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Hou, Y.

Publications and source records attributed to Hou, Y..

At least 19 recordsLinked to original sources

Pair-complete structural gating enables Pareto optimization of de novo cyclic peptides with preserved binding geometry and improved developability

Cyclic peptides can engage extended protein interfaces, but sequence changes that improve developability often disrupt the selected target-bound geometry. Existing property-guided design methods lack a principled way to preserve this geometry during local multiproperty optimization. Here we present RF-PepTune, which separates structural eligibility from property prioritization. Before any property score is queried, RF-PepTune evaluates single substitutions and all position-distinct pairs induced by admitted substitutions to build a parent-specific, pair-complete admission graph. Pareto Monte Carlo tree search then optimizes predicted permeability, solubility, non-fouling, and low-haemolysis scores exclusively within this graph, and selected sequences undergo full structural re-evaluation. In a matched three-arm comparison of 334 parents across MDM2, GABARAP, and MCL1, joint property-structure success rose from 10.2% without admission to 51.5% with single-substitution admission and 77.5% with pair-complete admission; pair-complete gating improved success by 26.0 percentage points over single-substitution gating (95% CI, 20.7-31.4). Property-positive but structure-failing endpoints fell from 88.3% to 9.3%. In a separate target-balanced set, all 90 prioritized outputs improved all four model-native scores while satisfying prespecified structural criteria. This work establishes pairwise structural gating as a general strategy for constrained multi-objective molecular optimization.

bioinformatics↗

Loss of DNA Demethylase Enhances Arsenic Resistance Via Reducing of PIN2 Antisense Long Noncoding RNA

DNA methylation dynamics regulate diverse plant stress responses, but the mechanisms governing arsenic (As) tolerance through epigenetic pathways remain largely unknown. Here we report that Arabidopsis mutants lacking the DNA demethylase, REPRESSOR OF SILENCING (ROS1), show substantially enhanced As resistance. Integrating transcriptome and methylome data, we found that PIN-FORMED 2 (PIN2), encoding an auxin efflux carrier that also transports As out of cells, represents a key ROS1 target. In ros1, we observed increased methylation in the last exon of PIN2, a region functioning as the promoter for an antisense long non-coding RNA (lncRNA). Hypermethylation of the promoter suppresses the antisense lncRNA, which follows reduction of sense PIN2 transcription. As a result, PIN2 expression increases in ros1 mutants during As exposure, enhancing As tolerance. Analysis of ros1 pin2 double mutants confirmed that PIN2 acts downstream of ROS1 in As tolerance. Our study demonstrates an epigenetic pathway in which ROS1 regulates As tolerance by controlling PIN2 expression through antisense lncRNA-mediated transcriptional interference, offering new epigenetic strategies using plants in heavy metal contaminated environments.

plant biology↗

LucaCell: a sequence-centric foundation model for cross-species single-cell analysis

Single-cell foundation models have transformed transcriptomic analysis, yet most rely on fixed gene identifiers that limit transfer across species and data types. Here we present LucaCell, a sequence-centric foundation model that represents genes through pre-trained mRNA sequence embeddings rather than static gene annotations. Gene expression is discretized into bins and modeled with a Transformer encoder, enabling sequence-informed cell representation without a fixed gene-ID vocabulary. Pre-training on 85 million human and mouse single cells, LucaCell is evaluated on human, mouse and lemur gene expression profiles, human chromatin accessibility data, unaligned reads from more than 50 prokaryotic taxa, and five influenza A virus genomes. LucaCell enables manual-mapping-free cross-species cell type annotation and an alignment-free microbial embedding framework that simultaneously distinguishes bacterial species identity and intra-species physiological states. It also improves gene expression reconstruction by incorporating donor-specific exonic SNP information into mRNA sequence embeddings, and predicts cellular viral load across influenza A virus strains while highlighting infection-like transcriptional states in mock-infected cells. These results show that sequence-informed gene representation can improve the generalization of single-cell foundation models across species, data types, and predictive tasks.

