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PubMed2025

Systematically investigating and identifying bacteriocins in the human gut microbiome.

Human gut microbiota produces unmodified bacteriocins, natural antimicrobial peptides that protect against pathogens and regulate host physiology. However, current bioinformatic tools limit the comprehensive investigation of bacteriocins' biosynthesis, obstructing research into their biological functions. Here, we introduce IIBacFinder, a superior analysis pipeline for identifying unmodified class II bacteriocins. Through large-scale bioinformatic analysis and experimental validation, we demonstrate their widespread distribution across the bacterial kingdom, with most being habitat specific. Analyzing over 280,000 bacterial genomes, we reveal the diverse potential of human gut bacteria to produce these bacteriocins. Guided by meta-omics analysis, we synthesized 26 hypothetical bacteriocins from gut commensal species, with 16 showing antibacterial activities. Further ex vivo tests show minimal impact of narrow-spectrum bacteriocins on human fecal microbiota. Our study highlights the huge biosynthetic potential of unmodified bacteriocins in the human gut, paving the way for understanding their biological functions and health implications.

Humans↗
PubMed2026

Elucidating shared genetic signals between type 2 diabetes and three neurodegenerative dementia phenotypes.

Type 2 diabetes (T2D) and dementia frequently co-occur, yet the biological mechanisms underlying this comorbidity remain incompletely understood. Here, we systematically investigate shared genetic signals between T2D and three forms of neurodegenerative dementia (Alzheimer disease, Lewy body dementia, and sporadic frontotemporal dementia) using large-scale genome-wide association studies of clinically diagnosed individuals. We identify five genomic regions harboring shared association signals between T2D and at least one dementia subtype. Among these, the APOE locus was common to all dementia subtypes, whereas the remaining four loci (GBA, CRY2/PEX16/MAPK8IP1, INO80E, and NSF) were each shared exclusively between T2D and one dementia subtype. Integrating multi-omics data across several disease-relevant tissues and orthogonal lines of functional evidence, we prioritize 26 candidate genes through which these shared genetic loci potentially mediate their effect. Pathway enrichment highlights lipid and lipoprotein regulatory biology as a central shared axis. Mendelian randomization analyses using genetically regulated gene expression in relevant tissues indicate pleiotropic mechanisms with divergent phenotypic consequences. Our findings identify shared genetic loci between T2D and neurodegenerative dementia, revealing systemic metabolic-neurodegenerative trade-offs and highlighting key genes that underpin the comorbidity, providing a framework for improved understanding of age-related multi-morbidity.

Alzheimer disease↗
PubMed2026

Comparative metabolomic and transcriptomic profiling of flavonoid diversity and antioxidant capacity in three Isatis species.

Flavonoids are key bioactive compounds in plants with significant health benefits. This study employs an integrated multi-omics approach to investigate flavonoid diversity and antioxidant capacity across three Isatis species: I. oblongata, I. tinctoria, and I. indigotica. Metabolomic profiling identified 200 flavonoids, with glycosides being the most abundant class. I. tinctoria exhibited the highest total flavonoid content and antioxidant activity, strongly correlated with the accumulation of 53 core differential flavonoid metabolites, most of which were glycosylated derivatives. Transcriptomic analysis revealed coordinated upregulation of phenylpropanoid pathway genes and specific UDP-glycosyltransferases (UGTs) in I. tinctoria, providing a genetic basis for its enhanced glycoside production. The study establishes a clear genotype-metabolite-phenotype linkage, highlighting glycosylation as a key mechanism underlying flavonoid-driven antioxidant superiority in Isatis. Although the current evidence is primarily correlative, the consistent and strong associations across independent transcriptomic, metabolomic, and antioxidant datasets provide a robust foundation for this conclusion. These findings offer new insights into the metabolic evolution and regulatory networks of flavonoids, with implications for breeding and metabolic engineering of high-value medicinal plants.

