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Within-herd prevalence of intramammary infection caused by Mycoplasma bovis and associations between cow udder health, milk yield, and composition

Open AccessPublished:June 07, 2017DOI:https://doi.org/10.3168/jds.2016-12267

      ABSTRACT

      Subclinical mastitis is one of the major health problems in dairy herds due to decreased milk production and reduced milk quality. The aim of this study was to examine the within-herd prevalence of subclinical intramammary infection caused by Mycoplasma bovis and to evaluate associations between M. bovis and cow daily milk yield, udder health, and milk composition. Individual cow composite milk samples (n = 522) were collected from all lactating dairy cows in 1 Estonian dairy farm in November 2014. Daily milk yield, days in milk, and parity were recorded. Collected milk samples were analyzed for somatic cell count, milk protein, fat, and urea content. The presence of M. bovis, Staphylococcus aureus, Streptococcus agalactiae, and Streptococcus uberis in the milk samples was confirmed by quantitative PCR analysis. The within-herd prevalence of M. bovis was 17.2% in the study herd. No association was observed between days in milk and parity to the presence of M. bovis in milk. According to linear regression analysis, the daily milk yield from cows positive for M. bovis was on average 3.0 kg lower compared with cows negative for M. bovis. In addition, the presence of M. bovis in milk samples was significantly associated with higher somatic cell count and lower fat and urea content compared with milk samples negative for M. bovis. In conclusion, subclinical M. bovis intramammary infection is associated with decreased milk yield and lower milk quality.

      Key words

      INTRODUCTION

      Mastitis, which can be caused by different udder pathogens, is one of the major concerns in dairy herds because it causes economic losses to the industry due to lower milk production and reduced milk quality (
      • Ruegg P.L.
      New perspectives in udder health management.
      ;
      • Hertl J.A.
      • Schukken Y.H.
      • Welcome F.L.
      • Tauer L.W.
      • Gröhn Y.T.
      Pathogen-specific effects in milk yield in repeated clinical mastitis episodes in Holstein dairy cows.
      ). In addition, milk fat and protein concentration have been shown to decrease due to lipolysis and proteolysis in mastitic milk (
      • Larsen L.B.
      • Hinz K.
      • Jørgensen A.L.W.
      • Møller H.S.
      • Wellnitz O.
      • Bruckmaier R.M.
      • Kelly A.L.
      Proteomic and peptidomic study of proteolysis in quarter milk after infusion with lipoteichoic acid from Staphylococcus aureus.
      ;
      • Vidanarachchi J.K.
      • Li S.
      • Lundh Å.S.
      • Johansson M.
      Short communication: Lipolytic activity on milk fat by Staphylococcus aureus and Streptococcus agalactiae strains commonly isolated in Swedish dairy herds.
      ;
      • Zhang L.
      • Boeren S.
      • van Hooijdonk A.C.
      • Vervoort J.M.
      • Hettinga K.A.
      A proteomic perspective on the changes in milk proteins due to high somatic cell count.
      ).
      The biggest effect on dairy herd milk quality and production arises from contagious mastitis pathogens such as Staphylococcus aureus, as well as Streptococcus agalactiae (
      • Reksen O.
      • Sølverød L.
      • Østerås O.
      Relationships between milk culture results and milk yield in Norwegian dairy cattle.
      ;
      • Paradis M.-È.
      • Bouchard È.
      • Scholl D.T.
      • Miglior F.
      • Roy J.-P.
      Effect of nonclinical Staphylococcus aureus or coagulase-negative staphylococci intramammary infection during the first month of lactation on somatic cell count and milk yield in heifers.
      ;
      • Sørensen L.P.
      • Mark T.
      • Sørensen M.K.
      • Østergaard S.
      Economic values and expected effect of selection index for pathogen-specific mastitis under Danish conditions.
      ). Mycoplasma bovis, a bacterium lacking a cell wall from genus Mycoplasma, mainly causes IMI (
      • Nicholas R.A.J.
      • Ayling R.D.
      Mycoplasma bovis: Disease, diagnosis and control.
      ;
      • Maunsell F.P.
      • Woolums A.R.
      • Francoz D.
      • Rosenbusch R.F.
      • Step D.L.
      • Wilson D.J.
      • Janzen E.D.
      Mycoplasma bovis infections in cattle.
      ). Mycoplasma bovis is usually classified as a contagious mastitis pathogen (

      USDA APHIS. 2008. Prevalence of contagious mastitis pathogens on U.S. dairy operations, 2007. USDA; Anim. Plant Health Insp. Serv.; Vet. Serv.; Center Epidemiol. Anim. Health, Fort Collins, CO.

