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Li M, Bai Y, Zhang J, Wang H, Li J, Wang W. Sperm metabolomics identifies freezability markers in Duroc, Landrace, and Large White boars. Theriogenology 2025; 240:117395. [PMID: 40112454 DOI: 10.1016/j.theriogenology.2025.117395] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2024] [Revised: 02/14/2025] [Accepted: 03/15/2025] [Indexed: 03/22/2025]
Abstract
Cryopreservation of boar semen is widely applied in the conservation of genetic resources and animal breeding to enhance the utilization efficiency of superior boars. However, accurately identifying individuals with good freezing tolerance in boar sperm remains challenging. In this study, based on the differences in sperm motility before and after cryopreservation from 328 boars, we selected six boars each from the Duroc, Landrace, and Large White breeds, and categorized them into poor freezability ejaculates (PFE) and good freezability ejaculates (GFE) groups for sperm metabolomic analysis. A total of 1288 metabolites were identified using both positive and negative ion modes. There were 148 differentially expressed metabolites between the GFE and PFE groups, which were enriched in pathways such as alanine, aspartate and glutamate metabolism; arginine biosynthesis; D-amino acid metabolism; histidine metabolism; beta-alanine metabolism; citrate cycle (TCA cycle); pantothenate and CoA biosynthesis; and pyruvate metabolism. Further analysis, including ROC curve evaluation, identified seven potential biomarkers for sperm cryopreservation. Argininosuccinic acid, asparagine, L-aspartate, fumarate, D-ornithine, DL-serine and histidine were tightly interconnected in a series of amino acids metabolism. In conclusion, our findings imply that differences in certain amino acid biosynthetic pathways contribute to the variations in freezing tolerance of boar sperm.
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Affiliation(s)
- Meicheng Li
- College of Animal Science and Technology, Hebei Agricultural University, Baoding, 071000, China
| | - Yifan Bai
- Key Laboratory of Agricultural Animal Genetics, Breeding, and Reproduction of Ministry of Education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Jiajun Zhang
- College of Animal Science and Technology, Hebei Agricultural University, Baoding, 071000, China
| | - Hongyang Wang
- Institute of Animal Science and Veterinary Medicine, Shanghai Academy of Agricultural Sciences, Key Laboratory of Livestock and Poultry Resources (Pig) Evaluation and Utilization, Ministry of Agriculture and Rural Affairs, Shanghai, China
| | - Junjie Li
- College of Animal Science and Technology, Hebei Agricultural University, Baoding, 071000, China
| | - Wenjun Wang
- College of Animal Science and Technology, Hebei Agricultural University, Baoding, 071000, China.
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Nunes AT, Faleiros CA, Poleti MD, Novais FJ, López-Hernández Y, Mandal R, Wishart DS, Fukumasu H. Unraveling Ruminant Feed Efficiency Through Metabolomics: A Systematic Review. Metabolites 2024; 14:675. [PMID: 39728456 DOI: 10.3390/metabo14120675] [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: 10/14/2024] [Revised: 11/22/2024] [Accepted: 11/28/2024] [Indexed: 12/28/2024] Open
Abstract
BACKGROUND Advancements in metabolomic technologies have revolutionized our understanding of feed efficiency (FE) in livestock, offering new pathways to enhance both profitability and sustainability in ruminant production. METHODS This review offers a critical and systematic evaluation of the metabolomics methods used to measure and assess FE in ruminants. We conducted a comprehensive search of PubMed, Web of Science, and Scopus databases, covering publications from 1971 to 2023. This review synthesizes findings from 71 studies that applied metabolomic approaches to uncover the biological mechanisms driving interindividual variations in FE across cattle, sheep, goats, and buffaloes. RESULTS Most studies focused on cattle and employed targeted metabolomics to identify key biomarkers, including amino acids, fatty acids, and other metabolites linked to critical pathways such as energy metabolism, nitrogen utilization, and muscle development. Despite promising insights, challenges remain, including small sample sizes, methodological inconsistencies, and a lack of validation studies, particularly for non-cattle species. CONCLUSIONS By leveraging state-of-the-art metabolomic methods, this review highlights the potential of metabolomics to provide cost-effective, non-invasive molecular markers for FE evaluation, paving the way for more efficient and sustainable livestock management. Future research should prioritize larger, species-specific studies with standardized methods to validate identified biomarkers and enhance practical applications in livestock production systems.
