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Sangwan S, Vikram R, Hooda E, Choudhary R, Jawla J, Somagond YM, Balhara S, Phulia SK, Khan MH, Girish PS, Datta TK, Mitra A, Balhara AK. Urinary metabolomics reveals potential biomarkers for early detection of pregnancy in Mithun (Bos frontalis) cows. J Proteomics 2024; 306:105259. [PMID: 39019397 DOI: 10.1016/j.jprot.2024.105259] [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: 05/20/2024] [Revised: 07/04/2024] [Accepted: 07/14/2024] [Indexed: 07/19/2024]
Abstract
The present study investigated the urinary metabolic profiles of early pregnant and non-pregnant Mithun to identify potential pregnancy detection biomarkers. Urine samples were collected on days 0, 10, 18, 35 and 45 of gestation from pregnant (n = 6) and on days 0, 10 and 18 from non-pregnant (n = 6) Mithun. Urinary metabolites were assessed using proton nuclear magnetic resonance (1H NMR) spectroscopy and identified 270 metabolites. Statistical analyses demonstrated pronounced distinctions in metabolite profiles between pregnant and non-pregnant samples. Twenty-five metabolites that could discriminate between pregnant and non-pregnant Mithun based on Variable Importance in Projection (VIP) scores >1 were identified. Upon further examination of six metabolites (kynurenine, kynurenate, 3-hydroxykynurenine, quinolinate, tyrosine and leucine) identified with high VIP scores, ROC curve analyses demonstrated their significant predictive potential, with AUC values ranging between 0.50 and 0.85. Additionally, a combined panel of top 25 metabolites yielded an AUC value of 0.85. Pathway analysis identified seven potential metabolic pathway modulations during early gestation, with particular emphasis on phenylalanine, tyrosine and tryptophan biosynthesis, tryptophan pathway and pathways involved in the metabolism of various amino acids. In conclusion, kynurenine, kynurenate, 3-hydroxykynurenine, quinolinate, tyrosine, and leucine show promise as non-invasive urinary biomarkers for early pregnancy detection in Mithun. SIGNIFICANCE: This study presents the first report on the metabolic profile of urine from early pregnant and non-pregnant Mithun (Bos frontalis). The metabolites like kynurenine and its derivatives (kynurenate, 3-hydroxykynurenine and quinolinate), tyrosine and leucine were documented signature urinary metabolites associated with early pregnancy in Mithun. The identified combination of metabolites holds promise as predictive biomarkers for non-invasive urinary-based early pregnancy diagnostics in Mithun. In addition, this study identified changes in metabolic pathways that involve phenylalanine, tyrosine, tryptophan and related amino acids and biomarkers identified were either precursors or products within these metabolic pathways.
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Affiliation(s)
- Suman Sangwan
- Indian Council of Agricultural Research-Central Institute for Research on Buffaloes, Hisar, Haryana 125 001, India
| | - R Vikram
- Indian Council of Agricultural Research-National Research Centre on Mithun, Nagaland 797 106, India
| | - Ekta Hooda
- Indian Council of Agricultural Research-Central Institute for Research on Buffaloes, Hisar, Haryana 125 001, India
| | - Renu Choudhary
- Indian Council of Agricultural Research-Central Institute for Research on Buffaloes, Hisar, Haryana 125 001, India
| | - Jyoti Jawla
- Indian Council of Agricultural Research-Indian Veterinary Research Institute, Izatnagar 243 122, Uttar Pradesh, India
| | - Y M Somagond
- Indian Council of Agricultural Research-National Research Centre on Mithun, Nagaland 797 106, India
| | - Sunesh Balhara
- Indian Council of Agricultural Research-Central Institute for Research on Buffaloes, Hisar, Haryana 125 001, India
| | - S K Phulia
- Indian Council of Agricultural Research-Central Institute for Research on Buffaloes, Hisar, Haryana 125 001, India
| | - M H Khan
- Indian Council of Agricultural Research-Indian Veterinary Research Institute, Izatnagar 243 122, Uttar Pradesh, India
| | - P S Girish
- Indian Council of Agricultural Research-National Research Centre on Mithun, Nagaland 797 106, India
| | - T K Datta
- Indian Council of Agricultural Research-Central Institute for Research on Buffaloes, Hisar, Haryana 125 001, India
| | - A Mitra
- Indian Council of Agricultural Research-National Research Centre on Mithun, Nagaland 797 106, India
| | - A K Balhara
- Indian Council of Agricultural Research-Central Institute for Research on Buffaloes, Hisar, Haryana 125 001, India.
