Contreras‑Aguilar et al. BMC Veterinary Research (2022) 18:275 https://doi.org/10.1186/s12917-022-03371-9 RESEARCH Open Access Changes in salivary analytes in cows due to the in vitro presence of feed M. D. Contreras‑Aguilar1*, P. J. Vallejo‑Mateo2, E. Lamy3, J. J. Cerón1 and C. P. Rubio1,4 Abstract Background: The effect in a sialochemistry profile of the presence of usually available feed in dairy cows was evalu‑ ated by an in vitro experiment. For this purpose, a pooled clean saliva from five healthy dairy cows was incubated five times with a standard feed based on a total mixed ration (F), wheat hay (H), and grass (G). The salivary panel was integrated by biomarkers of stress (cortisol -sCor-, salivary alpha-amylase -sAA-, butyrylcholinesterase -BChE-, total esterase -TEA-, and lipase -Lip-), immunity (adenosine deaminase -ADA-), oxidative status (Trolox equivalent antioxi‑ dant capacity -TEAC-, the ferric reducing ability of saliva -FRAS-, the cupric reducing antioxidant capacity -CUPRAC-, uric acid, and advanced oxidation protein products -AOPP-), and enzymes, proteins, and minerals of general metabo‑ lism and markers of liver, muscle, and renal damage (aspartate aminotransferase -AST-, alanine aminotransferase -ALP-, γ-glutamyl transferase -gGT-, lactate dehydrogenase -LDH-, creatine kinase -CK-, creatinine, urea, triglycerides, glucose, lactate, total protein, phosphorus, and total calcium). Results: Most of the evaluated analytes showed a coefficient of variations (CV) higher than 15% and/or significant changes compared with the clean saliva when feed was present. Some analytes, such as the oxidative status biomark‑ ers (CV > 80%), AST (CV > 60%), or glucose (CV > 100%), showed significant changes with all the feed types tested. Oth‑ ers showed significant differences only with certain types of feed, such as LDH with F (CV > 60%) or triglycerides with F (CV > 100%) and H (CV > 95%). However, sCor or gGT remained unchanged (CV < 15%, P > 0.05) in all the treatments. Conclusions: The presence of feed can produce changes in most of the analytes measured in cows’ saliva, being of high importance to consider this factor when saliva is used as a sample to avoid errors in the interpretation of the results. Keywords: Biomarkers, Cow, Feed contamination, Saliva, Sialochemistry Background in livestock species such as dairy cows, the detection of Nowadays, saliva is a diagnostic fluid with a growing poor animal welfare conditions is necessary since they research interest to evaluate and monitor inadequate produce decreases the productivity and meat quality, welfare or stress situations in veterinary science [1] since reducing sustainable meat production, the milk yield and it can be obtained by non-invasive and non-painful tech- quality, and increasing the prevalence of metabolic dis- niques [2, 3] without specialized staff [4]. Particularly eases and the release and virulence of infectious diseases due to an immune function drop [1, 5–7]. Therefore, the use of salivary biomarkers that evaluate these states *Correspondence: mariadolores.contreras@hotmail.com could be helpfully in avoiding such undesirable situa- 1 Interdisciplinary Laboratory of Clinical Analysis of the University of Murcia tions. Indeed, recent studies in dairy cows have detected (Interlab‑UMU), Department of Animal Medicine and Surgery, Veterinary changes in salivary analytes in physiological conditions School, Regional Campus of International Excellence Campus Mare Nostrum, University of Murcia, Campus de Espinardo, 30100 Espinardo, Murcia, Spain such as the peripartum period and in diseases such as Full list of author information is available at the end of the article mastitis and lameness [8–11]. © The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://​creat​iveco​mmons.​org/​licen​ses/​by/4.​0/. The Creative Commons Public Domain Dedication waiver (http://​creat​iveco​ mmons.​org/​publi​cdoma​in/​zero/1.​0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Contreras‑Aguilar et al. BMC Veterinary Research (2022) 18:275 Page 2 of 10 However, changes in saliva color, which usually is due to the presence of feed in the oral cavity, can interfere with analytical determinations, mainly if spectrophoto- metric/colorimetric methods are employed. In addition, the feed composition could also potentially interfere with selected analytes. For example, salivary alpha-amylase (sAA) activity can increase in the presence of food with a high amount of carbohydrates in humans [12]. Recently, a study in horses showed that the presence of feed could modify the results obtained from a panel of analytes measured in saliva [13]. Despite this, no scientific evi- dence about the feed effect on salivary analytes meas- ured in the cow has been reported to the author’s best knowledge. The possible interference due to the presence of feed in the analytes measured in saliva from livestock is an important question in order to make appropriate saliva analysis and interpretation. Thus, this study aimed to investigate the potential effect of the presence of different types of feed in dairy cows in selected salivary biomark- ers previously validated in cows’ saliva [10] by an in vitro experiment. This sialochemistry profile was integrated by biomarkers