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Cardoso AS, Whitby A, Green MJ, Kim DH, Randall LV. Identification of Predictive Biomarkers of Lameness in Transition Dairy Cows. Animals (Basel) 2024; 14:2030. [PMID: 39061492 PMCID: PMC11273747 DOI: 10.3390/ani14142030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 06/23/2024] [Accepted: 07/07/2024] [Indexed: 07/28/2024] Open
Abstract
The aim of this study was to identify with a high level of confidence metabolites previously identified as predictors of lameness and understand their biological relevance by carrying out pathway analyses. For the dairy cattle sector, lameness is a major challenge with a large impact on animal welfare and farm economics. Understanding metabolic alterations during the transition period associated with lameness before the appearance of clinical signs may allow its early detection and risk prevention. The annotation with high confidence of metabolite predictors of lameness and the understanding of interactions between metabolism and immunity are crucial for a better understanding of this condition. Using liquid chromatography-tandem mass spectrometry (LC-MS/MS) with authentic standards to increase confidence in the putative annotations of metabolites previously determined as predictive for lameness in transition dairy cows, it was possible to identify cresol, valproic acid, and gluconolactone as L1, L2, and L1, respectively which are the highest levels of confidence in identification. The metabolite set enrichment analysis of biological pathways in which predictors of lameness are involved identified six significant pathways (p < 0.05). In comparison, over-representation analysis and topology analysis identified two significant pathways (p < 0.05). Overall, our LC-MS/MS analysis proved to be adequate to confidently identify metabolites in urine samples previously found to be predictive of lameness, and understand their potential biological relevance, despite the challenges of metabolite identification and pathway analysis when performing untargeted metabolomics. This approach shows potential as a reliable method to identify biomarkers that can be used in the future to predict the risk of lameness before calving. Validation with a larger cohort is required to assess the generalization of these findings.
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Affiliation(s)
- Ana S. Cardoso
- School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Sutton Bonington, Leicestershire LE12 5RD, UK
| | - Alison Whitby
- Centre for Analytical Bioscience, Advanced Materials & Healthcare Technologies Division, School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK (D.-H.K.)
| | - Martin J. Green
- School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Sutton Bonington, Leicestershire LE12 5RD, UK
| | - Dong-Hyun Kim
- Centre for Analytical Bioscience, Advanced Materials & Healthcare Technologies Division, School of Pharmacy, University of Nottingham, Nottingham NG7 2RD, UK (D.-H.K.)
| | - Laura V. Randall
- School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Sutton Bonington, Leicestershire LE12 5RD, UK
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Lemas DJ, Du X, Dado-Senn B, Xu K, Dobrowolski A, Magalhães M, Aristizabal-Henao JJ, Young BE, Francois M, Thompson LA, Parker LA, Neu J, Laporta J, Misra BB, Wane I, Samaan S, Garrett TJ. Untargeted Metabolomic Analysis of Lactation-Stage-Matched Human and Bovine Milk Samples at 2 Weeks Postnatal. Nutrients 2023; 15:3768. [PMID: 37686800 PMCID: PMC10490210 DOI: 10.3390/nu15173768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 08/20/2023] [Accepted: 08/21/2023] [Indexed: 09/10/2023] Open
Abstract
Epidemiological data demonstrate that bovine whole milk is often substituted for human milk during the first 12 months of life and may be associated with adverse infant outcomes. The objective of this study is to interrogate the human and bovine milk metabolome at 2 weeks of life to identify unique metabolites that may impact infant health outcomes. Human milk (n = 10) was collected at 2 weeks postpartum from normal-weight mothers (pre-pregnant BMI < 25 kg/m2) that vaginally delivered term infants and were exclusively breastfeeding their infant for at least 2 months. Similarly, bovine milk (n = 10) was collected 2 weeks postpartum from normal-weight primiparous Holstein dairy cows. Untargeted data were acquired on all milk samples using high-resolution liquid chromatography-high-resolution tandem mass spectrometry (HR LC-MS/MS). MS data pre-processing from feature calling to metabolite annotation was performed using MS-DIAL and MS-FLO. Our results revealed that more than 80% of the milk metabolome is shared between human and bovine milk samples during early lactation. Unbiased analysis of identified metabolites revealed that nearly 80% of milk metabolites may contribute to microbial metabolism and microbe-host interactions. Collectively, these results highlight untargeted metabolomics as a potential strategy to identify unique and shared metabolites in bovine and human milk that may relate to and impact infant health outcomes.
