Biology subjects

Kulkarni, P.

Publications and source records attributed to Kulkarni, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Pick your battles: competitive strategies of green chromides (Etroplus suratensis) during inter- and intraspecific contests

Competitive ability is a key determinant of organismal fitness, yet high costs of interference competition necessitate strategic behavioural responses. This study investigated how green chromide (GC), a cichlid native to the Indian subcontinent, competes with the globally invasive tilapia species (T, Oreochromis spp.) that has encroached upon its habitats. We staged dyadic feeding competitions between GC and T, and analysed aggression, feeding, and hiding behaviours of both the species and further contrasted them with intraspecific contests in GC. We varied developmental stages, residency status of opponents, and used different combinations of body sizes of competitors to test their effects on the outcome of dyadic contests. We hypothesized that competitors would adjust their strategies based on the context of the competition, and thus, we aimed to identify the factors that contributed to such decision-making. Our findings showed residency as the primary driver of competitive strategy, wherein residents had higher aggression and feeding when compared to intruders. The developmental stage had a significant effect on feeding, increasing from young to older stages, but body size contrasts did not contribute significantly towards the outcome of the contests. For the species effect, T emerged as a winner in most of the interspecific contests, exhibiting a significant amount of total aggression. However, GC showed distinct behavioural strategies when competing against T versus conspecifics, and exhibited higher levels of aggression and reduced hiding during intra- when compared to interspecific trials. Surprisingly, the feeding behaviour of GC was not significantly impacted in the presence of T, possibly because GC used hiding as a defence strategy, emphasizing the context-dependent, strategic thinking of the species. Overall, the variety of behavioural tactics exhibited by GC in staged competitive interactions showcases robust survival skills of the species, a key trait that may help maintain its fitness in challenging ecological habitats.

animal behavior and cognition↗

bioRxiv2026

Acute lysergic acid diethylamide induces a time-dependent shift toward hippocampal control of default mode network reorganization

Background Classical psychedelics induce profound changes in brain function, yet the temporal organization of these effects remains incompletely understood. Methods We investigated the effects of acute lysergic acid diethylamide (LSD) on large-scale brain connectivity in nine male Long-Evans rats using resting-state functional magnetic resonance imaging. Following a 15-min baseline acquisition, rats received LSD (500 g/kg, i.p.), and imaging continued during two consecutive 15-min post-injection periods. Network reorganization was assessed using independent component analysis (ICA), seed-to-voxel mapping, stationary seed-to-seed connectivity, dynamic graph-based metrics, and dynamic causal modeling. Results LSD produced widespread but regionally heterogeneous changes across default mode network related, cortical, striatal, thalamic, sensory, and limbic systems. During the early post-injection window, ICA revealed a predominance of increased functional coupling, while dynamic analyses showed prominent fluctuations in hippocampal coupling strength and medial frontal network centrality. Dynamic causal modeling identified a false discovery rate-corrected reduction in retrosplenial-to-infralimbic influence, accompanied by a broader descriptive pattern of reduced posterior- and hippocampal-to-frontal coupling. During the later window, ICA showed a relative shift toward connectivity decreases, while complementary analyses revealed more selective hippocampal and parahippocampal involvement. Conclusions Across complementary analyses, acute LSD induced a temporally structured reorganization of brain hierarchy, characterized by an early weakening of directed cortical interactions followed by a later shift toward hippocampal-centered network control. These findings identify a dynamic shift in effective network organization and provide a mechanistic framework for psychedelic-induced default mode network reconfiguration.

neuroscience↗

bioRxiv2026

Regulatory stochasticity drives opposing phenotypic outcomes in cell-fate decision networks

Gene regulatory network models treat interaction parameters as fixed, although regulatory efficacy fluctuates. We asked how temporal fluctuations in interaction strength reshape phenotype occupancy in cell-fate decision GRN motifs. Across large parameter ensembles, anchored fluctuations largely preserved deterministic occupancies. Additive fluctuations increased occupancy of all-high co-expression states, particularly where high expression was accessible. In contrast, multiplicative fluctuations biased inhibitory interactions toward stronger repression and favored single-high states in a topology-dependent manner. Deterministic controls sampled from noise-induced parameter distributions did not fully reproduce these effects. A Boolean-limit analysis revealed an intrinsic upward bias: loss of repression increased expression regardless of regulator state, whereas stronger repression acted only when the regulator was present. Analyses of epithelial-mesenchymal plasticity and gonadal-fate networks showed increased occupancy of hybrid team-expression states under additive fluctuations. Thus, regulatory noise can reshape the developmental landscape in opposing directions, pushing cell-fate systems toward either progenitor-like or terminally differentiated states.

