Biology

Toxoplasma gondii is a widespread human pathogen that has multiple, clinically relevant stages in its complex life cycle, including fast-replicating tachyzoites and latent bradyzoites. Bradyzoite differentiation is triggered by stress responses that lead to changes in transcription, translation, and metabolism. Two aspects of this process are addressed in this report: first, whether proteins that play roles in bradyzoite differentiation are specific to T. gondii and other bradyzoite-forming parasites of the Sarcocystidae family, and second, whether new bradyzoite differentiation proteins can be identified in T. gondii. To answer these questions, a phylogenetic approach was used, comparing proteomes of select members of the Sarcocystidae family that form morphologically different bradyzoite cysts and members of the Eimeriidae family that do not form cysts. This approach resulted in 8 distinct clusters of T. gondii proteins that reflected different conservation patterns; for example, one cluster showed conservation among all organisms, while another showed conservation in bradyzoite cyst-forming organisms. Known T. gondii proteins involved in bradyzoite differentiation were found in all clusters, indicating that this process uses both highly conserved pathways as well as bradyzoite-specific pathways. Importantly, the cluster containing proteins that are conserved in bradyzoite-forming organisms contained several known regulators of bradyzoites, and will be a source for identifying novel T. gondii proteins that are involved in bradyzoite differentiation.

AO_SCPLOWBSTRACTC_SCPLOWImproving feed efficiency in pigs is essential for reducing production costs and environmental impacts. This study examines the influence of circadian feeding rhythms and genetic polymorphisms on feed efficiency variability using two pig lines divergently selected for Residual Feed Intake (RFI) over ten generations. Feeding behavior was monitored using automatic concentrate dispensers, recording 6,494,097 visits from 3,824 pigs to analyze meal frequency, duration, and diurnal patterns. LRFI pigs ate less frequently, with larger meals and longer durations, they exhibited two distinct feeding peaks: one around 8:00 AM and a higher one at 5:00 PM and they consumed more feed during the diurnal period and less at night. HRFI pigs showed a smoother, less rhythmic feeding behavior with increased nocturnal intake. The differences between the two RFI lines became more pronounced as the number of generations of selection increased, suggesting a genetic basis. Feeding behaviors, including intake during the two main diurnal peaks, were found to be heritable (heritability estimates: 0.30-0.40) and genetic correlations were observed between feed intake and RFI, especially for intake between the two peaks. Then, we investigated the evolution of allele frequencies of single nucleotide polymorphisms (SNPs) in DNA sequences surrounding 10 core clock genes (ARNTL, CLOCK, CRY1, CRY2, NPAS2, NR1D1, PER1, PER2, PER3, RORA) along generations of selection. SNPs with significant frequency changes were mapped to regulatory regions and transposable elements, especially in HRFI line, suggesting potential functional impacts on circadian regulation. These results underscore the role of feeding behavior and genetic variation in feed efficiency, offering insights for breeding programs aimed at improving metabolic efficiency and sustainability in pig production.

The replicability of experimental results is considered a cornerstone of empirical research. However, the reproducibility of results from groups that have not undergone experimental manipulation -- the standard against which comparisons in an experiment are made -- has been almost entirely neglected in animal research. Our aim is to address this gap by exemplarily determining within-laboratory replicability using research in pigs, an increasingly popular large animal model species. Drawing on data from twelve independent porcine holeboard studies conducted in our laboratory, we examine the replicability of groups that were not subjected to experimental manipulation (typically the control group), eventually including groups on which the experimental treatments had no effect. These analyses were also performed on all eight studies involving the Terra x Finnish Landrace x Duroc pig breed, with all other breeds excluded to increase genetic uniformity. The holeboard is a complex spatial discrimination task in which an animal must learn to find food at four of sixteen possible locations (holes) arranged in a 4 x 4 matrix. The main variables measured are spatial working memory (WM), reference memory (RM) and the inter-visit interval (IVI), which serves as an index of motivation. All studies showed predominantly linear improvements in WM and learning rates across successive trial blocks. IVI showed greater variation across trialblocks, but this did not affect WM and RM learning, which are robust and replicable indices of spatial learning in pigs. Assessing replicability provides relevant information, such as whether behavioural and physiological traits in a model species are stably expressed and robust across studies. Including replicability research and publishing its results can stimulate the development and use of more replicable methods and workflows, thereby increasing scientific rigour. Provided the data are available and accessible, the next step should be to expand replicability studies to include those conducted in different laboratories.

