Communications Biology最新文献

The Tibetan sheep is an ideal model animal for investigating adaptations to hypoxia and an important livestock species; however, the reproductive mechanisms that characterize its adaptive responses in extreme environments remain poorly understood. In this study, we employ single-nucleus RNA sequencing to characterize the transcriptomic landscape of the Tibetan sheep testis at four key developmental stages: newborn, pre-sexual maturity, and post-sexual maturity to adulthood. We constructed a single-nucleus transcriptomic atlas and identified two distinct subtypes of spermatogonial stem cells (SSCs): quiescent and active. Notably, we observed that pre-sexually mature Sertoli cells exhibit three distinct transcriptional states. Furthermore, we also identified a transitional state Sertoli cell that links immature and mature Sertoli cells. Analysis of testicular intercellular communication networks provides evidence for understanding somatic-germ cell interactions during spermatogenesis. Our study provides a comprehensive atlas of Tibetan sheep testicular development, revealing key insights into the dynamic changes and regulatory mechanisms of spermatogenesis and somatic cell maturation from birth to adulthood. These findings contribute to a detailed understanding of the genetic mechanisms underlying testicular development in Tibetan sheep and offer valuable insights and references for the study and comprehension of reproductive adaptations in other highland male domestic animals.

Covalent drugs have long played an essential role in therapeutics, yet computational design approaches remain largely confined to virtual screening of existing libraries. Despite recent advances in deep generative models for drug discovery, methods specifically tailored to de novo covalent drug generation are still lacking. Here we introduce CovaGEN, a conditional latent diffusion framework for the de novo design of covalent inhibitors with enhanced drug-likeness and safety. CovaGEN generates ligands from a drug-like latent space while conditioning on target sequences and employing a classifier to guide the formation of desirable covalent warheads. A reinforcement learning strategy further optimizes the safety profiles of generated molecules. Experimental results demonstrate that CovaGEN effectively generates covalent drugs with the desired covalent warheads, exhibiting strong target protein affinity, favorable drug-likeness, and low toxicity. When applied to EGFR T790M and Mpro, the generated compounds exhibit higher probabilities of covalent binding. Overall, CovaGEN offers a pioneering approach for the de novo design of covalent inhibitors, advancing the discovery of covalent drugs with improved properties.

The primary aim of COVID-19 vaccine development is to induce highly efficient broadly neutralizing antibodies (bNAbs) against circulating and emergent SARS-CoV-2 variants. Rapid and sustained germinal center (GC) responses at an early stage are crucial to produce bNAbs. However, the mechanisms underlying the formation of early GC responses and strategies to effectively promote these responses remain to be further investigated. In this study, we found that the combination of anti-CD25 monoclonal antibodies (mAb) with the COVID-19 subunit vaccine significantly enhances cross-reactive neutralizing antibody responses in mice. Modulation of CD25 at different time points before and after vaccination resulted in varying effects on the GC response, with day 0 being the most effective in assisting the vaccine to induce a stronger GC response. This enhancement is achieved by rapidly inhibiting regulatory T (Treg) cells in draining lymph nodes, an effect observed not only in antigen-specific subsets but also across the bulk lymphocyte population-thereby creating a pro-immune microenvironment that facilitates the induction of an effective early GC response. This leads to the generation of more antigen-recognizing B cells and significantly increases both the potency and breadth of neutralizing antibody responses. Our findings propose a strategy to enhance vaccine efficacy against SARS-CoV-2 and other hypervariable pathogens by effectively promoting the development of early and robust GC responses.

Unraveling the complex associations between human phenotypes and molecular pathways can pave the way to improved health and performance, but faces a fundamental challenge: the measurable genes, proteins, and metabolites vastly outnumber the participants in even the largest studies, yielding spurious correlations. To address this, we developed PhenoMol, a bioinformatic framework that integrates comprehensive phenotypic data predictive of outcomes and reduces multi-omic dimensionality using graph theory constrained by prior biological knowledge. This approach generates biologically informed "expression circuits" to identify causal patterns. Applied to a deeply characterized healthy cohort, PhenoMol successfully predicted elite physical performance and outperformed regression models lacking network-based dimensionality reduction. Designed to be versatile and generalizable, PhenoMol enables studies across small and large populations to predict wellness, performance, and disease outcomes. The software is openly available to support future research in health, disease, and performance optimization.

The functional domain of the cerebellum has expanded beyond motor control to also include cognitive and affective functions. In line with this notion, cerebellar volume has increased over recent primate evolution, and cerebellar alterations have been linked to heritable mental disorders. To map the genetic architecture of human cerebellar morphology, we here studied a large imaging genetics sample from the UK Biobank (n discovery = 27,302; n replication: 11,264) with state-of-the art neuroimaging and biostatistics tools. Multivariate GWAS on regional cerebellar MRI features yielded 351 significant genetic loci (226 novel, 94% replicated). Lead SNPs showed positive enrichment for relatively recent genetic mutations over the last 20-40k years (i.e., overlapping the Upper Paleolithic, a period characterized by rapid cultural evolution), while gene level analyses revealed enrichment for human-specific evolution over the last ∼6-8 million years. Finally, we observed genetic overlap with major mental disorders, supporting cerebellar involvement in psychopathology.

