A rapid and simple MALDI-TOF MS lipid profiling method for differentiating <i>Mycobacterium ulcerans</i> from <i>Mycobacterium marinum</i>

<i>Mycobacterium ulcerans</i>, a slow-growing nontuberculous mycobacterium, causes Buruli ulcer, a neglected tropical disease. Distinguishing <i>M. ulcerans</i> from related species, including <i>Mycobacterium marinum</i>, poses challenges with respect to making accurate identifications. In this study, we developed a rapid and simple identification method based on mycobacterial lipid profiles and used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze the lipid profiles of <i>M. ulcerans</i> (<i>n</i> = 35) and <i>M. marinum</i> (<i>n</i> = 19) isolates. Bacterial colonies pre-cultured on 2% Ogawa egg slants for 2 months were collected, and total lipids were extracted using an MBT Lipid Xtract kit. Spectra were obtained in negative ion mode using a MALDI Biotyper Sirius system, with ClinProTools v3.0 being used to analyze the spectra based on the application of three algorithms (genetic algorithm [GA], supervised neural network [SNN], and quick classifier [QC)]). Cross-validation was performed using a 20% leave-out set randomly selected from the samples. Models generated using GA, SNN, and QC showed cross-validation values of 100%, 100%, and 97.9%, respectively, and all algorithms achieved 100% recognition capability values. Our findings indicate that MALDI-TOF analysis of lipid profiles can accurately differentiate two mycobacterial species (<i>M. ulcerans</i> and <i>M. marinum</i>) that are difficult to distinguish using conventional protein-targeting methods.IMPORTANCEBuruli ulcer, caused by <i>Mycobacterium ulcerans</i>, is a neglected tropical disease. However, distinguishing <i>M. ulcerans</i> from related species, including <i>Mycobacterium marinum</i>, presents certain challenges. In this study, we demonstrate the utility of a rapid yet simple method for differentiating isolates of these mycobacteria based on their lipid profiles using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. This new approach can accurately identify species that are otherwise difficult to distinguish using conventional techniques. This represents a significant diagnostic advance for clinical laboratories, in that it enables a more rapid and precise identification, thereby leading to earlier treatment initiation and more appropriate treatment regimens for infections caused by these bacteria.

Authors

Institutions

Publication Details

Journal
Journal of Clinical Microbiology
Published
2025-01-27
DOI
https://doi.org/10.1128/jcm.01400-24
Citations
2
Primary Topic
Mycobacterium research and diagnosis
Type
article
Field-Weighted Citation Impact
2.71

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A rapid and simple MALDI-TOF MS lipid profiling method for differentiating Mycobacterium ulcerans from Mycobacterium marinum

Kohei Doke, Makoto Nakaya, Takeshi Komine, Yoshihiko Hoshino et al.
2 citations
Journal of Clinical Microbiology
Mycobacterium research and diagnosis
2.71
article

A rapid and simple MALDI-TOF MS lipid profiling method for differentiating Mycobacterium ulcerans from Mycobacterium marinum

Kohei Doke, Makoto Nakaya, Takeshi Komine, Yoshihiko Hoshino, Hanako Fukano, Mitsunori Yoshida, Azumi Fujinaga, Yuji Miyamoto
article en
2 citations

Abstract

<i>Mycobacterium ulcerans</i>, a slow-growing nontuberculous mycobacterium, causes Buruli ulcer, a neglected tropical disease. Distinguishing <i>M. ulcerans</i> from related species, including <i>Mycobacterium marinum</i>, poses challenges with respect to making accurate identifications. In this study, we developed a rapid and simple identification method based on mycobacterial lipid profiles and used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) to analyze the lipid profiles of <i>M. ulcerans</i> (<i>n</i> = 35) and <i>M. marinum</i> (<i>n</i> = 19) isolates. Bacterial colonies pre-cultured on 2% Ogawa egg slants for 2 months were collected, and total lipids were extracted using an MBT Lipid Xtract kit. Spectra were obtained in negative ion mode using a MALDI Biotyper Sirius system, with ClinProTools v3.0 being used to analyze the spectra based on the application of three algorithms (genetic algorithm [GA], supervised neural network [SNN], and quick classifier [QC)]). Cross-validation was performed using a 20% leave-out set randomly selected from the samples. Models generated using GA, SNN, and QC showed cross-validation values of 100%, 100%, and 97.9%, respectively, and all algorithms achieved 100% recognition capability values. Our findings indicate that MALDI-TOF analysis of lipid profiles can accurately differentiate two mycobacterial species (<i>M. ulcerans</i> and <i>M. marinum</i>) that are difficult to distinguish using conventional protein-targeting methods.IMPORTANCEBuruli ulcer, caused by <i>Mycobacterium ulcerans</i>, is a neglected tropical disease. However, distinguishing <i>M. ulcerans</i> from related species, including <i>Mycobacterium marinum</i>, presents certain challenges. In this study, we demonstrate the utility of a rapid yet simple method for differentiating isolates of these mycobacteria based on their lipid profiles using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. This new approach can accurately identify species that are otherwise difficult to distinguish using conventional techniques. This represents a significant diagnostic advance for clinical laboratories, in that it enables a more rapid and precise identification, thereby leading to earlier treatment initiation and more appropriate treatment regimens for infections caused by these bacteria.

Journal of Clinical MicrobiologyVol. 63(3)
Bruker (United States) (US), National Institute of Infectious Diseases (JP)
Harvard University, Japan Agency for Medical Research and Development, Instituut voor Tropische Geneeskunde, Ministry of Education, Culture, Sports, Science and Technology, Japan International Cooperation Agency, Japan Society for the Promotion of Science
Life below water
Openalex Percentile: Top 12%
Mycobacterium research and diagnosis
2.71
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.