bioinformatics↗

BioIMA: a one-click desktop tool for standardized extraction of phenotypic traits from biological images

Standardized extraction of quantitative phenotypes from images is increasingly important across plant biology, from ecological and evolutionary studies to genetics, breeding, and functional genomics. However, as large image datasets are increasingly used for trait analysis, many biologically relevant traits, including size, shape, color, and spatial patterning, are still measured manually or using fragmented semi-automated workflows. These limitations reduce throughput, reproducibility, and accessibility, especially for researchers without computational expertise. Here, we present BioIMA, an open-source desktop tool for rapid and standardized phenotyping from biological images. BioIMA integrates foundation model-based segmentation with automated trait computation, allowing users to extract quantitative measurements from images through an intuitive graphical interface and without model training. To validate its performance, we quantified a set of knot morphological traits in two Populus species, as these measurements are typically time-consuming to perform manually. Automatic measurements showed strong agreement with manual ImageJ-based measurements (R2 > 0.95), while reducing per-image processing time by approximately 75% (from ~15 s to ~4 s). BioIMA was further applied to diverse plant datasets, including Helianthus and Rhododendron images with varying morphologies and background conditions. Although developed for plant phenotyping, BioIMA may also be extended to other biological samples where region-based size, shape, or color traits are of interest. By combining accessibility and standardization in a lightweight local application, BioIMA provides a practical community resource for image-based phenotyping in ecological and evolutionary studies.

bioinformatics↗

An Intronic SINE at Pou5f1 Links Hormone Signaling to Blastocyst Hatching

Before implantation, mammalian embryos must escape from the zona pellucida, a protective glycoprotein coat that surrounds the blastocyst. This process, known as hatching, is essential for uterine attachment and has been viewed largely as a mechanical consequence of blastocyst expansion and zona weakening. Whether hatching is actively timed by embryo-intrinsic gene regulation remains unclear. Here we show that timely hatching of mouse embryos requires signal-responsive repression of Pou5f1/OCT4 in the trophectoderm by a single intronic B2 short interspersed nuclear element. Deleting this element preserves blastocyst formation and stem-cell competence, but disrupts trophectodermal OCT4 repression, delays zona escape, causes hatching-uterine receptivity mismatch, perturbs implantation-site organization and reduces peri-implantation fitness. CRISPR activation screening, siRNA and pharmacological perturbation, and defined progesterone/estradiol/EGF culture conditions identify an ESRRA-linked endocrine/growth-factor response that requires the B2 element to consolidate trophectoderm maturation. Comparative analyses further show that young intronic SINEs are enriched in developmental gene programs, whereas human POU5F1 intronic Alu elements exhibit genetic constraint and repressive potential. These findings identify intronic SINEs as molecular entry points that couple extracellular cues to lineage-restricted transcriptional control and morphogenic transition.

developmental biology↗

PAM-DB: Revealing Protein Activation Mechanisms for Next-Generation Rational Drug Discovery

Current rational drug design relies predominantly on computational (CADD/AIDD) methods that model binding thermodynamics and static conformations of target proteins, primarily in their inactive states. However, the kinetic parameters that govern experimental efficacy-such as catalytic turnover and signaling potency-are determined by molecular interactions with transition states (TS), intermediate states (IS), and the entire continuum of conformations along the least free-energy activation pathway. The absence of this dynamic dimension has fundamentally limited the predictive power and success rate of conventional structure-based approaches. Here, we present a structural database that systematically maps the complete activation trajectories of pharmaceutically relevant targets, encompassing TS, IS, and all connecting conformational ensembles. This resource offers multiple strategic advantages for drug discovery: enabling rational targeting of previously "undruggable" proteins, facilitating biased agonism/antagonism design, revealing cryptic allosteric sites in inactive conformations, identifying novel transient pockets along the activation route, rationalizing the mechanisms of existing drugs, predicting mutational effects on activation barriers, and prospectively forecasting drug resistance and off-target liabilities. We demonstrate the utility of this database through representative case studies and provide implementation guidelines for integration into existing discovery pipelines. More detailed information can be found at our website: https://www.momedpamdb.com/en.

