Literature DB >> 23040012

Distinct composition of bovine milk from Jersey and Holstein-Friesian cows with good, poor, or noncoagulation properties as reflected in protein genetic variants and isoforms.

H B Jensen1, N A Poulsen, K K Andersen, M Hammershøj, H D Poulsen, L B Larsen.   

Abstract

The objective of this study was to examine variation in overall milk, protein, and mineral composition of bovine milk in relation to rennet-induced coagulation, with the aim of elucidating the underlying causes of milk with impaired coagulation abilities. On the basis of an initial screening of 892 milk samples from 42 herds with Danish Jersey and Holstein-Friesian cows, a subset of 102 samples was selected to represent milk with good, poor, or noncoagulating properties (i.e., samples that within each breed represented the most extremes in regard to coagulation properties). Milk with good coagulation characteristics was defined as milk forming a strong coagulum based on oscillatory rheology, as indicated by high values for maximum coagulum strength (G'(max)) and curd firming rate (CFR) and a short rennet coagulation time. Poorly coagulating milk formed a weak coagulum, with a low G'(max) and CFR and a long rennet coagulation time. Noncoagulating milk was defined as milk that failed to form a coagulum, having G'(max) and CFR values of zero at measurements taken within 1h after addition of rennet. For both breeds, a lower content of total protein, total casein (CN) and κ-CN, and lower levels of minerals (Ca, P, Mg) were identified in poorly coagulating and noncoagulating milk in comparison with milk with good coagulation properties. Liquid chromatography/electrospray ionization-mass spectrometry revealed the presence of a great variety of genetic variants of the major milk proteins, namely, α(S1)-CN (variants B and C), α(S2)-CN (A), β-CN (A(1), A(2), B, I, and F), κ-CN (A, B, and E), α-lactalbumin (B), and β-lactoglobulin (A, B, and C). In poorly coagulating and noncoagulating milk samples of both breeds, the predominant composite genotype of α(S1)-, β-, and κ-CN was BB-A(2)A(2)-AA, which confirmed a genetic contribution to impaired milk coagulation. Interestingly, subtle variations in posttranslational modification of CN were observed between the coagulation classes in both breeds. Poorly coagulating and noncoagulating milk contained a lower fraction of the least phosphorylated α(S1)-CN form, α(S1)-CN 8P, relative to total α(S1)-CN, along with a lower fraction of glycosylated κ-CN relative to total κ-CN. Thus, apparent variation was observed in the milk and protein composition, in the genetic makeup of the major milk proteins, and in the posttranslational modification level of CN between milk samples with either good or impaired coagulation ability, whereas the composition of poorly coagulating and noncoagulating milk was similar.
Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 23040012     DOI: 10.3168/jds.2012-5675

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  12 in total

1.  Estimation of genetic parameters and detection of quantitative trait loci for minerals in Danish Holstein and Danish Jersey milk.

Authors:  Bart Buitenhuis; Nina A Poulsen; Lotte B Larsen; Jakob Sehested
Journal:  BMC Genet       Date:  2015-05-21       Impact factor: 2.797

Review 2.  Animal board invited review: advances in proteomics for animal and food sciences.

Authors:  A M Almeida; A Bassols; E Bendixen; M Bhide; F Ceciliani; S Cristobal; P D Eckersall; K Hollung; F Lisacek; G Mazzucchelli; M McLaughlin; I Miller; J E Nally; J Plowman; J Renaut; P Rodrigues; P Roncada; J Staric; R Turk
Journal:  Animal       Date:  2014-10-31       Impact factor: 3.240

3.  Quantitation and Identification of Intact Major Milk Proteins for High-Throughput LC-ESI-Q-TOF MS Analyses.

Authors:  Delphine Vincent; Aaron Elkins; Mark R Condina; Vilnis Ezernieks; Simone Rochfort
Journal:  PLoS One       Date:  2016-10-17       Impact factor: 3.240

4.  Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits.

Authors:  Grum Gebreyesus; Mogens S Lund; Bart Buitenhuis; Henk Bovenhuis; Nina A Poulsen; Luc G Janss
Journal:  Genet Sel Evol       Date:  2017-12-05       Impact factor: 4.297

5.  Effect of Antioxidant Supplementation on Milk Yield and Quality in Italian Mediterranean Lactating Buffaloes.

Authors:  Chiara Evangelista; Umberto Bernabucci; Loredana Basiricò
Journal:  Animals (Basel)       Date:  2022-07-26       Impact factor: 3.231

6.  Identification of QTL on Chromosome 18 Associated with Non-Coagulating Milk in Swedish Red Cows.

Authors:  Sandrine I Duchemin; Maria Glantz; Dirk-Jan de Koning; Marie Paulsson; Willem F Fikse
Journal:  Front Genet       Date:  2016-04-15       Impact factor: 4.599

7.  Milk Bottom-Up Proteomics: Method Optimization.

Authors:  Delphine Vincent; Vilnis Ezernieks; Aaron Elkins; Nga Nguyen; Peter J Moate; Benjamin G Cocks; Simone Rochfort
Journal:  Front Genet       Date:  2016-01-11       Impact factor: 4.599

8.  Long-Term Oral Administration of LLHK, LHK, and HK Alters Gene Expression Profile and Restores Age-Dependent Atrophy and Dysfunction of Rat Salivary Glands.

Authors:  Yasuko Ishikawa; Tomasz D Pieczonka; Aneta M Bragiel-Pieczonka; Harumichi Seta; Tadahiro Ohkuri; Yumi Sasanuma; Yuji Nonaka
Journal:  Biomedicines       Date:  2020-02-20

9.  Ingestion of Gouda Cheese Ameliorates the Chronic Unpredictable Mild Stress in Mice.

Authors:  Bohyun Yun; Ja Yeon Yoo; Mi Ri Park; Sangdon Ryu; Woong Ji Lee; Hye Jin Choi; Min Kyoung Kang; Younghoon Kim; Sangnam Oh
Journal:  Food Sci Anim Resour       Date:  2020-01-01

10.  The effect of seasonal thermal stress on milk production and milk compositions of Korean Holstein and Jersey cows.

Authors:  Dong-Hyun Lim; Vijayakumar Mayakrishnan; Kwang-Seok Ki; Younghoon Kim; Tae-Il Kim
Journal:  Anim Biosci       Date:  2020-05-12
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