Systemic profiling of ectopic fat deposits in the reproductive tract of dairy cows

Adipose Tissue Inflammation: Linking Physiological Stressors to Disease Susceptibility

The study of adipose tissue (AT) is enjoying a renaissance. White, brown, and beige adipocytes are being investigated in adult animals, and the critical roles of small depots like perivascular AT are becoming clear. But the most profound revision of the AT dogma has been its cellular composition and regulation. Single-cell transcriptomic studies revealed that adipocytes comprise well under 50% of the cells in white AT, and a substantial portion of the rest are immune cells. Altering the function of AT resident leukocytes can induce or correct metabolic syndrome and, more surprisingly, alter adaptive immune responses to infection. Although the field is dominated by obesity research, conditions such as rapid lipolysis, infection, and heat stress impact AT immune dynamics as well. Recent findings in rodents lead to critical questions that should be explored in domestic livestock as potential avenues for improved animal resilience to stressors, particularly as animals age.

Predicting Pregnancy Outcome in Dairy Cows: The Role of IGF-1 and Progesterone

The purpose of this study was to determine the link between insulin-like growth factor 1 (IGF-1), progesterone (PROG), non-esterified fatty acids (NEFAs), β-hydroxybutyrate (BHB), and glucose (GLU) and pregnancy probability after the first artificial insemination (AI) and during the first 100 days in milk (DIM), during the critical transition period. We determined levels of serum IGF-1, PROG, NEFA, BHB, and GLU in Holstein dairy cows via ELISA, using blood samples collected 7 days before parturition (DAP) until 21 days postparturition (DPP). The group was split into cows diagnosed pregnant at 100 DIM (PREG) and those that did not conceive at 100 and 150 DIM (NPREG). Serum IGF-1 and PROG median levels at 7 DAP were significantly higher in PREG vs. NPREG (p = 0.029), the only statistically significant differences across the subgroups. At 7 DAP, IGF-1 levels within the initial group showed a strong negative correlation with PROG (r = -0.693; p = 0.006), while for the PREG subgroup, the IGF-1 levels exhibited a very strong positive correlation with GLU (r = 0.860; p = 0.011) and NEFA (r = 0.872; p = 0.013). IGF-1 and PROG levels detected at 7 DAP may be useful to predict pregnancy at 100 DIM. The positive correlation of NEFA and GLU levels during the transition period demonstrates that the initial group is not in NEB; thus, the NEFA level was not a decisive factor for reproduction success.

Reproductive tract size and position score: Estimation of genetic parameters for a novel fertility trait in dairy cows

The dairy industry is moving toward selecting animals with better fertility to decrease the economic losses linked to reproductive issues. The reproductive tract size and position score (SPS) was recently developed in physiological studies as an indicator of pregnancy rate and the number of services to conception. Cows are scored as SPS 1, 2, or 3 based on the size of their reproductive tract and its position in the pelvis, as determined by transrectal palpation. The objective of this study was to estimate genetic parameters for SPS to assess its potential as a novel fertility trait. Phenotypes were collected at the University of British Columbia's research herd from 2017 to 2020, consisting of 3,247 within- and across-lactation SPS records from 490 Holstein cows. A univariate animal model was used to estimate the variance components for SPS. Both threshold and linear models were fit under a Bayesian approach and the results were compared using the Spearman rank correlation (r) between the estimated breeding values. The 2 models ranked the animals very similarly (r = 0.99), and the linear model was selected for further analysis. Genetic correlations with other currently evaluated traits were estimated using a bivariate animal model. The posterior means (± posterior standard deviation) for heritability and repeatability within- and across-lactation were 0.113 (± 0.013), 0.242 (± 0.012), and 0.134 (± 0.014), respectively. The SPS showed null correlations with production traits and favorable correlations with traditional fertility traits, varying from -0.730 (nonreturn rate) to 0.931 (number of services). Although preliminary, these results are encouraging because SPS seems to be more heritable than and strongly genetically correlated with number of services, nonreturn rate, and first service to conception, indicating potential for effective indirect selection response on these traits from SPS genetic selection. Therefore, further studies with larger data sets to validate these findings are warranted.

Metabolomic profiles of plasma and uterine luminal fluids from healthy and repeat breeder Holstein cows

Background

Repeat breeding is a critical reproductive disorder in cattle. The problem of repeat breeder cattle remains largely unmanageable due to a lack of informative biomarkers. Here, we utilized metabolomic profiling in an attempt to identify metabolites in the blood plasma and uterine luminal fluids. We collected blood and uterine fluid from repeat breeder and healthy cows on day 7 of the estrous cycle.

