ArticleAnalytical chemistry2019
Model-Based Spectral Library Approach for Bacterial Identification via Membrane Glycolipids.
Article in Analytical chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 17 citations in OpenAlex.
- Rapid Multi-Omics for Bacterial Identification Using Flow Injection-Ion Mobility-Mass Spectrometry.Analytical chemistry · 2025Article
- HILIC-IM-MS for Simultaneous Lipid and Metabolite Profiling of Bacteria.ACS measurement science au · 2024Article
- Manipulating the crystal plane angle within the primary particle arrangement for the radial ordered structure in a Ni-rich cathode.Chemical science · 2023Article
- Silver Nanoparticle Targets Fabricated Using Chemical Vapor Deposition Method for Differentiation of Bacteria Based on Lipidomic Profiles in Laser Desorption/Ionization Mass Spectrometry.Antibiotics (Basel, Switzerland) · 2023Article
- "Omic" Approaches to Bacteria and Antibiotic Resistance Identification.International journal of molecular sciences · 2022Review
- Recent applications of mass spectrometry in bacterial lipidomics.Analytical and bioanalytical chemistry · 2020Review
- MGMS2: Membrane glycolipid mass spectrum simulator for polymicrobial samples.Rapid communications in mass spectrometry : RCM · 2020Article
- Detection of Species-Specific Lipids by Routine MALDI TOF Mass Spectrometry to Unlock the Challenges of Microbial Identification and Antimicrobial Susceptibility Testing.Frontiers in cellular and infection microbiology · 2020Review
- Progress in Characterization of Lipopolysaccharides and Lipid A by Mass Spectrometry.Mass spectrometry reviewsReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
Abstract
By circumventing the need for a pure colony, MALDI-TOF mass spectrometry of bacterial membrane glycolipids (lipid A) has the potential to identify microbes more rapidly than protein-based methods. However, currently available bioinformatics algorithms (e.g., dot products) do not work well with glycolipid mass spectra such as those produced by lipid A, the membrane anchor of lipopolysaccharide. To address this issue, we propose a spectral library approach coupled with a machine learning technique to more accurately identify microbes. Here, we demonstrate the performance of the model-based spectral library approach for microbial identification using approximately a thousand mass spectra collected from multi-drug-resistant bacteria. At false discovery rates < 1%, our approach identified many more bacterial species than the existing approaches such as the Bruker Biotyper and characterized over 97% of their phenotypes accurately. As the diversity in our glycolipid mass spectral library increases, we anticipate that it will provide valuable information to more rapidly treat infected patients.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.