Understanding the dynamics of HIV epidemics is important to control them effectively. Classical methods that mainly rely on occurrence data are limited by the fact that an unknown part of the epidemic eludes sampling. Since the early 2000s, phylodynamic methods have enabled the estimation of key epidemiological parameters from virus genetic sequence data. These methods have the advantage of being less sensitive to partial sampling and to provide insights about epidemic history that even predates the first samples. In this study, we analysed 2,205 HIV sequences from the French ANRS PRIMO C06 cohort. We identified and were able to reconstruct the temporal dynamics of two large clades that represent the HIV-1 epidemics in the country. Using Bayesian phylodynamic inference models, we found that the first clade, from subtype B, originated in the end of 1970s, grew rapidly during the 80s before decreasing from 2000 to 2015 and stagnating since then. The second clade, from circulating recombinant form CRF02_AG, emerged and spread in the 80s, grew again in the early 2000s, before declining slightly. We also estimated key epidemiological parameters associated with each clade. Finally, using numerical simulations, we investigated prospective scenarios and assessed the possibility to meet the 2030 UNAIDS targets. This is one of the rare studies to analyse the HIV epidemic in France using molecular epidemiology methods. It highlights the value of routine HIV sequence data for studying past epidemic trends or designing public health policies.

Dog (Canis lupus familiaris) vocal communication occurs across a wide range of social contexts, including dog-human social play, a common and dynamic interaction in which diverse vocal signals are expressed, particularly in young dogs. However, most available open datasets of dog vocalizations focus primarily on barks, leaving other sound types underrepresented. Here we present a bioacoustic dataset of dog-human social play sessions recorded under standardized laboratory conditions, comprising 30 play sessions involving 17 young dogs (6-24 months old) of different breeds playing with familiar humans. Raw audio recordings are accompanied by two layers of annotations covering the dog sounds produced during sessions. Video recordings of the sessions are provided for contextual reference, along with metadata describing each dog and the experimental sessions. Additionally, permutation-based classification analysis showed that annotated sound categories exhibit above-chance and generalizable acoustic differences across individuals. The dataset may support research on dog vocal communication and expand the range of sounds documented during positive dog-human social interactions.

In our society, ageing, longevity, and neurodegenerative diseases are major concerns of public health. Recently, in Drosophila, we have identified a new cluster of three snoRNAs, including jouvence, and showed that each of them affect longevity and neurodegeneration. As these snoRNAs are required in the epithelium of the gut, these results point-out a causal relationship between the epithelium of the gut and the neurodegenerative lesions through the metabolic parameters, indicating a gut-brain axis. Here, we demonstrate that each snoRNA pseudouridylates a specific site on ribosomal-RNA, which consequently affects the amount of ribosomes as well as the translational efficacy. Moreover, using TRAP experiment assay, we also show that these lacks of pseudouridylations modify the translation of specific genes involved in lipid metabolism. Consequently, these lead to a chronic deregulation of trigycerides and sterols levels, whose correlate to an increase of neurogenerative lesions in old flies, as well as to a modification of longevity.

African swine fever virus (ASFV) causes a lethal haemorrhagic fever in pigs and spread of this disease threatens many pig species (Suidae) globally. By contrast, ASFV infections in the natural evolved hosts, the warthog and bushpig, are subclinical. The macrophage (M{varphi}) is the primary target of ASFV and species-dependent responses in M{varphi}s are presumed to influence disease susceptibility. In an attempt to model these differences in vitro, we generated transgene-regulated induced pluripotent stem cells (iPSCs) from domestic pig, wild boar, red river hog and warthog, and confirmed that their corresponding iPSC-derived M{varphi}s (iPSCdMs) supported infection and replication of ASFV. In contrast to the other species, however, warthog iPSCdMs did not induce interferon upon infection by either virulent or attenuated ASFV. iPSCdMs may therefore represent an experimental system to understand how ASFV infection of M{varphi}s contributes to disease and aid development of strategies to combat this economically and environmentally devastating pathogen.