biophysics↗

Port of Protein-Protein Interactomes: An experiment-based protein-protein interactome database for rice

Protein-protein interactions (PPIs) play a crucial role in enabling proteins to carry out their functions within various biological processes (Hui et al., 2003). Since the introduction of the yeast two-hybrid (Y2H) method for PPI detection in 1989 (Fields and Song, 1989), the identification of PPIs has become a significant focus in modern biological research. PPI goes beyond examining individual proteins, allowing researchers to establish a comprehensive network that regulates biological processes. Rice, as a key model organism in plant biological studies, has been at the forefront of PPI research. In 2008, prominent rice scientists in China called for concerted efforts to define a comprehensive protein-protein interaction network experimentally, which aimed to facilitate the prediction of the functional mechanisms operating throughout a plants lifecycle (Zhang et al., 2008). With efforts for 2 decades, the experimentally identified rice PPIs have reached over ten thousand. Several public databases have been established to systematically collate and store PPIs, including STRING (Szklarczyk et al., 2019), BioGRID (Oughtred et al., 2020), IntAct (del Toro et al., 2022), PRIN (Gu et al., 2011), RicePPINet (Liu et al., 2017) and RiceNet v2 (Lee et al., 2015). However, most PPI datasets in rice stem from computational predictions, while experiment-based rice PPI datasets are fragmented due to the lack of systematic profiling at the rice PPIome level, which largely hinders information sharing in the rice research community. To bridge this gap, we constructed the Port of Protein-Protein Interactomes (POPPIN; https://riceome.hzau.edu.cn/poppin/), an integrated database dedicated to sharing experimentally verified PPIs and functional clues in rice. Empowered by high-throughput PPIome profiling technologies and text mining assisted by a large language model (Huang et al., 2025; Liu et al., 2025), POPPIN currently has deposited over 150,451 pieces of rice PPI-related information. Additionally, POPPIN provides detailed protein information, including GO annotations, subcellular localizations, domains, trait ontology (TO) information, and hyperlinks to external biological databases. Through offering a user-friendly web interface for search and dynamic network visualization, POPPIN serves as the first large-scale, experiment-based database for searchable PPIs in rice, and has the potential to be extended to other species under this structural framework.

systems biology↗

Iterative co-creation of harmonized human and non-human primate cellular and structural ontologies and 3D common coordinate frameworks for the basal ganglia

A major goal of the BRAIN Initiative Cell Atlas Network (BICAN) is to create a suite of foundational reference cell atlases and associated standards for human and non-human primate brains. Central to this goal is the creation of cross-species harmonized cellular taxonomies and structural parcellations with formal ontologies that can be mapped into 3D reference frameworks bridging neuroimaging and cellular and histological resolutions. We describe here an iterative approach, focused initially on the basal ganglia, to co-create structural and cellular ontologies in human, macaque and marmoset brains, including a Harmonized Ontology of Mammalian Brain Anatomy (HOMBA), and to map and refine structural parcellations into neuroimaging-based common coordinate frameworks. These references provide the framework for documenting and mapping all experimental sampling in BICAN, allowing analyses of cellular and molecular variation as a function of topographic position, and enabling comparisons of cellular, molecular and neuroimaging-based functional variation within and between primate species. HighlightsO_LIA hierarchical Harmonized Ontology of Mammalian Brain Anatomy (HOMBA) covering 2348 structures C_LIO_LIHOMBA-annotated 3D common coordinate frameworks (CCFs) of the basal ganglia across species C_LIO_LIHistologically informed 3D parcellation/atlas of 280 human subcortical structures indexed by HOMBA C_LIO_LIMapping and integration of structural, cellular and functional data with HOMBA and CCFs C_LI

neuroscience↗

Diagnostic Performance of Fluorescence-Based Rapid On-Site Specimen Evaluation for Helicobacter pylori Antimicrobial Susceptibility Testing Before and After Algorithm Optimization: A Two-Round Comparative Study