Flavonoids↗
PubMed2025

Transfer learning with multiomics integration and deep neural networks reveals drug resistance mechanisms in cancer.

Drug resistance remains one of the primary challenges in effective cancer therapy. In this study, we employed a deep neural network (DNN)-based transfer learning (TL) approach to predict drug response and uncover drug resistance mechanisms. We integrated gene expression, somatic mutation, and copy number aberration (CNA) data with drug response profiles using multi-omics integration (MI). We used the Genomics of Drug Sensitivity in Cancer (GDSC) data for training and incorporated drugs with same pathways into the training models. We then evaluated drug response predictions on independent in-vivo PDX Encyclopedia (PDX) and ex-vivo the Cancer Genome Atlas (TCGA) datasets. In addition, we conducted pathway enrichment analyses to elucidate the mechanisms underlying drug resistance for paclitaxel, 5-fluorouracil (5-FU), gemcitabine, and cetuximab. We also applied Fisher's exact test (FET) to assess potential associations between drug resistance and the presence of mutations or CNAs. Our pan-drug models outperformed other methods based on the area under the precision-recall curve (AUCPR). Our pathway enrichment analyses revealed LDHB-mediated pyruvate metabolism and FYN-mediated focal adhesion might have pivotal roles in paclitaxel resistance, while PINK1-mediated mitophagy might be critical in 5-FU resistance. In addition to transcriptional activation, FET suggested that CNAs in LDHB and PINK1 may also be associated with resistance to paclitaxel and 5-FU, respectively. Furthermore, enrichment results for paclitaxel and cetuximab indicated shared resistance mechanisms between the two drugs. Importantly, our findings are consistent with prior experimental studies, providing literature-based validation of our results. Overall, our DNN-based TL approach achieved strong predictive performance across PDX & TCGA datasets and enrichment analyses provided valuable biological insights into drug resistance mechanisms.

Humans↗
PubMed2026

Clinical proteomics in inborn errors of metabolism: from biomarker discovery to implementation.

INTRODUCTION: Inborn errors of metabolism (IEMs) are rare, heterogeneous disorders traditionally diagnosed through genetic testing, enzyme assays, and metabolite measurements. However, these tools often do not fully explain phenotypic variability, organ involvement, disease progression, or treatment response. Clinical proteomics provides a complementary functional layer by capturing changes in protein abundance, proteoforms, post-translational modifications (PTM), and biological pathways, offering insights beyond genotype- and metabolite-based approaches. AREAS COVERED: This review examines the role of high-resolution mass spectrometry and computational proteomics in biomarker discovery and clinical decision-making for IEMs. It focuses on their contribution to diagnosis, variant interpretation, patient stratification, and treatment monitoring. Disease-specific applications are discussed, with the strongest evidence in lysosomal storage disorders, mitochondrial diseases, congenital disorders of glycosylation, and selected neurodegenerative or renal metabolic conditions. The literature search was performed in PubMed, Scopus, Web of Science, and Google Scholar, covering peer-reviewed articles available up to 2026, with emphasis on methodological advances and translational applications in clinical proteomics for IEMs. EXPERT OPINION: Proteomics will not replace established diagnostic tools, but it can help address clinically actionable questions in selected contexts. Translation into clinical practice will require standardized workflows, multicenter validation, clinically anchored endpoints, and integration with other omics approaches.

Humans↗
PubMed2026

Mutational signatures in blood-brain barrier: mechanisms, computational insights, and clinical applications in precision oncology.