of stress (salivary cortisol -sCor-, sAA, butyrylcholinesterase -BChE-, total esterase -TEA-, and lipase -Lip-); immunity (adenosine deaminase -ADA-); oxidative status (Trolox equivalent antioxidant capacity -TEAC-, the ferric reducing ability of saliva -FRAS-, the Fig. 1 Color obtained after the centrifugation of the Salivette tubes once a cows’ saliva pool and deionized water were submitted to cupric reducing antioxidant capacity -CUPRAC-, uric incubation during 5 min at 38 °C (C2) and with 250 mg of feed-based acid, and advanced oxidation protein products -AOPP-); on a standard total mixed ration usually offered to lactation cows in and enzymes, proteins, and minerals of general metabo- production (F), wheat hay (H), and grass (G) lism and biomarkers of liver, muscle, and renal damage (aspartate aminotransferase -AST-, alanine aminotrans- ferase -ALP-, γ-glutamyl transferase -gGT-, lactate dehy- difference with H = 0.858 mmol/L, CV = 114%; and mean drogenase -LDH-, creatine kinase -CK-, creatinine, urea, difference with G = 0.471 mmol/L, CV = 99%; P < 0.001), triglycerides, glucose, lactate, total protein, phosphorus, CUPRAC (mean difference with F = 0.462 mmol/L, and total calcium). CV = 99%; mean difference with H = 0.536 mmol/L, CV = 103%; and mean difference with G = 0.272 mmol/L, Results CV = 81%; P < 0.001), AOPP (mean difference with Effects of different treatments in saliva F = 383.3 µmol/L, CV = 112%; mean difference with The different treatments (addition of a standard feed H = 350.6, µmol/L CV = 109%; and mean difference with based on a total mixed ration = specimen F, wheat G = 335.6 µmol/L, CV = 108%; P < 0.01), AST (mean dif- hay = specimen H, and grass = specimen G) in the ference with F = 10.3 IU/L, CV = 84%; mean difference in vitro experiment modified the original color from the with H = 7.4 IU/L, CV = 72%; and mean difference with clean saliva control (C1) (Fig. 1a). G = 75.4 IU/L, CV = 129%; P < 0.05), and glucose (mean Most of the analytes showed significant differences difference with F = 3.91 mmol/L, CV = 140%; mean dif- between C1 and after the different treatments (Table 1), ference with H = 0.31 mmol/L, CV = 123%; and mean dif- and with variations higher than 15% of the intraassay ference with G = 0.10 mmol/L, CV = 99%; P < 0.001). coefficient of variation (CV) compared to the C1 results The analytes that did not show these variations (Fig. 2). Those mainly were TEAC (mean difference with were sCor (mean difference = 0.022 µg/dL, CV = 12%, F = 0.527 mmol/L, CV = 117%; mean difference with P = 0.100), ALP (mean difference = –0.2 IU/L, CV = 1%, H = 0.538 mmol/L, CV = 118%; and mean difference with P = 0.757), gGT (mean difference = –1.0 IU/L, CV = 3%, G = 0.267 mmol/L, CV = 101%; P < 0.001), FRAS (mean P = 0.088), and CK (mean difference = 0.0 IU/L, difference with F = 0.638 mmol/L, CV = 107%; mean CV = 0%, P > 0.999) in the treatment F; sCor (mean Contreras‑Aguilar et al. BMC Veterinary Research (2022) 18:275 Page 3 of 10 Table 1 Means and standard deviation (SD) from five replicates of the measurements of the cows’ saliva specimens labeled C1 (clean saliva), C2 (clean saliva after incubation during 5 min at 38 °C), F (saliva with a total mixed ration usefully offered to lactation dairy cows), H (saliva with wheat hay), and G (saliva with grass); and of the deionized water specimens labeled C ­ 2w (water after incubation during 5 min at 38 °C), ­Fw (water with a total mixed ration usually offered to lactation dairy cows), ­Hw (water with wheat hay), and ­Gw (water with grass) SALIVA DEIONIZED WATER C1 C2 F H G P ­value1 C2w Fw Hw Gw sCor mean 0.094 0.109 0.116 0.109 0.094 .461 0.055aa 0.050aa 0.105 0.050aa (µg/dL) SD 0.009 0.014 0.034 0.029 0.006 0.008 0.000 0.031 0.000 sAA mean 1.2 1.3 4.8b 2.5a 1.9a .001 0.2a 2.1a 0.9 1.1a (IU/L) SD 0.5 0.6 1.1 0.8 0.4 0.3 0.6 0.2 0.5 BChE mean 15.3 14.7 21.4a 14.2 22.8a .017 0.9ba 8.8ab 2.9ab 6.4aa (nmol/mL/min) SD 2.3 2.5 2.6 1.5 4.7 0.3 0.2 1.0 2.5 TEA mean 80.1 84.3 126.0c 103.8a 83.5 .006 0.0dd 13.3cb 14.8db 9.6cb (IU/L) SD 0.83 3.80 7.99 15.72 3.05 0.00 2.67 0.55 1.08 Lip mean 5.7 3.9a 0.0d 2.5 3.1b .024 3.2ab 0.0d 4.0 4.5 (IU/L) SD 0.3 0.1 0.0 2.4 0.3 0.1 0.0 5.0 0.7 ADA mean 2.2 2.0 4.2a 1.9 1.9b .003 0.1 cc 4.7b 0.5aa 0.4ba (IU/L) SD 0.0 0.1 1.2 0.7 0.2 0.1 0.4 0.5 0.3 TEAC mean 0.053 0.056 0.580c 0.591c 0.320a < .001 0.000d 0.405b 0.410b 0.688a (mmol/L) SD 0.001 0.002 0.078 0.127 0.165 0.000 0.025 0.047 0.238 FRAS (mmol/L) mean 0.101 0.095 0.739c 0.959a 0.572c < .001 0.000 cc 0.512ca 0.690a 1.466b SD 0.003 0.002 0.095 0.218 0.293 0.000 0.016 0.077 0.650 CUPRAC (mmol/L) mean 0.099 0.101 0.561d 0.635c 0.371a < .001 0.047dc 0.407da 0.485b 0.847aa SD 0.001 0.002 0.067 0.134 0.181 0.001 0.004 0.052 0.306 uric acid (µmol/L) mean 6.12 6.49 9.71c 3.78b 1.10a .001 5.12 2.38bb 0.00ba 0.00b SD 0.41 0.37 0.54 1.14 2.08 0.66 0.48 0.00 0.00 AOPP (µmol/L) mean 51.3 37.2b 434.6c 401.9b 386.9a .002 5.0cb 215.4ba 229.2b 514.3a SD 2.9 3.6 67.8 142.9 203.8 1.4 11.5 33.9 230.1 AST mean 3.5 3.1 13.8a 10.9a 78.9a .021 0.2bb 8.9a 28.7bb 322.5aa (IU/L) SD 0.6 0.2 5.6 4.3 44.8 0.3 2.9 5.2 160.3 ALP mean 22.6 17.6b 22.4 33.8 19.5b .086 1.4 cc 5.9cb 16.8a 4.5bb (IU/L) SD 0.7 0.4 2.0 13.5 0.9 0.2 1.5 8.3 2.1 gGT mean 23.6 19.0b 22.6 22.3 20.1a .063 1.5 cc 3.0 cc 2.5cb 2.4 cc (IU/L) SD 0.7 0.5 0.7 1.6 0.9 0.1 0.2 0.6 0.2 LDH mean 24.2 23.8 60.0b 24.9 24.7 .002 4.2bb 54.3a 5.6aa 3.7bb (IU/L) SD 1.8 1.9 10.4 4.9 1.7 1.9 9.8 2.8 2.6 CK mean 2.1 1.9b 2.1 3.6a 43.0c .001 0.0cb 0.4aa 2.3 55.6d (IU/L) SD 0.07 0.09 0.23 0.76 8.97 0.00 0.32 0.10 0.52 creatinine (µmol/L) mean 50.93 52.17 128.92d 91.43b 71.18a < .001 0.59 cc 77.51bb 20.63ab 25.05ca SD 0.48 1.08 6.63 14.07 11.70 1.02 3.11 10.06 1.02 urea (mmol/L) mean 3.45 3.41c 12.53d 3.68a 3.28b .002 0.00bb 11.92c 0.13ac 0.00bb SD 0.06 0.14 0.72 0.37 0.37 0.00 1.71 0.11 0.00 triglycerides (mmol/L) mean 0.13 0.18c 1.41d 0.68a 0.18b .002 0.06bb 1.38c 0.36 0.11a SD 0.00 0.01 0.12 0.40 0.01 0.01 0.04 0.15 0.02 glucose (mmol/L) mean 0.02 0.03a 3.93d 0.33a 0.13 < .001 0.00a 4.18a 0.30a 0.50aa SD 0.00 0.00 0.25 0.19 0.10 0.00 0.97 0.14 0.15 lactate (mmol/L) mean 0.28 0.35 4.57d 0.37 0.25 .001 0.03ba 4.71d 0.09ba 0.02ba SD 0.00 0.06 0.28 0.09 0.04 0.02 0.99 0.03 0.03 total protein (g/L) mean 0.52 0.51 0.89c 0.54 0.86a .014 0.01 cc 0.12bb 0.04cb 0.80 SD 0.01 0.02 0.06 0.03 0.25 0.00 0.03 0.01 0.40 Contreras‑Aguilar et al. BMC Veterinary Research (2022) 18:275 Page 4 of 10 Table 1 (continued) SALIVA DEIONIZED WATER 1 C1 C2 F H G P ­value C2w Fw Hw Gw phosphorus (mmol/L) mean 7.70 7.55 6.25b 6.90c 7.64 < .001 0.00 cd 2.38bb 0.26cb 2.24bb SD 0.13 0.08 0.34 0.31 0.13 0.00 0.20 0.13 0.51 total calcium (mmol/L) mean 0.33 0.08b 1.18d 0.53 0.19a < .001 0.00ab 3.40ba 0.79 0.93aa SD 0.08 0.01 0.07 0.17 0.06 0.00 0.51 0.37 0.23 sCor = Salivary cortisol; sAA = salivary alpha-amylase; BChE = butyrylcholinesterase; TEA = total esterase; Lip = lipase; ADA = adenosine deaminase; TEAC = Trolox equivalent antioxidant capacity; FRAS = The ferric reducing ability of saliva; CUPRAC = The cupric reducing antioxidant capacity; AOPP = Advanced oxidation protein products; AST = Aspartate aminotransferase; ALP = Alanine aminotransferase; gGT = γ-glutamyl transferase; LDH = Lactate dehydrogenase; CK = Creatine kinase 1 One-way repeated measures analysis of variance (ANOVA) study to evaluate if there were differences in the values obtained between the saliva specimens C1 (clean control saliva), C2, F, H, and G a,b,c,d Upper letters show statistical results between the saliva specimens (C2, F, H, and G) with C1 in uncorrected Fisher’s least significant difference (LSD) test for multiple comparisons: a: P < .05; b: P < .01; c: P < .001; d: P < .0001 a,b,c,d Down letters show statistical results between the water specimens ­(C2w, ­Fw, ­Hw, and G ­ w) with their homologous with saliva in uncorrected Fisher’s least significant difference (LSD) test for multiple comparisons: a: P < .05; b: P < .01; c: P < .001; d: P < .0001 difference = 0.015 µg/dL, CV = 10%; P = 0.406), BChE difference = –0.03 mmol/L, P = 0.681), glucose (mean dif- (mean difference = –1.0 nmol/mL/min, CV = 1%, ference = 0.25 mmol/L, P = 0.709), and lactate (mean dif- P > 0.999), ADA (mean difference = –0.3 IU/mL, ference = 0.14 mmol/L, P = 0.860); for the treatment H in CV = 11%, P = 0.392), gGT (mean difference = –1.3 IU/ Lip (mean difference = 1.5 IU/L, P = 0.607), TEAC (mean mL, CV = 4%, P = 0.181), LDH (mean difference = 0.7 IU/ difference = –0.181 mmol/L, P = 0.117), FRAS (mean dif- mL, CV = 2%, P = 0.389), and total protein (mean dif- ference = –0.269 mmol/L, P = 0.102), CUPRAC (mean ference = 0.02 g/L, CV = 2%, P = 0.428) in the treat- difference = –0.150 mmol/L, P = 0.169), AOPP (mean ment H; and sCor (mean difference = 0.000 µg/dL, difference = –172.7 µmol/L, P = 0.129), triglycerides CV = 0%, P > 0.999), TEA (mean difference = 3.4 IU/L, (mean difference = –0.32 mmol/L, P = 0.223), glucose CV = 3%, P = 0.085), gGT (mean difference = –3.5 IU/ (mean difference = –0.03 mmol/L, P = 0.792), and total mL, CV = 4%, P = 0.05), LDH (mean difference = 0.5 IU/ calcium (mean difference = 0.26 mmol/L, P = 0.154); and mL, CV = 2%, P = 0.248), lactate (mean differ- for the treatment G in Lip (mean difference = 1.4 IU/L, ence = –0.03 mmol/L, CV = 7%, P = 0.235), and phos- P = 0.607), TEAC (mean difference = 0.368 mmol/L, phorus (mean difference = –0.06 mmol/L, CV = 1%, P = 0.117), FRAS (mean difference = 0.894 mmol/L, P = 0.508) in the treatment G. P = 0.102), and AOPP (mean difference = 127.4 µmol/L, The clean saliva specimen incubation at 38ºC (C2) P = 0.129). produced significant changes compared to C1 (Fig. 2) in the levels of AOPP (CV = –22.5%), ALP (CV = –17.6%), triglycerides (CV = 23.8%), and total calcium Discussion (CV = –87.3%). This study evaluated the effect of feed on a sialochem- istry profile in dairy cows in order to provide scientific evidence about the conditions in which the saliva should Effects of the different treatments in water be obtained in this species. The analytes included in this The presence of F, H and G added color on the water profile are biomarkers of stress, poor welfare, or health deionized after the different treatments in the in vitro status [9, 10]. In humans, it is recommended to perform experiment (Fig. 1b) with lower intensity than on saliva the saliva sampling procedure after rinsing the individu- (Fig. 1a). als’ mouths to avoid any analytical measurement inter- The values in the water specimens compared to ferences due to the