systems biology↗

bioRxiv2026

A Novel Syngeneic Mouse Model to Study Immune Evasion in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide, and patient outcomes have remained largely unchanged despite advances in multimodal therapy. Immune checkpoint inhibitors (ICIs), which block the PD-1/PD-L1 axis to restore T cell-mediated anti-tumor immunity, have emerged as a promising treatment strategy. However, response rates remain below 20% in HNSCC, underscoring the need to better understand mechanisms of immune evasion within the tumor microenvironment. Syngeneic mouse models are essential for studying tumor-immune interactions, yet currently available HNSCC models are limited. Here, we report the development of a novel FVB/NJ-derived syngeneic HNSCC model generated from 7,12-dimethylbenz(a)anthracene (DMBA)-induced primary on floor of mouth/buccal tumors, designated FMOC1, FMOC2, and FMOC3 (FVB/NJ Mouse Oral Cancer). In vitro, all FMOC cell lines exhibited robust proliferative capacity with distinct proliferation kinetics. In vivo, all FMOC cell lines exhibited characteristic HNSCC histopathology, including cytokeratin 5 positivity, and were tumorigenic in immunodeficient NCG mice; however, in syngeneic immunocompetent mice, only FMOC1 demonstrated sustained tumor growth at orthotopic and flank sites, whereas FMOC2 and FMOC3 tumors underwent spontaneous regression within 2 weeks, indicating differential immune-dependent tumorigenicity among the lines. Consistent with this, depletion of CD4+ and/or CD8+ T cells restored tumor growth in FMOC2 and FMOC3 models, indicating a critical role for T cell-mediated immunity in tumor suppression. Notably, FMOC1 tumors were responsive to anti-PD-L1 and anti-CTLA-4 therapy, supporting their utility for evaluating immunotherapeutic strategies. Collectively, these findings establish the FMOC model as a novel and versatile platform to study tumor-immune interactions and immune evasion mechanisms in HNSCC, with potential applications in preclinical immunotherapy development.

cancer biology↗

bioRxiv2026

Ecological Cascades and Future Hantavirus Spillover Risk in a Changing Climate

Anthropogenic climate change is reshuffling global biodiversity and accelerating zoonotic spillover at the human-wildlife interface. The 2026 multi-country cruise ship outbreak of Andes virus highlights the unpredictable and globalized threat posed by rodent-borne orthohantaviruses, which cause severe, highly fatal human diseases worldwide. Despite this significant public health risk, macroecological synthesis linking environmental drivers to systemic shifts in hantavirus hazards has been lacking. Here, we implement an integrated ecological and machine learning framework combining 89 unique virus-host associations across 61 reservoir species with mechanistic Force-of-Infection (FOI) modeling to project global spillover hazards under current and future climate scenarios (SSP2-4.5 and SSP5-8.5) for 2041-2060. Our models demonstrate a spatially uneven but geographically extensive expansion of spillover hazards, with approximately 74.9% of modeled land area experiencing an increase in FOI. We identify three distinct high-hazard belts heavily concentrated in already-temperate reservoir ranges: western and central North America, central and northeastern Europe extending into western Russia, and discrete patches within central South America. Crucially, our findings reveal that hantavirus hazards are fundamentally shaped along virus-specific ecological axes. While thermal and precipitation anomalies predominate the transmission dynamics of Old and New World lineages like Sin-Nombre virus and Thailand virus, distinct urban-centric Profiles emerge for Seoul virus and Mamore virus, driven explicitly by fine-scale anthropogenic landscape modifications. These results reveal that climate change will not simply intensify viral spillover uniformly but will fundamentally restructure it across varied climatic and human-dominated environments. Our maps provide a critical baseline for targeted global surveillance and highlight the urgent need to integrate spatial conservation planning with public health preparedness.