The blood - brain barrier (BBB) plays a central role in maintaining central nervous system (CNS) homeostasis, and its disruption is a defining feature of malignant brain tumors such as glioblastoma. Emerging evidence indicates that BBB dysfunction not only alters the tumor microenvironment but also shapes the mutational processes that drive genomic instability in CNS malignancies. This review synthesizes current understanding of the biological mechanisms linking BBB breakdown with distinct mutational signatures, including those arising from oxidative stress, hypoxia-induced replication stress, lipid peroxidation, inflammation, and metabolic reprogramming. Advances in next-generation sequencing, coupled with computational tools such as non-negative matrix factorization, Bayesian modeling, and deep learning, have enabled precise extraction of these signatures and their integration with multi-omics data. Clinically, BBB-associated mutational signatures offer significant promise for therapeutic stratification, prediction of treatment response, and noninvasive monitoring through cerebrospinal fluid - derived circulating tumor DNA. Despite these advances, challenges persist due to limited tissue accessibility, low-yield CSF samples, incomplete mechanistic models, and the lack of CNS-specific analytical frameworks. A deeper understanding of BBB-driven mutational processes, supported by improved computational approaches and integrative datasets, holds potential to advance precision oncology in neuro-oncology.

Humans↗
PubMed2025

Stepping out of the dark: how metabolomics shed light on fungal biology.

Metabolomics, a critical tool for analyzing small-molecule metabolites, integrates with genomics, transcriptomics, and proteomics to provide a systems-level understanding of fungal biology. By mapping metabolic networks, it elucidates regulatory mechanisms driving physiological and ecological adaptations. In fungal pathogenesis, metabolomics reveals host-pathogen dynamics, identifying virulence factors like gliotoxin in Aspergillus fumigatus and metabolic shifts, such as glyoxylate cycle upregulation in Candida albicans. Ecologically, it highlights fungal responses to abiotic stressors, including osmolyte production like trehalose, enhancing survival in extreme environments. These insights highlight metabolomics' role in decoding fungal persistence and niche colonization. In drug discovery, it aids target identification by profiling biosynthetic pathways, supporting novel antifungal and nanostructured therapy development. Combined with multi-omics, metabolomics advances insights into fungal pathogenesis, ecological interactions, and therapeutic innovation, offering translational potential for addressing antifungal resistance and improving treatment outcomes for fungal infections. Its progress shed light on complex fungal molecular profiles, advancing discovery and innovation in fungal biology.

Metabolomics↗
PubMed2025

TRAIT: A Comprehensive Database for T-cell Receptor-antigen Interactions.

Comprehensive and integrated resources on interactions between T-cell receptors (TCRs) and antigens are still lacking for adoptive T-cell-based immunotherapies, highlighting a significant gap that must be addressed to fully understand the mechanisms of antigen recognition by T cells. In this study, we present the T-cell receptor-antigen interaction database (TRAIT), a comprehensive database that profiles the interactions between TCRs and antigens. TRAIT stands out due to its comprehensive description of TCR-antigen interactions by integrating sequences, structures, and affinities. It provides millions of experimentally validated TCR-antigen pairs, resulting in an exhaustive landscape of antigen-specific TCRs. Notably, TRAIT emphasizes single-cell omics as a major reliable data source for TCR-antigen interactions and includes millions of reliable non-interactive TCRs. Additionally, it thoroughly demonstrates the interactions between mutations of TCRs and antigens, thereby benefiting affinity optimization of engineered TCRs as well as vaccine design. TCRs on clinical trials are innovatively provided. With the significant efforts made toward elucidating the complex interactions between TCRs and antigens, TRAIT is expected to ultimately contribute superior algorithms and substantial advancements in the field of T-cell-based immunotherapies. TRAIT is freely accessible at https://pgx.zju.edu.cn/traitdb.

Receptors, Antigen, T-Cell↗
PubMed2026

Recent Advances in the Comprehension of Molecular and Genetic Mechanisms Underlying Yeast Biocontrol Efficacy Against Fungal Pathogens in Agriculture.