presence of food particles [14, 15]. their homologs in saliva (F vs. ­Fw, H vs. ­Hw, and G vs. In horses, the use of clean saliva is also advised to evalu- ­Gw,Table 1) were not statistically different for the treat- ate biomarkers in saliva [13]. Therefore, these authors ment F in Lip (mean difference = 0.0 IU/L, P > 0.999), hypothesized that the analytes evaluated in this sialo- ADA (mean difference = 0.5 IU/L, P = 0.461), TEAC chemistry profile could be altered due to the feed pres- (mean difference = –0.175 mmol/L, P = 0.061), AST ence in cows. However, to the author’s best knowledge, (mean difference = –4.9 IU/L, P = 0.152), LDH (mean there is no scientific evidence about this effect in measur- difference = –5.7 IU/L, P = 0.583), urea (mean differ- ing analytes in dairy cows’ saliva. ence = –0.61 mmol/L, P = 0.681), triglycerides (mean Contreras‑Aguilar et al. BMC Veterinary Research (2022) 18:275 Page 5 of 10 Fig. 2 Coefficient of variations (CVs) of the means (n = 5) from the specimens C2 (cows’ saliva pool submitted to incubation during 5 min at 38 °C), F, H, and G (cows’ saliva pool submitted to incubation with 250 mg of feed-based a standard total mixed ration, wheat hay, and grass, respectively) compared to their control clean saliva pool (specimen C1) Contreras‑Aguilar et al. BMC Veterinary Research (2022) 18:275 Page 6 of 10 Our results confirmed that most analytes included in of the feed tested in our sutdy. This would be relevant the sialochemistry profile in dairy cows were affected since ADA, gGT, and lactate in saliva have been proposed by the presence of the feed usually available for this as inflammatory biomarkers [8, 10, 23], and CK related to species. These changes could be due to various rea- the milk yield in dairy cows. sons. One would be the feed composition. For exam- In any case, it would be recommended as much as pos- ple, the broccoli remains in the total mixed ration [16], sible to obtain clean specimens when analytes are going the wheat hay, and the grass have a per se antioxidant to be measured in cows’ saliva. When mouth washing is capacity [17, 18], and their its content in glucose, fats, not possible, alternatives for obtaining clean saliva, such and minerals, among others, may cause several inter- as sampling in the milking parlor or holding cows with ferences in the analyte assays measured as previously the headgate closed before the feed is offered, are advised. observed in human [19]. A second reason could be However, the latter could stimulate the saliva production the color/turbidity change when adding the feed, as due to neuronal impulses if the feeding time is close to observed in Fig. 1, which can also interfere with the and, therefore, produce changes in the measured salivary analytical measurements, especially those measured analytes’ concentration/activity; an effect to be evaluated by spectrophotometric/colorimetric methods [20]. in the future. In addition, changes in some analytes, such as AOPP, This study has some limitations. The results obtained in ALP, triglycerides, and total calcium, in the clean saliva this report must be taken carefully since they are related control 2 (C2) could be due to the effect of the incu- to the cow population sampled and obtained under bation at 38ºC. For example, the total calcium concen- healthy status. Therefore, additional studies in other cow trations in that warmed clean saliva (C2) were much populations and diseases or stress situations must be lower (mean concentration = 0.08 ± 0.01 mmol/L) performed to check whether these changes due to the than in the clean control saliva (C1, mean concentra- feed presence produce a similar effect compared to the tion = 0.33 ± 0.08 mmol/L). It has been postulated that clean sample, and whether these variabilities could mask the salivary components and enzymes (i.e., sAA) can changes in salivary analytes due to these situations. use the initial calcium from saliva for their activities Also, in our report the incubation in vitro lasted 5 min in after being activated by the temperature [21], reducing order to take into consideration that many times feed can the total available calcium concentration in the sample. be around the buccal vestibule or under the tongue and However, further studies should evaluate the mecha- persist mixed with saliva during approximately this time. nisms that can produce these analytical variations in However, the influence of other times of incubations has cow saliva. not been evaluated. Additionally, this results’ interpreta- The changes occurring in our study due to the presence tion should not be extrapolated to another animal species of feed in cow saliva could affect the clinical interpreta- since some analytes (i.e., gGT, or phosphorus) changed tion of selected analytes when assessing pathological/ differently compared to horses when a similar experi- stressful conditions, as is the case of the Lip, oxidative mental procedure was performed [13]. status biomarkers, AST, triglycerides, glucose, or lactate measured in saliva with all or some of the feeds evalu- ated in this study, since their values changed by around Conclusions 100% compared to the clean saliva. However, there were In the conditions of this study, the cows’ saliva