Hostname: page-component-65b85459fc-997vn Total loading time: 0 Render date: 2025-10-17T11:04:02.496Z Has data issue: false hasContentIssue false
  • English
  • Français

Compositional and microbial transitions from colostrum to transition milk in Guanzhong dairy goats

Published online by Cambridge University Press:  15 October 2025

Tongyu Sun ,
Shuzhen Wang ,
Morteza Hosseini Ghaffari Open the ORCID record for Morteza Hosseini Ghaffari [Opens in a new window] ,
Jingyi Lv ,
Hangshu Xin  and
Tao Ma Open the ORCID record for Tao Ma [Opens in a new window]
Tongyu Sun
Affiliation:
Key laboratory of Feed Biotechnology of the Ministry of Agriculture, Institute of Feed Research of Chinese Academy of Agricultural Sciences, Beijing, China
Shuzhen Wang
Affiliation:
Key laboratory of Feed Biotechnology of the Ministry of Agriculture, Institute of Feed Research of Chinese Academy of Agricultural Sciences, Beijing, China
Morteza Hosseini Ghaffari
Affiliation:
Institute for Farm Animal Biology (FBN), Dummerstorf, Germany
Jingyi Lv
Affiliation:
College of Animal Sciences and Technology, Northeast Agricultural University, Harbin, China
Hangshu Xin
Affiliation:
College of Animal Sciences and Technology, Northeast Agricultural University, Harbin, China
Tao Ma*
Affiliation:
Key laboratory of Feed Biotechnology of the Ministry of Agriculture, Institute of Feed Research of Chinese Academy of Agricultural Sciences, Beijing, China
*
Corresponding author: Tao Ma; Email: matao@caas.cn
Get access Rights & Permissions [Opens in a new window]

Abstract

Colostrum (CM) and transition milk (TM) are crucial for neonatal development but knowledge about the changes in their composition in dairy goats is still limited. The aim of this study was to characterise the immunological, lipid and microbial changes from CM to TM in Guanzhong dairy goats, an indigenous, highly productive Chinese breed. Milk samples were collected from eight primiparous goats at day 0 (CM) and day 7 (TM) postpartum. Immunoglobulin concentrations (IgG, IgA, IgM) were measured by ELISA, long-chain saturated fatty acids (FA) were analysed by gas chromatography, and bacterial communities were profiled by 16S rRNA gene amplicon sequencing. Microbial functions were inferred using PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States) software based on KEGG (Kyoto Encyclopedia of Genes and Genomes) orthologs. Immunoglobulin concentrations declined significantly from CM to TM, reflecting a transition from immunoprotection to food supply. The TM had increased concentrations of long-chain saturated FA, particularly palmitic acid (C16:0) and stearic acid (C18:0) and higher concentrations of branched-chain FA, suggesting an adaptation to the growing energy demands of the newborn. Although overall microbial diversity was stable, taxonomic shifts were observed. CM was enriched in Emticicia, which may be involved in oligosaccharide degradation, while TM had higher abundance of Faecalibacterium, Ruminococcus and Salinicoccus, genera associated with SCFA production and intestinal development. Functional predictions indicated enrichment of cold shock and haem biosynthetic pathways in CM and enhanced carbohydrate degradation pathways in TM. Correlation analyses revealed relationships between specific FA and bacterial genera, suggesting interactions between host, microbes and nutrients that may influence milk functionality. This integrative analysis of milk components during early lactation provides new insights into the compositional and functional dynamics of goat milk.

Keywords

colostrumgoatlong-chain saturated fatty acidsmilk bacteriatransition milk

Information

Type
Research Article
Information
Journal of Dairy Research , First View , pp. 1 - 10
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of Hannah Dairy Research Foundation.

