Metabolomic and Proteomic Profiles Associated With Ketosis in Dairy Cows

Differentiation of three commercial tuna species through GC-Q-TOF and UPLC-Q/Orbitrap mass spectrometry-based metabolomics and chemometrics

Food fraud is common in the tuna industry because of the economic benefits involved. Ensuring the authenticity of tuna species is crucial for protecting both consumers and tuna stocks. In this study, GC-Q-TOF and UPLC-Q/Orbitrap mass spectrometry-based metabolomics were used to investigate the metabolite profiles of three commercial tuna species (skipjack tuna, bigeye tuna and yellowfin tuna). A total of 22 and 77 metabolites were identified with high confidence using GC-Q-TOF and UPLC-Q/Orbitrap mass spectrometry, respectively. Further screening via chemometrics revealed that 38 metabolites could potentially serve as potential biomarkers. Hierarchical cluster analysis showed that the screened metabolite biomarkers successfully distinguished the three tested tuna species. Furthermore, a total of 27 metabolic pathways were identified through enrichment analysis based on the Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathways.

L-Histidine attenuates NEFA-induced inflammatory responses by suppressing Gab2 expression

Non-esterified fatty acids (NEFAs), key to energy metabolism, may become pathogenic at elevated levels, potentially eliciting immune reactions. Our laboratory's findings of reduced L-histidine in ketotic states, induced by heightened NEFA concentrations, suggest an interrelation with NEFA metabolism. This observation necessitates further investigation into the mitigating role of L-histidine on the deleterious effects of NEFAs. Our study unveiled that elevated NEFA concentrations hinder the proliferation of Bovine Mammary Epithelial Cells (BMECs) and provoke inflammation in a dose-responsive manner. Delving into L-histidine's influence on BMECs, RNA sequencing revealed 2124 genes differentially expressed between control and L-histidine-treated cells, with notable enrichment in pathways linked to proliferation and immunity, such as cell cycle and TNF signaling pathways. Further analysis showed that L-histidine treatment positively correlated with an increase in EdU-555-positive cell rate and significantly suppressed IL-6 and IL-8 levels (p < 0.05) compared to controls. Crucially, concurrent treatment with high NEFA and L-histidine normalized the number of EdU-555-positive cells and cytokine expression to control levels. Investigating the underlying mechanisms, Gab2 (Grb2-associated binder 2) emerged as a central player; L-histidine notably reduced Gab2 expression, while NEFA had the opposite effect (p < 0.05). Gab2 overexpression escalated nitric oxide (NO) production and IL6 and IL8 expression. However, L-histidine addition to Gab2-overexpressing cells resulted in NO concentrations indistinguishable from controls. Our findings collectively indicate that L-histidine can counteract NEFA-induced inflammation in BMECs by inhibiting Gab2 expression, highlighting its therapeutic potential against NEFA-related metabolic disturbances.

Comparative Metabolomic Profiling of L-Histidine and NEFA Treatments in Bovine Mammary Epithelial Cells

Non-esterified fatty acids (NEFAs) are pivotal in energy metabolism, yet high concentrations can lead to ketosis, a common metabolic disorder in cattle. Our laboratory observed lower levels of L-histidine in cattle suffering from ketosis, indicating a potential interaction between L-histidine and NEFA metabolism. This relationship prompted us to investigate the metabolomic alterations in bovine mammary epithelial cells (BMECs) induced by elevated NEFA levels and to explore L-histidine's potential mitigating effects. Our untargeted metabolomic analysis revealed 893 and 160 metabolite changes in positive and negative models, respectively, with VIP scores greater than 1 and p-values below 0.05. Notable metabolites like 9,10-epoxy-12-octadecenoic acid were upregulated, while 9-Ethylguanine was downregulated. A pathway analysis suggested disruptions in fatty acid and steroid biosynthesis pathways. Furthermore, L-histidine treatment altered 61 metabolites in the positive model and 34 in the negative model, with implications for similar pathways affected by NEFA. Overlaying differential metabolites from both conditions uncovered a potential key mediator, 1-Linoleoylglycerophosphocholine, which was regulated in opposite directions by NEFA and L-histidine. Our study uncovered that both NEFA L- and histidine metabolomics analyses pinpoint similar lipid biosynthesis pathways, with 1-Linoleoylglycerophosphocholine emerging as a potential key metabolite mediating their interaction, a discovery that may offer insights for therapeutic strategies in metabolic diseases.