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Affiliation(s)
- Dominick J. Lemas
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
- Department of Obstetrics and Gynecology, College of Medicine, University of Florida, Gainesville, FL 32608, USA;
- Center for Perinatal Outcomes Research, College of Medicine, University of Florida, Gainesville, FL 32608, USA;
| | - Xinsong Du
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Bethany Dado-Senn
- Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA;
| | - Ke Xu
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Amanda Dobrowolski
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Marina Magalhães
- Department of Behavioral Nursing Science, College of Nursing, University of Florida, Gainesville, FL 32603, USA;
| | - Juan J. Aristizabal-Henao
- Department of Physiological Science, Center for Environmental and Human Toxicology, College of Veterinary Science, University of Florida, Gainesville, FL 32608, USA;
| | - Bridget E. Young
- Division of Breastfeeding and Lactation Medicine, University of Rochester Medical Center, Rochester, NY 14642, USA;
| | - Magda Francois
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Lindsay A. Thompson
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Leslie A. Parker
- Center for Perinatal Outcomes Research, College of Medicine, University of Florida, Gainesville, FL 32608, USA;
| | - Josef Neu
- Department of Pediatrics, College of Medicine, University of Florida, Gainesville, FL 32608, USA;
| | - Jimena Laporta
- Department of Obstetrics and Gynecology, College of Medicine, University of Florida, Gainesville, FL 32608, USA;
| | | | - Ismael Wane
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Samih Samaan
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32608, USA; (X.D.); (K.X.); (A.D.); (M.F.); (L.A.T.); (I.W.); (S.S.)
| | - Timothy J. Garrett
- Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL 32608, USA;
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Hu L, Brito LF, Luo H, Chen S, Johnson JS, Sammad A, Guo G, Xu Q, Wang Y. Differential Responses of Physiological Parameters, Production Traits, and Blood Metabolic Profiling between First- and Second-Parity Holstein Cows in the Comparison of Spring versus Summer Seasons. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023; 71:11902-11920. [PMID: 37490609 DOI: 10.1021/acs.jafc.3c00043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/27/2023]
Abstract
Heat stress (HS) negatively influences cows' welfare and productivity. Therefore, a better understanding of the physiological and molecular mechanisms of HS responses from multiple parities is paramount for the development of effective management and breeding strategies. In comparison with first-parity cows in the spring (Spring-1), first-parity cows in the summer (Summer-1) had a significantly higher rectal temperature (RT), respiration rate (RR), drooling score (DS), and daily activity (DA), while lower (P < 0.05) daily rumination (DR), seven-day average milk yield (7AMY), milk yield on sampling day (MY_S), milk yield on test day (MY_T), and lactose percentage (LP) were observed. When comparing the spring (Spring-2) and summer (Summer-2) of the second-parity cows, significant differences were also found in RT, RR, DS, DA, and DR (P < 0.05), corresponding to similar trends with the first parity while having smaller changes. Moreover, significantly negative impacts on performance traits were only observed on fat percentage (FP) and LP. These results showed that there were different biological responses between first- and second-parity Holstein cows. Further, 18 and 17 metabolites were involved in the seasonal response of first- and second-parity cows, respectively. Nine differential metabolites were shared between the two parities, and pathway analyses suggested that cows had an inhibited tricarboxylic acid cycle, increased utilization of lipolysis, and a dysregulated gut microbiome during the summer. The metabolites identified exclusively for each parity highlighted the differences in microbial response and host amino acid metabolism between two parities in response to HS. Moreover, glucose, ethanol, and citrate were identified as potential biomarkers for distinguishing individuals between Spring-1 and Summer-1. Ethanol and acetone were better predictors for distinguishing individuals between Spring-2 and Summer-2. Taken together, the present study demonstrated the impact of naturally induced HS on physiological parameters, production traits, and the blood metabolome of Holstein cows. There are different biological responses and regulation mechanisms between first- and second-parity Holstein cows.
