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DI/LC-MS/MS-based metabolic profiling for identification of early predictive serum biomarkers of metritis in transition dairy cows Guanshi Zhang, Qilan Deng, Rupasri Mandal, David S. Wishart, and Burim N. Ametaj J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b02000 • Publication Date (Web): 01 Sep 2017 Downloaded from http://pubs.acs.org on September 3, 2017

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Journal of Agricultural and Food Chemistry

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DI/LC-MS/MS-based metabolic profiling for identification of early predictive

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serum biomarkers of metritis in transition dairy cows

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Guanshi Zhang,†- Qilan Deng†-, Rupasri Mandal,‡ David S. Wishart,‡ and Burim N. Ametaj*,†

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†

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‡

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Canada

Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada Departments of Biological Sciences and Computing Science, University of Alberta, Edmonton, AB T6G 2E9,

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*Corresponding author: [email protected]; Tel: 780-492-9841; Fax: 780-492-4265

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-The first two authors contributed equally to this manuscript.

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ACS Paragon Plus Environment


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ABSTRACT: The objectives of this study were to evaluate alterations of metabolites in the

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blood of dairy cows before, during, and after diagnosis of metritis and identify predictive serum

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metabolite biomarkers for metritis. DI/LC-MS/MS was used to analyze serum samples collected

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from both healthy and metritic cows during -8, -4, disease diagnosis, +4 and +8 wks relative to

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parturition. Results indicated that cows with metritis experienced altered concentrations of serum

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amino acids, glycerophospholipids, sphingolipids, acylcarnitines, and biogenic amines during the

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entire experimental period. Moreover, two sets of predictive biomarker models and one set of

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diagnostic biomarker model for metritis were developed and all of them showed high sensitivity

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and specificity (e.g., high AUC values by the ROC curve evaluation), which indicate that serum

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metabolites identified have pretty accurate predictive, diagnostic, and prognostic abilities for

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metritis in transition dairy cows.

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KEYWORDS: Metritis, dairy cow, metabolomics, biomarkers, amino acids, sphingolipids

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INTRODUCTION

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Metritis is defined as the inflammation of uterus involving endometrium, myometrium and

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serosa, usually characterized by fetid reddish-brown vaginal discharge.1 In dairy cows it usually

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occurs within 21 days after parturition. Metritis affects as an average almost 40% of dairy cows

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in a herd.2 Cows with metritis have lower conception rates and longer days open and hence a

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greater risk of culling. Even after successful treatment, metritic cows are less fertile compared

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with their herdmates.2 Consequently, it is crucial and important to identify the susceptible cows

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and take appropriate measures to prevent development of metritis.

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Several studies have shown association between changes of some blood variables and the

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likelihood of occurrence of metritis. It was reported that beta-hydroxybutyrate (BHBA) in the

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serum greater than 1,200 to 1,400 micromol/L during the first or second week after calving is

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associated with increased risk of metritis.3 Moreover, cows with serum non-esterified fatty acids

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(NEFA) greater than or equal to 0.3 mEq/L at one week before calving were more likely to

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develop metritis after calving than cows with lower concentrations of NEFA.4

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Beside lipid metabolites, blood haptoglobin level greater than or equal to 1 g/L is associated

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with 6.7 times more likelihood of developing metritis.5 However, these studies were focused on a

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single or a few metabolites which could also be associated with other diseases, thus, lacking

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specificity and accuracy for its prediction. For example, greater concentration of BHBA (>1,200

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to 1,400 µM/L) is also associated with clinical ketosis and displaced abomasum.3 Moreover,

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cows with greater concentrations of non-esterified fatty acids (NEFA) (≥ 0.3 mEq/L) in the

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serum are also more likely to develop fatty liver and retained placenta.4 Cows with fatty liver

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could also have increased haptoglobin, serum amyloid A (SAA), and NEFA.6

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Metabolomics, the latest ‘omics’ science, can give an instantaneous and comprehensive

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snapshot of the physiological state of a certain biological sample through its global metabolite

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profiling. Analytical technologies based on liquid chromatography coupled to tandem mass

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spectrometry (LC-MS/MS) are becoming a major source of global metabolite profiling data due

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to the ability to measure multiple components in one run with high specificity and sensitivity

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which is cost-effective and holds the potential to be employed for analyzing drug- or disease-

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associated metabolic changes and identification of screening biomarkers. Recently, our group

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identified 3 metabolites (carnitine, propionyl carnitine, and lysophosphatidylcholine acyl C14:0)

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that separated cows affected by multiple diseases from the healthy ones at 4 wks before

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parturition with a sensitivity of 87% and a specificity of 85% by employing direct flow injection

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and mass spectrometry.7 In order to better understand the pathobiology of metritis and be more

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disease specific, this study was aimed to screen potential serum metabolites that could be used to

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identify susceptible dairy cows to metritis before the onset of disease using a combination of

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direct injection and tandem mass spectrometry (DI-MS/MS) with a reverse-phase LC-MS/MS.

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The objectives of this study were to profile the metabolic state of dairy cows (i.e., metabotyping)

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before, during, and after the diagnosis of metritis in order to identify metabolic signatures of

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metritis, better understand the pathobiology of the disease as well as to identify potential

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screening, and diagnostic biomarkers of the disease.

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MATERIALS AND METHODS

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This study was part of a large project designed to study the pathobiology of periparturient

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diseases of transition dairy cows and also to identify potential predictive biomarkers of those

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diseases. All experimental procedures were approved by the University of Alberta Animal Policy

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and Welfare Committee for Livestock and animals were cared for in accordance with the

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guidelines of the Canadian Council on Animal Care (1993).8 Data related to concentrations of

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serum cytokines and acute phase proteins, dry matter intake (DMI), milk production and milk

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composition for this experiment have been reported previously.9 The metabolomics analyses

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were performed at the Metabolomics Innovation Centre, University of Alberta, Edmonton, AB,

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Canada.

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Animals and Diets. One hundred pregnant Holstein dairy cows were used in this study. All

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cases with metritis were diagnosed by an experienced veterinary practitioner. Monitoring of the

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health status and the procedure for diagnosis of metritis are provided in the Supporting

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Information. Six pregnant multiparous (parity: 2.7 ± 0.7, Mean ± SEM) Holstein dairy cows with

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metritis and 20 healthy control cows (CON) that were similar in parity (3.3 ± 0.6; P = 0.60) and

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body condition score (BCS), were selected for this nested case-control study.

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The total experimental period for each cow was 16 wks starting from -8 wks before

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parturition until +8 wks postpartum. Information about rations used are provided in the

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Supplementary Tables 1 and 2. Total mixed rations (TMR) were formulated to meet or exceed

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nutrient requirements of a 680 kg lactating cows as per NRC guidelines (2001).10

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Blood Sample Collection. For this study, blood samples were obtained from the coccygeal

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veins of 100 transition dairy cows (-8 to +8 wks around calving) and 26 of them were

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retrospectively selected for further analyses. Cows that were affected by another or multiple

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periparturient diseases at the same time were excluded from further analyses. Twenty cows out of

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a total of 26 selected were completely healthy cows, with no clinical signs of any disease

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(control cows - CON) and 6 cows were diagnosed postpartum as metritic cows. Cows with

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metritis had no other concurrent diseases. Blood samples were obtained once per week at 0700

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before feeding at -8 wks (53-59 d), -4 wks (25-31 d), disease wk (+1 to +3 wk; 8-21 d), +4 wks

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(25-31 d) and +8 wks (53-59 d) around calving.

