Additional file 1: of Lower plasma trans-4-hydroxyproline and methionine sulfoxide levels are associated with insulin dysregulation in horses

Online Resource 1. List of metabolites measured by the Absolute-IDQ p180 Kit. Name and abbreviation of metabolites measured in the targeted metabolomics analysis approach by using the Absolute-IDQ p180 Kit of Biocrates Life Sciences AG (Innsbruck, Austria). (DOCX 17 kb

FoxO1 total protein expression (tFoxO1) (A) and the extent of phosphorylation of FoxO1 at serine 256 (pFoxO1) (B) in liver of cows.

<p>Data are shown in least squares means with standard errors in each group and at each time point. The results of type 3 test for the effects of time and diets are shown in the table under the diagrams. LC-CON (n = 5), HC-CON (n = 5), LC-NA (n = 5), HC-NA (n = 6): “CON or NA”: Dietary supplement of nicotinic acid (0 or 24 g/d) from d-42 to d24, “LC or HC”: 30 or 60% of concentrate proportion in the diet from d-42 to d0, increase in concentrate proportion in the diet after calving from 30 to 50% within 16 or 24 days. d: Days related to calving, N: Nicotinic acid, C: Concentrate proportion in the diet, d×N, d×C, N×C, d×N×C: Interaction effects of d, N, C, tFoxO1: Total protein expression of forkhead box protein O1, pFoxO1: Extent of phosphorylation of FoxO1 at serine 256.</p

Correlations between FoxO1-related variables and other investigated variables in the hepatic metabolic pathways related to gluconeogenesis.

<p>To demonstrate correlations graphically, the scheme was adopted to one published by Aschenbach et al. [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0146670#pone.0146670.ref011" target="_blank">11</a>]. Pearson’s correlation analyses were performed using the data set from d21 (A) and d100 (B) (N = 21 dairy cows for each). Variables with positive correlations were connected by green solid lines and those with negative correlations by red dotted lines. The level of significance was at least P ≤ 0.01. The metabolites connected by black arrows show the representative metabolic pathways related to gluconeogenesis (not investigated, OAA: Oxaloacetate, PEP: Phosphoenolpyruvate, Glucose-6-P: Glucose-6-phosphate). The variables other than DMI used in the correlation analysis are shown in boxes (blue, red, white for hepatic protein expression, hepatic mRNA expression, and blood metabolites, respectively). FoxO1: Forkhead box protein O1, tFoxO1: Total protein expression of FoxO1, pFoxO1: Extent of phosphorylation of FoxO1 at serine 256, pFo/tFo: pFoxO1-to-tFoxO1 ratio, PCCA: Propionyl CoA carboxylase A, PC: Pyruvate carboxylase, PCK1: Cytosolic phosphoenolpyruvate carboxykinase, G6P: Glucose-6-phosphatase, SLC2A2: Glucose transporter 2 (solute carrier family 2 (facilitated glucose transporter), member 2), IRA, IRB: Insulin receptor isoform A and B, PYGL: Glycogen phosphorylase, liver form, DMI: Dry matter intake, NEFA: Serum concentration of non-esterified fatty acid, Insulin: Insulin serum concentration.</p

Hepatic protein expression as affected by NA and adipose protein expression as affected by time.

<p>A: The ratios of pooled groups (pool “NA” = HC-NA, LC-NA and pool “CON” = HC-CON, LC-CON, 24 or 0 g/d nicotinic acid from d1 to d21) were tested for the influence of nicotinic acid supplementation on the hepatic protein expression of PI3K and GLUT2 by one-way ANOVA (n = 10/group). Hepatic GLUT2 expression decreased from d-21 to d21 (ratio < 1) in cows fed NA, and it was lower in cows fed NA (*p = 0.03) compared to control cows at d21. B, C: The ratios of the protein expression in subcutaneous (B, “SCAT”) and retroperitoneal (C, “RPAT”) adipose tissue from all the cows. Cows were pooled (HC-NA, LC-NA, HC-CON, LC-CON) and tested for the difference to 1 by one-sample t-test (n = 20). The expression of signaling proteins in RPAT was generally lower at d21 compared to at d-21 (ratio < 1; **p < 0.01). Ratio = protein expression d21/d-21; ratio > 1: increase, ratio < 1: decrease; The red line indicates the ratio of protein expression at d-21 (d-21/d-21 = 1). Data are shown as mean ± standard error. NA: nicotinic acid, PI3K: phosphatidylinositol-3-kinase, GLUT2: glucose transporter 2, INSR: insulin receptor, PKCζ = protein kinase Cζ.</p

Table_2_Cow’s microbiome from antepartum to postpartum: A long-term study covering two physiological challenges.XLSX

Little is known about the interplay between the ruminant microbiome and the host during challenging events. This long-term study investigated the ruminal and duodenal microbiome and metabolites during calving as an individual challenge and a lipopolysaccharide-induced systemic inflammation as a standardized challenge. Strong inter- and intra-individual microbiome changes were noted during the entire trial period of 168 days and between the 12 sampling time points. Bifidobacterium increased significantly at 3 days after calving. Both challenges increased the intestinal abundance of fiber-associated taxa, e.g., Butyrivibrio and unclassified Ruminococcaceae. NMR analyses of rumen and duodenum samples identified up to 60 metabolites out of which fatty and amino acids, amines, and urea varied in concentrations triggered by the two challenges. Correlation analyses between these parameters indicated a close connection and dependency of the microbiome with its host. It turns out that the combination of phylogenetic with metabolite information supports the understanding of the true scenario in the forestomach system. The individual stages of the production cycle in dairy cows reveal specific criteria for the interaction pattern between microbial functions and host responses.</p

