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Zhang, Z.

Publications and source records attributed to Zhang, Z..

At least 163 records · Page 9Linked to original sources

Neuromodulation of Foxp2+ hypothalamic neurons induces therapeutic hypothermia

The inability to selectively trigger therapeutic hypothermia independent of environmental cooling has hindered causal analysis of its broader physiological benefits. Here, we employed P57, a natural product that pharmacologically induces therapeutic hypothermia circumventing external cold stress, to identify the neuronal substrates underlying hypothermia-induced antitumor effects. Integrating functional ultrasound imaging, activity-dependent neuronal labeling, and single-nucleus RNA sequencing, we identify a previously unrecognized population of Foxp2 neurons in the medial preoptic area (MPA) that are selectively activated by P57. Inhibition of MPA Foxp2+ neurons abolishes P57-induced hypothermia, whereas the paraventricular hypothalamus (PVH) serves as a critical downstream node. Importantly, targeted activation of MPA Foxp2 neurons is sufficient to induce sustained hypothermia, suppress systemic metabolism, and inhibit tumor growth, providing causal evidence that neuronally driven reductions in core body temperature can exert antitumor effects. Together, these findings establish MPA Foxp2 neurons as a controllable node for therapeutic hypothermia induction and demonstrate that neuromodulation of defined neuronal populations can achieve therapeutic benefit by directly controlling physiological states.

neuroscience↗

Multimodal alignments of in vivo imaging and spatial biology datasets at cellular resolution

Parallel revolutions in intravital microscopy and spatial biology techniques have respectively enabled large-scale recordings of cellular dynamics in live animals and multi-dimensional molecular profiling at single-cell resolution. However, due to the challenges of aligning data from different modalities at cellular resolution, these two transformational approaches have generally been applied on separate biological samples, stymying the ability to link activity patterns and molecular attributes in the same exact cells. To enable routine, multimodal investigations of cells in vivo dynamics and molecular content, we created TRU-FACT (Total Registration Under Functional Activity, Connectivity, and Transcriptomics), a broadly applicable experimental and computational pipeline for registering large populations of individual cells across intravital imaging and spatial biology datasets. The pipeline combines three key innovations: an optomechanical tissue handling and alignment method to parallelize specimen planes, a graph-theoretic method to register individual cells based on their geometric relationships to neighboring cells, and a statistical framework that provides for each cell an a posteriori probability of correct registration. We validated TRU-FACT with several preparations for imaging neural Ca2+ activity in cortical and deep brain areas in head-fixed and freely behaving mice, RNA-barcode-expressing viruses for labeling neural projections, and low- and high-plex spatial transcriptomic methods. In mice performing a skilled reaching task, TRU-FACT alignments revealed the movement-related signaling patterns of intratelencephalic, extratelencephalic, and striatum-, superior colliculus-, and thalamus-projecting motor cortical neurons. Overall, TRU-FACT constitutes a scalable, multimodal discovery platform that is applicable to diverse tissue-types and spatial biology techniques, thereby enabling multiscale analyses of many complex biological systems.

neuroscience↗

SpaCir-VDJ: a broadly compatible circularization strategy for spatial immune repertoire profiling

Deciphering the spatial organization of immune clonal lineages is critical for understanding the evolution of adaptive immune responses. However, mainstream spatial transcriptomics platforms struggle to reconcile cost-effective short-read sequencing with the simultaneous and efficient capture of V(D)J sequences. To address this gap, we developed SpaCir-VDJ, an approach that utilizes a "multiplex PCR enrichment plus library circularization" strategy to integrate spatial barcodes and V(D)J CDR3 regions into a compact circular template optimized for standard short-read sequencing. This workflow is accompanied by an automated computational pipeline designed for circular-library data parsing, sequence reconstruction, spatial barcode deconvolution, and high-fidelity clonotype calling. In human lymphoid tissues, SpaCir-VDJ delineated germinal center (GC)-associated clonal organization and isotype-linked somatic hypermutation (SHM) patterns. Notably, lineage-based spatial analyses inferred inter-GC clonal redistribution events, suggesting that GCs in the analyzed samples may not be fully isolated reaction units. Functional perturbation provided orthogonal support for candidate SHM regulators identified by spatial analysis, with knockdown of MDM4, LYN, EAF2, and H2AFY each leading to reduced SHM. Finally, in gastric cancer, SpaCir-VDJ localized dominant BCR lineages within tertiary lymphoid structures and tumor-margin plasma cell-rich regions, with lineage patterns consistent with extension toward the tumor interior. We further observed a significant positive correlation between cumulative tumor mutations and spatial TCR diversity, consistent with a spatial association between local mutational burden and T-cell remodeling within the tumor microenvironment. Collectively, SpaCir-VDJ provides a scalable and cost-effective framework for interrogating the spatiotemporal dynamics of immune microenvironments.

