Biology subjects

Yang, Y.

Publications and source records attributed to Yang, Y..

At least 145 records · Page 8Linked to original sources

bioRxiv2026

Trustworthy ML/AI for Aging Clocks: Preventing Systematic Prediction Bias in Biological Age Estimation

Machine learning (ML)- and artificial intelligence (AI)-based aging clocks are increasingly used to quantify physiological and molecular aging from omics and medical imaging data as distinct from chronological age. Here, we characterize a fundamental but underappreciated statistical limitation of commonly used ML/AI regression models for continuous outcomes: systematic prediction bias and its propagation to downstream association estimates. This issue becomes more challenging when the true outcome, biological age, is latent and therefore unobserved during ML/AI model training. We demonstrate that systematic prediction bias can distort and, in some cases, even reverse downstream association analyses that use aging clocks as ML/AI-predicted outcomes to assess their associations with exposures or clinical factors. For example, it can produce spurious associations suggesting that older predicted brain age is linked to better cognitive performance, or that older epigenetic age is associated with better kidney function. To address this problem, we introduce a principled and broadly applicable ML/AI regression framework based on constrained optimization, yielding better calibrated aging-clock estimates and valid downstream inference.

bioinformatics↗

bioRxiv2026

Interplay of stability and dynamics in the optimization of a highly proficient de novo enzyme

The development of highly active de novo enzymes that catalyze new-to-nature reactions is becoming increasingly possible. Here, we identify the features underlying the catalytic efficiency of a highly proficient de novo enzyme, from the original computational design to an optimized catalyst obtained through two rounds of directed evolution. Computational, spectroscopic, and biochemical studies reveal successfully designed features, including precise alignment of catalytic residues, transition state stabilization, and environmental tuning. In the most evolved enzyme, binding of a transition state analog also led to widespread increases in backbone conformational stability throughout the protein, except within a helix near the active site entrance, where the introduction of Gly and Pro increased dynamics and catalytic activity. Thus, the entire protein contributes to catalysis in the most optimized enzyme. Also, the initial design considered only the transition state but not substrate binding, leading to a dynamic Michaelis complex prior to optimization. These studies show the multiple features that need to be optimized to achieve high activity in a designed enzyme.

biochemistry↗

bioRxiv2026

Cobamide-Dependent Dichloromethane Fermentation by Dehalobacter Reveals a Hidden Acetogenic Route for Organohalide Biotransformation

Halogenated one-carbon (C1) compounds, such as dichloromethane (DCM), drive critical fluxes in global carbon and halogen cycles. While the genus Dehalobacter is canonically defined by obligate organohalide respiration, its physiological and ecological roles in anaerobic C1 metabolism have remained fundamentally ambiguous. Here, we document a paradigm-shifting metabolic capacity within a sediment-derived microbial consortium: the autonomous fermentation of DCM by a novel population, Candidatus Dehalobacter formatiformans strain J1. Over successive transfers, strain J1 outcompeted co-existing Dehalobacterium formicoaceticum to become the overwhelmingly dominant population (>80% relative abundance), converting DCM stoichiometrically to acetate and formate (4:1) without auxiliary substrates. Genome-resolved metagenomics revealed that strain J1 couples a distinct mec gene cassette--mediating methyl-transfer reactions during DCM activation--to a complete Wood-Ljungdahl pathway for efficient C1 assimilation. Crucially, strain J1 lacks the complete genetic repertoire for de novo cobamide biosynthesis. Physiological validation confirmed that this fermentative pathway is strictly dependent on exogenous cobamides, exposing a profound reliance on community cross-feeding. These findings reveal an unexpected acetogenic lifestyle within Dehalobacter, a lineage historically viewed as comprising obligate organohalide-respiring bacteria. More broadly, this work identifies cobamide-dependent methyl-transfer metabolism as an ecological control on anaerobic DCM fermentation and expands the known roles of Dehalobacter in carbon-halogen cycling in anoxic environments.

microbiology↗

bioRxiv2026

SynFit: Synergistic Contrastive Learning for Multi-Objective Protein Fitness Prediction and Optimization