ecology↗

bioRxiv2026

Dissecting the sources of variation in neuronally differentiated iPSC lines through multi-omics analysis

Induced pluripotent stem cells (iPSCs) are widely used as patient-specific disease models, yet substantial unexplained variability in molecular and functional readouts limits their reliability. Here, we systematically investigated the sources of variation in iPSC-derived neurons for three rare genetic disorders: Myotonic Dystrophy Type 1, chromodomain-DNA-helicase-binding protein 2-related disorder and N-acetylneuraminic acid synthase deficiency. This was performed by profiling multi-omics layers: genomics, epigenomics, transcriptomics, proteomics, metabolomics and lipidomics. Our study found that clonal variability was comparable to inter-patient differences and that neuronal differentiation state and nutrient-driven metabolic activity emerged as dominant contributors to variability observed across omics layers. Clonal differences could partly be attributed to stochastic differences in DNA methylation established during reprogramming. By modeling and correcting the observed variation, we improved the detection of disease-associated molecular signatures. Our study provides guidelines for improved study design and data analysis to minimize variability, enabling robust biomarker discovery and reliable iPSC-based disease modeling.

cell biology↗

bioRxiv2026

Bidirectional coupling among EMT, AXL-RB1 signaling and lineage switch drives resistance to osimertinib and worse clinical outcomes in NSCLC

Acquired resistance to osimertinib remains a major barrier in EGFR-mutant lung adenocarcinoma (LUAD), and in many patients cannot be explained by secondary targetable mutations. This pattern highlights a central role for non-genetic plasticity programs, including epithelial-mesenchymal transition (EMT), drug tolerance, immune evasion, and lineage switch. Here, we used a systems-level framework to define how these processes are coordinated. We constructed a minimal gene regulatory network integrating core EMT regulators with AXL, RB1, PD-L1, and NF-{kappa}B, and analysed its emergent behaviour using dynamical simulations. The network resolved into two mutually inhibitory, self-reinforcing "teams": an epithelial/sensitive team centred on RB1, miR-200, miR-34, p53, and E-cadherin, and a mesenchymal/resistant team centred on ZEB1, SNAIL, AXL, PD-L1, and NF-{kappa}B. Simulations predicted a strong coupling between EMT and osimertinib resistance, which was validated across bulk transcriptomic datasets from NSCLC cell lines, EGFR-mutant patient cohorts, and perturbation experiments. Inducing EMT increased RB1-loss programs, whereas osimertinib exposure induced AXL and EMT programs, supporting bidirectional regulation and reinforcement. Single-cell and spatial transcriptomic analyses further showed that EMT, AXL, PD-L1 activity, and reduced RB1 signaling co-occur within tumors. Clinically, activation of individual axes such as EMT, RB1 loss, or PD-L1 upregulation was associated with worse outcomes, while combined activation produced markedly poorer survival than any single axis alone. Extending the network to incorporate lineage regulators further linked a partial LUAD-to-LUSC shift with EMT, RB1 loss, and resistance. Together, these findings identify a network topology that coordinates multiple plasticity programs driving osimertinib resistance and suggest that disrupting this cooperative architecture may offer a therapeutic strategy in EGFR-mutant LUAD.

cancer biology↗

bioRxiv2026

Spatial Decoding of Tertiary Lymphoid Structure Maturation in Non-Small Cell Lung Cancer Using Deep Neural Networks

Understanding the role of tertiary lymphoid structures (TLS) is crucial in non-small cell lung cancer (NSCLC), as they are associated with patient prognosis and treatment outcomes. Specific cellular ecosystems that originate anti-tumor activity or predict immunotherapy response remain poorly characterized. To this end, we developed a high-resolution, multimodal spatial atlas jointly profiling transcriptomics, proteomics, and histology to characterize TLS maturation in NSCLC alongside secondary lymph organs as a baseline. Using this atlas, we proposed a pathologist-in-the-loop framework that combines a variational graph autoencoder (VGAE) with diffusion pseudotime to refine human expert annotations and characterize TLS maturation. These spatial molecular representations were extended to H&E whole-slide images via a vision transformer-based foundation model. Next, we resolved cellular composition, spatial organization, and cell-cell interactions within these data and defined two divergent spatial ecosystems. Clinical evidence suggests that these ecosystems are associated with distinct patient outcomes: a mature germinal center niche with favorable prognoses, and a tumor-macrophage-fibroblast niche with unfavorable prognoses. In summary, our work decodes key components of TLS heterogeneity, identifies hallmark spatial patterns involved in NSCLC adaptive immunity, and provides a framework for translating spatial omics insights into clinical applications.

