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Functional Adaptations of the Transcriptome to Mastitis-Causing Pathogens: The Mammary Gland and Beyond

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Abstract

Application of microarrays to the study of intramammary infections in recent years has provided a wealth of fundamental information on the transcriptomics adaptation of tissue/cells to the disease. Due to its heavy toll on productivity and health of the animal, in vivo and in vitro transcriptomics works involving different mastitis-causing pathogens have been conducted on the mammary gland, primarily on livestock species such as cow and sheep, with few studies in non-ruminants. However, the response to an infectious challenge originating in the mammary gland elicits systemic responses in the animal and encompasses tissues such as liver and immune cells in the circulation, with also potential effects on other tissues such as adipose. The susceptibility of the animal to develop mastitis likely is affected by factors beyond the mammary gland, e.g. negative energy balance as it occurs around parturition. Objectives of this review are to discuss the use of systems biology concepts for the holistic study of animal responses to intramammary infection; providing an update of recent work using transcriptomics to study mammary and peripheral tissue (i.e. liver) as well as neutrophils and macrophage responses to mastitis-causing pathogens; discuss the effect of negative energy balance on mastitis predisposition; and analyze the bovine and murine mammary innate-immune responses during lactation and involution using a novel functional analysis approach to uncover potential predisposing factors to mastitis throughout an animal’s productive life.

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Abbreviations

PMN:

polymorphonuclear leukocytes

IMI:

intramammary infection

ORA:

overrepresented approach

FDR:

false discovery rate

IPA:

ingenuity pathway analysis

DIA:

dynamic impact approach

E. coli :

Escherichia coli

APR:

acute-phase response

CXCL5 :

C-X-C motif chemokine 5

DEG:

differentially expressed genes

S. epidermis :

streptococcus epidermis

S. aureus :

staphylococcus aureus

IL6 :

interleukin 6

NFKB2 :

NF-Kappa-B p100 subunit

S. uberis :

streptococcus uberis

XBP1 :

X-box binding protein 1

SREBF1 :

sterol-regulatory element binding factor 1

PPAR:

peroxisome proliferator activated receptor

PAMP:

pathogen-associated molecular patterns

LPS:

lipopolysacharide

LTA:

lipoteichoic acid

NO:

nitric oxide

SCC:

somatic cell count

NET:

neutrophil extracellular traps

GCP2:

granulocyte chemotactic protein 2

C5a:

complement 5a

pi:

post-inoculation

NEFA:

non-esterified fatty acids

NEB:

negative energy balance

BHBA:

hydroxybutyric acid

MHC:

major histocompatibility complex

XDH :

xanthine dehydrogenase

SPP1 :

osteopontin

MUC1 :

mucin 1

SNP:

single nucleotide polymorphism

References

  1. Rinaldi M, Li RW, Capuco AV. Mastitis associated transcriptomic disruptions in cattle. Vet Immunol Immunopathol. 2010;138(4):267–79.

    PubMed  CAS  Google Scholar 

  2. Loor JJ, Cohick WS. ASAS centennial paper: lactation biology for the twenty-first century. J Anim Sci. 2009;87(2):813–24.

    PubMed  CAS  Google Scholar 

  3. Bruggeman FJ, Westerhoff HV. The nature of systems biology. Trends Microbiol. 2007;15(1):45–50.

    PubMed  CAS  Google Scholar 

  4. Cornish-Bowden A, Cardenas ML, Letelier JC, et al. Understanding the parts in terms of the whole. Biol Cell. 2004;96(9):713–7.

    PubMed  CAS  Google Scholar 

  5. Wheeler MB, Monaco E, Bionaz M, et al. The role of existing and emerging biotechnologies for livestock production: toward holism. Acta Scientiae Veterinariae. 2010;s463–s84.

  6. Greene CS, Troyanskaya OG. Integrative systems biology for data-driven knowledge discovery. Semin Nephrol. 2010;30(5):443–54.