Proteins function through a complex interplay of structural and biochemical properties, and mutations can reshape these properties to generate fitness landscapes spanning multiple functional objectives. A central challenge in protein engineering is the need to simultaneously optimize multiple properties. In biocatalysis, for example, practical enzyme development routinely requires the concurrent optimization of catalytic activity, selectivity, stability, and substrate generality. However, despite recent advances in computational protein design and fitness prediction, most existing approaches treat these properties independently and do not explicitly capture the dependencies and trade-offs that govern real-world protein performance. We present SynFit, a multi-objective learning framework that integrates pretrained protein language models with experimental fitness measurements for protein fitness prediction and engineering. SynFit learns both shared and property-specific protein sequence representations through a synergistic contrastive learning strategy, enabling the identification of variants that simultaneously optimize multiple functional properties. Across a large-scale multi-fitness deep mutational scanning benchmark, SynFit consistently outperforms state-of-the-art supervised models trained on individual objectives and more accurately identifies variants that balance competing functional constraints. We further applied SynFit to multi-objective enzyme design for a new-to-nature biocatalytic enantioselective borylation reaction, providing a diverse array of novel cytochrome c sextuple variants in a single round of design with simultaneously improved catalytic activity and enantioselectivity that rival the best variants obtained through directed evolution. Together, these results establish SynFit as a general framework for multidimensional protein fitness prediction and highlight its potential to enable efficient multi-objective optimization in protein engineering, particularly in biocatalysis.

bioinformatics↗

bioRxiv2026

Fibroblast TGF-β3 promotes tissue-residency and survival of CD8 T cells in barrier tissues and tumors

Fibroblasts are key organizers of tissue architecture and immune cell homeostasis, yet how they shape adaptive immune function within non-lymphoid tissues remains incompletely understood. CD8+ tissue-resident memory T cells (TRM) provide localized protection against pathogens and contribute to tumor control, but the microenvironmental signals that maintain their persistence and survival are poorly defined. Here, we identify fibroblast-derived TGF-{beta}3 as a conserved stromal niche factor that specifically sustains CD8+ TRM in both steady-state and disease settings. Across human single-cell cross-tissue atlases, CD8+ TRM preferentially correlated with fibroblast abundance in healthy barrier tissues and multiple tumor types, and TGFB3 emerged as a key fibroblast-enriched candidate mediator. In human and murine co-culture systems, fibroblast-derived TGF-{beta}3 promoted CD8 TRM-like differentiation in vitro. Using a novel genetic in vivo model, inducible fibroblast-specific deletion of Tgfb3 reduced CD8 TRM across barrier tissues at steady state and impaired antigen-specific CD8 TRM formation following viral infection. In tumor models, genetic loss or antibody mediated neutralization of TGF-{beta}3 impaired CD8 T cell residency and cytotoxicity, induced dysfunction via proteotoxic stress and apoptotic programs, and accelerated tumor growth. These findings provide mechanistic insight into the limited efficacy of pan-TGF-{beta} blockade in cancer therapy. Collectively, we describe a novel fibroblast-CD8 T cell axis mediated by TGF-{beta}3 that sustains residency and restrains proteotoxic stress in barrier tissues and tumors.

immunology↗

bioRxiv2026

Rhythmic temporal structure organizes recurrent dynamics to support sequential working memory

Rhythmic temporal structure improves working memory, but how this benefit emerges from recurrent dynamics remains unclear. Here, we trained excitatory-inhibitory recurrent neural networks with short-term synaptic plasticity to perform a sequential delayed match-to-sample task with either regular or jittered sample timing. Rhythmic input produced a small but reliable improvement in task accuracy and was associated with more differentiated population trajectories during encoding. This behavioral advantage was accompanied by an organization of population dynamics around the dominant input frequency: temporal regularity progressively brought stimulus arrivals closer to preferred encoding phases, modulated phase advancement during stimulus presentation, and reduced the deviation of inter-stimulus phase-progression frequency from the dominant input rhythm. As a result, internal oscillations increasingly tracked the temporal structure of the input across the sequence, providing a phase-based scaffold for encoding ordered information. This scaffold preferentially supported temporal-order representations rather than uniformly enhancing all stimulus features. Decoding analyses further showed that stronger temporal regularity increased the fidelity and persistence of stimulus information in both neuronal activity and synaptic efficacy, whereas perturbing synaptic efficacy produced the largest impairment during delay-period maintenance. These findings suggest that rhythmic input supports sequential working memory by imposing a reliable temporal structure on recurrent dynamics and stabilizing synaptic-state representations.