genomics↗

bioRxiv2025

Sex Differences in Plasma Levels of Endocannabinoids and Related Lipids Before and After acute and repeated mTBI: an exploratory study for plasma biomarkers for mTBI

Mild traumatic brain injury (mTBI) is common diagnosis across all age groups and while most symptoms resolve within a few weeks; between 10 and 25 percent of mTBI patients suffer long-term problems. Known as post-concussion syndrome (PCS), symptoms include headache, a range of cognitive deficits, and depression. Currently, there are no established treatments for PCS and no clear predictive biometrics to determine which patients are at increased risk. Previous studies have identified some protein-derived plasma biomarkers for mTBI, however, the effects of mTBI on lipid signaling molecules and metabolites in blood is largely unknown. Endogenous lipids (endolipids) such as the endocannabinoids (eCBs) and their congeners are lipid signaling molecules that are associated with promoting neuroprotective responses after head trauma in animal models. Here, we examine the plasma lipidome using a rat model of acute and repeated mTBI that we previously demonstrated had a sex dependent change in neuroinflammation wherein females showed a higher degree of neurodegeneration after repeated head-injury than males. Key results of this exploratory lipidomics screen here demonstrates that acute head injury drives significantly more changes in plasma endolipids in males (32%) than females (8%), whereas, on the second day of head injury, only 11% change in males but 15% in females. Some key endolipids were modified in both males are precursors for resolving molecules and this was lacking in females. Given that females with repeated mTBI in this model demonstrated aspects of PCS, this could be an important component in evaluating clinical cases. Endolipids in the screen were measurable in plasma using only 100{micro}L, a volume necessary to be able to perform multiple blood draws on these rodent subjects. This threshold provides evidence that the levels of these endolipids could be readily measured throughout a patients recovery. Therefore, this family of endolipids has the potential to provide data on the progression of the injury and could be another crucial aspect in predicting mTBI outcomes.

neuroscience↗

bioRxiv2025

Mitochondrial Dynamics Through the Lens of Nonlinear Chemical Oscillations: A Theoretical Exploration Inspired by the Belousov-Zhabotinsky Reaction

In biology, oscillations are observed across a wide spectrum of processes and systems. Oscillatory systems are typically leveraged to transmit information within cells. However, they can also serve to transmit information between organisms underscoring their fundamental role in regulating transitions, maintaining stability, and responding to environmental stimuli. In this study, we explore mitochondrial fission and fusion dynamics through the framework of the Belousov-Zhabotinsky (BZ) reaction, a hallmark of non-equilibrium system that exhibits periodic changes in reactant concentrations through autocatalysis and feedback regulation. We observed that mitochondrial changes followed an oscillatory dynamic where the fission, fusion and intermediary factors undergo oscillations. Also, by modelling comparison with publicly available datasets of diseased condition before and after therapy, we observed similarities, where under diseased condition there is increased concentration of the fission and fusion factors but upon treatment the concentration of the intermediary factors increase. Also, patient survival data analysis showed that increase in fission and fusion factors correlated with increased deaths but when there is increase in the intermediary factor concentration, we see better patient survival. These results highlight the possibility of targeting mitochondrial dynamics as a potential strategy for therapeutic development for diseases such as cancer where mitochondrial dynamics is dysregulated.

systems biology↗

bioRxiv2025

Downregulation of KRT proteins in the Neuroendocrine System of Amyotrophic Lateral Sclerosis with PT150 as a Multi-Target Neuroprotectant

Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by motor neuron degeneration. Although ALS biomarkers exist, they lack specificity and early-onset. ALS also has a 40% misdiagnosis rate. This paper proposes the use of a Graph Neural Network (GNN) to diagnose ALS, new ALS-specific biomarkers, and a therapeutic based on this group. Gene expression and proteomic datasets were sourced. A kNN data representation was used to train a GNN for disease diagnosis. Achieving 98% accuracy between ALS and control, and 85% between ALS patients and ALS mimics (the specific diseases within this class were not disclosed), outperforming existing approaches. Integrated Gradients then quantified each genes importance in the models decision. KRTAP3-1 and KRTAP9-8 were substantial in the models classification process due to involvement in cytoskeletal organization. In parallel, statistical proteomi analysis revealed the significance of KRT6A, KRT6B, and KRT4 due to involvement in cytoskeletal organization, tissue development, and cellular differentiation, all related to ALS. These keratin proteins were expressed in the pituitary gland, suggesting that their downregulation contributes to hormonal dysregulation in ALS. Once Glucocorticoid Receptor (GR) was found to be the reason for keratin downregulation, molecular docking identified PT150 as a therapeutic, binding with and inhibiting GR and Cyclooxygenase 2, also reducing neuroinflammation in ALS.

systems biology↗

bioRxiv2025

Dose-dependent changes in global brain activity and functional connectivity following exposure to psilocybin: a BOLD MRI study in awake rats.

Psilocybin is a hallucinogen with complex neurobiological and behavioral effects. This is the first study to use MRI to follow functional changes in brain activity in response to different doses of psilocybin in fully awake, drug naive rats. Female and male rats were given IP injections of vehicle or psilocybin in doses of 0.03 mg/kg, 0.3 mg/kg, and 3.0 mg/kg while fully awake during the imaging session. Changes in BOLD signal were recorded over a 20 min window. Data for resting state functional connectivity were collected approximately 35 min post injection All data were registered to rat 3D MRI atlas with 173 brain regions providing site-specific changes in global brain activity and changes in functional connectivity. Treatment with psilocybin resulted in a significant dose-dependent increase in positive BOLD signal. The areas most affected by the acute presentation of psilocybin were the somatosensory cortex, basal ganglia and thalamus. Females were significantly more sensitive to the 0.3 mg/kg dose of psilocybin than males. There was a significant dose-dependent global increase in functional connectivity, highlighted by hyperconnectivity to the cerebellum. Brain areas hypothesized to be involved in loss of sensory filtering and organization of sensory motor stimuli such as the claustrum and the cortico-basal ganglia-thalamic-cortical loop were all affected by psilocybin in a dose-dependent manner. Indeed, the general neuroanatomical circuitry associated with the psychedelic experience was affected but the direction of the BOLD signal and pattern of activity between neural networks was inconsistent with the human literature.

neuroscience↗

bioRxiv2025

Conformational dynamics and multi-modal interaction of Paxillin with the Focal Adhesion Targeting Domain

Paxillin (PXN) and focal adhesion kinase (FAK) are two major components of the focal adhesion complex, a multiprotein structure linking the intracellular cytoskeleton to the cell exterior. The interaction between the disordered N-terminal domain of PXN and the C-terminal targeting domain of FAK (FAT) is necessary and sufficient for localizing FAK to focal adhesions. Furthermore, PXN serves as a platform for recruiting other proteins that together control the dynamic changes needed for cell migration and survival. Here, we show that the PXN N-domain undergoes significant compaction upon FAT binding, forming a 48-kDa multi-modal complex with four major interconverting states. Although the complex is flexible, each state has unique sets of contacts involving disordered regions that are both highly represented in ensembles and conserved. PXN being a hub protein, the results provide a structural basis for understanding how shifts in the multi-state equilibrium (e.g. through ligand binding and phosphorylation) may rewire cellular networks leading to phenotypic changes. TeaserThe fuzzy complex between Paxillin and Focal adhesion targeting domain is resolved, with functional and translational implications.