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Zwierzchowski G, Haxhiaj K, Wójcik R, Wishart DS, Ametaj BN. Identifying Predictive Biomarkers of Subclinical Mastitis in Dairy Cows through Urinary Metabotyping. Metabolites 2024; 14:205. [PMID: 38668333 PMCID: PMC11051925 DOI: 10.3390/metabo14040205] [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: 02/26/2024] [Revised: 03/22/2024] [Accepted: 03/30/2024] [Indexed: 04/28/2024] Open
Abstract
Mastitis is a significant infectious disease in dairy cows, resulting in milk yield loss and culling. Early detection of mastitis-prone cows is crucial for implementing effective preventive measures before disease onset. Current diagnosis of subclinical mastitis (SCM) relies on somatic cell count assessment post-calving, lacking predictive capabilities. This study aimed to identify metabolic changes in pre-SCM cows through targeted metabolomic analysis of urine samples collected 8 wks and 4 wks before calving, using mass spectrometry. A nested case-control design was employed, involving a total of 145 multiparous dairy cows, with disease occurrence monitored pre- and postpartum. Among them, 15 disease-free cows served as healthy controls (CON), while 10 cows exclusively had SCM, excluding those with additional diseases. Urinary metabolite profiling revealed multiple alterations in acylcarnitines, amino acids, and organic acids in pre-SCM cows. Metabotyping identified 27 metabolites that distinguished pre-SCM cows from healthy CON cows at both 8 and 4 wks before parturition. However, only four metabolites per week showed significant alterations (p < 0.005). Notably, a panel of four serum metabolites (asymmetric dimethylarginine, proline, leucine, and homovanillate) at 8 wks prepartum, and another panel (asymmetric dimethylarginine, methylmalonate, citrate, and spermidine) at 4 wks prepartum, demonstrated predictive ability as urinary biomarkers for SCM risk (AUC = 0.88; p = 0.02 and AUC = 0.88; p = 0.03, respectively). In conclusion, our findings indicate that metabolite testing can identify cows at risk of SCM as early as 8 and 4 wks before parturition. Validation of the two identified metabolite panels is warranted to implement these predictive biomarkers, facilitate early intervention strategies, and improve dairy cow management to mitigate the impact of SCM. Further research is needed to confirm the efficacy and applicability of these biomarkers in practical farm settings.
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Affiliation(s)
- Grzegorz Zwierzchowski
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada; (G.Z.); (K.H.)
- Faculty of Biology and Biotechnology, University of Warmia and Mazury, 1a Oczapowskiego Str., 10-719 Olsztyn, Poland
| | - Klevis Haxhiaj
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada; (G.Z.); (K.H.)
| | - Roman Wójcik
- Faculty of Veterinary Medicine, University of Warmia and Mazury, 1a Oczapowskiego Str., 10-719 Olsztyn, Poland;
| | - David S. Wishart
- Department of Biological and Computer Sciences, University of Alberta, Edmonton, AB T6G 2P5, Canada;
| | - Burim N. Ametaj
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada; (G.Z.); (K.H.)
