MALDI-TOF mass spectrometry discriminates drug-susceptible and -resistant strains in Mycobacterium abscessus

Mycobacterium abscessus (M. abscessus) infection is a significant public-health concern due to its resistance to multiple antibiotics and associated treatment challenges. There is a pressing need for a rapid and effective method capable of reliably identifying M. abscessus drug resistance. Our study aimed to investigate the capacity of matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) to identify M. abscessus drug-resistant isolates, offering potential proteomic spectrum markers for detecting resistant strains in clinical diagnosis and treatment. With the aid of machine learning, particularly the decision-tree algorithm, predictive models demonstrated excellent performance with 100% sensitivity and specificity. Peaks at 4,062 Da, 7,518 Da, 8,359 Da and 2,493 Da were potential biomarkers that can distinguish between phenotypes resistant or susceptible to amikacin, linezolid, clarithromycin and cefoxitin, respectively. Besides diagnosing these phenotypes, the combination of machine learning and MALDI-TOF can identify patterns of resistance and susceptibility to various drugs in serially sampled isolates. In an analysis of nine serially collected samples from a single patient, MALDI-TOF could differentiate between M. abscessus strains resistant to three drugs-amikacin, linezolid and clarithromycin-and those completely susceptible to these drugs, based on distinct peak intensities. Furthermore, alterations in the patterns of amikacin and clarithromycin resistance/susceptibility influenced the MALDI-TOF spectra in serial isolates, whereas changes in susceptibility to linezolid did not affect the patterns. Hence, MALDI-TOF could be considered an efficient and dependable method for identifying M. abscessus drug resistance. This diagnostic tool has the potential to streamline the traditionally lengthy process of antimicrobial susceptibility testing while maintaining reliable results.

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PLoS ONE
Published
2025-03-26
DOI
https://doi.org/10.1371/journal.pone.0319809
Citations
4
Primary Topic
Mycobacterium research and diagnosis
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article
Field-Weighted Citation Impact
5.42
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MALDI-TOF mass spectrometry discriminates drug-susceptible and -resistant strains in Mycobacterium abscessus

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article

MALDI-TOF mass spectrometry discriminates drug-susceptible and -resistant strains in Mycobacterium abscessus

Lumyai Wonglakorn, Benjawan Kaewseekhao, Chutipapa Sukkasem, Auttawit Sirichoat, Kiatichai Faksri, Arnone Nithichanon, Nut Nithimongkolchai, Janejira Samarnjit, Tran Duong Thai
article en
4 citations

Abstract

Mycobacterium abscessus (M. abscessus) infection is a significant public-health concern due to its resistance to multiple antibiotics and associated treatment challenges. There is a pressing need for a rapid and effective method capable of reliably identifying M. abscessus drug resistance. Our study aimed to investigate the capacity of matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) to identify M. abscessus drug-resistant isolates, offering potential proteomic spectrum markers for detecting resistant strains in clinical diagnosis and treatment. With the aid of machine learning, particularly the decision-tree algorithm, predictive models demonstrated excellent performance with 100% sensitivity and specificity. Peaks at 4,062 Da, 7,518 Da, 8,359 Da and 2,493 Da were potential biomarkers that can distinguish between phenotypes resistant or susceptible to amikacin, linezolid, clarithromycin and cefoxitin, respectively. Besides diagnosing these phenotypes, the combination of machine learning and MALDI-TOF can identify patterns of resistance and susceptibility to various drugs in serially sampled isolates. In an analysis of nine serially collected samples from a single patient, MALDI-TOF could differentiate between M. abscessus strains resistant to three drugs-amikacin, linezolid and clarithromycin-and those completely susceptible to these drugs, based on distinct peak intensities. Furthermore, alterations in the patterns of amikacin and clarithromycin resistance/susceptibility influenced the MALDI-TOF spectra in serial isolates, whereas changes in susceptibility to linezolid did not affect the patterns. Hence, MALDI-TOF could be considered an efficient and dependable method for identifying M. abscessus drug resistance. This diagnostic tool has the potential to streamline the traditionally lengthy process of antimicrobial susceptibility testing while maintaining reliable results.

PLoS ONEVol. 20(3)
Khon Kaen University (TH)
Reduced inequalities, Peace, Justice and strong institutions
Openalex Percentile: Top 5%
Mycobacterium research and diagnosis
5.42
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