Biology subjects

Wang, R.

Publications and source records attributed to Wang, R..

At least 73 records · Page 4Linked to original sources

bioRxiv2026

A motif for domain-specific analysis applets that are easy to learn, reuse, test, and to compose into pipelines: application to vision science

Scientific progress depends on the analysis of primary data, yet the small, domain-specific programs that perform most scientific analyses are typically poorly documented, narrowly tested, and difficult to reuse outside the lab that created them. General-purpose pipeline tools address the problem of running steps in order but do not enforce documentation, testing, or standardized outputs. We describe a motif for building domain-specific analysis applets, which we call calculators, that constrains developer choices in order to produce code that is readable, tested, and reusable almost as a byproduct of following the template. Calculators operate on a typed, searchable database of documents, eliminating the need to explicitly wire inputs and outputs together; instead, each calculator searches the database for documents it can operate on and adds its results as new typed documents. Calculators must provide documentation in a standard location, self-tests that can be run and inspected interactively, adjustable input parameters, a single well-defined output document type, and a default plotting method. Sets of calculators compose naturally into pipelines whose outputs satisfy FAIR principles at every stage. We demonstrate the motif by implementing calculators for common analyses in vision science, including orientation and direction selectivity, contrast tuning, spatial and temporal frequency tuning, speed tuning, and Hartley reverse correlation. These calculators have been used in published work and are in active use across collaborating laboratories. We discuss the design principles of the motif, its advantages and limitations, and its applicability to domain-specific computation across neuroscience and beyond. Significance StatementScientists often must write small programs to analyze their own data. These programs are usually poorly documented, lightly tested, and hard for other labs to reuse. Mistakes in this kind of code have even caused well-known papers to be retracted. We describe a simple pattern for writing these programs, which we call a calculator. The pattern requires the programmer to include clear documentation, built-in tests, adjustable settings, and a standard form of output. Calculators work by searching a shared database for data they know how to handle, so many calculators can be chained together into a pipeline without extra setup. We show how this works by building calculators for common visual neuroscience analyses that other labs are already using.

neuroscience↗

bioRxiv2026

Spatial Multi-Omics Reveals Extracellular Matrix Remodeling and VSMC Phenotypic Switching in Moyamoya Disease

BackgroundMoyamoya disease (MMD) is a progressive cerebrovascular disorder characterized by steno-occlusive lesions and intimal hyperplasia. Although vascular smooth muscle cell (VSMC) phenotypic switching is implicated in its pathogenesis, the precise spatial interplay between extracellular matrix (ECM) remodeling and local metabolic alterations within the distinct vascular microenvironments remains unknown. MethodsSuperficial temporal artery (STA) samples from patients with MMD and controls were analyzed by histology, immunofluorescence, spatial transcriptomics, spatial proteomics, and spatial metabolomics. Single cell RNA sequencing was used to profile the cellular landscape of STA tissues. To functionally validate the identified pathway, human brain vascular smooth muscle cells (HBVSMCs) were stimulated with fibronectin 1 (FN1), and patient derived induced pluripotent stem cell smooth muscle cells (iPSC-SMCs) were generated for migration and protein expression assays following ITGA5 silencing or focal adhesion kinase (FAK) inhibition. ResultsMMD STA samples exhibited marked intimal hyperplasia with medial thinning and intimal accumulation of -SMA positive cells. Spatial transcriptomic and proteomic analyses identified an intimal remodeling program characterized by increased FN1, EFEMP1, fibronectin, ITGA5, and FAK, together with reduced MYH11. FN1 stimulation promoted smooth muscle cell migration, ECM associated protein expression, and FAK phosphorylation, whereas ITGA5 knockdown or FAK inhibition attenuated these effects. Patient derived MMD iPSC-SMCs showed similar abnormalities, including enhanced migration, increased FAK activation, reduced contractile markers, and increased ECM associated proteins. Spatial metabolomics and integrated multi-omics analyses further revealed that these changes were coupled to a metabolically depleted intimal niche enriched for reduced acyl-CoA related metabolites. ConclusionsIntegrated spatial multi-omics identifies coupled ECM remodeling and metabolic alteration in the hyperplastic intima of MMD. Within this context, the FN1-ITGA5-FAK axis emerges as a plausible mediator of smooth muscle remodeling that warrants further validation. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=165 SRC="FIGDIR/small/721225v1_ufig1.gif" ALT="Figure 1"> View larger version (90K): org.highwire.dtl.DTLVardef@3f6e19org.highwire.dtl.DTLVardef@554d49org.highwire.dtl.DTLVardef@451dd9org.highwire.dtl.DTLVardef@1aac1e9_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

