Biology subjects

Zhou, X.

Publications and source records attributed to Zhou, X..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Unifying physical and molecular coordinate systems across modalities in spatial biology

Establishing a unified physical and molecular coordinate system from fragmented multi-modal data is a longstanding challenge in biology. Here, we present MAPS, a modality-agnostic platform for spatial biology comprising (1) MAPS-alignment for ultrafast alignment of any modality, (2) MAPS-integration for both anchored and unanchored integration across orthogonal modalities for 3D multi-modal reconstruction, and (3) MAPS-Explorer for large-scale interactive 3D analysis. MAPS outperformed existing methods across extensive benchmarks on 34 datasets spanning 16 technology platforms and 6 modalities, while delineating fine-grained multi-modal tissue architectures across diverse biological systems in mouse and human. At cross-consortium scale, MAPS integrated 434 slices comprising 21 million cells from 18 atlases and 5 modalities to construct the most comprehensive 3D multi-modal mouse brain atlas. At individual laboratory scale, MAPS empowered routine 2D spatial assays to reconstruct continuous 3D multi-modal landscapes of human hepatocellular carcinoma, revealing the limitations of 2D spatial relationships and uncovering depth-dependent immune-state transitions.

bioinformatics↗

bioRxiv2026

Absence of a spindle position checkpoint in the fungal pathogen Cryptococcus neoformans

To maintain genome stability, it is crucial that cells do not initiate cytokinesis until chromosomes have been properly segregated. In the model budding yeast Saccharomyces cerevisiae, a surveillance mechanism called the Spindle Position Checkpoint (SPoC) ensures this coordination by regulating the Mitotic Exit Network (MEN) to couple exit from mitosis and cytokinesis to spindle position. The MEN is conserved in Ascomycota where the orthologous pathway in the fission yeast Schizosaccharomyces pombe, the Septation Initiation Network (SIN), regulates cytokinesis in response to defects in spindle elongation. Here, we show that the MEN/SIN pathway is conserved in the basidiomycetous budding yeast and human pathogen, Cryptococcus neoformans, and controls cytokinesis. However, spindle position or elongation does not regulate pathway activation or cell cycle progression in C. neoformans. In essence, there appears to be no SPoC in this organism to delay cytokinesis upon defects in mitosis. We speculate that while increasing the risk of genome instability, the lack of a SPoC might facilitate C. neoformans's ability to change ploidy in the host.

cell biology↗

bioRxiv2026

A closed-loop reinforcement learning framework for rapid compound directed optimization

Generative artificial intelligence (AI) holds transformative potential for drug discovery, yet existing architectures typically operate in open loops without experimental feedback. Here we introduce rapid compound directed optimization (RCDO), a closed-loop reinforcement learning framework that accelerates the optimization process by bridging dry-lab computation with wet-lab feedback. RCDO couples a three-dimensional structure-guided generative model with a multi-level reward system updated after each design cycle using experimental measurements from all synthesized compounds, including inactive or developability-failed compounds. By continuously aligning the generative model with accumulated wet-lab measurements, RCDO substantially compresses optimization timelines. We evaluated RCDO through retrospective benchmarking against historical optimization trajectories and prospective wet-lab campaigns targeting ROR1, NLRP3, and NSD3. Across prospective evaluations, RCDO rapidly resolved key optimization bottlenecks within two to three design cycles: improving the oral exposure of an ROR1 inhibitor by 40-fold while maintaining antitumor efficacy, reducing CYP2C19 inhibition of an NLRP3 antagonist by 20-fold while preserving inflammasome activity, and boosting the binding affinity of an NSD3 hit by 18-fold. By directly coupling wet-lab feedback to generative learning, RCDO establishes an efficient platform for compound directed optimization, transforming AI-driven drug discovery from static generation into continuous experimental adaptation.