    PubMed  Google Scholar 

  7. Feist AM, Palsson BO. The growing scope of applications of genome-scale metabolic reconstructions using Escherichia coli. Nat Biotechnol. 2008;26(6):659–67.

    PubMed  CAS  Google Scholar 

  8. Germain RN, Meier-Schellersheim M, Nita-Lazar A, et al. Systems biology in immunology: a computational modeling perspective. Annu Rev Immunol. 2011;29:527–85.

    PubMed  CAS  Google Scholar 

  9. Piantoni P, Bionaz M, Graugnard DE, et al. Functional and gene network analyses of transcriptional signatures characterizing pre-weaned bovine mammary parenchyma or fat pad uncovered novel inter-tissue signaling networks during development. BMC Genomics. 2010;11:331.

    PubMed  Google Scholar 

  10. da Huang W, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009;37(1):1–13.

    Google Scholar 

  11. Draghici S, Khatri P, Tarca AL, et al. A systems biology approach for pathway level analysis. Genome Res. 2007;17(10):1537–45.

    PubMed  CAS  Google Scholar 

  12. Bionaz M, Periasamy K, Rodriguez-Zas S, et al. The bovine mammary transcriptome: a novel dynamics impact approach to uncover functional adaptations of the mammary gland during the lactation cycle. PLoS One. 2011 (Submitted).

  13. da Huang W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44–57.

    CAS  Google Scholar 

  14. Buitenhuis B, Rontved CM, Edwards SM, et al. In depth analysis of genes and pathways of the mammary gland involved in the pathogenesis of bovine Escherichia coli-mastitis. BMC Genomics. 2011;12:130.

    PubMed  CAS  Google Scholar 

  15. Rinaldi M, Li RW, Bannerman DD, et al. A sentinel function for teat tissues in dairy cows: dominant innate immune response elements define early response to E. coli mastitis. Funct Integr Genomics. 2010;10(1):21–38.

    PubMed  CAS  Google Scholar 

  16. Mitterhuemer S, Petzl W, Krebs S, et al. Escherichia coli infection induces distinct local and systemic transcriptome responses in the mammary gland. BMC Genomics. 2010;11:138.

    PubMed  Google Scholar 

  17. Bonnefont CM, Toufeer M, Caubet C, et al. Transcriptomic analysis of milk somatic cells in mastitis resistant and susceptible sheep upon challenge with Staphylococcus epidermidis and Staphylococcus aureus. BMC Genomics. 2011;12:208.

    PubMed  CAS  Google Scholar 

  18. Brand B, Hartmann A, Repsilber D, et al. Comparative expression profiling of E. coli and S. aureus inoculated primary mammary gland cells sampled from cows with different genetic predispositions for somatic cell score. Genet Sel Evol. 2011;43(1):24.

    PubMed  Google Scholar 

  19. Vorbach C, Capecchi MR, Penninger JM. Evolution of the mammary gland from the innate immune system? Bioessays. 2006;28(6):606–16.

    PubMed  CAS  Google Scholar 

  20. Genini S, Badaoui B, Sclep G, et al. Strengthening insights into host responses to mastitis infection in ruminants by combining heterogeneous microarray data sources. BMC Genomics. 2011;12(1):225.

    PubMed  Google Scholar 

  21. Fierro AC, Vandenbussche F, Engelen K, et al. Meta analysis of gene expression data within and across species. Curr Genomics. 2008;9(8):525–34.

    PubMed  CAS  Google Scholar 

  22. Huang Q, Liu D, Majewski P, et al. The plasticity of dendritic cell responses to pathogens and their components. Science. 2001;294(5543):870–5.

    PubMed  CAS  Google Scholar 

  23. Nau GJ, Richmond JF, Schlesinger A, et al. Human macrophage activation programs induced by bacterial pathogens. Proc Natl Acad Sci USA. 2002;99(3):1503–8.