Screening for potential warning biomarkers in cows with ketosis based on host-microbiota co-metabolism analysis

Introduction

The risk of ketosis is assessed by monitoring changes in plasma metabolites and cow behavior during the peripartum period. However, little is known about changes in the fecal bile acid and microbiota of cows before parturition. Therefore, this study clarified the bile acid profile and screened potential warning biomarkers in heifers 7 days before calving.

Methods

Ninety healthy cows were tracked in the transition period, and plasma and feces were collected 7 days before calving, on calving day, and 7 days after calving. The cows were divided into ketosis and healthy groups based on the blood β-hydroxybutyric acid levels from day 7 after calving. The levels of serum biochemical indices were measured at three time points using commercial kits. Ten cows in the ketosis group (KET-7) and 10 healthy cows (HEA-7) were randomly selected 7 days before calving for metabolome and 16S rRNA amplicon sequencing.

Results

No significant differences in serum energy-related indices were observed 7 days before calving. The major bile acids in the feces of the KET-7 group were non-conjugated secondary bile acids (UnconSBA). Differential bile acids were primarily derived from UnconSBA. The potential ketosis warning metabolite in feces for 7 days before delivery was isodeoxycholic acid. The abundance of Rikenellaaceae-RC9-gut-group in the KET-7 group increased, whereas the abundance of Oscillospiraceae UCG-010 bacteria significantly decreased. Lactobacillus and Prevotella-9 in feces were potential warning biomarkers for ketosis in dairy cows 7 days before calving. The variation in differential bile acids in the plasma, consistent with the feces, was mainly derived from UnconSBA. Lithocholic acid in the plasma was a potential ketosis warning metabolite 7 days before delivery.

Conclusion

Ketotic cows experienced bile acid metabolism disorders 7 days before calving, and the gut microbiota was closely related to bile acid metabolism disorders. Future studies should investigate the relationship between secondary bile acids and the development of ketosis.

Non-targeted metabolomics identifies biomarkers in milk with high and low milk fat percentage

Milk is widely recognized as an important food source with health benefits. Different consumer groups have different requirements for the content and proportion of milk fat; therefore, it is necessary to investigate the differential metabolites and their regulatory mechanisms in milk with high and low milk fat percentages (MFP). In this study, untargeted metabolomics was performed on milk samples from 13 cows with high milk fat percentage (HF) and 13 cows with low milk fat percentage (LF) using ultra-high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS/MS). Forty-eight potential differentially labeled compounds were screened using the orthogonal partial least squares-discriminant analysis (OPLS-DA) combined with the weighted gene co-expression network analysis (WGCNA) method. Amino acid metabolism was the key metabolic pathway with significant enrichment of L-histidine, 5-oxoproline, L-aspartic acid, and L-glutamic acid. The negative correlation with MFP differentiated the HF and LF groups. To further determine the potential regulatory role of these amino acids on milk fat metabolism, the expression levels of marker genes in the milk fat synthesis pathway were explored. It was noticed that L-histidine reduced milk fat concentration primarily by inhibiting the triglycerides (TAG) synthesis pathway. L-aspartic acid and L-glutamic acid inhibited milk fat synthesis through the fatty acid de novo and TAG synthesis pathways. This study provides new insights into the mechanism underlying milk fat synthesis and milk quality improvement.