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DI/LC-MS/MS Compound Identification and Quantification. A targeted quantitative

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metabolomics commercial kit (AbsoluteIDQ 180, BIOCRATES Life Science AG, Innsbruck,

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Austria) was applied for identification and quantification of serum metabolites. The kit assay was

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run on an ABI 4000 Q-Trap (Applied Biosystems/MDS Sciex, Foster City, CA) mass

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spectrometer. In total, the kit can identify and quantify 186 different endogenous metabolites

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including amino acids (AAs), acylcarnitines, biogenic amines (BAs), phospho- and

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sphingolipids, and hexoses could be quantified. Please refer to the ‘Supporting Information’ as

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well as at Zhang et al. (2017) for a more detailed information on DI/LC-MS/MS analysis of

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serum samples.11

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Statistical Analysis. Univariate analysis was performed using Wilcoxon-Mann-Whitney

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(rank sum) test provided by R (Version 3.0.3, R Development Core Team, 2008). Statistical

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significance was declared at P < 0.05. Multivariate analysis and biomarker analysis were

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processed and analyzed by the MetaboAnalyst software.12 Recommended statistical procedures

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for metabolomics analysis were followed according to previously published protocols.12 A more

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detailed description of the protocols used for statistical analyses are presented in ‘Supporting

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Information’.

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RESULTS

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Metabolomics analysis using DI/LC-MS/MS was performed for 6 cases of metritis and 20 CON

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cows. A total of 128 out of 186 metabolites were identified and quantified using an in-house

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mass-spectrometry library. The species of metabolites measured can be classified into six groups:

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AAs (21), biogenic amines (8), glycerophospholipids (77), sphingolipids (14), acylcarnitines (7),

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and hexose (1). By a combination of univariate and multivariate analyses, we compared the

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metritic group with the CON group at five time points separately. A total of 55, 58, 35, 79, and

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46 metabolites were identified to have significant concentration differences in the serum at -8

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wks, -4 wks, disease diagnosis, +4 wks, and +8 wks, respectively, around the expected day of

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parturition between the two groups. The mean ± SEM concentration values, P values along with

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the fold change and direction of change in metritic cases relative to CON cows are provided in

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Table 1 and Supplementary Table 3.

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Metabolic alterations before disease diagnosis. Results of the univariate analysis indicated

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that a total of 55 and 58 metabolites in the serum were significantly different at -8 and -4 wks

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between the two groups. Specifically, one acylcarnitine, 25 glycerophospholipids, 10

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sphingolipids, and 15 AAs were elevated, whereas one glycerophospholipid, one sphingolipid

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and two AAs were lowered in the serum of pre-metritic cows at -8 wks prepartum (Table 1).

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Similar alterations were observed during the -4 wks before occurrence of metritis with one

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acylcarnitine, 36 glycerophospholipids, five sphingolipids, and 15 AAs increased and one

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sphingolipid decreased in premetritic cows versus the CON ones (Table 1).

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Multivariate analysis showed that when data from CON cows were compared with those

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from premetritic cows at -8 and -4 wks, both PCA and PLS-DA had two separate clusters at two

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time points (Figure 1A,B; Figure 2A,B). Permutation testing (P < 0.05) revealed that the

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observed separation was not by chance and the results of cross validation were reliable. A VIP

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plot of the PLS-DA from -8 and -4 wks in which the metabolites were ranked based on their

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contribution to discriminating the premetritic cows from CON ones are shown in Figure 1C and

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2C. The top 15 important metabolites are shown in the VIP plots. The greater the distance from

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the Y-axis (i.e., the greater the VIP value), the greater the contribution of a particular metabolite

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in distinguishing premetritic cows from CON ones. The VIP plots indicated that lysine (Lys),

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lysophosphatidylcholine acyl C17:0 (lysoPC a C17:0), lysophosphatidylcholine acyl C18:0

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(lysoPC a C18:0), isoleucine (Ile), and lysophosphatidylcholine acyl C16:0 (lysoPC a C16:0) at -

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8 wks and Lys, Ile, Leu, sphingomyelin C20:2 (SM C20:2), and lysoPC a C17:0 at -4 wks were

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the strongest discriminating metabolites for separating metritis cases from the CON cows. The

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heat map on the right side of the two VIP plots indicates that 14 metabolites were increased and

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one metabolite (i.e., SM C20:2) was decreased in pre-metritis cows relative to CON ones. A

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ROC curve plot showing the performance of the top five metabolites in predicting which cows

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will develop metritis at -8 wks (empirical P = 0.001) and -4 wks (empirical P = 0.001) using a

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PLS-DA model are shown in Figure 1D and 2D. The AUC for two curves are 0.995 (95% CI,

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0.945-1) at -8 wks and 0.992 (95% CI, 0.938-1) at -4 wks, respectively, which indicates that

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these serum biomarkers have strong predictive abilities. Interestingly, none of the six cows

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affected by metritis postpartum exhibited clinical signs of sickness before parturition, although

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systemically the disease processes preceded at least -8 wks prior to parturition. Moreover, these

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results also demonstrate that biomarker models developed at -8 and -4 wks could be used to

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predict which cows are susceptible to develop metritis postpartum.

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Metabolic alterations during the week of diagnosis of metritis. A total of 35 metabolites

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in the serum were different during the wks of diagnosis of metritis between the two groups by

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univariate analyses. Cows with metritis experienced elevated concentrations of three

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acylcarnitines, seven glycerophospholipids, six sphingolipids, and 16 AAs in the serum (Table

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1). In addition, two acylcarnitines and one glycerophospholipid were decreased in metritic cows

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(Table 1).

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When metritic cows were compared with CON ones at the disease wk, unsupervised

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multivariate analysis PCA and supervised multivariate analysis PLS-DA (permutation testing: P

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< 0.05) once again revealed a distinctive separation between the two groups of cows (Figure

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3A,B). In this case, five metabolites [i.e., Lys, Ile, Leu, kynurenine (Kyn), and

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phosphatidylcholine acyl-alkyl C30:1 (PC ae C30:1)] with greatest VIP scores contributed most

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significantly to the observed separation (Figure 3C). The ROC curve (Figure 3D; empirical P =

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0.001) indicated that these metabolite combinations were highly significant biomarkers of

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metritis: AUC, 0.988 (95% CI, 0.913-1).

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Metabolic alterations after diagnosis of metritis. After recovery from metritis, cows that

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were affected by metritis still continued to have alterations of serum metabolites at +4 and +8

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wks after parturition in comparison with CON cows. Interestingly even though postmetritic cows

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were healthy in appearance at +4 wks after parturition, they still had 79 metabolites altered in the

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serum compared to CON cows. In particular, all of the 79 metabolites (i.e., two acylcarnitines, 54

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glycerophospholipids, 12 sphingolipids, and 11 AAs) were elevated in postmetritic cows at +4

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wks postpartum. Intriguingly, during the +8 wks after parturition, postmetritic cows continued to

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have alterations of 46 metabolites, including 44 (i.e., 24 glycerophospholipids, nine

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sphingolipids, and 11 AAs) enhanced and two (i.e., Asn and Asp) decreased (Supplementary

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Table 3).

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Multivariate analyses [i.e., PCA and PLS-DA (permutation testing: P < 0.05) revealed that

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CON cows and postmetritic cows clearly separated at +4 and +8 wks postpartum (Supplementary

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Figure 1B; Supplementary Figure 2A,B). The corresponding VIP plots for these two time points

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are shown in Supplementary Figure 1C and 2C, which indicated that Lys, Ile, Leu, lysoPC a

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C17:0, and lysoPC a C16:0 were the most discriminating metabolites at +4 wks and Lys, Ile,

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Leu, acetylornithine, and Phe were the top five metabolites for the separation of clusters at +8

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wks. Multivariate models (ROC curves) combining five discriminating metabolites (i.e., Lys, Ile,

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Leu, lysoPC a C17:0, and lysoPC a C16:0) at +4 wks (empirical P < 0.05) and five metabolites

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(i.e., Lys, Ile, Leu, acetylornithine, and Phe) at +8 wks (empirical P < 0.05) produced an area

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under the receiver-operating curve of 1 (95% CI: 1-1, Supplementary Figure 1D) and 0.99 (95%

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CI: 1-1, Supplementary Figure 2D), respectively.

