MALDI-TOF MS Protein Profiling Combined with Multivariate Analysis for Identification and Quantitation of Beef Adulteration

Pu, Keyuan; Qiu, Jiamin; Huang, Wei; Lai, Xiaopin; Liu, Cheng; Lin, Yan; Ng, Kwan‐Ming

doi:10.1007/s12161-022-02403-2

Cited by 7 publications

(6 citation statements)

References 48 publications

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“…The work of Zambonin (2021) is expanded on further by Pu et al. (2022), and although meat allergy is not common, it is useful to be able to detect adulteration of meat species as well as to check for correct product labeling purposes. Pu et al.…”

Section: Methodsmentioning

confidence: 99%

“…Pu et al. (2022) have shown that MALDI–ToF MS protein profiling combined with multivariate analysis allows for the identification and quantitation of beef adulteration with chicken, duck, or pork (Pu et al., 2022).…”

Section: Methodsmentioning

confidence: 99%

“…The work of Zambonin ( 2021) is expanded on further by Pu et al (2022), and although meat allergy is not common, it is useful to be able to detect adulteration of meat species as well as to check for correct product labeling purposes. Pu et al (2022) have shown that MALDI-ToF MS pro-tein profiling combined with multivariate analysis allows for the identification and quantitation of beef adulteration with chicken, duck, or pork (Pu et al, 2022).…”

Section: Maldimentioning

confidence: 99%

See 2 more Smart Citations

Food allergen analysis: A review of current gaps and the potential to fill them by matrix‐assisted laser desorption/ionization

Birse,

Burns,

Walker

et al. 2023

Comp Rev Food Sci Food Safe

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Food allergy remains a public health, business, and regulatory challenge. Risk analysis (RA) and risk management (RM) of food allergens are of great importance and analysis for food allergens is necessary for both. The current workhorse techniques for allergen analysis (enzyme linked immunosorbent assay [ELISA] and real‐time polymerase chain reaction) exhibit recognized challenges including variable and antibody specific responses and detection of species DNA rather than allergen protein, respectively. Liquid chromatography–tandem mass spectrometry (LC–MS/MS) enables protein identification, with potential for multiplex analysis and traceability to the System of International units (SI), aiding global measurement standardization. In this review, recent literature has been systematically reviewed to assess progress in LC–MS/MS and define the potential and benefits of matrix‐assisted laser desorption/ionization–time‐of‐flight MS (MALDI–ToF‐MS) technology for allergen analysis. MALDI–ToF‐MS of initially intact protein is already applied to verify in silico‐derived peptide sequences for LC–MS/MS analysis. We describe the origins of MALDI and its future perspectives, including affinity bead‐assisted assays coupled to MALDI. Based on the proliferation of reliable and reproducible MALDI‐based clinical applications, the technique should emulate the detection capability (sensitivity) of established allergen detection techniques, whilst reducing technical support and having equivalent multiplexing potential to competing techniques, for example, LC–MS/MS and ELISA. Although unlikely to offer inherent SI traceability, MALDI‐based allergen analysis will complement existing MS approaches for allergens. Affinity bead‐MALDI appears capable of higher throughput at lower cost per sample than almost any existing technique, enabling repeated sub‐sampling as a way to reduce representative sampling issues.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Maldimentioning

confidence: 99%

See 1 more Smart Citation

Food allergen analysis: A review of current gaps and the potential to fill them by matrix‐assisted laser desorption/ionization

Birse,

Burns,

Walker

et al. 2023

Comp Rev Food Sci Food Safe

View full text Add to dashboard Cite

show abstract

“…MALDI commonly uses the PLS-DA model for breeds or species discrimination. MALDI-MS was used to analyze three other species (pork, chicken, and duck) in beef, obtaining an average discrimination accuracy of 94.7% using the PLS-DA model ( Pu et al, 2022 ). MALDI and PLS-DA was used to identify cow-milk adulteration in feta milk at an accuracy of 83.5% ( Kritikou et al, 2022 ).…”

Section: Principle and Research Progress In Rapid Analysis Technologymentioning

confidence: 99%

Rapid analysis technologies with chemometrics for food authenticity field: A review

Zhang,

Li,

Zhao

et al. 2024

Current Research in Food Science

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“…Currently, it has been widely combined with chemometrics methods to achieve microorganism identification and metabolomics. For meat authentication, MALDI-TOF MS-based methods were explored for qualitative and quantitative detection of raw meat adulteration. − Moreover, qualitative detection of heat-processed meat was achieved by cluster analysis, but the study did not discover heat-stable characteristic proteins nor explore their potential in quantitative analysis. The MALDI-TOF MS method based on heat-stable characteristic proteins for the authentication of heat-processed meat remains to be investigated.…”

Section: Introductionmentioning

confidence: 99%

Integration of Non-targeted Proteomics Mass Spectrometry with Machine Learning for Screening Cooked Beef Adulterated Samples

Qiu

Tong

et al. 2022

J. Agric. Food Chem.

Self Cite

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The degradation of ingredients in heat-processed meat products makes their authentication challenging. In this study, protein profiles of raw beef, chicken, duck, pork, and binary simulated adulterated beef samples (chicken–beef, duck–beef, and pork–beef) and their heat-processed samples were obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Heat-stable characteristic proteins were found by screening the overlapping characteristic protein ion peaks of the raw and corresponding heat-processed samples, which were discovered by partial least-squares discriminant analysis. Based on the 36 heat-stable characteristic proteins, qualitative classification for the raw and heat-processed meats was achieved by extreme gradient boosting. Moreover, quantitative analysis via partial least squares regression was applied to determine the adulteration ratio of the simulated adulterated beef samples. The validity of the approach was confirmed by a blind test with the mean accuracy of 97.4%. The limit of detection and limit of quantification of this method were determined to be 5 and 8%, respectively, showing its practical aspect for the beef authentication.

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MALDI-TOF MS Protein Profiling Combined with Multivariate Analysis for Identification and Quantitation of Beef Adulteration

Cited by 7 publications

References 48 publications

Food allergen analysis: A review of current gaps and the potential to fill them by matrix‐assisted laser desorption/ionization

Food allergen analysis: A review of current gaps and the potential to fill them by matrix‐assisted laser desorption/ionization

Rapid analysis technologies with chemometrics for food authenticity field: A review

Integration of Non-targeted Proteomics Mass Spectrometry with Machine Learning for Screening Cooked Beef Adulterated Samples

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