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Šedo O, Roblíčková A, Ježek F, Gintar P, Kameník J, Zdráhal Z. Discriminatory power of MALDI-TOF MS protein profiling analysis of pork meat and meat products. Food Chem 2024; 449:139155. [PMID: 38608601 DOI: 10.1016/j.foodchem.2024.139155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 03/08/2024] [Accepted: 03/25/2024] [Indexed: 04/14/2024]
Abstract
Forty different sample preparation methods were tested to obtain the most informative MALDI-TOF MS protein profiles of pork meat. Extraction by 25% formic acid with the assistance of zirconia-silica beads followed by defatting by methanol:chloroform mixture (1:1, v/v) and deposition by using the layer-by-layer method was determined as the optimum sample preparation protocol. The discriminatory power of the method was then examined on samples of pork meat and meat products. The method was able to discriminate between selected salami based on the production method and brand and was able to monitor the ripening process in salami. However, it was not able to differentiate between different brands of pork ham or closely located parts of pork meat. In the latter case, a more comprehensive analysis using LC-MS/MS was used to assess the differences in protein abundance and their relation to the outputs of MALDI - TOF MS profiling.
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Affiliation(s)
- Ondrej Šedo
- Masaryk University, Central European Institute of Technology, Kamenice 5, 625 00 Brno, Czech Republic.
| | - Alena Roblíčková
- Masaryk University, Central European Institute of Technology, Kamenice 5, 625 00 Brno, Czech Republic
| | - František Ježek
- University of Veterinary Sciences Brno, Faculty of Veterinary Hygiene and Ecology, Palackého tř. 1946/1, 612 42 Brno, Czech Republic.
| | - Petr Gintar
- Masaryk University, Central European Institute of Technology, Kamenice 5, 625 00 Brno, Czech Republic; Masaryk University, Faculty of Science, National Centre for Biomolecular Research, Kamenice 5, 625 00 Brno, Czech Republic.
| | - Josef Kameník
- University of Veterinary Sciences Brno, Faculty of Veterinary Hygiene and Ecology, Palackého tř. 1946/1, 612 42 Brno, Czech Republic.
| | - Zbyněk Zdráhal
- Masaryk University, Central European Institute of Technology, Kamenice 5, 625 00 Brno, Czech Republic; Masaryk University, Faculty of Science, National Centre for Biomolecular Research, Kamenice 5, 625 00 Brno, Czech Republic.
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Chen W, Soko WC, Xie J, Bi H. Discovery of mass spectral peak markers and protein biomarkers in fish muscle exudates for rapid and precise recognition of fish species via magnetic beads (MBs) and mass spectrometry. Food Chem X 2024; 22:101509. [PMID: 38883916 PMCID: PMC11179567 DOI: 10.1016/j.fochx.2024.101509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 05/23/2024] [Accepted: 05/23/2024] [Indexed: 06/18/2024] Open
Abstract
In this study, muscle exudates from five fishes belonging to the family Sciaenidae, in the order Perciformes, were analyzed as models for the discovery of biomarkers by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS). MagSi-weak cation exchange magnetic beads (WCX-MBs) were utilized for the enrichment of proteins from fish exudate samples, allowing protein biomarkers to be identified and subsequently used for fish species differentiation. Buffers with pH ranging from 4.0 to 9.0 can provide an environment for proteins in fish muscle exudate to bind to the WCX-MBs. The optimal enrichment based on WCX-MBs can be achieved when the exudate samples are diluted 100folds. More species-specific biomarkers in mass spectra can be identified when using WCX-MBs. The number of ions that can be considered as peak markers and can differentiate the analyzed fishes increases from 38 to 121 when using WCX-MBs to isolate peptides/protein in fish muscle exudate. Particularly, eight peak markers in mass spectra were assigned to be specific to Nibea albiflora (NA), three peak markers specific to Larimichthys crocea (LC), two peak markers specific to Miichthys miiuy (MM), seven peak markers specific to Collichthys lucidus (CL), and six peak markers specific to Larimichthys polyactis (LP). Furthermore, five proteins were identified based on the characterization of tryptic peptides and their potential to be biomarkers, of which four proteins specific to CL and one specific to LC were identified. The single-blind samples analysis demonstrated that these species-specific peak markers and protein biomarkers can be successfully utilized for corresponding fish recognition. The utilization of WCX-MBs can improve the discovery of fish species-specific biomarkers in fish muscle exudate samples. The present protocol holds potential of being a rapid and accurate identification tool for recognition of fish species.