ObjectiveThis study was designed to evaluate the diagnostic performance of fluorescence-based rapid on-site specimen evaluation (F-ROSE) for antimicrobial susceptibility testing of Helicobacter pylori (H. pylori) and to compare test performance before and after iterative optimization of fluorescence image acquisition and of the artificial intelligence (AI) recognition algorithm, using two consecutive rounds of paired testing, so as to provide trial data supporting clinical implementation of rapid susceptibility testing. MethodsForty patients with a urea breath test (UBT) or rapid urease test (RUT) positive for H. pylori within the preceding 2 weeks, together with strongly positive endoscopic findings, were prospectively enrolled. In order of enrollment they were allocated to two rounds in which F-ROSE was compared with culture-based susceptibility testing. Twenty patients were tested in round 1 on an automated fluorescence immunoassay scanner running the original algorithm; a further 20 were tested in round 2 with the optimized algorithm. With in vitro culture and E-test as the reference standard, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy of F-ROSE were calculated for each round for amoxicillin, levofloxacin hydrochloride and clarithromycin, and agreement between methods was assessed with Cohens kappa. Receiver operating characteristic (ROC) analysis was used to identify the optimal cutoff of the fluorescence residual rate (FRR) and to determine how far threshold adjustment improved performance. ResultsCulture succeeded in 15 patients in round 1 and in 14 patients in round 2, leaving 29 evaluable samples. Overall diagnostic performance after algorithm optimization was clearly better than before. Pooled across the three antibiotics, sensitivity was 92.9%, specificity 71.0% and accuracy 77.8% before optimization; after optimization sensitivity rose to 100.0%, specificity increased slightly to 74.2% and accuracy to 81.0%. NPV reached 100.0% for all three agents after optimization, and no resistant isolate was missed. The gain was largest for clarithromycin, for which sensitivity rose from 85.7% to 100.0%, accuracy from 66.7% to 78.6% and kappa from 0.348 to 0.571, indicating a clear improvement in agreement between the two methods. ROC analysis showed that drug-specific optimal cutoffs derived from the Youden index improved specificity appreciably compared with the uniform 50% FRR threshold currently applied, the gain being most evident for levofloxacin hydrochloride. ConclusionsWith sharper fluorescence images and an improved AI recognition algorithm, F-ROSE performs better in H. pylori susceptibility testing, and the reduction in missed resistant strains is particularly noteworthy; the assay is therefore a plausible option for rapid susceptibility screening in clinical practice. Multicenter studies with larger samples are still required to confirm the stability of the technique.

microbiology↗

Culture-Free Rapid Phenotypic Antimicrobial Susceptibility Testing for Helicobacter pylori Based on Fluorescence Rapid On-Site Evaluation Technology: A Preliminary Study