      ;
      • Royster E.
      • Wagner S.
      Treatment of mastitis in cattle.
      ). Transmission between animals occurs mainly at the milking time (
      • Ruegg P.L.
      New perspectives in udder health management.
      ). Mycoplasma bovis usually causes subclinical or mild clinical IMI, which can progress to chronic mastitis. Severe clinical mastitis outbreaks may also develop (
      • Bushnell R.B.
      Mycoplasma mastitis.
      ;
      • Pothmann H.
      • Sperqser J.
      • Elmer J.
      • Prunner I.
      • Iwersen M.
      • Klein-Jöbstl D.
      • Drillich M.
      Severe Mycoplasma bovis outbreak in an Austrian dairy herd.
      ;
      • Ruegg P.L.
      • Erskine R.J.
      Mastitis caused by other organisms.
      ). Mycoplasma bovis mastitis is not treatable with antibiotics; therefore, the control strategies of M. bovis IMI are to keep the herd uninfected, and to segregate and cull infected cows (
      • Fox L.K.
      • Kirk J.H.
      • Britten A.
      Mycoplasma mastitis: A review of transmission and control.
      ;
      • Royster E.
      • Wagner S.
      Treatment of mastitis in cattle.
      ;
      • Nicholas R.A.
      • Fox L.K.
      • Lysnyansky I.
      Mycoplasma mastitis in cattle: To cull or not to cull.
      ).
      Traditionally, M. bovis has been identified using culture-based methods, but due to low sensitivity and a long incubation period, molecular diagnostic methods have become preferable during recent years (
      • Dorman S.A.
      • Wilson D.J.
      • Smith T.F.
      Comparison of growth of Mycoplasma pneumoniae on modified New York and Hayflick media.
      ;
      • Sachse K.
      • Salam H.S.H.
      • Diller R.
      • Schubert E.
      • Hoffmann B.
      • Hotzel H.
      Use a novel real-time PCR technique to monitor and quantitate Mycoplasma bovis infection in cattle herds with mastitis and respiratory disease.
      ;
      • Gioia G.
      • Werner B.
      • Nydam D.V.
      • Moroni P.
      Validation of a mycoplasma molecular diagnostic test and distribution of mycoplasma species in bovine milk among New York State dairy farms.
      ). Detection of M. bovis in bulk tank milk samples (BTMS) or cow composite milk samples (CMS) by using quantitative PCR (qPCR) allows an identification of udder pathogens, including M. bovis, rapidly, with high sensitivity, and without previous isolation of bacteria (
      • Ghadersohi A.
      • Coelen R.J.
      • Hirst R.G.
      Development if a specific DNA probe and PCR for the detection of Mycoplasma bovis.
      ;
      • Ghadersohi A.
      • Hirst R.G.
      • Forbes-Faulkener J.
      • Coelen R.J.
      Preliminary studies on the prevalence of Mycoplasma bovis mastitis in dairy cattle in Australia.
      ;
      • Fox L.K.
      • Kirk J.H.
      • Britten A.
      Mycoplasma mastitis: A review of transmission and control.
      ). Identification of infected herds is best made by analyzing BTMS. Mycoplasma bovis positive result indicates that the pathogen is introduced to the herd. However, the true within-herd prevalence cannot be estimated with only a positive BTMS result. Further identification of infected cows should be made by analyzing CMS (
      • Fox L.K.
      • Kirk J.H.
      • Britten A.
      Mycoplasma mastitis: A review of transmission and control.
      ).
      Although mycoplasmas were identified in North America and Europe decades ago, the prevalence of M. bovis mastitis is not widely studied (
      • Fox L.K.
      • Kirk J.H.
      • Britten A.
      Mycoplasma mastitis: A review of transmission and control.
      ;
      • Fox L.K.
      Mycoplasma mastitis: Causes, transmission and control.
      ). The herd prevalence of M. bovis udder infection ranges between 0.9% in Australia and 1.5% in Belgium (
      • Passchyn P.
      • Piepers S.
      • De Meulemeester L.
      • Boyen F.
      • Haesebrouck F.
      • De Vliegher S.
      Between-herd prevalence of Mycoplasma bovis in bulk milk in Flanders, Belgium.
      ;
      • Morton J.
      • Malmo J.
      • House J.
      • Mein G.
      • Izzo M.
      • Penry J.
      Letter to the editor: Mycoplasma bovis in Australian dairy herds.
      ). According to a longitudinal study made in Israel, the number of M. bovis-positive dairy herds has increased annually from 2008 to 2014 (
      • Lysnyansky I.
      • Freed M.
      • Rosales R.S.
      • Mikula I.
      • Khateb N.
      • Gerchman I.
      • van Straten M.
      • Levisohn S.
      An overview of Mycoplasma bovis mastitis in Israel (2004–2014).
      ). However, the within-herd prevalence of M. bovis mastitis is still not widely studied to this day. By knowing the within-herd prevalence and course of the disease, it could be possible to develop functional control programs and predict new outbreaks. In a study by
      • Murai K.
      • Lehenbauer T.W.
      • Champagne J.D.
      • Glenn K.
      • Aly S.S.
      Cost-effectiveness of diagnostic strategies using quantitative real-time PCR and bacterial culture to identify contagious mastitis cases in large dairy herds.
      , a within-herd prevalence of M. bovis mastitis was 2.8% (n = 1,210). According to the Estonian Animal Recording Centre database, 19.6% of BTMS (n = 112), analyzed with the PCR method, were positive to M. bovis in 2013 (

