26 research outputs found

    Hybrid Data Acquisition and Processing Strategies with Increased Throughput and Selectivity: pSMART Analysis for Global Qualitative and Quantitative Analysis

    No full text
    Data-dependent acquisition (DDA) and data-independent acquisition strategies (DIA) have both resulted in improved understanding of proteomics samples. Both strategies have advantages and disadvantages that are well-published, where DDA is typically applied for deep discovery and DIA may be used to create sample records. In this paper, we present a hybrid data acquisition and processing strategy (pSMART) that combines the strengths of both techniques and provides significant benefits for qualitative and quantitative peptide analysis. The performance of pSMART is compared to published DIA strategies in an experiment that allows the objective assessment of DIA performance with respect to interrogation of previously acquired MS data. The results of this experiment demonstrate that pSMART creates fewer decoy hits than a standard DIA strategy. Moreover, we show that pSMART is more selective, sensitive, and reproducible than either standard DIA or DDA strategies alone

    Rapid development of sensitive, high-throughput, quantitative and highly selective mass spectrometric targeted immunoassays for clinically important proteins in human plasma and serum

    No full text
    OBJECTIVES: The aim of this study was to develop high-throughput, quantitative and highly selective mass spectrometric, targeted immunoassays for clinically important proteins in human plasma or serum. DESIGN AND METHODS: The described method coupled mass spectrometric immunoassay (MSIA), a previously developed technique for immunoenrichment on a monolithic microcolumn activated with an anti-protein antibody and fixed in a pipette tip, to selected reaction monitoring (SRM) detection and accurate quantification of targeted peptides, including clinically relevant sequence or truncated variants. RESULTS: In this report, we demonstrate the rapid development of MSIA-SRM assays for sixteen different target proteins spanning seven different clinically important areas (including neurological, Alzheimer's, cardiovascular, endocrine function, cancer and other diseases) and ranging in concentration from pg/mL to mg/mL. The reported MSIA-SRM assays demonstrated high sensitivity (within published clinical ranges), precision, robustness and high-throughput as well as specific detection of clinically relevant isoforms for many of the target proteins. Most of the assays were tested with bona-fide clinical samples. In addition, positive correlations, (R2 0.67–0.87, depending on the target peptide), were demonstrated for MSIA-SRM assay data with clinical analyzer measurements of parathyroid hormone (PTH) and insulin growth factor 1 (IGF1) in clinical sample cohorts. CONCLUSIONS: We have presented a practical and scalable method for rapid development and deployment of MS-based SRM assays for clinically relevant proteins and measured levels of the target analytes in bona fide clinical samples. The method permits the specific quantification of individual protein isoforms and addresses the difficult problem of protein heterogeneity in clinical proteomics applications

    Functional Microbiomics Reveals Alterations of the Gut Microbiome and Host Co‐Metabolism in Patients With Alcoholic Hepatitis

    No full text
    Alcohol-related liver disease is a major public health burden, and the gut microbiota is an important contributor to disease pathogenesis. The aim of the present study is to characterize functional alterations of the gut microbiota and test their performance for short-term mortality prediction in patients with alcoholic hepatitis. We integrated shotgun metagenomics with untargeted metabolomics to investigate functional alterations of the gut microbiota and host co-metabolism in a multicenter cohort of patients with alcoholic hepatitis. Profound changes were found in the gut microbial composition, functional metagenome, serum, and fecal metabolomes in patients with alcoholic hepatitis compared with nonalcoholic controls. We demonstrate that in comparison with single omics alone, the performance to predict 30-day mortality was improved when combining microbial pathways with respective serum metabolites in patients with alcoholic hepatitis. The area under the receiver operating curve was higher than 0.85 for the tryptophan, isoleucine, and methionine pathways as predictors for 30-day mortality, but achieved 0.989 for using the urea cycle pathway in combination with serum urea, with a bias-corrected prediction error of 0.083 when using leave-one-out cross validation. Conclusion: Our study reveals changes in key microbial metabolic pathways associated with disease severity that predict short-term mortality in our cohort of patients with alcoholic hepatitis

    Functional Microbiomics Reveals Alterations of the Gut Microbiome and Host Co‐Metabolism in Patients With Alcoholic Hepatitis

    No full text
    Alcohol-related liver disease is a major public health burden, and the gut microbiota is an important contributor to disease pathogenesis. The aim of the present study is to characterize functional alterations of the gut microbiota and test their performance for short-term mortality prediction in patients with alcoholic hepatitis. We integrated shotgun metagenomics with untargeted metabolomics to investigate functional alterations of the gut microbiota and host co-metabolism in a multicenter cohort of patients with alcoholic hepatitis. Profound changes were found in the gut microbial composition, functional metagenome, serum, and fecal metabolomes in patients with alcoholic hepatitis compared with nonalcoholic controls. We demonstrate that in comparison with single omics alone, the performance to predict 30-day mortality was improved when combining microbial pathways with respective serum metabolites in patients with alcoholic hepatitis. The area under the receiver operating curve was higher than 0.85 for the tryptophan, isoleucine, and methionine pathways as predictors for 30-day mortality, but achieved 0.989 for using the urea cycle pathway in combination with serum urea, with a bias-corrected prediction error of 0.083 when using leave-one-out cross validation. Conclusion: Our study reveals changes in key microbial metabolic pathways associated with disease severity that predict short-term mortality in our cohort of patients with alcoholic hepatitis
    corecore