biophysics↗

bioRxiv2024

Comprehensive multi-omics profiling of a healthy human cohort

Multi-omics approaches can offer powerful insights into personalized biomarker profiles relevant for disease diagnosis, prognosis, and therapeutics. However, separating meaningful biological variability from technical noise remains a major challenge. The EATRIS-Plus consortium analyzed blood samples from 127 healthy adults across six omics layers using twelve platforms, resulting in one of the most comprehensive multi-omics profiling datasets of healthy individuals available to date. We applied reproducible workflows to analyze and integrate these data, revealing several key findings. Sex significantly influenced all omics layers, emphasizing the importance of sex-balanced study designs. Age could be accurately predicted using epigenetic clocks, achieving high performance with our high-resolution enzymatic methylation sequencing data (R2 = 0.90), whereas candidate aging biomarkers were identified across all omics layers. The resulting dataset provides reference ranges in healthy individuals for abundance and variability of omics features, enabling robust power analyses, sample size estimations, and benchmarking of multi-omics integration methods. This resource can guide future biomarker discovery and personalized health research and was made FAIR-compliant and publicly available via the ClinData Portal (https://clindata.imtm.cz) and a Zenodo repository (https://doi.org/10.5281/zenodo.17514796).

bioinformatics↗

bioRxiv2024

DNA walk of specific fused oncogenes exhibit distinct fractal geometric characteristics in nucleotide patterns

Background/ObjectivesThe complex system of cancer has led to an emphasis on understanding the more general causal relationship within the disease. In this context, concepts of symmetry and symmetry-breaking in distinct biological cell features or components have been examined as an approach to cancer investigation. However, there can be possible limitations in directly interpreting the symmetry-based approach from a physical viewpoint due to the lack of understanding of physical laws governing symmetry in complex systems like cancer. MethodsFractal geometry and DNA walk representation were employed to investigate the geometric features i.e., self-similarity and heterogeneity in DNA nucleotide coding sequences of wild-type and mutated oncogenes, tumour-suppressor, and other unclassified genes. The mutation-facilitated self-similar and heterogenous features were quantified by the fractal dimension and lacunarity coefficient measures, respectively. Additionally, the geometrical orderedness and disorderedness in the analyzed sequences were interpreted from the combination of the fractal measures. ResultsThe findings showed distinct fractal geometric features in the case of fusion mutations. It also highlights the possible interpretation of the observed fractal features as geometric analogues concerning explicit observations corresponding to specific cancer types. In addition, the two-dimensional multi-fractal analysis highlighted the presence of a single exponent in the scaling of mutation-mediated gene sequence self-similarity/complexity and heterogeneity. ConclusionsThe approach identified mutation-induced geometric features in gene sequences, demonstrating the potential of DNA walks and fractal analysis in translational research regarding cancer. The findings suggest that investigating fractal parameters can capture unique geometric features in nucleotide sequences, contributing to the understanding of cancers molecular complexity.

bioinformatics↗

bioRxiv2024

Shifting human-rodent interfaces under climate change: modeling the distribution of the reservoir for Junin virus and associated drivers

BackgroundThe drylands vesper mouse (Calomys musculinus) is the principal host for Junin mammarenavirus (JUNV), which causes Argentine Hemorrhagic Fever (AHF) in humans. In our study, we aimed to assess the probable range of C. musculinus and to identify hotspots for potential disease transmission to humans under current and future climate change scenarios. Methodology/Principal FindingsWe used tree-based machine learning (ML) classification algorithms to generate and project C. musculinus habitat suitability under two climate change scenarios for the years 2050 and 2070 using bioclimatic and landscape related predictors. Evaluation of the models showed high accuracy, with AUCROC ranging from 86.81-89.84%. The analysis of the importance and influence of different variables indicated that the rodent prefers warm temperatures, moderate annual precipitation, low precipitation variability, and low pasture coverage. While a severe climate change scenario (Representative Concentration Pathway 8.5) suggests a reduction in suitable areas for JUNV reservoir and a decrease in hotspots for potential disease transmission, an intermediate scenario (Representative Concentration Pathway 4.5) displays expansion in areas for C. musculinus distribution alongside increased potential hotspot zones. Conclusions/SignificanceWhile acknowledging the complexity of ecological systems and the limitations of the species distribution models, our findings offer a framework for developing preventive measures and conducting ecological studies in regions prone to C. musculinus expansion and hotspots for potential disease transmission driven by climate change. Preventive interventions will need to be adapted to target C. musculinus changing spatial dynamics. Author SummaryClimate change might modify where animals live, including those that carry diseases than can spread to humans. This study focused on how climate change might affect the drylands vesper mouse (Calomys musculinus). This rodent carries the Junin virus, which causes Argentine Hemorrhagic Fever, a dangerous disease if left untreated. We used species distribution models to predict how this rodents range might change by 2050 and 2070 under an intermediate and severe climate change scenario. We found that a temperature rise of 1.1{degrees}C to 2.6{degrees}C (intermediate change scenario) could allow the rodent to move into new areas, potentially increasing disease transmission to humans. These new areas might have warm temperatures, moderate rainfall, and low grass cover, as we found that C. musculinus prefers those climate and landscape conditions. Knowing the rodents potential distribution and preferred habitat enables preparedness and monitoring for early warning systems. By establishing monitor systems and online platforms featuring species distribution models and predictions, we can facilitate communication and resource sharing among researchers, policymakers, healthcare professionals and the public. These tools will help protect public health as climate change continues to bring new challenges.