Isolation of folate-producing probiotics and its regulatory effects on homocysteine metabolism and gut microbiota composition

BackgroundFolate deficiency is a global nutritional problem associated with multiple adverse health outcomes, including impaired one-carbon metabolism and elevated homocysteine levels (hyperhomocysteinemia). Gut microbiota-mediated folate biosynthesis has emerged as a promising strategy for improving host folate status. This study aimed to isolate folate-producing probiotic strains, clarify their folate synthesis mechanisms, and evaluate their regulatory effects on folate metabolism and gut microbiota in folate-deficient mice. MethodsHigh-throughput cultivation and screening were performed to isolate folate-producing probiotics. Whole-genome sequencing, pathway reconstruction, and metabolite profiling in fermented milk were used to explore folate biosynthesis pathways and potential microbial cross-feeding interactions. A folate-deficient mouse model was established to evaluate the effects of a probiotic cocktail on serum folate, homocysteine (Hcy) levels, and gut microbiota composition using microbiological assays, biochemical analyses, qPCR, 16S rRNA gene sequencing, alpha diversity analysis, principal coordinates analysis (PCoA), and Linear discriminant analysis Effect Size (LEfSe) analysis. ResultsOver 1,000 bacterial isolates were obtained, and over 10 strains, mainly belonging to Lactobacillus, Bifidobacterium, and Bacillus, showed folate production levels above 100 ng/mL. Genomic analysis revealed that most selected probiotic strains lacked genes involved in para-aminobenzoic acid (pABA) biosynthesis but retained downstream folate synthesis modules, suggesting a potential dependence on pABA-producing gut commensals for precursor supply through microbial cross-feeding. In fermented milk, probiotic strains mainly produced bioactive folates (5-MeTHF and THF), with strain-specific production capacities; L. plantarum, W. coagulans, and B. animalis subsp. lactis significantly increased 5-MeTHF levels in fermented milk. In vivo, high-dose probiotic intervention significantly elevated serum folate (p<0.01) and reduced Hcy (p<0.05) in folate-deficient mice, while medium-dose intervention showed no significant effects. The probiotic strains colonized the mouse gut in a dose-dependent manner: high-dose group exhibited >4,000-fold increase in relative abundance (Bifidobacteriaceae and Bacillaceae enriched), medium-dose group only enriched Bacillaceae, and low-dose group showed no effective colonization. High dose probiotic treatment enhanced gut microbial species diversity (increased Shannon index) and restored folate deficiency-induced gut microbiota dysbiosis (PCoA clustering closer to normal group). ConclusionThis study screened high folate-producing probiotic strains and demonstrated their ability to synthesize active 5-MeTHF, which may rely on microbial cross-feeding in gut microbiota. Furthermore, we demonstrated that folate-producing probiotic intervention significantly improves folate status and Hcy metabolism and restores gut microbiota homeostasis in folate-deficient mice. These findings suggensted that such probiotics could serve as a safer, more physiological intervention for folate deficiency and hyperhomocysteinemia, especially in populations with MTHFR polymorphisms.

microbiology↗

bioRxiv2026

Dissecting the molecular triggers of early and late long-term potentiation

The brain stores information by changing the strength of its synapses, a process that has at least two phases: Late long-term potentiation (L-LTP) is thought to result from the consolidation of early LTP (E-LTP), just as long-term memory requires the prior establishment of short-term memory. Recently, inhibitory avoidance experiments under CaMKII inhibition have challenged this notion, demonstrating long-term fear memory without measurable short-term memory. Here we use optogenetic activation and inhibition of CaMKII during induction of spike-timing-dependent potentiation (tLTP) to dissect the signaling pathways. While CaMKII activation in CA1 neurons was sufficient to induce E-LTP, growth of the postsynaptic density and spine neck expansion, we found that CaMKII-induced LTP does not give rise to L-LTP. Conversely, inhibition of CaMKII during tLTP induction prevented E-LTP, but FOS and L-LTP were still expressed, driven by CaMKK and PKM{zeta}. Thus, both long-term memory and L-LTP form in the absence of CaMKII activation.