contami- other salivary analytes showing significant changes nation by a standard feed based on a total mixed ration, when the saliva is contaminated with feed, but whose wheat hay, and grass can produce changes in the results changes would not be clinically relevant. For instance, of salivary analytes related to welfare and health status. ADA with the total mixed ration increased from 2.2 IU/L Although saliva from diseased or stressed cows was not to 4.2 IU/L; however, it is reported median values of evaluated in this study, these changes could potentially 22.4 IU/L within the 12 first hours after calving, a situa- have an influence on the interpretation of the analytes tion in which there is an inflammatory component, com- when applied as biomarkers. Therefore, ideally, it would pared to median values of 6.1 IU/L before calving [22]. be advised to use saliva samples in cows where mouths In addition, there were analytes that showed no signifi- are as clean as possible to have consistent results. This cant changes and/or variations lower than 15% of the CV could be obtained by washing their mouth or collecting of the analyte when some of the feeds were added. This the saliva sample before the feed is offered. In the case of occurred in the sCor, ALP, gGT, phosphorus, ADA in being not possible, researchers should be aware that feed the presence of wheat hay and/or grass, CK in the total can affect selected salivary analytes measurements, and mixed ration, or lactate in the grass. Therefore, these ana- comparisons of results from different studies should take lytes would not be affected in cow saliva by the presence this fact into account. Contreras‑Aguilar et al. BMC Veterinary Research (2022) 18:275 Page 7 of 10 Materials and methods Once the saliva was obtained, sponges were placed into Cow population a commercially available saliva device (Salivette, Sarstedt, Five Holstein-Friesians cows (age range = 2–8 years; body Aktiengesellschaft & Co, Nümbrecht, Germany). They condition score range = 2.5–3) from a southeast Spain were kept on ice until arrival at the laboratory (less than commercial dairy herd (38º2´ N, 1º15´W) were enrolled one hour), where the tubes were processed as previously in this study. They were examined by an experienced vet- described [10]. Saliva specimens were stored at − 80 ◦C erinarian (PJV-M) and were considered being clinically until analysis (less than five months). healthy, with no sign of painful disorders (i.e., lameness, acute mastitis, or metritis) or discomfort after a physi- cal examination,and with normal heart and respiratory In vitro experiment rates (68.2 ± 3.37 and 32.4 ± 4.42, respectively). The dairy The clean saliva specimens previously obtained from cows were in dry period (from 45 to 15 days to expected the five cows were thawed and mixed in a pool (50 mL parturition time). They were housed in small groups of in total, approximately). Then, the clean saliva pool was 20–25 cows in sand-bedded free stalls (1.2 stalls/cow). divided into five specimens, and each one was addition- Their feeding was based on a far-off total mixed ration ally divided into × 5 replicates (Fig. 3). Specimen C1 from − 50 d relative to calving to pre-calving time offered was defined as the clean saliva control and measured ad libitum at 08:30 am. This mixed ration (supplementary without any treatment. The additional four specimens material, B) was based on (% of DM) oat silage (36.65%), were submitted to the followings treatments: 1.6 mL of oat hay (31.41%), barley -bagasse- (20.94%), rapeseed clean saliva were placed into different standard polysty- by-product (rapeseed cake) (7.33%), corn -ground- rene tubes with round bottoms (10 mL, 16 × 95 mm) and (3.14%), and a mineral premix. Its nutrient composition mixed each one with 250 mg of a standard lactating cow (% of DM, DM = 52.0%) was of N ­ EL 1.21 Mcal/kg, ADF feed (specimen F) based on broccoli -remains-, oat silage, 33.90%, NDF 44.84%, crude protein 13.87%, soluble pro- corn -ground-, barley -bagasse-, alfalfa silage, wet corn tein 4.74%, RDP 8.72%, RUP 5.15%. The farm is free of pulp, rapeseed by-product (rapeseed cake), dehydrated brucellosis, tuberculosis, Bovine Leukosis Virus, and alfalfa, dry beet pulp, non-protein hydrogen source, bar- pleuropneumonia. The cows were vaccinated for Bovine ley straw, and a mineral pre-mix (supplementary mate- Viral Diarrhea, Infectious Bovine Rhinotracheitis, Bovine rial, A), wheat hay (specimen H), and grass (specimen G), parainfluenza-3, and Bovine respiratory syncytial virus. or without any contamination with feed (specimen C2 or clean saliva control 2). The feed mixed with saliva in the F, H, and G specimens was crushed with forceps for Salivary sampling 1 min to simulate feed chewing. Then, these four speci- The saliva samplings were performed from 09:30 am to mens were incubated for 5 min at 38 °C (AccuTherm, 12:25 pm along five different days for each cow along Labnet International Inc., Madrid, Spain) since the nor- December 2020 and by the same researcher. The aver- mal adult cow rectal temperature range is 38.5–39.5 °C age temperature and humidity were 18.5 ± 2.33 °C and [25]. Finally, a polypropylene sponge was introduced 65.4 ± 15.21%, respectively. The cows were driven to each