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Affiliation(s)
- Alanne T Nunes
- Department of Veterinary Medicine, School of Animal Science and Food Engineering (FZEA), University of São Paulo, Pirassununga 13635-900, Brazil
| | - Camila A Faleiros
- Department of Veterinary Medicine, School of Animal Science and Food Engineering (FZEA), University of São Paulo, Pirassununga 13635-900, Brazil
| | - Mirele D Poleti
- Department of Veterinary Medicine, School of Animal Science and Food Engineering (FZEA), University of São Paulo, Pirassununga 13635-900, Brazil
| | - Francisco J Novais
- Department of Agricultural, Food and Nutritional Science, Faculty of Agricultural, Life and Environmental Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
| | - Yamilé López-Hernández
- Departments of Biological Sciences and Computing Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
- Metabolomics and Proteomics Laboratory, CONAHCyT-Autonomous University of Zacatecas, Zacatecas 98066, Mexico
| | - Rupasri Mandal
- Departments of Biological Sciences and Computing Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
| | - David S Wishart
- Departments of Biological Sciences and Computing Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
| | - Heidge Fukumasu
- Department of Veterinary Medicine, School of Animal Science and Food Engineering (FZEA), University of São Paulo, Pirassununga 13635-900, Brazil
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Yang H, Ren J, Ji P, Zhang X, Mai Z, Li C, Zhao N, Ma T, Zhu X, Hua Y, Wei Y. Investigating the regulatory effect of Shen Qi Bu Qi powder on the gastrointestinal flora and serum metabolites in calves. Front Cell Infect Microbiol 2024; 14:1443712. [PMID: 39247054 PMCID: PMC11377352 DOI: 10.3389/fcimb.2024.1443712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Accepted: 08/02/2024] [Indexed: 09/10/2024] Open
Abstract
Object To investigate the effects of Shen Qi Bu Qi Powder (SQBQP) on the average daily gain, blood indexes, gastrointestinal microflora, and serum metabolites of calves. Methods A total of 105 calves were randomly assigned to three groups (n = 35 per group): the control group (C, fed with a basal diet for 21 days) and two treatment groups (SQBQP-L and SQBQP-H, fed with the basal diet supplemented with 15 and 30 g/kg of SQBQP), respectively for 21 days. The active components of SQBQP were identified using LC-MS/MS. Serum digestive enzymes and antioxidant indices were determined by ELISA kits and biochemical kits, respectively. Serum differential metabolites were analyzed by liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS), while flora in rumen fluid and fecal were analyzed by 16S rDNA sequencing. Further correlation analysis of gastrointestinal flora and serum metabolites of SQBQP-H and C groups were performed with Spearman's correlation. Results The principal active components of SQBQP mainly includes polysaccharides, flavonoids, and organic acids. Compared to the control group (C), calves in the SQBQP-H (high dose) and SQBQP-L (low dose) groups showed a significant increase in serum amylase (AMS) levels (P<0.001), while lipase content significantly decreased (P<0.05). Additionally, the average daily gain, T-AOC, and cellulase content of calves in the SQBQP-H group significantly increased (P<0.05). Proteobacteria and Succinivibrio in the rumen flora of the SQBQP-H group was significantly lower than that of the C group (P<0.05). The relative abundance of Proteobacteria, Actinobacteria, Candidatus_Saccharibacteria, Deinococcus_Thermus, Cyanobacteria, and Succinivibrio in the SQBQP-H group was significantly increased (P<0.05), while the relative abundance of Tenericutes and Oscillibacter was significantly decreased (P<0.05). Serum metabolomics analysis revealed 20 differential metabolites, mainly enriched in amino acid biosynthesis, β-alanine metabolism, tyrosine, and tryptophan biosynthesis metabolic pathways (P<0.05). Correlation analysis results showed that Butyrivibrio in rumen flora and Oscillibacter_valericigenes in intestinal flora were significantly positively correlated with average daily gain, serum biochemical indexes, and differential metabolite (-)-Epigallocatechin (R>0.58, P<0.05). Conclusion SQBQP can promote calves weight gain and enhance health by modulating gastrointestinal flora and metabolic processes in the body.
