IDBac: an open-access web platform to identify bacteria and analyze relationships in culture collections using MALDI-TOF mass spectrometry

Abstract The identification and analysis of bacteria is central to the microbiological sciences. While gene sequencing methods have been the standard to achieve this, use of MALDI-TOF mass spectrometry (MS), particularly in clinical microbiology, can provide high-throughput identification to the subspecies level. However, biotyping has yet to be adopted outside of clinical settings due to the lack of a centralized public database of MS protein signatures that would facilitate isolate identification via spectral comparison. Further, most current MALDI MS data analysis platforms lack meaningful ways to compare properties from large numbers of bacterial isolates. Herein we present the IDBac web platform, a crowd-sourced central knowledgebase of protein MS signatures spanning seven bacterial phyla. Accompanying the knowledgebase is analysis infrastructure to identify unknown isolates, probe relationships within culture collections using metadata integration, and visualize specialized metabolite differences within groups of closely related bacteria. To highlight this utility and encourage wide community contribution, examples of each are presented.

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Publication Details

Journal
Nature Communications
Published
2026-07-22
DOI
https://doi.org/10.1038/s41467-026-75579-4
Primary Topic
Bacterial Identification and Susceptibility Testing
Type
article
Field-Weighted Citation Impact
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article

IDBac: an open-access web platform to identify bacteria and analyze relationships in culture collections using MALDI-TOF mass spectrometry

Alessandra S. Eustáquio, Michael W. Mullowney, Skylar Carlson, D. Cole Stevens et al.
Nature Communications
Bacterial Identification and Susceptibility Testing
article

IDBac: an open-access web platform to identify bacteria and analyze relationships in culture collections using MALDI-TOF mass spectrometry

Alessandra S. Eustáquio, Michael W. Mullowney, Skylar Carlson, D. Cole Stevens, Roger G. Linington, Zachary Daniel, Laura M. Sanchez, Eric G. Pamer, Neha Garg, Chelsi D. Cassilly, Lisa Guan, Bruno S. Paulo, Nyssa K. Krull, Valentina Petukhova, Robert A. Shepherd, Chase M. Clark, Jaclyn M. Winter, Adriana Blachowicz, Abigail F. Scott, Erin P. McCauley, Mingxun Wang, Hazel A. Barton, Tim S. Bugni, Paul R. Jensen, Brian T. Murphy, Shaun M. K. McKinnie, Liana Zaroubi, Barbara I. Adaikpoh, William W. Metcalf, Jessia Raherisoanjato, Julia Saulog, David Carter, Antonio Bencomo Hernández, Sriya Pokharel, Mónica Monge-Loría, Gabrielle Mingolelli, Claire E. Dylla, Mandisa Timba, Manasi M. Natu, Sean Romanowski, Douglas R. Braun, Carlo De Silva, Matthew T. Henke, Claire Fergusson, Michael Strobel
article en

Abstract

Abstract The identification and analysis of bacteria is central to the microbiological sciences. While gene sequencing methods have been the standard to achieve this, use of MALDI-TOF mass spectrometry (MS), particularly in clinical microbiology, can provide high-throughput identification to the subspecies level. However, biotyping has yet to be adopted outside of clinical settings due to the lack of a centralized public database of MS protein signatures that would facilitate isolate identification via spectral comparison. Further, most current MALDI MS data analysis platforms lack meaningful ways to compare properties from large numbers of bacterial isolates. Herein we present the IDBac web platform, a crowd-sourced central knowledgebase of protein MS signatures spanning seven bacterial phyla. Accompanying the knowledgebase is analysis infrastructure to identify unknown isolates, probe relationships within culture collections using metadata integration, and visualize specialized metabolite differences within groups of closely related bacteria. To highlight this utility and encourage wide community contribution, examples of each are presented.

Nature Communications
Industry, innovation and infrastructure
Openalex Percentile: Top 11%
Bacterial Identification and Susceptibility Testing
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