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Relationships among quarter milk leukocyte proportions and cow and quarter-level variables under different intramammary infection statuses † ‡ § † †,1 Sushil Paudyal, Gustavo Pena, Pedro Melendez, Ivette Noa Roman-Muniz, and Pablo J. Pinedo † ‡ Department of Animal Sciences, Colorado State University, Fort Collins, CO 80523; Advanced Animal Diagnostics, Morrisville, NC 27560; and Department of Clinical Sciences, University of Missouri, Columbia, MO 65211 ABSTRACT: The use of milk leukocyte differential leukocyte ratios (NEU:LYM, NEU:MAC, and (MLD) test has been proposed as a complement to phagocyte:LYM) were different for multiple TLC somatic cell count (SCC) to assess the presence and categories (P < 0.05). There was no association the severity of intramammary infection. However, between parity number and MLD; however, cows detailed information regarding the behavior of in early lactation had the greatest proportions of MLD under different physiological or pathological NEU and LYM. Leukocyte ratios varied depend- stages of the cow is nonexistent. The objective was ing on parity number and stage of lactation. Cows to analyze the association between milk leukocyte in the medium milk-yield category had the smallest proportions provided by a commercial automated proportions of NEU and LYM, and there was sig- MLD test and multiple cow and quarter-level nificant variation in leukocyte ratios, depending on variables. The study population consisted of 104 the level of milk yield. In healthy quarters, MLD Holstein cows (32 primiparous and 72 multiparous) were not associated with quarter position; how- in one farm. Cows were categorized by days in milk ever, the NEU:MAC ratio was greater in rear quar- as early (<50 DIM; n=29), middle (50–250 DIM; ters than in front quarters. In quarters with TLC n=25), and late lactation (>250 DIM; n = 50). Milk >100,000, NEU% was greater in rear quarters than from 416 quarters was collected and analyzed for in front quarters (P = 0.03). For quarters with path- lymphocytes (LYM), neutrophils (NEU), and mac- ogen growth, TLC was greatest for GN followed by rophages (MAC) counts using an automated milk OTH and GP (P < 0.001). Milk LD depended on fluorescence microscopy system. Concurrently, a the isolated pathogen group, although the magni- sterile composite milk sample was collected from tudes of the differences were small. Although the each cow for pathogen identification through changes in the proportions of leukocytes in milk microbiological culture. Culture results were clas- were associated with categories of TLC, levels of sified as no growth ( NOG), gram-negative (GN), milk yield, and mastitis-causing pathogen groups, gram-positive (GP), or other (OTH). Milk leuko- the deviations were small in magnitude. Additional cyte proportions varied depending on the level of research is necessary to determine the potential total leukocyte counts (TLC; P < 0.001). Similarly, applications for this methodology. Key words: differential leukocyte count, mastitis, quarters © The Author(s) 2018. Published by Oxford University Press on behalf of the American Society of Animal Science. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact firstname.lastname@example.org Transl. Anim. Sci. 2018.2:231–240 doi: 10.1093/tas/txy065 Corresponding author: email@example.com Received March 29, 2018. Accepted June 4, 2018. Downloaded from https://academic.oup.com/tas/article-abstract/2/3/231/5033002 by Ed 'DeepDyve' Gillespie user on 31 July 2018 232 Paudyal et al. INTRODUCTION of IMI and the infectious pathogens. Therefore, the study objective was to analyze the association Mastitis remains one of the most prevalent and between milk leukocyte proportions provided by a costly diseases in dairy systems (Damm et al., 2017). commercial automated MLD test and multiple cows The use of somatic cell count (SCC) for the diag- and quarter-level variables, including SCC, parity nosis of intramammary infection (IMI) is widely number, stage of lactation, level of milk produc- accepted and is considered a reliable procedure tion, and presence of mastitis-causing pathogens. for the detection of subclinical mastitis (SCM). Although SCC is a robust methodology, it does not MATERIALS AND METHODS provide a differentiation of cell types (Damm et al., 2017). The use of a milk leukocyte differential (MLD) test, providing the proportions of specific Study Population leukocytes in milk, has been proposed as a comple- All experimental procedures were approved by ment to SCC to assess the presence and the sever- the Institutional Animal Care and Use Committee ity of IMI (Dohoo et al., 1981; Leitner et al., 2003; at Colorado State University (protocol ID: Godden et al., 2017). Moreover, in recent studies, 16-6775A). MLD has been