immunology↗

Defining the Immunomodulatory Determinants of 3-mer Oligonucleotides on TLR7 and TLR8 sensing

Chemical modifications such as 2'-O-methyl (2'-OMe) are central to the efficacy and tolerability of RNA therapeutics. We recently identified that 2'-OMe RNA fragments as short as three nucleotides can exert opposing effects on Toll-like receptor 8 (TLR8) sensing in a motif-dependent manner. This discovery raises important considerations for degradation products of chemically modified RNA therapeutics, which may generate such immunologically active fragments. Here, leveraging their short length, we systematically map how base and sugar modifications within 3-mer oligonucleotides regulate TLR7 and TLR8 responses, and we resolve the structural basis for both TLR8 potentiation and TLR7/8 antagonism by RNA fragments. Building on these insights, we report the development of a dual TLR7/8 inhibitory oligonucleotide with therapeutic potential in autoimmune disease. Together, these findings provide unprecedented resolution of the immunomodulatory properties of oligonucleotide modifications on TLR7/8 and establish 3-mer oligonucleotides as the shortest functional class of RNA therapeutics described to date.

immunology↗

Evaluation of Diffusion Tensor Imaging in the Corpus Callosum on a Portable 100 mT MRI System

Low-cost portable MRI has the potential to improve the accessibility of MRI, but new acquisition methods and protocols must be developed and evaluated to accommodate the reduction in SNR and greater impact of system imperfections. Diffusion tensor imaging (DTI) is a candidate tool for monitoring population health, but the bias and variance of quantitative diffusion tensor-derived metrics must be evaluated prior to designing such studies. DTI of the corpus callosum was performed on an in-house, portable 100 mT MRI system using a slab diffusion weighted Fast Spin Echo with radiofrequency (RF) encoding. Slice coverage was restricted to the corpus callosum to shorten scan time and reduce sensitivity to large rigid motion. In vivo DTI images were obtained in two healthy volunteers with nominal voxel size 50 mm3, scan time 25 minutes, and two different volunteers using nominal voxel size 25 mm3, scan time 35 minutes. Mean diffusivity (MD) and fractional anisotropy (FA) coefficients of variation were estimated in the 50 mm3 acquisition using a bootstrap approach and compared to resolution-matched data obtained on a conventional 1.5T system. MD / FA maps were compared quantitatively and qualitatively. Mean MD values in the corpus callosum obtained on the 100 mT system were within 10% of the reference 1.5T acquisition, but FAs were underestimated by 20-30%. The corpus callosum median MD coefficient of variation was 3.7%, and the median FA coefficient of variation was 7.5%. FA maps obtained at 100 mT had an elevated FA noise floor and color FA maps had lower apparent resolution but some white matter tracts were still distinguishable. HighlightsO_LIDiffusion Tensor Imaging (DTI) of the corpus callosum was performed on a portable 100 mT MRI scanner with 50 mm3 voxels in 25 minutes scan time. C_LIO_LIMean Diffusivity estimates in the corpus callosum obtained at 100 mT and 1.5T differed by less than 0.1 x 10-3 mm2/s. C_LIO_LISome white matter tracts were visible in color Fractional Anisotropy maps obtained at 100 mT but FA maps were underestimated by 20- 30% when compared to a resolution-matched 1.5T acquisition, and had lower apparent resolution. C_LI

bioengineering↗

Macronutrient Composition and Genetic Background Determine the Response to a Ketogenic Diet