neuroscience↗

bioRxiv2026

Differences in other-directed emotion regulation tracks connectivity between amygdala and prefrontal regions during fairness decisions

Fairness decisions often integrate affective responses within a social context, yet emotion regulation in this literature has been largely studied as a self-directed process rather than an interpersonal one. We examined how individual differences in other-directed emotion regulation--measured with the Emotion Regulation of Others and Self (EROS) scale--relate to behavioral and neural responses during fairness decisions in 138 adults completing a variant of the Ultimatum Game with human and computer partners during fMRI. Behaviorally, participants who more strongly endorsed worsening others emotions rejected unfair offers more frequently, and this tendency interacted with offer fairness to amplify rejection of unfair offers. At the neural level, the left anterior insula tracked offer unfairness more strongly in social versus nonsocial contexts, consistent with sociality modulating the neural encoding of fairness. Right dlPFC activation during socially unfair offers was greater among individuals who preferred to improve others emotions. Connectivity analyses revealed that social fairness sensitivity predicted stronger amygdala-orbitofrontal and amygdala-dmPFC coupling; the latter was further amplified among individuals higher in other-directed emotion worsening. Together, these findings identify interpersonal emotion regulation as an understudied source of variation in the affective and prefrontal systems supporting fairness-based social decisions.

neuroscience↗

bioRxiv2026

The human gut virome is a non-redundant and clinically informative component of the microbiome

The gut virome represents a vast reservoir of genetic diversity with profound implications for human health, yet it remains the "dark matter" of the microbiome due to the staggering complexity of reproducible viral profiling. It remains fundamentally contested whether biologically informative virome signals can be robustly recovered from routine whole-metagenome sequencing (WMS), and to what extent these signals offer ecological insights independent of the bacteriome. Here we present VIP2B, a framework that leverages Type IIB restriction tags to extract multifaceted viral features (encompassing taxonomy, coverage, function, and phenotype) directly from bulk WMS data. Through extensive benchmarking across incomplete references, unseen genomes, and high bacterial or host background, we demonstrate that VIP2B achieved high precision and robust taxonomic concordance. By applying VIP2B to paired bulk and virus-like particle (VLP)-enriched datasets, we reveal a species-level overlap far greater than previously recognized, proving that standard bulk metagenomes contain a wealth of recoverable viral information. Analysis of 20 clinical cohorts demonstrates that coverage-, function-, and phenotype-resolved viral features consistently identify disease-associated signatures that escape taxonomic analysis alone, significantly improving diagnostic models over bacteriome-only approaches. Finally, we define two distinct gut virome community states at the population scale (n=6,090), characterized by divergent diversity profiles and health associations. Our findings establish the gut virome as a non-redundant, clinically actionable component of the human holobiont and provide the methodology necessary to transition microbiome research toward a truly multi-kingdom framework.

bioinformatics↗

bioRxiv2026

Structure and Mechanism of a Two-component Lanthipeptide Toxin

The enterococcal cytolysin is a two-component lanthipeptide natural product that co-operatively kills mammalian cells and bacteria. It is a virulence factor in typically commensal strains of gut-dwelling Enterococcus faecalis and causes a fatal form of alcoholic hepatitis. Despite its clinical significance, little is known about the mechanism of action. We present here the molecular details of cytolysins remarkable bioactivity. A high-resolution cryo-electron microscopy structure revealed highly ordered tubular assemblies comprising the two subunits. We further demonstrate these structures disrupt the membranes of eukaryotic and bacterial cells. These results provide the first high-resolution structure of two distinct lanthipeptides interacting with one another and offer an explanation for the unique bioactivity of the cytolysin toxin.