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Affiliation(s)
- Haochi Yang
- College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, China
| | - Jianming Ren
- College of Chemistry and Life Sciences, Gansu Minzu Normal University, Gannan, China
| | - Peng Ji
- College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, China
| | - Xiaosong Zhang
- Innovation Center for Traditional Chinese Veterinary Medicine, College of Veterinary Medicine, China Agricultural University, Beijing, China
| | - Zhanhai Mai
- College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, China
| | - Chenchen Li
- College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, China
| | - Nianshou Zhao
- College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, China
| | - Ting Ma
- College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, China
| | - Xiaopeng Zhu
- Zhangye Wanhe Animal Husbandry Industry Technology Development Co., Ltd, Zhangye, China
| | - Yongli Hua
- College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, China
| | - Yanming Wei
- College of Veterinary Medicine, Gansu Agricultural University, Lanzhou, China
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Zheng G, Wang D, Mao K, Wang M, Wang J, Xun W, Huang S. Exploring the Rumen Microbiota and Serum Metabolite Profile of Hainan Black Goats with Different Body Weights before Weaning. Animals (Basel) 2024; 14:425. [PMID: 38338068 PMCID: PMC10854652 DOI: 10.3390/ani14030425] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 01/20/2024] [Accepted: 01/22/2024] [Indexed: 02/12/2024] Open
Abstract
The critical role of the rumen microbiota in the growth performance of livestock is recognized, yet its significance in determining the body weight of goat kids before weaning remains less understood. To bridge this gap, our study delved into the rumen microbiota, serum metabolome, rumen fermentation, and rumen development in goat kids with contrasting body weights before weaning. We selected 10 goat kids from a cohort of 100, categorized into low body weight (LBW, 5.56 ± 0.98 kg) and high body weight (HBW, 9.51 ± 1.01 kg) groups. The study involved sampling rumen contents, tissues, and serum from these animals. Our findings showed that the HBW goat kids showed significant enrichment of VFA-producing bacteria, particularly microbiota taxa within the Prevotellaceae genera (UCG-001, UCG-003, and UCG-004) and the Prevotella genus. This enrichment correlated with elevated acetate and butyrate levels, positively influencing rumen papillae development. Additionally, it was associated with elevated serum levels of glucose, total cholesterol, and triglycerides. The serum metabonomic analysis revealed marked differences in fatty acid metabolism between the LBW and HBW groups, particularly in encompassing oleic acid and both long-chain saturated and polyunsaturated fatty acids. Further correlational analysis underscored a significant positive association between Prevotellaceae_UCG-001 and specific lipids, such as phosphatidylcholine (PC) (22:5/18:3) and PC (20:3/20:1) (r > 0.60, p < 0.05). In summary, this study underscores the pivotal role of the rumen microbiota in goat kids' weight and its correlation with specific serum metabolites. These insights could pave the way for innovative strategies aimed at improving animal body weight through targeted modulation of the rumen microbiota.
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Affiliation(s)
| | | | | | | | | | | | - Shuai Huang
- Forage Processing and Ruminant Nutrition Laboratory, School of Tropical Agriculture and Forestry, Hainan University, Haikou 570228, China; (G.Z.)
