Biology-Basel最新文献

Precise drug target discovery is pivotal to mitigating the escalating costs and high attrition rates that characterize pharmaceutical research and development. Given that traditional single-omics methods often fail to elucidate the systemic complexity of human diseases, deep learning (DL)-enabled multi-omics integration has emerged as a transformative frontier. This review systematically summarizes the advancements in DL-driven multi-omics integration for drug target discovery. First, the multi-omics data foundation and integration strategies are delineated, followed by an exploration of the DL architectures utilized for processing such data. Subsequently, the efficacy of DL-driven multi-omics integration is examined regarding the identification of novel disease drivers, prediction of synthetic lethality interactions, and prioritization of therapeutic targets. Finally, addressing persistent challenges related to data sparsity, model interpretability, and target druggability and validation hurdles, emerging opportunities driven by Generative AI, Large Multimodal Models (LMMs), Explainable AI (XAI), and multidimensional feasibility assessment frameworks are discussed in the context of advancing precision medicine.

This study focused on optimizing endoglucanase production using a peculiar fungal co-culture comprising Rhizopus arrhizus and Aspergillus fumigatus, identified through morphological and 18S rDNA analyses. The co-culture achieved the highest enzyme production after 72 h of fermentation with alkaline-treated substrates. Scanning Electron Microscopy (SEM) revealed substantial structural disruption in pretreated biomass, enhancing enzyme accessibility. Among the tested substrates, pea hulls proved to be the most effective for enzyme production. Optimization of physical and nutritional parameters was performed using Design of Experiments (DOE) approaches, specifically Plackett-Burman Design (PBD) for screening and Central Composite Design (CCD) for fine optimization. The maximum endoglucanase activity of 119.58 U/mL/min was obtained under the optimized conditions of 27.5 °C, pH 5.5, inoculum age 3.5 days, and supplementation with 1.5% fructose, 1.25% yeast extract, 1.25% sodium nitrate, and 1.25% Tween 80. Analysis of Variance (ANOVA) confirmed the significance of these parameters and their interactions at a 95% confidence level, with a strong model fit (R² = 0.9052). This study demonstrates the potential of waste pea hulls as a cost-effective substrate for enzyme production, supporting waste valorization and contributing to a circular bioeconomy through sustainable biomass utilization.

In addition to binding to and regulating over 400 different proteins, calmodulin (CaM) also binds to lipids. Binding occurs to the prenylated tails of various small GTPases, to specific lipids in biological membranes and to free lipids in the cytoplasm. Here, CaM binding to Rac1, RalA, and KRAS4b is covered, emphasizing its importance in protein translocation from the cell membrane to the cytosol and its resultant impact on cell signaling. Binding phosphatidylserine and phosphatidylethanolamine in membranes not only leads to the tethering of CaM, but also to the disruption of lipid bilayers. Binding to sphingolipids also occurs, an event that acts as a competitive inhibitor of CaM function. The mechanism through which CaM binds to lipids is also examined. In total, the current state of affairs regarding calcium-dependent CaM-lipid binding is reviewed, including potential therapeutic uses, setting the stage for future work on this important biological event.

Among various ethanologenic microorganisms, thermotolerant Zymomonas mobilis has emerged as a promising candidate for industrial ethanol production at elevated temperatures. However, the comparative fermentation efficiency and the underlying molecular mechanisms driving thermotolerance in newly developed strains remain largely unexplored, hindering their industrial application. In this study, the recently developed thermotolerant strains Z. mobilis 200M and Z. mobilis PYK exhibited critical high temperatures for growth approximately 2.0 and 2.5 °C higher than the wild-type, respectively. While 40 °C represents severe heat stress that completely inhibits the growth of the wild-type, the thermotolerant strains remained viable, exhibiting significantly shorter cell lengths under these conditions. This study provides the first evidence of their superior multi-stress tolerance toward heat, ethanol, acetic acid, formic acid, and H₂O₂. Furthermore, the thermotolerant strains exhibited significantly higher ethanol fermentation efficiencies than the wild-type. At 40 °C, Z. mobilis 200M produced approximately 5.8-fold and 3.0-fold more ethanol than the wild-type after 24 and 48 h, respectively, while Z. mobilis PYK yielded 6.4-fold and 3.1-fold increases. Novel transcriptional insights via RT-qPCR revealed the simultaneous overexpression of genes involved in ethanol production, protein quality control, and signal transduction, particularly during the exponential phase under heat stress. Collectively, these findings bridge the gap between strain development and molecular understanding, suggesting that the coordinated upregulation of these genetic pathways enhances the adaptive capacity and fermentation efficiency of these thermotolerant strains during sustained growth at 40 °C.