    PubMed  CAS  Google Scholar 

  24. Moyes KM, Drackley JK, Morin DE, et al. Mammary gene expression profiles during an intramammary challenge reveal potential mechanisms linking negative energy balance with impaired immune response. Physiol Genomics. 2010.

  25. Moyes KM, Drackley JK, Morin DE, et al. Gene network and pathway analysis of bovine mammary tissue challenged with Streptococcus uberis reveals induction of cell proliferation and inhibition of PPARgamma signaling as potential mechanism for the negative relationships between immune response and lipid metabolism. BMC Genomics. 2009;10:542.

    PubMed  Google Scholar 

  26. Petzl W, Zerbe H, Gunther J, et al. Escherichia coli, but not Staphylococcus aureus triggers an early increased expression of factors contributing to the innate immune defense in the udder of the cow. Vet Res. 2008;39(2):18.

    PubMed  Google Scholar 

  27. Burvenich C, Van Merris V, Mehrzad J, et al. Severity of E. coli mastitis is mainly determined by cow factors. Vet Res. 2003;34(5):521–64.

    PubMed  Google Scholar 

  28. Kanneganti TD, Lamkanfi M, Nunez G. Intracellular NOD-like receptors in host defense and disease. Immunity. 2007;27(4):549–59.

    PubMed  CAS  Google Scholar 

  29. Rainard P, Riollet C. Innate immunity of the bovine mammary gland. Vet Res. 2006;37(3):369–400.

    PubMed  CAS  Google Scholar 

  30. Lee JY, Hwang DH. The modulation of inflammatory gene expression by lipids: mediation through toll-like receptors. Mol Cells. 2006;21(2):174–85.

    PubMed  CAS  Google Scholar 

  31. Taraktsoglou M, Szalabska U, Magee DA, et al. Transcriptional profiling of immune genes in bovine monocyte-derived macrophages exposed to bacterial antigens. Vet Immunol Immunopathol. 2011;140(1–2):130–9.

    PubMed  CAS  Google Scholar 

  32. Wright SD, Ramos RA, Tobias PS, et al. CD14, a receptor for complexes of lipopolysaccharide (LPS) and LPS binding protein. Science. 1990;249(4975):1431–3.

    PubMed  CAS  Google Scholar 

  33. Aderem A, Ulevitch RJ. Toll-like receptors in the induction of the innate immune response. Nature. 2000;406(6797):782–7.

    PubMed  CAS  Google Scholar 

  34. Henneke P, Morath S, Uematsu S, et al. Role of lipoteichoic acid in the phagocyte response to group B streptococcus. J Immunol. 2005;174(10):6449–55.

    PubMed  CAS  Google Scholar 

  35. Schroder NW, Morath S, Alexander C, et al. Lipoteichoic acid (LTA) of Streptococcus pneumoniae and Staphylococcus aureus activates immune cells via Toll-like receptor (TLR)-2, lipopolysaccharide-binding protein (LBP), and CD14, whereas TLR-4 and MD-2 are not involved. J Biol Chem. 2003;278(18):15587–94.

    PubMed  Google Scholar 

  36. Franchini M, Schweizer M, Matzener P, et al. Evidence for dissociation of TLR mRNA expression and TLR agonist-mediated functions in bovine macrophages. Vet Immunol Immunopathol. 2006;110(1–2):37–49.

    PubMed  CAS  Google Scholar 

  37. Paape MJ, Bannerman DD, Zhao X, et al. The bovine neutrophil: structure and function in blood and milk. Vet Res. 2003;34(5):597–627.

    PubMed  CAS  Google Scholar 

  38. Medina E. Neutrophil extracellular traps: a strategic tactic to defeat pathogens with potential consequences for the host. J Innate Immun. 2009;1(3):176–80.

    PubMed  Google Scholar 

  39. Brinkmann V, Reichard U, Goosmann C, et al. Neutrophil extracellular traps kill bacteria. Science. 2004;303(5663):1532–5.

