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1.
Nat Commun ; 12(1): 6073, 2021 10 18.
Article in English | MEDLINE | ID: covidwho-1860369

ABSTRACT

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further utilize a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data-dependent acquisition-based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies.


Subject(s)
Glycopeptides/analysis , Proteome/analysis , Proteomics/methods , Algorithms , Blood Proteins/chemistry , Glycoproteins/chemistry , Humans , Mass Spectrometry , Polysaccharides/chemistry , Schizosaccharomyces pombe Proteins/chemistry , Workflow
2.
Biomark Med ; 16(8): 589-597, 2022 06.
Article in English | MEDLINE | ID: covidwho-1855268

ABSTRACT

Aim: To investigate the change in a serum level of copeptin, a neuroendocrine biomarker, in differentiating grades of COVID-19 severity on admission time and to find its diagnostic potential. Materials & Methods: 160 COVID-19 patients were classified according to disease severity into 80 mild to moderate and 80 severe patients. Serum copeptin level was assessed by ELISA on their admission time. Besides, serum CRP, ferritin and D-dimer were estimated. Results: Severe COVID-19 patients showed higher serum copeptin level in comparison to mild to moderate cases, with diagnostic potential to distinguish disease severity with 93.33% sensitivity and 100% specificity at cutoff value >18.5 Pmol/l. Conclusion: Serum copeptin was remarkably increased with COVID-19 severity with reasonable differentiation potential for recently admitted patients.


We conducted a biochemical study on the role of copeptin ­ a biomarker of acute stress due to COVID-19 infection ­ in classification of COVID-19 severity on admission over 160 adult patients. Copeptin was highly elevated in severe cases more than the mild to moderate ones. So, it may be an early marker in admission departments to ease early clinical decisions and medical intervention.


Subject(s)
COVID-19 , Biomarkers , COVID-19/diagnosis , Glycopeptides , Humans , Prognosis , Severity of Illness Index
3.
J Am Chem Soc ; 144(20): 9057-9065, 2022 05 25.
Article in English | MEDLINE | ID: covidwho-1839492

ABSTRACT

Glycosylation of proteins is a complicated post-translational modification. Despite the significant progress in glycoproteomics, accurate functions of glycoproteins are still ambiguous owing to the difficulty in obtaining homogeneous glycopeptides or glycoproteins. Here, we describe a streamlined chemoenzymatic method to prepare complex glycopeptides by integrating hydrophobic tag-supported chemical synthesis and enzymatic glycosylations. The hydrophobic tag is utilized to facilitate peptide chain elongation in the liquid phase and expeditious product separation. After removal of the tag, a series of glycans are installed on the peptides via efficient glycosyltransferase-catalyzed reactions. The general applicability and robustness of this approach are exemplified by efficient preparation of 16 well-defined SARS-CoV-2 O-glycopeptides, 4 complex MUC1 glycopeptides, and a 31-mer glycosylated glucagon-like peptide-1. Our developed approach will open up a new range of easy access to various complex glycopeptides of biological importance.


Subject(s)
COVID-19 , Glycopeptides , SARS-CoV-2 , Glycopeptides/chemical synthesis , Glycopeptides/chemistry , Glycoproteins/chemistry , Glycosylation , Humans , Peptides/metabolism , SARS-CoV-2/chemistry
4.
Viruses ; 14(3)2022 03 07.
Article in English | MEDLINE | ID: covidwho-1732249

ABSTRACT

Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glycoisoform distributions of 597 abundant serum glycopeptides and nonglycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR < 0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glycoisoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding and, potentially, the clinical management of serious acute infectious conditions.


Subject(s)
COVID-19 , Artificial Intelligence , COVID-19/diagnosis , Chromatography, Liquid/methods , Glycopeptides/analysis , Glycopeptides/chemistry , Glycopeptides/metabolism , Glycoproteins , Humans
5.
Sci Rep ; 11(1): 23561, 2021 12 07.
Article in English | MEDLINE | ID: covidwho-1559302

ABSTRACT

N-glycosylation plays an important role in the structure and function of membrane and secreted proteins. The spike protein on the surface of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, is heavily glycosylated and the major target for developing vaccines, therapeutic drugs and diagnostic tests. The first major SARS-CoV-2 variant carries a D614G substitution in the spike (S-D614G) that has been associated with altered conformation, enhanced ACE2 binding, and increased infectivity and transmission. In this report, we used mass spectrometry techniques to characterize and compare the N-glycosylation of the wild type (S-614D) or variant (S-614G) SARS-CoV-2 spike glycoproteins prepared under identical conditions. The data showed that half of the N-glycosylation sequons changed their distribution of glycans in the S-614G variant. The S-614G variant showed a decrease in the relative abundance of complex-type glycans (up to 45%) and an increase in oligomannose glycans (up to 33%) on all altered sequons. These changes led to a reduction in the overall complexity of the total N-glycosylation profile. All the glycosylation sites with altered patterns were in the spike head while the glycosylation of three sites in the stalk remained unchanged between S-614G and S-614D proteins.


