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Quantitative N-glycoproteomics reveals altered glycosylation levels of various plasma proteins in bloodstream infected patients.

ABSTRACT: Bloodstream infections are associated with high morbidity and mortality with rates varying from 10-25% and higher. Appropriate and timely onset of antibiotic therapy influences the prognosis of these patients. It requires the diagnostic accuracy which is not afforded by current gold standards such as blood culture. Moreover, the time from blood sampling to blood culture results is a key determinant of reducing mortality. No established biomarkers exist which can differentiate bloodstream infections from other systemic inflammatory conditions. This calls for studies on biomarkers potential of molecular profiling of plasma as it is affected most by the molecular changes accompanying bloodstream infections. N-glycosylation is a post-translational modification which is very sensitive to changes in physiology. Here we have performed targeted quantitative N-glycoproteomics from plasma samples of patients with confirmed positive blood culture together with age and sex matched febrile controls with negative blood culture reports. Three hundred and sixty eight potential N-glycopeptides were quantified by mass spectrometry and 149 were further selected for identification. Twenty four N-glycopeptides were identified with high confidence together with elucidation of the peptide sequence, N-glycosylation site, glycan composition and proposed glycan structures. Principal component analysis, orthogonal projections to latent structures-discriminant analysis (S-Plot) and self-organizing maps clustering among other statistical methods were employed to analyze the data. These methods gave us clear separation of the two patient classes. We propose high-confidence N-glycopeptides which have the power to separate the bloodstream infections from blood culture negative febrile patients and shed light on host response during bacteremia. Data are available via ProteomeXchange with identifier PXD009048.

SUBMITTER: Joenvaara S

PROVIDER: S-EPMC5875812 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Quantitative N-glycoproteomics reveals altered glycosylation levels of various plasma proteins in bloodstream infected patients.

Joenvaara Sakari S Saraswat Mayank M Kuusela Pentti P Saraswat Shruti S Agarwal Rahul R Kaartinen Johanna J Järvinen Asko A Renkonen Risto R

PloS one 20180329 3

Bloodstream infections are associated with high morbidity and mortality with rates varying from 10-25% and higher. Appropriate and timely onset of antibiotic therapy influences the prognosis of these patients. It requires the diagnostic accuracy which is not afforded by current gold standards such as blood culture. Moreover, the time from blood sampling to blood culture results is a key determinant of reducing mortality. No established biomarkers exist which can differentiate bloodstream infecti ...[more]

PMID: 29596458

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Project description:BACKGROUND:Visceral leishmaniasis (VL) is a deadly parasitic diseases caused by Leishmania donovani; it is a major health problem in many countries. A lack of proper understanding of the disease biology, poor diagnostic methods and increasing drug resistance are the main reasons for the growing burden of VL infection. Comparative plasma proteomics are a relatively useful technique that can be used to investigate disease-associated alterations that can help in understanding host responses against pathogens, and might be useful in disease management and diagnosis. RESULT:In this study, a comparative proteomics and glycoproteomics approach using 2DE and 2D-DIGE was employed between early diagnosed VL patients of all age groups and healthy endemic and non-endemic controls in order to aid the recognition of disease-associated alterations in host plasma. Comparative proteomics was performed by the depletion of seven highly abundant plasma proteins. Comparative glycoproteomics was performed by the depletion of albumin and IgG, followed by purification of plasma glycoproteins using a multi lectin affinity column. From these two approaches, 39 differentially expressed protein spots were identified and sequenced using MALDI-TOF/TOF mass spectrometry. This revealed ten distinct proteins that appeared in multiple spots, suggesting micro-heterogeneity. Among these proteins, alpha-1-antitrypsin, alpha-1-B glycoprotein and amyloid-A1 precursor were up-regulated, whereas vitamin-D binding protein, apolipoprotein-A-I and transthyretin were down-regulated in VL. Alterations in the levels of these proteins in VL-infected plasma were further confirmed by western blot and ELISA. CONCLUSIONS:These proteins may be involved in the survival of parasites, resisting neutrophil elastase, and in their multiplication in macrophages, potentially maintaining endogenous anti-inflammatory and immunosuppressive conditions. Consequently, the results of this study may help in understanding the host response against L.donovani, which could help in the discovery of new drugs and disease management. Finally, these alterations on protein levels might be beneficial in improving early diagnosis considering those as biomarkers in Indian VL.