ecology↗

bioRxiv2024

PPTC7 antagonizes mitophagy by promoting BNIP3 and NIX degradation via SCFFBXL4

Mitophagy must be carefully regulated to ensure that cells maintain appropriate numbers of functional mitochondria. The SCFFBXL4 ubiquitin ligase complex suppresses mitophagy by controlling the degradation of BNIP3 and NIX mitophagy receptors, and FBXL4 mutations result in mitochondrial disease as a consequence of elevated mitophagy. Here, we reveal that the mitochondrial phosphatase PPTC7 is an essential cofactor for SCFFBXL4-mediated destruction of BNIP3 and NIX, suppressing both basal and induced mitophagy. Disruption of the phosphatase activity of PPTC7 is not required for BNIP3 and NIX turnover. Rather, a pool of PPTC7 on the mitochondrial outer membrane acts as an adaptor linking BNIP3 and NIX to FBXL4, facilitating the turnover of these mitophagy receptors. PPTC7 accumulates on the outer mitochondrial membrane in response to mitophagy induction or the absence of FBXL4, suggesting a homeostatic feedback mechanism that attenuates high levels of mitophagy. We mapped critical residues required for PPTC7-NIX/BNIP3 and PPTC7-FBXL4 interactions and their disruption interferes with both NIX/BNIP3 degradation and mitophagy suppression. Collectively, these findings delineate a complex regulatory mechanism that restricts NIX/BNIP3-induced mitophagy.

cell biology↗

bioRxiv2023

A Multi-omics Data Analysis Workflow Packaged as a FAIR Digital Object

BackgroundApplying good data management and FAIR data principles (Findable, Accessible, Interoperable, and Reusable) in research projects can help disentangle knowledge discovery, study result reproducibility, and data reuse in future studies. Based on the concepts of the original FAIR principles for research data, FAIR principles for research software were recently proposed. FAIR Digital Objects enable discovery and reuse of Research Objects, including computational workflows for both humans and machines. Practical examples can help promote the adoption of FAIR practices for computational workflows in the research community. We developed a multi-omics data analysis workflow implementing FAIR practices to share it as a FAIR Digital Object. FindingsWe conducted a case study investigating shared patterns between multi-omics data and childhood externalizing behavior. The analysis workflow was implemented as a modular pipeline in the workflow manager Nextflow, including containers with software dependencies. We adhered to software development practices like version control, documentation, and licensing. Finally, the workflow was described with rich semantic metadata, packaged as a Research Object Crate, and shared via WorkflowHub. ConclusionsAlong with the packaged multi-omics data analysis workflow, we share our experiences adopting various FAIR practices and creating a FAIR Digital Object. We hope our experiences can help other researchers who develop omics data analysis workflows to turn FAIR principles into practice. O_TEXTBOXKey PointsO_LIThe FAIR4RS principles provide guidelines to enhance the discovery and reuse of research software. C_LIO_LIFAIR Digital Objects support Findability, Accessibility, Interoperability, and Reusability by both humans and machines. C_LIO_LIWe here demonstrate the implementation multi-omics data analysis workflow and share it as a FAIR Digital Object. C_LI C_TEXTBOX

bioinformatics↗