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Ashokan M, Rana E, Sneha K, Namith C, Naveen Kumar GS, Azharuddin N, Elango K, Jeyakumar S, Ramesha KP. Metabolomics-a powerful tool in livestock research. Anim Biotechnol 2023; 34:3237-3249. [PMID: 36200897 DOI: 10.1080/10495398.2022.2128814] [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] [Indexed: 11/01/2022]
Abstract
Advancements in the Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS) along with recent developments in omics sciences have resulted in a better understanding of molecular mechanisms and pathways associated with the physio-pathological state of the animal. Metabolomics is a post-genomics tool that deals with small molecular metabolites in a given set of time which provides clear information about the status of an organism. Recently many researchers mainly focus their research on metabolomics studies due to its valuable information in the various fields of livestock management and precision dairying. The main aim of the present review is to provide an insight into the current research output from different sources and application of metabolomics in various areas of livestock including nutri-metabolomics, disease diagnosis advancements, reproductive disorders, pharmaco-metabolomics, genomics studies, and dairy production studies. The present review would be helpful in understanding the metabolomics methodologies and use of livestock metabolomics in various areas in a brief way.
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Affiliation(s)
- M Ashokan
- Southern Regional Station, ICAR-National Dairy Research Institute, Bangalore, India
- Animal Genetics and Breeding Division, Hassan Veterinary College, Hassan, India
- Department of Animal Husbandry, Cattle Breeding and Fodder Development, Thiruvarur, India
| | - Ekta Rana
- Southern Regional Station, ICAR-National Dairy Research Institute, Bangalore, India
| | - Kadimetla Sneha
- Animal Genetics and Breeding Division, Hassan Veterinary College, Hassan, India
| | - C Namith
- Southern Regional Station, ICAR-National Dairy Research Institute, Bangalore, India
| | - G S Naveen Kumar
- Animal Genetics and Breeding Division, Hassan Veterinary College, Hassan, India
| | - N Azharuddin
- Southern Regional Station, ICAR-National Dairy Research Institute, Bangalore, India
| | - K Elango
- Southern Regional Station, ICAR-National Dairy Research Institute, Bangalore, India
| | - S Jeyakumar
- Southern Regional Station, ICAR-National Dairy Research Institute, Bangalore, India
| | - K P Ramesha
- Southern Regional Station, ICAR-National Dairy Research Institute, Bangalore, India
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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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Hyuk Suh J. Critical review: metabolomics in dairy science - evaluation of milk and milk product quality. Food Res Int 2022; 154:110984. [DOI: 10.1016/j.foodres.2022.110984] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 12/20/2021] [Accepted: 12/27/2021] [Indexed: 12/13/2022]
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Eom JS, Kim ET, Kim HS, Choi YY, Lee SJ, Lee SS, Kim SH, Lee SS. Metabolomics comparison of serum and urine in dairy cattle using proton nuclear magnetic resonance spectroscopy. Anim Biosci 2021; 34:1930-1939. [PMID: 33902181 PMCID: PMC8563233 DOI: 10.5713/ab.20.0870] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 02/04/2021] [Accepted: 03/09/2021] [Indexed: 12/22/2022] Open
Abstract
OBJECTIVE The aim of the study was to conduct metabolic profiling of dairy cattle serum and urine using proton nuclear magnetic resonance (1H-NMR) spectroscopy and to compare the results obtained with those of other dairy cattle herds worldwide so as to provide a basic dataset to facilitate research on metabolites in serum and urine. METHODS Six dairy cattle were used in this study; all animals were fed the same diet, which was composed of total mixed ration; the fed amounts were based on voluntary intake. Blood from the jugular neck vein of each steer was collected at the same time using a separate serum tube. Urine samples were collected by hand sweeping the perineum. The metabolites were determined by 1H-NMR spectroscopy, and the obtained data were statistically analyzed by performing principal component analysis, partial least squares-discriminant analysis, variable importance in projection scores, and metabolic pathway data using Metaboanalyst 4.0. RESULTS The total number of metabolites in the serum and urine was measured to be 115 and 193, respectively, of which 47 and 81, respectively were quantified. Lactate (classified as an organic acid) and urea (classified as an aliphatic acylic compound) exhibited the highest concentrations in serum and urine, respectively. Some metabolites that have been associated with diseases such as ketosis, bovine respiratory disease, and metritis, and metabolites associated with heat stress were also found in the serum and urine samples. CONCLUSION The metabolites measured in the serum and urine could potentially be used to detect diseases and heat stress in dairy cattle. The results could also be useful for metabolomic research on the serum and urine of ruminants in Korea.
