Post-translational modifications (PTMs) of proteins add to the complexity of proteomes, thereby complicating the task of proteome characterization. An efficient strategy to identify this peptide heterogeneity is important for determination of protein function, as well as for mass spectrometry-based protein quantification. Furthermore, studies of allelic variation or single nucleotide polymorphisms (SNPs) at the proteome level, as well as mRNA editing, are increasingly relevant, but validation and determination of false positive rates are challenging. Here we describe an effective workflow for large scale PTM and amino acid substitution identification based on high resolution and high mass accuracy RPLC-MS data sets. A systematic validation strategy of PTMs using RPLC retention time shifts was implemented, and a decision tree for validation is presented. This workflow was applied to Arabidopsis proteome preparations; 1.5 million MS/MS spectra were processed resulting in 20% sequence assignments, with 5% from modified sequences and matching to 2904 proteins; this high assignment rate is in part due to the high quality spectral data. A searchable modified peptide library for Arabidopsis is available online at http://ppdb.tc.cornell.edu/. We discuss confidence in peptide and PTM assignment based on the acquired data set, as well as implications for quantitative analysis of physiologically induced and preparation-related modifications.

Download full-text PDF

Source
http://dx.doi.org/10.1021/ac9011792DOI Listing

Publication Analysis

Top Keywords

workflow large
8
large scale
8
modified peptide
8
peptide library
8
peptide
5
scale detection
4
validation
4
detection validation
4
validation peptide
4
peptide modifications
4

Similar Publications

In this tutorial, we introduce the reader to analyzing ecological momentary assessment (EMA) data as applied in psychological sciences with the use of Bayesian (generalized) linear mixed-effects models. We discuss practical advantages of the Bayesian approach over frequentist methods and conceptual differences. We demonstrate how Bayesian statistics can help EMA researchers to (a) incorporate prior knowledge and beliefs in analyses, (b) fit models with a large variety of outcome distributions that reflect likely data-generating processes, (c) quantify the uncertainty of effect-size estimates, and (d) quantify the evidence for or against an informative hypothesis.

View Article and Find Full Text PDF

Mass spectrometry is a cornerstone of quantitative proteomics, enabling relative protein quantification and differential expression analysis () of proteins. As experiments grow in complexity, involving more samples, groups, and identified proteins, interactive differential expression analysis tools become impractical. The addresses this challenge by providing a command-line interface that simplifies , making it accessible to nonprogrammers and seamlessly integrating it into workflow management systems.

View Article and Find Full Text PDF

Introduction: Limited research is available regarding recommendations about which drug allergy alerts (DAAs) in clinical decision support (CDS) systems should interrupt provider workflow. The objective was to evaluate the frequency of penicillin and cephalosporin DAA overrides at two institutions. A secondary objective was to redesign DAAs using a new tiered alerting system based on patient factors.

View Article and Find Full Text PDF

Purpose Of Review: Artificial intelligence (AI) offers a new frontier for aiding in the management of both acute and chronic pain, which may potentially transform opioid prescribing practices and addiction prevention strategies. In this review paper, not only do we discuss some of the current literature around predicting various opioid-related outcomes, but we also briefly point out the next steps to improve trustworthiness of these AI models prior to real-time use in clinical workflow.

Recent Findings: Machine learning-based predictive models for identifying risk for persistent postoperative opioid use have been reported for spine surgery, knee arthroplasty, hip arthroplasty, arthroscopic joint surgery, outpatient surgery, and mixed surgical populations.

View Article and Find Full Text PDF

Purpose: MR-based FID navigators (FIDnavs) do not require gradient pulses and are attractive for prospective motion correction (PMC) due to short acquisition times and high sampling rates. However, accuracy and precision are limited and depend on a separate calibration measurement. Besides FIDnavs, stationary NMR field probes are also capable of measuring local, motion-induced field changes.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!