bioinformatics↗

bioRxiv2026

A virus co-opts vector's m⁶A machinery for adaptive compensation

Insect vectors harbor diverse viruses that threaten human health and agricultural production, yet the genetic basis of mutualistic virus-vector interactions remain elusive. This underscores a long-standing paradox in pest management: viruses that cause destructive diseases also facilitate vector adaptation in ways that benefit both parties. Here we show that the globally devastating tomato yellow leaf curl virus (TYLCV) acts as a Cooperative Partner, co-opting its vector's m6A epitranscriptomic machinery to offset the reproductive fitness costs of neonicotinoid resistance in the whitefly. In resistant vectors, TYLCV infection alleviates reproductive deficits via the m6A-dependent pathway, where the methyltransferase METTL14 and demethylase ALKBH4 coordinately stabilize vitellogenin (Vg) transcripts to boost female fecundity. Mechanistically, the viral C2 and CP proteins directly interact with METTL14 and ALKBH4, respectively, remodeling their RNA binding affinity to facilitate mA modification on Vg. Disrupting either of these viral-vector protein interactions restores a reproductive cost phenotype in viruliferous resistant vectors, offering novel targets for sustainable pest control. Our findings uncover a fundamental role of epigenetic marks in adaptive trait, reshaping beneficial virus-vector relationships and providing new insights for innovative public health and crop protection strategies to address global challenges.

microbiology↗

bioRxiv2026

AI-driven framework modeling perturbation in brain organoids reveals candidate genes for autism

Autism gene discovery is constrained by the rarity and heterogeneity of damaging variants, requiring large cohorts to identify susceptibility genes. Neural organoids and single-cell foundation models enable perturbation modeling in neurodevelopmental contexts. Here, we show that perturbation-informed foundation modeling of neural organoids can provide functional context for prioritizing candidate genes with genomic and clinical support. We constructed a 3.6-million-cell organoid atlas and trained models to predict genome-wide perturbation responses. Benchmarking 17 models identified a telencephalic neuron-specific model best preserving autism-relevant perturbation structure. Genome-wide profiling revealed two clusters associated with mid-fetal synaptic neuronal processes and early radial glia ubiquitin signaling. These clusters were supported by damaging-variant enrichment and clinical phenotypes across 89,916 family-based samples. Logistic-regression prioritization identified 343 candidates, including 167 in the key clusters, with convergence across TADA signals and recurrent evidence for NBEA and KLHDC10. This framework integrates predicted perturbation effects with genomic evidence to support autism candidate prioritization.

bioinformatics↗

bioRxiv2026

An inflammation-associated five-gene expression signature stratifies survival and immune states in lung adenocarcinoma: an integrative public-cohort analysis

Background: Inflammation and the tumor immune microenvironment contribute to lung adenocarcinoma (LUAD) progression, but the relationship among inflammation-linked transcriptional heterogeneity, patient survival, and immune-state variation remains incompletely defined. Objective: We aimed to identify inflammation-associated LUAD subtypes, derive a parsimonious survival-stratification signature, and characterize its immune and pathway context across public transcriptomic cohorts. Methods: Expression profiles and clinical data were obtained from TCGA-LUAD, GTEx normal lung, and GEO datasets GSE11969, GSE30219, GSE31210, and GSE40791. A curated set of 596 inflammation-related genes was used for consensus clustering. Differential-expression analysis, functional enrichment, univariate Cox regression, and LASSO-Cox modeling were integrated to construct a gene-expression risk score. The prognostic dataset comprised 730 cases and was randomly divided into training (n=502) and internal-validation (n=228) sets; 85 GSE30219 cases formed an external-validation cohort. Immune-cell enrichment, gene set enrichment analysis (GSEA), gene set variation analysis (GSVA), and pan-cancer analyses were used for biological contextualization. Results: The LUAD-versus-control comparison identified 1,305 differentially expressed genes, including 498 upregulated and 807 downregulated genes. Consensus clustering resolved two inflammation-associated subtypes and 67 subtype-associated genes, of which 64 were higher and 3 were lower in Cluster 1 relative to Cluster 2. Thirty-three genes overlapped between the tumor-control and subtype contrasts. LASSO-Cox regression selected CHRDL1, FDCSP, CXCL13, CYP4B1, and S100P. The 1-, 3-, and 5-year areas under the time-dependent receiver operating characteristic curve were 0.6625, 0.6581, and 0.6658 in the training set; 0.7422, 0.6537, and 0.6761 in internal validation; and 0.6560, 0.6387, and 0.6753 in external validation. Risk groups differed across multiple T-cell, B-cell, natural-killer-cell, myeloid, dendritic-cell, macrophage, and granulocyte signatures. Positive GSEA signals included cell cycle (normalized enrichment score [NES]=2.67; adjusted P=1.42 x 10-), DNA replication (NES=2.52; adjusted P=2.52 x 10-), and mismatch repair (NES=2.20; adjusted P=1.77 x 10-). Conclusions: The five-gene expression score separated LUAD survival groups and captured coordinated proliferative and immune transcriptional states. Its moderate discrimination supports further biological and clinical validation rather than immediate clinical application.