Subject(s)
Glycopeptides/analysis , Mass Spectrometry/methods , SARS-CoV-2/metabolism , Spike Glycoprotein, Coronavirus/metabolism , Angiotensin-Converting Enzyme 2/chemistry , Angiotensin-Converting Enzyme 2/metabolism , COVID-19/pathology , COVID-19/virology , Chromatography, High Pressure Liquid , Glycosylation , Humans , Mutation , Protein Binding , Protein Structure, Tertiary , SARS-CoV-2/isolation & purification , Spike Glycoprotein, Coronavirus/chemistry
6.
Clin Res Cardiol ; 111(3): 343-354, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1516853

ABSTRACT

BACKGROUND: COVID-19 has been associated with a high prevalence of myocardial injury and increased cardiovascular morbidity. Copeptin, a marker of vasopressin release, has been previously established as a risk marker in both infectious and cardiovascular disease. METHODS: This prospective, observational study of patients with laboratory-confirmed COVID-19 infection was conducted from June 6th to November 26th, 2020 in a tertiary care hospital. Copeptin and high-sensitive cardiac troponin I (hs-cTnI) levels on admission were collected and tested for their association with the primary composite endpoint of ICU admission or 28-day mortality. RESULTS: A total of 213 eligible patients with COVID-19 were included of whom 55 (25.8%) reached the primary endpoint. Median levels of copeptin and hs-cTnI at admission were significantly higher in patients with an adverse outcome (Copeptin 29.6 pmol/L, [IQR, 16.2-77.8] vs 17.2 pmol/L [IQR, 7.4-41.0] and hs-cTnI 22.8 ng/L [IQR, 11.5-97.5] vs 10.2 ng/L [5.5-23.1], P < 0.001 respectively). ROC analysis demonstrated an optimal cut-off of 19.3 pmol/L for copeptin and 16.8 ng/L for hs-cTnI and an increase of either biomarker was significantly associated with the primary endpoint. The combination of raised hs-cTnI and copeptin yielded a superior prognostic value to individual measurement of biomarkers and was a strong prognostic marker upon multivariable logistic regression analysis (OR 4.274 [95% CI, 1.995-9.154], P < 0.001). Addition of copeptin and hs-cTnI to established risk models improved C-statistics and net reclassification indices. CONCLUSION: The combination of raised copeptin and hs-cTnI upon admission is an independent predictor of ICU admission or 28-day mortality in hospitalized patients with COVID-19.


Subject(s)
COVID-19/blood , COVID-19/mortality , Glycopeptides/blood , Patient Admission/statistics & numerical data , Troponin I/blood , Aged , Biomarkers/blood , Female , Hospital Mortality , Humans , Intensive Care Units , Male , Middle Aged , Predictive Value of Tests , Prognosis , Prospective Studies , ROC Curve , SARS-CoV-2
7.
Glycobiology ; 32(1): 60-72, 2022 02 26.
Article in English | MEDLINE | ID: covidwho-1501077

ABSTRACT

Extensive glycosylation of the spike protein of severe acute respiratory syndrome coronavirus 2 virus not only shields the major part of it from host immune responses, but glycans at specific sites also act on its conformation dynamics and contribute to efficient host receptor binding, and hence infectivity. As variants of concern arise during the course of the coronavirus disease of 2019 pandemic, it is unclear if mutations accumulated within the spike protein would affect its site-specific glycosylation pattern. The Alpha variant derived from the D614G lineage is distinguished from others by having deletion mutations located right within an immunogenic supersite of the spike N-terminal domain (NTD) that make it refractory to most neutralizing antibodies directed against this domain. Despite maintaining an overall similar structural conformation, our mass spectrometry-based site-specific glycosylation analyses of similarly produced spike proteins with and without the D614G and Alpha variant mutations reveal a significant shift in the processing state of N-glycans on one specific NTD site. Its conversion to a higher proportion of complex type structures is indicative of altered spatial accessibility attributable to mutations specific to the Alpha variant that may impact its transmissibility. This and other more subtle changes in glycosylation features detected at other sites provide crucial missing information otherwise not apparent in the available cryogenic electron microscopy-derived structures of the spike protein variants.