biochemistry↗

bioRxiv2026

Massilia varians P2-4, A Potential Biocontrol Agent against Pathogenic Pseudomonas aeruginosa in Eriocheir sinensis

Pseudomonas aeruginosa is a clinically significant bacterial pathogen that poses a serious threat to aquaculture. However, there are limited information on Massilia isolates against pathogenic P. aeruginosa in aquaculture. In the present study, a facultative predator, M. varians isolate P2-4, was isolated from aquaculture sediment using Chinese mitten crab Eriocheir sinensis-pathogenic P. aeruginosa as the prey bacterium, and its genomic feature, bacteriolysis-related genes, safety, bacteriolytic spectrum, and in vitro and in vivo antibacterial effects against pathogenic P. aeruginosa in E. sinensis were further characterized. Isolate P2-4 consisted of one chromosome and one plasmid (with a total of 75 tRNAs, 7 5S rRNAs, 7 16S rRNAs, 7 23S rRNAs, 34 sRNAs, 5,238 coding genes, 20 genomic islands, 1 prophage, 23 insertion sequences, and 102 repeat sequences), and harbored 19 bacteriolysis-related genes (pilA, pilB, pilC, pilD, pilF, pilG, pilH, pilM, pilO, pilP, pilQ, pilS, pilR, pilT, mltA, mltB, mltC, mltD, and dacB) associated with cellular motility and cell wall lysis. In addition, the isolate carried no virulence genes, was unable to produce haemolysin, hydrogen sulfide, nitrite and ammonia, and avirulent in E. sinensis with a 7-day acute intraperitoneal LD50 value of above 5.0 x 108 CFU/mL. Furthermore, the isolate possessed a wide bacteriolytic spectrum against pathogenic Shewanella algae, Aeromonas caviae, A. hydrophila, and Photobacterium damselae besides P. aeruginosa, exhibited bacteriolysis rates of 99.35% to 99.99% towards the pathogenic P. aeruginosa at 1.0x103 to 1.0x10{square} CFU/mL, and displayed relative percentage survivals of 42.31% to 73.08% against P. aeruginosa infection in E. sinensis at doses of 6.0 x 103 to 6.0 x 105 CFU/g diet. To our knowledge, this study for the first time demonstrates a M. varians strain as a potential biocontrol agent against pathogenic P. aeruginosa in aquaculture.

microbiology↗

bioRxiv2026

Collective cancer cell calcium activity drives brain metastasis

Communication in multicellular networks is a cancer-intrinsic neural feature and crucial for primary brain tumor growth and resistance, but it is unclear whether brain metastases (BrM), the most common and deadliest brain malignancy, are also driven by communicating cancer networks. Using intravital two-photon microscopy in awake mice, clinical specimens, and Ca2+ integrators, we demonstrate that brain-colonizing breast and lung cancer and melanoma cells display gap-junction-dependent, coordinated Ca2+ activity in multicellular, cancer-cell intrinsic networks, which drives their proliferation. Mechanistically, Ca2+ oscillations induce transcription of immediate early genes, adoption of a neuronal expression profile, and cell cycle progression. While many of those features are enriched in BrM, all investigated cancer cell lines showed collective Ca2+ activity. Therapeutically, blocking Ca2+ activity with gap junction inhibitors reduces BrM burden in mouse models. Here we show communicating cancer cell syncytia as drivers of BrM growth, pointing to a targetable pathomechanism, and potentially a new pan-cancer hallmark. Graphical AbstractIn brief Brain metastases form gap-junction-coupled networks exhibiting spontaneous, coordinated Ca2+ activity linked to immediate early gene activation, neuronal gene programs, and cell cycle progression. Disrupting Ca2+ network communication with gap junction inhibitors induces cell cycle arrest and reduces brain metastatic burden in vivo. O_FIG O_LINKSMALLFIG WIDTH=195 HEIGHT=200 SRC="FIGDIR/small/723715v1_ufig1.gif" ALT="Figure 1"> View larger version (88K): org.highwire.dtl.DTLVardef@1130ea0org.highwire.dtl.DTLVardef@254dcdorg.highwire.dtl.DTLVardef@117021forg.highwire.dtl.DTLVardef@18c4f1e_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIBrain metastases display collective Ca2+ activity in gap-junction-coupled networks C_LIO_LICa2+ co-activity is conserved across cancers but enriched in brain metastasis C_LIO_LICa2+ oscillations robustly induce neuronal gene programs and cell cycle progression C_LIO_LIGap junction inhibition reduces brain metastasis burden in mice C_LI