neuroscience↗

bioRxiv2026

Cholesterol-dependent lysosomal docking of mTORC1 mediated by TM6SF1

The Transmembrane 6 Superfamily (TM6SF) comprises two members: TM6SF1, a ubiquitously expressed lysosomal membrane protein of unknown function, and TM6SF2, an endoplasmic reticulum protein required for bulk lipidation of Apolipoprotein B-containing lipoproteins. Here we used cryo-electron microscopy (cryo-EM) to determine the structure of human TM6SF1 at 2.9- [A] resolution. TM6SF1 forms a polytopic homodimer, with each protomer comprising ten transmembrane helices (TMs). TMs 1-6 form a pocket that accommodates a cholesterol molecule. Cell-based assays revealed that loss of TM6SF1 perturbs mTORC1 signaling, resulting in reduced phosphorylation of S6 kinase 1 and 4E-BP1 and constitutive activation of Transcription Factor EB (TFEB) and that cholesterol is required for these effects. Biochemical analyses support the model that TM6SF1 directly engages LAMTOR1, a component of Ragulator complex, in a cholesterol-dependent manner. Together, these findings identify TM6SF1 as a lysosomal cholesterol binding protein involved in regulating mTORC1 signaling. Significance StatementWe determine the cryo-EM structure of TM6SF1 and show that it is a lysosomal membrane protein that associates with LAMTOR1, a component of Ragulator complex, in a cholesterol-dependent manner. Loss of TM6SF1 impairs mTORC1 signaling and promotes nuclear accumulation of TFEB, suggesting a role for TM6SF1 in lysosome-dependent nutrient sensing and signaling. Together, our findings suggest that TM6SF1 is involved in the regulation of mTORC1 activity and provide insight into the functional diversification of the TM6SF protein family.

cell biology↗

bioRxiv2026

AINN-P1: A Compact Sequence-Only Protein Language Model Achieves Competitive Fitness Prediction on ProteinGym

Protein language models (PLMs) are increasingly central to protein engineering and drug discovery. Many high-performing systems, however, rely on large parameter counts, multiple sequence alignments (MSAs), explicit structural inputs, or computationally intensive attention mechanisms, limiting their accessibility and throughput. Here we present AINN-P1, a 167M-parameter protein language model trained exclusively on raw UniRef amino-acid sequences using an autoregressive next-token prediction objective. AINN-P1 employs a multiplicative LSTM (mLSTM) architecture--an attention-free, recurrent design that scales linearly with sequence length and avoids growing key-value caches during inference. We evaluate AINN-P1 on ProteinGym fitness prediction tasks spanning activity, binding, expression, and stability using a frozen-encoder protocol with lightweight few-shot regression heads. Under this protocol, AINN-P1 achieves an average Spearman{rho} of 0.441 across four task categories and a Spearman{rho} of 0.625 on stability--the highest among sequence-only models in our comparison set. Because our evaluation uses few-shot supervised regression rather than the zero-shot scoring employed by most ProteinGym leaderboard baselines, direct numerical comparison requires caution; we discuss this methodological distinction throughout. Beyond benchmark performance, AINN-P1 emphasizes practical deployability: its recurrent architecture avoids quadratic memory scaling, supports fixed-state inference on long sequences, and enables rapid adaptation through frozen embeddings rather than costly end-to-end fine-tuning. We discuss when sequence-only models are sufficient when structural information remains beneficial and how compact foundation models can serve as efficient front-end filters in drug discovery workflows.

bioinformatics↗

bioRxiv2026

Endotoxemia and TLR4 via tissue resident macrophages triggers anemia in mouse model of colitis