suggested as a screening option The research was conducted in a commercial for IMI in selective dry cow therapy and fresh cow dairy herd in West Texas (Plainview, TX). Cows assessment (Godden et al., 2017; Gonçalves et al., were housed in a freestall barn and milked three 2017). According to a recent study (Godden et al., times daily in a rotary milking parlor (Afimilk, 2017), costs for the MLD test are approximately Kibbutz Afikim, Israel). Cows were not vaccinated $18,000 for the reader, $5.00 per cow for the cas- against any mastitis pathogen. A total of 104 clinic- sette, in addition to the cost of labor for the sam- ally healthy Holstein cows were randomly selected, pling and the analysis procedures. among which 32 animals were primiparous, and 72 The proportions of leukocytes in milk have were multiparous cows (26, 20, and 26 cows in 2nd, been shown to change depending on the degree 3rd, and ≥3rd lactation). of IMI, suggesting that different frequencies of white cell types may be an indication of the diverse stages of progression of infection (Sarikaya et al., MLD Test and Bacteriological Cultures 2006). In addition, it is plausible to speculate that these fluctuations in cell proportions in milk from Milk samples obtained from 416 quarters inflamed mammary glands may exhibit character - were evaluated for MLD using Qscout (Advanced istic patterns, depending on the presence of specific Animal Diagnostics, Durham, NC). Milk was groups of pathogens. collected following standard aseptic procedures Microbiological culture of milk is the accepted (National Mastitis Council, 1999) that included gold standard for determining IMI status in both, teat-end disinfection with alcohol and disposal of clinical or SCM. In addition, this information is of the first streams of milk. The device reader has significant value when selecting for the appropri - programmable threshold levels on a scale of 1 to ate treatment options. However, the cost and time 18 that may be selected by the user, and different requirements associated with milk culture, together thresholds would result in higher sensitivity or with the risk for contamination and mishandling of higher specificity ( Godden et al., 2017; Gonçalves samples, limit this approach as a routine diagnos- et al., 2017). The reported sensitivity and specificity tic procedure in commercial farms (Godden et al., for this technology at threshold level 7, using micro- 2017). Consequently, a rapid, cow-side test to deter- biological culture as a gold standard, were 65.4% mine IMI, providing an indication of the potential and 79.3%, respectively (Gonçalves et al., 2017). groups of pathogens involved, would be a beneficial Milk from each quarter was applied into a plas- tool in the control of mastitis. tic container connected to one of four quadrants of As the application of the differential cell count a single-use cassette. The cassette was immediately in milk develops, more details on this parameter loaded into the automated reading device, using the behavior under different physiological or patho- research mode (threshold level 6) that required about logical stages of the cow are required. The study 15 min per cassette and offered increased accuracy hypothesis was that specific white cell proportions for the differentials. The device uses a fluorescence in milk will deviate depending upon multiple cows microscopy imaging system taking images to iden- and quarter-level variables, including the presence tify and count lymphocytes (LYM), neutrophils Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/3/231/5033002 by Ed 'DeepDyve' Gillespie user on 31 July 2018 Milk leukocyte proportions dynamics 233 (NEU), and macrophages (MAC; Godden et al., 401,000–700,000; 701,000–1,000,000; 1,001,000– 2017; Gonçalves et al., 2017). Results are provided 3,000,000; 3,001,000–10,000,000; and >10,000,000 as total leukocyte counts (TLC) and as absolute cells/mL). Results from bacterial culture (cow-level values for each cell type (NEU, LYM, and MAC). composite milk sample) were classified as gram-neg - In addition, the percentages of NEU, LYM, and ative (GN) pathogens (Acinetobacter spp., E. coli, MAC for each sample were directly obtained from Pasteurella spp., and Pseudomonas spp.); gram-pos- the device for statistical analyses. Finally, absolute itive (GP; CN Staphylococcus, Corynebacterium cell counts from MLD were used for determin- spp., S. aureus, Streptococcus spp., and Trueperella ation of NEU:LYM, NEU:MAC, and phagocyte pyogenes); other (OTH; Mycoplasma spp. and (PHAG):LYM (indicated by NEU + MAC) ratios. Prototheca spp.); and culture negative (NOG). Right before collection for MLD, a composite Other variables at the cow level included parity milk sample from the four quarters was collected number (1; 2; 3; >3) and stage of lactation (early from each study cow in a sterile tube using asep- [<50 DIM], middle [50–250 DIM], and late [>250 tic technique (National Mastitis Council, 1999). DIM]). Individual milk yield provided by in-line Briefly, the teats were cleaned and disinfected using milk meters (Afimilk, Kibbutz Afikim, Israel) at 70% alcohol in a cotton gauze. The first few streams the time of sampling was available. The average of milk were discarded, and 10 mL of foremilk was (SD) milk yield per day for the study cows was 32.6 aseptically collected in a sterile tube as a compos- (10.9) kg, with a range from 6.7 to 52.1 kg. Milk ite sample from each of the four quarters. Samples yield at the day of sampling was categorized into were immediately frozen before lab submission for quartiles (Q1 <20 kg; Q2–Q3 = 20.1–29.0 kg; and bacteriological culture. Q4 >29.0 kg). To evaluate the effect of quarter posi- All milk samples were submitted to and tion, quarters were grouped into front and rear quar- received at The Dairy Authority, LLC (Greely, ters and were subsequently categorized as healthy if CO). Approximately, 0.01 mL of each milk sam- TLC ≤100,000 and as affected if TLC >100,000. ple was inoculated using a disposable inoculation loop (Hardy Diagnostics, Santa Maria, CA) onto Statistical Analyses blood agar plates containing 4% washed bovine blood (Quad Five, Ryegate, MT) and 0.1% esculin Cow and quarter-level data were entered into (Sigma–Aldrich, St. Louis, MO) and MacConkey spreadsheets (Excel 2016, Microsoft, Redmond, agar plates (Oxoid, ThermoFisher Scientific, WA) and analyzed using SAS version 9.3 (SAS Waltham, MA) and incubated aerobically at 37 °C. Institute Inc., Cary, NC). Data were checked for Bacterial growth was identified after 24 and 48 h normal distribution, and subsequently, MLD val- of incubation according to National Mastitis ues were arcsine transformed, while TLC data were Council standards. Briefly, Staphylococcus aureus reciprocally transformed, where they did not show and Staphylococcus spp. were identified by hemo - a normal distribution. After completion of the lytic pattern and tube coagulase test. Streptococcus analyses, the results were back-transformed to be spp. was identified by a catalase test (Hydrogen reported in the original scales. Peroxide) and gram stain (JorVet gram stain kit, Pathogen data originated from bacteriological Sigma–Aldrich). Escherichia coli and Klebsiella spp. cultures from composite samples (cow-level data). were identified using morphologic characteristics of Therefore, in cows with positive cultures, only the colonies on MacConkey agar, production of indole, quarter with the greatest TLC was considered for the motility, and utilization of citrate. Approximately, analyses testing associations between MLD and mas- 0.1 mL of each milk sample was also inoculated titis-causing pathogen groups. For cows with negative onto a Modified Eaton’s Mycoplasma Agar (The cultures, the average for the four quarters was con- Dairy Authority Labs) with a polyester swab sidered. Statistical models were tested using PROC (Hardy Diagnostics). Mycoplasma agar plates were MIXED in SAS and included pathogen category, incubated in an 8–10% CO incubator at 37 °C for parity number, stage of lactation, milk-yield category 10 d. Mycoplasma agar plates were examined under at the time of sampling, and quarter position. a dissecting microscope at 3, 7, and 10 d. In general, depending on the analysis, the mod- els were defined as follows: Cow and Quarter-level Variable Categorization Y =+ µ Path ++ Par St ijklm ij k Eight categories were created for quarter TLC ++ Mlk Qp + e lm ijklm (≤100,000; 101,000–200,000; 201,000–400,000; Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/3/231/5033002 by Ed 'DeepDyve' Gillespie user on 31 July 2018 234 Paudyal et al. Where: smallest during early lactation (P < 0.001 and P < Y = dependent variable (TLC, quarter-level 0.001, respectively; Figure 3). Leukocyte propor- ijklm MLD, or leukocyte ratios) tions and ratios were both associated with milk- µ = overall population mean yield category (P < 0.05). NEU% was greater in Path = effect of pathogen category (NOG, GN, the high milk-yield category compared with the GP, or OTH) medium-yield category (P = 0.01). LYM% was Par = effect of parity number (1, 2, 3, or >3) greater in the high milk-yield level than in both the St = effect of stage of lactation (early, mid, medium- and the low-yield categories (P < 0.005). or late) Finally, MAC% was greater in the low and medium Mlk = effect of milk yield (low, medium, categories (P < 0.001), and the NEU:MAC and or high) the PHAG:LYM ratios were both greater in the Qp = effect of quarter position (front or rear) low and medium milk-yield categories than in e = error term the high-yield category (P = 0.002 and P = 0.02, ijklm For