Gabon harbors one of Africa's richest assemblages of non-human primates (NHPs), yet integrated national-scale evidence on their conservation status remains limited. To inform conservation strategies, we conducted the first nationwide assessment integrating habitat dynamics, the geographic distribution of species, and the effectiveness of the protected-area network in the country. We harmonized 300 m land-cover maps (ESA CCI 1992; Copernicus 2022), compiled 481 georeferenced occurrences, and identified concentration areas using kernel density estimation and Getis-Ord Gi* analysis. We quantified land-cover transitions with a per-pixel transition matrix and assessed protected-area capture using Monte Carlo randomization. Ten fully protected species are confirmed, including Gorilla gorilla and Pan troglodytes. Occurrences concentrate mainly in the Ogooué-Ivindo and Haut-Ogooué Provinces; ~10% of the national territory lies above the 90th kernel density percentile (≈26,700 km²), and 1.5% of cells qualify as hotspots at the 99% threshold. Primate records are strongly associated with evergreen broadleaved forests (87.9% of points), which remained persistent from 1992 to 2022 (forest-to-forest = 223,476 km²; 98.13%) with a net decline (-2571.66 km²; -1.19%). Gross losses (4046.58 km²) were mainly attributable to agricultural conversion (68.63%; χ² = 31,525; p < 0.001). Over 90% of records fall in areas stable across 1992-2022. Protected areas (PAs) captured more occurrences (observed 40.1% vs. expected 18.47%; p < 0.001), yet gaps remain for some taxa (e.g., Allochorocebus solatus, 86% outside PAs). Overall, Gabon retains an extensive core of suitable habitat, but targeted action outside PAs and maintenance of landscape connectivity are needed to secure populations where agricultural expansion and fragmentation are intensifying.

Autoimmune diseases arise from complex interactions between genetic susceptibility, immune regulation, and tissue-specific inflammatory processes, yet most risk variants identified by genome-wide association studies occur in non-coding regions with poorly defined biological functions. This review addresses the challenge of interpreting non-coding regulatory variants in autoimmunity by synthesizing emerging analytical frameworks that integrate functional genomics, single-cell profiling, spatial transcriptomics, and multi-omics data. We describe stepwise strategies that refine statistical associations through regulatory annotation, immune cell-state resolution, and perturbational evidence, highlighting complementary approaches such as massively parallel reporter assays, transcriptome-wide association studies, and single-cell expression quantitative trait locus mapping. These methods demonstrate that many autoimmune risk variants exert context-dependent effects that emerge only in specific immune cell states, activation trajectories, or tissue microenvironments. Advances in spatial and chromatin-informed technologies further clarify how regulatory variation shapes immune circuits in diseases such as systemic lupus erythematosus and rheumatoid arthritis. Finally, we discuss how machine learning-enabled multi-omics integration supports molecular endotyping and therapeutic inference while emphasizing interpretability and reproducibility. Collectively, this review highlights a shift from static variant annotation toward dynamic, context-aware analytical frameworks that enable mechanism-informed interpretation of genetic risk in autoimmune disease.