Subject(s)
COVID-19/epidemiology , Glycopeptides/chemistry , Mutation , Polysaccharides/chemistry , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus/chemistry , Angiotensin-Converting Enzyme 2/genetics , Angiotensin-Converting Enzyme 2/metabolism , COVID-19/transmission , COVID-19/virology , Carbohydrate Sequence , Datasets as Topic , Glycopeptides/genetics , Glycopeptides/metabolism , Glycosylation , HEK293 Cells , Humans , Mass Spectrometry , Peptide Mapping , Polysaccharides/metabolism , Protein Binding , Receptors, Virus/genetics , Receptors, Virus/metabolism , Recombinant Proteins/chemistry , Recombinant Proteins/genetics , Recombinant Proteins/metabolism , SARS-CoV-2/pathogenicity , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/metabolism
8.
Rev Assoc Med Bras (1992) ; 67(8): 1137-1142, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1477630

ABSTRACT

OBJETIVE: Coronavirus disease 2019 (COVID-19) has quickly turned into a health problem globally. Early and effective predictors of disease severity are needed to improve the management of the patients affected with COVID-19. Copeptin, a 39-amino acid glycopeptide, is known as a C-terminal unit of the precursor pre-provasopressin (pre-proAVP). Activation of AVP system stimulates copeptin secretion in equimolar amounts with AVP. This study aimed to determine serum copeptin levels in the patients with COVID-19 and to examine the relationship between serum copeptin levels and the severity of the disease. METHODS: The study included 90 patients with COVID-19. The patients with COVID-19 were divided into two groups according to disease severity as mild/moderate disease (n=35) and severe disease (n=55). All basic demographic and clinical data of the patients were recorded and blood samples were collected. RESULTS: Copeptin levels were significantly higher in the patients with severe COVID-19 compared with the patients with mild/moderate COVID-19 (p<0.001). Copeptin levels were correlated with ferritin and fibrinogen levels positively (r=0.32, p=0.002 and r=0.25, p=0.019, respectively), and correlated with oxygen saturation negatively (r=-0.37, p<0.001). In the multivariate logistic regression analysis, it was revealed that copeptin (OR: 2.647, 95%CI 1.272-5.510; p=0.009) was an independent predictor of severe COVID-19 disease. A cutoff value of 7.84 ng/mL for copeptin predicted severe COVID-19 with a sensitivity of 78% and a specificity of 80% (AUC: 0.869, 95%CI 0.797-0.940; p<0.001). CONCLUSION: Copeptin could be used as a favorable prognostic biomarker while determining the disease severity in COVID-19.


Subject(s)
COVID-19 , Biomarkers , Glycopeptides , Humans , Prognosis , SARS-CoV-2
10.
Anal Bioanal Chem ; 413(29): 7215-7227, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1375628

ABSTRACT

Glycosylation analysis of viral glycoproteins contributes significantly to vaccine design and development. Among other benefits, glycosylation analysis allows vaccine developers to assess the impact of construct design or producer cell line choices for vaccine production, and it is a key measure by which glycoproteins that are produced for use in vaccination can be compared to their native viral forms. Because many viral glycoproteins are multiply glycosylated, glycopeptide analysis is a preferrable approach for mapping the glycans, yet the analysis of glycopeptide data can be cumbersome and requires the expertise of an experienced analyst. In recent years, a commercial software product, Byonic, has been implemented in several instances to facilitate glycopeptide analysis on viral glycoproteins and other glycoproteomics data sets, and the purpose of the study herein is to determine the strengths and limitations of using this software, particularly in cases relevant to vaccine development. The glycopeptides from a recombinantly expressed trimeric S glycoprotein of the SARS-CoV-2 virus were first analyzed using an expert-based analysis strategy; subsequently, analysis of the same data set was completed using Byonic. Careful assessment of instances where the two methods produced different results revealed that the glycopeptide assignments from Byonic contained more false positives than true positives, even when the data were assessed using a 1% false discovery rate. The work herein provides a roadmap for removing the spurious assignments that Byonic generates, and it provides an assessment of the opportunity cost for relying on automated assignments for glycopeptide data sets from viral glycoproteins.


