The purpose of this study was to assess the metabolic profile of plasma samples from cows with clinical and subclinical ketosis. According to clinical signs and 3-hydroxybutyrate plasma levels, 81 multiparous Holstein cows were selected from a dairy farm 7 to 21 d after calving. The cows were divided into 3 groups: cows with clinical ketosis, cows with subclinical ketosis, and healthy control cows. (1)H-Nuclear magnetic resonance-based metabolomics was used to assess the plasma metabolic profiles of the 3 groups. The data were analyzed by principal component analysis, partial least squares discriminant analysis, and orthogonal partial least-squares discriminant analysis. The differences in metabolites among the 3 groups were assessed. The orthogonal partial least-squares discriminant analysis model differentiated the 3 groups of plasma samples. The model predicted clinical ketosis with a sensitivity of 100% and a specificity of 100%. In the case of subclinical ketosis, the model had a sensitivity of 97.0% and specificity of 95.7%. Twenty-five metabolites, including acetoacetate, acetone, lactate, glucose, choline, glutamic acid, and glutamine, were different among the 3 groups. Among the 25 metabolites, 4 were upregulated, 7 were downregulated, and 14 were both upregulated and downregulated. The results indicated that plasma (1)H-nuclear magnetic resonance-based metabolomics, coupled with pattern recognition analytical methods, not only has the sensitivity and specificity to distinguish cows with clinical and subclinical ketosis from healthy controls, but also has the potential to be developed into a clinically useful diagnostic tool that could contribute to a further understanding of the disease mechanisms.

Nephrotoxicity of colistin is the major factor limiting its clinical application. However, the exact mechanism of colistin-induced nephrotoxicity is still elusive. N 6 -Methyladenosine (m 6 A) modification has been implicated in many biological processes, however, its role in colistin-induced nephrotoxicity needs to be elucidated. Mouse renal tubular epithelial cells (mRTECs) were treated with 200 μM colistin with or without METTL3 overexpression. Cells injury, m 6 A assay, oxidative stress and apoptosis were examined. Levels of m 6 A are decreased after colistin treatment in mRTECs. METTL3 is the major factor involved in abnormal m 6 A modification. METTL3 overexpression plays a protective role against colistin-induced oxidative stress and apoptosis. Moreover, METTL3 interacts with the microprocessor protein DGCR8 and positively modulates miR-873-5p mature process in an m 6 A-dependent manner. Further experiments show that miR-873-5p could regulate Keap1-Nrf2 pathway against colistin-induced oxidative stress and apoptosis. These studies revealed an important role of METTL3/m 6 A in colistin-induced nephrotoxicity and provide a new insight on m 6 A modification in drug induced toxicity.

BackgroundKetosis is an important problem for dairy cows` production performance. However, it is still little known about plasma metabolomics details of dairy ketosis.ResultsA gas chromatography/mass spectrometry (GC/MS) technique was used to investigate plasma metabolic differences in cows that had clinical ketosis (CK, n=22), subclinical ketosis (SK, n=32), or were clinically normal controls (NC, n=22). The endogenous plasma metabolome was measured by chemical derivatization followed by GC/MS, which led to the detection of 267 variables. A two-sample t-test of 30, 32, and 13 metabolites showed statistically significant differences between SK and NC, CK and NC, and CK and SK, respectively. Orthogonal signal correction-partial least-square discriminant analysis (OPLS-DA) revealed that the metabolic patterns of both CK and SK were mostly similar, with the exception of a few differences. The development of CK and SK involved disturbances in many metabolic pathways, mainly including fatty acid metabolism, amino acid metabolism, glycolysis, gluconeogenesis, and the pentose phosphate pathway. A diagnostic model arbitrary two groups was constructed using OPLS-DA and receiver–operator characteristic curves (ROC). Multivariate statistical diagnostics yielded the 19 potential biomarkers for SK and NC, 31 for CK and NC, and 8 for CK and SK with area under the curve (AUC) values. Our results showed the potential biomarkers from CK, SK, and NC, including carbohydrates, fatty acids, amino acids, even sitosterol and vitamin E isomers, etc. 2-piperidinecarboxylic acid and cis-9-hexadecenoic acid were closely associated with metabolic perturbations in ketosis as Glc, BHBA and NEFA for dealing with metabolic disturbances of ketosis in clinical practice. However, further research is needed to explain changes of 2,3,4-trihydroxybutyric acid, 3,4-dihydroxybutyric acid, α-aminobutyric acid, methylmalonic acid, sitosterol and α-tocopherol in CK and SK, and to reveal differences between CK and SK.ConclusionOur study shows that some new biomarkers of ketosis from plasma may find new metabolic changes to have clinically new utility and significance in diagnosis, prognosis, and prevention of ketosis in the future.

Our results showed that the metabolic changes in cows with clinical ketosis involve complex metabolic networks and signal transduction. These results are important for future studies elucidating the pathogenesis, diagnosis, and prevention of clinical ketosis in dairy cows.