Given that Acer sutchuenense Franch., an endangered maple endemic to China, severely threatened by habitat degradation and climate fluctuations, understanding its spatiotemporal dynamics is crucial for formulating conservation strategies. Herein, climatic, topographic and soil variables were employed to simulate historical, present, and future distribution patterns of A. sutchuenense using the optimized MaxEnt model. Our results indicated that Mean Temperature of Driest Quarter (Bio9) and Temperature Seasonality (Bio4) were the key environmental drivers. Since the Last Interglacial, A. sutchuenense had experienced a continuously reduction in its suitable area, though the mountains surrounding the Sichuan Basin functioned as vital glacial shelters. Although the potential suitable habitat was distributed in a ring shape, A. sutchuenense occurs only on the east and west sides of the Sichuan Basin, probably due to the terrain complexity and limited dispersal ability. In the future, A. sutchuenense faces a westward contraction and a migration lag behind climate velocity due to dispersal constraints. Overall, we recommend a multi-dimensional conservation framework that prioritizes in situ conservation in core refugia, urgently establishes ecological corridors to facilitate eastward migration under climate change, implements ex situ conservation through germplasm collection for vulnerable southwestern populations, and enhances long-term monitoring to ensure species persistence.

Autoimmune hepatitis (AIH) is an inflammatory liver disease characterised by immune-mediated hepatic injury, often leading to liver failure. The underlying molecular mechanisms of AIH remain poorly elucidated, hindering diagnostic and therapeutic advances. This review overviews the current understanding of AIH pathogenesis, which arises from a complex interplay of genetic predisposition, environmental triggers, and immune mechanisms (loss of tolerance, regulatory T cell dysfunction). Furthermore, current technologies and models which are being used to deconvolve the molecular profiles and pathophysiology of AIH are also discussed. Although AIH has a low reported global burden, AIH research is critically skewed towards European ancestry populations. This leaves a significant knowledge gap in diverse ancestry groups, such as those of African ancestry, where emerging research suggests that these patients may experience a more aggressive disease. Collectively, this highlights the need for research in underrepresented global populations to develop tailored diagnostics and effective targeted treatments.

Locus coeruleus (LC) noradrenergic neurons project their axons to the cerebellar cortex and modulate cerebellar circuit function via distinct adrenergic receptor (AR) subtypes. The present study investigated the mechanism by which optogenetic activation of LC noradrenergic neurons modulates facial stimulation-evoked long-term synaptic plasticity at cerebellar mossy fiber-granule cell (MF-GrC) synapses in urethane-anesthetized DBH-Cre mice. Blockade of GABA_A receptors, 20 Hz facial stimulation induced MF-GrC long-term potentiation (LTP) in the control group, and this LTP was impaired by optogenetic activation of LC noradrenergic neurons via α2-ARs. Meanwhile, facial stimulation induced LTP of glutamate sensor fluorescence in the granular layer, which was abolished by chemogenetic activation of LC noradrenergic neurons. Following NMDA receptor blockade, optogenetic activation of LC noradrenergic neurons triggered facial stimulation-induced MF-GrC long-term depression (LTD) via α2A-ARs. Optogenetically activated LC noradrenergic neuron-induced MF-GrC LTD was abolished by protein kinase A (PKA) inhibition but not by protein kinase C inhibition. Immunofluorescence results revealed abundant α2A-AR expression in the granular layer, with particularly high levels in glomeruli, and no colocalization with the glutamate sensor. These results indicate that optogenetic activation of LC noradrenergic neurons impairs facial stimulation-induced MF-GrC LTP by triggering presynaptic LTD via the α2A-AR/PKA signaling cascade.

Snow leopards (Panthera uncia) are a flagship species for global biodiversity conservation, and their effective protection relies on accurate habitat assessment. This study focused on the Chengdu section of the Giant Panda National Park (Pengzhou, Dujiangyan, Chongzhou, Dayi), integrating terrain, climate, vegetation and human disturbance factors. Using the MaxEnt model (AUC = 0.943) and field infrared camera data, we evaluated snow leopard habitat quality. Results showed that: (1) 95.7% of snow leopard records were concentrated in Dayi County; (2) Key drivers included annual mean temperature (peak at -2 °C), annual mean ground temperature (peak at -1 °C) and human population density (>5 km), while NDVI (≈2000) had a significant negative effect; (3) Suitable habitat was 320.98 km² (22.20%), decreasing from Qionglai Mountain to Minshan. This study fills regional survey gaps and provides a scientific basis for snow leopard conservation.