Lipolysis inhibition as a treatment of clinical ketosis in dairy cows: Effects on adipose tissue metabolic and immune responses

Dairy cows with clinical ketosis (CK) exhibit excessive adipose tissue (AT) lipolysis and systemic inflammation. Lipolysis in cows can be induced by the canonical (hormonally induced) and inflammatory lipolytic pathways. Currently, the most common treatment for CK is oral propylene glycol (PG); however, PG does not reduce lipolysis or inflammation. Niacin (NIA) can reduce the activation of canonical lipolysis, whereas cyclooxygenase inhibitors such as flunixin meglumine (FM) can limit inflammation and inhibit the inflammatory lipolytic pathway. The objective of this study was to determine the effects of including NIA and FM in the standard PG treatment for postpartum CK on AT function. Multiparous Jersey cows [n = 18; 7.1 (SD = 3.8) DIM] were selected from a commercial dairy. Inclusion criteria were CK symptoms (lethargy, depressed appetite, and drop in milk yield) and high blood levels of β-hydroxybutyrate (BHB ≥ 1.2 mmol/L). Cows with CK were randomly assigned to one of 3 treatments: 1) PG: 310 g administered orally once per d for 5 d, 2) PG+NIA: 24 g administered orally oral once per d for 3 d, 3) PG+NIA+FM: 1.1 mg/kg administered IV once per day for 3 d. Healthy cows (HC; n = 6) matched by lactation and DIM (±2 d) were sampled. Subcutaneous AT explants were collected at d 0 (d0) and 7 (d7) relative to enrollment. To assess AT insulin sensitivity, explants were treated with insulin (INS = 1 µL/L) during lipolysis stimulation with a β-adrenergic receptor agonist (isoproterenol, ISO = 1 µM). Lipolysis was quantified by glycerol release in the media. Lipid mobilization and inflammatory gene networks were evaluated using real-time qPCR. Protein biomarkers of lipolysis, insulin signaling, and AT inflammation, including HSL, AKT, and ERK1/2, were quantified by capillary immunoassays. Flow cytometry of AT cellular components was used to characterize macrophage inflammatory phenotypes. Statistical significance was determined by a non-parametric t-test when 2 groups (HC vs CK) were analyzed and an ANOVA test with Tukey adjustment when 3 treatment groups (PG vs PGNIA vs PGNIAFM) were evaluated. At d0, AT from CK cows showed higher mRNA expression of lipolytic enzymes ABHD5, LIPE, and LPL, as well as increased phosphorylation of the lipase HSL (pHSL) compared with HC. At d0, INS reduced lipolysis by 41 ± 8% in AT from HC, while CK cows were unresponsive (-2.9 ± 4%). AT from CK cows exhibited reduced Akt phosphorylation compared with HC. CK had increased AT expression of inflammatory gene markers, including CCL2, IL8, IL10, TLR4, and TNF, along with ERK1/2 phosphorylation. AT from CK cows showed increased macrophage infiltration compared with HC. By d7, AT from PGNIAFM cows had a more robust response to INS, as evidenced by reduced glycerol release (36.5 ± 8% compared with PG, 26.9 ± 7%, and PGNIA, 7.4 ± 8%) and enhanced phosphorylation of Akt. By d7, PGNIAFM cows presented lower inflammatory markers, including ERK1/2 phosphorylation and reduced macrophage infiltration, compared with PG and PGNIA. These data suggest that including NIA and FM in CK treatment improves AT insulin sensitivity and reduces AT inflammation and macrophage infiltration.

Differences in Milk Proteomic Profiles between Estrous and Non-Estrous Dairy Cows

Efficient reproductive management of dairy cows depends primarily upon accurate estrus identification. However, the currently available estrus detection methods, such as visual observation, are poor. Hence, there is an urgent need to discover novel biomarkers in non-invasive bodily fluids such as milk to reliably detect estrus status. Proteomics is an emerging and promising tool to identify biomarkers. In this study, the proteomics approach was performed on milk sampled from estrus and non-estrus dairy cows to identify potential biomarkers of estrus. Dairy cows were synchronized and timed for artificial insemination, and the cows with insemination leading to conception were considered to be in estrus at the day of insemination (day 0). Milk samples of day 0 (estrus group) and day -3 (non-estrus group) from dairy cows confirming to be pregnant were collected for proteomic analysis using the tandem mass tags (TMT) proteomics approach. A total of 89 differentially expressed proteins were identified, of which 33 were upregulated and 56 were downregulated in the estrus milk compared with the non-estrus milk. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that acetyl coenzyme A carboxylase α (ACACA), apolipoprotein B (APOB), NAD(P)H steroid dehydrogenase-like (NSDHL), perilipin 2 (PLIN2), and paraoxonase 1 (PON1) participated in lipid binding, lipid storage, lipid localization, and lipid metabolic process, as well as fatty acid binding, fatty acid biosynthesis, and fatty acid metabolism, and these processes are well documented to be related to estrus regulation. These milk proteins are proposed as possible biomarkers of estrus in dairy cows. Further validation studies are required in a large population to determine their potential as estrus biomarkers.

