Journal of Dairy Science

Introducing cognitive enrichment from an early age has the potential to enhance an animals capacity to learn both simple and complex tasks, promote neural plasticity, and support cognitive development. This is applicable for young cattle who are at a critical stage in their development and could benefit from the influence cognitive enrichment has on their behavioral expression. This study aims to explore the effects cognitive enrichment has on weaned dairy calves through analyzing behavioral measures of voluntary participation and short-term behavioral reactions to enrichment exposure. Our study involved a total of five pairs of weaned calves (n=8 treatment; n=2 control). The treatment groups were presented with three variations of a puzzle box, each equipped with unique challenges that offer different solutions (push, slide, pull). These boxes were provided to the calves twice daily over the span of nine days in an isolated corridor located behind their pen. We hypothesized that motivated calves would consistently engage with cognitive enrichment voluntarily over time and express directed natural behaviors, reflecting sustained participation across repeated trials. Results demonstrated that calves consistently visited the cognitive enrichment area across trials, with an average latency of 75.7 {+/-} 47.0s from the pen to the enrichment. Secondly, the calves spent a significant proportion of trial time within the enrichment area at 65% (870.1 {+/-} 21s). Lastly, all calves expressed a broad range of behaviors in line with their natural exploration within the enrichment area, while the puzzle box treatment groups expressed higher durations of behavioral expressions when compared to the control (F=11.7, p<0.0001). Combined, these results indicate the calves motivations to voluntarily participate in a cognitive challenge. While these are promising findings for cognitive enrichment and its applicability to dairy calves, further work is needed to understand broader parameters. Specifically, how can social dynamics influence enrichment interaction in groups, how can this type of enrichment be implemented on farms, and what are the long-term effects to providing cognitive enrichment in the early stages of development.

Epigenetics may play a crucial role in livestock adaptation to environmental challenges like heat stress. In recent years, a growing number of studies have investigated the epigenetic mechanisms underlying dairy cow adaptation to heat stress. However, there is still limited knowledge about the effects of heat stress on immune cells and immune-related phenotypes. Herein we aim to identify heat-stress induced DNA methylation variations on blood methylome potentially affecting regulatory regions and associated phenotypes. Blood samples were collected and peripheral blood mononuclear cell (PBMC) isolated from four cows before (D0) and after (D14) a 14-d heat stress challenge (cyclical THI 72-82) and, from four cows kept in thermoneutral conditions (THI 61-64). Heat-stressed cows had ad libitum access to diets supplemented with adequate levels of vitamin D and Ca (12,000 IU/kg of vitamin D and 0.73% Ca, respectively). To eliminate confounding effects due to differences in nutrient intake, cows maintained under thermoneutral conditions were pair-fed (PF) to their heat-stressed counterparts and received adequate concentrations of vitamin D and Ca as well. Reduced representation bisulphite sequencing (RRBS) was used to profile PBMCs methylome. Differential methylation analysis was performed using methylKit and DSS softwares ({Delta}meth [&ge;] 25%, adjusted p-value < 0.01), retaining only commonly detected differentially methylated cytosines (DMCs). A total of 2,908 DMCs were identified when comparing pre- and post-heat stress samples. After excluding 649 DMCs that were also detected under thermoneutral conditions, as these changes were likely associated with feed restriction inherent to the pair-feeding design rather than with heat stress per se, 2,259 heat stress-specific DMCs remained, predominantly hypomethylated. About half of the DMCs are annotated in intronic and intergenic regions; known to harbor regulatory elements. By intersecting the DMRs with publicly available functional annotation data, we observed hypomethylation on regulatory regions putatively affecting cows immune system. As an example, we identified a loss of methylation within an enhancer region of the MSN gene, which is involved in lymphocyte homeostasis, and a loss of methylation in the promoter region of MECP2, a well-established epigenetic regulator with a central role in chromatin organization and gene expression. These findings highlight the impact of heat stress on dairy cow immunity and provide new insights into its epigenetic regulation under environmental stress. Interpretative summaryThis study examined DNA methylation changes induced by heat stress in dairy cows to elucidate epigenetic mechanisms of thermal adaptation. Using RRBS on PBMCs, 2,259 heat stress-specific differentially methylated cytosines were identified, predominantly hypomethylated and enriched in regulatory regions. Functional annotation highlighted immune-related pathways, including hypomethylated regulatory regions near genes (e.g., MSN, ZBTB33, SLC25A5, GNAS, FAM3A, and MECP2) associated with immune function. These findings indicate that heat stress induces targeted epigenetic modifications potentially affecting immune regulation in dairy cows.