Elongases are essential enzymes in the biosynthesis of sex pheromones in many lepidopteran species. Together with desaturases, they determine the carbon skeletons of many pheromone precursors, thereby contributing to the production of species-specific chemical signals. However, to date, such fatty acyl elongase gene has not been functionally characterized. The rice leaffolder, Cnaphalocrocis medinalis, utilizes a blend of C18 monounsaturated aldehydes and alcohols as its sex pheromone, implying a critical elongation step from C16 precursors. In this study, we performed pheromone gland transcriptome analysis and identified 45 candidate biosynthetic genes. Functional assays in Nicotiana benthamiana showed that the {Delta}11 desaturase Cmed070400 produces (Z)-11-hexadecenoic acid, which serves as the substrate for elongation. Multiple elongases catalyzed its conversion to (Z)-13-octadecenoic acid, with Cmed092440 showing the highest activity. These findings provide the first experimental evidence for elongase-mediated formation of C18 pheromone precursors in C. medinalis. The identification of a minimal set of functionally active enzymes further enables reconstruction of this pathway in plant systems, offering a basis for sustainable production of pheromone precursors for pest management applications.

BackgroundIn computational biology, embedding known physical laws into deep learning models to construct "Physics-Informed Neural Networks" (PINNs) is a mainstream paradigm for enhancing model interpretability and extrapolation capability. However, in complex multi-physics coupling problems, there is a risk of competitive imbalance between the physical term and the flexible artificial intelligence (AI) residual term, causing the model to degenerate into a "black-box" fit and lose the original purpose of being physics-driven. MethodsIn this study, targeting the problem of predicting protein liquid-liquid phase separation (LLPS) behavior in response to environmental factors (temperature, salt concentration), we identified physical distortions, gradient vanishing, and numerical instability in the initial physics-AI hybrid model. Three core correction strategies were proposed: (1) Weight Allocation Logic Reconstruction: Force the physical trunk weight to 1.0 at the output layer, suppressing the AI residual term to the perturbation level of 0.05~0.1, ensuring physics dominance; (2) Robust Physics Formula Construction: Abandon the unstable power function and introduce a combination of Softplus and logarithmic functions to stably simulate the nonlinear effects of charge shielding; (3) Gain Compensation Alignment: Apply gain compensation to the weak signal branch (temperature) to ensure its effective participation in optimization. ResultsThe optimized model maintained a fitting accuracy of R2{approx}0.62 on the test set, while physical consistency was significantly enhanced. The model successfully restored the monotonic increase in solubility with temperature characteristic of UCST-type phase diagrams and correctly captured the nonlinear charge shielding features in the salt concentration response. The weights of key physical parameters (e.g., hydrophobic contribution w_h, net charge contribution w_ncpr) increased from <10-3 to the 10-2 magnitude, demonstrating the reactivation of the physical branch. ConclusionsThe weight control, formula stabilization, and signal gain alignment strategies proposed in this study effectively address the classic problem of "AI hijacking" physics in physics-AI hybrid models. This work provides a universal solution for constructing biophysical predictive models that combine high fitting accuracy with strong physical interpretability.

In this study, resource-constrained learning methods were developed as a model for the learning behavior of the fly brain, specifically the mushroom body. Recent research on the mushroom bodies of flies shows that unfamiliar odors activate certain output neurons (MBONs); however, these effects are rapidly suppressed upon repeated exposure to the same odor. Such MBON behaviors appear to reflect odor learning. We investigated how flies continue learning about odors throughout their lives despite their small brains. Researchers have suggested that learning about new odors can help flies forget existing memories. Therefore, we hypothesized that the main reason for continual learning is that it serves as a strategy for forgetting. To test the validity of this hypothesis, we designed three models using a kernel perceptron. This approach is suitable for estimating ongoing learning capacity within a budget. According to the results of computer simulations and theoretical analysis, the model demonstrated the importance of forgetting mechanisms for two reasons: first, to prepare for subsequent learning sessions, and second, to reduce the negative effects of deleting memories.

High level of protein expression is usually welcomed in industry and research, and codon optimization is widely used to achieve high expression. Methods of implementing codon optimization can be divided into two branches, one is classical methods which develop cost functions based on empirical law, another is AI methods which learn the codon choice principles from endogenous genes with neural networks. Here we develop two codon optimization tools based on two branches respectively, namely OptimWiz 2.1 and OptimWiz 3.0. Results of fusion protein fluorescence detection indicate that both OptimWiz 2.1 and OptimWiz 3.0 are superior to all the other commercially available codon optimization tools. Principles of codon optimization are revealed in the process of machine learning on both tools.