all the analyses, statistical significance was respectively; Figure 4) defined at P value <0.05. No associations between quarter position and NEU, L YM, and MAC% were determined in healthy quarters (TLC ≤ 100,000 cells/mL). Similarly, no RESULTS associations were found for the NEU:LYM and the Overall, milk leukocyte proportions from 411 PHAG:LYM ratios. Interestingly, the PHAG:LYM quarters were available. Samples from five quarters ratio was greater in rear quarters than in front did not return MLD results from Qscout and were quarters (P = 0.01; Table 1). In high TLC quarters, removed from the analysis. Composite milk sam- only NEU (%) was greater in the rear quarters than ples from 104 cows were submitted for bacterio- in front quarters (P = 0.03). logic testing. Cultures indicated no growth (NOG) Values for TLC varied by pathogen group for 44 samples, and 5 samples registered multiple (P < 0.001) and were largest in GN, followed by pathogens growth (>2 different bacteria) and were OTH and GP pathogens (Table 2). However, TLC considered contaminated and removed from the were not different for GP and GN groups. subsequent analyses. Main categories of reported Milk leukocyte proportions also varied pathogens were Coagulase Negative S. aureus according to the pathogen group involved. NEU% (n = 30), Streptococcus spp. (8), Corynebacterium were highest in the OTH and GP groups, with spp. (5), Mycoplasma spp. (4), E. coli (2), S. aur- the lowest level in GN and NOG (P < 0.001). eus (2), T. pyogenes (2), Prototheca spp. (1), and However, no significant difference was established Pasteurella spp. (1). for GP vs. GN groups. On the other hand, LYM% Mean (median) for quarter TLC was 1,553,000 were reduced in all GN, GP, and OTH pathogens (209,000) cells/mL. Milk leukocyte proportions var- as compared with the NOG group (P < 0.001). ied depending on the category of TLC (P < 0.001; Furthermore, LYM% was greater for the GN Figure 1). NEU% consistently increased as catego- compared with the GP group (P < 0.01). Finally, ries of TLC augmented (P < 0.001). This response MAC% was increased in the GN group of patho- was opposite for MAC%, which were larger for gens and decreased in the OTH and the GP groups small TLC categories (P < 0.001). LYM% also var- (P = 0.03), as compared with the NOG group ied by category of TLC (P < 0.0001) but in a smaller (Table 2). magnitude. Similarly, the three presented leukocyte The smallest NEU:LYM ratio (mean ± SE) ratios (NEU:LYM, NEU:MAC, and PHAG:LYM) was for the NOG group (3.68 ± 0.27), and val- were different depending on the TLC category ues increased to 5.16 (±0.28) in the GP group, (P < 0.001, P < 0.001, and P = 0.01, respectively; 6.08 (± 0.78) in the OTH group, and 7.16 (± Figure 1). There was no association between parity 1.25) in the GN group (P< 0.001). No difference number and MLD; however, LYM% were greatest among pathogen groups was observed for the in early lactation (P < 0.001). Contrarily, the great- NEU:MAC ratio. The PHAG:LYM ratio varied est value for MAC% was determined in late lacta- by pathogen group with 5.79 (±0.59) in the NO tion (P = 0.009; Figure 2). Only the NEU:MAC group, 23.5 (±2.64) in the GN group, and 7.93 ratio was associated with parity, with the great- (±1.68) in the OTH, followed by 7.40 (±0.59) in est value in parity 1 (P = 0.01). Conversely, the the GP group (P < 0.001). The ratio was greater NEU:LYM ratio and the PHAG:LYM ratio in the GN group, compared with the GP group were associated with time after calving and were (P = 0.001). Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/3/231/5033002 by Ed 'DeepDyve' Gillespie user on 31 July 2018 Milk leukocyte proportions dynamics 235 Figure 1. Milk leukocyte proportions (a) and milk leukocyte ratios (b) by category of TLC. Categories within same group (leukocyte type or leukocyte ratio) with different letters indicate statistically significant difference at P < 0.05. DISCUSSION 37–38% NEU, 13–20% LYM, and 17–20% MAC. In more recent reports, NEU proportions ranged We analyzed the association between milk leu- between 6 and 50%, LYM proportions between kocyte proportions provided by a commercial auto- 14 and 80%, and MAC proportions between 12 mated MLD test and multiple cow and quarter-level and 46% (Rivas et al., 2001; Merle et al., 2007; variables. Values for milk leukocyte proportions in Koess and Hamann, 2008; Schwarz et al., 2011b). normal milk reported in previous studies are widely Interestingly, our observed distribution of white variable (Koess and Hamann, 2008; Schwarz et al., cells in milk from healthy quarters was similar to 2011b). According to some researchers, MAC are that recently described by Gonçalves et al. (2017). the predominant cell type (Leitner et al., 2000; The main cell type for healthy quarters in our study Riollet et