in each polystyrene tube, and it was crushed for 1 min free-stall headgate and held immobilized once closed. No for the saliva to soak up the sponge and centrifuged as feed was presented in the ground. This driving procedure described above. The recovered saliva was then used did not suppose an extra stressful situation since they are for measuring each replicate. Each replicate from each used to having these handling procedures for their rou- specimen was obtained at the same time. Additionally, an tine clinical examinations. Five minutes before the saliva identical experimental procedure was performed, replac- was obtained, cows’ mouths were washed as previously ing the saliva with deionized water for the specimens F described in horses [13] to obtain a clean sample with ­(Fw), H ­(Hw), G ­(Gw), and C2 ­(C2w). no feed interference. Then, a 5 × 2 × 2 cm polypropylene sponge (Esponja Marina, La Griega E. Koronis, Madrid, Analytical methods Spain) clipped to an independent flexible thin metal rod was introduced into the cow mouth vestibule and under The sialochemistry profile was integrated by: de tongue until thoroughly moist since the parotid and sublingual salivary glands are the most developed [24]. • Stress biomarkers. sCor, sAA, BChE, TEA, and Lip. Cows were previously accustomed to washing mouth and • Immunity biomarkers. ADA. saliva collection by an earlier performance one day before • Oxidative status biomarkers. TEAC, FRAS, the first saliva sampling. CUPRAC, uric acid, and AOPP. • Biomarkers of general metabolism and liver, muscle, and renal damage (enzymes, proteins, and minerals). Contreras‑Aguilar et al. BMC Veterinary Research (2022) 18:275 Page 8 of 10 Fig. 3 In vitro experimental workflow performed for the food effect evaluation in a profile of salivary analytes measurement in pool saliva from five cows during five different days. *Standard feed based on a total mixed ration (broccoli -remains-, oat silage, corn -ground-, barley -bagasse-, alfalfa silage, wet corn pulp, rapeseed, dehydrated alfalfa, dry beet pulp, non-protein hydrogen source, barley straw, and a mineral pre-mix) AST, ALP, gGT, LDH, CK, creatinine, urea, triglycer- chemiluminescent immunoassay system (Immulite 1000, ides, glucose, lactate, total protein, phosphorus, and Siemens Healthcare Diagnostic, Deerfield, IL, USA). All total calcium. these assays were adapted to saliva and previously vali- dated in cow saliva [9, 10]. All the analytes involved in this salivary profile were analyzed on an automated chemistry analyzer (Olympus Statistical analysis Diagnostica GmbH AU 400, Beckman Coulter, Ennis, To evaluate if there were differences in the values Ireland) using commercial kits from Beckman (Beck- obtained between the specimens C1 (clean control saliva), man Coulter Inc., Fullerton, CA, USA), except for BChE C2, F, H, and G, a one-way repeated measures analysis of and TEA, which were measured according to previously variance (ANOVA) and an uncorrected Fisher’s least sig- reported assays [26, 27], ADA, which was measured nificant difference (LSD) test for multiple comparisons with a Diazyme kit (ADA-D assay kit, Diazyme Labo- was performed to determine what specimens showed ratories, Poway, CA, USA); TEAC, FRAS, CUPRAC, statistically different values to C1 specimen. Addition- and AOPP, which were assessed in saliva according to ally, another Fisher’s LSD test was calculated to analyze if Rubio et al., [28], and total proteins, which it was meas- there would be differences between the saliva specimens ured by a commercial colorimetric kit to measure urine with their homologous with water ­(C2w, ­Fw, ­Hw, and ­Gw). and cerebrospinal fluid (CSF) proteins (protein in urine Data were checked for normality using the Shapiro–Wilk and CSF, Spinreact, Spain). sCor was analyzed using a normality test previous to the analysis. The biomarkers Contreras‑Aguilar et al. BMC Veterinary Research (2022) 18:275 Page 9 of 10 showing non-normal distribution (BChE, ADA, uric Availability of data and materials The datasets generated and/or analyzed during the current study are not acid, AST, creatinine, lactate, and total protein) were public due to legal reasons but available from the corresponding authors on then base-e log-transformed [29] to restore normality. A reasonable request. P-value < 0.05 was considered as being statistically signifi- cant. The statistical analyses were calculated using Graph Declarations Pad Software Inc. (GraphPad Prism, version 9.1.0 for Ethics approval and consent to participate macOS; Graph Pad Software Inc., San Diego, CA, USA). The Bioethical Committee (“Comité Ético de Experimentación Animal”, CEEA) The CV (%) of the means from specimens C2, F, H, from Murcia University (Spain) with the number 171/2015 approved this and G compared to C1 was calculated as the following study. The experimental protocol followed the European Directive 2010/63/EU concerning the protection of animals used for scientific purposes. formula: Consent for publication SD(xC1, xx) × 100 Not applicable. ± x(xC1, xx) Competing interests where x C1 was the arithmetic mean from the × 5 repli- The authors declare that they have no competing interests. cates measured from specimen C1, and xXthe arithmetic Author details mean from the × 5 replicates measured from specimens 1 Interdisciplinary Laboratory of Clinical Analysis of the University of Murcia C2, F, H, or G. Positive ( +) or negative (–) CV value indi- (Interlab‑UMU), Department of Animal Medicine and Surgery, Veterinary School, Regional Campus of International Excellence Campus Mare Nostrum, cates that the average value obtained from specimens University of Murcia, Campus de Espinardo, 30100 Espinardo, Murcia, Spain. C2, F, H, or G were higher or lower from specimen C1, 2 Department of Animal Medicine and Surgery, Veterinary School, Regional respectively. Campus of International Excellence Campus Mare Nostrum, University of Mur‑ cia, Campus de Espinardo, 30100 Espinardo, Murcia, Spain. 