bioinformatics↗

bioRxiv2026

Systematic Benchmarking of AI-Based Molecular Generation Models for Structure-Based Drug Design

Generative artificial intelligence is accelerating molecular design, yet the relative suitability of available models for different targets and stages of preclinical drug discovery remains unclear. Here we benchmarked 12 molecular generation and optimization methods across 176 curated protein-ligand systems spanning diverse therapeutic target classes, with experimentally validated ligands providing reference chemical space. The evaluated methods encompassed pocket-conditioned 3D generation, diffusion and flow-based modeling, autoregressive construction, reference-conditioned optimization and synthesis-aware design. Performance was assessed using operational robustness, chemical validity, uniqueness, molecular and scaffold diversity, quantitative estimate of drug-likeness, synthetic accessibility, docking, physicochemical and ADMET properties, and computational resource requirements. The results revealed architecture-dependent trade off such as receptor-conditioned methods exploited binding-pocket geometry, flow-based approaches enabled efficient sampling, reference-conditioned methods favored analogue generation, and synthesis-aware approaches improved chemical feasibility, but no method consistently optimized all criteria. To address the functional potential of generated molecules, we further developed a state-aware functional classifier (SAFC) that integrates molecular dynamics derived receptor ensembles, ensemble docking and protein ligand interaction graphs. SAFC provided dynamics-aware functional activity rankings for generated molecules that were partly complementary to docking, drug-likeness and synthetic accessibility scores. These findings support hybrid, stage specific deployment of generative models rather than reliance on any single architecture or evaluation metric. This study provides practical guidelines for generative AI based preclinical drug development processes.

bioinformatics↗

bioRxiv2026

Optimized Kakadu Plum Extracts Inhibit Intracellular Oxidative Stress in Canine Small Intestinal Cell Model

Kakadu plum (Terminalia ferdinandiana), an Australian native fruit, is among the richest known dietary sources of vitamin C and hydrolysable tannins, yet its capacity to protect the intestinal epithelium against oxidative stress remains largely unexplored. This study optimised the extraction of bioactive compounds from freeze-dried Kakadu plum powder and evaluated their antioxidant activity using both chemical and cellular antioxidant in vitro assay. Phenolic compounds were extracted using three solvents (water, 80% ethanol, and 80% methanol) combined with shaking, ultrasound, or microwave assistance. Solvent, rather than processing technique, was the dominant determinant of antioxidant capacity: ethanol and methanol maximised total phenolic content, total flavonoid content, and DPPH radical-scavenging activity, whereas water extracts showed the highest ferric-reducing antioxidant power. Twenty-four phenolic compounds identified by HPLC-ESI-QTOF-MS/MS were mapped by network pharmacology to nine core oxidative-stress targets, and cross-species molecular docking predicted conserved binding of key phenolics to canine orthologs of PTGS2 and MMP2. In an H2O2-induced oxidative-stress in vitro cell model using canine small intestinal epithelial cells, both water (less than 25 ug/mL) and ethanol (less than 250 ug/mL) extracts significantly suppressed intracellular reactive oxygen species (ROS) in a dose-dependent manner, with the ethanol extract effective across a wider concentration range. This work demonstrated that Kakadu plum extract could be a promising natural, multi-target antioxidant ingredient for canine intestinal health, and provided a reference for future in vivo research.