BackgroundPhenotypic antibiotic susceptibility testing (AST) for Helicobacter pylori (H. pylori) has relied on bacterial culture for three decades, requiring 5-7 days to yield results. Genotypic rapid tests can only detect known resistance mutations and fail to reliably identify amoxicillin resistance. To our knowledge, no culture-free rapid phenotypic AST method for H. pylori has been previously reported. MethodsWe developed a phenotypic AST method based on fluorescence rapid on-site evaluation (ROSE) technology that completely bypasses bacterial culture. Gastric mucosal biopsy specimens from 40 H. pylori-positive patients were homogenized and co-incubated with an acridine orange/ethidium bromide (AO/EB)-based viability staining reagent and three first-line antibiotics--amoxicillin, clarithromycin, and levofloxacin--at concentrations corresponding to the European Committee on Antimicrobial Susceptibility Testing (EUCAST) breakpoints for H. pylori, at 37 {degrees}C for 1 hour. Fluorescence intensity was measured using a microplate reader. A reduction in fluorescence relative to an antibiotic-free control indicated susceptibility, whereas no significant reduction indicated resistance. Conventional culture-based AST (E-test) served as the reference method. The overall concordance rate, sensitivity, specificity, and Cohens kappa coefficient were calculated. ResultsFourteen of the 40 samples had unsuccessful culture and were excluded, leaving 26 samples for statistical analysis of each antibiotic. The overall concordance rates between the ROSE method and culture-based AST were 84.6% (22/26) for amoxicillin, 76.9% (20/26) for levofloxacin, and 69.2% (18/26) for clarithromycin. Cohens kappa coefficients indicated moderate agreement for all three antibiotics ({kappa} = 0.523, 0.539, and 0.412, respectively). Unlike genotypic methods, the ROSE method successfully assessed amoxicillin susceptibility in all 40 patients--a critical first-line antibiotic for which no reliable genetic resistance marker currently exists. The turnaround time was approximately 1 hour (55-65 minutes), compared with 5-7 days for culture-based methods; preliminary estimates indicated a cost reduction of approximately 3,000-5,000 Chinese yuan (CNY) per patient, mainly attributable to the elimination of culture media, prolonged incubation, and repeat clinic visits. ConclusionsThis study reports, for the first time, a culture-free 1-hour phenotypic AST for H. pylori. The method enables same-day, susceptibility-guided treatment decisions, addressing an unmet clinical need spanning three decades. Algorithm optimization and a prospective randomized controlled trial are currently underway to further improve diagnostic accuracy and validate clinical utility.

microbiology↗

An open-access CT-based 3D anatomical dataset of extant sharks across all major lineages

0Sharks exhibit extraordinary morphological diversity across a wide range of ecological niches, yet large-scale, high-resolution digital datasets of their internal anatomy remain limited. Here we present an open-access 3D shark anatomical repository derived from published X-ray computed tomography (CT) data, featuring manually segmented and systematically annotated models of the chondrocranium, visceral arches, axial skeleton, musculature, and viscera in standard STL format. The dataset comprises 117 individuals, representing 72 species across 25 families and all nine extant shark orders, with 115 full-body reconstructions and two head-only models. This open-access dataset offers a comprehensive resource for comparative anatomy, biomechanical simulations, evolutionary developmental biology and biomimetics research of extant sharks.

evolutionary biology↗

Data-adaptive three-dimensional deconvolution and evaluation for volumetric fluorescence microscopy

Optical fluorescence microscopy enables visualization of biological structures and dynamics. However, the intrinsic diffraction limit, especially axially, and depth-related scattering noise compromise the image resolution and fidelity. Computational 3D deconvolution is a promising approach for mitigating these issues, yet its execution is hindered by inaccurate and cumbersome theoretical modeling or experimental measurement of 3D point spread function (PSF), as well as ineffective 3D noise regularization. Furthermore, in the 3D super-resolution regime, there remains a lack of standardized tools for evaluating 3D super-resolution fidelity. Here, we present the 3D adaptive deconvolution and evaluation (3D-ADE) toolkit, which comprises 3D-Ada deconvolution with physics-oriented automatic 3D-PSF calibration, and 3D-SQUIRREL for 3D super-resolution quality assessment. It effectively resolves noise instability, eliminates the need for 3D-PSF calibration, and reliably assesses the fidelity of 3D resolution extension via deconvolution, physical, and deep-learning-based methods. Accessible via multiple software platforms, 3D-ADE enhances the versatility of 3D deconvolution and fills the gap in 3D super-resolution evaluation tools, and thereby advances volumetric fluorescence imaging applications.