Untargeted metabolomics and lipidomics to assess plasma metabolite changes in dairy goats with subclinical hyperketonemia

Subclinical hyperketonemia (SCHK) is the major metabolic disease observed during the transition period in dairy goats, and is characterized by high plasma levels of nonesterified fatty acids (NEFA) and β-hydroxybutyrate (BHB). However, no prior study has comprehensively assessed metabolomic profiles of dairy goats with SCHK. Plasma samples were collected within 1 h after kidding from SCHK goats (BHB concentration >0.8 mM, n = 7) and clinically healthy goats (BHB concentration <0.8 mM, n = 7) with similar body condition score (2.75 ± 0.15, mean ± standard error of the mean) and parity (primiparous). A combination of targeted and untargeted mass spectrometric approaches was employed for analyzing the various changes in the plasma lipidome and metabolome. Statistical analyses were performed using the GraphPad Prism 8.0, SIMCA-P software (version 14.1), and R packages (version 4.1.3). Plasma aminotransferase, nonesterified fatty acids, and BHB concentrations were greater in the SCHK group, but plasma glucose concentrations were lower. A total of 156 metabolites and 466 lipids were identified. The analysis of untargeted metabolomics data by principal component analysis and orthogonal partial least squares discriminant analysis revealed a separation between SCHK and clinically healthy goats. According to the screening criteria (unpaired t-test, P < 0.05), 30 differentially altered metabolites and 115 differentially altered lipids were detected. Pathway enrichment analysis identified citrate cycle, alanine, aspartate and glutamate metabolism, glyoxylate and dicarboxylate metabolism, and phenylalanine metabolism as significantly altered pathways. A greater concentration of plasma isocitric acid and cis-aconitic acid levels was observed in SCHK goats. In addition, AA such as lysine and isoleucine were greater, whereas alanine and phenylacetylglycine were lower in SCHK dairy goats. Dairy goats with SCHK also exhibited greater oleic acid, acylcarnitine, and phosphatidylcholine and lower choline and sphingomyelins. Acylcarnitines, oleic acid, and tridecanoic acid displayed positive correlations with several lipid species. Alanine, hippuric acid, and histidinyl-phenylalanine were negatively correlated with several lipids. Overall, altered metabolites in SCHK dairy goats indicated a more severe degree of negative energy balance. Data also indicated an imbalance in the tricarboxylic acid (TCA) cycle, lipid metabolism, and AA metabolism. The findings provide a more comprehensive understanding of the pathogenesis of SCHK in dairy goats.

Milk proteins as a feed restriction signature indicating the metabolic adaptation of dairy cows

Milk production in dairy cows is affected by numerous factors, including diet. Feed restriction is known to have little impact on milk total protein content but its effect on the fine protein composition is still poorly documented. The objective of this study was to describe the effects of two feed restriction trials of different intensities on the milk protein composition of Holstein cows. One restriction trial was of high intensity (H: 8 mid-lactation Holstein cows) and the second of moderate intensity (M: 19 peak lactation Holstein cows). Feed restriction decreased the milk protein yield for caseins under the M trial and of all six major milk proteins under the H trial. These decreased yields lead to lower concentrations of αs1-, αs2- and β-caseins during the H trial. The milk proteome, analyzed on 32 milk samples, was affected as a function of restriction intensity. Among the 345 proteins identified eight varied under the M trial and 160 under the H trial. Ontology analyses revealed their implication in carbohydrate, lipid and protein metabolisms as well as in the immune system. These proteins reflected adaptations of the animal and mammary gland physiology to feed restriction and constituted a signature of this change.