Subject(s)
Glycopeptides/metabolism , Spike Glycoprotein, Coronavirus/metabolism , Algorithms , Amino Acid Sequence , Chromatography, Liquid/methods , Spike Glycoprotein, Coronavirus/chemistry , Tandem Mass Spectrometry/methods
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.
Commun Biol ; 4(1): 934, 2021 08 03.
Article in English | MEDLINE | ID: covidwho-1341013

ABSTRACT

We describe an analytical method for the identification, mapping and relative quantitation of glycopeptides from SARS-CoV-2 Spike protein. The method may be executed using a LC-TOF mass spectrometer, requires no specialized knowledge of glycan analysis and exploits the differential resolving power of reverse phase HPLC. While this separation technique resolves peptides with high efficiency, glycans are resolved poorly, if at all. Consequently, glycopeptides consisting of the same peptide bearing different glycan structures will all possess very similar retention times and co-elute. Rather than a disadvantage, we show that shared retention time can be used to map multiple glycan species to the same peptide and location. In combination with MSMS and pseudo MS3, we have constructed a detailed mass-retention time database for Spike glycopeptides. This database allows any accurate mass LC-MS laboratory to reliably identify and quantify Spike glycopeptides from a single overnight elastase digest in less than 90 minutes.


Subject(s)
Glycopeptides/chemistry , Mass Spectrometry/methods , Spike Glycoprotein, Coronavirus/chemistry , Databases, Protein , Time Factors
13.
J Proteome Res ; 20(9): 4475-4486, 2021 09 03.
Article in English | MEDLINE | ID: covidwho-1333872

ABSTRACT

A method for representing and comparing distributions of N-linked glycans located at specific sites on proteins is presented. The representation takes the form of a simple mass spectrum for a given peptide sequence, with each peak corresponding to a different glycopeptide. The mass (in place of m/z) of each peak is that of the glycan mass, and its abundance corresponds to its relative abundance in the electrospray MS1 spectrum. This provides a facile means of representing all identifiable glycopeptides arising from a single protein "sequon" on a specific sequence, thereby enabling the comparison and searching of these distributions as routinely done for mass spectra. Likewise, these reference glycopeptide abundance distribution spectra (GADS) can be stored in searchable libraries. A set of such libraries created from available data is provided along with an adapted version of the widely used NIST-MS library-search software. Since GADS contain only MS1 abundances and identifications, they are equally suitable for expressing collision-induced fragmentation and electron-transfer dissociation determinations of glycopeptide identity. Comparisons of GADS for N-glycosylated sites on several proteins, especially the SARS-CoV-2 spike protein, demonstrate the potential reproducibility of GADS and their utility for comparing site-specific distributions.


Subject(s)
COVID-19 , Glycopeptides/metabolism , Glycoproteins , Glycosylation , Humans , Polysaccharides , Reproducibility of Results , SARS-CoV-2 , Spike Glycoprotein, Coronavirus
15.
Front Immunol ; 12: 698672, 2021.
Article in English | MEDLINE | ID: covidwho-1295644

ABSTRACT

The world is currently experiencing the coronavirus disease 2019 (COVID-19) pandemic caused by Severe Acute Respiratory Syndrome-2 (SARS-CoV-2). Its global spread has resulted in millions of confirmed infections and deaths. While the global pandemic continues to grow, the availability of drugs to treat COVID-19 infections remains limited to supportive treatments. Moreover, the current speed of vaccination campaigns in many countries has been slow. Natural substrates with biological immunomodulatory activity, such as glucans, may represent an adjuvant therapeutic agent to treat SARS-CoV-2. AM3, a natural glycophosphopeptical, has previously been shown to effectively slow, with no side effects, the progression of infectious respiratory diseases by regulating effects on innate and adaptive immunity in experimental models. No clinical studies, however, exist on the use of AM3 in SARS-CoV-2 infected patients. This review aims to summarize the beneficial effects of AM3 on respiratory diseases, the inflammatory response, modulation of immune response, and attenuation of muscle. It will also discuss its potential effects as an immune system adjuvant for the treatment of COVID-19 infections and adjuvant for SARS-CoV-2 vaccination.