Table_4_Cow’s microbiome from antepartum to postpartum: A long-term study covering two physiological challenges.XLSX

Little is known about the interplay between the ruminant microbiome and the host during challenging events. This long-term study investigated the ruminal and duodenal microbiome and metabolites during calving as an individual challenge and a lipopolysaccharide-induced systemic inflammation as a standardized challenge. Strong inter- and intra-individual microbiome changes were noted during the entire trial period of 168 days and between the 12 sampling time points. Bifidobacterium increased significantly at 3 days after calving. Both challenges increased the intestinal abundance of fiber-associated taxa, e.g., Butyrivibrio and unclassified Ruminococcaceae. NMR analyses of rumen and duodenum samples identified up to 60 metabolites out of which fatty and amino acids, amines, and urea varied in concentrations triggered by the two challenges. Correlation analyses between these parameters indicated a close connection and dependency of the microbiome with its host. It turns out that the combination of phylogenetic with metabolite information supports the understanding of the true scenario in the forestomach system. The individual stages of the production cycle in dairy cows reveal specific criteria for the interaction pattern between microbial functions and host responses.</p

Data_Sheet_2_Cow’s microbiome from antepartum to postpartum: A long-term study covering two physiological challenges.PDF

Little is known about the interplay between the ruminant microbiome and the host during challenging events. This long-term study investigated the ruminal and duodenal microbiome and metabolites during calving as an individual challenge and a lipopolysaccharide-induced systemic inflammation as a standardized challenge. Strong inter- and intra-individual microbiome changes were noted during the entire trial period of 168 days and between the 12 sampling time points. Bifidobacterium increased significantly at 3 days after calving. Both challenges increased the intestinal abundance of fiber-associated taxa, e.g., Butyrivibrio and unclassified Ruminococcaceae. NMR analyses of rumen and duodenum samples identified up to 60 metabolites out of which fatty and amino acids, amines, and urea varied in concentrations triggered by the two challenges. Correlation analyses between these parameters indicated a close connection and dependency of the microbiome with its host. It turns out that the combination of phylogenetic with metabolite information supports the understanding of the true scenario in the forestomach system. The individual stages of the production cycle in dairy cows reveal specific criteria for the interaction pattern between microbial functions and host responses.</p

Table_6_Cow’s microbiome from antepartum to postpartum: A long-term study covering two physiological challenges.XLSX

Little is known about the interplay between the ruminant microbiome and the host during challenging events. This long-term study investigated the ruminal and duodenal microbiome and metabolites during calving as an individual challenge and a lipopolysaccharide-induced systemic inflammation as a standardized challenge. Strong inter- and intra-individual microbiome changes were noted during the entire trial period of 168 days and between the 12 sampling time points. Bifidobacterium increased significantly at 3 days after calving. Both challenges increased the intestinal abundance of fiber-associated taxa, e.g., Butyrivibrio and unclassified Ruminococcaceae. NMR analyses of rumen and duodenum samples identified up to 60 metabolites out of which fatty and amino acids, amines, and urea varied in concentrations triggered by the two challenges. Correlation analyses between these parameters indicated a close connection and dependency of the microbiome with its host. It turns out that the combination of phylogenetic with metabolite information supports the understanding of the true scenario in the forestomach system. The individual stages of the production cycle in dairy cows reveal specific criteria for the interaction pattern between microbial functions and host responses.</p

Table_1_Cow’s microbiome from antepartum to postpartum: A long-term study covering two physiological challenges.XLSX

Little is known about the interplay between the ruminant microbiome and the host during challenging events. This long-term study investigated the ruminal and duodenal microbiome and metabolites during calving as an individual challenge and a lipopolysaccharide-induced systemic inflammation as a standardized challenge. Strong inter- and intra-individual microbiome changes were noted during the entire trial period of 168 days and between the 12 sampling time points. Bifidobacterium increased significantly at 3 days after calving. Both challenges increased the intestinal abundance of fiber-associated taxa, e.g., Butyrivibrio and unclassified Ruminococcaceae. NMR analyses of rumen and duodenum samples identified up to 60 metabolites out of which fatty and amino acids, amines, and urea varied in concentrations triggered by the two challenges. Correlation analyses between these parameters indicated a close connection and dependency of the microbiome with its host. It turns out that the combination of phylogenetic with metabolite information supports the understanding of the true scenario in the forestomach system. The individual stages of the production cycle in dairy cows reveal specific criteria for the interaction pattern between microbial functions and host responses.</p

Table_3_Cow’s microbiome from antepartum to postpartum: A long-term study covering two physiological challenges.XLSX

Little is known about the interplay between the ruminant microbiome and the host during challenging events. This long-term study investigated the ruminal and duodenal microbiome and metabolites during calving as an individual challenge and a lipopolysaccharide-induced systemic inflammation as a standardized challenge. Strong inter- and intra-individual microbiome changes were noted during the entire trial period of 168 days and between the 12 sampling time points. Bifidobacterium increased significantly at 3 days after calving. Both challenges increased the intestinal abundance of fiber-associated taxa, e.g., Butyrivibrio and unclassified Ruminococcaceae. NMR analyses of rumen and duodenum samples identified up to 60 metabolites out of which fatty and amino acids, amines, and urea varied in concentrations triggered by the two challenges. Correlation analyses between these parameters indicated a close connection and dependency of the microbiome with its host. It turns out that the combination of phylogenetic with metabolite information supports the understanding of the true scenario in the forestomach system. The individual stages of the production cycle in dairy cows reveal specific criteria for the interaction pattern between microbial functions and host responses.</p