Recent advances in biotechnologies have enabled scientists to uncover biological processes across multiple research fields. Still, the molecular and genetic mechanisms underlying the biological control efficacy of yeast biocontrol agents (YBCAs) against fungal plant pathogens remain incompletely elucidated. This review focuses on recent insights into the regulatory bases and molecular interplay underlying successful disease control by YBCAs. It provides a detailed description of core antagonistic molecular mechanisms-nutrient and iron competition, mycoparasitism via cell wall degradation, antifungal compounds production, oxidative stress resistance, biofilm formation and colonization, and induction of the host defense responses-and integrates genomic, transcriptomic, proteomic, and metabolomic evidence to elucidate each mechanism. Further, how genetic engineering-based approaches that leverage omics data and functional genetics can help overcoming obstacles to translate YBCAs efficacy from laboratory conditions to the field are also discussed. Finally, the use of the CRISPR-Cas technology is recommended to better exploit how master transcription factors coordinate multiple mechanisms simultaneously; these factors are crucial for the synergistic antifungal effect, which is critical for developing highly effective YBCAs. Ultimately, the mechanism-based perspective provides a unified conceptual framework for understanding YBCAs efficacy and can guide the rational design of next-generation biocontrol agents for sustainable agriculture.

CRISPR-Cas technology↗
PubMed2026

Molecular biomarker profiling in noninfectious uveitis: a chronological review of discovery.

PURPOSE OR REVIEW: Noninfectious uveitis (NIU) encompasses a heterogeneous group of immune-mediated intraocular inflammatory diseases whose complexity has driven systematic molecular biomarker discovery. This review presents NIU molecular biomarkers organized by biological category; autoantigens, human leukocyte antigens (HLA) and genetic markers, cellular immune subsets, cytokines, chemokines, and multiomics platforms including proteomics, microbiome metagenomics, metabolomics, and single-cell transcriptomics with each category presented in strict chronological order of landmark discovery. RECENT FINDINGS: We present a review organized along two nested timelines. Categories are presented in the order they historically emerged in the field, and within each category, landmark discoveries appear in chronological sequence. This allows the reader to trace how each biomarker category evolved: from foundational autoantigen identification in experimental uveitis models, through the genomic revolution of HLA association studies, into cellular immunophenotyping, cytokine profiling of aqueous humor, chemokine mapping of intraocular trafficking, and finally the emerging omics platforms that may potentially anchor precision medicine in NIU. Each biomarker is paired in line with its linked targeted therapeutic. SUMMARY: Biomarker research has transformed the understanding of NIU from a clinically defined syndrome into a group of molecularly distinct immune disorders. Advances spanning autoantigens, genetics, immune-cell profiling, cytokines, chemokines, and multiomics have revealed novel pathogenic mechanisms and therapeutic targets. Integration of these biomarkers with targeted therapies may accelerate the transition toward precision medicine in uveitis care.

cytokines↗
PubMed2025

Whole genome sequence-based association analysis of African American individuals with bipolar disorder and schizophrenia.

In studies of individuals of primarily European genetic ancestry, common and low-frequency variants and rare coding variants have been found to be associated with the risk of bipolar disorder (BD) and schizophrenia (SZ). However, less is known for individuals of other genetic ancestries or the role of rare non-coding variants in BD and SZ risk. We performed whole genome sequencing of African American individuals: 1,598 with BD, 3,295 with SZ, and 2,651 unaffected controls (InPSYght study). We increased power by incorporating 14,812 jointly called psychiatrically unscreened ancestry-matched controls from the Trans-Omics for Precision Medicine (TOPMed) Program for a total of 17,463 controls. To identify variants and sets of variants associated with BD and/or SZ, we performed single-variant tests, gene-based tests for singleton protein truncating variants, and rare and low-frequency variant annotation-based tests with conservation and universal chromatin states and sliding windows. We found suggestive evidence of BD association with single-variants on chromosome 18 and of lower BD risk associated with rare and low-frequency variants on chromosome 11 in a region with multiple BD GWAS loci, using a sliding window approach. We also found that chromatin and conservation state tests can be used to detect differential calling of variants in controls sequenced at different centers and to assess the effectiveness of sequencing metric covariate adjustments. Our findings reinforce the need for continued whole genome sequencing in additional samples of African American individuals and more comprehensive functional annotation of non-coding variants.

