[Comparison of different methods for monitoring of acid base status in dairy cow herds]. / Methodenvergleich zur Überwachung des Säuren-Basen-Status in Milchviehherden.

OBJECT AND PURPOSE: Acid-base disorders in dairy herds can be diagnosed by determining urinary net base excretion (NBE). Modifications of this method are the differential NBE (dNBE) with determination of the urinary concentration-independent base-acid ratio (BAR) and the simplified NBE test with reduced urine volume (sNBE). The aim of this study was to compare these methods among themselves and as a pooled test, in their assessment of cow group acid base status as well as to derive recommendations for practical use. ANIMALS, MATERIAL, AND METHODS: The concentrations of NBE, dNBE, and sNBE were measured in urine samples derived from 855 German-Holstein cows in 127 cow groups at different stages of lactation. BAR was then calculated. dNBE and BAR were determined both individually per cow and as a pool of a group. Mixed linear models were used to examine the relationship between the mean of the individual animal values and the pool sample result of a group for these two parameters. In addition, all groups were evaluated with respect to acidotic or alkalotic load based on their single animal results of the respective methods, the mean values formed from them, and the measured pool result. By using the single animal BAR as reference, the sensitivity and specificity of the different methods were calculated. RESULTS: The calculated mean values of the individual measurements of dNBE and BAR differed from the measured value in the pool sample, especially in low and high measurement ranges. In the group assessment, NBE showed the best combined sensitivity and specificity for the detection of acid base disorders. The dNBE pool assay showed satisfactory specificity with respect to acidosis and alkalosis, while the sNBE on an individual animal basis and the BAR determination in the pool showed satisfactory sensitivity with respect to acidosis. CONCLUSIONS AND CLINICAL RELEVANCE: It was shown that NBE determined in individual animal samples is well suited for the assessment of acid base status of cow groups and can therefore be recommended for practical use. The determination of dNBE as well as BAR as a pool test is not sufficient for the detection of alkalotic load in cow groups but may help to confirm an existing acidotic load.

Antibodies against SARS-CoV-2 Suggestive of Single Events of Spillover to Cattle, Germany.

Human infection with SARS-CoV-2 poses a risk for transmission to animals. To characterize the risk for cattle, we serologically investigated 1,000 samples collected from cattle in Germany in late 2021. Eleven antibody-positive samples indicated that cattle may be occasionally infected by contact with SARS-CoV-2-positive keepers, but we found no indication of further spread.

Effects of Parity and Stage of Lactation on Trend and Variability of Metabolic Markers in Dairy Cows.

Metabolic monitoring is a tool that is helpful with the increasing requirements regarding feeding and health management in dairy herds. This study aimed at describing the trend and variability of different biochemical parameters in blood and urine in relation to the stages of lactation and parity, in a retrospective analysis of laboratory data from clinically healthy German Holstein cows. The results were derived from metabolic monitoring in Thuringia (Germany), during 2009-2019. A total of 361,584 measured values, of 13 different metabolic variables, were assigned to parity (primiparous and multiparous) and stage of lactation (10 classes from -30 to 300 days in milk). The Kruskal-Wallis test was applied for the evaluation of differences regarding parity or the stage of lactation. Non-esterified fatty acids, beta hydroxybutyrate, and the activity of aspartate aminotransferase in serum were clearly affected by parity and lactation. Serum concentrations of cholesterol, bilirubin, and phosphorus, as well as the serum activity of glutamate dehydrogenase, were affected by the stage of lactation, while parity impacted urea concentration. The serum activity of creatine kinase, serum concentrations of calcium, and urine concentrations of net acid base excretion, potassium, and sodium were not affected by parity or lactation. In conclusion, specific reference limits, with respect to parity and the stage of lactation, are necessary.

Maternal Impact on Serum Immunoglobulin and Total Protein Concentration in Dairy Calves.

For dairy calves, sufficient supply with high-quality maternal colostrum is crucial to achieve adequate passive transfer of immunoglobulins. This observational cross-sectional study aimed to determine the influence of the prepartum metabolic status of dams on the serum immunoglobulin and total protein concentrations of their dairy calves, taking other relevant management factors into account. A total of 551 cows and their calves from 124 German dairy farms were included. Blood and urine samples of the cows were sampled 1 to 3 weeks before the expected calving date. Two generalized linear mixed effects regression models were fitted to the data. An increase in a dam's prepartum serum non-esterified fatty acids concentration was associated with greater serum immunoglobulin concentration in her calf. Calves of herds with established birth monitoring at night showed greater serum immunoglobulin and total protein concentrations. Calves being fed more than 2 L of colostrum and higher Brix values for colostrum were related to greater serum immunoglobulin and total protein concentrations in calves. In conclusion, there is evidence that, besides timely and sufficient supply of high-quality colostrum to new-born calves, the prepartum metabolic status of cows and birth monitoring impact the passive transfer of immunoglobulins.