cancer biology↗

bioRxiv2026

Chemogenetic Inhibition of the Cortical Amygdala Reduces Alcohol Intake and Restores Thalamic Connectivity in Dependent Female Mice

BackgroundAlcohol use disorder is a chronic relapsing condition characterized by excessive drinking and withdrawal symptoms. Alcohol dependence disrupts function across multiple brain regions, and recent evidence implicates the cortical amygdala (CoA) as a critical node in alcohol-related circuits. However, how CoA activity influences alcohol intake and brain-wide network function during withdrawal remains unclear. MethodsAlcohol dependence was induced using chronic intermittent ethanol vapor (CIE). In one cohort, electrophysiological activity of CoA neurons was assessed during withdrawal. In a second cohort, mice underwent CIE paired with two-bottle choice drinking, and inhibitory DREADDs (hM4Di) were used to suppress CoA activity during drinking and withdrawal while behavioral outcomes were measured. Brains were then collected for Fos immunolabeling and iDISCO+ based whole-brain activity mapping to determine how CoA inhibition during withdrawal altered network organization. ResultsRepeated CIE increased alcohol sensitivity in CoA neurons during withdrawal. Chemogenetic inhibition of the CoA reduced alcohol intake in dependent mice without affecting withdrawal-related behaviors. Whole-brain Fos mapping showed that CoA inhibition reduced activity within the CoA while enhancing functional connectivity across multiple brain regions, particularly in the isocortex, thalamus, and anterior hypothalamic nucleus. During withdrawal without CoA inhibition, thalamic regions exhibited negative connectivity, consistent with disrupted network function; CoA inhibition reversed this pattern, producing strongly positive thalamic and medial prefrontal cortex connectivity. ConclusionsThese findings demonstrate that alcohol dependence alters CoA sensitivity, alcohol dependence-induced drinking and brain-wide network organization during withdrawal. The CoA appears to selectively regulate withdrawal-associated alcohol drinking, and its inhibition may reduce intake by restoring thalamic and cortical connectivity. HighlightsO_LIThis study identifies the cortical amygdala as a previously underexplored brain region involved in alcohol-related behaviors. C_LIO_LIBy integrating chemogenetic inhibition with brain-wide network analysis, the study reveals candidate circuit connections through which the CoA may regulate alcohol dependence-related brain activity. C_LIO_LIThis study establishes the CoA as a potential driver of excessive alcohol drinking and alcohol-related network dysfunction. C_LI

neuroscience↗

bioRxiv2026

Loss of mitochondrial co-chaperone GRPEL2 protects mice from age- and diet-induced obesity

Mitochondrial protein homeostasis intersects with metabolic control, but the in vivo roles of specific mitochondrial co-chaperones remain unclear. The chaperone mtHSP70 plays a key role in import and folding of nuclear-encoded proteins targeted to mitochondrial matrix. Its protein folding cycle is regulated by the GrpE-like nucleotide exchange factor GRPEL1. Vertebrates also have a GRPEL2 paralog, postulated as the stress-sensitive counterpart, but its physiological relevance is not known. We show here that GRPEL2 is not essential for viability in mice, and its absence does not induce proteotoxic stress responses in stark contrast to GRPEL1. However, we find that GRPEL2 has a role in regulating body weight homeostasis. GRPEL2 knockout mice are protected from age- and diet-induced weight gain and maintain a better metabolic health and insulin sensitivity. Transcriptional profiling revealed minimal changes in liver and skeletal muscle, whereas white adipose tissue from Grpel2-deficient mice lacked the obesity-associated remodeling seen in controls. We propose that GRPEL2 fine-tunes metabolic setpoints without broadly perturbing mitochondrial protein import, thereby maintaining adipose tissue health during nutritional excess. These findings show that subtle alterations in mitochondrial chaperone systems reshape systemic metabolism and could suggest strategies to mitigate obesity and insulin resistance through targeted modulation of mitochondrial proteostasis.