      Estonian Animal Recording Centre. 2014. Annual report 2013. Tartu, Estonia.

      ).
      To our knowledge, no studies are available about the associations between M. bovis mastitis and cow milk yield or milk composition. Research about this, however, would clarify the importance of M. bovis as an udder pathogen and as a cause of production losses.
      The first objective of this study was to identify the within-herd prevalence of subclinical IMI caused by M. bovis by qPCR method. The second aim was to find associations between subclinical M. bovis infection, cow daily milk yield, SCC, and milk composition.

      MATERIALS AND METHODS

      Characteristics of the Study Herd

      The milk samples were collected from one large, loose-housing dairy herd in Estonia in November 2014. The study herd included 611 dairy cows, of which 89% were Estonian Holstein, and 11% were Estonian Red breed cows. Cows were milked twice a day in the 2 × 12 parallel milking parlors. The average 305-d milk yield was 9,916 kg and bulk milk SCC ranged between 259,000 and 358,000 cells/mL in 2014. Mycoplasma bovis was previously detected in BTMS and cow CMS of single cows with clinical mastitis by PCR in 2011.

      Collection and Analysis of Composite Milk Samples

      The CMS of all 525 lactating dairy cows were collected once during the routine milk recording in November 2014. The daily milk yield of each cow was measured by using a calibrated milk meter (Tru-Test Limited, Auckland, New Zealand). Parity and DIM of all lactating dairy cows were recorded.
      All milk samples were preserved with bronopol and transported to the milk laboratory of the Estonian Animal Recording Centre in Tartu. In the laboratory, milk fat (%), protein (%), urea (mg/L), and SCC (× 1,000/mL) were analyzed with accredited methods using the automatic analyzer Combifoss 6000 FC (Hillerød, Denmark).
      After analysis, 1.5 mL of each milk sample was collected and transported to the Estonian University of Life Sciences. Cows with visible signs of clinical mastitis (n = 3) were excluded from the study, and 2 cows without production data were excluded only from the regression analysis. All milk samples (n = 522) were stored at –18°C for further analysis.

      qPCR Analysis of Milk Samples

      A commercial qPCR test kit Mastit4B (DNA Diagnostic A/S, Risskov, Denmark) was used for qPCR analysis to detect bacterial DNA directly from the milk samples.
      The oligos of the Mastitis 4B are designed to detect DNA of Staph. aureus, Strep. agalactiae, Strep. uberis, and M. bovis. After thawing, the milk samples were vortexed and from each sample, 500 μL of milk was used for DNA extraction before PCR analysis according to the instructions (http://dna-diagnostic.com/files/Downloads/Mastit4/Instruction_protocol_M4B_2017.04.26.pdf) from the manufacturer (DNA Diagnostic, Risskov, Denmark). The PCR mixture consisted of 15 μL of the qPCR Master Mix and 5 μL of purified DNA. The real-time PCR instrument thermal cycler Stratagene Mx3005P (Agilent Technologies Inc., Santa Clara, CA) was used for amplification. The amplification conditions were as follows: 95°C for 1 min, 1 cycle; 95°C for 5 s and 60°C for 25 s, 40 cycles. Cycle threshold (Ct) values were reported for all samples. For all bacteria identified in the analysis, a Ct value of ≤37.0 was considered a positive result. The assay included controls for the validation of each run including negative DNA extraction controls, internal amplification standard (positive PCR controls), and nontemplate control. The assay was validated on both bacterial strains and milk samples by DNA Diagnostic. According to the internal validation protocol of the laboratory, the sensitivity and specificity of the test kit Mastitis 4B is 100% when tested directly on a bacterial colony.