bioengineering↗

A GPX4 phosphorylation switch by FGFR1 guards against ferroptosis

Ferroptosis is driven by lipid peroxidation, yet the mechanisms by which cells rapidly adjust their sensitivity to ferroptosis in response to extracellular cues remain elusive. We identify a direct phosphorylation switch controlling the activity of glutathione peroxidase 4 (GPX4), the core ferroptosis regulator. The receptor tyrosine kinase FGFR1 directly binds and phosphorylates GPX4 at Tyr180/Tyr196 in a kinase-dependent manner, requiring its Tyr730 as a docking site. This phosphorylation enhances GPX4s catalytic activity and suppresses ferroptosis. In cardiac ischemia/reperfusion injury, the FGFR1-GPX4 axis is suppressed, and a selective FGFR1 agonist (FGF-1{Delta}NT) reactivates it to protect against ferroptosis-mediated damage. Critically, a phosphorylation-deficient GPX4 knock-in mouse exhibits hypersensitivity to injury and non-responsive to this agonist, proving that GPX4 phosphorylation is essential. Our findings reveal a rapid mechanism for regulating ferroptosis via GPX4 tyrosine phosphorylation, directly linking receptor tyrosine kinase signaling to ferroptosis, and offering new strategies for treating ischemic-and other ferroptosis-associated diseases.

Cell Biology↗

Fibroblast response to burn injury in larval zebrafish mirrors developmental maturation and is inhibited by infiltrating neutrophils

Fibroblasts mediate tissue repair after damage, but aberrant fibroblast behavior in response to injury can result in impaired wound healing. Severe burn injury often results in tissue scarring, but the underlying mechanisms by which fibroblasts respond to burn injury and the role of inflammation in fibrosis are not well understood. Here we developed fluorescent reporters of collagen expressing mesenchymal cells enabling real time imaging of fibroblasts during homeostatic development and in response to burn injury using larval zebrafish. We find that fibroblasts derived from the mesenchyme respond to burn injury by engaging in a maturation process, characterized by the expression of vimentin, which is reminiscent of larval development. In burned tissue, fibroblast maturation is perturbed by prolonged neutrophil infiltration, resulting in disorganized extracellular matrix (ECM) and delayed ECM remodeling, which can be rescued by neutrophil depletion. This work adds to our understanding of fibroblast development in zebrafish and shows that collagen expressing mesenchymal cells regulate ECM remodeling in coordination with immune cells during burn wound healing. Summary StatementVimentin-positive fibroblasts are required for normal wound healing in larval zebrafish, but the presence of inflammatory neutrophils after burn injury impairs fibroblast maturation and collagen remodeling.

Developmental Biology↗

Gaze shifts in freely moving mice comprise distinct head-eye coordination motifs

Freely moving mice are generally thought to redirect gaze mainly through head-coupled movements, with eye movements stabilizing the retinal image or resetting eye position. This reflexive view leaves unresolved whether gaze shifts also include active coordination modes. Here we show that a single gaze-shift class resolves into multiple distinct head-eye coordination motifs. Using high-resolution head and eye tracking in freely moving mice, we identified four reproducible motifs: Head-before-Eye (HbE), Head-with-Eye (HwE), Head-Dominant (HD), and Eye-Dominant (ED). The motifs differed in head-eye timing, locomotor context, and pre-onset visual-behavioral structure. Their short-timescale sequential organization was non-random: HD formed alternating side-to-side head movements, whereas HwE-HbE-ED formed a directed transition chain preserved within each movement direction. Simultaneous neural recordings further revealed motif-dependent responses in primary visual cortex (V1) and superficial superior colliculus (sSC), with stronger sSC than V1 modulation for the three motifs distinguished by pre-onset visual-behavioral structure (all but HbE). HwE showed the clearest signature of active orienting, combining near-synchronous head-eye onset, strong relevance to visual-behavioral features, and the largest pre-onset and earliest peri-onset responses in sSC. These results expand a unitary view of gaze shifts in freely moving mice into a diverse, structured repertoire of coordination motifs, and identify HwE as a candidate active gaze-shift mode during natural behavior.