physiology↗

bioRxiv2026

SigBridgeR: An Integrative Framework and Toolkit for Comprehensive Screening and Benchmarking of Phenotype-Associated Cell Subpopulations in Single-Cell Transcriptomics

Single-cell RNA sequencing has revolutionized our understanding of cellular heterogeneity, yet linking specific cell subpopulations to clinically relevant phenotypes remains a persistent challenge. Although multiple computational methods have been developed to bridge this gap, they are typically implemented as standalone packages with heterogeneous preprocessing pipelines, incompatible parameter conventions, and divergent output formats, thereby hindering rigorous cross-method benchmarking and reproducible multi-method workflows. Here, we present SigBridgeR, an extensible R framework and comprehensive toolkit that currently unifies eight state-of-the-art phenotype-associated cell screening algorithms within consistent workflows. We conducted a systematic benchmarking study across four cancer types HER2-positive breast cancer, triple-negative breast cancer, lung adenocarcinoma, and ovarian cancer using both binary phenotypes and patient survival endpoints. Our evaluation incorporated positive and negative control assessments based on differentially expressed genes and randomly selected marker panels, alongside quantitative accuracy comparisons using ground-truth cell labels. Building upon these insights, SigBridgeR provides standardized preprocessing for scRNA-seq and bulk transcriptomic data, unified algorithmic interfaces through a registry-based architecture, ensemble analysis via weighted voting, and comprehensive visualization utilities for multi-method comparison. By lowering technical barriers and promoting methodological standardization, SigBridgeR facilitates reliable discovery of phenotype-relevant cell subpopulations and enhances the translational potential of single-cell omics research.

bioinformatics↗

bioRxiv2026

A data-driven redefinition of global biodiversity hotspots

The 36 global biodiversity hotspots harbor a disproportionate share of the worlds endemic species, making their conservation critical for planetary health. Traditionally hotspots were defined as ecoregions with [≥]1,500 endemic vascular plant species and >70% natural habitat loss; this relied heavily on expert judgment, with subjective assessments of endemism and habitat loss applied. Challenges in defining endemism, quantifying habitat loss, and the global unevenness in available vascular plant data have hindered hotspot identification over the past decades. Here, we built a global dataset of 150,487 rare vascular plants, identified from 88.1% of the worlds known vascular species, and recognize hotspots based on their richness using three complementary conservation targets and algorithms. We then quantified natural habitat loss and habitat fragmentation using high-resolution remote sensing data and assessed the diversity and distribution of terrestrial vertebrates within these newly identified hotspots. Our data-driven method recovered all the 36 established global biodiversity hotspots, revised 17, and identified 11 new hotspots spanning diverse ecosystems across six continents. These 47 hotspots cover 26.63% of global land area, yet contain 83.8% of rare vascular plants, 92.4% of mammals, 96.1% of birds, 87.8% of reptiles, and 95.0% of amphibians. Collectively, they encompass >89% of terrestrial vertebrates classified as IUCN threatened species. Only 10 hotspots have undergone [≥]70% habitat loss, and the lack of a consistent relationship with habitat fragmentation suggests that this criterion is not globally applicable. Effectively protecting [~]27% of Earths land could theoretically safeguard >89.8% of threatened terrestrial species and >67% of threatened terrestrial species hotspot area, assuming effective protection of the identified biodiversity hotspots. Targeted conservation efforts within these global biodiversity hotspots can meet the established biodiversity targets of the Kunming-Montreal Global Biodiversity Framework as well as post-2030 biodiversity targets. Most importantly, our framework enables conservation scientists to iteratively identify and update global biodiversity hotspots in step with growing global biodiversity data.