Anemia is one of the most debilitating and frequent complication of inflammatory bowel diseases (IBD) and is often treated with iron supplementation, which has limited efficacy and causes additional co-morbidities. Damaged intestinal barrier function is a hallmark of IBD and causes the translocation of endotoxins from gut bacteria into the bloodstream. A previous study in mice reported that endotoxins suppress erythropoiesis by reprogramming erythroblastic island macrophages (EBI M{varphi}). Here, we show that IBD patients and mice with acute colitis developed endotoxemia associated with anemia. Endotoxemia in IBD patients was negatively correlated with blood erythrocyte counts. In line with this, mice with acute colitis caused by drinking water containing dextrin sodium sulphate (DSS) had endotoxemia together with anemia characterized by reduced red blood cell counts, hemoglobin content and hematocrit, and reduced medullary erythropoiesis which was in part compensated by increased extramedullary erythropoiesis. As the endotoxin receptor TLR4 is expressed by CD169+ gut-resident macrophages as well as erythroid island macrophages in the bone marrow, we tested the hypothesis that TLR4 expressed by these CD169+ macrophages mediate both inflammatory colitis and anemia. Indeed, mice with a conditional deletion of the Tlr4 gene specifically in CD169+ tissue-resident macrophages were protected from DSS-induced anemia, inflammation and colitis. In addition, treatment with the TLR4 inhibitor C34 abated inflammation and anemia in DSS mice. These results suggest that endotoxins leaking from the inflamed gut may play a crucial role in IBD and associated anemia via CD169+ tissue-resident macrophages and that drugs targeting TLR4 may protect against IBD-associated anemia.

immunology↗

bioRxiv2026

A generalized life-motion mechanism supports invariant directional coding of local biological kinematics in humans

Humans can detect biological motion (BM) from sparse local kinematic cues, yet whether the visual system encodes directional information in a category-invariant manner remains unresolved. Here we combined a visual adaptation paradigm with computational modelling to reveal direction-sensitive neural mechanisms specialized for local biological kinematics. Adapting to a side-view scrambled point-light walker produced a robust repulsive aftereffect in the perceived direction of an intact human walker near the frontal view. Notably, this aftereffect generalized across different terrestrial vertebrates (pigeon, cat, dog) and across various actions (running, crawling, cycling), demonstrating a high degree of kinematic invariance. Crucially, the effect disappeared when biological kinematics were disrupted (inversion or removal of gravitational acceleration cues) or when the test stimulus was replaced with non-biological object motion. Individuals direction-discrimination abilities were also highly correlated across diverse local BM patterns, indicating a shared underlying mechanism. Drift-diffusion modeling further revealed that adaptation primarily altered the efficiency of sensory evidence accumulation rather than decision-level processes, and individual drift-rate changes strongly predicted the magnitude of perceptual aftereffects. These findings provide compelling evidence for a generalized, direction-sensitive neural system tuned to local biological kinematics, extending the life-motion detector theory and revealing a fundamental principle of biological motion perception. Significance StatementHumans possess an exceptional ability to detect and interpret the movements of living beings--an ability fundamental to survival, social interaction, and adaptive behavior. But how does the visual system extract "life motion" so adeptly amidst the complexity of natural scenes? Using visual adaptation and computational modelling, we provide direct evidence for direction-sensitive neural mechanisms specialized for local biological kinematics. These mechanisms operate robustly across species and actions, and remain selective for natural biological dynamics. Our findings advance the life-motion detector theory by demonstrating that the human visual system encodes directional information in a highly invariant manner, revealing a fundamental computational strategy for detecting animate agents.

neuroscience↗

bioRxiv2026

Single cell analysis of neonatal naïve CD8α+ T cells reveals novel subsets bridging the innate-adaptive spectrum