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Affiliation(s)
- Jun Sik Eom
- Division of Applied Life Science (BK21), Gyeongsang National University, Jinju 52828, Korea
| | - Eun Tae Kim
- National Institute of Animal Science, Rural Development Administration, Cheonan 31000, Korea
| | - Hyun Sang Kim
- Division of Applied Life Science (BK21), Gyeongsang National University, Jinju 52828, Korea
| | - You Young Choi
- Division of Applied Life Science (BK21), Gyeongsang National University, Jinju 52828, Korea
| | - Shin Ja Lee
- Institute of Agriculture and Life Science & University-Centered Labs, Gyeongsang National University, Jinju 52828, Korea
| | - Sang Suk Lee
- Ruminant Nutrition and Anaerobe Laboratory, College of Bio-industry Science, Sunchon National University, Suncheon 57922, Korea
| | - Seon Ho Kim
- Ruminant Nutrition and Anaerobe Laboratory, College of Bio-industry Science, Sunchon National University, Suncheon 57922, Korea
| | - Sung Sill Lee
- Division of Applied Life Science (BK21), Gyeongsang National University, Jinju 52828, Korea
- Institute of Agriculture and Life Science & University-Centered Labs, Gyeongsang National University, Jinju 52828, Korea
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Abstract
The metabolic alterations associated with the increase in milk production make the transition period critical to the health of dairy cows, usually leading to a higher incidence of disease in periparturient animals. In this manuscript, we describe the use of NMR-based untargeted metabolomics to follow how these changes impact the serum metabolome in a group of 28 transition dairy cows with no initial clinical diseases. Principal component analysis (PCA) of serum 1H NMR data from four weeks before calving to 8 weeks after parturition allowed us to clearly identify four stages during the transition period. Pairwise comparisons using orthogonal partial least square discriminant analysis (OPLS-DA) and univariate data analysis led to the identification of 18 metabolites that varied significantly through these stages. Species such as acetate, betaine, and creatine are observed early after calving, while other markers of metabolic stress, including acetone, β-hydroxybutyrate (BHB), and choline, accumulate significantly at the height of milk production. Furthermore, marked variations in the levels of lactate, allantoin, alanine, and other amino acids reveal the activation of different gluconeogenic pathways following parturition. Concomitant with a return to homeostasis, a gradual normalization of the serum metabolome occurs 8 weeks after calving. Correlations of metabolite levels with dietary and metabolic adaptations based on animal parity could also be identified. Overall, these results show that NMR-based chemometric methods are ideally suited to monitor manifestations of metabolic diseases throughout the transition period and to assess the impact of nutritional management schemes on the metabolism of dairy cows.
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Zhang G, Mandal R, Wishart DS, Ametaj BN. A Multi-Platform Metabolomics Approach Identifies Urinary Metabolite Signatures That Differentiate Ketotic From Healthy Dairy Cows. Front Vet Sci 2021; 8:595983. [PMID: 33575283 PMCID: PMC7871000 DOI: 10.3389/fvets.2021.595983] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Accepted: 01/04/2021] [Indexed: 12/19/2022] Open
Abstract
Ketosis and subclinical ketosis are widespread among dairy cows especially after calving. Etiopathology of ketosis has been related to negative energy balance. The objective of this study was to investigate metabolite fingerprints in the urine of pre-ketotic, ketotic, and post-ketotic cows to identify potential metabolite alterations that can be used in the future to identify susceptible cows for ketosis and metabolic pathways involved in the development of disease. In this study, NMR, DI/LC-MS/MS, and GC-MS-based metabolomics were used to analyze urine samples from 6 cows diagnosed with ketosis and 20 healthy control (CON) cows at -8 and -4 weeks prepartum, the week (+1 to +3) of ketosis diagnosis, and at +4 and +8 weeks after parturition. Univariate and multivariate analyses were used to screen metabolite panels that can identify cows at their pre-ketotic stage. A total of 54, 42, 48, 16, and 31 differential metabolites between the ketotic and CON cows were identified at -8 and -4 weeks prepartum, ketosis week, and at +4, and +8 weeks postpartum, respectively. Variable importance in projection (VIP) plots ranked the most significant differential metabolites, which differentiated ketotic cows from the CON ones. Additionally, several metabolic pathways that are related to ketosis were identified. Moreover, two promising metabolite panels were identified which clearly separated ketotic from CON cows with excellent level of sensitivity and specificity. Overall, multiple urinary metabolite alterations were identified in pre-ketotic, ketotic, and post-ketotic cows. The metabolite panels identified need to be validated in the future in a larger cohort of animals.