3 MED Mediter‑ CV higher than 15% between the mean values from ranean Institute for Agriculture, Environment and Development, IIFA Instituto each saliva treatment and the mean values obtained from de Investigação e Formação Avançada, University of Évora, Núcleo da Mitra, specimen C1 (clean saliva) were considered high enough Apartado 94, 7006‑554 Évora, Portugal. 4 Department of Animal and Food Science, School of Veterinary Science, Universitat Autònoma de Barcelona, to show imprecise values [30]. Therefore, they were con- 08193 Cerdanyola del Vallès, Barcelona, Spain. sidered as specimens in which interference has occurred. Received: 4 October 2021 Accepted: 4 July 2022 Abbreviations sAA: Salivary alpha-amylase; sCor: Salivary cortisol; BChE: Butyrylcholinester‑ ase; TEA: Total esterase; Lip: Lipase; ADA: Adenosine deaminase; TEAC: Trolox equivalent antioxidant capacity; FRAS: The ferric reducing ability of saliva; References CUPRAC​: The cupric reducing antioxidant capacity; AOPP: Advanced oxidation 1. García Pinillos R, Appleby MC, Manteca X, Scott-Park F, Smith C, Velarde A. protein products; AST: Aspartate aminotransferase; ALP: Alanine aminotrans‑ One Welfare - A platform for improving human and animal welfare. Vet ferase; gGT: γ-Glutamyl transferase; LDH: Lactate dehydrogenase; CK: Creatine Rec. 2016;179:412–3. https://​doi.​org/​10.​1136/​vr.​i5470. kinase; CV: Coefficient of variation; ANOVA: Analysis of variance; LSD: Least 2. Tvarijonaviciute A, Martínez-Subiela S, López-Jornet P, Lamy E. Saliva significant difference. in Health and Disease The Present and Future of a Unique Sample for Diagnosis. 1st edition. Switzerland: Springer, Cham; 2020. doi: https://​doi.​ org/​10.​1007/​978-3-​030-​37681-9. Supplementary Information 3. Burnett TA, Madureira AML, Silper BF, Nadalin A, Tahmasbi A, Veira DM, The online version contains supplementary material available at https://​doi.​ et al. Short communication: Factors affecting hair cortisol concentrations org/​10.​1186/​s12917-​022-​03371-9. in lactating dairy cows. J Dairy Sci. 2014;97:7685–90. https://​doi.​org/​10.​ 3168/​jds.​2014-​8444. 4. Lamy E, Mau M. Saliva proteomics as an emerging, non-invasive tool Additional file 1. to study livestock physiology, nutrition and diseases. J Proteomics. 2012;75:4251–8. https://​doi.​org/​10.​1016/j.​jprot.​2012.​05.​007. Acknowledgements 5. Velarde A, Fàbrega E, Blanco-Penedo I, Dalmau A. Animal welfare towards Not applicable. sustainability in pork meat production. Meat Sci. 2015;109:13–7. https://​ doi.​org/​10.​1016/j.​meats​ci.​2015.​05.​010. Authors’ contributions 6. Grandin T. Reducing Handling Stress Improves Both Productivity and All authors contributed to the study design, data analysis and interpretation, Welfare. Prof Anim Sci. 1998;14:1–10. preparation, and approval of the manuscript. Additionally, PJV-M and MDC-A 7. Cavallini D, Mammi LME, Buonaiuto G, Palmonari A, Valle E, Formigoni A. contributed to data collection. MDC-A and CPR contributed particularly to Immune-metabolic-inflammatory markers in Holstein cows exposed to a study design, data analysis preparation of the manuscript, and interpretation. nutritional and environmental stressing challenge. J Anim Physiol Anim PJV-M, EL, JJC, and CPR contributed particularly to study design and data Nutr (Berl). 2021;105:42–55. interpretation. All authors read and approved the final manuscript. 8. Contreras-Aguilar MD, Monkeviciene I, Ceron JJ, Silinskas I, Vallejo-Mateo PJ, Tecles F, et al. Biochemical changes in saliva of cows with inflamma‑ Funding tion: A pilot study. Res Vet Sci. 2019;124:383–6. https://​doi.​org/​10.​1016/j.​ This work was supported by the Seneca foundation of Murcia Regional Gov‑ rvsc.​2019.​04.​019. ernment, Spain (grant number 19894/GERM/15). 9. Contreras-Aguilar MD, Vallejo-Mateo PJ, Želvytè R, Tecles F, Rubio CP. Changes in Saliva Analytes Associated with Lameness in Cows: A Pilot Study. Animals. 2020;10:2078. https://​doi.​org/​10.​3390/​ani10​112078. Contreras‑Aguilar et al. BMC Veterinary Research (2022) 18:275 Page 10 of 10 10. Contreras-Aguilar MD, Vallejo-mateo PJ, Lamy E, Cer JJ, Tecles F, Rubio 29. Rohleder N, Nater UM. Determinants of salivary α-amylase in humans CP. Changes in Saliva Analytes in Dairy Cows during Peripartum : A Pilot and methodological considerations. Psychoneuroendocrinology. Study. Animals. 2021;11:749. https://​doi.​org/​10.​3390/​ani11​030749. 2009;34:469–85. https://​doi.​org/​10.​1016/j.​psyne​uen.​2008.​12.​004. 