There is growing evidence that neonates harbor innate-like CD8a+ T cell subsets that contribute to both protection and hyper-inflammatory states. It remains unclear, however, where these innate-like features are found among the many conventional and unconventional T cell populations that can upregulate the CD8 receptor. Further delineation of these unique populations and functions, with a focus on CD8ab co-expression, will enable studies that seek to understand the unique immune features in conventional T cell populations that are present during fetal and early postnatal life. We used cord blood from infants across the full viable gestational age range to examine phenotypic and transcriptional heterogeneity, with a particular focus on the naive T cell pool. We report a set of fetally-derived and innate-like naive CD8{beta}+ T cells ( FITs) that are marked by their KLRG1+CD161+ phenotype, unique transcriptomic features and which are sparsely detected in adult peripheral blood. Additionally, using T cell receptor repertoire profiling, we can distinguish FITs from well-described and semi-invariant unconventional T cell populations such as mucosa-associated invariant T cells. Our delineation of FITs unique features will enable future investigation into their ontogeny and tissue distribution, and ultimately their role in immune-related outcomes in preterm infants.

immunology↗

bioRxiv2026

Cross hybridization Inference for Phylogenetic Resolution (CIPHR)-FISH enables microbiome imaging with strain level taxonomic resolution

The spatial organization of microbial communities is a critical determinant of host-microbe interactions, yet species-level mapping remains challenging due to high 16S rRNA sequence homology and spectral crosstalk in multiplexed fluorescence in situ hybridization (FISH). To address this challenge, we developed Cross-hybridization Inference for Phylogenetic Resolution (CIPHR)-FISH, a pipeline that integrates strategic probe design with supervised machine learning. CIPHR-FISH transforms probe cross-hybridization and spectral overlap, traditionally viewed as experimental noise, into informative molecular signatures. Using a gnotobiotic zebrafish model colonized with a defined mix of 10 zebrafish bacterial strains, we trained a support vector machine (SVM) on empirical hybridization patterns from pure bacterial cultures. CIPHR-FISH achieved 99.2 % macro-averaged accuracy, significantly outperforming standard linear unmixing (62.5 %), and successfully discriminated strains with 99.7% sequence homology. Applying this tool to gnotobiotic zebrafish larvae revealed distinct biogeographies: the intestinal bulb hosted highly structured, multi-layered polymicrobial aggregates, while the skin exhibited sparse, uniformly dispersed individual bacterial cells. Notably, we observed significant inter-individual variation in spatial community structure that was obscured by traditional bulk 16S rRNA sequencing. CIPHR-FISH provides a robust, scalable framework for high-resolution spatial biology by converting the limitations of molecular labeling into a rich data source for taxonomic classification. This approach enables the quantification of micro-scale ecological and stochastic forces that shape the microbiome across hosts.

microbiology↗

bioRxiv2026

Geometric-aware and interpretable deep learning for single-cell batch correction via explicit disentanglement and optimal transport

Single-cell RNA sequencing enables high-resolution characterization of cellular heterogeneity, yet integrating datasets from diverse sources remains challenging due to batch effects. Current methods rely on implicit feature disentanglement and and lack geometric constraints, often result in under-correction, over-correction, or compromised biological fidelity. Here, we present iDLC, an interpretable deep learning framework that performs dual-level correction through explicit feature disentanglement and optimal transport-regularized adversarial alignment. iDLC separates biological and technical components within a structured latent space, then leverages high-confidence mutual nearest neighbor pairs to guide geometrically constrained distribution alignment. Systematic evaluation across pancreatic cancer datasets with varying batch effect intensities, multi-source human immune cells, and large-scale cross-species atlases demonstrates that iDLC robustly eliminates complex batch effects while preserving fine-grained cell subtypes, continuous developmental trajectories, and rare populations. The framework scales efficiently to datasets exceeding one million cells and consistently outperforms existing methods in both batch correction and biological conservation metrics. iDLC provides a principled and reliable tool for constructing unified single-cell reference atlases across diverse experimental conditions and biological systems.

bioinformatics↗

bioRxiv2026

BEEP Learning: Multi-View Image Decomposition for Massively Multiplexed Biological Fluorescence Microscopy