Results

Metabolomic analysis identified 17 plasma metabolites detected at concentrations that distinguished between the two groups, including decreased various bile acids among the repeat breeders. However, no metabolites that varied significantly were detected in the uterine luminal fluids between two groups. Among the plasma samples, kynurenine was identified as undergoing the most significant variation. Kynurenine is a metabolite produced from tryptophan via the actions of indoleamine 2,3-dioxygenase (IDO). As IDO is key for maternal immune tolerance and induced in response to interferon tau (IFNT, ruminant maternal recognition of pregnancy factor), we examined the responsiveness to IFNT on peripheral blood mononuclear cells (PBMC) isolated from healthy and repeat breeder cows. The mRNA expression of IFNT-response makers (ISG15 and MX2) were significantly increased by IFNT treatment in a dose-dependent manner in both groups. Although treatment with IFNT promoted the expression of IDO in PBMCs from both groups, it did so at a substantially reduced rate among the repeat breeder cows, suggesting that decreased levels of kynurenine may relate to the reduced IDO expression in repeat breeder cows.

Conclusions

These findings provide valuable information towards the identification of critical biomarkers for repeat breeding syndrome in cattle.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12917-021-02755-7.

Unsupervised clustering of multiparametric fluorescent images extends the spectrum of detectable cell membrane phases with sub-micrometric resolution

Solvatochromic probes undergo an emission shift when the hydration level of the membrane environment increases and are commonly used to distinguish between solid-ordered and liquid-disordered phases in artificial membrane bilayers. This emission shift is currently limited in unraveling the broad spectrum of membrane phases of natural cell membranes and their spatial organization. Spectrally resolved fluorescence lifetime imaging can provide pixel-resolved multiparametric information about the biophysical state of the membranes, like membrane hydration, microviscosity and the partition coefficient of the probe. Here, we introduce a clustering based analysis that, leveraging the multiparametric content of spectrally resolved lifetime images, allows us to classify through an unsupervised learning approach multiple membrane phases with sub-micrometric resolution. This method extends the spectrum of detectable membrane phases allowing to dissect and characterize up to six different phases, and to study real-time phase transitions in cultured cells and tissues undergoing different treatments. We applied this method to investigate membrane remodeling induced by high glucose on PC-12 neuronal cells, associated with the development of diabetic neuropathy. Due to its wide applicability, this method provides a new paradigm in the analysis of environmentally sensitive fluorescent probes.

Machine-learning assisted confocal imaging of intracellular sites of triglycerides and cholesteryl esters formation and storage

All living systems are maintained by a constant flux of metabolic energy and, among the different reactions, the process of lipids storage and lipolysis is of fundamental importance. Current research has focused on the investigation of lipid droplets (LD) as a powerful biomarker for the early detection of metabolic and neurological disorders. Efforts in this field aim at increasing selectivity for LD detection by exploiting existing or newly synthesized probes. However, LD constitute only the final product of a complex series of reactions during which fatty acids are transformed into triglycerides and cholesterol is transformed in cholesteryl esters. These final products can be accumulated in intracellular organelles or deposits other than LD. A complete spatial mapping of the intracellular sites of triglycerides and cholesteryl esters formation and storage is, therefore, crucial to highlight any potential metabolic imbalance, thus predicting and counteracting its progression. Here, we present a machine learning assisted, polarity-driven segmentation which enables to localize and quantify triglycerides and cholesteryl esters biosynthesis sites in all intracellular organelles, thus allowing to monitor in real-time the overall process of the turnover of these non-polar lipids in living cells. This technique is applied to normal and differentiated PC12 cells to test how the level of activation of biosynthetic pathways changes in response to the differentiation process.

Quantitative imaging of membrane micropolarity in living cells and tissues by spectral phasors analysis

Intracellular micropolarity is essential in several metabolic processes, as it controls membrane permeability, regulating the fluxes of molecules and energy. Here we describe a method for the determination of the micropolarity in living cells using spectral confocal microscopy. The method is based on a phasor analysis of spectrally resolved images of live cells, labelled with the solvatochromic probe Nile Red. An application is provided to extract a polarity profile from the acquired Spectral datasets, which represent the contribution of hyperpolar, polar and non-polar lipids, and to generate a micropolarity map at submicrometric spatial resolution. A metabolic parameter, representing a quantitative index of the fatty acid-triacylglycerol turnover, is also furnished. This method allows a functional profiling of cells and tissues and the detection of metabolic imbalances between lipid storage and usage. •Use of spectral resolved confocal microscopy of Nile Red labelled cells for pixel resolved determination of the membranes micropolarity.•Spectral acquisition increases the specificity and sensitivity of the detection to provide a polarity profile and a metabolic index for fatty acid-TG turnover.•Use of spectral resolved confocal microscopy of Nile Red labelled cells for pixel resolved determination of the membranes micropolarity.