 Jul 07.
Article in English | MEDLINE | ID: covidwho-1267989

ABSTRACT

Coronavirus (CoV) nonstructural proteins (nsps) assemble to form the replication-transcription complex (RTC) responsible for viral RNA synthesis. nsp7 and nsp8 are important cofactors of the RTC, as they interact and regulate the activity of RNA-dependent RNA polymerase and other nsps. To date, no structure of the full-length SARS-CoV-2 nsp7:nsp8 complex has been published. The current understanding of this complex is based on structures from truncated constructs, with missing electron densities, or from related CoV species where SARS-CoV-2 nsp7 and nsp8 share upward of 90% sequence identity. Despite available structures solved using crystallography and cryo-EM representing detailed static snapshots of the nsp7:nsp8 complex, it is evident that the complex has a high degree of structural plasticity. However, relatively little is known about the conformational dynamics of the individual proteins and how they complex to interact with other nsps. Here, the solution-based structural proteomic techniques, hydrogen-deuterium exchange mass spectrometry (HDX-MS) and cross-linking mass spectrometry (XL-MS), illuminate the dynamics of SARS-CoV-2 full-length nsp7 and nsp8 proteins and the nsp7:nsp8 protein complex. Results presented from the two techniques are complementary and validate the interaction surfaces identified from the published three-dimensional heterotetrameric crystal structure of the SARS-CoV-2 truncated nsp7:nsp8 complex. Furthermore, mapping of XL-MS data onto higher-order complexes suggests that SARS-CoV-2 nsp7 and nsp8 do not assemble into a hexadecameric structure as implied by the SARS-CoV full-length nsp7:nsp8 crystal structure. Instead, our results suggest that the nsp7:nsp8 heterotetramer can dissociate into a stable dimeric unit that might bind to nsp12 in the RTC without significantly altering nsp7-nsp8 interactions.


Subject(s)
Coronavirus RNA-Dependent RNA Polymerase/chemistry , Proteomics/methods , Viral Nonstructural Proteins/chemistry , COVID-19/virology , Coronavirus RNA-Dependent RNA Polymerase/genetics , Coronavirus RNA-Dependent RNA Polymerase/metabolism , Humans , Hydrogen Deuterium Exchange-Mass Spectrometry , Models, Molecular , Protein Conformation , SARS-CoV-2/chemistry , Viral Nonstructural Proteins/genetics , Viral Nonstructural Proteins/metabolism
19.
Nat Commun ; 12(1): 3406, 2021 06 07.
Article in English | MEDLINE | ID: covidwho-1260941

ABSTRACT

Prognostic characteristics inform risk stratification in intensive care unit (ICU) patients with coronavirus disease 2019 (COVID-19). We obtained blood samples (n = 474) from hospitalized COVID-19 patients (n = 123), non-COVID-19 ICU sepsis patients (n = 25) and healthy controls (n = 30). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was detected in plasma or serum (RNAemia) of COVID-19 ICU patients when neutralizing antibody response was low. RNAemia is associated with higher 28-day ICU mortality (hazard ratio [HR], 1.84 [95% CI, 1.22-2.77] adjusted for age and sex). RNAemia is comparable in performance to the best protein predictors. Mannose binding lectin 2 and pentraxin-3 (PTX3), two activators of the complement pathway of the innate immune system, are positively associated with mortality. Machine learning identified 'Age, RNAemia' and 'Age, PTX3' as the best binary signatures associated with 28-day ICU mortality. In longitudinal comparisons, COVID-19 ICU patients have a distinct proteomic trajectory associated with mortality, with recovery of many liver-derived proteins indicating survival. Finally, proteins of the complement system and galectin-3-binding protein (LGALS3BP) are identified as interaction partners of SARS-CoV-2 spike glycoprotein. LGALS3BP overexpression inhibits spike-pseudoparticle uptake and spike-induced cell-cell fusion in vitro.


Subject(s)
COVID-19/prevention & control , Critical Care/statistics & numerical data , Proteomics/methods , RNA, Viral/genetics , SARS-CoV-2/genetics , Adult , Animals , Antibodies, Neutralizing/immunology , Antigens, Neoplasm/metabolism , Biomarkers, Tumor/metabolism , C-Reactive Protein/metabolism , COVID-19/metabolism , COVID-19/virology , Female , HEK293 Cells , Humans , Kaplan-Meier Estimate , Male , Middle Aged , RNA, Viral/blood , SARS-CoV-2/metabolism , SARS-CoV-2/physiology , Serum Amyloid P-Component/metabolism , Spike Glycoprotein, Coronavirus/immunology , Spike Glycoprotein, Coronavirus/metabolism , Viral Load/immunology
20.
Anal Bioanal Chem ; 413(29): 7265-7275, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1235721

ABSTRACT

COVID-19 is the most disturbing pandemic of the past hundred years. Its causative agent, the SARS-CoV-2 virus, has been the subject of an unprecedented investigation to characterize its molecular structure and intimate functioning. While markers for its detection have been proposed and several diagnostic methodologies developed, its propensity to evolve and evade diagnostic tools and the immune response is of great concern. The recent spread of new variants with increased infectivity requires even more attention. Here, we document how shotgun proteomics can be useful for rapidly monitoring the evolution of the SARS-CoV-2 virus. We evaluated the heterogeneity of purified SARS-CoV-2 virus obtained after culturing in the Vero E6 cell line. We found that cell culture induces significant changes that are translated at the protein level, such changes being detectable by tandem mass spectrometry. Production of viral particles requires careful quality control which can be easily performed by shotgun proteomics. Although considered relatively stable so far, the SARS-CoV-2 genome turns out to be prone to frequent variations. Therefore, the sequencing of SARS-CoV-2 variants from patients reporting only the consensus genome after its amplification would deserve more attention and could benefit from more in-depth analysis of low level but crystal-clear signals, as well as complementary and rapid analysis by shotgun proteomics.


Subject(s)
Genome, Viral , Proteomics/methods , SARS-CoV-2/isolation & purification , Amino Acid Sequence , Cell Culture Techniques , Humans , Real-Time Polymerase Chain Reaction/methods , SARS-CoV-2/genetics , SARS-CoV-2/pathogenicity , Tandem Mass Spectrometry/methods , Viral Proteins/chemistry , Virulence
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