Fluorescence imaging with spectrally variant fluorophores allows the spatial mapping of biological structures with exquisite cellular and molecular specificity. However, the ability to robustly discriminate multiple fluorophores in any single imaging experiment is greatly hindered by the broad emission spectra of bio-compatible fluorophores and the large contribution of noise in low-energy regime fluorescence microscopy. In this study, we propose a novel machine learning framework, Bleaching-Excitation-Emission Photodynamics (BEEP) learning, that exploits multiple discriminatory features of fluorescent dyes to greatly expand the number of distinguishable objects in an image by integrating emission spectra, excitation variability, and bleaching dynamics into a unified multi-view, fluorescence unmixing approach. Our method is built upon a rank-one-tensor-based generalized linear model and leverages two biophysically grounded assumptions: consistent spectral and bleaching behaviors under fixed excitation, and invariant fluorophore abundances across excitations. We first extract excitation-specific spectral and bleaching signatures from reference images, and then use them to estimate abundances in complex mixtures. Experimental results on both simulated and real images of microbial populations demonstrate that our approach significantly outperforms conventional and partially multi-view methods, offering improved robustness and accuracy in highly multiplexed fluorescence imaging.

biophysics↗

bioRxiv2026

Komagataella phaffii encodes two functional Pho4 transcription factors

The transcription factor Pho4 is crucial for the response to phosphate starvation in many fungi, and it has been linked to tolerance to alkalinization of the medium and to pathogenicity. It is widely accepted that it is encoded by a single gene. However, the industrially relevant yeast Komagataella phaffii might contain two Pho4-encoding genes (PAS_chr1-1_0265 and PAS_chr2-1_0177, designated here PHO4(A) and PHO4(B), respectively), which have never been functionally characterized. The phenotypic analysis of single and double mutants suggests that Pho4(B) plays a major role in the adaptation to Pi scarcity. While single mutants exhibited limited and non-overlapping phenotypic defects, the pho4(A) pho4(B) strain was sensitive to multiple types of stress, including phosphate starvation and alkaline pH. Transcriptomic analysis confirms that Pho4(B) is crucial for the transcriptional response to phosphate starvation, including induction of typical gene markers (PHO5, PHO89, VTC1, etc.). However, by using a GFP reporter we found that PHO4(A) also participates in the induction of PHO89 under high pH stress. Expression of both PHO4(A) and PHO4(B) in S. cerevisiae complemented the pho4 mutation under phosphate limitation by restoring growth, expression of the Pho84 transporter and secreted phosphatase activity. These results indicate that both transcription factors display partially overlapping functions, responding differently to diverse stimuli, and that together they constitute a key component in the adaptation to a variety of stresses. Therefore, K. phaffii is an exceptional example among fungi that encodes two Pho4 functional transcription factors.

molecular biology↗

bioRxiv2026

A Multimodal Single-Cell Epigenomic and 3D Genome Atlas of the Human Basal Ganglia

The basal ganglia (BG) underlie motor control, reward processing, and many neurological and psychiatric disorders, but a comprehensive epigenomic and 3D-genome atlas of the human BG is lacking. Here we present a multimodal single-cell atlas profiling DNA methylation and 3D chromatin conformation in 261,331 nuclei (snm3C-seq) across eight subregions, resolving 12 classes, 31 subclasses, and 59 groups. Harmonized under the HMBA basal-ganglia consensus taxonomy, this atlas integrates with matched RNA, ATAC-seq, and histone-modification data across five regulatory layers. We identify millions of cell-type- and region-specific differentially methylated regions enriched for distinct transcription factor motifs and link them to disease-associated heritability. Neuron-specific loops dominate cell-type-specific 3D contact remodeling, while most non-neuron-specific loops are constitutive. Among spiny projection neurons (SPNs), chromatin loops, rather than TAD boundaries, distinguish D1, D2, and eccentric SPN subclasses, with eccentric SPNs showing the most loop-level reorganization among the three. We characterize STR D2 SMYD2-HTR7 SPN, a newly recognized POU6F2 D2-SPN subtype, and reveal region-specific methylation and contact gradients of disease-associated genes, including CADM1 and PDE8B. Integrative gene-regulatory networks reconstruct cell-type-resolved enhancer-promoter links to interpret Parkinsons disease risk variants at SNCA. Finally, MERFISH spatial profiling combined with cross-species Patch-seq identifies non-SPN neuronal subtypes, including a MOXD1 striosomal STR FS PTHLH-PVALB GABA subtype with distinct electrophysiology, partitioning across the striatal matrix-striosome boundary. HighlightsO_LIA multimodal single-cell atlas maps DNA methylation and 3D genome architecture across human basal ganglia cell types and subregions. C_LIO_LINeuron-specific loops dominate cell-type-specific 3D contact remodeling in the human BG, whereas most non-neuron-specific loops are constitutive. C_LIO_LISpiny Projection Neuron (SPN) subtypes exhibit regionally organized epigenomic and 3D genome signatures that align with dorsal-ventral identities. C_LIO_LIChromatin loops are the primary distinguishing feature among D1, D2, and eccentric SPN subclasses, with eccentric SPNs being the most 3D-reorganized. C_LIO_LIIntegrated regulatory maps link cell-type-specific enhancers to disease-associated genetic risk in the human basal ganglia. C_LIO_LINon-SPN interneurons differ in distribution and in transcriptional and epigenetic identity across the matrix-striosome boundary. C_LI