BackgroundThis study investigated rumen microbiome reconstitution and methane (CH4) emissions following a complete exchange of rumen contents between low- and high-CH4-yielding Norwegian Red dairy cows. Twenty cows were screened for CH4 yield, and two low and two high emitters were selected for rumen cannulation and content swap. Total rumen contents were swapped after complete evacuation and washing of both the rumen and omasum. Rumen samples were collected twice in weeks -1, 1, 3, and 7 for fermentation analysis, metagenomics, and metaproteomics, and at week 8 CH4 production was measured. ResultsPrior to the swap, low and high emitters produced 21.2 {+/-} 0.7 and 26.3 {+/-} 1.4 g CH4/kg dry-matter intake (DMI), respectively. Eight weeks after swap, CH4 yields were 12.7 {+/-} 0.3 and 28.9 {+/-} 0.3 g CH4/kg DMI, respectively, showing that the CH4 phenotype of each cow was maintained. Analysis of metagenome-derived 16S rRNA gene sequences showed that low emitters gradually re-established their original microbial community, whereas high emitters retained donor-like microbiota. Metaproteomic mapping suggested higher expression of Prevotella-associated succinate-propionate pathway enzymes in low emitters at week 7, though these differences were modest. ConclusionThese findings suggest that host factors influence CH4 output and microbial reconstitution, with low emitters restoring their native microbiome while high emitters retained a donor-associated community yet continued to emit high CH4. Results should be interpreted with caution given the small sample size (n = 2 per phenotype) and require confirmation in larger studies. ImportanceReducing enteric methane from cattle requires understanding whether the rumen microbiome or the host animal is the primary driver of methane output. We exchanged the entire rumen contents between low- and high-methane-yielding dairy cows and measured methane production alongside metagenomic and metaproteomic profiling over two months. Despite receiving each others microbiomes, each cows methane phenotype persisted--low emitters stayed low and high emitters stayed high. Microbiome reconstitution was asymmetric: low emitters restored their original microbial community, while high emitters retained the donor microbiota. Methanogen communities did not differ between phenotypes, pointing to host-level rather than microbial-level control of methane yield. These pilot findings suggest that breeding for favorable host traits may be essential for lasting methane reduction, and that microbiome transfer alone is unlikely to shift an animals methane phenotype. Larger studies are needed to confirm these observations.

Restlessness is a symptom of chronic boredom in humans and a behavioural phenomenon anecdotally described as a concern in bulls raised for fattening purposes, but it has so far not been addressed in research. The two studies presented in this paper aimed to gain first insights into restlessness in bulls. We operationally defined restlessness by the number of transitions between behaviours in a given time period, and quantified restlessness in bulls of different weight classes (300, 400, 500 kg) on farms keeping bulls on fully-slatted floors (n=8, Study 1) as well as across three different husbandry systems (fully-slatted floor (FS, n=4), straw-based (SB, n=4) and organic pasture (OP, n=3), Study 2). All farms were visited twice, and the behaviour of different individuals was continuously recorded for 15 minutes each between 9 a.m. and 5 p.m. (Study 1) and for 8 minutes each between 6 a.m. and 10 p.m. (Study 2). The effects of weight class and husbandry system were analysed using generalised linear mixed-effects models, and we ran a sequence analysis to cluster observations by the sequence, frequency, and duration of bulls behaviours in Study 1. Bulls kept in fully-slatted floor systems in Study 1 changed their behaviour on average 48.3 times per 10 minutes, with high variability both within and across farms. Weight class did not have a statistically supported effect on the number of transitions, and the sequence analysis revealed four clusters that differed in sequence and in the number of transitions. In Study 2, OP bulls showed fewer transitions than SB and FS bulls (X22 = 23.6, p < 0.001), while SB and FS bulls did not differ. While SB pens were more structured and offered more space per animal, both SB and FS systems can be characterised by monotony, which may explain the similar level of restlessness in both systems. Alternatively, or in addition, the high feeding intensity in SB and FS systems may have caused the higher number of transitions compared to the OP system, potentially elicited by subacute ruminal acidosis and/or laminitis and the resulting pain. However, these explanations are speculative and require systematic disentanglement in future studies. This study provides initial insights into restlessness in bulls and lays the groundwork for future research to identify the causes underlying restlessness and investigate its association with bull welfare.