    PubMed  CAS  Google Scholar 

  40. Yu C, Shi ZR, Chu CY, et al. Expression of bovine granulocyte chemotactic protein-2 (GCP-2) in neutrophils and a mammary epithelial cell line (MAC-T) in response to various bacterial cell wall components. Vet J. 2010;186(1):89–95.

    PubMed  CAS  Google Scholar 

  41. Stevens MG, Peelman LJ, De Spiegeleer B, et al. Differential gene expression of the toll-like receptor-4 cascade and neutrophil function in early- and mid-lactating dairy cows. J Dairy Sci. 2011;94(3):1277–88.

    PubMed  CAS  Google Scholar 

  42. Guo RF, Riedemann NC, Ward PA. Role of C5a-C5aR interaction in sepsis. Shock. 2004;21(1):1–7.

    PubMed  Google Scholar 

  43. Stevens MG, Van Poucke M, Peelman LJ, et al. Anaphylatoxin C5a-induced toll-like receptor 4 signaling in bovine neutrophils. J Dairy Sci. 2011;94(1):152–64.

    PubMed  CAS  Google Scholar 

  44. Worku M, Morris A. Binding of different forms of lipopolysaccharide and gene expression in bovine blood neutrophils. J Dairy Sci. 2009;92(7):3185–93.

    PubMed  CAS  Google Scholar 

  45. Sohn EJ, Paape MJ, Connor EE, et al. Bacterial lipopolysaccharide stimulates bovine neutrophil production of TNF-alpha, IL-1beta, IL-12 and IFN-gamma. Vet Res. 2007;38(6):809–18.

    PubMed  CAS  Google Scholar 

  46. Yang W, Zerbe H, Petzl W, et al. Bovine TLR2 and TLR4 properly transduce signals from Staphylococcus aureus and E. coli, but S. aureus fails to both activate NF-kappaB in mammary epithelial cells and to quickly induce TNFalpha and interleukin-8 (CXCL8) expression in the udder. Mol Immunol. 2008;45(5):1385–97.

    PubMed  CAS  Google Scholar 

  47. Hattar K, Grandel U, Moeller A, et al. Lipoteichoic acid (LTA) from Staphylococcus aureus stimulates human neutrophil cytokine release by a CD14-dependent, Toll-like-receptor-independent mechanism: Autocrine role of tumor necrosis factor-[alpha] in mediating LTA-induced interleukin-8 generation. Crit Care Med. 2006;34(3):835–41.

    PubMed  CAS  Google Scholar 

  48. Riollet C, Rainard P, Poutrel B. Cell subpopulations and cytokine expression in cow milk in response to chronic Staphylococcus aureus infection. J Dairy Sci. 2001;84(5):1077–84.

    PubMed  CAS  Google Scholar 

  49. Arditi M, Zhou J, Dorio R, et al. Endotoxin-mediated endothelial cell injury and activation: role of soluble CD14. Infect Immun. 1993;61(8):3149–56.

    PubMed  CAS  Google Scholar 

  50. Van Oostveldt K, Paape MJ, Dosogne H, et al. Effect of apoptosis on phagocytosis, respiratory burst and CD18 adhesion receptor expression of bovine neutrophils. Domest Anim Endocrinol. 2002;22(1):37–50.

    PubMed  Google Scholar 

  51. Hoeben D, Burvenich C, Trevisi E, et al. Role of endotoxin and TNF-alpha in the pathogenesis of experimentally induced coliform mastitis in periparturient cows. J Dairy Res. 2000;67(4):503–14.

    PubMed  CAS  Google Scholar 

  52. Wenz JR, Barrington GM, Garry FB, et al. Bacteremia associated with naturally occuring acute coliform mastitis in dairy cows. J Am Vet Med Assoc. 2001;219(7):976–81.

    PubMed  CAS  Google Scholar 

  53. Fleck A. Clinical and nutritional aspects of changes in acute-phase proteins during inflammation. Proc Nutr Soc. 1989;48(3):347–54.