Journal Article↗
PubMed2025

Genomic analysis of Dasiphora on the Qinghai-Tibet Plateau provides insights into genetic divergence and flower color variation.

The Qinghai-Tibet Plateau (QTP) harbors diverse alpine flora, including the ecologically significant shrubs Dasiphora fruticosa and D. glabra, for which taxonomic uncertainties remain and adaptive mechanisms are still poorly understood. Based on high-quality genome assembly, population resequencing, and multi-omics integration, we elucidated their evolutionary divergence and flower color genetics. Chromosome-level haplotype-resolved genomes were assembled: autotetraploid D. fruticosa (929.99 Mb) and diploid D. glabra (450.89 Mb). Phylogenetic analysis showed that the tetraploid D. fruticosa and D. glabra in this study clustered together, while the diploid D. fruticosa sequenced by previous research formed a distinct lineage clustered outside. Consistently, population structure analysis of 55 samples revealed three major clades, with D. fruticosa further subdivided into two divergent branches. Additionally, hybridization events detected by Admixture, coupled with ploidy complexity identified via flow cytometry highlight the intricate genetic relationships within this genus. Adaptive gene families expanded in antioxidant (flavonoid synthesis) and secondary metabolism pathways, adapting to ultraviolet radiation and cold stress. Natural selection analysis identified 193 candidate genes (e.g., TFB5 in the DNA repair pathway), predominantly localized to chromosome 5, which are potential candidates for high-altitude adaptation. Transcriptome and metabolome analyses showed D. fruticosa's yellow petals derive from flavonol (quercetin) accumulation, while D. glabra's white petals result from proanthocyanidin biosynthesis via high LAR/ANR expression. This study provides insights into the taxonomic revision and adaptive genetic divergence of alpine plants, and offers a foundation for horticultural improvement of Dasiphora.

Flowers↗
PubMed2025

Harnessing fern stress adaptations: From evolution and ecophysiology to molecular biology.

Ferns are the second most diverse vascular plant lineage after angiosperms and have been a key ecological component of Earth's biodiversity for more than 380 million years. Importantly, ferns are sister to seed plants, providing a critical outgroup for understanding the evolution of seed plant features. Ferns are remarkably resilient to abiotic and biotic stresses due to a long evolutionary history with adaptations to diverse habitats, stresses, and herbivores. As a result, ferns produce a multitude of secondary metabolites with unique bioactivities; these chemicals are potentially linked to the adaptation of ferns to herbivory, various abiotic and biotic stresses, and changing environments. Assembled reference genomes and the identification of key metabolic compounds of multiple ferns have already made significant contributions to human health and well-being. Here, we review the recent scientific advances in fern research, including evolution, stress resistance, metabolites and medicinal utilization, and comparative multi-omics applications. We propose that integrated investigations involving ecological, physiological, and molecular techniques will facilitate the future research translation of fern resources in diverse areas including soil remediation, biopesticides, and medicine. Advances in our understanding of fern molecular biology will provide new insights into the evolution of land plants and promote the utilization of ferns for heightened environmental restoration, crop protection and human health.

Ferns↗
PubMed2026

Sex-specific ethylene responses drive floral sexual plasticity in Cannabis sativa.