al., 2001; Lindmark-Mansson et al., was NEU (51.4%), followed by MAC (30.1%) 2006), whereas others have indicated that LYM are and LYM (17.4%). In agreement, Gonçalves et al. the major population (Park et al., 1992; Schwarz (2017) reported NEU, MAC, and LYM percentages et al. 2011a, 2011b). in milk of culture negative udder quarters of 49.4, Mielke and Koblenz (1981) reported that milk 28.9, and 17.7%, respectively. from cows with no evidence of clinical mastitis had Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/3/231/5033002 by Ed 'DeepDyve' Gillespie user on 31 July 2018 236 Paudyal et al. Figure 2. Milk leukocyte proportions by (a) parity number (1; 2; 3; >3) and (b) stage of lactation (early [<50 DIM], middle [50–250 DIM], and late [>250 DIM]). Categories within same leukocyte type with dif- ferent letters indicate statistically significant difference at P < 0.05. Figure 3. Milk leukocyte ratios by (a) parity number (1; 2; 3; >3) and (b) stage of lactation (early [<50 DIM], middle [50–250 DIM], and late [>250 DIM]). Categories within same leukocyte ratio with differ- As reported previously (Leitner et al., 2000; ent letters indicate statistically significant difference at P < 0.05. Pillai et al., 2001; Dosogne et al., 2003; Pilla et al., 2013), stage of lactation was a significant factor 2006). Nevertheless, this difference is not observed affecting milk leukocyte proportions in our study. in affected quarters, which may be a result of Dosogne et al. (2003) found that in early lactation, inflammation during mastitis. Furthermore, in the the percentage of LYM was greater and the percent- affected quarters, NEU% were higher in rear quar- ages of mature MAC and NEU were lower than in ters, which may also be attributed to disproportion- the other stages of lactation. In another study (Pilla ate milk production. et al., 2013), percentages of mature MAC and NEU With increasing TLC levels, we observed in early lactation were only about half of the values increasing NEU% and decreasing MAC%. This found in mid and late lactation. These findings have phenomenon illustrates that MLD may be depend- not been studied in detail, but a possible explan- ent on the severity of the inflammation, as deter - ation may be that specific pathogens prevail in IMI mined here across the various levels of TLC, and at different stages of lactation, and each pathogen thus can be used to indicate a specific level of will recruit different proportions of white cell pop- inflammation in the quarter. However, in the case ulations (Leitner et al., 2000). Moreover, parity of leukocyte ratios, the patterns illustrated that number was another factor influencing the propor - the ratios can only be used to differentiate extreme tions of white cells in healthy milk. low and high categories. Nonetheless, it should be In healthy quarters, the position of quarters noted that the accuracy of cell differentiation may did not affect the MLD, as well as milk white cells be affected when TLC are greater and cell overlap- ratios; however, there were significant differences ping results on conflicting image interpretation. in the NEU:MAC ratios when quarters were cat- The association of MLD and leukocyte ratios egorized as front vs. rear. This difference in front for milk-yield categories, as observed in this study, and rear quarters may be related to greater volume suggests an effect for different milk-yield catego- of milk (about 60 vs. 40%) secreted from the rear ries. The MLD distribution in high-yield category quarter than from the front quarter (Tancin et al., is different from medium- and low-yield categories. Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/3/231/5033002 by Ed 'DeepDyve' Gillespie user on 31 July 2018 Milk leukocyte proportions dynamics 237 Thus, any mastitis detection algorithm based on As reviewed by Schwarz et al. (2011b), LYM, MLD should consider milk yield in the model to MAC, and NEU play specific roles in inflamma - best identify the alterations of MLD related to tory responses within the mammary gland. LYM infections. regulate immune responses recognizing specific antigens through membrane receptors. MAC are active-phagocytic cells, ingesting bacteria, and cel- lular debris. In addition, the release of chemoat- tractants from MAC induces the recruitment of NEU that will act against bacteria at the beginning of an acute inflammatory process. In consequence, the distribution of leukocyte numbers is important for the success of intramammary defenses against invading pathogens (Leitner et al., 2003), mak- ing plausible the idea that cell proportions would change depending on the type of pathogen and the severity and chronicity of infection. In fact, differ- ent cell patterns have been documented in the pres- ence of different pathogens and during the course of