      Statistical Analyses

      A causal diagram was drawn for variables to evaluate their causal associations and identify any confounders. Dependent variables were milk yield (kg), SCC (× 1,000/mL), milk protein, fat percentages, and milk urea content (mg/L). Cow parity and DIM were considered to be confounders according to the causal diagram. A linear regression model was chosen for estimating the associations between udder pathogens and milk yield, SCC, and milk compositions. The distribution of dependent variables was checked graphically. To achieve normal distribution, natural logarithm transformation was used for SCC, the square root was taken from the milk fat content, and an inverse scale was used for milk protein content.
      The PCR test results were dichotomized for each bacterium as either presence or absence by using the cut-off values (≤37.0) set by the manufacturer. Associations between the presence of 3 mastitis pathogens (M. bovis, Staph. aureus, and Strep. agalactiae) cow parity, and DIM were assessed using the χ2 test. Due to low number of qPCR-positive Strep. uberis CMS, the cow infection status of that pathogen was not added to the risk factor models. Statistical significance was set at P ≤ 0.05.
      Multivariable models were composed separately for each production indices serving as outcome variables. In multivariable models, cow parity (categorized into 1, 2, and ≥3 lactations) and DIM (categorized as 1–90, 91–200, and ≥201 DIM) were inserted to control for confounding effects. Dichotomized results (yes = 1, no = 0) of M. bovis, Staph. aureus, and Strep. agalactiae were included to assess the association with the outcome variable. Interaction terms were tested for significance to see whether the combined effect of 2 mastitis pathogens differs from the sum of the individual effects of the pathogens tested (
      • Dohoo I.
      • Martin W.
      • Stryhn H.
      Model building strategies.
      ). Assumptions of the equal variance of the outcome in all levels of predictor variables and normal distribution of the residuals were checked graphically (
      • Dohoo I.
      • Martin W.
      • Stryhn H.
      Model building strategies.
      ).
      The STATA IC 10 (StataCorp, College Station, TX) software was used for statistical analyses.

      RESULTS

      Descriptive Statistics

      Out of 522 cow CMS, 38.3% (n = 200) contained DNA from at least one targeted bacterial species. The DNA of one detected bacterial species was found in 61% (n = 122), 2 species in 31% (n = 62), and 3 species were detected simultaneously in 8% (n = 16) of pathogen-positive milk samples. Mycoplasma bovis alone was detected in 15% (n = 30) of pathogen-positive milk samples and in combination with Strep. agalactiae in 19.5% (n = 39) of pathogen-positive milk samples. The most prevalent bacterial species was Strep. agalactiae alone, presented in 37.5% (n = 75) of pathogen-positive milk samples. The different combinations of udder pathogens in pathogen-positive cow CMS are present in Table 1.
      Table 1Different combinations of detected bacteria in pathogen-positive milk samples
      PathogenNumber of positive samples (%)
      Streptococcus agalactiae75 (37.5)
      Mycoplasma bovis30 (15.0)
      Staphylococcus aureus14 (7.0)
      Streptococcus uberis3 (1.5)
      Mycoplasma bovis, Streptococcus agalactiae39 (19.5)
      Streptococcus agalactiae, Staphylococcus aureus17 (8.5)
      Mycoplasma bovis, Staphylococcus aureus, Streptococcus agalactiae15 (7.5)
      Mycoplasma bovis, Staphylococcus aureus6 (3.0)
      Streptococcus agalactiae, Staphylococcus aureus, Streptococcus uberis1 (0.5)
      Total200 (100)

      Prevalence of Udder Pathogens

      The within-herd prevalence of M. bovis was 17.2% (n = 90; 95% CI 14.1–20.8). Streptococcus agalactiae had the highest within-herd prevalence of 28.4% (n = 148; 95% CI 24.5–34.2). The within-herd prevalence of Staph. aureus was 10.2% (n = 53; 95% CI 7.7–13.1). Streptococcus uberis was found only in 5 CMS with prevalence of 1% (95% CI 0.3–2.2).
      The presence of M. bovis or Staph. aureus was not significantly associated with DIM. The probability of detecting Strep. agalactiae in milk samples was higher (P < 0.05) in dairy cows in late lactation stage (>201 DIM) compared with the first 3 mo of lactation. There was a significantly higher risk of detecting Staph. aureus in milk samples from older cows (≥3 lactations) compared with ≤2 lactation dairy cows (Table 2).
      Table 2Distribution of detected mastitis pathogens (alone or in combination) in composite milk samples of 520 dairy cows according to lactation stage and parity
      ItemNumber of cowsMycoplasma bovis positive, no. (%)Staphylococcus aureus positive, no. (%)Streptococcus agalactiae positive, no. (%)
      DIM
       0–9013323 (17.3)15 (11.3)25 (18.8)
       91–20017035 (20.6)15 (8.8)53 (31.2)
       ≥20121732 (14.7)23 (10.6)70 (32.2)
      Statistically significant in χ2 test (P < 0.05) by DIM or lactation number.
      Parity
       1 Lactation22029 (13.2)18 (8.2)58 (26.4)
       2 Lactations15930 (18.9)13 (8.2)49 (30.8)
       ≥3 Lactations14131 (22.0)22 (15.6)
      Statistically significant in χ2 test (P < 0.05) by DIM or lactation number.
      41 (29.1)
      * Statistically significant in χ2 test (P < 0.05) by DIM or lactation number.