While standard high fat diets cause hyperphagia and obesity in mice, high fat-low carbohydrate ketogenic diets (KDs) reduce food intake and body weight. Because the basis for this difference is still unclear, we systematically altered the macronutrient content of a standard KD and found that feeding C57BL/6J (B6J) mice a KD with 5% protein resulted in hypophagia, weight loss, and hypoglycemia, whereas the same diet with 10% protein led to increased adiposity and glucose intolerance. However, these effects were strain-dependent as C57BL/6NJ (B6NJ) weighed similar amounts on the two diets leading us to investigate the molecular mechanisms. When fed the KD-5% diet, B6J but not B6NJ mice showed increased levels of two anorexigenic factors, GDF15 and LCN2, and loss of function of either blunted the weight loss of B6J mice fed the diet. B6J mice harbor mutations in Nnt (Nicotinamide nucleotide transhydrogenase) and Nlrp12 (NLR family pyrin domain containing 12), both of which are wildtype in B6NJ mice. B6J mice fed the KD-5% diet showed the RNA signature of oxidative and integrated stress responses (ISR) and restoring NNT function in liver reduced the levels of GDF15. RNA-seq also revealed that B6J but not B6NJ mice had the RNA signature for hepatic inflammation and a knockout of Nlrp12 led B6NJ mice to lose weight on the KD-5% diet with increased levels of LCN2. Suppression of oxidative stress with N-acetylcysteine (NAC) reduced expression of both GDF15 and LCN2 and prevented the weight loss associated with the KD-5% protein diet in B6J mice, whereas inhibition of the integrated stress response with ISRIB only attenuated the GDF15 axis. Collectively, these findings explain why B6J mice lose weight on a ketogenic diet and reveal a critical interplay between macronutrient composition and genetic background leading to increased levels of GDF15 and LCN2 to induce hypophagia. Finally, these data suggest that the response to different diets among humans might be similarly variable based on genetic variation and macronutrient composition, suggesting the possible need for personalized dietary interventions.

physiology↗

A Noncontiguous Code for RNA-Guided DNA Recognition Preceded CRISPR

CRISPR-Cas systems use RNA-guided proteins for adaptive immunity through a mechanism whose origin is unknown. Here we report the discovery of Viral Interference Programmable Repeat (VIPR) systems consisting of a Vipr protein more ancient than CRISPR-Cas and vrRNAs comprising alternating GGY/NN motifs. Unlike canonical guide RNAs that base pair with nucleic acid targets using an uninterrupted sequence, vrRNAs recognize double-stranded DNA through a noncontiguous code in which the variable NNs of each repeat collectively specify a target that itself contains a gapped recognition sequence. Analysis of natural vrRNA targets suggests VIPR acts against competing phages. We demonstrate programmable phage defense by redirecting the complex for transcriptional repression. These results suggest that the roots of adaptive immunity lie in ancient warfare between viruses, and reveal a new logic for programmable genetic control.

molecular biology↗

Triplex formation drives noncontiguous VIPR RNA-guided DNA recognition

Viral Interference Programmable Repeat (VIPR) systems use a noncontiguous code for RNA-guided transcriptional silencing. How the Vipr protein and a vrRNA comprising alternating GGY and NN segments achieve precise DNA targeting is unknown. Here we present 21 cryo-electron microscopy structures that span the VIPR assembly pathway. Vipr protomers oligomerize along the vrRNA to form a right-handed helical filament, sequestering each GGY motif and positioning the adjacent NN bases for target base pairing. DNA binding, in which every third nucleotide is skipped, results in target strand rotation to form a gapped vrRNA-DNA hybrid helix that wraps around the non-target DNA strand to form a structural triplex. These findings provide the structural basis of noncontiguous RNA-guided DNA binding in VIPR, establishing triplex-driven target-strand handoff as an elegant mechanism of programmable nucleic acid recognition.

