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Xiao T, Zeng J, Zhao C, Hou Y, Wu T, Deng Z, Zheng L. Comparative Analysis of Protein Digestion Characteristics in Human, Cow, Goat, Sheep, Mare, and Camel Milk under Simulated Infant Condition. J Agric Food Chem 2023; 71:15035-15047. [PMID: 37801409 DOI: 10.1021/acs.jafc.3c03123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/08/2023]
Abstract
An infant in vitro digestion model was utilized to investigate protein digestion characteristics in human and diverse mammalian milk (i.e., cow, goat, sheep, mare, and camel milk) using electrophoresis and chromatography. Digestive differences among milks were mainly manifested in the infant gastric phase, as evidenced by varying degrees of protein digestion. Notably, proteins (i.e., lactoferrin, serum albumin, and immunoglobulin G-heavy chain) remained partially intact in human milk, whereas these proteins in animal milk were exclusively degraded after gastrointestinal digestion. The peptide spectra of human, mare, and camel milk were highly similar, with a predominant formation of low-intensity small peptides, whereas the other three milk showed the opposite phenomenon. Heatmap cluster analysis indicated that camel milk was the most comparable to human milk before digestion, yet sheep milk was the most similar to human milk regarding protein digestion behaviors following infant gastric digestion.
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Affiliation(s)
- Ting Xiao
- State Key Laboratory of Food Science and Resources, Nanchang University, Nanchang 330047, P. R. China
| | - Junpeng Zeng
- State Key Laboratory of Food Science and Resources, Nanchang University, Nanchang 330047, P. R. China
| | - Caidong Zhao
- State Key Laboratory of Food Science and Resources, Nanchang University, Nanchang 330047, P. R. China
| | - Yanmei Hou
- Hyproca Nutrition Co., Ltd., Changsha, Hunan 410200, P. R. China
| | - Tong Wu
- Hyproca Nutrition Co., Ltd., Changsha, Hunan 410200, P. R. China
| | - Zeyuan Deng
- State Key Laboratory of Food Science and Resources, Nanchang University, Nanchang 330047, P. R. China
- Institute for Advanced Study, Nanchang University, Nanchang 330031, P. R. China
| | - Liufeng Zheng
- State Key Laboratory of Food Science and Resources, Nanchang University, Nanchang 330047, P. R. China
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Cui Y, Ge L, Lu W, Wang S, Li Y, Wang H, Huang M, Xie H, Liao J, Tao Y, Luo P, Ding YY, Shen Q. Real-Time Profiling and Distinction of Lipids from Different Mammalian Milks Using Rapid Evaporative Ionization Mass Spectrometry Combined with Chemometric Analysis. J Agric Food Chem 2022; 70:7786-7795. [PMID: 35696488 DOI: 10.1021/acs.jafc.2c01447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The price of mammalian milk from different animal species varies greatly due to differences in their yield and nutritional value. Therefore, the authenticity of dairy products has become a hotspot issue in the market due to the replacement or partial admixture of high-cost milk with its low-cost analog. Herein, four common commercial varieties of milk, including goat milk, buffalo milk, Holstein cow milk, and Jersey cow milk, were successfully profiled and differentiated from each other by rapid evaporative ionization mass spectrometry (REIMS) combined with chemometric analysis. This method was developed as a real-time lipid fingerprinting technique. Moreover, the established chemometric algorithms based on multivariate statistical methods mainly involved principal component analysis, orthogonal partial least squares-discriminant analysis, and linear discriminant analysis as the screening and verifying tools to provide insights into the distinctive molecules constituting the four varieties of milk. The ions with m/z 229.1800, 243.1976, 257.2112, 285.2443, 299.2596, 313.2746, 341.3057, 355.2863, 383.3174, 411.3488, 439.3822, 551.5051, 577.5200, 628.5547, 656.5884, 661.5455, 682.6015, and 684.6146 were selected as potential classified markers. The results of the present work suggest that the proposed method could serve as a reference for recognizing dairy fraudulence related to animal species and expand the application field of REIMS technology.