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Affiliation(s)
- Lirong Hu
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory for Animal Breeding, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
- College of Life Sciences and Bioengineering, Beijing Jiaotong University, Beijing 100044, China
- Department of Animal Sciences, Purdue University, West Lafayette, Indiana 47907, United States
| | - Luiz F Brito
- Department of Animal Sciences, Purdue University, West Lafayette, Indiana 47907, United States
| | - Hanpeng Luo
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory for Animal Breeding, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Shaokan Chen
- Beijing Sunlon Livestock Development Co. Ltd, Beijing 100176, China
| | - Jay S Johnson
- USDA-ARS Livestock Behavior Research Unit, West Lafayette, Indiana 47907, United States
| | - Abdul Sammad
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory for Animal Breeding, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Gang Guo
- Beijing Sunlon Livestock Development Co. Ltd, Beijing 100176, China
| | - Qing Xu
- College of Life Sciences and Bioengineering, Beijing Jiaotong University, Beijing 100044, China
| | - Yachun Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory for Animal Breeding, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
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Barden M, Phelan MM, Hyde R, Anagnostopoulos A, Griffiths BE, Bedford C, Green M, Psifidi A, Banos G, Oikonomou G. Serum 1H nuclear magnetic resonance-based metabolomics of sole lesion development in Holstein cows. J Dairy Sci 2023; 106:2667-2684. [PMID: 36870845 PMCID: PMC10073068 DOI: 10.3168/jds.2022-22681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2022] [Accepted: 11/15/2022] [Indexed: 03/06/2023]
Abstract
Sole hemorrhage and sole ulcers, referred to as sole lesions, are important causes of lameness in dairy cattle. We aimed to compare the serum metabolome of dairy cows that developed sole lesions in early lactation with that of cows that remained unaffected. We prospectively enrolled a cohort of 1,169 Holstein dairy cows from a single dairy herd and assessed animals at 4 time points: before calving, immediately after calving, early lactation, and late lactation. Sole lesions were recorded by veterinary surgeons at each time point, and serum samples were collected at the first 3 time points. Cases were defined by the presence of sole lesions in early lactation and further subdivided by whether sole lesions had been previously recorded; unaffected controls were randomly selected to match cases. Serum samples from a case-control subset of 228 animals were analyzed with proton nuclear magnetic resonance spectroscopy. Spectral signals, corresponding to 34 provisionally annotated metabolites and 51 unlabeled metabolites, were analyzed in subsets relating to time point, parity cohort, and sole lesion outcome. We used 3 analytic methods (partial least squares discriminant analysis, least absolute shrinkage and selection operator regression, and random forest) to determine the predictive capacity of the serum metabolome and identify informative metabolites. We applied bootstrapped selection stability, triangulation, and permutation to support the inference of variable selection. The average balanced accuracy of class prediction ranged from 50 to 62% depending on the subset. Across all 17 subsets, 20 variables had a high probability of being informative; those with the strongest evidence of being associated with sole lesions corresponded to phenylalanine and 4 unlabeled metabolites. We conclude that the serum metabolome, as characterized by proton nuclear magnetic resonance spectroscopy, does not appear able to predict sole lesion presence or future development of lesions. A small number of metabolites may be associated with sole lesions although, given the poor prediction accuracies, these metabolites are likely to explain only a small proportion of the differences between affected and unaffected animals. Future metabolomic studies may reveal underlying metabolic mechanisms of sole lesion etiopathogenesis in dairy cows; however, the experimental design and analysis need to effectively control for interanimal and extraneous sources of spectral variation.