Managing post-weaning diarrhoea (PWD) in piglets is difficult due to limits on antibiotics and zinc. Chitosan is emerging as a potential feed additive. We analysed a chito-oligosaccharide hydrochloride (COS-HCl), a low molecular weight (LMW) chitosan, and a medium molecular weight (MMW) chitosan, and assessed their effects on growth, faecal consistency, microbiota, and potential interference with enterotoxigenic Escherichia coli (ETEC). The three chitosans were characterised using {superscript 1}H-NMR, SEC-RI-MS, and SEC-RI-MALLS. COS-HCl had an Mw of 0.824 kDa; LMW and MMW showed Mw ranges of 14.4 kDa (0.3-30 kDa) and 116 kDa (15-600 kDa). Degrees of acetylation were 9.5%, 6.5%, and 15%. Two 42-day field studies evaluated average daily gain (ADG), faecal consistency, and microbiota. In the first trial, COS-HCl at 0.025-0.1% did not significantly affect ADG (-33 to - 12 g/d). In the second, LMW and MMW at 0.01% did not significantly change ADG (-7 and +3 g/d). Faecal consistency, ETEC shedding, and microbiota composition were similar to controls. An enzymatic HPLC-MS method enabled quantification of MMW chitosan in premix. Our results highlight the importance of advanced chitosan characterisation for precision nutrition and suggest that a threshold dosemay be needed to benefit growth and gut health in PWD management. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/714014v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@19c9e23org.highwire.dtl.DTLVardef@152461aorg.highwire.dtl.DTLVardef@7886e0org.highwire.dtl.DTLVardef@df0d9b_HPS_FORMAT_FIGEXP M_FIG C_FIG

Enteric methane emissions from ruminant livestock contribute to global warming, creating an urgent need for effective mitigation strategies that do not compromise animal productivity and welfare. Methanogenic archaea within the rumen microbiome drive enteric methane emissions. However, large-scale rumen-fluid sampling in commercial production systems is impractical, due to its invasive nature and the associated logistical challenges. This study hypothesised that rumination enables the capture of rumen microbial signals within the oral cavity and using oral microbiome profiles to provide a practical, non-invasive alternative method for proxy methane phenotyping in commercial production systems. To test the hypothesis, we estimated the oral microbiability, defined as the proportion of phenotypic variance in methane emissions explained by oral microbiome variation. Samples were collected from 209 animals across two trials in Queensland, Australia. Oral microbiome samples were obtained from all animals, with paired rumen samples in one trial, and methane emissions were measured using either the sulphur hexafluoride (SF6) tracer technique or the GreenFeed system. Microbial features were characterised using taxonomic and functional annotations, and microbiability was estimated using mixed linear models incorporating microbiome-based relationship matrices. Although the small sample size limited strong conclusions, the oral microbiability estimates reported in this study were comparable to those derived from rumen samples. Functional microbial profiles generally explained a greater proportion of methane variation than taxonomic profiles, suggesting that microbial function is more closely linked to methane production than community composition alone. However, these differences were not statistically significant due to large standard errors. These findings suggest that oral microbiome sampling potentially provides a practical, minimally invasive, scalable proxy method for methane emissions of individual cattle in grazing systems, where direct methane gas measurements are labour-intensive and difficult to implement. Integrating oral microbiome profiles in the existing breeding model with the host genetics, weight and environmental factors could provide a promising pathway for enabling selection for low emissions and advancing reduced emissions livestock farming under real-world production conditions. Lay summaryCattle produce methane as part of their normal digestion and this contributes to climate change. Reducing methane emission in grazing livestock systems is therefore important. However, measuring methane from individual grazing animals is difficult, costly, and often impractical under commercial conditions. The rumen microbiome has been used as a proxy for estimating methane emissions, but collecting rumen samples is invasive and impractical for large-scale use. Because rumination transfers material from the rumen to the mouth, we investigated whether microbes found in cattle mouths could also be used to estimate how much methane an individual animal produced. We suggest that mouth-swab sampling method can be an alternative to rumen fluid sampling because it was less invasive, relatively quick and practically applicable in commercial conditions. Importantly, the microbiome explained a meaningful proportion of the between-animal variation for methane emission. This suggests that collection of mouth swabs is a potentially scalable alternative proxy method to identify cattle that naturally produce less methane. Overall, our findings support the potential use of oral ruminant microbial information to improve breeding and management strategies aimed at reducing methane emissions while maintaining productive livestock systems. Teaser TextThis study demonstrates that collecting oral swabs from the mouths of grazing beef cattle could provide a scalable method to estimate individual methane emissions in commercial production systems, offering a practical alternative to invasive rumen sampling and complex gas measurement systems. These findings support the development of scalable breeding and management strategies for methane mitigation in large-scale livestock production systems.