Genome-wide elucidation of CNV regions and their association with production and reproduction traits in composite Vrindavani cattle

The present study was aimed to analyze the genome-wide copy number variations (CNVs) in Vrindavani composite cattle and concatenate them into CNV regions (CNVRs), and finally test the association of CNVRs with different production and reproduction traits. Genotypic data, generated on BovineSNP50 Beadchip (v3) array for 96 Vrindavani animals, was used to elucidate the CNVs at the genome level. Intensity data covering over 53,218 SNP genotypes on bovine genome was used. Algorithm based on Hidden Markov Model was employed in PennCNV program to detect, normalize and filter CNVs across the genome. 252 putative CNVs, detected via PennCNV program, in different individuals were concatenated into 71 CNV regions (CNVRs) using CNVRuler program. Association of CNVRs with important (re)production traits in Vrindavani animals was assessed using linear regression. Five CNVRs were found to be significantly associated with ten important (re)production traits. The genes harbored in these regions provided useful insights into the association of CNVRs with genes and ultimately the variation at phenotype level. Important genes that overlapped with CNVRs included WASHC4, HS6ST3, MBNL2, TOLLIP, PIDD1 and TSPAN4. Furthermore, the CNVRs were found to overlap with important QTLs available in AnimalQTL database which affect milk yield and composition along with reproduction and immune function traits. The copy number states of three enes were validated using digital droplet PCR technique. The results from the present study significantly enhance the understanding about CNVs in Vrindavani cattle and should help establish its CNV map. The study will also enable further investigation on association of these variants with important traits of economic interest including disease incidence.

Effects of higher plasma growth hormone levels on subclinical ketosis in postpartum Holstein cows

Ketosis is a major metabolic disorder that can lead to huge economic losses in postpartum dairy cows by influencing milk production and reproduction performance. Therefore, it is very important to understand the characteristics and significance of plasma GH levels and dynamic changes in postpartum dairy cows for finding pathogenesis of subclinical ketosis (SK). The present study aimed to determine the role of growth hormone (GH) from the onset of SK to the fifth week postpartum and to explain the variations in GH, and metabolic markers namely, β-hydroxybutyric acid (BHBA), non-esterified fatty acid (NEFA) and glucose (GLU) at early and later SK stages in postpartum Holstein cows. A 5-wk test and an intraday 12-h test were conducted in postpartum Holstein cows. Both tests were carried out every three hours from 10:00–22:00 for 7–14 days postpartum (12-h test: n = 16) to determine plasma concentrations of GH, BHBA, NEFA and GLU. The 5-wk test results showed that GH, BHBA and NEFA concentrations were significantly higher in the SK group during the five-weeks postpartum (p < 0.01); GLU concentration was significantly lower in the SK group (p < 0.01). Intraday 12-h test results revealed that the feeding time affected the plasma concentrations of GH, BHBA, NEFA and GLU. After 1-h of feeding time, GH concentrations decreased, while BHBA, NEFA and GLU concentrations increased. After 4-h of feeding time GH, BHBA and NEFA had the highest plasma concentrations, and GLU the lowest. In both experiments, GH was positively correlated with BHBA, NEFA, and negatively correlated with GLU. It can be suggested that GH has a potential role in development and aetiology of subclinical ketosis.