Project description:Aims/hypothesisIndividual variation in plasma N-glycosylation has mainly been studied in the context of diabetes complications, and its role in type 1 diabetes onset is largely unknown. Our aims were to undertake a detailed characterisation of the plasma and IgG N-glycomes in patients with recent onset type 1 diabetes, and to evaluate their discriminative potential in risk assessment.MethodsIn the first part of the study, plasma and IgG N-glycans were chromatographically analysed in a study population from the DanDiabKids registry, comprising 1917 children and adolescents (0.6-19.1 years) who were newly diagnosed with type 1 diabetes. A follow-up study compared the results for 188 of these participants with those for their 244 unaffected siblings. Correlation of N-glycan abundance with the levels and number of various autoantibodies (against IA-2, GAD, ZnT8R, ZnT8W), as well as with sex and age at diagnosis, were estimated by using general linear modelling. A disease predictive model was built using logistic mixed-model elastic net regression, and evaluated using a 10-fold cross-validation.ResultsOur study showed that onset of type 1 diabetes was associated with an increase in the proportion of plasma and IgG high-mannose and bisecting GlcNAc structures, a decrease in monogalactosylation, and an increase in IgG disialylation. ZnT8R autoantibody levels were associated with higher IgG digalactosylated glycan with bisecting GlcNAc. Finally, an increase in the number of autoantibodies (which is a better predictor of progression to overt diabetes than the level of any individual antibody) was accompanied by a decrease in the proportions of some of the highly branched plasma N-glycans. Models including age, sex and N-glycans yielded notable discriminative power between children with type 1 diabetes and their healthy siblings, with AUCs of 0.915 and 0.869 for addition of plasma and IgG N-glycans, respectively.Conclusions/interpretationWe defined N-glycan changes accompanying onset of type 1 diabetes, and developed a predictive model based on N-glycan profiles that could have valuable potential in risk assessment. Increasing the power of tests to identify individuals at risk of disease development would be a considerable asset for type 1 diabetes prevention trials.

Project description:Sepsis remains a predominant cause of mortality in the ICU, yet strategies to increase survival have proved largely unsuccessful. This study aimed to identify proteins linked to sepsis outcomes using a glycoproteomic approach to target extracellular proteins that trigger downstream pathways and direct patient outcomes.Plasma was obtained from the Lactate Assessment in the Treatment of Early Sepsis cohort. N-linked plasma glycopeptides were quantified by solid-phase extraction coupled with mass spectrometry. Glycopeptides were assigned to proteins using RefSeq (National Center of Biotechnology Information, Bethesda, MD) and visualized in a heat map. Protein differences were validated by immunoblotting, and proteins were mapped for biological processes using Database for Annotation, Visualization and Integrated Discovery (National Institute of Allergy and Infectious Diseases, National Institutes of Health; Bethesda, MD) and for functional pathways using Kyoto Encyclopedia of Genes and Genomes (Kanehisa Laboratories, Kyoto, Japan) databases.Hospitalized care.Patients admitted to the emergency department were enrolled in the study when the diagnosis of sepsis was made, within 6 hours of presentation.None.A total of 501 glycopeptides corresponding to 234 proteins were identified. Of these, 66 glycopeptides were unique to the survivor group and corresponded to 54 proteins, 60 were unique to the nonsurvivor group and corresponded to 43 proteins, and 375 were common responses between groups and corresponded to 137 proteins. Immunoblotting showed that nonsurvivors had increased total kininogen; decreased total cathepsin-L1, vascular cell adhesion molecule, periostin, and neutrophil gelatinase-associated lipocalin; and a two-fold decrease in glycosylated clusterin (all p < 0.05). Kyoto Encyclopedia of Genes and Genomes analysis identified six enriched pathways. Interestingly, survivors relied on the extrinsic pathway of the complement and coagulation cascade, whereas nonsurvivors relied on the intrinsic pathway.This study identifies proteins linked to patient outcomes and provides insight into unexplored mechanisms that can be investigated for the identification of novel therapeutic targets.

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Quantitative N-glycoproteomics reveals altered glycosylation levels of various plasma proteins in bloodstream infected patients.

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Quantitative N-glycoproteomics reveals altered glycosylation levels of various plasma proteins in bloodstream infected patients.

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