molecular biology↗

A recurrent neural network model of chronic pain development and recovery

Chronic pain presents a leading challenge in the world today for both clinicians and researchers. Because chronic pain is difficult to explain and treat, it is often managed with opioids despite providing limited relief and contributing to dependence and misuse. Persistent pain can be maintained by altered central nervous system processing even in the absence of distinct tissue damage or disease, which may limit the efficacy of conventional pharmacological therapies that target nociceptive signal transmission rather than maladaptive central nervous system dynamics often present in those with chronic pain. Although neuroimaging studies have identified this shift from nociceptive to emotional circuits during pain chronification, a quantitative framework linking these neural changes to longitudinal pain trajectories or recovery is lacking. We present a parsimonious firing-rate model that can account for the development of and recovery from chronic pain, which is based on the theoretical framework established by Wilson and Cowan. The model provides a quantitative explanation of how sensitization, anxiety, and fear maintain pain even after an injury has healed, and how calming stimulus downregulates these processes to facilitate recovery. A study applying the same principles as the model produced an average pain decrease of 3.5 on the Visual Analog Scale (VAS), with all subjects experiencing a reduction in pain. These results, coupled with our model and findings in prior studies, suggest that increasing calming stimulus can reduce pain without necessitating pharmacological or invasive, resource-intensive interventions.

neuroscience↗

BridgeBP: A Toolbox for Bridging Brain Parcellations and Standardizing Structural Connectivity Matrices

Brain network analysis has emerged as a critical framework for understanding the complex organization and function of the human brain, underpinning insights into cognition, behavior, and neuropsychiatric conditions. Central to this approach is the parcellation of the brain into discrete regions, which simplifies high-dimensional connectome data and facilitates the investigation of network architectures. However, the proliferation of brain parcellation schemes introduces significant challenges: different parcellations often yield varying network sizes and measures, complicating cross-study comparisons and the reproducibility of findings. Moreover, most connectome construction pipelines are rigid, typically outputting connectivity matrices from only one or a few parcellation schemes, which limits flexibility. In this paper, we address these issues by introducing BridgeBP, a novel toolbox designed to bridge brain parcellations by leveraging continuous brain connectivity concepts. BridgeBP transforms structural connectivity matrices derived from one parcellation scheme into matrices corresponding to more than 40 alternative schemes, standardizing analyses and enhancing the robustness of network studies. Through extensive evaluations, we demonstrate that BridgeBP enables consistent network comparisons across diverse parcellation frameworks, paving the way for more reproducible and generalizable insights in brain connectome research.

neuroscience↗

Dissecting the coordinated progression of cell states in spatial transcriptomics with CoPro

Spatial transcriptomics enables the study of how cells coordinate their molecular states within tissue, providing insight into both normal function and disease processes. A key challenge is to identify gene expression programs that vary continuously across space and are coordinated between cell types. We present CoPro, a computational framework for detecting the spatially coordinated progression of cellular states. CoPro can operate in both supervised and unsupervised modes to identify gene programs that co-vary within or between cell types, and to disentangle multiple overlapping spatial patterns. CoPro can be applied to single-cell-level spatial transcriptomics datasets, including MERFISH, SeqFISH+, Xenium, and histology-imputed transcriptomic data. We demonstrate the utility of CoPro with data collected from colon, brain, liver, and kidney tissues. In the colon, CoPro separates epithelial differentiation along the crypt axis from spatially localized inflammatory signals. In the aging liver, it identifies multiple aging-associated cellular programs superimposed on anatomical zonation. In the brain, the flexible kernel design enables the decoupling of the gene expression gradient along the dorsal-ventral and medial-lateral axes. In the kidney, CoPro identifies tubule-vasculature coordination that is essential in nephron function. These results demonstrate CoPros utility for analyzing spatial coordination of gene expression in complex tissues and disentangling overlapping biological processes, such as anatomical organization and disease-associated variation.

bioinformatics↗

A global metagenomic atlas uncovers ubiquitous biosynthetic potential linked to adaptation in extreme environments