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It is interesting to note that throughout the 17-wks of the study, 13 serum metabolites [i.e.,

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PC aa C30:0, PC aa C30:2, PC aa C32:2, PC ae C30:1, hydroxysphingomyelin C24:1 (SMOH

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C24:1), sphingomyelin C24:0 (SM C24:0), SM C26:0, His, Ile, Leu, Lys, acetylornithine, and

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Kyn) appeared to play a consistent role in distinguishing between the CON and metritic cows

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(Table 1 and Supplementary Table 3).

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DISCUSSION

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We hypothesized that cows susceptible to metritis might have characteristic serum metabolite

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signatures before, during, and after the occurrence of the disease. Consistent with this

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hypothesis, this study was designed to metabotype periparturient dairy cows before (at -8 and -4

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wks prepartum), during (disease wk), and after (at +4 and +8 wks postpartum) the occurrence of

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metritis and screen for metabolite signatures that can be used to monitor cows at risk of metritis

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and to better understand the pathomechanism of the disease. Indeed, using a targeted quantitative

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metabolomics approach, the data showed that premetritic, metritic, and postmetritic cows and

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CON ones could be distinguished from the concentrations of selected serum amino acids (AAs),

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glycerophospholipids, sphingolipids, biogenic amines, and acylcarnitines throughout the

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experimental period. More specifically, there were 13 serum metabolites including PC aa C30:0,

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C30:2, C32:2, and PC ae C30:1, SMOH C24:1, SM C24:0 and C26:0, His, Ile, Leu, Lys,

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acetylornithine, and Kyn showing consistent differences between the metritic and CON cows

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throughout the experimental period. The discussion that follows will be focused on the main

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identified groups of metabolites that characterize premetritic and metritic cows.

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Phosphatidylcholines (PC aa and PC ae) were the group of glycerophospholipid compounds

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that had the highest number of altered metabolites in the serum of premetritic and metritic cows

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with PC aa having 12, 18, 4, 26, and 11 species and PC ae having 8, 13, 1, 22, and 10 species

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altered during -8, -4, disease wk, +4, and +8 wks around calving, respectively. All but one

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species of both PC aa and PC ae were increased in the serum of premetritic and metritic cows.

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Although the number of PC species altered was high there were only three PC compounds that

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were found to be altered during all five time points studied including PC aa C30:0, C30:2, and

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C32:2. Additionally, the most dominant species of PC in the serum of all cows including metritic

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and CON were PC aa C36:2, C34:2, and C34:1. Most elevated PC species contained unsaturated

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long-chain fatty acids. Similar findings with regards to increased serum concentrations of

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multiple PC species were reported in mice and human subjects with endometriosis.13,14 The same

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authors also reported that multiple species of SMs and lysoPCs were increased in subjects with

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endometriosis.

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A large number of SMs were found to be greater in metritic cows including 11, 6, 6, 12, and

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9 species during -8, -4, metritis wk, +4, and +8 wks around calving, respectively. Five SM

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molecules including SMOH C22:1, C22:2, and C24:1 as well as SM C24:0 and C26:0 were

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consistently greater in premetritic and metritic cows at all time points studied. It should be noted

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that the two most dominant species of SMs in the serum of both groups of cows were SM C16:0

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and C24:0. Research conducted by Memon et al. (1998) indicates that during inflammatory

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conditions and activation of acute phase response proinflammatory cytokines (i.e., tumor

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necrosis factor (TNF) and interleukin (IL) -1) stimulate production of SM from liver hepatocytes

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and its release into the blood circulation, attached to multiple lipoprotein species.15 Indeed,

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premetritic and metritic cows in our study had greater concentrations of IL-6, TNF, and SAA in

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the serum. Moreover, the same group of investigators demonstrated that lipopolysaccharide

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(LPS)

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palmitoyltransferase), a rate limiting enzyme, important in the synthesis of sphingolipids and

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more specifically SM from liver hepatocytes.15 Additionally, the same authors reported that LPS

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increased the content of SM and other sphingolipids in the lipoproteins of Syrian hamsters. The

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authors suggested that sphingolipid and other lipid alterations during inflammatory conditions

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are part of the acute phase response.

stimulated

the

activity

and

increased

mRNA

expression

of

SPT

(serine

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Several species of lysoPC (i.e., 5, 5, 2, 6, and 1 at -8, -4, disease wk, +4, and +8 wks around

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calving, respectively) were observed to be elevated in the serum of premetritic, metritic, and

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postmetritic cows. Lysophosphatidylcholine is produced by the hydrolysis of PC, mainly by the

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action of phospholipase A2. Lysophosphatidylcholine has been shown to influence various

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immune cells and immune responses. For instance, lysoPC has been shown to increase

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chemotaxis of T lymphocytes, monocytes, and macrophages. It also activates macrophages and

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upregulates the expression of adhesion molecules.16,17 Intriguingly, Yan et al. (2004) have shown

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that treatment of mice with lysoPC lowers mortality in animal models of septic shock triggered

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by intraperitoneal inoculation of Escherichia coli.18 This protective effect of lysoPC was

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attributed to its ability to increase clearance of bacteria, lower deactivation of neutrophils, and

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decrease concentrations of TNF and IL-1. Therefore, increased serum lysoPC might be a host

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response to the state of chronic inflammation present in those cows. The source of inflammation

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in our cows is unknown presently and warrants further investigation.

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Results of this study show that premetritic, metritic, and postmetritic cows had greater

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concentrations of multiple AAs in the serum. Indeed, there were a total of 11, 12, 11, 7, and 9

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AAs that were found to be different in metritic cows compared with CON ones at -8, -4 wks

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prepartum, at disease wk as well as at +4 and +8 wks postaprtum, respectively. Except for Asn,

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which was lower, all AAs identified as altered were elevated and were greater than CON cows. It

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is important to note that four AAs including His, Ile, Leu, and Lys were consistently greater in all

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5 time-points studied. Other important AAs that altered around calving were Ala, Arg, and Ser (at

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four time points) and Asn, Glu, Phe, and Val (at three time points), as shown in the respective

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tables. Also, it should be pointed out that the two most dominant species of AAs during all time

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points studied, in cows that became metritic, were Lys and Leu, whereas those in the normal

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healthy cows were Gly and Gln.

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Lysine and Leu are the only purely ketogenic AAs. Indeed, premetritic cows in this study

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had a tendency for greater BHBA in the serum at -8 wks and significantly greater BHBA at -4

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wks prior to parturition, as reported in a companion article.9 This supports the idea that these

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AAs were partly used for production of ketone bodies, as a source of energy for cows. Recent

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data show that Lys is also used as a building block for important innate immunity proteins. For

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instance, Iseri and Klasing (2014) reported that Lys is the most dominant AA used for synthesis

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of multiple acute phase proteins in poultry.19 No such data exist for dairy cows or other species.