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Affiliation(s)
- Yiwei Cui
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Lijun Ge
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Weibo Lu
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Shitong Wang
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Yunyan Li
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Haifeng Wang
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Min Huang
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Hujun Xie
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Jie Liao
- Zhejiang Huacai Testing Technology Co., Ltd., Shaoxing, Zhejiang 311800, China
| | - Ye Tao
- Hangzhou Linping District Maternal & Child Health Care Hospital, Hangzhou, Zhejiang 311113, China
| | - Pei Luo
- State Key Laboratories for Quality Research in Chinese Medicines, Faculty of Pharmacy, Macau University of Science and Technology, Macau 999078, China
| | - Yin-Yi Ding
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
| | - Qing Shen
- Collaborative Innovation Center of Seafood Deep Processing, Zhejiang Province Joint Key Laboratory of Aquatic Products Processing, Institute of Seafood, Zhejiang Gongshang University, Hangzhou, Zhejiang 310012, China
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Walter L, Shrestha P, Fry R, Leury BJ, Logan A. Lipid metabolic differences in cows producing small or large milk fat globules: Fatty acid origin and degree of saturation. J Dairy Sci 2019; 103:1920-1930. [PMID: 31759596 DOI: 10.3168/jds.2019-16775] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Accepted: 09/10/2019] [Indexed: 11/19/2022]
Abstract
This study compared cows that consistently produce milk with small (volume-weighted mean diameter of 2.92-3.83 µm, with an average diameter of 3.29 µm) or large (volume-weighted mean diameter of 4.58-5.67 µm, with an average diameter of 4.92 µm) milk fat globule (MFG) size distributions in terms of the fatty acid (FA) composition of the MFG core. Selected cows fell into the respective size group over at least 3 independent measurements, including an observation period before the experiment. Further selection criteria were similar milk production traits between cows (milk yield, fat yield, fat/protein ratio) and established lactation (>50 d in milk). However, the selected groups differed in parity (parity 1-3 and 3-5 in the small and large MFG groups, respectively), and the small MFG group was an average of 25 d in milk later in their lactation period. All cows were under the same nutritional management and environmental conditions. Here, we show that cows with the small or large MFG phenotype differed in their lipid metabolism in terms of the FA composition of the MFG core. Our results indicate that cows with the small MFG phenotype produced milk with higher concentrations of unsaturated FA despite being fed the same diet. We suggest that this characteristic of the small MFG phenotype is the result of increased uptake of long-chain FA from the blood circulation. A relationship between the degree of unsaturation and MFG size was also identified in preliminary studies across other species-namely, camels, sheep, and goats. These findings show the potential for on-farm selection of cows (and potentially other dairy species) based on MFG size to produce milk with improved nutrient composition. This could lead to purpose-specific separation of milk based on MFG size and FA profile, both known to alter the technological properties of milk.
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Affiliation(s)
- L Walter
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, Victoria, Australia 3010; CSIRO Agriculture and Food, Werribee, Victoria, Australia 3030
| | - P Shrestha
- CSIRO Agriculture and Food, Black Mountain, Canberra, Australia 2601
| | - R Fry
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, Victoria, Australia 3010
| | - B J Leury
- Faculty of Veterinary and Agricultural Sciences, The University of Melbourne, Parkville, Victoria, Australia 3010
| | - A Logan
- CSIRO Agriculture and Food, Werribee, Victoria, Australia 3030.