Objective: To investigate in the National School Feeding Program (PNAE) the local level drivers and barriers to the implementation of four guidelines: the banning of sugary drinks; restrictions on the procurement of processed and ultra-processed foods; the mandatory increase in weekly servings of fruits and vegetables offered to students; and mandatory direct procurement from family farmers. Design: Qualitative study that used semi-structured interviews. Street level bureaucracy theory informed the theoretical framework and thematic analysis. Setting: Brazilian municipalities, across the country five geographic regions (North, Northeast, Southeast, South, and Midwest). Participants: Stakeholders (e.g. nutritionists, school cooks, and food procurement managers) involved in the local implementation of the PNAE program across the country. Results: Ninety stakeholders were interviewed. Stakeholders reported having autonomy to perform their activities, collaboration and support from other members within the local government and food providers, adequate infrastructure such as a well-equipped kitchens, the availability of trained personnel, and political commitment as drivers for optimum program implementation. Reported barriers included lack of support and resistance to change among cooks, teachers and parents; insufficient physical and human resources; and limited political commitment. When barriers outweighed drivers, interviewees reported adapting their practices, often in restrictive ways that could compromise the implementation of the program. Conclusions: Drivers and barriers to local PNAE implementation were generally similar across studied municipalities, although their magnitude varied. In contexts of greater economic vulnerability and fiscal constraint, additional support and targeted actions from the federal government may be required to strengthen local implementation

Background: Elevated lipoprotein(a) [Lp(a)] is a known risk factor for several cardiovascular-related diseases established from multiple genetic and observational studies. However, the underlying mechanisms mediating the effects of Lp(a) levels on cardiovascular disease risk and major adverse cardiovascular events (MACE) are unclear. The aim of this study was to identify proteins downstream of Lp(a) using mendelian randomization (MR) - a genetic causal inference approach. Methods: A two-sample MR was performed by initially identifying Lp(a) genetic instruments based on data from genome wide association studies (GWAS) of Lp(a) blood concentrations. These instruments were then tested for association with proteins from proteomic pQTL data (Olink from UK Biobank, 2940 proteins and SomaScan from deCODE, 4907 proteins). Results: A total of 521 proteins associated with Lp(a) were identified. Using pathway enrichment analysis, the following MACE-relevant pathways were identified comprising a total of 91 Lp(a) downstream proteins: oxidized phospholipid-related, chemotaxis of immune cells and endothelial cell activation, pro-inflammatory monocyte activation, neutrophil activity, coagulation, and lipid metabolism. Conclusion: The results suggest that the influence of Lp(a) treatments is primarily through modifying inflammation rather than lipid-lowering, thus providing insight into the mechanistic framework which mediates the effects of elevated Lp(a) on atherosclerotic cardiovascular disease.

It is well established that the microbiome can have major effects on animal biology. Here we have investigated the composition of the bacterial and eukaryotic gut microbiome of wild mice from three sample sites and sought to understand what affects its composition. We find that the bacterial and eukaryotic microbiome differs among mice from different sites. Among mouse traits, we found that only gut inflammation and the concentration of faecal immunoglobulin A affected the microbiome diversity. However, the microbiome diversity was more commonly affected by the microbiome composition itself, both within-bacterial and within-eukaryotic, but also by cross bacterial-eukaryotic effects. We found that most hosts produce IgA that binds some of their gut bacteria, though mice are largely idiosyncratic in which taxa they bind with IgA, with a few taxa commonly IgA-bound. The eukaryotic microbiome was dominated by fungal taxa, and included Eimeria infection that was particularly common at one of the sites. At the high Eimeria prevalence site, mice had comparatively marked caecal inflammation and significantly greater IgA responses. Our results emphasise the substantial among-individual mouse differences in gut microbiome composition, gut physiology and immunology, and the biological significance of the bacterial-eukaryotic effects that we suggest requires further study.