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Indeed, SAA was greater during -8 and -4 weeks prior to calving and during disease week in

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premetritic and metritic cows as reported previously.9 On the other hand, Leu has been shown to

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play a role in cell-mediated immunity. Consistent with this Du et al. (2017) showed that Leu

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enhanced the capacity of murine macrophages to kill Escherchia coli in a dose dependent

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manner.20

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One of the most important findings of this study was that concentrations of the biogenic

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amine, Kyn, were greater in premetritic, metritic, and postmetritic cows at all tested time points

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around parturition. Kynurenine is a molecule deriving from catabolism of Trp. In fact, more than

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95% of the dietary Trp is oxidized in the liver through the Kyn pathway.21,22 Chen and Guillemin

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(2009) showed that Kyn pathway is up-regulated when the immune response is activated.23

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Moreover, production of Kyn plays a crucial role in the host immune responses. Therefore,

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elevated concentrations of Kyn in the blood of premetritic, metritic, and postmetritic cows

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indicates that those cows were subjected to a chronic inflammation during the experimental

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period as serum Kyn is upregulated by pro-inflammatory molecules. Indeed, in a companion

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article,9 we reported that premetritic, metritic, and postmetritic cows had chronic elevation of

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various cytokines and acute phase proteins including IL-6 and SAA during -8 and -4 wks

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prepartum and TNF during the disease week. On the other hand, Kyn has been shown to have

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immunosuppressive effects on the secretion of pro-inflammatory molecules including TNF, nitric

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oxide (NO), and other proteins mediating immune response to bacterial LPS.23 Moreover, Kyn

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pathway catabolites have been shown to trigger apoptosis of Th1 cell but not those of Th2

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phenotype, indicating that Trp catabolites are involved in alteration of Th1/Th2 cell balance and

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orientation of the immune response toward humoral immunity.24 Additionally, Kyn catabolites

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also inhibit natural killer cell functions,25,26 emphasizing that the Kyn pathway metabolites are

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involved in the suppression of a number of various inflammatory processes.

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Another biogenic amine that was found to be consistently greater in the serum of premetritic,

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metritic, and postmetrtitic cows, at all five time-points studied, was acetylornithine.

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Acetylornithine is a catabolite of Orn metabolism. Ornithine is synthesized from Arg and also

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serves as a precursor for synthesis of Arg. The enzyme that removes a carboxyl group from Orn,

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ornithine decarboxylase (ODC), is the first and rate-limiting enzyme in the synthesis of

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endogenous polyamines. Serum Arg was greater in premetritic cows versus the CON ones, at

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four time points during this study. Previously we reported that both acetylornithine and Arg were

328

greater in ketotic cows suggesting a typical host response during chronic inflammatory states.11

329

Moreover, Arg and Orn contribute to production of nitric oxide (NO) and polyamines like

330

putrescine, spermidine, and spermine. The latter have been demonstrated to be involved in the

331

control of the innate immune system and have a significant impact on the inflammatory events

332

that take place during bacterial infection.27 Indeed, Soulet and Rivest (2003) reported that a

333

single systemic administration of LPS triggered over-expression of the gene encoding ODC

334

supporting our finding that premetritic cows are in a state of chronic inflammation potentially

335

related to bacterial insults.27

336

Several acylcarnitines (C3, C4, C10, C16, and C18) were found to be greater in cows with

337

metritis during the week of disease occurrence. There was one acylcarnitine (C10) that was

338

greater in premetritic cows during wks -8 and -4 prior to parturition and five acylcarnitines were

339

greater during the week of disease. Acylcarnitines are acyl esters of carnitine that results from

340

malfunctioning of β-oxidation of long-chain fatty acids in mitochondria. Since they are toxic

341

compounds they are released into the blood circulation and are excreted through urinary system.

342

Intriguingly greater blood concentrations of acylcarnitines have been reported in humans with

343

type 2 diabetes and insulin resistance.28 Recently it was shown that medium-chain acylcarnitines

344

including C12 and C14 are able to trigger proinflammatory cytokine production in macrophages

345

and IL-8 from human epithelial cells in vitro.29 We also reported greater concentrations of

346

acylcarnitines in preketotic and ketotic cows.11

347

It should be noted that metabolic alterations in cows affected by metritis were present not

15



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348

only prior to clinical appearance of the disease but also at +4 and + 8 wks after parturition.

349

Contrary to the belief that cows that go through metritis might heal soon after their vaginal

350

discharges are normalized, our data show that metabolic homeostasis is not restored even at +8

351

wks after calving. This suggest that a specific care should be given to those cows in order for

352

complete recovery. Metabolic perturbations detected in cows that were affected by metritis might

353

offer a partial answer to the reported findings that cows affected by metritis have poor

354

reproductive performance.30 This also suggest that metabolic transition of cows affected by

355

metritis spreads beyond the traditional transition period of -3 to +3 wks around calving.

356

Overall data from this study indicated that premetritic cows showed typical metabolic

357

signatures that can be used to early identify dairy cows at risk of developing metritis.

358

Additionally, metabolic alterations identified throw light into the mechanisms of disease

359

development. It is obvious that some of the metabolites altered in the serum support immune

360

responses (AAs and lysoPC), some others (acylcarnitines) suggest dysfunction of mitochondrial

361

burning of fatty acids, and others (biogenic amines) suggest host responses to keep inflammatory

362

processes under control. More research is warranted to look at the complex interactions of all the

363

metabolites identified during disease and health processes in transition dairy cows.

364

ASSOCIATED CONTENT

365

Supporting Information

366

“Material and Methods Extended”, Supplementary Table 1, Table 2, Table 3, Figure 1, Figure 2.

367

This material is available free of charge via the Internet at http://pubs.acs.org.

368 369

AUTHOR INFORMATION

370

Corresponding Author

16


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371

*Email: [email protected]; Tel: 780-492-9841; Fax: 780-492-4265

372

Funding

373

This study was supported by research grants awarded to principal investigators Dr. Burim N.

374

Ametaj and Dr. David S. Wishart from Genome Alberta (Calgary, Alberta, Canada), Alberta

375

Livestock and Meat Agency Ltd. (Edmonton, Alberta, Canada), and the Natural Sciences and

376

Engineering Research Council of Canada (Ottawa, Ontario, Canada).

377

Notes

378

The authors declare no competing financial interest.

379 380

ACKNOWLEDGMENTS

381

We thank E. Dervishi, D. Hailemariam, S. A. Goldansaz, and J. F. Odhiambo for helping with

382

collection of samples from cows and the technical staff at the Dairy Research and Technology

383

Center, University of Alberta, for their help and care with the cows. We also are grateful to the

384

staff at The Metabolomics Innovation Centre, University of Alberta, Edmonton, AB, Canada,

385

especially to P. Liu for his help in the preparation of the DI/LC-MS/MS kit, and B. Han for his

386

advice in data analysis.

387 388

REFERENCES

389

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predictive serum biomarkers for the risk of disease. Metabolomics 2017, 13, 43-57.

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in experimental sepsis. Nat. Med. 2004, 10, 161-167.

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immune cells after a systemic response to dead Escherichia coli: implications for the nutritional

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for L-leucine-induced metabolome to eliminate Streptococcus iniae. J. Proteome Res. 2017, doi:

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10.1021/acs.jproteome.6b00944.

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genetic and environmental impacts in major depressive disorder: the serotonin hypothesis

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States. Int. J. Tryptophan Res. 2009, 2, 1-19.

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C.; Puccetti, P. T cell apoptosis by tryptophan catabolism. Cell Death Differ. 2002, 9, 1069-1077.

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mediation of suppression by tryptophan metabolites. J. Exp. Med. 2002, 196, 447-457.  

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Tryptophan-derived catabolites are responsible for inhibition of T and natural killer cell

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proliferation induced by indoleamine 2,3-dioxygenase. J. Exp. Med. 2002, 196, 459-468.  

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response in the mouse central nervous system. J. Cell Biol. 2003,162, 257-268.