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Affiliation(s)
- Weijiao Chen
- College of Food Science and Technology, Shanghai Ocean University (SHOU), 999 Hucheng Ring Road, Pudong New District, 201306 Shanghai, China
| | - Winnie C Soko
- College of Food Science and Technology, Shanghai Ocean University (SHOU), 999 Hucheng Ring Road, Pudong New District, 201306 Shanghai, China
| | - Jing Xie
- College of Food Science and Technology, Shanghai Ocean University (SHOU), 999 Hucheng Ring Road, Pudong New District, 201306 Shanghai, China
| | - Hongyan Bi
- College of Food Science and Technology, Shanghai Ocean University (SHOU), 999 Hucheng Ring Road, Pudong New District, 201306 Shanghai, China
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Frigerio J, Campone L, Giustra MD, Buzzelli M, Piccoli F, Galimberti A, Cannavacciuolo C, Ouled Larbi M, Colombo M, Ciocca G, Labra M. Convergent technologies to tackle challenges of modern food authentication. Heliyon 2024; 10:e32297. [PMID: 38947432 PMCID: PMC11214499 DOI: 10.1016/j.heliyon.2024.e32297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Revised: 05/30/2024] [Accepted: 05/31/2024] [Indexed: 07/02/2024] Open
Abstract
The authentication process involves all the supply chain stakeholders, and it is also adopted to verify food quality and safety. Food authentication tools are an essential part of traceability systems as they provide information on the credibility of origin, species/variety identity, geographical provenance, production entity. Moreover, these systems are useful to evaluate the effect of transformation processes, conservation strategies and the reliability of packaging and distribution flows on food quality and safety. In this manuscript, we identified the innovative characteristics of food authentication systems to respond to market challenges, such as the simplification, the high sensitivity, and the non-destructive ability during authentication procedures. We also discussed the potential of the current identification systems based on molecular markers (chemical, biochemical, genetic) and the effectiveness of new technologies with reference to the miniaturized systems offered by nanotechnologies, and computer vision systems linked to artificial intelligence processes. This overview emphasizes the importance of convergent technologies in food authentication, to support molecular markers with the technological innovation offered by emerging technologies derived from biotechnologies and informatics. The potential of these strategies was evaluated on real examples of high-value food products. Technological innovation can therefore strengthen the system of molecular markers to meet the current market needs; however, food production processes are in profound evolution. The food 3D-printing and the introduction of new raw materials open new challenges for food authentication and this will require both an update of the current regulatory framework, as well as the development and adoption of new analytical systems.
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Affiliation(s)
- Jessica Frigerio
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza, 2, 20216, Milano, Italy
| | - Luca Campone
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza, 2, 20216, Milano, Italy
| | - Marco Davide Giustra
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza, 2, 20216, Milano, Italy
| | - Marco Buzzelli
- Department of Informatics Systems and Communication, University of Milano-Bicocca, viale Sarca, 336, 20216, Milano, Italy
| | - Flavio Piccoli
- Department of Informatics Systems and Communication, University of Milano-Bicocca, viale Sarca, 336, 20216, Milano, Italy
| | - Andrea Galimberti
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza, 2, 20216, Milano, Italy
| | - Ciro Cannavacciuolo
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza, 2, 20216, Milano, Italy
| | - Malika Ouled Larbi
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza, 2, 20216, Milano, Italy
| | - Miriam Colombo
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza, 2, 20216, Milano, Italy
| | - Gianluigi Ciocca
- Department of Informatics Systems and Communication, University of Milano-Bicocca, viale Sarca, 336, 20216, Milano, Italy
| | - Massimo Labra
- Department of Biotechnology and Biosciences, University of Milano-Bicocca, Piazza della Scienza, 2, 20216, Milano, Italy
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Xu Y, Koidis A, Tian X, Xu S, Xu X, Wei X, Jiang A, Lei H. Bayesian Fusion Model Enhanced Codfish Classification Using Near Infrared and Raman Spectrum. Foods 2022; 11:foods11244100. [PMID: 36553842 PMCID: PMC9777887 DOI: 10.3390/foods11244100] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/14/2022] [Accepted: 12/14/2022] [Indexed: 12/24/2022] Open
Abstract
In this study, a Bayesian-based decision fusion technique was developed for the first time to quickly and non-destructively identify codfish using near infrared (NIRS) and Raman spectroscopy (RS). NIRS and RS spectra from 320 codfish samples were collected, and separate partial least squares discriminant analysis (PLS-DA) models were developed to establish the relationship between the raw data and cod identity for each spectral technique. Three decision fusion methods: decision fusion, data layer or feature layer, were tested and compared. The decision fusion model based on the Bayesian algorithm (NIRS-RS-B) was developed on the optimal discrimination features of NIRS and RS data (NIRS-RS) extracted by the PLS-DA method whereas the other fusion models followed conventional, non-Bayesian approaches. The Bayesian model showed enhanced classification metrics (92% sensitivity, 98% specificity, 98% accuracy) that were significantly superior to those demonstrated by any of other two spectroscopic methods (NIRS, RS) and the two data fusion methods (data layer fused, NIRS-RS-D, or feature layer fused, NIRS-RS-F). This novel proposed approach can provide an alternative classification for codfish and potentially other food speciation cases.