biochemistry↗

bioRxiv2026

TGF-β2-induced Snail-mediated EndMT signaling relies on both Smad-dependent and independent pathways

Endothelial-to-mesenchymal transition (EndMT) has become a central mechanism in developmental biology, fibrosis, vascular disease, and cancer. We previously reported on an integrated signaling model in which TGF-{beta}2 induces EndMT through coordinated activation of Smad-dependent and Smad-independent signaling pathways converging on Snail, while GSK-3{beta} regulates Snail activity. We performed a systematic figure-by-figure reproducibility analysis of the original publication. Independent studies published between 2011 and 2026 were identified and curated according to predefined inclusion criteria. Each original experimental conclusion was evaluated for independent confirmation. In parallel, selected biochemical experiments were independently reproduced using newly acquired reagents and contemporary Western blot methodologies. Independent publications consistently reproduced each major mechanistic conclusion of the original study, including activation of Smad, ERK, PI3K/AKT, and p38 MAPK signaling, regulation of Snail expression, EndMT-associated marker switching, and GSK-3{beta}-dependent control of Snail activity. Independent laboratory experiments reproduced the principal biochemical findings using contemporary reagents and experimental workflows. The combined literature analysis and independent laboratory replication demonstrate that the mechanistic framework in our previous study has remained reproducible across multiple laboratories, endothelial cell types, disease models, and fifteen years of investigation. This work illustrates a complementary framework for assessing reproducibility that integrates direct experimental replication with cumulative independent validation.

cell biology↗

bioRxiv2026

A neurofunctional signature of romantic love predicts rewards on social media, effects of oxytocin and drug-cue reactivity

Romantic love is a selective motivational state supporting pair bonding, yet its neural representation and relation to other affiliative-rewarding experiences remain unclear. Across eight fMRI studies (n=420) spanning naturalistic affiliative-reward, pharmacological and addiction-relevant experiments, we developed and evaluated multivariate whole-brain decoders of romantic love and friendship. Both signatures engaged mesocorticolimbic reward systems and the precuneus, yet were dissociable at the whole-brain level and in their recruitment of social-cognitive systems. The love signature generalized to reward on social media, was specific to positive valence, and did not track sweet-taste or monetary reward, indicating a distinct social-affiliative reward representation. Oxytocin selectively increased love - but not friendship - signature reactivity to the romantic partner. In an independent drug-cue-reactivity dataset, the love signature specifically identified heavy cannabis users. These findings establish a dissociable neurofunctional signature of romantic love in conserved bonding circuits that extend to digital affiliation and are co-opted in addiction.

neuroscience↗

bioRxiv2026

RNA m6A demethylase ALKBH4 governs whitefly development

N6-methyladenosine (m6A) modification is the most predominant and ubiquitous internal modification of RNA in eukaryotes, serving as a key post-transcriptional regulator of gene expression that is dynamically modulated by methyltransferases (writers) and demethylases (erasers). However, while the functions of m6A methylases have been partially elucidated in insects, the identity of m6A erasers in arthropods and their chemical catalytic mechanisms, as well as biological functions, remains largely enigmatic. Here, we uncovered 2499 putative methylase genes and 1148 putative demethylase genes in 266 insect genomes, and demonstrated that ALKBH4 functions as an m6A demethylase in the whitefly, Bemisia tabaci, catalyzing the oxidative reversal of mRNA m6A modifications both in vitro and in vivo. Furthermore, we established that ALKBH4, in coordination with other core components of the m6A pathway, fulfills an essential function in regulating the transcript stability of Imaginal Disk Growth Factor 1 (IDGF1) during whitefly development. Collectively, our findings expand the evolutionary scope of the eukaryotic m6A modification system, and reveal a conserved yet insect-specific epitranscriptomic regulatory mechanism governing fundamental physiological processes and adaptive phenotypes. Significance statementThe addition of a methyl group to the N6-position of adenosine (m6A) is a highly abundant chemical modification of RNA. However, the functional role of m6A in insects and the key enzymes that regulate its levels remains poorly understood. In this study, we explored putative methylase genes and demethylase genes in hundreds insect genomes, and identified an m6A RNA demethylase, ALKBH4, in the whitefly, Bemisia tabaci. We demonstrate that ALKBH4 oxidatively reverses mRNA methylation in vivo and in vitro, in combination with other components of the m6A pathway, plays an important role in whitefly development. These findings provide new insight into m6A methylation system of insect.