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Ayala, L, Gómez-Cortés, P, Hernández, F, Madrid, J, MartÍnez-Miró, S and Fuente, M A (2024) Comparison of the fatty acid profiles of sow and goat colostrum. Veterinary Sciences 11, 341.CrossRefGoogle ScholarPubMed
Bainbridge, ML, Cersosimo, LM, Wright, A-DG and Kraft, J (2016) Content and composition of branched-chain fatty acids in bovine milk are affected by lactation stage and breed of dairy cow. PLoS One 11, e0150386.CrossRefGoogle ScholarPubMed
Bokulich, NA, Kaehler, BD, Rideout, JR, Dillon, M, Bolyen, E, Knight, R, Huttley, GA and Gregory Caporaso, J (2018) Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin. Microbiome 6, 90.10.1186/s40168-018-0470-zCrossRefGoogle ScholarPubMed
Bolyen, E, Rideout, JR, Dillon, MR, Bokulich, NA, Abnet, CC, Al-Ghalith, GA, Alexander, H, Alm, EJ, Arumugam, M, Asnicar, F, Bai, Y, Bisanz, JE, Bittinger, K, Brejnrod, A, Brislawn, CJ, Brown, CT, Callahan, BJ, Caraballo-Rodríguez, AM, Chase, J, Cope, EK, Da Silva, R, Diener, C, Dorrestein, PC, Douglas, GM, Durall, DM, Duvallet, C, Edwardson, CF, Ernst, M, Estaki, M, Fouquier, J, Gauglitz, JM, Gibbons, SM, Gibson, DL, Gonzalez, A, Gorlick, K, Guo, J, Hillmann, B, Holmes, S, Holste, H, Huttenhower, C, Huttley, GA, Janssen, S, Jarmusch, AK, Jiang, L, Kaehler, BD, Kang, KB, Keefe, CR, Keim, P, Kelley, ST, Knights, D, Koester, I, Kosciolek, T, Kreps, J, Langille, MGI, Lee, J, Ley, R, Liu, YX, Loftfield, E, Lozupone, C, Maher, M, Marotz, C, Martin, BD, McDonald, D, McIver, LJ, Melnik, AV, Metcalf, JL, Morgan, SC, Morton, JT, Naimey, AT, Navas-Molina, JA, Nothias, LF, Orchanian, SB, Pearson, T, Peoples, SL, Petras, D, Preuss, ML, Pruesse, E, Rasmussen, LB, Rivers, A, Robeson, MS, Rosenthal, P, Segata, N, Shaffer, M, Shiffer, A, Sinha, R, Song, SJ, Spear, JR, Swafford, AD, Thompson, LR, Torres, PJ, Trinh, P, Tripathi, A, Turnbaugh, PJ, Ul-Hasan, S, van der Hooft, JJJ, Vargas, F, Vázquez-Baeza, Y, Vogtmann, E, von Hippel, M, Walters, W, Wan, Y, Wang, M, Warren, J, Weber, KC, Williamson, CHD, Willis, AD, Xu, ZZ, Zaneveld, JR, Zhang, Y, Zhu, Q, Knight, R and Caporaso, JG (2019) Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology 37, 852–857. doi:10.1038/s41587-019-0209-9CrossRefGoogle ScholarPubMed
Bonsaglia, ECR, Gomes, MS, Canisso, IF, Zhou, Z, Lima, SF, Rall, VLM Oikonomou, G, Bicalho, RC and Lima, FS (2017) Milk microbiome and bacterial load following dry cow therapy without antibiotics in dairy cows with healthy mammary gland. Scientific Reports 7, 8067.10.1038/s41598-017-08790-5CrossRefGoogle ScholarPubMed
Callahan, BJ, Mcmurdie, PJ, Rosen, MJ, Han, AW, Johnson, AJ and Holmes, SP (2016) DADA2: high-resolution sample inference from Illumina amplicon data. Nature Methods 13, 581–583.10.1038/nmeth.3869CrossRefGoogle ScholarPubMed
Claridge-Chang, A and Assam, PN (2016) Estimation statistics should replace significance testing. Nature Methods 13, 108–109.10.1038/nmeth.3729CrossRefGoogle ScholarPubMed
Crichton, N (2000) Information point: Mann-Whitney test. Journal of Clinical Nursing 9, 583.Google ScholarPubMed
D'amico, DJ and Donnelly, CW (2010) Microbiological quality of raw milk used for small-scale artisan cheese production in Vermont: effect of farm characteristics and practices. Journal of Dairy Science 93, 134–147.CrossRefGoogle ScholarPubMed