Subject(s)
Adjuvants, Immunologic/pharmacology , COVID-19/diet therapy , Calcium Phosphates/pharmacology , Dietary Supplements , Glycopeptides/pharmacology , Immunomodulation/immunology , SARS-CoV-2/drug effects , COVID-19 Vaccines/immunology , Cytokines/immunology , Humans , SARS-CoV-2/immunology , Vaccination
16.
Chem Commun (Camb) ; 57(55): 6804-6807, 2021 Jul 08.
Article in English | MEDLINE | ID: covidwho-1284708

ABSTRACT

Glycosylation plays important roles in SARS-CoV-2 infection. We describe here a facile chemoenzymatic synthesis of core-fucosylated N-glycopeptides derived from the SARS-CoV-2 Spike protein and their binding with glycan-dependent neutralizing antibody S309 and human lectin CLEC4G. The synthetic glycopeptides provide tools for further functional characterization of viral glycosylation.


Subject(s)
Glycopeptides/chemical synthesis , Glycopeptides/metabolism , Spike Glycoprotein, Coronavirus/chemistry , Antibodies, Neutralizing/immunology , Chemistry Techniques, Synthetic , Glycopeptides/chemistry , Glycopeptides/immunology , Glycosylation , Polysaccharides/metabolism
17.
Anal Bioanal Chem ; 413(29): 7295-7303, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1274805

ABSTRACT

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents a serious threat to human health all over the world. The development of effective vaccines has been focusing on the spike (S) glycoprotein, which mediates viral invasion to human cells through its interaction with the angiotensin-converting enzyme 2 (ACE2) receptor. In this work, we perform analytical characterization of N- and O-linked glycosylation of the SARS-CoV-2 S glycoprotein. We explore the novel use of dual-functionalized titanium (IV)-immobilized metal affinity chromatography (Ti-IMAC) material for simultaneous enrichment and separation of neutral and sialyl glycopeptides of a recombinant SARS-CoV-2 S glycoprotein from HEK293 cells. This strategy helps eliminate signal suppression from neutral glycopeptides for the detection of sialyl glycopeptides and improves the glycoform coverage of the S protein. We profiled 19 of its 22 potential N-glycosylated sites with 398 unique glycoforms using the dual-functional Ti-IMAC approach, which exhibited improvement of coverage by 1.6-fold compared to the conventional hydrophilic interaction chromatography (HILIC) glycopeptide enrichment method. We also identified O-linked glycosylation site that was not found using the conventional HILIC approach. In addition, we reported on the identification of mannose-6-phosphate (M6P) glycosylation, which substantially expands the current knowledge of the spike protein's glycosylation landscape and enables future investigation into the influence of M6P glycosylation of the spike protein on its cell entry.


Subject(s)
Glycopeptides/isolation & purification , N-Acetylneuraminic Acid/chemistry , SARS-CoV-2/chemistry , Spike Glycoprotein, Coronavirus/chemistry , Amino Acid Sequence , Chromatography, Liquid/methods , Glycopeptides/chemistry , HEK293 Cells , Humans , Mannosephosphates/chemistry , Static Electricity , Tandem Mass Spectrometry/methods
18.
Ann Clin Microbiol Antimicrob ; 20(1): 37, 2021 May 21.
Article in English | MEDLINE | ID: covidwho-1238722

ABSTRACT

BACKGROUND: Drug repurposing otherwise known as drug repositioning or drug re-profiling is a time-tested approach in drug discovery through which new medical uses are being established for already known drugs. Antibiotics are among the pharmacological agents being investigated for potential anti-SARS-COV-2 activities. The antibiotics are used either to resolve bacterial infections co-existing with COVID-19 infections or exploitation of their potential antiviral activities. Herein, we aimed to review the various antibiotics that have been repositioned for the management of COVID-19. METHODS: This literature review was conducted from a methodical search on PubMed and Web of Science regarding antibiotics used in patients with COVID-19 up to July 5, 2020. RESULTS: Macrolide and specifically azithromycin is the most common antibiotic used in the clinical management of COVID-19. The other antibiotics used in COVID-19 includes teicoplanin, clarithromycin, doxycycline, tetracyclines, levofloxacin, moxifloxacin, ciprofloxacin, and cefuroxime. In patients with COVID-19, antibiotics are used for their immune-modulating, anti-inflammatory, and antiviral properties. The precise antiviral mechanism of most of these antibiotics has not been determined. Moreover, the use of some of these antibiotics against SARS-CoV-2 infection remains highly controversial and not widely accepted. CONCLUSION: The heavy use of antibiotics during the COVID-19 pandemic would likely worsen antibiotic resistance crisis. Consequently, antibiotic stewardship should be strengthened in order to prevent the impacts of COVID-19 on the antibiotic resistance crisis.


