Serum metabolomics identifies metabolite panels that differentiate lame dairy cows from healthy ones

Dynamic changes of rumen bacteria and their fermentative ability in high-producing dairy cows during the late perinatal period

Background

High-producing dairy cows face varying degrees of metabolic stress and challenges during the late perinatal period, resulting in ruminal bacteria abundance and their fermentative ability occurring as a series of changes. However, the dynamic changes are still not clear.

Aims/methods

Ten healthy, high-producing Holstein dairy cows with similar body conditions and the same parity were selected, and ruminal fluid from the dairy cows at postpartum 0, 7, 14, and 21 d was collected before morning feeding. 16S rRNA high-throughput sequencing, GC-MS/MS targeted metabolomics, and UPLC-MS/MS untargeted metabolomics were applied in the study to investigate the dynamic changes within 21 d postpartum.

Results

The results displayed that the structures of ruminal bacteria were significantly altered from 0 to 7 d postpartum (R = 0.486, P = 0.002), reflecting the significantly declining abundances of Euryarchaeota and Chloroflexi phyla and Christensenellaceae, Methanobrevibacter, and Flexilinea genera (P < 0.05) and the obviously ascending abundances of Ruminococcaceae, Moryella, Pseudobutyrivibrio, and Prevotellaceae genera at 7 d postpartum (P < 0.05). The structures of ruminal bacteria also varied significantly from 7 to 14 d postpartum (R = 0.125, P = 0.022), reflecting the reducing abundances of Christensenellaceae, Ruminococcaceae, and Moryella genera (P < 0.05), and the elevating abundances of Sharpea and Olsenella genera at 14 d postpartum (P < 0.05). The metabolic profiles of ruminal SCFAs were obviously varied from 0 to 7 d postpartum, resulting in higher levels of propionic acid, butyric acid, and valeric acid at 7 d postpartum (P < 0.05); the metabolic profiles of other ruminal metabolites were significantly shifted from 0 to 7 d postpartum, with 27 significantly elevated metabolites and 35 apparently reduced metabolites (P < 0.05). The correlation analysis indicated that propionic acid was positively correlated with Prevotellaceae and Ruminococcaceae (P < 0.05), negatively correlated with Methanobrevibacter (P < 0.01); butyric acid was positively associated with Prevotellaceae, Ruminococcaceae, and Pseudobutyrivibrio (P < 0.05), negatively associated with Christensenellaceae (P < 0.01); valeric acid was positively linked with Prevotellaceae and Ruminococcaceae (P < 0.05); pyridoxal was positively correlated with Flexilinea and Methanobrevibacter (P < 0.05) and negatively correlated with Ruminococcaceae (P < 0.01); tyramine was negatively linked with Ruminococcaceae (P < 0.01).

Conclusion

The findings contribute to the decision of nutritional management and prevention of metabolic diseases in high-producing dairy cows during the late perinatal period.

Serum 1H nuclear magnetic resonance-based metabolomics of sole lesion development in Holstein cows

Sole hemorrhage and sole ulcers, referred to as sole lesions, are important causes of lameness in dairy cattle. We aimed to compare the serum metabolome of dairy cows that developed sole lesions in early lactation with that of cows that remained unaffected. We prospectively enrolled a cohort of 1,169 Holstein dairy cows from a single dairy herd and assessed animals at 4 time points: before calving, immediately after calving, early lactation, and late lactation. Sole lesions were recorded by veterinary surgeons at each time point, and serum samples were collected at the first 3 time points. Cases were defined by the presence of sole lesions in early lactation and further subdivided by whether sole lesions had been previously recorded; unaffected controls were randomly selected to match cases. Serum samples from a case-control subset of 228 animals were analyzed with proton nuclear magnetic resonance spectroscopy. Spectral signals, corresponding to 34 provisionally annotated metabolites and 51 unlabeled metabolites, were analyzed in subsets relating to time point, parity cohort, and sole lesion outcome. We used 3 analytic methods (partial least squares discriminant analysis, least absolute shrinkage and selection operator regression, and random forest) to determine the predictive capacity of the serum metabolome and identify informative metabolites. We applied bootstrapped selection stability, triangulation, and permutation to support the inference of variable selection. The average balanced accuracy of class prediction ranged from 50 to 62% depending on the subset. Across all 17 subsets, 20 variables had a high probability of being informative; those with the strongest evidence of being associated with sole lesions corresponded to phenylalanine and 4 unlabeled metabolites. We conclude that the serum metabolome, as characterized by proton nuclear magnetic resonance spectroscopy, does not appear able to predict sole lesion presence or future development of lesions. A small number of metabolites may be associated with sole lesions although, given the poor prediction accuracies, these metabolites are likely to explain only a small proportion of the differences between affected and unaffected animals. Future metabolomic studies may reveal underlying metabolic mechanisms of sole lesion etiopathogenesis in dairy cows; however, the experimental design and analysis need to effectively control for interanimal and extraneous sources of spectral variation.