    PubMed  CAS  Google Scholar 

  54. Vels L, Rontved CM, Bjerring M, et al. Cytokine and acute phase protein gene expression in repeated liver biopsies of dairy cows with a lipopolysaccharide-induced mastitis. J Dairy Sci. 2009;92(3):922–34.

    PubMed  CAS  Google Scholar 

  55. Jiang L, Sorensen P, Rontved C, et al. Gene expression profiling of liver from dairy cows treated intra-mammary with lipopolysaccharide. BMC Genomics. 2008;9:443.

    PubMed  Google Scholar 

  56. Bruzzone P, Siegel JH, Chiarla C, et al. Leucine dose response in the reduction of urea production from septic proteolysis and in the stimulation of acute-phase proteins. Surgery. 1991;109(6):768–78.

    PubMed  CAS  Google Scholar 

  57. Bertoni G, Trevisi E, Han X, et al. Effects of inflammatory conditions on liver activity in puerperium period and consequences for performance in dairy cows. J Dairy Sci. 2008;91(9):3300–10.

    PubMed  CAS  Google Scholar 

  58. Bionaz M, Trevisi E, Calamari L, et al. Plasma paraoxonase, health, inflammatory conditions, and liver function in transition dairy cows. J Dairy Sci. 2007;90(4):1740–50.

    PubMed  CAS  Google Scholar 

  59. Drackley JK. ADSA Foundation Scholar Award. Biology of dairy cows during the transition period: the final frontier? J Dairy Sci. 1999;82(11):2259–73.

    PubMed  CAS  Google Scholar 

  60. Reynolds CK, Harmon DL, Cecava MJ. Absorption and delivery of nutrients for milk protein synthesis by portal-drained viscera. J Dairy Sci. 1994;77(9):2787–808.

    PubMed  CAS  Google Scholar 

  61. Drackley JK, Dann HM, Douglas GN, et al. Physiological and pathological adaptations in dairy cows that may increase susceptibility to periparturient diseases and disorders. Ital J Anim Sci. 2005;4(4):323–44.

    Google Scholar 

  62. Desruisseaux MS, Nagajyothi F, Trujillo ME, et al. Adipocyte, adipose tissue, and infectious disease. Infect Immun. 2007;75(3):1066–78.

    PubMed  CAS  Google Scholar 

  63. Weisberg SP, McCann D, Desai M, et al. Obesity is associated with macrophage accumulation in adipose tissue. J Clin Invest. 2003;112(12):1796–808.

    PubMed  CAS  Google Scholar 

  64. Maeda N, Shimomura I, Kishida K, et al. Diet-induced insulin resistance in mice lacking adiponectin/ACRP30. Nat Med. 2002;8(7):731–7.

    PubMed  CAS  Google Scholar 

  65. Mukesh M, Bionaz M, Graugnard DE, et al. Adipose tissue depots of Holstein cows are immune responsive: inflammatory gene expression in vitro. Domest Anim Endocrinol. 2010;38(3):168–78.

    PubMed  CAS  Google Scholar 

  66. Khovidhunkit W, Kim MS, Memon RA, et al. Effects of infection and inflammation on lipid and lipoprotein metabolism: mechanisms and consequences to the host. J Lipid Res. 2004;45(7):1169–96.

    PubMed  CAS  Google Scholar 

  67. Janovick NA, Boisclair YR, Drackley JK. Prepartum dietary energy intake affects metabolism and health during the periparturient period in primiparous and multiparous Holstein cows. J Dairy Sci. 2011;94(3):1385–400.

    PubMed  CAS  Google Scholar 

  68. Barkema HW, Schukken YH, Lam TJ, et al. Incidence of clinical mastitis in dairy herds grouped in three categories by bulk milk somatic cell counts. J Dairy Sci. 1998;81(2):411–9.