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Jiang S, Si J, Mo J, Zhang S, Chen K, Gao J, Xu D, Bai L, Lan G, Liang J. Integrated Microbiome and Serum Metabolome Analysis Reveals Molecular Regulatory Mechanisms of the Average Daily Weight Gain of Yorkshire Pigs. Animals (Basel) 2024; 14:278. [PMID: 38254447 PMCID: PMC10812420 DOI: 10.3390/ani14020278] [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: 11/01/2023] [Revised: 12/31/2023] [Accepted: 01/08/2024] [Indexed: 01/24/2024] Open
Abstract
The average daily weight gain (ADG) is considered a crucial indicator for assessing growth rates in the swine industry. Therefore, investigating the gastrointestinal microbiota and serum metabolites influencing the ADG in pigs is pivotal for swine breed selection. This study involved the inclusion of 350 purebred Yorkshire pigs (age: 90 ± 2 days; body weight: 41.20 ± 4.60 kg). Concurrently, serum and fecal samples were collected during initial measurements of blood and serum indices. The pigs were categorized based on their ADG, with 27 male pigs divided into high-ADG (HADG) and low-ADG (LADG) groups based on their phenotype values. There were 12 pigs in LADG and 15 pigs in HADG. Feces and serum samples were collected on the 90th day. Microbiome and non-targeted metabolomics analyses were conducted using 16S rRNA sequencing and liquid chromatography-mass spectrometry (LC-MS). Pearson correlation, with Benjamini-Hochberg (BH) adjustment, was employed to assess the associations between these variables. The abundance of Lactobacillus and Prevotella in LADG was significantly higher than in HADG, while Erysipelothrix, Streptomyces, Dubosiella, Parolsenella, and Adlercreutzia in LADG were significantly lower than in HADG. The concentration of glutamine, etiocholanolone glucuronide, and retinoyl beta-glucuronide in LADG was significantly higher than in HADG, while arachidonic acid, allocholic acid, oleic acid, phenylalanine, and methyltestosterone in LADG were significantly lower than in HADG. The Lactobacillus-Streptomyces networks (Lactobacillus, Streptomyces, methyltestosterone, phenylalanine, oleic acid, arachidonic acid, glutamine, 3-ketosphingosine, L-octanoylcarnitine, camylofin, 4-guanidinobutyrate 3-methylcyclopentadecanone) were identified as the most influential at regulating swine weight gain. These findings suggest that the gastrointestinal tract regulates the daily weight gain of pigs through the network of Lactobacillus and Streptomyces. However, this study was limited to fecal and serum samples from growing and fattening boars. A comprehensive consideration of factors affecting the daily weight gain in pig production, including gender, parity, season, and breed, is warranted.
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Affiliation(s)
- Shan Jiang
- College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (S.J.); (J.S.); (J.M.); (S.Z.); (K.C.); (J.G.); (D.X.); (G.L.)
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Jinglei Si
- College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (S.J.); (J.S.); (J.M.); (S.Z.); (K.C.); (J.G.); (D.X.); (G.L.)
- Guangxi State Farms Yongxin Animal Husbandary Group Co., Ltd., Nanning 530022, China
| | - Jiayuan Mo
- College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (S.J.); (J.S.); (J.M.); (S.Z.); (K.C.); (J.G.); (D.X.); (G.L.)
| | - Shuai Zhang
- College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (S.J.); (J.S.); (J.M.); (S.Z.); (K.C.); (J.G.); (D.X.); (G.L.)
| | - Kuirong Chen
- College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (S.J.); (J.S.); (J.M.); (S.Z.); (K.C.); (J.G.); (D.X.); (G.L.)
| | - Jiuyu Gao
- College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (S.J.); (J.S.); (J.M.); (S.Z.); (K.C.); (J.G.); (D.X.); (G.L.)
| | - Di Xu
- College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (S.J.); (J.S.); (J.M.); (S.Z.); (K.C.); (J.G.); (D.X.); (G.L.)
| | - Lijing Bai
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518124, China
| | - Ganqiu Lan
- College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (S.J.); (J.S.); (J.M.); (S.Z.); (K.C.); (J.G.); (D.X.); (G.L.)
| | - Jing Liang
- College of Animal Science & Technology, Guangxi University, Nanning 530004, China; (S.J.); (J.S.); (J.M.); (S.Z.); (K.C.); (J.G.); (D.X.); (G.L.)
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