zoology↗

bioRxiv2026

Molecular and functional characterization of CYP6AN1 orthologs involved in capsaicin metabolism in two Helicoverpa species

The generalist Helicoverpa armigera and the specialist Helicoverpa assulta are closely related noctuid pests and are among the few insect herbivores capable of feeding on and damaging hot pepper fruits, which contain the defensive compound capsaicin. Cytochrome P450 monooxygenases (P450s) contribute to the metabolism of plant defensive compounds and can facilitate insect adaptation to chemically defended host plants. Here, we identified CYP6AN1 in H. assulta (HassCYP6AN1) and comparatively characterized the CYP6AN1 orthologs from H. armigera (HarmCYP6AN1) and H. assulta. RACE identified one full-length HarmCYP6AN1 transcript and three full-length HassCYP6AN1 transcript isoforms. The HassCYP6AN1 isoforms contained distinct 5' UTRs generated by alternative transcription initiation and splicing but shared an identical coding sequence. Sequence comparisons and phylogenetic analysis supported their assignment as orthologs. Constitutive CYP6AN1 expression was higher in the H. assulta midgut, whereas dietary capsaicin significantly induced CYP6AN1 expression in the H. armigera midgut. Recombinant CYP6AN1 proteins were co-expressed with NADPH-cytochrome P450 reductase in Escherichia coli, and their substrate-metabolizing activities were evaluated using HPLC-based depletion assays. Both orthologs metabolized capsaicin, but HarmCYP6AN1 exhibited an approximately 2.3-fold higher depletion activity than HassCYP6AN1 under the conditions tested. HarmCYP6AN1 also showed P450-content-dependent xanthotoxin depletion, whereas no detectable xanthotoxin metabolism was observed for HassCYP6AN1. These findings establish CYP6AN1 as a component of the capsaicin-metabolizing repertoire of both species and reveal substantial divergence between the orthologs in transcript organization, expression regulation, catalytic activity, and detectable substrate range.

zoology↗

bioRxiv2026

Spatium: A Protein Language Foundation Model for Spatial Proteomics

Spatial proteomics provides single-cell protein measurements under highly constrained and heterogeneous protein panels across datasets, resulting in limited and partially overlapping measurement spaces for cellular characterization. Existing analyses predominantly rely on statistical or task-specific modeling, while learning scalable representations of spatial protein data remain underexplored. This gap motivates the need for models that can learn stable representations of cellular identity from constrained protein measurements. Here we introduce Spatium, a protein language foundation model trained on over 51 million cells across multiple spatial proteomics platforms. Spatium learns intrinsic co-expression hierarchies that capture cell identity in a manner robust to panel composition and measurement scale. Spatium builds a generalizable representation of cell states grounded in biologically interpretable protein expression patterns. We demonstrate that Spatium learns biologically meaningful cell representations across multiple downstream tasks. Spatium recovers accurate cell identities with marker expression patterns consistent with known biology and reveals functionally distinct spatial microenvironments characterized by coherent marker enrichment signatures. It further enables reconstruction of missing protein measurements while preserving biologically meaningful expression patterns. Across these analyses, Spatium demonstrates stable and interpretable performance with lightweight task-specific adaptation, highlighting the robustness of the learned representations across diverse biological and experimental contexts.