Cannabis sativa L. exhibits pronounced sexual plasticity in which both XX and XY plants can undergo floral phenotypic sex reversal in response to ethylene modulation, yet the underlying molecular mechanisms remain poorly defined. Here, we present the most extensive multi-omic analysis of ethylene-induced sex change in C. sativa to date, integrating over 130 RNA-seq libraries, ethylene pathway metabolite quantification, and whole-genome sequencing across three XX and XY genotypes. Treatments with silver thiosulfate and ethephon induced more than 80% phenotypic conversion, but transcriptomic responses diverged sharply between XX and XY plants. Profiling 47 ERGs revealed 14 high-confidence candidates, including CsACS1, CsACO5, CsERF1, and CsMTN, with sex-specific and temporal expression patterns that show dynamic ethylene mediation of plasticity. Early transcriptional activation occurred prior to the emergence of flowers, within 18 h of sex-change treatments and the photoperiod-induced transition to flowering. As opposite-sex floral tissues emerged, ethylene-related gene expression shifted accordingly within developing floral organs, with distinct sets of genes stabilizing the opposite-sex phenotype in XX and XY plants. Several candidates were located in non-recombining regions of the X chromosome or were absent from the Y chromosome, and most exhibited low nucleotide diversity, consistent with functional constraint. These results provide a high-resolution view of ethylene-responsive sexual plasticity in cannabis and show that the shared capacity for sex reversal in XX and XY plants is implemented through distinct regulatory trajectories that produce opposite-sex floral phenotypes. This work expands the mechanistic understanding of sex expression in dioecious species and identifies candidate genes relevant to the development of sex-stable cultivars.

Ethylenes↗
PubMed2026

Leptospira-host interactions: advancing next-generation vaccines and diagnostics.

SUMMARYLeptospirosis, a widespread zoonotic disease caused by pathogenic Leptospira species, remains a major public health challenge, particularly in tropical and subtropical regions. Despite advances in understanding Leptospira biology and pathogenesis, effective disease control continues to be limited by the lack of rapid, early diagnostics, and broadly protective vaccines. This review comprehensively examines recent progress in deciphering Leptospira-host interactions, with emphasis on key virulence factors, immune-evasion mechanisms, and host immune responses that influence disease outcomes. Particular focus is placed on the molecular and cellular basis of adhesion, invasion, immune modulation, and persistent colonization. We further discuss the limitations of current vaccines and diagnostic approaches, and highlight how emerging technologies, including pan-genomics, proteomics, reverse vaccinology, immunoinformatics, and omics-based antigen discovery, are facilitating the development of next-generation vaccines and diagnostics. Finally, we outline major translational challenges and future perspectives for improving clinical management, surveillance, and prevention of leptospirosis. The concepts discussed in this review may also provide broader insights into vaccine and diagnostic development for other zoonotic bacterial infections.

Humans↗
PubMed2026

Genome-wide identification and functional analysis of the BES1-like (VfBES1) gene family in Vernicia fordii reveals its role in floral development.

BACKGROUND: Vernicia fordii Hemsl (also known as Tung tree), an significant commercial oil-producing tree species, is a monoecious and diclinous species with male and female flowers on the same inflorescence; however, the molecular mechanisms governing its floral sex determination remain elusive, particularly the genetic basis underlying the skewed female-to-male flower ratio and the evolutionary dynamics of sex-related gene families, which severely restrict targeted breeding for yield enhancement. In the model plant Arabidopsis, the BRI1 EMS SUPPRESSOR 1 (BES1) transcription factor family plays a crucial role in Brassinosteroid (BR) signaling and reproductive development. However, its function remains largely unexplored in woody perennials. RESULTS: In this study, we introduce the genome-wide identification and functional characterization of the BES1-like (VfBES1) gene family in the Tung tree for the first time. Integrative multi-omics approaches reveal seven VfBES1 genes that are clustered into three phylogenetically distinct clades, each characterized by clade-specific motifs and structural simplicity. Segmental duplication events (VfBES1-1/VfBES1-5 and VfBES1-4/VfBES1-7) and promoter cis-element enrichment (hormone-responsive and abiotic stress-related motifs) highlight evolutionary innovation and functional diversification. Spatiotemporal expression profiling reveals VfBES1 genes' tissue- and stage-specific roles. VfBES1-1 predominantly expresses in female flowers and fruits, suggesting its possible roles in late-stage sex maintenance or ovule and fruit development. VfBES1-2 and VfBES1-6 exhibit male flower-specific and early floral developmental activation, respectively. Nuclear-localized VfBES1-6 displays co-expression with VfMYB35-1 gene, which is a regulator of male structure degeneration. CONCLUSIONS: Findings in this study shed light on the regulatory roles of VfBES1 genes in the floral development of the Tung tree, providing a reference for its precision breeding to enhance flowering synchrony and seed productivity. This study also provides a comparative framework for understanding the functional diversity of BES1-like genes in non-model woody plants.