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Affiliation(s)
- Matthew Barden
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst Campus, Liverpool, CH64 7TE, United Kingdom.
| | - Marie M Phelan
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, United Kingdom; High Field NMR Facility, Liverpool Shared Research Facilities University of Liverpool, Liverpool, L69 7ZB, United Kingdom
| | - Robert Hyde
- School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Leicestershire, LE12 5RD, United Kingdom
| | - Alkiviadis Anagnostopoulos
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst Campus, Liverpool, CH64 7TE, United Kingdom
| | - Bethany E Griffiths
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst Campus, Liverpool, CH64 7TE, United Kingdom
| | - Cherry Bedford
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst Campus, Liverpool, CH64 7TE, United Kingdom
| | - Martin Green
- School of Veterinary Medicine and Science, University of Nottingham, Sutton Bonington Campus, Leicestershire, LE12 5RD, United Kingdom
| | - Androniki Psifidi
- Department of Clinical Science and Services, Royal Veterinary College, North Mymms, Hertfordshire, AL9 7TA, United Kingdom
| | - Georgios Banos
- Animal & Veterinary Sciences, SRUC, Roslin Institute Building, Easter Bush, Midlothian, EH25 9RG, United Kingdom
| | - Georgios Oikonomou
- Department of Livestock and One Health, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Leahurst Campus, Liverpool, CH64 7TE, United Kingdom
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Mastitis: What It Is, Current Diagnostics, and the Potential of Metabolomics to Identify New Predictive Biomarkers. DAIRY 2022. [DOI: 10.3390/dairy3040050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/09/2023] Open
Abstract
Periparturient diseases continue to be the greatest challenge to both farmers and dairy cows. They are associated with a decrease in productivity, lower profitability, and a negative impact on cows’ health as well as public health. This review article discusses the pathophysiology and diagnostic opportunities of mastitis, the most common disease of dairy cows. To better understand the disease, we dive deep into the causative agents, traditional paradigms, and the use of new technologies for diagnosis, treatment, and prevention of mastitis. This paper takes a systems biology approach by highlighting the relationship of mastitis with other diseases and introduces the use of omics sciences, specifically metabolomics and its analytical techniques. Concluding, this review is backed up by multiple studies that show how earlier identification of mastitis through predictive biomarkers can benefit the dairy industry and improve the overall animal health.
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Zhang X, Liu T, Hou X, Hu C, Zhang L, Wang S, Zhang Q, Shi K. Multi-Channel Metabolomics Analysis Identifies Novel Metabolite Biomarkers for the Early Detection of Fatty Liver Disease in Dairy Cows. Cells 2022; 11:cells11182883. [PMID: 36139459 PMCID: PMC9496829 DOI: 10.3390/cells11182883] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 09/09/2022] [Accepted: 09/10/2022] [Indexed: 11/17/2022] Open
Abstract
Fatty liver disease, a type of metabolic disorder, frequently occurs in dairy cows during the parturition period, causing a high culling rate and, therefore, considerable economic losses in the dairy industry owing to the lack of effective diagnostic methods. Here, metabolite biomarkers were identified and validated for the diagnosis of metabolic disorders. A total of 58 participant cows, including severe fatty liver disease and normal control groups, in the discovery set (liver biopsy tested, n = 18), test set (suspected, n = 20) and verification set (liver biopsy tested, n = 20), were strictly recruited and a sample collected for their feces, urine, and serum. Non-targeted GC-MS-based metabolomics methods were used to characterize the metabolite profiles and to screen in the discovery set. Eventually, ten novel biomarkers involved in bile acid, amino acid, and fatty acid were identified and validated in the test set. Each of them had a higher diagnostic ability than the traditional serum biochemical indicators, with an average area under the receiver operating characteristic curve of 0.830 ± 0.0439 (n = 10) versus 0.377 ± 0.182 (n = 9). Especially, combined biomarker panels via different metabolic pipelines had much better diagnostic sensitivity and specificity than every single biomarker, suggesting their powerful utilization potentiality for the early detection of fatty liver disease. Intriguingly, the serum biomarkers were confirmed perfectly in the verification set. Moreover, common biological pathways were found to be underlying the pathogenesis of fatty liver syndrome in cattle via different metabolic pipelines. These newly-discovered and non-invasive metabolic biomarkers are meaningful in reducing the high culling rate of cows and, therefore, benefit the sustainable development of the dairy industry.