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Affiliation(s)
- Yi Xu
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Precision Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China
- College of Light Industry and Engineering, Sichuan Technology & Business College, Chengdu 611800, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
| | - Anastasios Koidis
- Institute for Global Food Security, Queen’s University Belfast, 19 Chlorine Gardens, Belfast BT9 5DJ, UK
| | - Xingguo Tian
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Precision Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China
| | - Sai Xu
- Public Monitoring Center of Agricultural Products, Guangdong Academy of Agricultural Sciences, Guangzhou 510642, China
| | - Xiaoyan Xu
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Precision Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China
| | - Xiaoqun Wei
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Precision Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China
| | - Aimin Jiang
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Precision Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China
- Correspondence: (A.J.); (H.L.); Tel.: +86-20-8528-0270 (A.J.); +86-20-8528-3925 (H.L.)
| | - Hongtao Lei
- Guangdong Provincial Key Laboratory of Food Quality and Safety/Nation-Local Joint Engineering Research Center for Precision Machining and Safety of Livestock and Poultry Products, College of Food Science, South China Agricultural University, Guangzhou 510642, China
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangzhou 510642, China
- Correspondence: (A.J.); (H.L.); Tel.: +86-20-8528-0270 (A.J.); +86-20-8528-3925 (H.L.)
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Chaudhary V, Kajla P, Dewan A, Pandiselvam R, Socol CT, Maerescu CM. Spectroscopic techniques for authentication of animal origin foods. Front Nutr 2022; 9:979205. [PMID: 36204380 PMCID: PMC9531581 DOI: 10.3389/fnut.2022.979205] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 08/29/2022] [Indexed: 11/13/2022] Open
Abstract
Milk and milk products, meat, fish and poultry as well as other animal derived foods occupy a pronounced position in human nutrition. Unfortunately, fraud in the food industry is common, resulting in negative economic consequences for customers as well as significant threats to human health and the external environment. As a result, it is critical to develop analytical tools that can quickly detect fraud and validate the authenticity of such products. Authentication of a food product is the process of ensuring that the product matches the assertions on the label and complies with rules. Conventionally, various comprehensive and targeted approaches like molecular, chemical, protein based, and chromatographic techniques are being utilized for identifying the species, origin, peculiar ingredients and the kind of processing method used to produce the particular product. Despite being very accurate and unimpeachable, these techniques ruin the structure of food, are labor intensive, complicated, and can be employed on laboratory scale. Hence the need of hour is to identify alternative, modern instrumentation techniques which can help in overcoming the majority of the limitations offered by traditional methods. Spectroscopy is a quick, low cost, rapid, non-destructive, and emerging approach for verifying authenticity of animal origin foods. In this review authors will envisage the latest spectroscopic techniques being used for detection of fraud or adulteration in meat, fish, poultry, egg, and dairy products. Latest literature pertaining to emerging techniques including their advantages and limitations in comparison to different other commonly used analytical tools will be comprehensively reviewed. Challenges and future prospects of evolving advanced spectroscopic techniques will also be descanted.
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Affiliation(s)
- Vandana Chaudhary
- College of Dairy Science and Technology, Lala Lajpat Rai University of Veterinary and Animal Sciences, Hisar, India
| | - Priyanka Kajla
- Department of Food Technology, Guru Jambheshwar University of Science and Technology, Hisar, India
| | - Aastha Dewan
- Department of Food Technology, Guru Jambheshwar University of Science and Technology, Hisar, India
| | - R. Pandiselvam
- Division of Physiology, Biochemistry and Post-Harvest Technology, ICAR–Central Plantation Crops Research Institute, Kasaragod, India
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Chai Z, Bi H. Capture and identification of bacteria from fish muscle based on immunomagnetic beads and MALDI-TOF MS. Food Chem X 2022; 13:100225. [PMID: 35498980 PMCID: PMC9039919 DOI: 10.1016/j.fochx.2022.100225] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Revised: 01/02/2022] [Accepted: 01/20/2022] [Indexed: 11/12/2022] Open
Abstract
A protocol for the bacterial analysis in fish muscle was developed. Anti-bacterial antibodies modified magnetic beads (MBs) were used to capture bacteria. The bacterial identification accuracy from different complex food matrices was good. The presence of 10 CFU/mL E. coli is still detectable. It is promising to be applied in bacterial analysis to ensure muscle food safety.