Understanding cellular responses to perturbations is a central objective in biology and biomedicine, yet rigorously evaluating predictions from high-dimensional transcriptomic models remains an open challenge. Here, we propose the SBB principles (Signal, Bounds, and Baselines) for evaluating biological perturbation prediction. The Signal pillar introduces diagnostic meta-metrics and promotes differentially expressed gene (DEG)-based weighting or filtering to verify and recover metric sensitivity to biological signal masked by high-dimensional noise. The Bounds pillar provides perturbation-wise metric calibration against empirical reference points, transforming raw metric values into interpretable quantities that clarify the actual scale of model improvements. The Baselines pillar establishes a hierarchy of interpretable linear models that serve as rigorous performance floors. Applying these principles across seven transcriptomic perturbation datasets, including single and double perturbations, we demonstrate that complex deep learning methods, including foundation models, often still fail to meaningfully surpass simple linear baselines, and that substantial room for improvement remains even where they do. These principles provide a critical standard for distinguishing genuine biological signal from statistical artifacts and for guiding more robust model development.

Arthropod-borne pathogens, many of which are neurotropic, can disseminate beyond the central nervous system to infect peripheral organs. In recent years, an increasing number of cardiac dysfunctions have been reported following arthropod-borne viral infections; however, the mechanism underlying these cardiac manifestations remains poorly understood. In this study, we investigated the impact of Venezuelan Equine Encephalitis Virus (VEEV) TC-83 infection on cardiac function and immune-response of human induced-pluripotent stem cell (hIPSC)-derived cardiomyocytes (hIPSC-CMs). We first confirmed the successful differentiation of hIPSCs into spontaneously beating hIPSC-CMs. We then demonstrated that these cells are highly susceptible to VEEV TC-83 infection, which induced pronounced arrhythmias and complete cessation of beating within 24 hours post-infection. To quantify these functional changes, we developed a segmentation-free computational pipeline that converts frame-to-frame motion in brightfield time-lapse movies into a one-dimensional signal reflecting contractile activity and extracts beat timing, beat rate, and rhythm-regularity features in the time and frequency domains. This analysis revealed progressive disruption of beating dynamics following VEEV TC-83 infection, with early rhythm instability and complete loss of coordinated beating by 24 hours post-infection. Furthermore, mass spectrometry analysis of VEEV TC-83-infected hIPSC-CMs supernatants revealed the presence of biomarkers typically associated with heart failure in patients, underscoring a virus-induced cardiac functional impairment. Together, these findings provide new insight into cardiac complications associated with arthropod-borne viral infections and may support advances in preventive medicine.

Introduction: Hypertrophic Cardiomyopathy (HCM) is a disease defined by the development of left ventricle hypertrophy. One of the most commonly mutated genes in HCM is cardiac myosin binding protein C (MYBPC3). MYBPC3 protein localizes to the cardiomyocyte sarcomere, but studies have reported detection of both MYBPC3 RNA and protein in non-cardiomyocyte cell populations. Therefore, it was unclear if MYBPC3 expression in non-cardiomyocyte cell populations altered the development of cardiomyopathy caused by MYBPC3 protein deficiency. Methods: We utilized genetically modified murine models with germline deletion of Mybpc3 exons 3 to 5 (Mybpc3-/-) or cardiomyocyte specific deletion of Mybpc3 exons 3 to 5 (Mybpc3fl/fl ; Myh6-Cre). Gene expression was assessed using quantitative RT-PCR. Whole tissue protein levels were assessed using immunoblots. Immunohistochemistry and proximity ligation assays were performed to evaluate in situ protein expression. Echocardiography was utilized to measure left ventricular structure and function. Results: Mybpc3 mRNA was detected in multiple organs including the heart, lung and blood from both humans and mice. Utilizing transgenic murine models with germline or cardiomyocyte specific deletion of Mybpc3 exons 3-5, we discovered that the Mybpc3 mRNA detected in extracardiac locations originated primarily from cardiomyocytes. Likewise, MYBPC3 protein was identified in myocardial tissue but not in other organs and cardiomyocytes were the only cell population in myocardial tissue that had detectable MYBPC3 protein. Importantly, cardiomyocyte deletion of Mybpc3 caused similar pathological myocardial remodeling and alterations in left ventricular function compared to germline deletion of Mybpc3 in all cell populations. Conclusions: Our results show that cardiomyocytes are the primary cell source of Mybpc3 mRNA detected in extracardiac organs and they are the principal cell type responsible for the cardiomyopathy caused by MYBPC3 protein deficiency. These results suggest that selective targeting of cardiomyocytes should be the most efficient approach to treat cardiomyopathies associated with MYBPC3 deficiency.