animal behavior and cognition↗

Physics-Driven Zero-Shot Reconstruction of Isotropic 3D Fluorescence Microscopy under Undersampled Acquisition

Three-dimensional (3D) imaging represents the development of next generation of fluorescence microscopy. However, routine axial down-sampling makes isotropic resolution unrealistic. Here, we propose DeepUI, a physical zero-shot framework designed to achieve isotropic 3D fluorescence images from a low axial sampling rate. DeepUI fully leverages the intrinsic characteristics of 3D images through physics-guided degradation, which incorporates spatial-frequency joint learning to generate a scaled optical transfer function, combined with noise degradation and an up-sampling branch. Typically requiring just 5 minutes for training and 0.5 minutes for high-throughput and fast prediction, we demonstrate the superior performance of DeepUI to get isotropic results, and the exclusivity to axial down-sampling conditions, even in more challenging conditions, including defocused background, noise, and resolution blur.

bioinformatics↗

scRNA-seq and genomics analyses reveal key mechanisms of inverted papilloma-associated sinonasal squamous cell carcinoma malignant transformation

Sinonasal inverted papilloma (IP) carries a 10% risk of malignant transformation to IP-associated sinonasal squamous cell carcinoma (IP-SNSCC), yet the molecular and immune drivers of this progression remain poorly defined. This study integrates single-cell RNA sequencing, multiplexed spatial proteomics, whole-exome sequencing, and functional assays across IP and IP-SNSCC cohorts to define mechanisms of malignant transformation. Respiratory epithelial basal cells are identified as the putative cell of origin, with progression marked by recurrent CDKN2A loss and TP53 mutations. Spatial profiling reveals immune reorganization at the lesional interface in IP-SNSCC, characterized by enrichment of alternatively activated M2 macrophages. CXCL14 is shown to directly induce an immunosuppressive myeloid phenotype that suppresses T-cell IFN{gamma} production through an IDO-pathway-dependent mechanism. Integration of these multimodal datasets defines a previously unrecognized CXCL14-IDO mechanism that constrains anti-tumor immunity at the tumor-stroma interface. These findings establish IDO-targeted immunomodulation as a rational adjuvant strategy and provide a comprehensive molecular framework for understanding IP-SNSCC pathogenesis.

genomics↗

Simultaneous brain-wide single-cell recording resolves spatiotemporal memory architecture

Many fundamental mammalian brain functions emerge from the coordinated activity of cells distributed across large, brain-wide networks. To understand these processes in healthy and diseased states, ideally one would simultaneously measure and analyze single-cell activity at the brain-wide scale, an enduring challenge for live-measurement approaches that often face an inherent tradeoff between spatial resolution and scale. Here, we present GLOBE (sinGle-cell spatiotemporaL recOrding Brain-widE), a technology for brain-wide single-cell recording of cellular activity in vivo with spatiotemporal resolution, physiological sensitivity, and parallelization-accelerated readout. GLOBE leverages genetically encoded intracellular protein tape recorders and a high-throughput computational platform for integrated image and signal analysis. GLOBE records analog signal amplitudes across a continuous time axis, requires only standard light microscopy for in situ readout, and is compatible with expansion microscopy and RNA readouts. We applied GLOBE to simultaneously record transcriptional activity of the immediate early gene Fos in up to 219,703 neurons simultaneously across a single mouse brain over 5.5 continuous days, with a timestamp precision of 3.1-6.7 hours (median absolute error), a local recording density of 69-90% of neurons per imaging field of view, and a post-mortem imaging readout speed of 2.9 seconds per neuron on average. GLOBE resolves the brain-wide spatiotemporal structure of single-cell activity, revealing that Fos transcriptional dynamics associated with fear learning and memory retrieval are distributed across the brain with region-specific temporal heterogeneity, and that the variance of this structure scales down as the number of sampled cells increases. We envision GLOBE to have broad applications for dissecting and decoding physiological and pathological processes at the brain-wide scale.

neuroscience↗