Davis, NM, Proctor, DM, Holmes, SP, Relman, DA and Callahan, BJ (2018) Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome 6, 226.10.1186/s40168-018-0605-2CrossRefGoogle ScholarPubMed
Douglas, GM, Maffei, VJ, Zaneveld, JR, Yurgel, SN, Brown, JR, Taylor, CM Huttenhower, C, Langille, MG (2020) PICRUSt2 for prediction of metagenome functions. Nature Biotechnology 38, 685–688.10.1038/s41587-020-0548-6CrossRefGoogle ScholarPubMed
Doyle, CJ, Gleeson, D, O'toole, PW and Cotter, PD (2016) Impacts of seasonal housing and teat preparation on raw milk microbiota: a high-throughput sequencing study. Applied and Environmental Microbiology 83, e02694–16.Google ScholarPubMed
Fan, R, Zhang, W, Zhao, X, Ji, Z, Du, Q, Han, R, Wang, J and Yang, Y (2023) Changes in milk fat globule physical properties and milk fatty acid composition throughout the lactation cycle of Laoshan goat. Journal of Animal Science 101, 1–9.CrossRefGoogle ScholarPubMed
Fecteau, G, Baillargeon, P, Higgins, R, Paré, J and Fortin, M (2002) Bacterial contamination of colostrum fed to newborn calves in Québec dairy herds. Canadian Veterinary Journal 43, 523–527.Google ScholarPubMed
Fischer-Tlustos, AJ, Hertogs, K, Van Niekerk, JK, Nagorske, M, Haines, DM and Steele, MA (2020) Oligosaccharide concentrations in colostrum, transition milk, and mature milk of primi- and multiparous Holstein cows during the first week of lactation. Journal of Dairy Science 103, 3683–3695.Google ScholarPubMed
Godden, SM, Lombard, JE and Woolums, AR (2019) Colostrum management for dairy calves. Veterinary Clinics of North America: Food Animal Practice 35, 535–556. doi:10.1016/j.cvfa.2019.07.005.Google ScholarPubMed
Gómez-Cortés, P and Juárez, M and De La Fuente, MA (2018) Milk fatty acids and potential health benefits: an updated vision. Trends in Food Science & Technology 81, 1–9.10.1016/j.tifs.2018.08.014CrossRefGoogle Scholar
Greenland, S, Senn, SJ, Rothman, KJ, Carlin, JB, Poole, C, Goodman, SN and Altman, DG (2016) Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations. European Journal of Epidemiology 31, 337–350. doi:10.1007/s10654-016-0149-3.CrossRefGoogle Scholar
Hu, M, Lu, X, Qin, S, Liu, R, Wang, Q, Lu, C and Li, W (2024) Research progress on the biosynthesis, activity and application of natural tetrapyrrole compounds. Arabian Journal of Chemistry 17, 105736.10.1016/j.arabjc.2024.105736CrossRefGoogle Scholar
Kaneda, T (1991) Iso- and anteiso-fatty acids in bacteria: biosynthesis, function, and taxonomic significance. Microbiological Reviews 55, 288–302.10.1128/mr.55.2.288-302.1991CrossRefGoogle ScholarPubMed
Legrand, P and Rioux, V (2015) Specific roles of saturated fatty acids: beyond epidemiological data. European Journal of Lipid Science and Technology 117, 1489–1499.10.1002/ejlt.201400514CrossRefGoogle Scholar
Liu, Q, Wang, C, Guo, G, Huo, WJ, Zhang, SL, Pei, CX, Zhang, YL, Wang, H (2018) Effects of branched-chain volatile fatty acids on lactation performance and mRNA expression of genes related to fatty acid synthesis in mammary gland of dairy cows. Animal 12, 2071–2079.CrossRefGoogle ScholarPubMed
Liu, S, Kulinich, A, Cai, ZP, Ma, HY, Du, YM, Lv, YM, Liu, L (2016) The fucosidase-pool of Emticicia oligotrophica: biochemical characterization and transfucosylation potential. Glycobiology 26, 871–879.CrossRefGoogle ScholarPubMed