11. Drackley JK. Biology of Dairy Cows During the Transition Period: the Final 30. Food and Drug Administration. Guidance for Industry: Bioanalytical Frontier? J Dairy Sci. 2010;82:2259–73. https://​doi.​org/​10.​3168/​jds.​s0022-​ Method Validation. U.S.: Department of Health and Human Services; 0302(99)​75474-3. 2001. 12. Strahler J, Skoluda N, Kappert MB, Nater UM. Simultaneous measurement of salivary cortisol and alpha-amylase: Application and recommenda‑ tions. Neurosci Biobehav Rev. 2017;83 August:657–77. doi:https://​doi.​org/​ Publisher’s Note 10.​1016/j.​neubi​orev.​2017.​08.​015. Springer Nature remains neutral with regard to jurisdictional claims in pub‑ 13. Contreras-Aguilar MD, Luisa M, Escribano D, Lamy E, Tecles F, Cerón JJ. lished maps and institutional affiliations. Effect of food contamination and collection material in the measurement of biomarkers in saliva of horses. Res Vet Sci. 2020;129:90–5. https://​doi.​ org/​10.​1016/j.​rvsc.​2020.​01.​006. 14. Sondej M, Denny PA, Xie Y, Ramachandran P, Si Y, Takashima J, et al. Glyco‑ profiling of the Human Salivary Proteome. Clin Proteomics. 2009;5:52–68. https://​doi.​org/​10.​1007/​s12014-​008-​9021-0. 15. DeCaro JA. Methodological Considerations in the Use of Salivary α-Amylase as a Stress Marker in Field Research. Am J Hum Biol. 2008;20:617–9. https://​doi.​org/​10.​1002/​ajhb.​20795. 16. Leja M, Mareczek A, Starzyńska A, Rozek S. Antioxidant ability of broccoli flower buds during short-term storage. Food Chem. 2001;72:219–22. https://​doi.​org/​10.​1016/​S0308-​8146(00)​00224-7. 17. Arora DS, Sharma RK, Chandra P. Biodelignification of wheat straw and its effect on in vitro digestibility and antioxidant properties. Int Biodeterior Biodegrad. 2011;65:352–8. https://​doi.​org/​10.​1016/j.​ibiod.​2010.​12.​009. 18. Esfandi R, Walters ME, Tsopmo A. Antioxidant properties and potential mechanisms of hydrolyzed proteins and peptides from cereals. Heliyon. 2019;5: e01538. https://​doi.​org/​10.​1016/j.​heliy​on.​2019.​e01538. 19. Nunes LAS, De MDV. Saliva as a diagnostic fluid in sports medicine: Potential and limitations. J Bras Patol e Med Lab. 2013;49:247–55. https://​ doi.​org/​10.​1590/​S1676-​24442​01300​04000​03. 20. Franco-Martínez L, Peres CR, Contreras-Aguilar MD. Methodology Assays for the Salivary Biomarkers’ Identification and Measurement. In: Saliva in Health and Disease The Present and Future of a Unique Sample for Diagnosis. 2020. p. 67–95. doi: doi: https://​doi.​org/​10.​1007/​ 978-3-​030-​37681-9_4. 21. Contreras-Aguilar MD, Gómez-García F. Salivary Glands’ Anatomy and Physiology. In: Tvarijonaviciute A, Martínez-Subiela S, López-Jornet P, Lamy E, editors. Saliva in Health and Disease: The Present and Future of a Unique Sample for Diagnosis. Cham: Springer International Publishing; 2020. p. 3–21. doi:https://​doi.​org/​10.​1007/​978-3-​030-​37681-9_1. 22. Contreras-Aguilar MD, Tvarijonaviciute A, Monkeviciene I, Martín-Cuervo M, González-Arostegui LG, Franco-Martínez L, et al. Characterization of total adenosine deaminase activity (ADA) and its isoenzymes in saliva and serum in health and inflammatory conditions in four different species: An analytical and clinical validation pilot study. BMC Vet Res. 2020;16:384. https://​doi.​org/​10.​1186/​s12917-​020-​02574-2. 23. Franco-Martinez L, Muñoz-Prieto A, Contreras-aguilar MD, Želvytė R, Monkevičienė I, Horvatić A, et al. Changes in saliva proteins in cows with mastitis: A proteomic approach. Res Vet Sci. 2021. https://​doi.​org/​10.​ 1016/j.​rvsc.​2021.​08.​008. 24. Vázquez-Autón J, Gil-Cano F, Latorre-Reviriego R, Ramírez-Zarzosa G, López-Albors O, Ayala-Florenciano M, et al. Manual de Prácticas de Anato‑ mía Veterinaria: Sistemas Viscerales. 1st ed. Murcia: Diego Marín; 2002. 25. Araki CT, Nakamura RM, Kam LWG, Clarke N. Effect of Lactation on Diurnal Temperature Patterns of Dairy Cattle in Hot Environments. J Dairy Sci. Ready to submit your research ? Choose BMC and benefit from: 1984;67:1752–60. https://​doi.​org/​10.​3168/​jds.​S0022-​0302(84)​81501-5. 26. Tecles F, Cerón JJ. Determination of whole blood cholinesterase in differ‑ • fast, convenient online submission ent animal species using specific substrates. Res Vet Sci. 2001;70:233–8. https://​doi.​org/​10.​1053/​rvsc.​2001.​0465. • thorough peer review by experienced researchers in your field 27. Tecles F, Contreras-Aguilar MD, Martínez-Miró S, Tvarijonaviciute A, Mar‑ • rapid publication on acceptance tínez-Subiela S, Escribano D, et al. Total esterase measurement in saliva • support for research data, including large and complex data types of pigs: Validation of an automated assay, characterization and changes in stress and disease conditions. Res Vet Sci. 2017;114:170–6. https://​doi.​ • gold Open Access which fosters wider collaboration and increased citations org/​10.​1016/j.​rvsc.​2017.​04.​007. • maximum visibility for your research: over 100M website views per year 28. Rubio CP, Contreras-Aguilar MD, Quiles A, López-Arjona M, Cerón JJ, Martínez-Subiela S, et al. Biomarkers of oxidative stress in saliva of sheep: At BMC, research is always in progress. Analytical performance and changes after an experimentally induced stress. Res Vet Sci. 2019;123. doi: https://​doi.​org/​10.​1016/j.​rvsc.​2018.​12.​ Learn more biomedcentral.com/submissions 015.