Transcriptomic analyses are widely used to elucidate the molecular mechanisms driving gametogenesis and reproduction in fish, yet their accuracy depends heavily on appropriate normalization of gene expression data. Conventional approaches that rely on single or multiple reference genes are problematic during teleost oogenesis, as profound structural and physiological remodeling of the ovary challenges the assumption that commonly used reference transcripts remain stable. In this study, we assessed by qPCR the transcriptional variability of four widely used reference genes (actb, ef-1, gapdh, and 18S rRNA) throughout the oogenic cycle of the thicklip grey mullet (Chelon labrosus), using geNorm and NormFinder analyses, and we additionally evaluated total cDNA concentration as an alternative normalization factor. To examine the performance and interpretive consequences of each normalization strategy, we compared expression patterns of key steroidogenic genes (star, cyp19a1a, and cyp11b) normalized by individual reference genes, combinations of reference genes, or total cDNA concentration. All evaluated reference genes displayed notable transcriptional variability across oogenesis, confirming their limited suitability as sole internal controls. In contrast, normalization approaches integrating multiple reference genes and/or total cDNA concentration consistently provided greater stability and more reliable biological interpretation. These results support a refined and more robust normalization framework for transcriptional analyses in fish ovaries, particularly during stages of extensive tissue remodeling. Our findings demonstrate cDNA-based normalization is straightforward, rapid, and easy to implement across laboratories, providing a practical alternative for achieving accurate, reproducible transcript quantification in fish ovary studies.

Mycoplasma bovis was first detected in cattle in New Zealand in 2017, prompting an eradication programme that incorporated extensive surveillance and a test-and-cull policy. Genome sequence data and phylodynamic models were used to inform decision making throughout the eradication programme. Isolates from 697 cattle on 126 farms were collected and sequenced between July 2017 and December 2023. Phylodynamic models were used to estimate the time of most recent common ancestor, the effective reproduction number (Reff) and effective population size, and long-range and local between-farm transmission dynamics. The analysis revealed the dramatic impact of movement restrictions and culling up to early 2020, with a sharp reduction in the Reff to less than 1 in 2018/9 and the extinction of two of three major lineages in 2020. This was followed by three-years of residual infection in farms in the South Island, associated with persistent infection of a large feedlot farm and nearby farms. The comprehensive dataset of genomic and epidemiological data provided a unique opportunity to study the dynamics of a country-wide outbreak of a single-host pathogen from first detection to potential eradication, underlining the utility of integrated genomic surveillance during an outbreak response. Author summaryThe economically important cattle pathogen, Mycoplasma bovis, was first detected in New Zealand in 2017. This led to a large-scale, successful control programme aimed at eradication of the pathogen. The decision to undertake an eradication programme was informed by initial analyses of whole genome sequences from isolates collected as part of the surveillance programme. The analysis showed that the bacteria had entered New Zealand relatively recently and was unlikely to be widespread. Over the subsequent years, genome sequencing and modelling of transmission dynamics informed important policy decisions made by the New Zealand Government and the cattle industry, and helped to monitor progress of the eradication programme. The impact of the detection, movement control and culling programme was profound, with sharp reductions in transmission between 2018 and 2020. This was followed by a long tail of localised infection in the South Island, involving transmission from a large feedlot farm. Provisional eradication was achieved after depopulation of this feedlot. This analysis highlights the role of genomic surveillance and modelling to inform decision making during an infectious disease outbreak.

IntroductionAntimicrobial Resistance (AMR) presents a critical public health challenge, particularly in smallholder broiler farming, where antibiotics are often used preventively in the absence of effective biosecurity measures. ObjectiveThis study investigates the adoption of biosecurity practices as a sustainable alternative to antibiotics through Participatory Systems Mapping and Experimental Games. MethodsA participatory mixed-methods study was conducted in southern Bangladesh (September 2024-June 2025). Causal Loop Diagrams (CLDs) were co-created with farmers, dealers, and veterinary officers. Ten broiler farmers from single village were selected via purposive and snowball sampling. Experimental games simulated four production cycles where farmers chose Option A (biosecurity, adopters) or Option B (antibiotics, non-adopters) after several interactive trainings. Key metrics including biosecurity compliance (0-12 scale), mortality, FCR, antibiotic use, outbreak history, and economic outcomes were recorded. ResultsCLD analysis revealed a reinforcing loop of increased antibiotic reliance driven by fear of mortality, and balancing loops involving training, biosecurity practices, and consumer incentives to reduce use. Five farmers chose Option A, and both groups remained stable until Round 4. Adopters had flock sizes of 800-2000 birds (non-adopters, 600-1000; mean for both = 1000), were younger, and more educated compared to non-adopters. At baseline, both groups had similar biosecurity scores (0). Adopters had higher mean outbreaks (2 vs. 1.4), mortality (5.6 vs. 4.2), antibiotic use (3.6 vs. 3), and FCR (1.8 vs. 1.6) compared to non-adopters. By Round 4, adopters improved biosecurity scores by 125%, eliminated outbreaks, reduced mortality by 52.6%, stopped antibiotic use, improved FCR by 13.3%, and gained 71.72% profit per bird compared to non-adopters. Non-adopters, influenced by adopters, increased biosecurity scores by 25%, reducing outbreaks, mortality, antibiotic use, and FCR. Adopters also increased direct sales to consumers, yielding a 10%-16% profit gain per bird each round. ConclusionThis study highlights the successful adoption of biosecurity practices by farmers, replacing antibiotics and improving production outcomes. Farmer-driven adoption of these practices fosters long-term sustainability and supports a healthier planet within the One Health framework.