neuroscience↗

bioRxiv2026

Optimization of Agrobacterium-mediated transformation of commercial heirloom tomato cultivars to develop novel traits via CRISPR/Cas9 Genome Editing

Genetic improvement using new genome editing approaches rely on the efficient delivery of the CRISPR/Cas system in the vegetable crop tomato. Previous protocols for tomato transformation have primarily focused on a handful of cultivars (M82, Alisa Craig, Microtom, Sweet-100) with very little commercial relevance, and it is not clear if these protocols can be implemented directly in other commercially relevant varieties. Heirloom tomatoes are sought for their deep and diverse flavor but have not been subjected to systematic crop improvement via conventional breeding or biotechnology approaches such as transgenesis or genome editing. Therefore, we tested the transformation and regeneration capacity of six different heirloom cultivars known for their superior taste and market relevance in the US. Subsequently, we optimized rooting conditions and used the GRF4-GIF1 chimeric developmental regulator to successfully recover transgenic plants. Finally, we evaluated the efficiency of targeted genetic modification using the CRISPR/Cas9 genome editing system in several of these cultivars. We demonstrate that our optimizations led to successful transformation of several heirloom varieties, including the generation of edited plants for target genes modifying plant architecture and flowering time. Our results set the foundation for a biotechnology platform to deliver improved traits to local and regional heirloom varieties using genome editing.

plant biology↗

bioRxiv2026

Computational modeling of head direction cells in three-dimensional space: directional encoding and visual cue manipulation

Head direction (HD) cells can fire selectively as a function of the animals head azimuth direction and form an internal compass for navigation. They were found in the mammalian limbic system including the dorsal presubiculum and entorhinal cortex. The underlying network updates its directional estimate in a self-organized fashion and can be recalibrated by external sensory cues. Although ring-attractor models were proposed to account for azimuth coding on horizontal planes, they cannot explain conjunctive azimuth-and-pitch tuning observed in HD cells of the presubiculum of flying bats navigating in three-dimensional (3-D) space. Based on the 3-D electrophysiological recordings, we developed a toroidal continuous attractor network that jointly encodes horizontal azimuth and vertical pitch angle of head direction. The model can reproduce the experimentally recorded tuning curves of individual HD cells, and accurately encode the 3-D dynamic head direction of bat by HD cell population. The model also simulate the influence of horizontal visual cue manipulation on the HD system in 3-D space and predicts how horizontal landmark rotation induces a sustained azimuthal offset that persists after the cue is removed, which is comparable to two-dimensional experimental findings. This research clarifies how conjunctive 3-D direction codes are generated and modified by vestibular input, visual information and recurrent connectivity. It also uncovers the computational principles and properties of the brains navigation functions in realistic 3-D environments and offers new theoretical reference for future studies. Author summaryA central function of the brains navigation system is to track head direction, which in terrestrial mammals is largely confined to a horizontal plane. However, for animals like bats that navigate freely in three-dimensional (3-D) space, the neural code for head direction has been found to be high-dimensional. While ring attractor network models elegantly explain horizontal azimuth coding, how the 3-D head direction code is formed and affected by sensory information remains unknown. Here, we develop a toroidal continuous attractor network model with vestibular and visual modules that explains the jointly encoding of azimuth and pitch angles, and the effect of visual cue. We introduce the toroidal topology to the continuous attractor network, and the high-dimensional angular velocity signal from vestibular system and visual input are used to update the population dynamics of the network. Our model is constrained by and reproduces 3-D electrophysiological data from flying bats, captures the unique tuning curves of individual head direction cells, and further achieves the accurate encoding of dynamic 3-D head movements by population activity. Evidences in the rodent have suggested visual cue manipulation recalibrates head direction coding horizontally. Our model further successfully simulates the influence of visual cue rotation in 3-D space, predicting a persistent, global offset in the azimuth encoding--an effect that endures after cue removal and aligns with 2-D rodent experimental phenomena. This work provides a mechanistic, network-level explanation for 3-D head direction encoding and reveals how multimodal cues are integrated to form the internal compass in a volumetric world.