      Associations Between Detected Mastitis Pathogens and Milk Yield, Somatic Cell Count, and Milk Composition

      The presence of M. bovis DNA in milk samples was associated with a lower (−3.0 kg) daily milk yield compared with dairy cows without M. bovis DNA in the milk samples. The daily milk yield was also lower (−4.0 kg) in dairy cows that tested positive for Strep. agalactiae compared with Strep. agalactiae negative dairy cows (Table 3).
      Table 3Results of multivariable linear regression model of association between detected mastitis pathogens in cow composite milk samples and daily milk yield (kg) of dairy cows (n = 520)
      ItemNumber of cowsCoefficient95% CIP-valueWald test
      Mycoplasma bovis negative4300
      Mycoplasma bovis positive90−3.0−5.2; −0.80.007
      Staphylococcus aureus negative4670
      Staphylococcus aureus positive530.8−1.8; 3.50.546
      Streptococcus agalactiae negative3720
      Streptococcus agalactiae positive148−4.0−5.9; −2.2<0.001
      1 Lactation2200<0.001
      2 Lactations1593.71.9; 5.5<0.001
      ≥3 Lactations1413.31.4; 5.30.001
      <90 DIM1330<0.001
      91–200 DIM170−4.4−6.5; −2.3<0.001
      ≥201 DIM217−13.6−15.6; −11.6<0.001
      Intercept36.034.2; 37.9<0.001
      The lnSCC was significantly higher in milk samples, in which DNA from M. bovis, Staph. aureus, and Strep. agalactiae was detected, compared with milk samples negative for these pathogens (Table 4).
      Table 4Results of multivariable linear regression model of association between SCC in cow composite milk samples and mastitis pathogens (n = 520)
      ItemNumber of cowsCoefficient
      Estimates are in logarithmic scale.
      95% CIP-valueWald test
      Mycoplasma bovis negative4300
      Mycoplasma bovis positive900.80.5; 1.1<0.001
      Staphylococcus aureus negative4670
      Staphylococcus aureus positive530.90.5; 1.3<0.001
      Streptococcus agalactiae negative3720
      Streptococcus agalactiae positive1480.60.3; 0.8<0.001
      1 Lactation2200<0.001
      2 Lactations1590.1−0.2; 0.40.459
      ≥3 Lactations1410.60.3; 0.8<0.001
      <90 DIM1330<0.001
      91–200 DIM1700.1−0.2; 0.40.399
      ≥201 DIM2170.50.2; 0.8<0.001
      Intercept3.73.4; 4.0<0.001
      1 Estimates are in logarithmic scale.
      In the CMS of cows positive for M. bovis, the milk fat and urea (P < 0.05) content were lower compared with the respective values of cows negative for M. bovis. Mycoplasma bovis was not significantly associated with milk protein content (Tables 5, 6, and 7). The presence of Strep. agalactiae in milk samples had a positive association with the milk fat content (P = 0.041) and protein content (P = 0.034; Table 5, Table 6).
      Table 5Results of multivariable linear regression model of association between milk fat in cow composite milk samples and mastitis pathogens (n = 520)
      ItemNumber of cowsCoefficient
      Estimates are on a square root scale.
      95% CIP-valueWald test
      Mycoplasma bovis negative4300
      Mycoplasma bovis positive90−0.05−0.1; −0.0040.035
      Staphylococcus aureus negative4670
      Staphylococcus aureus positive53−0.1−0.07; 0.050.732
      Streptococcus agalactiae negative3720
      Streptococcus agalactiae positive1480.050.002; 0.090.041
      1 Lactation22000.021
      2 Lactations159−0.06−0.1; −0.010.011
      ≥3 Lactations141−0.05−0.1; −0.0010.046
      <90 DIM1330<0.001
      91–200 DIM170−0.03−0.08; 0.020.233
      ≥201 DIM2170.080.04; 0.10.001
      Intercept2.01.95; 2.04<0.001
      1 Estimates are on a square root scale.
      Table 6Results of multivariable linear regression model of association between milk protein in cow composite milk samples and mastitis pathogens (n = 520)
      ItemNumber of cowsCoefficient
      Estimates are on an inverse scale (negative estimate means higher content of protein).
      95% CIP-valueWald test
      Mycoplasma bovis negative4300
      M. bovis positive900.001−0.005; 0.0070.706
      Staphylococcus aureus negative4670
      Staph. aureus positive530.002−0.006; 0.0090.674
      Streptococcus agalactiae negative3720
      Strep. agalactiae positive148−0.006−0.01; −0.00040.034
      1 Lactation22000.282
      2 Lactations1590.003−0.002; 0.0080.214
      ≥3 Lactations1410.004−0.002; 0.0090.190
      <90 DIM1330<0.001
      91–200 DIM170−0.02−0.02; −0.01<0.001
      ≥201 DIM217−0.04−0.05; −0.04<0.001
      Intercept0.30.30; 0.31<0.001
      1 Estimates are on an inverse scale (negative estimate means higher content of protein).
      Table 7Results of multivariable linear regression model of association between milk urea (mg/L) in cow composite milk samples and mastitis pathogens (n = 520)
      ItemNumber of cowsCoefficient95% CIP-valueWald test
      Mycoplasma bovis negative4300
      M. bovis positive90−15.6−25.6; −5.60.002
      Staphylococcus aureus negative4670
      Staph. aureus positive53−6.0−18.2; 6.30.339
      Streptococcus agalactiae negative3720
      Strep. agalactiae positive148−7.8−16.4; 0.70.072
      1 Lactation2200<0.001
      2 Lactations159−3.8−12.2; 4.70.379
      ≥3 Lactations141−16.8−25.7; −7.9<0.001
      <90 DIM1330<0.001
      91–200 DIM17028.218.7; 37.7<0.001
      ≥201 DIM21717.18.1; 26.2<0.001
      Intercept159.4150.8; 168.0<0.001

