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Article Abstract
Background: The traditional method for assessing the capacity of a microorganism to produce biofilm is generally a static model in a multi-well plate using the crystal violet (CV) binding assay, which takes 96 h. Furthermore, while the method is simple to perform, its reproducibility is poor.
Objective: We evaluated whether matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) could make it possible to differentiate between high-and low-biofilm-producing microorganisms on 24-h cultures of and .
Methods: We included 157 strains of . and 91 strains of . obtained from the blood cultures of patients with bacteremia/candidemia. We tested biofilm production using the CV binding assay as the gold standard to classify strains as low or high biofilm producers. We then applied MALDI-TOF MS to create a machine learning-based predictive model using 40 strains of . and . , each with extreme absorbance values, and validated this approach with the remaining 117 and 51 strains using the random forest algorithm and the support vector machine algorithm, respectively.
Results: Overall, 81.2% of the . strains (95/117) and 74.5% of the . strains (38/51) used for validation were correctly categorized, respectively, as low and high-biofilm-producing.
Conclusion: Classification based on MALDI-TOF MS protein spectra enables us to predict acceptable information about the capacity of 24-h cultures of . and . to form biofilm.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871577 | PMC |
| http://dx.doi.org/10.3389/fmicb.2022.1104405 | DOI Listing |
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