Extreme environments impose severe physicochemical stresses that drive microorganisms to evolve specialized survival strategies. Microbial secondary metabolites determined by biosynthetic gene clusters (BGCs) are recognized as important mediators of microbial adaptation to environmental stress. However, their ecological roles, particularly habitat-dependent preferences across different environments, remain poorly understood. Although extreme environments provide opportunities to mine microbiomes for unique adaptations, such research is hampered by a lack of systematic overview of its genomic diversity, BGC diversity, and the relationships between them. Here, we constructed a standardized extremophilic genomic catalogue (SEGC) from 1,462 metagenomic samples spanning seven representative extreme habitats. The catalogue comprised 54,661 metagenome-assembled genomes representing 21,805 species, 66.1% of which were previously uncharacterized. With this catalogue, we identified 162,855 BGCs distributed across 81.5% of MAGs. Gene cluster family analysis showed the strong habitat dependence largely explained by species-level habitat specificity. Terpene biosynthetic pathways illustrated habitat-linked adaptive strategies, with hopan-22-ol biosynthesis enriched in acid mine, deep sea and hydrothermal plume environments, while retinal-based phototrophy predominated in cryosphere and saline-alkaline habitats. Metatranscriptomic analyses supported in situ activity of these pathways. In conclusion, we presented a global atlas of biosynthetic potential across extreme-environment microbiota and revealed habitat-dependent patterns of secondary metabolism linked to microbial survival.

microbiology↗

Cardiac oxidative stress monitoring enabled by hierarchical mechanical adaptation

Soft bioelectronics have advanced cardiac monitoring through electrophysiological tracking, yet this alone cannot resolve the metabolic pathology essential to surgical decision-making. However, real-time molecular sensing on beating hearts remains unresolved due to deformation-induced sensor failure and stress-induced metabolite artifacts. This challenge is exemplified by ischemia-reperfusion injury (IRI), a major cardiac surgery complication characterized by reactive oxidative species (ROS) bursts, where true pathological ROS signals being confounded by mechanotransduction-induced ROS artifacts. Herein, we propose an enzymatic cardiac oxidative stress biosensor (E-cardiac) with hierarchical mechanical adaptation: macro-scale biofluid-mediated contact, micro-scale fiber reorganization, and nano-scale enzymatic confinement within gold nanoarches dissipate interfacial stress. This produces ultrathin ([~]460 nm), soft (0.79 kPa) E-cardiac with robust electrochemical stability (100% strain), low detection limit (380 nM), rapid adhesion (<3 s), stable biosensing on beating heart, as well as minimal invasive deployment capability. Mechanical analysis and cellular studies confirm mitigated stress-induced ROS and absent PIEZO channel activation. Validated across cardiomyocytes, ex vivo tissues, multi-species ischemia models (mouse, rat, rabbit, pig), rat ischemia-reperfusion injury, and Langendorff hearts simulating graded perfusion deficits, E-cardiac quantitatively differentiates IRI severity (sham < ischemia < reperfusion) as well as detecting the "ECG blind window". The E-cardiac platform provides real-time metabolic feedback for surgical guidance during cardiac procedures, enabling timely intervention before irreversible damage.

bioengineering↗

Ultra-sensitive FLORA-seq links cell-type-specific tRNAome dynamics to differentiation trajectories guiding therapeutic suppressor tRNA candidate selection

Mammalian genomes encode hundreds of tRNA genes, but the role of individual tRNAs in development and cell identity remains unclear. Here, we introduce FLORA-seq, a method for simultaneous, low-input profiling of tRNAs, tRNA-derived RNAs (tdRs) and their modifications from as few as 5-20 cells. Applying FLORA-seq to mouse hematopoiesis revealed 50 high-variance isodecoders whose expression profiles recapitulate known hematopoietic cell types and correlate with differentiation trajectories. At the isoacceptor level, tRNA pools are largely stable within hematopoietic stem and progenitor cells (HSPCs), showing only subtle, specific variations, but become both distinct from HSPCs and internally stable within each terminally differentiated lineage. We further detected dynamic changes in tdR ratios and modification patterns, underscoring precise tRNA regulation during differentiation. Crucially, analysis of 54 endogenous tRNA isodecoders and their engineered suppressor counterparts showed that efficient premature termination codon readthrough preferentially arises from highly expressed cognate isodecoders. This correlation provides a rational framework for prioritizing suppressor tRNA candidates and implies non-redundant functions for individual isodecoders.