Non-invasive glucose monitoring (NIGM) has been pursued for decades, yet no device has achieved regulatory approval despite numerous studies reporting high accuracy. This systematic review and meta-analysis of 32 studies (38 cohorts: 20 NIGM, 18 iCGM; N = 1,693) investigated methodological factors underlying this accuracy-regulatory gap. The pooled Mean Absolute Relative Difference (MARD) for NIGM (10.21%; 95% CI: 8.73-11.69%) showed no significant difference from iCGM (11.82%; 95% CI: 10.36-13.29%; p = 0.13), with extreme heterogeneity (I^2 = 95.2%). Meta-regression revealed that study duration was the strongest predictor of NIGM accuracy ({beta} = 3.94, p < 0.001), with MARD degrading from 8.7% in short-term to 15.2% in long-term studies, while iCGM accuracy remained stable. Only 15% of NIGM cohorts validated in the hypoglycemia range, compared to 89% of iCGM studies (p < 0.001). These findings suggest that reported NIGM accuracy is substantially influenced by methodological asymmetries.

Stable isotope analysis provides an important tool for reconstructing past livestock management practices and landscape use. However, isotopic data for sheep from Late Iron Age (AD 375/400-1050) Denmark remain limited. Here, we present bulk bone collagen {delta}{superscript 1}3C, {delta}{superscript 1}N, and {delta}3S isotope analyses of 27 sheep (Ovis aries) from six archaeological sites in Denmark, dated to the Germanic Iron Age (AD 375/400-750) and Viking Age (AD 750-1050). The analysed sheep exhibit a consistent pattern of enriched {delta}13C values relative to previously published isotopic datasets for Scandinavian livestock, while {delta}15N values display substantial inter-individual variability. Sulfur isotope values fall within moderate ranges consistent with mixed terrestrial and coastal environmental influences. The decoupling of {delta}13C enrichment from elevated {delta}15N values suggests that the observed carbon isotope signal does not reflect marine protein consumption but rather the incorporation of a 13C-enriched plant resource into sheep diets. We propose that eelgrass (Zostera sp.), either through direct grazing in coastal environments or supplementary foddering with harvested eelgrass, represents a plausible dietary source to explain this isotopic pattern. The results indicate that Late Iron Age sheep management strategies in Denmark incorporated coastal plant resources within flexible pastoral systems, potentially supporting intensified wool production associated with expanding textile economies. HighlightsO_LIStable isotope values of Late Iron Age sheep show some dietary marine input. C_LIO_LIEnriched {delta}13C values suggest eelgrass as supplementary fodder. C_LIO_LI{delta}34S values indicate adaptive grazing across coastal and inland landscapes. C_LI

Background: Few studies have examined racioethnic disparities in cardiovascular disease (CVD) in women after breast cancer treatment, who are at higher risk due to cardiotoxic cancer treatment. Methods: Based on the Pathways Heart Study of women with a history of breast cancer, this analysis examines the association between cardiometabolic risk factors (hypertension, diabetes, and dyslipidemia) and CVD events with self-reported race and ethnicity, as well as genetic similarity. Multivariable logistic and Cox proportional hazards regression models were used to test race and ethnicity and genetic similarity with prevalent and incident cardiometabolic risk factors and CVD events. Results: Of the 4,071 patients in this analysis, non-Hispanic Black (NHB), Asian, and Hispanic women were more likely to have prevalent and incident diabetes than non-Hispanic White (NHW) women. Analysis of genetic similarity revealed results consistent with self-reported race and ethnicity. For CVD risk, NHB women were more likely to develop heart failure and cardiomyopathy than NHW women. In contrast, Hispanic women were at lower risk of any incident CVD, serious CVD, arrhythmia, heart failure or cardiomyopathy, and ischemic heart disease, which was consistent with the associations found with Native American ancestry. Conclusions: This is the largest multi-ethnic study of disparities in CVD health in breast cancer survivors, demonstrating corroborating findings between self-reported race and ethnicity and genetic similarity. The results highlight disparities in cardiometabolic risk factors and CVD among breast cancer survivors that warrant more research and clinical attention in these distinct, high-risk populations.