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(28) Schooneman, M. G.; Vaz, F. M.; Houten, S. M.; Soeters, M. R. Acylcarnitines: reflecting or

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inflicting insulin resistance? Diabetes 2013, 62, 1-8.

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(29) Rutkowsky, J. M.; Knotts, T. A.; Ono-Moore, K. D.; McCoin, C. S.; Huang, S.; Schneider,

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D.; Singh, S.; Adams, S. H.; Hwang, D. H. Acylcarnitines activate proinflammatory signaling

466

pathways. Am. J. Physiol. Endocrinol. Metab. 2014, 306, E1378-1387.

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(30) Giuliodori, M. J.; Magnasco, R. P.; Becu-Villalobos, D.; Lacau-Mengido, I. M.; Risco, C.

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A.; de la Sota, R. L. Metritis in dairy cows: risk factors and reproductive performance. J. Dairy

469

Sci. 2013, 96, 3621-3631.

470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485

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486

Figure captions

487

Figure 1. (A) Principal component analysis (PCA) and (B) Partial least squares-discriminant

488

analysis (PLS-DA, permutation testing: P < 0.05) of 20 control (CON) and 6 pre-metritic cows at

489

-8 wks before parturition showing 2 separated clusters for 2 groups. (C) Variables ranked by

490

variable importance in projection (VIP), and (D) Receiver-operator characteristic (ROC) curve of

491

20 CON and 6 pre-metritic cows at -8 wks before parturition for the top 5 serum variables (i.e.,

492

Lys, lysoPC a C17:0, lysoPC a C18:0, Ile, and lysoPC a C16:0; empirical P = 0.001).

493 494

Figure 2. (A) PCA and (B) PLS-DA (permutation testing: P < 0.05) of 20 CON and 6 pre-

495

metritic cows at -4 wks before parturition showing 2 separated clusters for 2 groups. (C) VIP, and

496

(D) ROC curve of 20 CON and 6 pre-metritic cows at -4 wks before parturition for the top 5

497

serum variables (i.e., Lys, Ile, Leu, SM C20:2, and lysoPC a C17:0; empirical P = 0.001).

498 499

Figure 3. (A) PCA and (B) PLS-DA (permutation testing: P < 0.05) of 20 CON and 6 metritic

500

cows at disease wk showing 2 separated clusters for 2 groups. (C) VIP, and (D) ROC curve of 20

501

CON and 6 metritic cows at disease wk for the top 5 serum variables (i.e., Lys, Ile, Leu, Kyn,

502

and PC ae C30:1; empirical P = 0.001).

503 504 505 506

22


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Table 1. Concentrations of serum metabolites (mean (SEM)) in healthy control and pre-metritic/metritic cows at 3 time points (-8 wks, -4 wks, and wks of diagnosis of disease) as determined by DI/LC-MS/MS -8 wks before parturition 2

wk of diagnosis of disease1

-4 wks before parturition

Metabolite , µM

Metritis

CON

p-value

Metritis / CON

Metritis

CON

p-value

Metritis / CON

Metritis

CON

p-value

Metritis / CON

Number of cases C10 C16 C18 C2 C3 C4 C5 lysoPC a C16:0 lysoPC a C16:1 lysoPC a C17:0 lysoPC a C18:0 lysoPC a C18:1 lysoPC a C18:2 lysoPC a C20:3 lysoPC a C20:4 lysoPC a C28:0 lysoPC a C28:1 PC aa C28:1 PC aa C30:0 PC aa C30:2 PC aa C32:0 PC aa C32:1 PC aa C32:2 PC aa C32:3 PC aa C34:1 PC aa C34:2 PC aa C34:3 PC aa C34:4 PC aa C36:0 PC aa C36:1 PC aa C36:2 PC aa C36:3 PC aa C36:4 PC aa C36:5 PC aa C36:6 PC aa C38:0 PC aa C38:1

6 0.05 (0.01) 0.02 (0.003) 0.02 (0.004) 1.21 (0.11) 0.16 (0.01) 0.09 (0.01) 0.07 (0.01) 75.02 (7.93) 2.31 (0.19) 10.53 (1.53) 80.39 (6.79) 24.59 (2.44) 22.14 (3.01) 2.78 (0.35) 2.70 (0.14) 0.89 (0.34) 0.84 (0.13) 2.88 (0.45) 4.76 (0.61) 1.30 (0.11) 9.50 (0.99) 8.26 (1.29) 14.31 (2.38) 28.43 (4.90) 98.54 (12.88) 146.70 (21.83) 26.61 (4.28) 10.36 (1.74) 11.70 (2.11) 117.58 (13.08) 185.94 (18.99) 86.61 (11.73) 37.21 (4.60) 10.13 (1.39) 4.67 (0.68) 3.56 (0.81) 7.17 (1.50)

20 0.02 (0.01) 0.02 (0.004) 0.03 (0.004) 1.30 (0.10) 0.14 (0.01) 0.08 (0.01) 0.08 (0.01) 27.89 (2.68) 1.58 (0.17) 3.03 (0.36) 25.79 (3.09) 16.09 (1.54) 18.49 (1.87) 3.25 (0.33) 3.61 (0.36) 0.83 (0.05) 0.75 (0.10) 1.86 (0.18) 2.54 (0.25) 0.33 (0.05) 8.61 (0.75) 7.88 (0.71) 8.44 (0.89) 15.78 (1.97) 97.65 (8.90) 144.82 (13.13) 28.61 (2.98) 7.44 (0.91) 6.74 (0.77) 105.11 (9.08) 166.65 (14.53) 79.46 (7.61) 39.05 (3.45) 10.24 (0.94) 3.30 (0.33) 1.87 (0.20) 4.24 (0.62)

0.003* 0.738 0.447 0.744 0.242 0.744 0.738 0.001* 0.016* 0.001* 0.001* 0.007* 0.176 0.614 0.046* 0.196 0.421 0.033* 0.003* 0.001* 0.457 1 0.046* 0.019* 0.976 0.79 0.79 0.219 0.033* 0.387 0.494 0.573 0.744 1 0.083 0.033* 0.108

Up Down Down Down Up Up Down Up Up Up Up Up Up Down Down Up Up Up Up Up Up Up Up Up Up Up Down Up Up Up Up Up Down Down Up Up Up

6 0.06 (0.01) 0.02 (0.004) 0.02 (0.004) 1.20 (0.08) 0.16 (0.01) 0.08 (0.01) 0.07 (0.01) 58.56 (7.94) 1.96 (0.26) 8.73 (1.45) 71.88 (10.44) 22.01 (2.66) 16.98 (2.26) 2.53 (0.28) 2.48 (0.22) 0.47 (0.06) 0.56 (0.03) 1.73 (0.17) 2.78 (0.21) 0.92 (0.06) 6.18 (0.37) 5.09 (0.34) 8.98 (0.67) 16.04 (2.22) 71.01 (6.60) 91.20 (14.95) 15.70 (2.02) 6.72 (0.82) 7.79 (0.73) 98.53 (11.03) 142.55 (19.98) 61.36 (8.33) 25.89 (2.16) 7.20 (0.70) 3.48 (0.30) 2.29 (0.27) 5.28 (0.82)

20 0.03 (0.01) 0.03 (0.004) 0.04 (0.01) 1.43 (0.22) 0.14 (0.02) 0.07 (0.01) 0.06 (0.01) 24.44 (2.64) 1.26 (0.13) 2.00 (0.24) 19.49 (2.33) 14.14 (1.58) 17.12 (2.09) 1.67 (0.17) 2.24 (0.18) 0.61 (0.05) 0.51 (0.04) 1.54 (0.19) 2.17 (0.26) 0.23 (0.04) 7.06 (0.78) 6.74 (0.81) 5.99 (0.69) 10.64 (1.30) 99.96 (14.13) 154.36 (23.31) 23.14 (2.75) 3.86 (0.41) 4.40 (0.52) 90.50 (10.75) 157.08 (19.70) 69.68 (8.48) 30.96 (3.49) 7.96 (0.79) 2.13 (0.20) 1.28 (0.16) 2.84 (0.39)