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Li R, Wang S, Zhang J, Miao J, Chen G, Dong J, Wu L, Yue H, Yang J. Untargeted metabolomics allows to discriminate raw camel milk, heated camel milk, and camel milk powder. Int Dairy J 2022. [DOI: 10.1016/j.idairyj.2021.105140] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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Vidmar M, Hodnik JJ, Starič J. Review of guidelines for functional claw trimming and therapeutic approach to claw horn lesions in cattle. Trop Anim Health Prod 2021; 53:476. [PMID: 34553277 DOI: 10.1007/s11250-021-02924-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 09/10/2021] [Indexed: 11/30/2022]
Abstract
Lameness is one of the most pressing health and welfare problems in cattle, especially on dairy farms. The most common cause of lameness is claw pathology, often due to lack of appropriate functional claw trimming. Functional claw trimming restores the physiological shape of the claws and distributes weight properly between the claws and over the claw weight-bearing surface. It also allows closer examination of the claws for early signs of pathology. The methods of functional claw trimming described in the previous century are still applicable today, considering some recent findings on the subject. It is essential not to over-trim the claws and to maintain strict hygiene of the trimming tools. Claw horn pathology in the early stages is usually treated effectively by therapeutic claw trimming alone. The stoic nature of cattle and their natural tendency to hide pain often result in delayed treatment of claw diseases, leading to more advanced stages of disease/pathology associated with higher-grade lameness. This situation often leads to the development of neuropathic pain and hyperalgesia requiring multimodal treatment. Because claw horn diseases are multifactorial, veterinarians and others involved in animal management must be familiar with the preventive measures available to improve claw health in a cattle herd. Further research to improve claw horn quality and effectively control/prevent claw infections without polluting the environment or negatively affecting worker and animal health is still needed. This article reviews the latest knowledge on functional claw trimming and treatment of the most common claw horn diseases in cattle.
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Affiliation(s)
- M Vidmar
- University of Ljubljana, Veterinary faculty, Ljubljana, Slovenia
| | - J J Hodnik
- University of Ljubljana, Veterinary faculty, Ljubljana, Slovenia
| | - J Starič
- University of Ljubljana, Veterinary faculty, Ljubljana, Slovenia.
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Differences in lipid composition of Bigeye tuna (Thunnus obesus) during storage at 0 °C and 4 °C. Food Res Int 2021; 143:110233. [PMID: 33992346 DOI: 10.1016/j.foodres.2021.110233] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Revised: 02/13/2021] [Accepted: 02/14/2021] [Indexed: 12/17/2022]
Abstract
This study aimed to investigate the lipid oxidation and distribution in Bigeye tuna stored at 0 °C and 4 °C for 6 days. Tuna were evaluated by determining the peroxide value (POV), acid value (AV), anisidine value (AnV), polyene index, fluorescence ratio (FR), phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylinositol (PI) content, and major glycerophospholipid molecular species. The value of lipid oxidation indexes (POV, AV, AnV, FR, PC, PE and PI) increased as the storage time increased. High-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) results indicated that the major types of lipids included diacylglycerol (DAG), monoacylglycerol (MAG), phospholipid (PL), and triacylglycerol (TAG). At least 136 PC and 64 PE molecular species were identified in Bigeye tuna. The results of the confocal laser scanning microscope analysis indicated the distribution of TAG and PL particles. In addition, principal component analysis showed that the contents of PI and TAG were positively correlated with PC, polyene index and lipid content but negatively correlated with PI, POV, FR, AOV, AnV, MAG, and DAG, which might be explained by distinguishing the lipid parameters affecting lipid oxidation. Therefore, this study may provide a novel method to evaluate lipid changes and contribute to the balanced nutritional value of aquatic foods during cold storage.
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Jariyasopit N, Khamsaeng S, Panya A, Vinaisuratern P, Metem P, Asawalertpanich W, Visessanguan W, Sirivatanauksorn V, Khoomrung S. Quantitative analysis of nutrient metabolite compositions of retail cow’s milk and milk alternatives in Thailand using GC-MS. J Food Compost Anal 2021. [DOI: 10.1016/j.jfca.2020.103785] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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