      DISCUSSION

      Prevalence of Mycoplasma bovis in Cow CMS Using qPCR

      The within-herd prevalence of subclinical M. bovis udder infection is not widely studied in European dairy herds. Most of the previous studies are focusing on clinical mastitis cases or on between-herd prevalence of M. bovis (
      • Filioussis G.
      • Ghristodoulopoulos G.
      • Thatcher A.
      • Petridou V.
      • Bourtzi-Chatzopoulou E.
      Isolation of Mycoplasma bovis from bovine clinical mastitis cases in Northern Greece.
      ;
      • Arcangioli M.A.
      • Chazel M.
      • Sellal E.
      • Botrel M.A.
      • Bézille P.
      • Poumarat F.
      • Calavas C.
      • Le Grand D.
      Prevalence of Mycoplasma bovis udder infection in dairy cattle: Preliminary field investigation in southeast France.
      ;
      • Radaelli E.
      • Castiglioni V.
      • Losa M.
      • Benedetti V.
      • Piccinini R.
      • Nicholas R.A.J.
      • Scanziani E.
      • Luini M.
      Outbreak of bovine clinical mastitis caused by Mycoplasma bovis in a North Italian herd.
      ;
      • Passchyn P.
      • Piepers S.
      • De Meulemeester L.
      • Boyen F.
      • Haesebrouck F.
      • De Vliegher S.
      Between-herd prevalence of Mycoplasma bovis in bulk milk in Flanders, Belgium.
      ). We identified a M. bovis within-herd prevalence of 17.2% in one dairy herd. Previously,
      • Brown M.B.
      • Shearer J.K.
      • Elvinger F.
      Mycoplasmal mastitis in a dairy herd.
      identified a 5.7% (n = 1535) prevalence of mycoplasmas based on a study in one herd. According to the study of
      • Brown M.B.
      • Shearer J.K.
      • Elvinger F.
      Mycoplasmal mastitis in a dairy herd.
      , a higher within-herd prevalence of M. bovis IMI was found in our study. However, we collected milk samples only once and from a single dairy herd by using a high-sensitivity qPCR method to detect major udder pathogens from the CMS (
      • Koskinen M.T.
      • Wellenberg G.J.
      • Sampimon O.C.
      • Holopainen J.
      • Rothkamp A.
      • Salmikivi L.
      • van Haeringen W.A.
      • Lam T.J.G.M.
      • Pyörälä S.
      Field comparison of real-time polymerase chain reaction and bacterial culture for identification of bovine mastitis bacteria.
      ;
      • Murai K.
      • Lehenbauer T.W.
      • Champagne J.D.
      • Glenn K.
      • Aly S.S.
      Cost-effectiveness of diagnostic strategies using quantitative real-time PCR and bacterial culture to identify contagious mastitis cases in large dairy herds.
      ;
      • Nyman A.-K.
      • Persson Waller K.
      • Emanuelson U.
      • Frössling J.
      Sensitivity and specificity of PCR analysis and bacteriological culture of milk samples for identification of intramammary infections in dairy cows using latent class analysis.
      ). Therefore, the results of this study describe the within-herd prevalence of M. bovis only at the single point in time in one specific herd.
      Cow CMS are used to detect especially subclinical IMI when it is difficult to identify the infected udder quarter. However, milk originating from noninfected udder quarters may lower the sensitivity in IMI pathogen detection, due to a dilution effect (
      • Reyher K.K.
      • Dohoo I.R.
      Diagnosing intramammary infections: Evaluation of composite milk samples to detect intramammary infections.
      ). In this study, we used commercial qPCR analysis to detect 4 mastitis pathogens in cow CMS simultaneously. A high sensitivity of the PCR method to detect udder pathogens causing IMI is reported, also when cow CMS are used (

      Friendship, C., D. Kelton, D. van de Water, D. Slavic, and M. Koskinen. 2010. Field evaluation of the Pathoproof mastitis PCR assay for the detection of Staphylococcus aureus infected cows using DHI samples. NMC Annual Meeting Proceedings. 226–227.