0.002* 0.7 0.196 0.79 0.355 0.26 0.324 0.003* 0.046* 0.001* 0.001* 0.054 0.7 0.033* 0.533 0.196 0.494 0.295 0.046* 0.001* 0.573 0.242 0.019* 0.039* 0.421 0.242 0.176 0.006* 0.004* 0.573 0.836 0.744 0.421 0.744 0.003* 0.016* 0.011*

Up Down Down Down Up Up Up Up Up Up Up Up Down Up Up Down Up Up Up Up Down Down Up Up Down Down Down Up Up Up Down Down Down Down Up Up Up

6 0.06 (0.01) 0.04 (0.01) 0.08 (0.02) 1.97 (0.41) 0.17 (0.03) 0.09 (0.01) 0.06 (0.00) 50.77 (17.05) 1.71 (0.26) 2.46 (0.80) 39.79 (13.38) 19.59 (2.82) 18.91 (2.73) 1.08 (0.17) 1.32 (0.13) 0.41 (0.03) 0.58 (0.06) 2.42 (0.34) 4.09 (0.45) 0.76 (0.14) 7.45 (0.78) 8.01 (1.03) 8.80 (0.82) 13.50 (1.42) 120.97 (13.19) 156.69 (21.45) 21.79 (3.63) 3.56 (0.37) 6.41 (0.54) 104.09 (11.11) 168.08 (21.22) 70.71 (11.55) 30.51 (4.65) 8.19 (1.04) 2.66 (0.24) 1.23 (0.06) 3.17 (0.47)

20 0.03 (0.01) 0.02 (0.004) 0.04 (0.01) 1.22 (0.11) 0.15 (0.05) 0.07 (0.004) 0.06 (0.00) 23.78 (2.09) 1.26 (0.11) 1.85 (0.23) 17.67 (1.70) 13.37 (1.38) 17.43 (2.01) 1.82 (0.22) 2.30 (0.26) 0.63 (0.05) 0.53 (0.04) 1.66 (0.15) 2.28 (0.21) 0.28 (0.05) 6.68 (0.61) 6.70 (0.59) 6.33 (0.59) 11.33 (1.12) 94.61 (10.26) 147.47 (15.38) 24.09 (2.44) 4.39 (0.55) 4.89 (0.64) 87.64 (8.59) 149.78 (14.23) 69.02 (6.53) 31.91 (2.98) 8.14 (0.82) 2.49 (0.24) 1.34 (0.17) 3.22 (0.44)

0.002* 0.013* 0.031* 0.095 0.033* 0.039* 0.533 0.046* 0.123 0.79 0.046* 0.062 0.533 0.095 0.108 0.033* 0.7 0.039* 0.001* 0.001* 0.494 0.457 0.039* 0.196 0.139 0.614 0.929 0.324 0.108 0.355 0.573 0.976 0.836 0.929 1 0.976 0.836

Down Up Up Up Down Up Up Up Up Up Up Up Up Down Up Down Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up

23



PC aa C38:3 PC aa C38:4 PC aa C38:5 PC aa C38:6 PC aa C40:2 PC aa C40:3 PC aa C40:4 PC aa C40:5 PC aa C40:6 PC aa C42:1 PC aa C42:2 PC aa C42:4 PC aa C42:5 PC aa C42:6 PC ae C30:0 PC ae C30:1 PC ae C32:1 PC ae C32:2 PC ae C34:0 PC ae C34:1 PC ae C34:2 PC ae C34:3 PC ae C36:0 PC ae C36:1 PC ae C36:2 PC ae C36:3 PC ae C36:4 PC ae C36:5 PC ae C38:0 PC ae C38:1 PC ae C38:2 PC ae C38:3 PC ae C38:4 PC ae C38:5 PC ae C38:6 PC ae C40:1 PC ae C40:2 PC ae C40:3 PC ae C40:4 PC ae C40:5 PC ae C40:6 PC ae C42:1 PC ae C42:2

58.49 (7.23) 52.99 (3.90) 27.32 (3.15) 5.18 (0.58) 0.92 (0.36) 7.35 (1.99) 18.29 (3.35) 24.06 (2.85) 4.63 (0.36) 0.18 (0.07) 0.32 (0.11) 0.40 (0.09) 1.42 (0.42) 0.54 (0.05) 0.98 (0.10) 3.10 (0.46) 4.42 (0.62) 8.48 (1.14) 4.63 (0.48) 17.09 (2.11) 26.19 (3.89) 30.81 (5.72) 2.26 (0.19) 22.52 (2.41) 33.00 (4.48) 12.96 (1.79) 13.14 (2.09) 8.97 (1.21) 2.45 (0.27) 5.24 (1.17) 5.68 (1.42) 8.51 (1.25) 8.35 (0.70) 6.05 (0.55) 5.18 (0.75) 0.79 (0.29) 2.05 (0.78) 2.51 (0.89) 2.48 (0.47) 3.55 (0.31) 1.49 (0.13) 0.45 (0.25) 0.52 (0.22)

55.71 (5.47) 56.15 (4.79) 25.35 (2.17) 4.27 (0.35) 0.35 (0.05) 4.41 (0.64) 11.72 (1.16) 18.80 (1.69) 3.49 (0.27) 0.07 (0.01) 0.12 (0.01) 0.25 (0.03) 0.81 (0.09) 0.36 (0.02) 0.72 (0.06) 1.32 (0.18) 3.82 (0.37) 7.13 (0.80) 3.66 (0.36) 15.63 (1.42) 18.55 (1.95) 19.30 (2.50) 2.45 (0.24) 17.77 (1.47) 23.00 (2.23) 10.60 (1.17) 9.19 (1.09) 7.47 (0.81) 1.59 (0.14) 3.11 (0.31) 3.66 (0.35) 6.06 (0.63) 7.48 (0.71) 5.31 (0.49) 4.02 (0.39) 0.38 (0.04) 0.94 (0.10) 1.47 (0.16) 2.08 (0.20) 2.71 (0.24) 1.05 (0.08) 0.20 (0.02) 0.22 (0.02)

0.7 0.7 0.7 0.387 0.046* 0.139 0.062 0.108 0.033* 0.013* 0.001* 0.108 0.108 0.006* 0.062 0.002* 0.494 0.494 0.196 0.7 0.123 0.054 0.744 0.123 0.062 0.355 0.095 0.421 0.013* 0.054 0.123 0.157 0.494 0.457 0.219 0.139 0.023* 0.157 0.573 0.157 0.023* 0.614 0.023*

Up Down Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Down Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up

44.72 (3.64) 44.76 (3.00) 21.94 (2.12) 3.75 (0.34) 0.39 (0.04) 4.59 (0.74) 13.99 (1.29) 20.04 (1.34) 3.70 (0.23) 0.08 (0.01) 0.14 (0.01) 0.29 (0.04) 1.06 (0.09) 0.41 (0.02) 0.66 (0.03) 1.91 (0.22) 2.62 (0.09) 5.61 (0.26) 3.21 (0.14) 12.40 (0.76) 15.77 (0.93) 15.04 (1.63) 1.83 (0.08) 16.88 (1.19) 19.12 (1.68) 8.08 (0.63) 7.21 (0.66) 5.84 (0.33) 1.67 (0.07) 3.07 (0.25) 3.05 (0.13) 5.82 (0.59) 6.15 (0.45) 4.31 (0.17) 3.45 (0.18) 0.42 (0.03) 1.01 (0.09) 1.24 (0.15) 1.59 (0.11) 2.68 (0.15) 0.98 (0.05) 0.13 (0.01) 0.23 (0.03)