bioinformatics↗

bioRxiv2026

PFM: perturbed flow matching for structure-based drug design

Generating 3D molecules that bind to specific protein targets via generative models has shown great promise in structure-based drug design. Recently, diffusion-based methods have achieved promising results, but their reliance on high sampling steps poses risks of slowing the drug discovery process due to increased time and computational costs. In this work, we propose a novel method named Perturbed Flow Matching (PFM), which significantly reduces sampling steps by leveraging a Flow Matching framework. PFM introduces a unique perturbed conditional probability path design that incorporates pocket binding site information and atom type-coordinate coupled information to enhance molecular generation performance. Experiments on CrossDocked2020 dataset demonstrate that PFM generates molecules with competitive 3D structures and state-of-the-art (SOTA) binding affinities towards the protein targets, achieving an Avg. of -7.12. Additionally, PFM accelerates the generation of valid molecules by a factor of 21.3, while demonstrating potential for further improvement. The code is available at https://github.com/kurisu92725/PFM.

bioinformatics↗

bioRxiv2026

Hidden assumptions in nascent RNA sequencing pipelines define reproducibility states

Reproducibility of sequencing analyses is often assumed when identical data are processed with established pipelines, yet outcomes can depend on library assumptions that are not explicit to users. Here we compared commonly used pipelines for nascent RNA sequencing. Across public human PRO-seq datasets, identical inputs produced structured divergence in transcriptional profiles. A diagnostic workflow traced this divergence to interactions among paired-end library design, UMI organization, read trimming and alignment strategy. Similar patterns were observed in independently generated human and pig PRO-seq libraries sharing a dual-end UMI design, including divergence associated with pipeline behavior that could not be altered through user-accessible parameters alone. Beyond PRO-seq, GRO-seq analyses showed that assay-specific library architecture and signal-coordinate conventions could distort positional profiles even without UMI processing. In PRO-cap and re-examined PRO-seq datasets, incomplete UMI metadata either prevented pipeline execution or caused silent signal loss; unreported terminal UMIs were detected in four of five examined PRO-seq datasets. Together, these results define reproducibility states shaped by library design, pipeline assumptions and metadata availability.

bioinformatics↗

bioRxiv2026

Systematic Development of a Compact Genome-Editing Tool Leveraging the TAM-Independent DNA Nuclease TasR in Bacillus subtilis

Bacillus subtilis is a core microbial chassis in biomanufacturing, and establishing efficient gene editing technologies is key to engineering this strain. In conventional CRISPR gene editing technologies, the large size of DNA nucleases leads to difficulties in plasmid construction, low transformation efficiency, and cumbersome multi-round editing operations; therefore, developing miniature gene editing tools can effectively address these issues. Although our group previously established a miniature gene editing tool based on IscB in B. subtilis SCK6, IscB relies on the 5'-CAGGAA-3' TAM recognition sequence, and 83.36% of the genes in the SCK6 genome harbor no or only one TAM sequence, indicating a bottleneck of restricted editing for IscB in this strain. The novel miniature DNA nuclease TasR does not require a TAM sequence and can thus compensate for the limitation of IscB; however, the applicability of TasR in B. subtilis remains unknown. Therefore, this study first constructed a single plasmid, pBsuTasR, capable of expressing TasR and its guide RNA (tigRNA), which enabled gene deletion of regular-sized fragments in SCK6 with editing efficiencies of 21.7%- 78.3%. Subsequently, the capacity of TasR to delete a long DNA fragment (169.9 kb) was evaluated, and it was found that under the guidance of a single tigRNA, the deletion efficiency was 21.73%, whereas after optimizing to two tigRNAs, the efficiency increased to 39.13%. Furthermore, the gene integration capability of pBsuTasR was further tested, and TasR was able to integrate the aprN gene into the amyE locus at an efficiency of 13.3% under the guidance of a single tigRNA, and after increasing to two tigRNAs, the integration efficiency increased to 91.3%. In terms of iterative genome editing, this study developed the pBsu-SRP (Scissors-Rock-Paper) iterative editing system, which automatically cures the editing plasmid from the previous round while performing a new round of gene editing, with sequential gene deletion efficiencies of 4.34%-26.08%, and using this system, the editing cycle can be shortened from 4N days by the conventional method to 3N+1 days. Subsequently, the pBsu-SRP system was successfully used to achieve the integration of two and three copies of the mCherry fluorescent reporter gene in SCK6, and it was found that the fluorescence intensity increased with the copy number. Finally, this study also explored the escape of SCK6 from TasR cleavage and found that mutations in the tigRNA sequence are the cause of the escape. In summary, this study constructed a novel miniature genome editing system in B. subtilis using the TAM-independent nuclease TasR as the core component. This system can not only provide an efficient technical tool for genetic manipulation of industrial microorganisms, but also offer new instrumental support for the iterative engineering and functional optimization of chassis cells in biomanufacturing.