Subject(s)
Anti-Bacterial Agents/therapeutic use , COVID-19/drug therapy , Drug Repositioning , SARS-CoV-2 , Aminoglycosides/therapeutic use , Fluoroquinolones/therapeutic use , Glycopeptides/therapeutic use , Humans , Macrolides/therapeutic use
19.
J Med Virol ; 93(5): 3113-3121, 2021 May.
Article in English | MEDLINE | ID: covidwho-1196540

ABSTRACT

The clinical symptoms of community-acquired pneumonia (CAP) and coronavirus disease 2019 (COVID-19)-associated pneumonia are similar. Effective predictive markers are needed to differentiate COVID-19 pneumonia from CAP in the current pandemic conditions. Copeptin, a 39-aminoacid glycopeptide, is a C-terminal part of the precursor pre-provasopressin (pre-proAVP). The activation of the AVP system stimulates copeptin secretion in equimolar amounts with AVP. This study aims to determine serum copeptin levels in patients with CAP and COVID-19 pneumonia and to analyze the power of copeptin in predicting COVID-19 pneumonia. The study consists of 98 patients with COVID-19 and 44 patients with CAP. The basic demographic and clinical data of all patients were recorded, and blood samples were collected. The receiver operating characteristic (ROC) curve was generated and the area under the ROC curve (AUC) was measured to evaluate the discriminative ability. Serum copeptin levels were significantly higher in COVID-19 patients compared to CAP patients (10.2 ± 4.4 ng/ml and 7.1 ± 3.1 ng/ml; p < .001). Serum copeptin levels were positively correlated with leukocyte, neutrophil, and platelet count (r = -.21, p = .012; r = -.21, p = .013; r = -.20, p = .018; respectively). The multivariable logistic regression analysis revealed that increased copeptin (odds ratio [OR] = 1.183, 95% confidence interval [CI], 1.033-1.354; p = .015) and CK-MB (OR = 1.052, 95% CI, 1.013-1.092; p = .008) levels and decreased leukocyte count (OR = 0.829, 95% CI, 0.730-0.940; p = .004) were independent predictors of COVID-19 pneumonia. A cut-off value of 6.83 ng/ml for copeptin predicted COVID-19 with a sensitivity of 78% and a specificity of 73% (AUC: 0.764% 95 Cl: 0.671-0.856, p < .001). Copeptin could be a promising and useful biomarker to be used to distinguish COVID-19 patients from CAP patients.


Subject(s)
COVID-19/diagnosis , Glycopeptides/blood , Pneumonia, Bacterial/diagnosis , SARS-CoV-2 , Adult , Aged , Aged, 80 and over , Biomarkers/blood , Community-Acquired Infections , Female , Glycopeptides/metabolism , Humans , Logistic Models , Male , Middle Aged
20.
Mass Spectrom Rev ; 41(3): 488-507, 2022 05.
Article in English | MEDLINE | ID: covidwho-1001950

ABSTRACT

Proteomics studies allow for the determination of the identity, amount, and interactions of proteins under specific conditions that allow the biological state of an organism to ultimately change. These conditions can be either beneficial or detrimental. Diseases are due to detrimental changes caused by either protein overexpression or underexpression caused by as a result of a mutation or posttranslational modifications (PTM), among other factors. Identification of disease biomarkers through proteomics can be potentially used as clinical information for diagnostics. Common biomarkers to look for include PTM. For example, aberrant glycosylation of proteins is a common marker and will be a focus of interest in this review. A common way to analyze glycoproteins is by glycoproteomics involving mass spectrometry. Due to factors such as micro- and macroheterogeneity which result in a lower abundance of each version of a glycoprotein, it is difficult to obtain meaningful results unless rigorous sample preparation procedures are in place. Microheterogeneity represents the diversity of glycans at a single site, whereas macroheterogeneity depicts glycosylation levels at each site of a protein. Enrichment and derivatization of glycopeptides help to overcome these limitations. Over the time range of 2016 to 2020, several methods have been proposed in the literature and have contributed to drastically improve the outcome of glycosylation analysis, as presented in the sampling surveyed in this review. As a current topic in 2020, glycoproteins carried by pathogens can also cause disease and this is seen with SARS CoV2, causing the COVID-19 pandemic. This review will discuss glycoproteomic studies of the spike glycoprotein and interacting proteins such as the ACE2 receptor.


Subject(s)
COVID-19 , Glycopeptides , Glycopeptides/analysis , Glycoproteins/analysis , Glycosylation , Humans , Mass Spectrometry/methods , Pandemics
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