ArticleMolecular & cellular proteomics : MCP2017
Typing and Characterization of Bacteria Using Bottom-up Tandem Mass Spectrometry Proteomics.
Article in Molecular & cellular proteomics : MCP, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- MARLOWE: taxonomic characterization of unknown samples for forensics using de novo peptide identification.Scientific reports · 2026Article
- Antibiotic Resistance Detection and Concomitant Species Identification of ESKAPE Pathogens by Proteomics.Molecular & cellular proteomics : MCP · 2026Article
- From Identification to Insight: Making Full Use of the Diagnostic Potential of MS/MS Proteotyping in Clinical Microbiology Using Efficient Bioinformatics.Journal of proteome research · 2025Review
- Bacterial Proteomics and Antibiotic Resistance Identification: Is Single-Cell Analysis a Worthwhile Pursuit?Pathogens (Basel, Switzerland) · 2025Review
- Biological Function Assignment across Taxonomic Levels in Mass-Spectrometry-Based Metaproteomics via a Modified Expectation Maximization Algorithm.Journal of proteome research · 2025Article
- MultiStageSearch: An Iterative Workflow for Unbiased Taxonomic Analysis of Pathogens Using Proteogenomics.Journal of proteome research · 2025Article
- Review
- Universal Identification of Pathogenic Viruses by Liquid Chromatography Coupled with Tandem Mass Spectrometry Proteotyping.Molecular & cellular proteomics : MCP · 2024Article
- Multiplexing the Identification of Microorganisms via Tandem Mass Tag Labeling Augmented by Interference Removal through a Novel Modification of the Expectation Maximization Algorithm.Journal of the American Society for Mass Spectrometry · 2024Article
- Resolving the Temporal Splenic Proteome during Fungal Infection for Discovery of Putative Dual Perspective Biomarker Signatures.Journal of the American Society for Mass Spectrometry · 2023Article
- Mix24X, a Lab-Assembled Reference to Evaluate Interpretation Procedures for Tandem Mass Spectrometry Proteotyping of Complex Samples.International journal of molecular sciences · 2023Article
- Evaluation of the Limit of Detection of Bacteria by Tandem Mass Spectrometry Proteotyping and Phylopeptidomics.Microorganisms · 2023Article
- Strain-level bacterial typing directly from patient samples using optical DNA mapping.Communications medicine · 2023Article
- Direct Identification of Urinary Tract Pathogens by MALDI-TOF/TOF Analysis and De Novo Peptide Sequencing.Molecules (Basel, Switzerland) · 2022Article
- Identification of Antibiotic Resistance Proteins via MiCId's Augmented Workflow. A Mass Spectrometry-Based Proteomics Approach.Journal of the American Society for Mass Spectrometry · 2022Article
- Identification and Characterization of Marine Microorganisms by Tandem Mass Spectrometry Proteotyping.Microorganisms · 2022Article
- The Use of MALDI-TOF Mass Spectrometry to Analyze Commensal Oral Yeasts in Nursing Home Residents.Microorganisms · 2021Article
- Mass Spectrometry Proteotyping-Based Detection and Identification ofFrontiers in cellular and infection microbiology · 2021Article
- Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MSMolecular & cellular proteomics : MCP · 2020Article
- Flying blind, or just flying under the radar? The underappreciated power of de novo methods of mass spectrometric peptide identification.Protein science : a publication of the Protein Society · 2020Review
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Methods for rapid and reliable microbial identification are essential in modern healthcare. The ability to detect and correctly identify pathogenic species and their resistance phenotype is necessary for accurate diagnosis and efficient treatment of infectious diseases. Bottom-up tandem mass spectrometry (MS) proteomics enables rapid characterization of large parts of the expressed genes of microorganisms. However, the generated data are highly fragmented, making downstream analyses complex. Here we present TCUP, a new computational method for typing and characterizing bacteria using proteomics data from bottom-up tandem MS. TCUP compares the generated protein sequence data to reference databases and automatically finds peptides suitable for characterization of taxonomic composition and identification of expressed antimicrobial resistance genes. TCUP was evaluated using several clinically relevant bacterial species (
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