ecology↗

bioRxiv2026

Decorrelation by gain control in the mouse olfactory bulb

Classifying sensory stimuli requires neural circuits to transform overlapping inputs into representations that are more distinct and decodable. Odour representations in the olfactory bulb (OB) have been reported to decorrelate from sensory input to output, a transformation thought to enhance odour separability. What has been missing is a systematic quantification of this transformation across odours, and a mechanistic account of how it can be implemented by OB circuitry. Using in vivo two-photon calcium imaging, we recorded glomerular input and output responses to a chemically diverse panel of 47 odours in mice. We observed a robust decorrelation of odour-evoked activity patterns from input to output: correlations between odour representations were consistently reduced, while overall response variance was preserved. This transformation increased the dimensionality of the population code and improved the separability of odour representations. Consistent with this, classification analyses showed that odour identity could be decoded with significantly higher accuracy at the output. To understand the mechanisms underlying this transformation, we developed a linear model of the OB with different levels of connectivity. Models in which each channel underwent only self-gain modulation reproduced the observed decorrelation nearly as well as models with fully unconstrained lateral connectivity. Analysis revealed that channels contributing unique information were selectively amplified, while redundant channels were attenuated. Together, our results show that the OB implements a measurable input-output transformation that enhances odour separability. By combining systematic recordings with computational modelling, we found that feedforward gain modulation serves as a simple and scalable mechanism capable of explaining the observed decorrelation, reframing how we understand the functional architecture of early olfactory processing.

neuroscience↗

bioRxiv2026

Linking live-cell behavior to transcriptional responses across perturbations using dynamic caging

Single-cell technologies, encompassing molecular, morphological, and functional assays, have emerged as cornerstones of modern biological research and discovery. However, current experimental methods often fail to explicitly link these omic modalities, especially in live cells or longitudinally through time, impeding the study of multi-scale interactions and mechanisms of regulation. CellCage Enclosure (CCE) technology overcomes these limitations by dynamically compartmentalizing cells, allowing for scalable, live-cell, longitudinal exploration and simultaneous analysis of transcriptomic, proteomic, and morphological profiles. Using this novel technology, we generate previously inaccessible insights across various in vitro cellular systems under a diverse set of perturbations, including the discovery of morphological and proteomic features linked to immune suppressive gene set expression in human primary regulatory T cells (Tregs), as well as direct association of morphological and proteomic features with inflammatory gene modules in human colonic fibroblasts. We then develop a novel pooled CRISPR genetic screening technology using CCEs, PERTURB-LINK (PERTURBational LINKage of transcriptomics and imaging in single cells via enclosure-based screening) and apply this approach in murine bone marrow derived macrophages (BMDMs), enabling multiomic dissection of NF-{kappa}B pathway regulation in response to lipopolysaccharide (LPS) stimulation. Together, these findings demonstrate the broad impact that advancements in live-cell, paired multimodal technologies, especially upon perturbation, may offer in deepening our understanding of cellular biology.

cell biology↗

bioRxiv2026

Genetic suppression of myeloid receptor Clec7a attenuates microglia neuroinflammation and promotes microglial phagocytosis to delay disease progression in ALS models

Microglial activation has been closely associated with accelerated ALS disease progression. However, specific microglial pathways that regulate microglial activation and ALS disease progression remain limitedly understood. Here, we determined the role of Clec7a (or Dectin-1), a core signature gene of disease-associated microglia (DAM) in ALS, in regulating microglial activation and ALS disease progression. Our spinal cord scRNA-Seq results found that Clec7a deficiency specifically attenuated microglial neuroimmune gene expression in SOD1G93A mice and human ALS. In addition, in vivo two-photon imaging of human (h) TDP43 phagocytosis by microglia in the cortex showed that Clec7a deficiency promotes microglial phagocytosis of pathological hTDP43 by enhancing microglial process dynamics. Subsequent survival analysis further showed that selective deletion of Clec7a in microglia mitigates motor neuron degeneration and delays disease progression in SOD1G93A ALS mice. Together, our results establish that Clec7a is a key regulator in shaping disease microglial functions and promotes disease progression in ALS.

neuroscience↗