In the present study, E. coli was taken as a model bacterium, anti-E. coli functionalized magnetic beads were constructed and used to capture E. coli from aqueous extracts of fish sarcoplasmic protein (FSP) and fish muscle protein of sablefish. The excellency of the reproducibility of the present protocol was demonstrated by capturing E. coli from sablefish FSP extracts. The presence of 10 CFU/mL E. coli is still detectable. A microbial safety test on the surface of fish muscle was successfully performed. The bacterial identification accuracy from samples with different matrices was found to be excellent with RSD = 3%. High specific detection of target bacteria in complex biological samples was testified by spiking Staphylococcus aureus and Klebsiella pneumoniae in samples as interference. Ten biomarker ions were discovered for E. coli’s recognition. It is promising to apply the present protocol in bacterial analysis in muscle food samples to ensure their safety.
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Zhao X, Bi H. MALDI-TOF mass spectrometry applied for animal species identification based on bone samples. Analyst 2022; 147:1128-1134. [DOI: 10.1039/d1an02163j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Animal bones could be differentiated by mild acid-based hydrolysis, MALDI-TOF MS and PCA, holding a great potential for animal species monitoring in raw fish and meats, and for judicial authentication.
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Affiliation(s)
- Xin Zhao
- College of Food Science and Engineering, Shanghai Ocean University, Hucheng Ring Road 999, Pudong New District, 201306 Shanghai, China
| | - Hongyan Bi
- College of Food Science and Engineering, Shanghai Ocean University, Hucheng Ring Road 999, Pudong New District, 201306 Shanghai, China
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Chai Z, Wang C, Bi H. Rapid Identification between Two Fish Species Using UV-Vis Spectroscopy for Substitution Detection. Molecules 2021; 26:molecules26216529. [PMID: 34770938 PMCID: PMC8587656 DOI: 10.3390/molecules26216529] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2021] [Revised: 10/27/2021] [Accepted: 10/27/2021] [Indexed: 11/17/2022] Open
Abstract
Fish species substitution and fraud has become a worldwide economic issue in the seafood industry. In this study, an ultraviolet-visible (UV-Vis) spectroscopy-based method was developed for the identification of fish samples. Sixty fish samples from twelve commonly consumed fish species in China were analyzed as models to testify the protocol. The obtained results show that UV-Vis spectroscopy combined with chemometric analysis, such as principal component analysis (PCA), can accurately distinguish two fish species by boiling fish tissue sample in trifluoroacetic acid (TFA) solution for 2 min and analyzing the resultant samples using a UV-Vis spectrometer. The developed strategy was successfully applied to the classification and identification of fish samples on the market. It is a promising strategy that can be applied to the classification and authenticity testing of closely related fish species in order to detect and recognize fish substitution.
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Affiliation(s)
| | | | - Hongyan Bi
- Correspondence: ; Tel.: +86-21-6190-0364; Fax: +86-21-6190-0365
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Wang P, Fei P, Zhou C, Hong P. Preparation of acylated pectins with phenolic acids through lipase-catalyzed reaction and evaluation of their preservation performance. Lebensm Wiss Technol 2021. [DOI: 10.1016/j.lwt.2021.111615] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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MALDI-TOF Mass Spectrometry Applications for Food Fraud Detection. APPLIED SCIENCES-BASEL 2021. [DOI: 10.3390/app11083374] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Chemical analysis of food products relating to the detection of the most common frauds is a complex task due to the complexity of the matrices and the unknown nature of most processes. Moreover, frauds are becoming more and more sophisticated, making the development of reliable, rapid, cost-effective new analytical methods for food control even more pressing. Over the years, MALDI-TOF MS has demonstrated the potential to meet this need, also due to a series of undeniable intrinsic advantages including ease of use, fast data collection, and capability to obtain valuable information even from complex samples subjected to simple pre-treatment procedures. These features have been conveniently exploited in the field of food frauds in several matrices, including milk and dairy products, oils, fish and seafood, meat, fruit, vegetables, and a few other categories. The present review provides a comprehensive overview of the existing MALDI-based applications for food quality assessment and detection of adulterations.
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