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Di Francesco L, Di Girolamo F, Mennini M, Masotti A, Salvatori G, Rigon G, Signore F, Pietrantoni E, Scapaticci M, Lante I, Goffredo BM, Mazzina O, Elbousify AI, Roncada P, Dotta A, Fiocchi A, Putignani L. A MALDI-TOF MS Approach for Mammalian, Human, and Formula Milks' Profiling. Nutrients 2018; 10:nu10091238. [PMID: 30189627 PMCID: PMC6163840 DOI: 10.3390/nu10091238] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2018] [Revised: 08/30/2018] [Accepted: 08/31/2018] [Indexed: 11/16/2022] Open
Abstract
Human milk composition is dynamic, and substitute formulae are intended to mimic its protein content. The purpose of this study was to investigate the potentiality of matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS), followed by multivariate data analyses as a tool to analyze the peptide profiles of mammalian, human, and formula milks. Breast milk samples from women at different lactation stages (2 (n = 5), 30 (n = 6), 60 (n = 5), and 90 (n = 4) days postpartum), and milk from donkeys (n = 4), cows (n = 4), buffaloes (n = 7), goats (n = 4), ewes (n = 5), and camels (n = 2) were collected. Different brands (n = 4) of infant formulae were also analyzed. Protein content (<30 kDa) was analyzed by MS, and data were exported for statistical elaborations. The mass spectra for each milk closely clustered together, whereas different milk samples resulted in well-separated mass spectra. Human samples formed a cluster in which colostrum constituted a well-defined subcluster. None of the milk formulae correlated with animal or human milk, although they were specifically characterized and correlated well with each other. These findings propose MALDI-TOF MS milk profiling as an analytical tool to discriminate, in a blinded way, different milk types. As each formula has a distinct specificity, shifting a baby from one to another formula implies a specific proteomic exposure. These profiles may assist in milk proteomics for easiness of use and minimization of costs, suggesting that the MALDI-TOF MS pipelines may be useful for not only milk adulteration assessments but also for the characterization of banked milk specimens in pediatric clinical settings.
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Affiliation(s)
- Laura Di Francesco
- Unit of Human Microbiome, Bambino Gesù Children's Hospital, IRCCS, V.le San Paolo 15, 00146 Rome, Italy.
| | - Francesco Di Girolamo
- Unit of Human Microbiome, Bambino Gesù Children's Hospital, IRCCS, V.le San Paolo 15, 00146 Rome, Italy.
| | - Maurizio Mennini
- Allergy Unit, Bambino Gesù Children's Hospital, IRCCS, Piazza Sant'Onofrio 4, 00165 Rome, Italy.
| | - Andrea Masotti
- Gene Expression-Microarrays Laboratory, Bambino Gesù Children's Hospital, IRCCS, V.le San Paolo 15, 00146 Rome, Italy.
| | - Guglielmo Salvatori
- Neonatal Intensive Care Unit, Department of Medical and Surgical Neonatology, Bambino Gesù Children's Hospital, IRCCS, Piazza Sant'Onofrio 4, 00165 Rome, Italy.
| | - Giuliano Rigon
- Department of Obstetrics and Gynecology, San Camillo Forlanini Hospital, Circonvallazione Gianicolense 87, 00151 Rome, Italy.
| | - Fabrizio Signore
- Department of Obstetrics and Gynecology, Misericordia Hospital Grosseto, Usl Toscana Sud-est, 58036 Grosseto, Italy.
| | - Emanuela Pietrantoni
- Rehabilitation Hospital of High Specialization of Motta di Livenza, 31100 Treviso, Italy.
| | - Margherita Scapaticci
- Department of Laboratory Medicine, San Camillo Hospital, V.le Vittorio Veneto 18, 31100 Treviso, Italy.
| | - Isabella Lante
- Department of Laboratory Medicine, San Camillo Hospital, V.le Vittorio Veneto 18, 31100 Treviso, Italy.
| | - Bianca Maria Goffredo
- Metabolic Unit, Department of Pediatric Medicine, Bambino Gesù Children's Hospital, IRCCS, V.le San Paolo 15, 00146 Rome, Italy.
| | - Oscar Mazzina
- Allergy Unit, Bambino Gesù Children's Hospital, IRCCS, Piazza Sant'Onofrio 4, 00165 Rome, Italy.
| | | | - Paola Roncada
- Department of Health Sciences, Università degli Studi "Magna Græcia" di Catanzaro, 88100 Catanzaro, Italy.
| | - Andrea Dotta
- Neonatal Intensive Care Unit, Department of Medical and Surgical Neonatology, Bambino Gesù Children's Hospital, IRCCS, Piazza Sant'Onofrio 4, 00165 Rome, Italy.
| | - Alessandro Fiocchi
- Allergy Unit, Bambino Gesù Children's Hospital, IRCCS, Piazza Sant'Onofrio 4, 00165 Rome, Italy.
| | - Lorenza Putignani
- Unit of Human Microbiome, Bambino Gesù Children's Hospital, IRCCS, V.le San Paolo 15, 00146 Rome, Italy.
- Unit of Parasitology, Bambino Gesù Children's Hospital, IRCCS, Piazza Sant'Onofrio 4, 00165 Rome, Italy.
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