This study aimed to investigate the dynamics of gene expression in pigs during heat stress (HS), focusing on both short-term (STHA) and long-term (LTHA) heat acclimation phases. A total of 12 castrated males were exposed to thermoneutral temperatures (24{degrees}C) for 14 days (TN) and then to a constant temperature of 30{degrees}C for 21 days. Rectal temperature measurements indicated a biphasic thermoregulatory response, with an initial peak followed by acclimation. Using whole blood transcriptome analysis at seven time points between day 5 before the initiation of HS challenge and day 13 post HS. A total of 525 genes were differentially expressed during the STHA (day 0-day 2) phase. A switch in the expression of most genes was observed around 20 hours after HS. Functional pathway enrichment analysis identified through shape-based clustering revealed the activation of the immune system, especially mediated through toll-like receptor signaling pathways. The LTHA phase (day 2-day 13) revealed 985 differentially expressed genes, with pathways associated with various metabolisms, including mitochondrial fatty acid beta-oxidation, and electron transport, ATP synthesis, and heat production by uncoupling proteins. Interestingly, oxidative phosphorylation was predicted to be activated during the LTHA, particularly in Complex V, whereas other complexes showed mixed regulation. Comparative pathway analysis indicated distinct metabolic adaptations between STHA and LTHA, with up-regulation of glucose and lipid metabolism in late STHA and down-regulation of lipid metabolism during LTHA. This study contributes to a better understanding of the time course of adaptation mechanisms in pigs to HS, underlying a coordinated regulation during STHA involving several stress-specific mechanisms (via the HSP) and metabolic variation to help pigs achieve homeothermy.

Environmental factors affect crop growth and development thus their consideration across sites and years become essential for genotypic evaluation. Genomic selection (GS) has been broadly implemented to accelerate breeding cycles by skipping field evaluations thus allowing early identification of outperforming genotypes. In this study, 7,740 phenotypic records corresponding to 516 Miscanthus sacchariflorus genotypes evaluated in five locations across three years were considered for analysis. Additionally, environmental data on six weather covariates was implemented to characterize similarities between locations. Different sets of locations of variable sizes were used for model calibration based on two cross-validations (CV00 and CV0) schemes leaving out one location at a time. Predictive ability across locations of the best model varied between 0.45 and 0.90 for both schemes. These results were compared to associate predictive ability in function of weather patterns between training and testing sets to allow models calibration optimization. We found it is feasible to optimize resource allocation by considering environmentally correlated sets. In most cases, the information from only one and, at most, two locations were enough to deliver better results than using all four locations, reducing training sets by up to 75%. The results obtained shed light on helping breeders make informed decisions considering weather data when designing evaluations.

ObjectivesCD4+ T cells play key roles in regulating immune responses during pregnancy, therefore we aimed to understand the CD4+ T cell surface proteome and transcriptome during pregnancy. MethodsCD4+ T cells were analysed in blood and decidua from term-pregnancies (>37 weeks), and non-pregnant blood. >350 surface proteins were screened via flow cytometry, and transcriptomes were analysed using single-cell RNA sequencing with >130 CITE-seq barcoded antibodies. ResultsSurface protein screening identified changes to ILT4/CD85d, CD9, IFN-{gamma} receptor {beta}-chain, CX3CR1 and CCR5 in the pregnant blood and decidual CD4+ T cells. CX3CR1 and CCR5 had the highest expression on the effector-memory T cell (TEM) subset in the blood, with expression consistent across subsets in decidua. CD126/IL-6R was lower in pregnant blood and decidual CD4+ T cells, while scRNAseq identified enrichment in the IL-6R signalling pathway in naive CD4+ T cells in pregnant blood. Both sIL-6R and IL-6 concentrations were increased in plasma during pregnancy, suggesting perturbations to the IL-6/IL-6R signalling axis. Meanwhile, decidual CD4+ T cells had increased expression of transcription factor RUNX3 in the CD69+ tissue-resident-like subset. ConclusionsOur findings demonstrate altered molecular expression in CD4+ T cells during pregnancy. This provides important mechanistic insight of their adaptation and regulation during placental development, which may drive placental dysfunction or pregnancy complications including preeclampsia, fetal growth restriction and stillbirth. These new data may inform future studies that focus on determining the significance of differentially- expressed immune features in pregnancy to identify potential targets for immune modulation to treat pregnancy complications and infections.

