Machine Learning Approaches to Analyze MALDI-TOF Mass Spectrometry Protein Profiles

Lázari, Lucas Cardoso; Rosa-Fernandes, Lívia; Palmisano, Giuseppe

doi:10.1007/978-1-0716-2395-4_29

Cited by 2 publications

(1 citation statement)

References 26 publications

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“…Given the potential in disease diagnosis and biomarker discovery, coupled MALDI-TOF plus machine learning (ML) workflows have been gaining significant attention [20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Effect of Tryptic Digestion on Sensitivity and Specificity in MALDI-TOF-Based Molecular Diagnostics through Machine Learning

Sarkar,

Squire,

Diab

et al. 2023

Sensors

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The digestion of protein into peptide fragments reduces the size and complexity of protein molecules. Peptide fragments can be analyzed with higher sensitivity (often > 102 fold) and resolution using MALDI-TOF mass spectrometers, leading to improved pattern recognition by common machine learning algorithms. In turn, enhanced sensitivity and specificity for bacterial sorting and/or disease diagnosis may be obtained. To test this hypothesis, four exemplar case studies have been pursued in which samples are sorted into dichotomous groups by machine learning (ML) software based on MALDI-TOF spectra. Samples were analyzed in ‘intact’ mode in which the proteins present in the sample were not digested with protease prior to MALDI-TOF analysis and separately after the standard overnight tryptic digestion of the same samples. For each case, sensitivity (sens), specificity (spc), and the Youdin index (J) were used to assess the ML model performance. The proteolytic digestion of samples prior to MALDI-TOF analysis substantially enhanced the sensitivity and specificity of dichotomous sorting. Two exceptions were when substantial differences in chemical composition between the samples were present and, in such cases, both ‘intact’ and ‘digested’ protocols performed similarly. The results suggest proteolytic digestion prior to analysis can improve sorting in MALDI/ML-based workflows and may enable improved biomarker discovery. However, when samples are easily distinguishable protein digestion is not necessary to obtain useful diagnostic results.

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“…Given the potential in disease diagnosis and biomarker discovery, coupled MALDI-TOF plus machine learning (ML) workflows have been gaining significant attention [20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Effect of Tryptic Digestion on Sensitivity and Specificity in MALDI-TOF-Based Molecular Diagnostics through Machine Learning

Sarkar,

Squire,

Diab

et al. 2023

Sensors

View full text Add to dashboard Cite

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Using matrix assisted laser desorption ionisation mass spectrometry combined with machine learning for vaccine authenticity screening

Clarke,

Bharucha,

Arman

et al. 2024

npj Vaccines

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The global population is increasingly reliant on vaccines to maintain population health with billions of doses used annually in immunisation programmes. Substandard and falsified vaccines are becoming more prevalent, caused by both the degradation of authentic vaccines but also deliberately falsified vaccine products. These threaten public health, and the increase in vaccine falsification is now a major concern. There is currently no coordinated global infrastructure or screening methods to monitor vaccine supply chains. In this study, we developed and validated a matrix-assisted laser desorption/ionisation-mass spectrometry (MALDI-MS) workflow that used open-source machine learning and statistical analysis to distinguish authentic and falsified vaccines. We validated the method on two different MALDI-MS instruments used worldwide for clinical applications. Our results show that multivariate data modelling and diagnostic mass spectra can be used to distinguish authentic and falsified vaccines providing proof-of-concept that MALDI-MS can be used as a screening tool to monitor vaccine supply chains.

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Machine Learning Approaches to Analyze MALDI-TOF Mass Spectrometry Protein Profiles

Cited by 2 publications

References 26 publications

Effect of Tryptic Digestion on Sensitivity and Specificity in MALDI-TOF-Based Molecular Diagnostics through Machine Learning

Effect of Tryptic Digestion on Sensitivity and Specificity in MALDI-TOF-Based Molecular Diagnostics through Machine Learning

Using matrix assisted laser desorption ionisation mass spectrometry combined with machine learning for vaccine authenticity screening

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