infection. In acute mastitis, NEU are the pre- dominant cell type, whereas in chronic infections, the MAC cell type is more prevalent (Leitner et al., 2003). Our results evidenced significant differences in white cell proportions between specific pathogen groups, but the magnitude of the changes was small. In agreement with our findings, Damm et al. (2017) found increased proportions of NEU and reduced proportions of MAC in quarters with elevated SCC. However, LYM remained fairly constant, which was termed as antidromic trend of NEU and MAC. In a report by Schwarz et al. (2011b), the proportion of LYM decreased from >60% at SCC Figure 4. Milk leukocyte proportions (a) and milk leukocyte ratios values <10,000 cells/mL to 18.7% when SCC was (b) by milk-yield category. Categories within same group (leukocyte 1,394,000 cells/mL. Conversely, NEU increased type or leukocyte ratio) with different letters indicate statistically sig- from <30% within the SCC range of <10,000 cells/ nificant differences at P < 0.05. Milk-yield categories: Low = <20 kg, medium = 20.1–29.0 kg, and High = >29.0 kg). mL to 63.65% at SCC of 1,394,000 cells/mL. Table 1. Milk leukocyte proportions (mean ± SE) and milk leukocyte ratios by quarter position (front vs. rear) in healthy (TLC ≤ 100,000) and affected quarters (n = 411 quarters) Parameter Front quarters Rear quarters P value TLC ≤100,000 (n = 151) NEU (%) 51.4 ± 0.02 52.5 ± 0.02 0.50 LYM (%) 17.4 ± 0.02 19.1 ± 0.02 0.21 MAC (%) 30.1 ± 0.04 26.7 ± 0.03 0.11 NEU:LYM ratio 3.47 ± 0.28 3.48 ± 0.27 0.99 NEU:MAC ratio 1.84 ± 0.25 2.64 ± 0.24 0.01 PHAG:LYM ratio 5.78 ± 0.48 5.58 ± 0.46 0.75 TLC >100,000 (n = 260) NEU (%) 58.4 ± 0.017 62.4 ± 0.02 0.03 LYM (%) 14.6 ± 0.005 14.6 ± 0.01 0.99 MAC (%) 25.0 ± 0.02 21.5 ± 0.03 0.06 NEU:LYM ratio 4.50 ± 0.17 4.62 ± 0.18 0.61 NEU:MAC ratio 4.31 ± 0.35 4.50 ± 0.35 0.71 PHAG:LYM ratio 7.12 ± 0.33 6.59 ± 0.34 0.26 Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/3/231/5033002 by Ed 'DeepDyve' Gillespie user on 31 July 2018 238 Paudyal et al. Table 2. Least square means (±SE) for total milk leukocyte counts, milk leukocyte proportions, and milk leukocyte ratios by group of mastitis-causing pathogen (n = 99 quarters) GP vs. GN Parameter NOG GN GP OTH Group P value P value TLC (cells × 1000/mL) 263 ± 11.2 39,174 ± 1,245 1,290 ± 110 2,585 ± 481 <0.001 0.16 NEU (%) 55.4 ± 0.05 52.7 ± 1.02 66.9 ± 0.05 69.0 ± 0.42 0.001 0.16 LYM (%) 16.5 ± 0.11 6.54 ± 2.18 13.4 ± 0.01 11.6 ± 0.08 <0.001 0.01 MAC (%) 26.9 ± 0.08 35.5 ± 1.85 18.3 ± 0.77 17.7 ± 0.62 0.03 0.12 NEU:LYM ratio 3.68 ± 0.28 7.16 ± 1.25 5.16 ± 0.28 6.08 ± 0.80 <0.001 0.12 NEU:MAC ratio 3.57 ± 0.66 6.86 ± 2.95 4.97 ± 0.66 7.68 ± 1.88 0.11 0.53 PHAG:LYM ratio 5.79 ± 0.59 23.6 ± 2.64 7.40 ± 0.59 7.93 ± 1.68 <0.001 <0.001 Results from our study are similar to those group. Our results are in partial agreement with observed by Gonçalves et al. (2017), who also those from Gonçalves et al. (2017) where the cell reported higher MAC% in healthy quarters than ratio Log10 (NEU:LYM) was significantly higher in quarters infected by any pathogen. The pro- in quarters infected by miscellaneous (0.62), conta- portional decrease of MAC% with increases in gious (0.57), environmental (0.53), and minor path- NEU% was evident in both studies. More in detail, ogens (0.52) than in healthy contralateral quarters Gonçalves et al. (2017) indicated that the NEU% (0.47). On the other hand, there was no difference in were greater in specific-SCM (culture positive) the cell ratio Log10 (PHAG:LYM) between healthy cases (65.7%) than in nonspecific-SCM (culture quarters (0.67) and quarters infected with miscel- negative) cases (55.2%), latent-SCM (cases with laneous (0.69), contagious (0.67), environmental culture positive but low TLC; 55.0%), and healthy (0.66), and minor pathogens (0.65). quarters (49.4%). The MAC% were lesser in quar- Pathogens included in the GN group would ters with specific-SCM (12.3%), nonspecific-SCM normally produce acute inflammation ( Wenz et al., (17.3%), and latent-SCM TLC (23.0%), when com- 2001), thus resulting in high NEU percentages and pared with healthy quarters (28.9%). The LYM very high NEU:LYM and PHAG:LYM ratios. and PHAG% were similar among tested groups, However, in our study, low percentages of LYM can but mammary quarters with specific-SCM, non - be attributed to this scenario and may be regarded specific-SCM, and latent-SCM had greater mean as characteristic feature of this type of pathogen. value of absolute number of LYM and PHAG than On the other hand, the GP group had higher pro- healthy quarters. portions of NEU and low MAC values, compared An interesting finding in our study is that the with the healthy quarters. Pathogens in the OTH change in relative proportions of leukocytes par- group normally result in chronic infections, and