Phenotyping high-biomass perennial crops is laborious and the rate of genetic gain in perennial crop breeding programs is typically low. So, it is especially important to identify methods that produce efficiency gains in the breeding process. Miscanthus is a C4 perennial grass with favorable characteristics for producing biomass as a feedstock for biofuels and diverse biobased products. Increasing biomass yield will increase profitability and environmental benefits, so is a key target for Miscanthus breeding. In addition, the identification of well-adapted genotypes across a wide range of environmental conditions requires the establishment of multi-environment trials (METs). Sparse testing is a genomic prediction-based strategy that reduces the phenotyping costs in METs by selecting a subset of genotypes to evaluate in a subset of environments and then predicts the performance of the unobserved genotype-environment combinations. A Miscanthus sacchariflorus (MSA) population comprising 336 genotypes observed across three environments was analyzed. Three prediction models considering main effects (environments, genotypes, genomic) and interaction effects (genotype-by-environment; GxE interaction) were implemented for forecasting dry biomass yield (YDY), total culm (TCM), average internode length (AIL), and culm node number (CNN). Multiple calibration sets based on different compositions and sizes were considered to evaluate performance in terms of the predictive ability (PA) and the mean square error (MSE) for a fixed testing set size. The training set size ranged from 52 to 112 to predict a fixed set of 224 unobserved genotypes across all three environments. The results showed that the model accounting for GxE interaction presented the highest PA and the lowest MSE for CNN (PA: [~]0.77, MSE: [~]0.5) and YDY (PA: [~]0.70, MSE: [~]1.3) while for TCM and AIL these ranged from [~]0.28 to 0.41 and [~]1.3 to 4.3, respectively. Overall, varying training sets and allocation strategies did not affect PA and MSE, with 52 non-overlapping and 0 overlapping genotypes per environment as the optimal cost-effective allocation framework. This suggests that implementing sparse testing designs could significantly reduce phenotyping costs by fivefold, without compromising PA in breeding programs for perennial crops such as Miscanthus.

Assessing the risk of pesticides to birds requires models that can extrapolate laboratory data to realistic exposure scenarios. In this work, we propose a new modeling framework BIRDkiss (Bird - Impact on Reproduction via Diet, keep it simple and suitable) that accounts for both a simplified Dynamic Energy Budget (DEBkiss) of organisms and the toxicokinetic-toxicodynamic (TKTD) of chemical substances according to a trait-based approach, thereby reducing the number of parameters to identify and strengthening the statistical robustness of the critical endpoints. The BIRDkiss model describes how food intake and toxicant exposure affect growth and egg production in birds over time. The model is fully embedded within an R package, including routines for calibration, validation and prediction under single-compound scenarios performed via Bayesian inference using standard data from the OECD avian reproduction tests. The BIRDkiss model also allows the simulations of scenarios under both varying food availability and multi-compound exposures based on the two classical mixture-toxicity paradigms: Concentration Addition (CA) and Independent Action (IA). The results of calibration for single compounds show good results matching with observed weights and egg counts. From these calibrations, predictions for new exposure scenarios can be readily generated. For mixtures, the IA algorithm is simpler and does not require to scale variables as in CA. Simulations indicate that high food levels do not further increase egg production (saturation), whereas substantial food reductions markedly decrease reproduction because energy is reallocated to maintenance. Exposure to chemicals combined to low food availability amplify the decline in reproductive output. The ready-to-use mechanistic, open-source BIRDkiss tool enables predicting the impact of pesticides on avian reproduction under realistic dietary exposure profiles. The implementation of CA and IA models is a first step toward mechanistic assessment of chemical mixtures, although validation still requires empirical mixture data. The model highlights the importance of food availability and shows that chemical stress can exacerbate the negative effects of nutritional stress. Integrating such models into regulatory frameworks could improve the ecological relevance of risk assessments. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/712277v1_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@102246dorg.highwire.dtl.DTLVardef@1a58f65org.highwire.dtl.DTLVardef@695cd7org.highwire.dtl.DTLVardef@14e4329_HPS_FORMAT_FIGEXP M_FIG C_FIG