Multi-Channel Metabolomics Analysis Identifies Novel Metabolite Biomarkers for the Early Detection of Fatty Liver Disease in Dairy Cows

Fatty liver disease, a type of metabolic disorder, frequently occurs in dairy cows during the parturition period, causing a high culling rate and, therefore, considerable economic losses in the dairy industry owing to the lack of effective diagnostic methods. Here, metabolite biomarkers were identified and validated for the diagnosis of metabolic disorders. A total of 58 participant cows, including severe fatty liver disease and normal control groups, in the discovery set (liver biopsy tested, n = 18), test set (suspected, n = 20) and verification set (liver biopsy tested, n = 20), were strictly recruited and a sample collected for their feces, urine, and serum. Non-targeted GC-MS-based metabolomics methods were used to characterize the metabolite profiles and to screen in the discovery set. Eventually, ten novel biomarkers involved in bile acid, amino acid, and fatty acid were identified and validated in the test set. Each of them had a higher diagnostic ability than the traditional serum biochemical indicators, with an average area under the receiver operating characteristic curve of 0.830 ± 0.0439 (n = 10) versus 0.377 ± 0.182 (n = 9). Especially, combined biomarker panels via different metabolic pipelines had much better diagnostic sensitivity and specificity than every single biomarker, suggesting their powerful utilization potentiality for the early detection of fatty liver disease. Intriguingly, the serum biomarkers were confirmed perfectly in the verification set. Moreover, common biological pathways were found to be underlying the pathogenesis of fatty liver syndrome in cattle via different metabolic pipelines. These newly-discovered and non-invasive metabolic biomarkers are meaningful in reducing the high culling rate of cows and, therefore, benefit the sustainable development of the dairy industry.

Metabolomic changes in lactating multiparous naturally MAP-infected Holstein-Friesian dairy cows suggest changes in mitochondrial energy pathways

Mycobacterium avium subspecies paratuberculosis (MAP) is the causative organism of Johne's Disease, a chronic intestinal infection of ruminants. Infected cows begin shedding MAP within the asymptomatic, subclinical stage of infection before clinical signs, such as weight loss, diarrhoea and reduced milk yields develop within the clinical stages of disease. Herein, we examine the milk metabolomic profiles of naturally MAP-infected Holstein-Friesian cows. The study used biobanked milk samples which were collected 73.4 ± 3.79 (early lactation) and 143 ± 3.79 (mean ± SE) (mid-lactation) days post-calving from 5 MAP-infected and 5 control multiparous cows. The milk metabolome was assessed using flow infusion electrospray high-resolution mass spectrometry (FIE-HRMS) for sensitive, non-targeted metabolite fingerprinting. Metabolite fingerprinting assessments using partial least squares discriminate analyses (PLS-DA) indicated that lactation stage was a larger source of variation than MAP status. Examining each lactation stage separately for changes associated to MAP-infection status identified 45 metabolites, 33 in early lactation and 12 in mid-lactation, but only 6 metabolites were targeted in both stages of lactation. Pathway enrichment analysis suggested that MAP affected the malate-aspartate shuffle during early lactation. Pearson's correlation analysis indicated relationships between milk lactose concentrations in mid-lactation and 6 metabolites that were tentatively linked to MAP-infection status. The targeted metabolites were suggestive of wider changes in the bioenergetic metabolism that appear to be an acceleration of the effects of progressing lactation in healthy cows. Additionally, milk lactose concentrations suggest that MAP reduces the availability of lactose derivatives.

Metabolic profile distinguishes laminitis-susceptible and -resistant ponies before and after feeding a high sugar diet

Background

Insulin dysregulation (ID) is a key risk factor for equine endocrinopathic laminitis, but in many cases ID can only be assessed accurately using dynamic tests. The identification of other biomarkers could provide an alternative or adjunct diagnostic method, to allow early intervention before laminitis develops. The present study characterised the metabolome of ponies with varying degrees of ID using basal and postprandial plasma samples obtained during a previous study, which examined the predictive power of blood insulin levels for the development of laminitis, in ponies fed a high-sugar diet. Samples from 10 pre-laminitic (PL – subsequently developed laminitis) and 10 non-laminitic (NL – did not develop laminitis) ponies were used in a targeted metabolomic assay. Differential concentration and pathway analysis were performed using linear models and global tests.

Results

Significant changes in the concentration of six glycerophospholipids (adj. P ≤ 0.024) and a global enrichment of the glucose-alanine cycle (adj. P = 0.048) were found to characterise the response of PL ponies to the high-sugar diet. In contrast, the metabolites showed no significant association with the presence or absence of pituitary pars intermedia dysfunction in all ponies.

Conclusions

The present results suggest that ID and laminitis risk are associated with alterations in the glycerophospholipid and glucose metabolism, which may help understand and explain some molecular processes causing or resulting from these conditions. The prognostic value of the identified biomarkers for laminitis remains to be investigated in further metabolomic trials in horses and ponies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12917-021-02763-7.

Metabolic impact of weight variations in Icelandic horses

Background

Insulin dysregulation (ID) is an equine endocrine disorder, which is often accompanied by obesity and various metabolic perturbations. The relationship between weight variations and fluctuations of the insulin response to oral glucose tests (OGT) as well as the metabolic impact of ID have been described previously. The present study seeks to characterize the concomitant metabolic impact of variations in the insulin response and bodyweight during repeated OGTs using a metabolomics approach.

Methods

Nineteen Icelandic horses were subjected to five OGTs over one year and their bodyweight, insulin and metabolic response were monitored. Analysis of metabolite concentrations depending on time (during the OGT), relative bodyweight (rWeight; defined as the bodyweight at one OGT divided by the mean bodyweight across all OGTs) and relative insulin response (rAUC_ins; defined accordingly from the area under the insulin curve during OGT) was performed using linear models. Additionally, the pathways significantly associated with time, rWeight and rAUC_ins were identified by rotation set testing.

Results

The results suggested that weight gain and worsening of ID activate distinct metabolic pathways. The metabolic profile associated with weight gain indicated an increased activation of arginase, while the pathways associated with time and rAUC_ins were consistent with the expected effect of glucose and insulin, respectively. Overall, more metabolites were significantly associated with rWeight than with rAUC_ins.