30.27 (3.09) 36.75 (3.51) 21.00 (2.22) 3.97 (0.52) 0.20 (0.02) 1.97 (0.35) 6.47 (0.84) 14.34 (1.55) 3.17 (0.35) 0.05 (0.003) 0.08 (0.01) 0.13 (0.02) 0.54 (0.08) 0.28 (0.03) 0.56 (0.05) 0.83 (0.10) 3.10 (0.33) 5.26 (0.68) 2.35 (0.24) 11.80 (1.12) 14.92 (1.74) 15.06 (2.07) 1.62 (0.18) 12.83 (1.18) 17.17 (1.59) 7.58 (0.74) 6.13 (0.68) 5.25 (0.49) 1.14 (0.09) 1.76 (0.23) 2.31 (0.22) 3.21 (0.33) 4.71 (0.47) 3.70 (0.34) 3.00 (0.32) 0.28 (0.03) 0.65 (0.06) 0.78 (0.08) 1.18 (0.14) 1.94 (0.21) 0.84 (0.07) 0.13 (0.01) 0.14 (0.01)

0.033* 0.457 0.927 0.836 0.001* 0.001* 0.001* 0.072 0.242 0.003* 0.001* 0.003* 0.003* 0.004* 0.421 0.001* 0.242 0.355 0.046* 0.882 0.533 0.494 0.494 0.095 0.656 0.836 0.324 0.494 0.001* 0.006* 0.157 0.002* 0.054 0.355 0.563 0.019* 0.009* 0.028* 0.157 0.039* 0.295 0.421 0.009*

24


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Up Up Up Down Up Up Up Up Up Up Up Up Up Up Up Up Down Up Up Up Up Down Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Up Down Up

24.97 (4.23) 33.47 (4.10) 23.46 (2.54) 4.89 (0.45) 0.15 (0.03) 1.11 (0.17) 5.46 (0.26) 15.28 (0.91) 4.20 (0.25) 0.06 (0.004) 0.08 (0.01) 0.07 (0.01) 0.33 (0.05) 0.30 (0.02) 0.69 (0.08) 1.89 (0.23) 3.00 (0.29) 5.50 (0.63) 2.01 (0.14) 12.01 (1.31) 17.89 (2.10) 18.19 (2.08) 1.03 (0.04) 12.99 (1.37) 16.29 (1.95) 7.53 (0.96) 6.89 (1.07) 5.61 (0.64) 1.38 (0.09) 1.46 (0.17) 2.04 (0.27) 2.63 (0.34) 3.65 (0.38) 3.77 (0.41) 4.32 (0.37) 0.23 (0.03) 0.77 (0.08) 0.59 (0.10) 0.72 (0.09) 1.85 (0.13) 1.08 (0.11) 0.08 (0.01) 0.11 (0.01)

34.70 (4.31) 39.73 (4.36) 21.56 (2.14) 4.18 (0.45) 0.23 (0.03) 2.17 (0.46) 7.40 (1.13) 15.78 (1.65) 3.67 (0.40) 0.05 (0.004) 0.08 (0.01) 0.14 (0.03) 0.50 (0.09) 0.27 (0.02) 0.60 (0.06) 0.90 (0.11) 3.07 (0.27) 5.48 (0.55) 2.49 (0.34) 11.87 (1.15) 14.90 (1.48) 15.57 (1.71) 1.75 (0.20) 12.63 (1.23) 16.98 (1.62) 7.83 (0.75) 6.37 (0.59) 5.56 (0.52) 1.27 (0.11) 1.85 (0.28) 2.37 (0.27) 3.50 (0.49) 5.06 (0.68) 4.01 (0.40) 3.47 (0.33) 0.29 (0.04) 0.71 (0.08) 0.94 (0.15) 1.39 (0.21) 2.12 (0.24) 0.98 (0.09) 0.14 (0.02) 0.14 (0.02)

0.421 0.494 0.744 0.421 0.242 0.219 0.494 0.421 0.421 0.387 0.927 0.355 0.457 0.139 0.355 0.001* 0.614 0.79 0.656 0.929 0.355 0.242 0.083 0.929 0.929 0.614 0.79 0.929 0.614 0.533 0.656 0.573 0.324 0.573 0.242 0.457 0.79 0.355 0.139 0.268 0.656 0.094 0.421

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PC ae C42:3 PC ae C44:3 PC ae C44:4 PC ae C44:5 SM (OH) C14:1 SM (OH) C16:1 SM (OH) C22:1 SM (OH) C22:2 SM (OH) C24:1 SM C16:0 SM C16:1 SM C18:0 SM C18:1 SM C20:2 SM C24:0 SM C24:1 SM C26:0 SM C26:1 Hexose Alanine Arginine Asparagine Aspartic acid Citruline Glutamine Glutamate Glycine

0.53 (0.22) 0.13 (0.05) 0.12 (0.03) 0.11 (0.02) 15.93 (1.00) 12.97 (1.08) 23.19 (2.66) 8.68 (0.89) 2.44 (0.20) 123.98 (10.90) 14.44 (1.56) 15.09 (1.45) 4.83 (0.60) 0.06 (0.04) 34.55 (6.55) 10.03 (1.21) 0.52 (0.06) 0.19 (0.09) 3,279 (147) 249.38 (28.74) 225.17 (24.54) 16.18 (1.97) 23.06 (2.82) 85.53 (13.93) 307.06 (22.08) 196.09 (27.76) 311.09 (29.91)

0.23 (0.02) 0.05 (0.003) 0.08 (0.004) 0.07 (0.01) 10.95 (0.87) 8.48 (0.81) 12.57 (1.34) 5.55 (0.55) 1.24 (0.12) 83.03 (7.45) 9.75 (0.86) 9.37 (0.85) 3.97 (0.37) 0.28 (0.05) 17.37 (2.01) 8.08 (0.79) 0.24 (0.02) 0.10 (0.02) 3,093 (232) 195.40 (10.64) 108.14 (7.43) 30.59 (3.78) 16.06 (3.49) 53.75 (3.47) 286.15 (21.62) 90.53 (7.67) 208.55 (16.17)

0.016* 0.003* 0.033* 0.072 0.006* 0.009* 0.003* 0.016* 0.001* 0.016* 0.011* 0.008* 0.176 0.008* 0.011* 0.268 0.001* 0.605 0.421 0.107 0.001* 0.013* 0.121 0.002* 0.882 0.007* 0.011*

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0.21 (0.02) 0.05 (0.01) 0.10 (0.01) 0.08 (0.01) 11.91 (0.72) 9.18 (0.45) 13.79 (0.73) 5.95 (0.38) 1.45 (0.12) 82.81 (4.89) 10.13 (0.74) 9.76 (0.55) 3.46 (0.31) 0.02 (0.02) 19.25 (1.17) 7.43 (0.64) 0.35 (0.05) 0.16 (0.10) 3,012 (150) 230.05 (23.64) 156.81 (22.60) 20.71 (3.64) 16.87 (4.05) 93.32 (13.35) 282.74 (22.11) 129.70 (26.64) 300.06 (41.22)

0.13 (0.01) 0.03 (0.00) 0.06 (0.00) 0.05 (0.00) 8.94 (0.90) 6.26 (0.56) 11.97 (1.76) 4.36 (0.46) 1.00 (0.10) 70.51 (8.21) 6.85 (0.70) 8.17 (0.87) 3.27 (0.34) 0.17 (0.02) 12.94 (1.35) 7.65 (0.78) 0.19 (0.02) 0.13 (0.02) 2,458 (202) 158.36 (10.07) 103.05 (5.91) 26.45 (2.54) 14.60 (3.92) 56.30 (4.31) 247.88 (25.27) 71.90 (7.54) 269.50 (26.26)