      ;
      • Koskinen M.T.
      • Wellenberg G.J.
      • Sampimon O.C.
      • Holopainen J.
      • Rothkamp A.
      • Salmikivi L.
      • van Haeringen W.A.
      • Lam T.J.G.M.
      • Pyörälä S.
      Field comparison of real-time polymerase chain reaction and bacterial culture for identification of bovine mastitis bacteria.
      ;
      • Murai K.
      • Lehenbauer T.W.
      • Champagne J.D.
      • Glenn K.
      • Aly S.S.
      Cost-effectiveness of diagnostic strategies using quantitative real-time PCR and bacterial culture to identify contagious mastitis cases in large dairy herds.
      ;
      • Nyman A.-K.
      • Persson Waller K.
      • Emanuelson U.
      • Frössling J.
      Sensitivity and specificity of PCR analysis and bacteriological culture of milk samples for identification of intramammary infections in dairy cows using latent class analysis.
      ).
      A carry-over of the udder pathogen DNA may occur when CMS are collected with automated milk meters. Milk from a previously milked cow is mixed with milk from the cow currently being milked, leading to false-positive PCR test results (

      Løvendahl, P., M. Bjerring, and T. Larsen. 2010. Determination of carry-over in automated milking, recording and sampling systems using fluorescent tracers. Pages 147–152 in Proc. ICAR 37th Annual Meeting, Riga, Latvia, 2010.

      ;
      • Mahmmod Y.
      Implications of carryover on the diagnostic indications for intramammary infections in dairy herds.
      ). In conventional milking systems, the probability of carry-over is evaluated to range from 2 to 3.5% (
      • Løvendahl P.
      • Bjerring M.A.
      Detection of carryover in automated milk sampling equipment.
      ;

      Løvendahl, P., M. Bjerring, and T. Larsen. 2010. Determination of carry-over in automated milking, recording and sampling systems using fluorescent tracers. Pages 147–152 in Proc. ICAR 37th Annual Meeting, Riga, Latvia, 2010.

      ). The carry-over effect may be associated with the Ct-value cut-off (
      • Mahmmod Y.S.
      • Mweu M.M.
      • Nielsen S.S.
      • Katholm J.
      • Klaas I.C.
      Effect carryover and presampling procedures on the results of real-time PCR used for diagnosis of bovine intramammary infections with Streptococcus agalactiae at routine milk recordings.
      ). Lower cut-off values in discriminating positive and negative test results lower the sensitivity of the test, but reduce the number of false-positive test results that may occur due to carry-over (
      • Mahmmod Y.S.
      • Mweu M.M.
      • Nielsen S.S.
      • Katholm J.
      • Klaas I.C.
      Effect carryover and presampling procedures on the results of real-time PCR used for diagnosis of bovine intramammary infections with Streptococcus agalactiae at routine milk recordings.
      ). The cut-off value was set to be ≤37.0 in our study, which should be low enough to rule out most of the false-positive results and hence decrease the probability that contaminated samples are classified as positive (
      • Mahmmod Y.S.
      • Mweu M.M.
      • Nielsen S.S.
      • Katholm J.
      • Klaas I.C.
      Effect carryover and presampling procedures on the results of real-time PCR used for diagnosis of bovine intramammary infections with Streptococcus agalactiae at routine milk recordings.
      ).

      Associations Between Cow Mycoplasma bovis Infection and Milk Yield and Milk Composition