The continued spread and regular outbreaks of African swine fever (ASF) have severely threatened the pig-related industries, causing economic losses. African swine fever virus (ASFV) encoded more than 150 different proteins, but the biological characteristics of the majority of these proteins remain unknown. In this study, we leveraged the Phage ImmunoPrecipitation Sequencing (PhIp-Seq) platform to perform an exhaustive serological analysis of ASFV to characterize the specific reactivities of serum anti-ASFV IgG antibodies against the ASFV proteome at peptide resolution. High-resolution epitope mapping of the ASFV antigens was conducted, and a total of 29 ASFV antigens with high immunogenicity were identified, 14 of which, to the best of our knowledge, have not been previously identified as serological antigens. The immunogenicity of these 29 antigens was evaluated, and their conservation was statistically analyzed across 169 ASFV strains. We found that the uncharacterized protein DP238L is a conserved antigen that is widely hit within the population. The immunogenicity of DP238L and multi-epitope recombinant proteins was validated by immunoblotting and animal immunization trials, confirming the immunogenicity of the identified antigens and the reliability of the PhIp-Seq based epitope mapping strategy. These findings provide insights into the structures and functions of antigen proteins and identify crucial targets for ASFV detection and vaccine development.

We present a revised diagnosis of the extinct galeomorph shark †Bavariscyllium based on dental and skeletal material from the Upper Jurassic of Germany and test its purported carcharhiniform affinity through morphometric and phylogenetic analyses. Although †Bavariscyllium possesses a whisker-like throat barbel suggesting a closer relationship with orectolobiforms, our findings reveal insufficient evidence to confidently assign †Bavariscyllium to either Orectolobiformes or Carcharhiniformes. Additionally, we present quantitative evidence indicating that early galeomorphs, despite probably not being placed among extant orders, were exploring a variety of body forms, predating the divergence of most major body plans among modern representatives. †Bavariscyllium exhibits generalised clutching-type teeth with a hemiaulacorhize root characterised by strongly flared root lobes, closely resembling the supposed earliest carcharhiniforms from the Middle Jurassic. However, these features neither confirm nor refute a carcharhiniform affinity, questioning the reliability of these early galeomorphs as calibration fossils for dating the divergence of carcharhiniforms in phylogenomic analyses.

We previously identified Stromalin, a cohesin complex subunit, as a learning suppressor in Drosophila melanogaster that acts by limiting synaptic vesicle numbers in dopamine neurons. However, the mechanism by which Stromalin modulates synaptic vesicles remains unclear. We hypothesized that this occurred through the cohesin complex's function in developmental gene regulation. Through dopamine neuron-specific RNA-sequencing followed by RNAi screening, we identified Neprilysin 1 (Nep1), a zinc-dependent metallopeptidase, to be positively regulated by the cohesin complex and a key downstream effector of Stromalin. Nep1 knockdown phenocopies Stromalin knockdown effects, enhancing learning and memory and increasing synaptic vesicle markers in dopamine neurons. Like Stromalin, Nep1 suppresses synaptic strength between dopamine and mushroom body neurons. Finally, we show Nep1 overexpression rescues both memory and synaptic vesicle phenotypes caused by Stromalin reduction. Interestingly, while cohesin complex appears to set the expression levels for Nep1 during development, Nep1 function in adult flies supports its learning effects.

Liver cancer treatment with cisplatin is often hindered by drug resistance. This study aimed to identify key genes associated with cisplatin resistance in liver cancer and develop targeted inhibitors. Using genome-wide CRISPR-Cas9 screening, ATOX1 was identified as a critical gene for cisplatin resistance. ATOX1 was highly expressed in liver cancer tissues and associated with poor prognosis. Knockdown of ATOX1 in liver cancer cells enhanced cisplatin sensitivity in vitro and in vivo. Molecular dynamics simulation and virtual screening identified compound 8 as a potent ATOX1 inhibitor with high affinity (Kd = 12.5 μM) and exhibited synergistic effects with cisplatin on liver cancer cell growth. Mechanistically, compound 8 inhibits the activity of ATOX1, leading to intracellular copper accumulation. The elevated copper levels subsequently promote increased DNA methylation at the NOTCH1 promoter, resulting in suppression of the NOTCH1/HES1 signaling pathway and enhancing the sensitivity of liver cancer cells to cisplatin. In conclusion, ATOX1 is crucial for cisplatin resistance in liver cancer and linked to poor prognosis. Targeting ATOX1 with compound 8 may be a novel therapeutic strategy for overcoming cisplatin resistance.

Methamphetamine (Meth) abuse leads to cognitive impairment, with the hippocampus being severely affected. However, the precise cellular mechanisms underlying Meth-induced hippocampal damage remain unclear. This study utilizes single-nucleus RNA sequencing (snRNA-seq) to investigate the transcriptional changes in mouse hippocampal neurons after acute Meth exposure. We analyze 36,376 nuclei isolated from the hippocampus of acute Meth-treated and control mice, revealing significant alterations in excitatory neuron transcriptomes. Notably, oxidative phosphorylation (OXPHOS) and peroxisome pathways were prominently activated. Five distinct excitatory neuron subtypes were identified across different hippocampal regions, with the dorsal-ventral (DG) region exhibiting the most pronounced changes in gene expression, inflammatory response, reactive oxygen species (ROS) signaling, and OXPHOS activity. High-dimensional weighted correlation network analysis (hdWGCNA) reveals five modules endowed with functional roles in recognizing-associated pathways. Furthermore, it provides insights into intercellular communication and transcriptional regulation patterns within the hippocampus after Meth exposure. In conclusion, this study offers a comprehensive understanding of Meth's impact on hippocampal transcriptomes and may guide the development of therapeutic strategies for acute Meth-induced neurotoxicity.