0.004* 0.054 0.002* 0.011* 0.054 0.009* 0.176 0.095 0.039* 0.157 0.019* 0.176 0.494 0.001* 0.013* 0.882 0.004* 0.447 0.095 0.036* 0.019* 0.484 0.083 0.004* 0.605 0.031* 0.533

Up Up Up Up Up Up Up Up Up Up Up Up Up Down Up Down Up Up Up Up Up Down Up Up Up Up Up

0.10 (0.01) 0.03 (0.003) 0.06 (0.01) 0.05 (0.004) 12.35 (1.46) 7.24 (0.79) 20.99 (3.45) 6.89 (0.82) 1.41 (0.14) 104.70 (13.38) 8.86 (1.03) 13.14 (1.87) 4.20 (0.55) 0.09 (0.03) 18.80 (1.88) 9.99 (1.28) 0.37 (0.03) 0.23 (0.08) 2,580 (189) 223.57 (17.88) 189.58 (29.76) 19.62 (4.82) 16.29 (1.96) 63.36 (5.86) 296.41 (40.75) 125.03 (16.61) 309.02 (75.29)

0.15 (0.02) 0.03 (0.003) 0.05 (0.01) 0.05 (0.004) 9.73 (0.83) 6.84 (0.65) 12.23 (1.26) 4.45 (0.41) 1.03 (0.09) 74.72 (7.00) 7.54 (0.69) 8.48 (0.81) 3.43 (0.34) 0.16 (0.02) 13.85 (1.53) 7.45 (0.80) 0.19 (0.02) 0.12 (0.02) 2,354 (179) 135.39 (12.93) 96.03 (7.56) 26.11 (2.56) 12.33 (2.49) 51.87 (4.50) 218.18 (21.60) 68.42 (6.18) 252.83 (34.64)

0.355 0.324 0.573 0.656 0.176 0.927 0.016* 0.019* 0.046* 0.095 0.457 0.023* 0.614 0.139 0.033* 0.157 0.001* 0.247 0.836 0.006* 0.001* 0.324 0.073 0.157 0.123 0.004* 0.324

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Histidine Isoleucine Leucine Lysine Methionine Ornithine Phenylalanine Proline Serine Threonine Tryptophan Tyrosine Valine Acetylornithine Asymmetric dimethylarginine total Dimethylarginine

76.30 (4.47) 312.25 (21.35) 373.04 (23.54) 534.85 (57.54) 42.91 (13.57) 41.58 (13.85) 65.15 (7.14) 91.53 (4.93) 121.13 (16.65) 90.11 (9.58) 23.28 (2.48) 52.00 (6.14) 286.03 (33.79) 10.40 (3.01) 0.85 (0.10) 1.09 (0.07)

51.23 (3.37) 113.87 (10.02) 150.69 (15.62) 90.61 (5.80) 26.94 (3.19) 40.48 (2.60) 50.22 (3.84) 72.70 (5.72) 66.84 (6.58) 78.58 (8.16) 41.67 (3.33) 44.12 (3.12) 218.05 (17.60) 3.73 (0.47) 0.79 (0.06) 0.77 (0.06)

0.001* 0.001* 0.001* 0.001* 0.882 0.929 0.123 0.108 0.001* 0.139 0.003* 0.355 0.073 0.023* 0.744 0.026*

Up Up Up Up Up Up Up Up Up Up Down Up Up Up Up Up

57.55 (6.72) 335.29 (37.52) 399.27 (49.87) 541.37 (38.11) 40.08 (16.04) 37.59 (16.47) 71.43 (9.54) 85.40 (3.65) 100.26 (7.27) 90.63 (9.74) 23.42 (2.52) 49.06 (6.94) 269.81 (38.16) 12.63 (3.26) 0.58 (0.10) 0.90 (0.09)

39.51 (3.03) 99.88 (9.23) 134.57 (12.29) 74.14 (4.78) 21.86 (1.91) 30.55 (2.94) 43.73 (3.87) 63.36 (4.22) 66.76 (6.96) 70.66 (7.01) 29.48 (3.29) 35.55 (3.30) 185.31 (14.62) 3.72 (0.59) 0.60 (0.06) 0.68 (0.06)

0.039* 0.001* 0.001* 0.001* 0.927 0.315 0.009* 0.002* 0.007* 0.083 0.494 0.108 0.031* 0.006* 0.744 0.139

Up Up Up Up Up Up Up Up Up Up Down Up Up Up Down Up

57.84 (5.96) 291.15 (22.97) 395.14 (49.35) 559.86 (73.35) 30.88 (10.07) 38.62 (15.90) 45.04 (6.17) 79.42 (6.52) 100.12 (7.63) 84.93 (7.92) 21.95 (2.05) 50.03 (7.64) 275.17 (42.00) 8.85 (2.00) 0.67 (0.08) 0.90 (0.08)

38.33 (2.69) 100.92 (8.94) 129.56 (11.81) 69.24 (6.51) 19.19 (2.08) 29.23 (3.42) 41.71 (3.33) 57.62 (4.77) 59.38 (5.25) 64.22 (6.47) 29.90 (3.47) 35.00 (3.41) 183.46 (16.27) 3.32 (0.47) 0.55 (0.06) 0.64 (0.05)

0.009* 0.001* 0.001* 0.001* 0.605 0.744 0.976 0.019* 0.001* 0.028* 0.242 0.123 0.009* 0.019* 0.411 0.016*

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25



Carnosine Creatinine Kynurenine Sarcosine Taurine

8.73 (1.13) 83.60 (5.27) 17.77 (1.91) 5.47 (0.53) 60.08 (7.71)

5.60 (0.42) 77.12 (6.00) 8.34 (0.69) 2.74 (0.44) 37.70 (2.49)

0.014* 0.157 0.002* 0.003* 0.006*

Up Up Up Up Up

8.30 (0.68) 73.78 (4.64) 14.48 (1.65) 4.10 (0.73) 41.88 (3.28)

4.96 (0.33) 68.88 (3.98) 6.54 (0.60) 3.51 (0.65) 36.44 (3.11)

0.001* 0.523 0.001* 0.268 0.212

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Up Up Up Up Up

6.32 (0.88) 74.77 (4.77) 14.44 (1.14) 4.28 (0.67) 40.43 (5.74)

4.25 (0.37) 57.76 (4.36) 6.58 (0.77) 2.62 (0.64) 33.93 (4.02)

0.055 0.036* 0.001* 0.023* 0.324

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1

Cows were diagnosed with metritis (n=6) ranging from +1 wks to +3 wks.

2

C10: decanoyl-L-carnitine; C16: hexadecanoyl-L-carnitine; C18: octadecenoyl-L-carnitine; C2: acetyl-L-carnitine; C3: propionyl-L-carnitine; C4: butyryl-L-carnitine; C5: valeryl-L-

carnitine; lysoPC a: lysophosphatidylcholine acyl; PC aa: phosphatidylcholine diacyl; PC ae: phosphatidylcholine acyl-alkyl; SM (OH): hydroxysphingomyelin; SM: sphingomyelin; lysoPC, PC aa, and PC ae are glycerophospholipids; SM (OH) and SM are sphingolipids

26


Page 27 of 30

Figure 1

A

C


B

D

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Figure 2

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C


B

D

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Figure 3

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TOC Graphic

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MS-Based Metabolic Profiling for ... - ACS Publications

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