Flowers↗
PubMed2025

Advances in tumor subclone formation and mechanisms of growth and invasion.

Tumor subclones refer to distinct cell populations within the same tumor that possess different genetic characteristics. They play a crucial role in understanding tumor heterogeneity, evolution, and therapeutic resistance. The formation of tumor subclones is driven by several key mechanisms, including the inherent genetic instability of tumor cells, which facilitates the accumulation of novel mutations; selective pressures from the tumor microenvironment and therapeutic interventions, which promote the expansion of certain subclones; and epigenetic modifications, such as DNA methylation and histone modifications, which alter gene expression patterns. Major methodologies for studying tumor subclones include single-cell sequencing, liquid biopsy, and spatial transcriptomics, which provide insights into clonal architecture and dynamic evolution. Beyond their direct involvement in tumor growth and invasion, subclones significantly contribute to tumor heterogeneity, immune evasion, and treatment resistance. Thus, an in-depth investigation of tumor subclones not only aids in guiding personalized precision therapy, overcoming drug resistance, and identifying novel therapeutic targets, but also enhances our ability to predict recurrence and metastasis risks while elucidating the mechanisms underlying tumor heterogeneity. The integration of artificial intelligence, big data analytics, and multi-omics technologies is expected to further advance research in tumor subclones, paving the way for novel strategies in cancer diagnosis and treatment. This review aims to provide a comprehensive overview of tumor subclone formation mechanisms, evolutionary models, analytical methods, and clinical implications, offering insights into precision oncology and future translational research.

Humans↗
PubMed2026

A novel iPSC model of Bryant-Li-Bhoj neurodevelopmental/neurodegenerative syndrome demonstrates the role of histone H3.3 in chromatin dynamics, neuronal differentiation, and maturation.

BACKGROUND: Bryant-Li-Bhoj neurodevelopmental syndrome (BLBS) is neurogenetic disorder caused by variants in H3-3A and H3-3B, the two genes that encode histone H3.3. Ninety-nine percent of individuals with BLBS show developmental delay/intellectual disability, but the mechanism by which variants in H3.3 result in these phenotypes is not yet understood, limiting the therapeutic interventions available to individuals living with BLBS. METHODS: Here, we investigate how one BLBS-causative variant, H3-3B p.Leu48Arg (L48R), affects neurodevelopment using an induced pluripotent stem cell model differentiated to 2D neural progenitor cells (NPCs), 2D forebrain neurons (FBNs), and 3D dorsal forebrain organoids (DFBOs). We employ a multi-omic approach in the 2D models to quantify the resulting changes in gene expression and chromatin accessibility. We used immunofluorescence (IF) staining to define the identities of cells in the 3D DFBOs and whole-cell patch clamp to investigate the electrophysiological properties of neurons in DFBOs. RESULTS: In the 2D systems, we found dysregulated gene expression and chromatin accessibility affecting neuronal fate, adhesion, neurotransmission, and excitatory/inhibitory balance. Immunofluorescence of DFBOs corroborated altered proportions of radial glia and mature neuronal populations. Patch clamp recordings revealed decreased electrical activity in neurons from L48R DFBOs compared to control DFBOs. CONCLUSIONS: These data provide the first mechanistic insights into the pathogenesis of BLBS from a human-derived model of neurodevelopment, which suggest that H3.3 L48R increases H3-3B expression, resulting in the hyper-deposition of H3.3 into the nucleosome, which underlies changes in gene expression and chromatin accessibility. Functionally, this causes dysregulation of cell adhesion, neurotransmission, and the balance between excitatory and inhibitory signaling. These results are a crucial step towards preclinical development and testing of targeted therapies for this and related disorders.

Histones↗