tially depended on the mastitis pathogen group iso- therefore, moderate higher levels of all the leuko- lated from milk. In a study presented by Emanuelson cyte are expected (Oviedo-Boyso et al., 2007). This et al. (1989), a different classification system con - peculiar behavior in GN, OTH, and GP pathogens sidering minor and major pathogen groups resulted may be a useful tool for orientating toward specific on differential SCC classifying 96 and 38% of infec- pathogen groups. tions due to minor and major pathogens correctly. It is important to notice that we had a signifi - However, in our study, when milk with GP and GN cant proportion of culture negative samples in our isolates were compared, LYM were the only pop- study. Shedding of too low numbers of pathogens ulation that indicated significant differences. This or ceased growth may be reasons for negative bac- inability for differentiating GP from GN infections, teriological results. Although epithelial cells are probably due to a smaller sample size, limits the also detected from fluorescence microscopy, their practical use of this analysis, as one the most rele- immunological function is not well established; vant applications would be to direct the therapeutic therefore, we did not consider them for analysis. approach for these groups of infections. The number of cell fractions sampled also depends All the presented cell type ratios were moder- on milk sampled because cisternal milk shows a ately elevated in affected quarters when compared reduced NEU counts, compared with alveolar milk with those from healthy cows. In the three ratios, (Pilla et al., 2012). We used squirts of milk after dis- affected quarters showing NOG had slight increase carding first few streams of the milk from the teats, while the greatest changes occurred in the GN and this could have altered our results. Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/3/231/5033002 by Ed 'DeepDyve' Gillespie user on 31 July 2018 Milk leukocyte proportions dynamics 239 J. Dairy Res. 75:225–232. doi:10.1017/S0022029908003245 Another limitation of the study was the use of Leitner, G., R. Eligulashvily, O. Krifucks, S. Perl, and pooled milk samples for microbiological culture. A. Saran. 2003. Immune cell differentiation in This is a cost-effective method that does not allow mammary gland tissues and milk of cows chron- for quarter-level discrimination. To partially address ically infected with Staphylococcus aureus. J. Vet. this problem, we considered using the MLD values Med. B. Infect. Dis. Vet. Public Health 50:45–52. doi:10.1046/j.1439-0450.2003.00602.x corresponding to greatest TLC quarter for culture Leitner, G., E. Shoshani, O. Krifucks, M. Chaffer, and positive animals and an average MLD of all four A. Saran. 2000. Milk leucocyte population patterns quarters for the culture negative animals. Although in bovine udder infection of different aetiology. J. Vet. the procedure reduced the number of quarters used Med. B. Infect. Dis. Vet. Public Health 47:581–589. for the analyses, we are more confident about the doi:10.1046/j.1439-0450.2000.00388.x values for each category. Lindmark-Mansson, H., C. Branning, G. Alden, and M. Paulsson. 2006. Relationship between somatic cell count, individual leukocyte populations and milk compo- CONCLUSION nents in bovine udder quarter milk. Int. Dairy J. 16:717– 727. doi:10.1016/j.idairyj.2005.07.003 Our results demonstrated significant differences Merle, R., A. Schröder, and J. Hamann. 2007. Cell func- in white cell proportions in different physiologi- tion in the bovine mammary gland: a preliminary cal and pathological stages of the lactating dairy study on interdependence of healthy and infected cow, although the magnitudes of the differences udder quarters. J. Dairy Res. 74:174–179. doi:10.1017/ S002202990600238X were small. Altered MLD in multiple categories of Mielke, H., and C. Koblenz. 1981. Origin and behavior of mac- TLC suggests its value in detecting mastitis of var- rophages in the milk of cows with healthy and pathologi- ying severity. Differentiable patterns in the changes cal udders. Arch. Exp. Veterinarmed. 35:1–18. in cell proportions and leukocyte ratios observed National Mastitis Council. 1999. Laboratory handbook in the presence of specific pathogen groups may on bovine mastitis. Madison (WI): National Mastitis Council; p. 1–30. provide useful information for the identification Oviedo-Boyso, J., J. J. Valdez-Alarcón, M. Cajero-Juárez, of specific causal agent groups in mastitis cases. A. Ochoa-Zarzosa, J. E. López-Meza, A. Bravo-Patiño, Additional research is necessary to determine the and V. M. Baizabal-Aguirre. 2007. Innate immune potential applications for this methodology. response of bovine mammary gland to pathogenic bac- teria responsible for mastitis. J. Infect. 