    PubMed  CAS  Google Scholar 

  69. Sordillo LM, Contreras GA, Aitken SL. Metabolic factors affecting the inflammatory response of periparturient dairy cows. Anim Health Res Rev. 2009;10(1):53–63.

    PubMed  Google Scholar 

  70. Ingvartsen KL, Moyes KM. Nutrition, immune function and health of herbivores. Advances in Animal Bioscience 2011(In Press).

  71. Moyes KM, Drackley JK, Morin DE, et al. Predisposition of cows to mastitis in non-infected mammary glands: effects of dietary-induced negative energy balance during mid-lactation on immune-related genes. Funct Integr Genomics. 2011;11(1):151–6.

    PubMed  CAS  Google Scholar 

  72. Moyes KM, Drackley JK, Morin DE, et al. Greater expression of TLR2, TLR4, and IL6 due to negative energy balance is associated with lower expression of HLA-DRA and HLA-A in bovine blood neutrophils after intramammary mastitis challenge with Streptococcus uberis. Funct Integr Genomics. 2010;10(1):53–61.

    PubMed  CAS  Google Scholar 

  73. Loor JJ, Everts RE, Bionaz M, et al. Nutrition-induced ketosis alters metabolic and signaling gene networks in liver of periparturient dairy cows. Physiol Genomics. 2007;32(1):105–16.

    PubMed  CAS  Google Scholar 

  74. McCarthy SD, Waters SM, Kenny DA, et al. Negative energy balance and hepatic gene expression patterns in high-yielding dairy cows during the early postpartum period: a global approach. Physiol Genomics. 2010;42A(3):188–99.

    PubMed  CAS  Google Scholar 

  75. Wathes DC, Cheng Z, Chowdhury W, et al. Negative energy balance alters global gene expression and immune responses in the uterus of postpartum dairy cows. Physiol Genomics. 2009;39(1):1–13.

    PubMed  CAS  Google Scholar 

  76. Morris DG, Waters SM, McCarthy SD, et al. Pleiotropic effects of negative energy balance in the postpartum dairy cow on splenic gene expression: repercussions for innate and adaptive immunity. Physiol Genomics. 2009;39(1):28–37.

    PubMed  CAS  Google Scholar 

  77. Kimbrell DA, Beutler B. The evolution and genetics of innate immunity. Nat Rev Genet. 2001;2(4):256–67.

    PubMed  CAS  Google Scholar 

  78. Pensa S, Watson CJ, Poli V. Stat3 and the inflammation/acute phase response in involution and breast cancer. J Mammary Gland Biol Neoplasia. 2009;14(2):121–9.

    PubMed  Google Scholar 

  79. Piantoni P, Wang P, Drackley JK, et al. Expression of metabolic, tissue remodeling, oxidative stress, and inflammatory pathways in mammary tissue during involution in lactating dairy cows. Bioinform Biol Insights. 2010;4:85–97.

    PubMed  CAS  Google Scholar 

  80. Nickerson SC. Immunological aspects of mammary involution. J Dairy Sci. 1989;72(6):1665–78.

    PubMed  CAS  Google Scholar 

  81. Reed JR, Schwertfeger KL. Immune cell location and function during post-natal mammary gland development. J Mammary Gland Biol Neoplasia. 2010;15(3):329–39.

    PubMed  Google Scholar 

  82. Griesbeck-Zilch B, Osman M, Kuhn C, et al. Analysis of key molecules of the innate immune system in mammary epithelial cells isolated from marker-assisted and conventionally selected cattle. J Dairy Sci. 2009;92(9):4621–33.

    PubMed  CAS  Google Scholar 

  83. Rupp R, Boichard D. Genetics of resistance to mastitis in dairy cattle. Vet Res. 2003;34(5):671–88.

    PubMed  Google Scholar 

  84. Bionaz M, Rodriguez-Zas SL, Everts RE, et al. MammOmics (TM): transcript profiling of the mammary gland during the lactation cycle in Holstein cows. J Dairy Sci. 2007;90:207–8.