      To our knowledge this is the first study evaluating associations between subclinical M. bovis IMI, cow milk yield, SCC, and composition, when cow CMS are used. We identified no significant relation between co-infection with udder pathogens and cow milk yield, SCC, or milk composition. This may be due to relatively low numbers of samples with multiple pathogens detected and should be controlled in further studies using larger number of samples.
      The presence of M. bovis bacterial DNA in CMS was associated with an average of a 3.0 kg lower daily milk yield compared with cows negative for M. bovis. The negative effect of Strep. agalactiae or Staph. aureus subclinical IMI on milk yield was already discovered decades ago (
      • Keefe G.P.
      • Dohoo I.R.
      • Spangler E.
      Herd prevalence and incidence of Streptococcus agalactiae in the dairy industry of Prince Edward Island.
      ;
      • Reksen O.
      • Sølverød L.
      • Østerås O.
      Relationships between milk culture results and milk yield in Norwegian dairy cattle.
      ). In the present study, a negative association between presence of bacterium in subclinically infected cow CMS and milk yield was detected for Strep. agalactiae but not for Staph. aureus. Even though the number of M. bovis positive dairy cows was low in our study, a significant relation between M. bovis and cow daily milk yield was identified. As far as we know, no research has been published about the association between subclinical M. bovis IMI and milk yield. Therefore, this study provides essential knowledge about the economic effect of M. bovis on dairy farm production.
      A significant association was observed between M. bovis and milk SCC level after controlling for the presence of other mastitis pathogens, parity, and DIM. We found that in CMS positive for M. bovis, the lnSCC was on average 0.8 units higher compared with milk samples negative for this pathogen. It is speculated that the SCC of cows positive for M. bovis is higher in most of the cows, but not all of them (
      • Ghadersohi A.
      • Hirst R.G.
      • Forbes-Faulkener J.
      • Coelen R.J.
      Preliminary studies on the prevalence of Mycoplasma bovis mastitis in dairy cattle in Australia.
      ;
      • Pinho L.
      • Thompson G.
      • Machado M.
      • Carvalheira J.
      Management practices associated with the bulk tank milk prevalence of Mycoplasma spp. in dairy herds in Northwestern Portugal.
      ). Even though in our study there was an association between M. bovis IMI and cow SCC, using only cow SCC status in mastitis control programs may lead to an omission of some M. bovis positive dairy cows (
      • Ghadersohi A.
      • Hirst R.G.
      • Forbes-Faulkener J.
      • Coelen R.J.
      Preliminary studies on the prevalence of Mycoplasma bovis mastitis in dairy cattle in Australia.
      ;
      • Pinho L.
      • Thompson G.
      • Machado M.
      • Carvalheira J.
      Management practices associated with the bulk tank milk prevalence of Mycoplasma spp. in dairy herds in Northwestern Portugal.
      ).
      In our study, the subclinical M. bovis udder infection was negatively associated with some of the milk composition parameters. The milk fat and urea content in M. bovis-positive cows was lower than in M. bovis-negative cows. Spontaneous lipolysis during the IMI leads to lower milk fat content and changes in milk fat composition (
      • Forsbäck L.
      • Lindmark-Månsson H.
      • Andrén A.
      • Svannersten-Sjaunja K.
      Evaluation of quality changes in udder quarter milk from cows with low-to-moderate somatic cell count.
      ). Urea is formed in the liver from ammonium and absorbed to the milk from the blood in a stable form (
      • Hayton A.
      • Husband J.
      • Vecqueray R.
      Nutritional management of herd health.
      ). However, many factors influence the milk urea content, such as altered DMI, or the lack of rumen degradable protein and energy in feed ratio (
      • Rezamand P.
      • Hoagland T.A.
      • Moyes K.M.
      • Silbart L.K.
      • Andrew S.M.
      Energy status, lipid-soluble vitamins and acute phase proteins in periparturient Holstein and Jersey dairy cows with or without subclinical mastitis.
      ;
      • Hayton A.
      • Husband J.
      • Vecqueray R.
      Nutritional management of herd health.
      ). Therefore, it is not possible to make strong conclusions about the causality of M. bovis subclinical IMI and milk urea content.
      Intramammary infection usually causes a decrease in milk protein levels (
      • Rezamand P.
      • Hoagland T.A.
      • Moyes K.M.
      • Silbart L.K.
      • Andrew S.M.
      Energy status, lipid-soluble vitamins and acute phase proteins in periparturient Holstein and Jersey dairy cows with or without subclinical mastitis.
      ). In this study, we did not find a significant association between the presence of M. bovis in milk samples and milk protein content. Further studies using a larger sample size are needed to confirm the associations between subclinical M. bovis IMI and milk yield as well as milk composition parameters, making it possible to estimate the economic effect of M. bovis IMI and effects on cow well-being.

      CONCLUSIONS

      This study identified the within-herd prevalence of subclinical Mycoplasma bovis IMI of 17.2% by testing CMS of 522 lactating dairy cows using qPCR. Dairy cows infected with M. bovis had higher SCC, produced less milk, and had lower milk fat and urea content compared with M. bovis-negative dairy cows. Further studies should evaluate the associations between M. bovis and milk yield and milk quality in a larger number of herds. Our findings underlay the importance to apply control measures of M. bovis mastitis to reduce economic losses due to lower milk yield and milk quality caused by subclinical udder infection of M. bovis.

      ACKNOWLEDGMENTS

      This study was supported by the Estonian Ministry of Agriculture (research contract 3-15.4/04-2013).

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