Integration of Multiplied Omics, a Step Forward in Systematic Dairy Research

Due to their unique multi-gastric digestion system highly adapted for rumination, dairy livestock has complicated physiology different from monogastric animals. However, the microbiome-based mechanism of the digestion system is congenial for biology approaches. Different omics and their integration have been widely applied in the dairy sciences since the previous decade for investigating their physiology, pathology, and the development of feed and management protocols. The rumen microbiome can digest dietary components into utilizable sugars, proteins, and volatile fatty acids, contributing to the energy intake and feed efficiency of dairy animals, which has become one target of the basis for omics applications in dairy science. Rumen, liver, and mammary gland are also frequently targeted in omics because of their crucial impact on dairy animals’ energy metabolism, production performance, and health status. The application of omics has made outstanding contributions to a more profound understanding of the physiology, etiology, and optimizing the management strategy of dairy animals, while the multi-omics method could draw information of different levels and organs together, providing an unprecedented broad scope on traits of dairy animals. This article reviewed recent omics and multi-omics researches on physiology, feeding, and pathology on dairy animals and also performed the potential of multi-omics on systematic dairy research.

Integration of Urine Proteomic and Metabolomic Profiling Reveals Novel Insights Into Neuroinflammation in Autism Spectrum Disorder

Autism spectrum disorder (ASD) comprises a group of neurodevelopmental disorders whose etiology and pathogenesis are not fully understood. To gain insight into the molecular basis of ASD, we performed comparative integrated proteomic and metabolomic analyses of urine samples from children diagnosed with ASD and healthy children. All 160 samples underwent proteomics analysis and 60 were analyzed by liquid chromatography-mass spectrometry to obtain metabolite profiles. We identified 77 differentially expressed proteins (DEPs; 21 downregulated and 56 upregulated) and 277 differentially expressed metabolites; 31 of the DEPs including glutathione, leukocyte antigens, glycoproteins, neural adhesion factors, and immunoglobulins, have been implicated in neuroinflammation. The proteomic analysis also revealed 8 signaling pathways that were significantly dysregulated in ASD patients; 3 of these (transendothelial leukocyte migration, antigen processing and presentation, and graft vs. host disease) were associated with the neuroimmune response. The metabolism of tryptophan, which is also related to the neuroimmune response, has been found to play a potential role in ASD. Integrated proteome and metabolome analysis showed that 6 signaling pathways were significantly enriched in ASD patients, 3 of which were correlated with impaired neuroinflammation (glutathione metabolism, metabolism of xenobiotics by cytochrome P450 and transendothelial migration of leukocyte). We also found a correlation between prostaglandin (PG) E2 levels and the inflammatory response in ASD. These results underscore the prominent role of the neuroimmune response in ASD and provide potential biomarkers that can be used for diagnosis or as targets for early intervention.

NEFA Promotes Autophagosome Formation through Modulating PERK Signaling Pathway in Bovine Hepatocytes

During the perinatal period, the abnormally high plasma non-esterified fatty acids (NEFA) concentration caused by the negative energy balance (NEB) can impose a significant metabolic stress on the liver of dairy cows. Endoplasmic reticulum (ER) stress is an important adaptive response that can serve to maintain cell homeostasis in the event of stress. The protein kinase R-like endoplasmic reticulum kinase (PERK) pathway is the most rapidly activated cascade when ER stress occurs in cells and has an important impact on the regulation of hepatic lipid metabolism and autophagy modulation. However, it is unknown whether NEFA can affect autophagy through modulating the PERK pathway, under NEB conditions. In this study, we provide evidence that NEFA treatment markedly increased lipid accumulation, the phosphorylation level of PERK and eukaryotic initiation factor 2α (eIF2α), and the expression of glucose-regulated protein 78 (Grp78), activating transcription factor 4 (ATF4), and C/EBP homologous protein (CHOP). More importantly, NEFA treatment can cause a substantial increase in the protein levels of autophagy-related gene 7 (ATG7), Beclin-1 (BECN1), sequestosome-1 (p62), and microtubule-associated protein 1 light chain 3 (LC3)-II, and in the number of autophagosomes in primary bovine hepatocytes. The addition of GSK2656157 (PERK phosphorylation inhibitor) can significantly inhibit the effect of NEFA on autophagy and can further increase lipid accumulation. Overall, our results indicate that NEFA could promote autophagy via the PERK pathway in bovine hepatocytes. These findings provide novel evidence about the potential role of the PERK signaling pathway in maintaining bovine hepatocyte homeostasis.