    Google Scholar 

  85. Piantoni P, Hurley WL, Rodriguez-Zas SL, et al. Defining gene networks during involution of the mammary gland in dairy cows. J Dairy Sci. 2008;91(E-Suppl 1):819.

    Google Scholar 

  86. Rudolph MC, McManaman JL, Phang T, et al. Metabolic regulation in the lactating mammary gland: a lipid synthesizing machine. Physiol Genomics. 2007;28(3):323–36.

    PubMed  CAS  Google Scholar 

  87. Bionaz M, Loor JJ. Comparative MammOmics™ of milk fat synthesis in Mus musculus vs. Bos taurus. J Dairy Sci. 2008;91 Suppl 1:566–7.

    Google Scholar 

  88. Notebaert S, Meyer E. Mouse models to study the pathogenesis and control of bovine mastitis. A review Vet Q. 2006;28(1):2–13.

    CAS  Google Scholar 

  89. Brouillette E, Malouin F. The pathogenesis and control of Staphylococcus aureus-induced mastitis: study models in the mouse. Microbes Infect. 2005;7(3):560–8.

    PubMed  Google Scholar 

  90. Rudolph MC, McManaman JL, Hunter L, et al. Functional development of the mammary gland: use of expression profiling and trajectory clustering to reveal changes in gene expression during pregnancy, lactation, and involution. J Mammary Gland Biol Neoplasia. 2003;8(3):287–307.

    PubMed  Google Scholar 

  91. Zheng J, Watson AD, Kerr DE. Genome-wide expression analysis of lipopolysaccharide-induced mastitis in a mouse model. Infect Immun. 2006;74(3):1907–15.

    PubMed  CAS  Google Scholar 

  92. Goudswaard J, Bakker-de Koff EC, van Ravenswaaij-Kraan HP. Lysozyme and its presence in bovine milk and serum. Tijdschr Diergeneeskd. 1978;103(8):445–50.

    PubMed  CAS  Google Scholar 

  93. Ziegler-Heitbrock HW, Ulevitch RJ. CD14: cell surface receptor and differentiation marker. Immunol Today. 1993;14(3):121–5.

    PubMed  CAS  Google Scholar 

  94. Atabai K, Sheppard D, Werb Z. Roles of the innate immune system in mammary gland remodeling during involution. J Mammary Gland Biol Neoplasia. 2007;12(1):37–45.

    PubMed  Google Scholar 

  95. Oviedo-Boyso J, Valdez-Alarcon JJ, Cajero-Juarez M, et al. Innate immune response of bovine mammary gland to pathogenic bacteria responsible for mastitis. J Infect. 2007;54(4):399–409.

    PubMed  Google Scholar 

  96. Paulsson KM. Evolutionary and functional perspectives of the major histocompatibility complex class I antigen-processing machinery. Cell Mol Life Sci. 2004;61(19–20):2446–60.

    PubMed  CAS  Google Scholar 

  97. Fitzpatrick JL, Cripps PJ, Hill AW, et al. MHC class II expression in the bovine mammary gland. Vet Immunol Immunopathol. 1992;32(1–2):13–23.

    PubMed  CAS  Google Scholar 

  98. Mejdell CM, Lie O, Solbu H, et al. Association of major histocompatibility complex antigens (BoLA-A) with AI bull progeny test results for mastitis, ketosis and fertility in Norwegian cattle. Anim Genet. 1994;25(2):99–104.

    PubMed  CAS  Google Scholar 

  99. Sharif S, Mallard BA, Wilkie BN, et al. Associations of the bovine major histocompatibility complex DRB3 (BoLA-DRB3) alleles with occurrence of disease and milk somatic cell score in Canadian dairy cattle. Anim Genet. 1998;29(3):185–93.

    PubMed  CAS  Google Scholar 

  100. Sharif S, Mallard BA, Wilkie BN. Characterization of naturally processed and presented peptides associated with bovine major histocompatibility complex (BoLA) class II DR molecules. Anim Genet. 2003;34(2):116–23.