54:399–409. doi:10.1016/j.jinf.2006.06.010 LITERATURE CITED Park, Y. H., L. K. Fox, M. J. Hamilton, and W. C. Davis. Damm, M., C. Holm, M. Blaabjerg, M. N. Bro, and 1992. Bovine mononuclear leukocyte subpopulations in D. Schwarz. 2017. Differential somatic cell count—a peripheral blood and mammary gland secretions dur- novel method for routine mastitis screening in the frame ing lactation. J. Dairy Sci. 75:998–1006. doi:10.3168/jds. of dairy herd improvement testing programs. J. Dairy Sci. S0022-0302(92)77842-4 100:4926–4940. doi:10.3168/jds.2016-12409 Pillai, S. R., E. Kunze, L. M. Sordillo, and B. M. Jayarao. 2001. Dohoo, I. R., A. H. Meek, S. W. Martin, and D. A. Barnum. Application of differential inflammatory cell count as a 1981. Use of total and differential somatic cell counts tool to monitor udder health. J. Dairy Sci. 84:1413–1420. from composite milk samples to detect mastitis in individ- doi:10.3168/jds.S0022-0302(01)70173-7 ual cows. Can. J. Comp. Med. 45:8–14. Pilla, R., M. Malvisi, G. G. Snel, D. Schwarz, S. König, C. Dosogne, H., F. Vangroenweghe, J. Mehrzad, A. M. Massart- P. Czerny, and R. Piccinini. 2013. Differential cell count Leën, and C. Burvenich. 2003. Differential leukocyte count as an alternative method to diagnose dairy cow mastitis. J. method for bovine low somatic cell count milk. J. Dairy Dairy Sci. 96:1653–1660. doi:10.3168/jds.2012-6298 Sci. 86:828–834. doi:10.3168/jds.S0022-0302(03)73665-0 Pilla, R., D. Schwarz, S. König, and R. Piccinini. 2012. Emanuelson, U., and P. Wever. 1989. Potential of differential Microscopic differential cell counting to identify inflam - somatic cell counts as indicators of mastitis in quarter milk matory reactions in dairy cow quarter milk samples. J. samples from dairy cows. Acta Vet. Scand. 30:475–481. Dairy Sci. 95:4410–4420. doi:10.3168/jds.2012-5331 Godden, S. M., E. Royster, J. Timmerman, P. Rapnicki, and Riollet, C., P. Rainard, and B. Poutrel. 2001. Cell subpopu- H. Green. 2017. Evaluation of an automated milk leuko- lations and cytokine expression in cow milk in response cyte differential test and the California mastitis test for to chronic Staphylococcus aureus infection. J. Dairy Sci. detecting intramammary infection in early- and late-lac- 84:1077–1084. doi:10.3168/jds.S0022-0302(01)74568-7 tation quarters and cows. J. Dairy Sci. 100:6527–6544. Rivas, A. L., F. W. Quimby, J. Blue, and O. Coksaygan. 2001. doi:10.3168/jds.2017-12548 Longitudinal evaluation of bovine mammary gland Gonçalves, J. L., R. L. Lyman, M. Hockett, R. Rodriguez, health status by somatic cell counting, flow cytome - M. V. Dos Santos, and K. L. Anderson. 2017. Using try, and cytology. J. Vet. Diagn. Invest. 13:399–407. milk leukocyte differentials for diagnosis of subclinical doi:10.1177/104063870101300506 bovine mastitis. J. Dairy Res. 84:496–497. doi:10.1017/ Sarikaya, H., G. Schlamberger, H. H. D. Meyer, and R. S0022029917000577 M. Bruckmaier. 2006. Leukocyte populations and Koess, C., and J. Hamann. 2008. Detection of mastitis in the mRNA expression of inflammatory factors in quar - bovine mammary gland by flow cytometry at early stages. ter milk fractions at different somatic cell score levels in Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/3/231/5033002 by Ed 'DeepDyve' Gillespie user on 31 July 2018 240 Paudyal et al. dairy cows. J. Dairy Sci. 89:2479–2486. doi:10.3168/jds. clinically healthy and subclinically infected bovine mam- s0022-0302(06)72322-0 mary glands. J. Dairy Sci. 94:5033–5044. doi:10.3168/ Schwarz, D., U. S. Diesterbeck, S. König, K. Brügemann, jds.2011-4348 K. Schlez, M. Zschöck, W. Wolter, and C. P. Czerny. Tancin, V., B. Ipema, P. Hogewerf, and J. Macuhova. 2006. 2011a. Microscopic differential cell counts in milk for the Sources of variation in milk o fl w characteristics at udder evaluation of inflammatory reactions in clinically healthy and quarter levels. J. Dairy Sci. 89:978–988. doi:10.3168/ and subclinically infected bovine mammary glands. J. jds.S0022-0302(06)72163–4 Dairy Res. 78:448–455. doi:10.1017/S0022029911000574 Wenz, J. R., G. M. Barrington, F. B. Garry, K. D. McSweeney, Schwarz, D., U. S. Diesterbeck, S. König, K. Brügemann, R. P. Dinsmore, G. Goodell, and R. J. Callan. 2001. K. Schlez, M. Zschöck, W. Wolter, and C. P. Czerny. Bacteremia associated with naturally occurring acute 2011b. Flow cytometric differential cell counts in coliform mastitis in dairy cows. J. Am. Vet. Med. Assoc. milk for the evaluation of inflammatory reactions in 219:976–981. doi:10.1292/jvms.13–0610 Translate basic science to industry innovation Downloaded from https://academic.oup.com/tas/article-abstract/2/3/231/5033002 by Ed 'DeepDyve' Gillespie user on 31 July 2018
Translational Animal Science – Oxford University Press
Published: Sep 1, 2018
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