Louis, P and Flint, HJ (2017) Formation of propionate and butyrate by the human colonic microbiota. Environmental Microbiology 19, 29–41.10.1111/1462-2920.13589CrossRefGoogle ScholarPubMed
Martín, R, Rios-Covian, D, Huillet, E, Auger, S, Khazaal, S, Bermúdez-Humarán, LG Sokol, H, Chatel, JM and Langella, P (2023) Faecalibacterium: a bacterial genus with promising human health applications. FEMS Microbiology Reviews 47(4), fuad039. 10.1093/femsre/fuad039.CrossRefGoogle ScholarPubMed
Meyrand, M, Dallas, DC, Caillat, H, Bouvier, F, Martin, P and Barile, D (2013) Comparison of milk oligosaccharides between goats with and without the genetic ability to synthesize α(s1)-casein. Small Ruminant Research 113, 411–420.10.1016/j.smallrumres.2013.03.014CrossRefGoogle ScholarPubMed
Niyazbekova, Z, Yao, XT, Liu, MJ, Bold, N, Tong, JZ, Chang, JJ Wen, Y, Li, L, Wang, Y, Chen, DK and Ma, WT (2020) Compositional and functional comparisons of the microbiota in the colostrum and mature milk of dairy goats. Animals (Basel) 10(11), 1955.10.3390/ani10111955CrossRefGoogle ScholarPubMed
Porcellato, D, Meisal, R, Bombelli, A and Narvhus, JA (2020) A core microbiota dominates a rich microbial diversity in the bovine udder and may indicate presence of dysbiosis. Scientific Reports 10, 21608.CrossRefGoogle ScholarPubMed
Quigley, L, O'sullivan, O, Stanton, C, Beresford, TP, Ross, RP, Fitzgerald, GF and Cotter, PD (2013) The complex microbiota of raw milk. FEMS Microbiology Reviews 37, 664–698. doi:10.1111/1574-6976.12030.CrossRefGoogle ScholarPubMed
R Core Team (2020) R: a Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. URL https://www.R-project.org/.Google Scholar
Racine, JS (2012) RSTUDIO: a platform-independent ide for R and sweave. Journal of Applied Econometrics 27, 167–172. doi:10.1002/jae.1278.CrossRefGoogle Scholar
Ran-Ressler R, R, Khailova, L, Arganbright, KM, Adkins-Rieck, CK, Jouni, ZE, Koren, O, Ley, RE, Brenna, JT, Dvorak, B (2011) Branched chain fatty acids reduce the incidence of necrotizing enterocolitis and alter gastrointestinal microbial ecology in a neonatal rat model. PLoS One 6, e29032.10.1371/journal.pone.0029032CrossRefGoogle Scholar
Ran-Ressler, RR, Bae, S, Lawrence, P, Wang, DH and Brenna, JT (2014) Branched-chain fatty acid content of foods and estimated intake in the USA. British Journal of Nutrition 112, 565–572.10.1017/S0007114514001081CrossRefGoogle ScholarPubMed
Roman-Garcia, Y (2019) Assessing Dietary Conditions Influencing the Requirements by Rumen Bacteria for Branched Chain Volatile Fatty Acids. PhD. Diss. Columbus: The Ohio State UniversityGoogle Scholar
Ruiz-Núñez, B, Dijck-Brouwer, DA and Muskiet, FA (2016) The relation of saturated fatty acids with low-grade inflammation and cardiovascular disease. Journal of Nutritional Biochemistry 36, 1–20.10.1016/j.jnutbio.2015.12.007CrossRefGoogle ScholarPubMed
Sánchez-Macías, D, Moreno-Indias, I, Castro, N Morales-Delanuez, A and Argüello, A (2014) From goat colostrum to milk: physical, chemical, and immune evolution from partum to 90 days postpartum. Journal of Dairy Science 97, 10–16.10.3168/jds.2013-6811CrossRefGoogle ScholarPubMed