neuroscience↗

bioRxiv2026

Dysregulation of xenobiotic metabolism and mitochondrial dysfunction exacerbate acetaminophen-induced hepatotoxicity in human antigen R-deficient male mice

Acetaminophen (APAP) overdose is a leading cause of acute liver failure worldwide. The RNA-binding protein Human antigen R (HuR) is a multifunctional post-transcriptional regulator that plays a pivotal role in cellular stress responses, including those triggered by APAP toxicity. This study investigated the mechanisms by which HuR protects against APAP-induced hepatotoxicity in male mice. Hepatocyte-specific HuR-deficient (HuRHep-/-) male mice on a C57BL/6N background and wild-type (WT) littermates were treated with 200 mg/kg APAP, and liver tissues were collected at 2, 6, and 24 hours post-treatment. APAP administration increased hepatic HuR mRNA expression and induced HuR cleavage and the formation of a higher-molecular weight HuR-immunoreactive band, with the latter two correlating with injury severity. Compared with WT controls, HuRHep-/- mice exhibited markedly increased susceptibility to hepatotoxicity at both 2 and 6 hours. Metabolite profiling revealed altered APAP metabolism and reduced glutathione S-transferase (Gst) expression in HuRHep-/- livers, consistent with impaired APAP detoxification and increased APAP-protein adduct formation. Fourier-transform infrared (FTIR) spectroscopy further identified early biochemical differences between WT and HuRHep-/- livers as early as 2 hours after APAP exposure. Additionally, HuR deficiency resulted in pronounced mitochondrial structural abnormalities and dysfunction at 2 and 6 hours, accompanied by reduced expression of the mitochondrial fission and fusion proteins Drp1 and Mfn2, increased mitochondrial protein release, and enhanced hepatocyte death. Although pro-inflammatory cytokine levels were elevated in HuRHep-/- mice relative to WT controls at 24 hours, hepatocyte proliferation was similarly blunted in both genotypes, consistent with severe liver injury and delayed recovery. Collectively, these findings identify hepatocyte HuR as a critical regulator of xenobiotic metabolism and mitochondrial integrity and establish its essential role in early protection against APAP-induced hepatotoxicity in male mice.

pharmacology and toxicology↗

bioRxiv2026

Distinct allosteric remodeling of HIV-1 Env dynamics on virions by gp41-directed antibodies reveals two modes of neutralization

HIV-1 envelope glycoprotein (Env), a gp120-gp41 trimer, undergoes coordinated conformational changes that drive membrane fusion and allow immune evasion by transiently concealing neutralization-sensitive epitopes. Most broadly neutralizing antibodies (bNAbs) target gp120, whereas a distinct subset recognizes conserved gp41 regions, such as the fusion peptide and the membrane-proximal external region; however, their impact on Env dynamics and associated neutralization mechanisms remains unclear. Using bioorthogonal tagging for single-molecule FRET, we monitored real-time bNAb-induced conformational sampling of Env on intact virions. Most gp41-directed bNAbs allosterically stabilized the prefusion-closed (PC) state, whereas the bivalent 10E8.4/iMab favored both PC and CD4-bound open (predominant) states. Antibodies redistributed the conformational populations of Env with modest kinetic effects, preserving the sequential transition pathway. These findings reveal two modes of neutralization for gp41-directed antibodies: fixing the prefusion-closed conformation and opening it, in both cases via long-range allosteric control of Env dynamics.

microbiology↗