Associations between the metabolic status of the cow and colostrum quality as determined by Brix refractometry.

Supplying newborn calves with immunoglobins is critical for their health and a daily challenge in the dairy industry. Among various factors determining colostrum quality, the prepartum metabolic status of the cow might be of particular importance. The objective of this observational cross-sectional study was to evaluate relationships between cow-level variables and the colostrum quality as determined by Brix refractometry. A total of 873 cows of varying breed and parity from 124 German dairy herds were included in the study, and blood and urine samples were taken 3 to 1 wk before the expected calving date. Effectively, samples were collected on average 8.2 d (geometric mean) before calving, ranging from 2 to 45 d. The final variable set included body condition score, lameness score, breed, parity, vaccination of the cow, the activity of glutamate dehydrogenase and aspartate aminotransferase, the urine concentration of creatinine, net acid-base excretion, the serum concentration of cholesterol and calcium, and the difference in albumin and total protein concentration. Generalized linear mixed effects regression models with hierarchically structured random effects (cow within herd) using the maximum likelihood method were fitted to the data to identify associations between the Brix value as an outcome and cow-level variables as predictors. Cows entering second parity had lower Brix values compared with cows entering third or greater parity, and prepartum vaccination of cows led to higher Brix values compared with nonvaccinated cows. Cows with a moderate to high lameness score had lower Brix values than cows with low-grade lameness. An increase of glutamate dehydrogenase serum activity and serum calcium concentration were associated with lower Brix values, whereas an increase in the difference of total protein and albumin serum concentration led to higher Brix values. In conclusion, the metabolic health of the cow affects colostrum quality and may cause failure of passive immunoglobulin transfer as well as impaired calf health.

Relationships between body condition, body condition loss, and serum metabolites during the transition period in primiparous and multiparous cows.

In the transition period from late gestation to early lactation, dairy cows undergo tremendous metabolic changes. Insulin is a relevant antilipolytic factor. Decreasing serum concentrations of insulin and glucose, increasing serum concentrations of nonesterified fatty acids (NEFA) and ß-hydroxybutyrate (BHB), and changes in body condition score (BCS) reflect the negative energy balance around calving. This study investigated peripartum metabolic adaptation in 359 primiparous and 235 multiparous German Holstein cows from a commercial dairy herd under field conditions. Body condition score was recorded and blood samples were taken 10 to 1 d prepartum, 2 to 4 d postpartum, and 12 to 20 d postpartum. Generalized mixed models and generalized estimation equations were applied to assess associations between prepartum BCS; BCS changes during the transition period; insulin, glucose, NEFA, and BHB serum concentrations; and milk yield, which was taken from an electronic milk meter from d 6 of lactation. Serum insulin concentrations of multiparous postpartum cows were lower compared with prepartum, and compared with primiparous cows. In general, primiparous cows had lower postpartum NEFA and BHB concentrations than multiparous cows. In primiparous cows, we identified a positive association between prepartum BCS and prepartum serum insulin concentration. Prepartum obese multiparous cows, but not primiparous cows, were characterized by higher postpartum serum NEFA and BHB concentrations and lower milk yield than other cows in the same parity class. Primiparous cows with a smaller degree of BCS loss during the transition period had higher postpartum insulin and lower NEFA concentrations and lower milk yield than other primiparous cows. In conclusion, primiparous cows had less lipolysis and lower milk yield than multiparous cows, associated with higher insulin concentrations. Avoiding high body condition loss during the transition period is a main factor in preventing peripartal metabolic imbalances of glucose and fat metabolism.

Acid-base assessment of post-parturient German Holstein dairy cows from jugular venous blood and urine: A comparison of the strong ion approach and traditional blood gas analysis.

Evaluating acid-base status is important for monitoring dairy herd health. In a field study, we aimed to compare the acid-base status measured by net acid-base excretion (NABE) in urine with results of venous blood analysis in clinically healthy, but possibly metabolically burdened cows in their transition period. For this, we sampled blood from the jugular vein and urine from 145 German Holstein cows within 1 to 76 days post-partum. In blood, the metabolic parameters non-esterified fatty acids (NEFA) and ß-hydroxybutyrate (BHB), as well as numerous parameters of the acid-base status were measured. The traditional approach, based on bicarbonate concentration, base excess (BE) and anion gap (AG), was compared to the strong ion approach variables, e.g. acid total (Atot), measured strong ion difference (SIDm), strong ion gap (SIG), and unmeasured anions (XA), respectively. Results of both approaches were set against the outcome of urine analysis, i.e. the NABE, base-acid ratio and pH of urine, in a cluster analysis, which provided 7 moderately stable clusters. Evaluating and interpreting these 7 clusters offered novel insights into the pathophysiology of the acid-base equilibrium in fresh post-partum dairy cows. Especially in case of subclinical acid-base disorders, the parameters of the strong ion difference theory, particularly SIDm, Atot and SIG or XA, provided more in-depth information about acid-base status than the traditional parameters BE, bicarbonate or AG in blood. The acid-base status of fresh cows with protein aberrations in blood could be differentiated in a much better way using the strong ion approach than by traditional blood gas analysis or by the measurement of urinary excretion. Therefore, the strong ion approach seems to be a suitable supplement for monitoring acid-base balance in dairy cattle.

Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers.

A recombinant inbred line (RIL) population, derived from two Arabidopsis thaliana accessions, and the corresponding testcrosses with these two original accessions were used for the development and validation of machine learning models to predict the biomass of hybrids. Genetic and metabolic information of the RILs served as predictors. Feature selection reduced the number of variables (genetic and metabolic markers) in the models by more than 80% without impairing the predictive power. Thus, potential biomarkers have been revealed. Metabolites were shown to bear information on inherited macroscopic phenotypes. This proof of concept could be interesting for breeders. The example population exhibits substantial mid-parent biomass heterosis. The results of feature selection could therefore be used to shed light on the origin of heterosis. In this respect, mainly dominance effects were detected.

Predicting Arabidopsis freezing tolerance and heterosis in freezing tolerance from metabolite composition.

Heterosis, or hybrid vigor, is one of the most important tools in plant breeding and has previously been demonstrated for plant freezing tolerance. Freezing tolerance is an important trait because it can limit the geographical distribution of plants and their agricultural yield. Plants from temperate climates increase in freezing tolerance during exposure to low, non-freezing temperatures in a process termed 'cold acclimation'. Metabolite profiling has indicated a major reprogramming of plant metabolism in the cold, but it has remained unclear in previous studies which of these changes are related to freezing tolerance. In the present study, we have used metabolic profiling to discover combinations of metabolites that predict freezing tolerance and its heterosis in Arabidopsis thaliana. We identified compatible solutes and, in particular, the pathway leading to raffinose as crucial statistical predictors for freezing tolerance and its heterosis, while some TCA cycle intermediates contribute only to predicting the heterotic phenotype. This indicates coordinate links between heterosis and metabolic pathways, suggesting that a limited number of regulatory genes may determine the extent of heterosis in this complex trait. In addition, several unidentified metabolites strongly contributed to the prediction of both freezing tolerance and its heterosis and we present an exemplary analysis of one of these, identifying it as a hexose conjugate.

Improved heterosis prediction by combining information on DNA- and metabolic markers.

BACKGROUND: Hybrids represent a cornerstone in the success story of breeding programs. The fundamental principle underlying this success is the phenomenon of hybrid vigour, or heterosis. It describes an advantage of the offspring as compared to the two parental lines with respect to parameters such as growth and resistance against abiotic or biotic stress. Dominance, overdominance or epistasis based models are commonly used explanations. CONCLUSION/SIGNIFICANCE: The heterosis level is clearly a function of the combination of the parents used for offspring production. This results in a major challenge for plant breeders, as usually several thousand combinations of parents have to be tested for identifying the best combinations. Thus, any approach to reliably predict heterosis levels based on properties of the parental lines would be highly beneficial for plant breeding. METHODOLOGY/PRINCIPAL FINDINGS: Recently, genetic data have been used to predict heterosis. Here we show that a combination of parental genetic and metabolic markers, identified via feature selection and minimum-description-length based regression methods, significantly improves the prediction of biomass heterosis in resulting offspring. These findings will help furthering our understanding of the molecular basis of heterosis, revealing, for instance, the presence of nonlinear genotype-phenotype relationships. In addition, we describe a possible approach for accelerated selection in plant breeding.

Towards systems biology of heterosis: a hypothesis about molecular network structure applied for the Arabidopsis metabolome.

We propose a network structure-based model for heterosis, and investigate it relying on metabolite profiles from Arabidopsis. A simple feed-forward two-layer network model (the Steinbuch matrix) is used in our conceptual approach. It allows for directly relating structural network properties with biological function. Interpreting heterosis as increased adaptability, our model predicts that the biological networks involved show increasing connectivity of regulatory interactions. A detailed analysis of metabolite profile data reveals that the increasing-connectivity prediction is true for graphical Gaussian models in our data from early development. This mirrors properties of observed heterotic Arabidopsis phenotypes. Furthermore, the model predicts a limit for increasing hybrid vigor with increasing heterozygosity--a known phenomenon in the literature.