BackgroundRising global temperatures and eutrophication are increasing the intensity and frequency of cyanobacterial harmful algal blooms that release toxins including microcystin-LR (MC-LR). MC-LR inhibits protein phosphatases in the human liver and brain, but its accumulation in the placenta is unclear. Placental transporter expression varies across pregnancy and is influenced by physiological cues, such as low oxygen concentrations which activate HIF1A, and trophoblast cell fusion forming syncytiotrophoblasts that engage CREB-driven transcription. This study examined whether MC-LR accumulates in placental cells, which transporters mediate uptake, and how these transporters are regulated by HIF1A and CREB. MethodsIntracellular accumulation of MC-LR (0.1-10 {micro}M, 3 hour) was measured in human cytotrophoblasts (JAR, BeWo) and extravillous trophoblasts (HTR-8/SVneo) by western blotting for MC-LR-adducted proteins. Organic anion transporting polypeptide (OATP) involvement was tested using cyclosporin A (10 {micro}M), an OATP inhibitor, before exposure to the OATP substrate or MC-LR. Cells were also cultured under 3%, 8%, or 20% O2 to induce hypoxic responses or treated with forskolin (a potent intracellular cAMP inducer) to stimulate cell fusion before MC-LR exposure. ResultsMC-LR accumulated in all three placenta cell lines in a concentration-dependent manner. Cyclosporin A reduced MC-LR uptake by 57% in JAR cells, confirming OATP-mediated transport. Low O2 increased OATP4A1 expression and function but reduced protein phosphatase expression, decreasing MC-LR-bound proteins by 52-72%. Forskolin increased OATP4A1 expression and enhanced MC-LR uptake >2.5-fold. ConclusionMC-LR enters placental trophoblasts via active OATP transport, likely OATP4A1, and uptake increases under hypoxia and trophoblast fusion.

This study presents a multidisciplinary approach to evaluate the structure formation and digestion of lupin protein crosslinked with transglutaminase (TG). TG was applied at 0-10 U/g protein, and structural development was assessed by oscillatory rheology (G, G"), while SDS-PAGE and o-phthaldialdehyde (OPA) assays were used to evaluate protein participation and the reduction of free {varepsilon}-amino groups, respectively. Proteomics was further employed to characterise molecular features associated with crosslinking behaviour. Lupin protein showed a clear dose-dependent increase in gel strength during incubation, with G values reaching 214 {+/-} 43.9 Pa at 10 U/g TG, compared to 7.2 {+/-} 0.6 Pa in the untreated control. Across all conditions, G remained higher than G" throughout frequency sweeps, and low tan {delta} values confirmed the formation of elastic networks driven by covalent crosslinks. SDS-PAGE and OPA results consistently demonstrated efficient crosslink formation, which increased with both incubation time and TG dosage, with SDS-PAGE indicating involvement of specific protein fractions. Proteomic analysis revealed disordered structural domains in the protein are preferred regions to form crosslinks. Furthermore, TG treatment was found to slow the digestibility of the crosslinked lupin protein. Overall, this work demonstrates how integrating proteomic insights with functional measurements can guide the selection and optimisation of plant proteins for enzymatic structuring. The approach offers a rational pathway to enhance the functionality of alternative protein sources such as lupin, supporting the development of sustainable food systems, including applications in meat and dairy analogues.

Harbour porpoises (Phocoena phocoena) in the North and Baltic Seas are increasingly impacted by anthropogenic pressures, including underwater noise, fisheries and pollution. These pressures correlate with declining population health, particularly affecting the respiratory system. Growing pathological lesions, partly resulting from high prevalence of parasitic infestations and subsequent diseases, can impair tissue function and oxygen supply to distant end-organs. In this study, we applied an integrative MultiOmics approach (proteomics, metabolomics, lipidomics) to analyse the lungs and muscles of 12 wild harbour porpoises with compromised respiratory health. Our aim was to identify dysregulated biological pathways across omics layers to advance insights into adaptive physiological responses and to define disease-associated molecular signatures that could assist health assessments. Our analysis revealed pronounced immune system and antioxidative responses in the lungs and muscles, indicated by enhanced immunoglobulins, plasmalogens and glutathione-related proteins. In the lungs, high cardiolipin levels and reduced collagen suggest impaired tissue structure and function, while tissue maintenance processes were elevated in the muscle. Both tissues exhibited metabolic alterations suggestive of energetic imbalance, including increased purine metabolism in the lung and decreased lipid metabolism in the muscle. Several dysregulated molecules were shared across tissues, pointing to pathophysiological effects. The proposed disease-associated molecular signatures included the protein SLC25A4, the metabolite O-phosphoethanolamine and the lipid TG O-16:0_16:0_20:4 for the lung, and the protein SPEG, the metabolite pipecolic acid, and the lipid BMP 18:1_22:6 in the muscle. Our findings elucidate the complexity of molecular mechanisms linking anthropogenic and environmental stressors with vulnerability and resilience in a marine sentinel species. Furthermore, this study highlights the potential of integrative omics to define disease-related marker panels, thereby supporting ongoing and future health monitoring and conservation efforts.