    PubMed  CAS  Google Scholar 

  101. Takeshima S, Matsumoto Y, Chen J, et al. Evidence for cattle major histocompatibility complex (BoLA) class II DQA1 gene heterozygote advantage against clinical mastitis caused by Streptococci and Escherichia species. Tissue Antigens. 2008;72(6):525–31.

    PubMed  CAS  Google Scholar 

  102. Park YH, Joo YS, Park JY, et al. Characterization of lymphocyte subpopulations and major histocompatibility complex haplotypes of mastitis-resistant and susceptible cows. J Vet Sci. 2004;5(1):29–39.

    PubMed  Google Scholar 

  103. Fitzpatrick JL, Mayer SJ, Vilela C, et al. Cytokine-induced major histocompatibility complex class II antigens on cultured bovine mammary gland epithelial cells. J Dairy Sci. 1994;77(10):2940–8.

    PubMed  CAS  Google Scholar 

  104. Hackmann TJ, Spain JN. Invited review: ruminant ecology and evolution: perspectives useful to ruminant livestock research and production. J Dairy Sci. 2010;93(4):1320–34.

    PubMed  CAS  Google Scholar 

  105. Mepham TB. Physiology of lactation. Milton Keynes; Philadelphia: Open University Press; 1987.

    Google Scholar 

  106. McVey Jr WR, Williams GL. Mechanical masking of neurosensory pathways at the calf-teat interface: endocrine, reproductive and lactational features of the suckled anestrous cow. Theriogenology. 1991;35(5):931–41.

    PubMed  Google Scholar 

  107. Zwald NR, Weigel KA, Chang YM, et al. Genetic evaluation of dairy sires for milking duration using electronically recorded milking times of their daughters. J Dairy Sci. 2005;88(3):1192–8.

    PubMed  CAS  Google Scholar 

  108. Rauw WM, Kanis E, Noordhuizen-Stassen EN, et al. Undesirable side effects of selection for high production efficiency in farm animals: a review. Livest Prod Sci. 1998;56(1):15–33.

    Google Scholar 

  109. Nielsen CB, Cantor M, Dubchak I, et al. Visualizing genomes: techniques and challenges. Nat Methods. 2010;7(3 Suppl):S5–S15.

    PubMed  CAS  Google Scholar 

  110. O’Donoghue SI, Gavin AC, Gehlenborg N, et al. Visualizing biological data-now and in the future. Nat Methods. 2010;7(3 Suppl):S2–4.

    PubMed  Google Scholar 

  111. Hettinga K, van Valenberg H, de Vries S, et al. The host defense proteome of human and bovine milk. PLoS One. 2011;6(4):e19433.

    PubMed  CAS  Google Scholar 

  112. Lemay DG, Neville MC, Rudolph MC, et al. Gene regulatory networks in lactation: identification of global principles using bioinformatics. BMC Syst Biol. 2007;1:56.

    PubMed  Google Scholar 

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Authors and Affiliations

  1. Mammalian NutriPhysioGenomics, Department of Animal Sciences and Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA

    Juan J. Loor

  2. Department of Animal Science, Faculty of Agricultural Sciences, Aarhus University, Tjele, Denmark

    Kasey M. Moyes

  3. Institute of Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA

    Massimo Bionaz

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  1. Juan J. Loor
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  2. Kasey M. Moyes
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  3. Massimo Bionaz
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Correspondence to Juan J. Loor.

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Loor, J.J., Moyes, K.M. & Bionaz, M. Functional Adaptations of the Transcriptome to Mastitis-Causing Pathogens: The Mammary Gland and Beyond. J Mammary Gland Biol Neoplasia 16, 305–322 (2011). https://doi.org/10.1007/s10911-011-9232-2

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  • DOI: https://doi.org/10.1007/s10911-011-9232-2

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