molecular biology↗

bioRxiv2026

Driver-independent lexAop-tdTomato.nls reporter signal in the adult Drosophila proventriculus

Reporters are widely used in Drosophila genetics to visualize gene expression and cell lineages. However, uncharacterized limitations in specific reporter lines can lead to data misinterpretation. Here, we identify a consistent, driver-independent tdTomato signal in the adult proventriculus from the widely used lexAop-tdTomato.nls reporter line. This signal was observed across multiple lexA driver combinations and was directly detectable in lexAop-tdTomato.nls responder-alone adult proventriculi lacking any lexA driver and without antibody staining. In contrast, no comparable native red fluorescence was detected in larval proventriculi under the same no-antibody imaging condition. Mouse and rabbit anti-RFP immunostaining further supported the presence of proventriculus-associated tdTomato/RFP antigen in adult responder-alone animals. In larval responder-alone proventriculi, antibody-amplified staining was antibody-source-dependent: a detectable signal was observed only with rabbit anti-RFP, whereas mouse and rat anti-RFP produced no reliable detectable signal under the same staining condition. A driver-matched comparison using lexAop-RFP.nls did not reproduce the proventricular signal, arguing against detectable ectopic activity of the tested lexA driver in this tissue. However, because lexAop-tdTomato.nls and lexAop-RFP.nls differ in reporter/transgene architecture and possibly genomic insertion context, the underlying cause cannot be assigned specifically to the lexAop sequence. Our findings highlight the necessity of including driver-negative and no-antibody controls when using this reporter line in adult Drosophila proventriculus and gut studies.

genetics↗

bioRxiv2026

SALL2 constrains TEAD4 by maintaining repressive chromatin to restrict trophectoderm identity

Embryonic development is marked by the successive restriction of developmental potential and the specification of embryonic and extraembryonic lineages. Yet, how these lineage decisions are established, and how the epigenome is remodelled to promote and restrict cell fate transitions, remains poorly understood. Here, we demonstrate that SALL2 knockdown in primed human pluripotent stem cells (hPSCs) triggers a trophectoderm (TE)-like phenotype, characterized by palisade-like morphology and the up-regulation of TE-associated genes. Mechanistically, SALL2 physically interacts with the key TE driver TEAD4 and maintains bivalent, repressive chromatin (H3K4me3/H3K27me3) at TE-specific loci. Reduced SALL2 led to enhanced TEAD4 occupancy and disrupted H3K27me3 and increased active chromatin marks at TE genes. Importantly, depletion of TEAD4 abolished the TE-like phenotype induced by SALL2 knockdown, demonstrating that TEAD4 is required for the downstream effects of SALL2 loss. In support of this, blastoid-like aggregates can be generated from primed hPSCs with SALL2 knocked down. Together, our findings identify SALL2 as a key epigenetic barrier that restrains TE lineage commitment by limiting TEAD4-dependent activation of the trophoblast transcriptional program. Key findingsO_LISALL2 acts as a molecular barrier to trophectoderm differentiation. C_LIO_LISALL2 suppresses the trophectoderm by maintaining bivalent repressive chromatin at TEAD4-bound loci. C_LIO_LIBlastoid-like structures can be generated from primed-state media when SALL2 was knocked down. C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=91 SRC="FIGDIR/small/737659v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@42cafaorg.highwire.dtl.DTLVardef@11c040borg.highwire.dtl.DTLVardef@4d9ffborg.highwire.dtl.DTLVardef@42546a_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