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Affiliation(s)
- Guanshi Zhang
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Rupasri Mandal
- Departments of Biological Sciences and Computing Science, University of Alberta, Edmonton, AB, Canada
| | - David S Wishart
- Departments of Biological Sciences and Computing Science, University of Alberta, Edmonton, AB, Canada
| | - Burim N Ametaj
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
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Eom JS, Lee SJ, Kim HS, Choi YY, Kim SH, Lee YG, Lee SS. Metabolomics Comparison of Hanwoo ( Bos taurus coreanae) Biofluids Using Proton Nuclear Magnetic Resonance Spectroscopy. Metabolites 2020; 10:E333. [PMID: 32824041 PMCID: PMC7465992 DOI: 10.3390/metabo10080333] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 08/12/2020] [Accepted: 08/12/2020] [Indexed: 12/23/2022] Open
Abstract
The aim of this study was to identify the metabolomic profiles of rumen fluid, serum, and urine from Hanwoo (Bos taurus coreanae), using proton nuclear magnetic resonance (1H-NMR) spectroscopy. In all, 189, 110, and 188 metabolites were identified in rumen fluid, serum, and urine, and 107, 49, and 99 were quantified, respectively. Organic acids, carbohydrates, and aliphatic acyclic compound metabolites were present at the highest concentrations in rumen fluid, serum, and urine, respectively. In addition, acetate, glucose, and urea were the most highly concentrated individual metabolites in rumen fluid, serum, and urine, respectively. In all, 77 metabolites were commonly identified, and 19 were quantified across three biofluids. Metabolic pathway analysis showed that the common quantified metabolites could provide relevant information about three main metabolic pathways, phenylalanine, tyrosine, and tryptophan biosynthesis; caffeine metabolism; and histidine metabolism. These results can be useful as reference values for future metabolomic research on Hanwoo biofluids in Korea.
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Affiliation(s)
- Jun Sik Eom
- Division of Applied Life Science (BK21Plus), Gyeongsang National University, Gyeongsangnam-do, Jinju-si 52828, Korea; (J.S.E.); (H.S.K.); (Y.Y.C.)
| | - Shin Ja Lee
- Institute of Agriculture and Life Science & University-Centered Labs, Gyeongsang National University, Gyeongsangnam-do, Jinju-si 52828, Korea;
| | - Hyun Sang Kim
- Division of Applied Life Science (BK21Plus), Gyeongsang National University, Gyeongsangnam-do, Jinju-si 52828, Korea; (J.S.E.); (H.S.K.); (Y.Y.C.)
| | - You Young Choi
- Division of Applied Life Science (BK21Plus), Gyeongsang National University, Gyeongsangnam-do, Jinju-si 52828, Korea; (J.S.E.); (H.S.K.); (Y.Y.C.)
| | - Sang Ho Kim
- Animal Nutrition and Physiology Team, National Institute of Animal Science, RDA, Jeonrabuk-do, Jeonju-si 55365, Korea; (S.H.K.); (Y.G.L.)
| | - Yoo Gyung Lee
- Animal Nutrition and Physiology Team, National Institute of Animal Science, RDA, Jeonrabuk-do, Jeonju-si 55365, Korea; (S.H.K.); (Y.G.L.)
| | - Sung Sill Lee
- Division of Applied Life Science (BK21Plus), Gyeongsang National University, Gyeongsangnam-do, Jinju-si 52828, Korea; (J.S.E.); (H.S.K.); (Y.Y.C.)
- Institute of Agriculture and Life Science & University-Centered Labs, Gyeongsang National University, Gyeongsangnam-do, Jinju-si 52828, Korea;
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