Bats are exposed to a variety of pollutants, including cadmium (Cd), that can impair immune function and potentially increase viral shedding and burden. Despite this, little is known about the impacts of heavy metals on bats. This study aimed to determine the impacts of Cd exposure on bat T and B cell immune responses in naive and coronavirus infected bats and determine the impact of Cd on viral replication in Jamaican fruit bat (JFB; Artibeus jamaicensis) cells. To determine the impact of Cd exposure on adaptive immune responses, splenocyte cultures from naive and BANAL-52 coronavirus infected JFB were treated with 0, 1, and 10 {micro}M Cd and stimulated overnight with concanavalin A. RNA was extracted, a SYBR Green qPCR was used to assess gene expression. To determine if Cd exposure increased viral replication, two JFB kidney cell clones were treated with 0, 1, 10, and 50 {micro}M of CdCl2 overnight and then infected with Cedar virus (CedV). Supernatants were collected and viral titers determined. Several transcripts were upregulated in both naive and virus infected JFB splenocytes treated with Cd. B cell transcripts were significantly upregulated in a dose-dependent manner and T cell transcripts were also increased in Cd treated splenocytes. Assessment of transcripts associated with T cell subsets suggest a predominant Th2 response in Cd treated splenocytes. Viral replication was not significantly different in Cd treated kidney clones compared to the non-treated cells. These studies provide evidence that JFB adaptive immune responses are altered when exposed to low Cd concentrations.

BackgroundHumans and mice display elevated levels of IL-27, an immunosuppressive cytokine shown to increase during neonatal bacterial sepsis and compromise survival. This study explores two hypotheses for regulation of IL-27 expression: 1) decreased DNA methylation in newborns that contributes to increased expression of IL-27 genes; 2) neonatal hormones regulate IL-27 expression through upstream hormone response elements (HREs). MethodsWhole genome methyl-seq analysis of neonatal and adult blood-derived macrophages identified differentially methylated regions (DMRs) at steady-state. Quantitative PCR (qPCR) measured expression of IL-27 genes (IL27p28 and EBI3) in human and murine neonatal macrophages stimulated in vitro with synthetic glucocorticoid or progesterone. Confocal microscopy and chromatin immunoprecipitation (ChIP) of glucocorticoid receptor (GR) assessed translocation into the nucleus and binding to the EBI3 promoter. ResultsThe IL-27p28 promoter contained DMRs that were increased in the neonatal cohort. The analysis did not identify DMRs within the EBI3 promoter. Dexamethasone stimulation increased EBI3 gene expression in human and murine neonatal macrophages. GR localized to the nucleus in response to dexamethasone and was enriched at the EBI3 upstream regulatory region. ConclusionThese data suggest glucocorticoid (GC) signaling increases EBI3 expression. This has importance in the context of antenatal GC administration that may increase IL-27 levels. Impact Statement{blacksquare} Elevated expression of IL-27 in early life impairs the host response to invasive bacterial infection in neonates. {blacksquare}Understanding the regulatory mechanisms contributing to increased IL-27 during the neonatal period is necessary to reduce susceptibility to infection in this vulnerable population. {blacksquare}The methylation status of the IL-27 genes in macrophages from neonatal and adult blood donors does not suggest regulation of differential expression with age. {blacksquare}Glucocorticoids are a signal that can induce EBI3 gene expression in a GR-dependent manner. {blacksquare}Glucocorticoid therapy for premature infants may increase IL-27 expression and promote enhanced susceptibility to infection.

Genomic selection holds the potential to serve as a strategic tool to enhance the genetic gain of complex traits in Miscanthus breeding programs. The development of improved cultivars requires their assessment for various traits across diverse environments to ensure suitable overall performance. Hence, the multi-trait multi-environment (MTME) genomic prediction (GP) models offer an opportunity to improve selection accuracy. This study aims to evaluate the potential of five GP models: (1) three MTME models including genotype-by-trait-by-environment interaction (GxExT) and (2) two single-trait multi-environment (STME) models (with and without GxE interaction). A Miscanthus sacchariflorus population comprising 336 genotypes evaluated in three environments and scored for four traits (biomass yield YDY, total culm number TCM, average internode length AIL, and culm node number CNN) was analyzed. The predictive ability of the models was evaluated considering three cross-validation schemes resembling realistic scenarios (CV1: predicting new genotypes, CVP: predicting missing traits in a given environment, and CV2: predicting partially observed genotypes). On average, in all cross-validation schemes compared to the STME the predictive ability of the MTME models was 10% to 70% higher for TCM and AIL. On the other hand, for YDY and CNN, both STME models performed similarly or slightly better (between 5 to 64%) than the MTME models in most environments. While the MTME models were not successful for all traits when compared to their STME counterparts, MTME models improved the prediction of the performance of genotypes that were untested across environments or lacked trait information in a specific environment. Overall, our study suggests that MTME GP models can be implemented in Miscanthus breeding programs to improve the predictive ability of the complex traits, shorten breeding cycles, and accelerate selection decisions.