Sharma, M, Khurana, H, Singh, DN and Negi, RK (2021) The genus Sphingopyxis: systematics, ecology, and bioremediation potential – A review. Journal of Environmental Management 280, 111744.CrossRefGoogle ScholarPubMed
Sturm-Richter, K, Golitsch, F, Sturm, G, Kipf, E, Dittrich, A, Beblawy, S, Kerzenmacher, SK, Gescher, J (2015) Unbalanced fermentation of glycerol in Escherichia coli via heterologous production of an electron transport chain and electrode interaction in microbial electrochemical cells. Bioresource Technology 186, 89–96.CrossRefGoogle ScholarPubMed
Takeuchi, M, Hamana, K and Hiraishi, A (2001) Proposal of the genus Sphingomonas sensu stricto and three new genera, Sphingobium, Novosphingobium and Sphingopyxis, on the basis of phylogenetic and chemotaxonomic analyses. International Journal of Systematic and Evolutionary Microbiology 51, 1405–1417.10.1099/00207713-51-4-1405CrossRefGoogle ScholarPubMed
Vlaeminck, B, Fievez, V, Cabrita, ARJ, Fonseca, AJM and Dewhurst, RJ (2006) Factors affecting odd- and branched-chain fatty acids in milk: a review. Animal Feed Science and Technology 131, 389–417.10.1016/j.anifeedsci.2006.06.017CrossRefGoogle Scholar
Wang, Y, Nan, X, Zhao, Y, Wang, H, Wang, M, Jiang, L, Zhang, F, Xue, F, Hua, D, Li, K and Liu, J (2020) Coupling 16S rDNA sequencing and untargeted mass spectrometry for milk microbial composition and metabolites from dairy cows with clinical and subclinical mastitis. Journal of Agricultural and Food Chemistry 68, 8496–8508.10.1021/acs.jafc.0c03738CrossRefGoogle ScholarPubMed
Wilcoxon, F (1992) Individual comparisons by ranking methods[C]//Kotz S. In Johnson, NL, Breakthroughs in Statistics: Methodology and Distribution. New York: NSpringer, pp. 196–202.10.1007/978-1-4612-4380-9_16CrossRefGoogle Scholar
Wilms, JN, Hare, KS, Fischer-Tlustos, AJ, Vahmani, P, Dugan, MER, Leal, LN, Steele, MA(2022) Fatty acid profile characterization in colostrum, transition milk, and mature milk of primi- and multiparous cows during the first week of lactation. Journal of Dairy Science 105(3): 2612–2630. doi:10.3168/jds.2021-20880CrossRefGoogle ScholarPubMed
Xin, H, Xu, Y, Chen, Y, Chen, G, Steele, MA and Guan, LL (2020) Short communication: odd-chain and branched-chain fatty acid concentrations in bovine colostrum and transition milk and their stability under heating and freezing treatments. Journal of Dairy Science 103, 11483–11489.10.3168/jds.2020-18994CrossRefGoogle ScholarPubMed
Young, W, Hine, BC, Wallace, OA, Callaghan, M and Bibiloni, R (2015) Transfer of intestinal bacterial components to mammary secretions in the cow. PeerJ 3, e888.10.7717/peerj.888CrossRefGoogle ScholarPubMed
Zeder, MA and Hesse, B (2000) The initial domestication of goats (Capra hircus) in the Zagros mountains 10,000 years ago. Science 287, 2254–2257.10.1126/science.287.5461.2254CrossRefGoogle ScholarPubMed
Zhang, F, Wang, Z, Lei, F, Wang, B, Jiang, S, Peng, Q Zhang, J, Shao, Y (2017) Bacterial diversity in goat milk from the Guanzhong area of China. Journal of Dairy Science 100, 7812–7824.10.3168/jds.2017-13244CrossRefGoogle ScholarPubMed
Zhang, R, Huo, W, Zhu, W and Mao, S (2015) Characterization of bacterial community of raw milk from dairy cows during subacute ruminal acidosis challenge by high-throughput sequencing. Journal of the Science of Food and Agriculture 95, 1072–1079.CrossRefGoogle ScholarPubMed