molecular biology↗

BioClaw: Human-Bot Research Collaboration Ecosystems in Group Chats

Day-to-day research discussions in group chats often generate hypotheses, analysis requests, and interpretation decisions, yet executing those analyses still requires researchers to leave the conversation and rely on fragmented local tools, databases, visualization software, and literature search engines. In this work, we present BioClaw, a human-bot research collaboration ecosystem that converts natural-language requests in group conversations into tool-grounded analyses executed within isolated Docker containers. Deployed across 8 messaging platforms, BioClaw turns each group chat into a persistent execution workspace. Its design combines multi-channel orchestration, per-group state and workspace management, and isolated containerized execution for reliable shared use over long-lived conversations. To support practical research workflows, BioClaw combines containerized execution with preinstalled 31 biomedical tools and 95+ skills. The application of BioClaw spans various biomedical domains (e.g., genomics, clinics, structural biology) and data modalities (e.g., sequencing data, EHR data, protein structure data). These results establish the viability of embedding executable, tool-rich agent workflows within shared digital workspaces, positioning group chats as a transformative paradigm for collaborative scientific discovery and innovation.

bioinformatics↗

Retinoic acid resolves the conflict between X-chromosome inactivation and pluripotency program in female cleavage-stage embryos

The tight coupling of X-chromosome inactivation (XCI) and pluripotency is a paradigm of holistic developmental regulation, and their inverse correlation enables XCI establishment during implantation. In contrast, the co-establishment of imprinted XCI (iXCI) and pluripotency program in female preimplantation embryos challenges the holistic pattern, but how embryos coordinate the two remains unknown. Here, we find that Nanog during the cleavage stage strongly represses the co-upregulated Rnf12-Xist axis, the triggering signaling of iXCI, creating a conflict that threatens iXCI. We identify retinoic acid (RA) as the coordinator that resolves the conflict and safeguards iXCI. RA activates its receptor RARG to evict NANOG from Rnf12 5region, avoiding NANOGs threat. In vivo, either maternal vitamin A deficiency or embryonic RA synthesis defects results in impaired iXCI and female-biased embryonic lethality. Thus, we highlight RA as a master regulator to holistically balance iXCI and pluripotency during cleavage stages, thereby ensuring proper female embryogenesis.

developmental biology↗

MTB-KB: A Curated Knowledgebase of Mycobacterium tuberculosis Related Studies

Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), has regained its position as the worlds leading killer among infectious diseases. Despite extensive research progress across epidemiology, diagnosis, drug development, treatment regimens, vaccines, drug resistance, virulence factors, and immune mechanisms, MTB-related knowledge remains fragmented across thousands of publications, limiting its effective use. To address this gap, we present MTB-KB, a literature-curated knowledgebase that systematically integrates high-impact findings from eight major sections of TB research. The current release contains 75,170 associations from 1,246 publications, covering 18,439 entities standardized using authoritative databases and WHO-endorsed classifications. A central feature is the interactive knowledge graph, which links cross-section associations to reveal and infer MTB-host interactions, treatment strategies, and vaccine development opportunities. MTB-KB also provides a user-friendly interface with browsing, advanced search, and statistical visualization. Overall, by consolidating dispersed MTB knowledge into a structured and accessible platform, MTB-KB provides a valuable resource for researchers, clinicians, and policymakers, supporting both basic and clinical TB research, enabling evidence-based TB prevention, diagnosis, and treatment, and contributing to global elimination efforts. MTB-KB is accessible at https://ngdc.cncb.ac.cn/mtbkb/.

bioinformatics↗

Connectome-based spatial statistics enabling large-scale population analyses of human connectome across cohorts

Large-scale population analyses of structural connectome organization remain challenging because of cross-subject alignment, pathway interpretability and computational burden. No widely adopted standard exists for systematic evaluation across processing methods. We developed connectome-based spatial statistics (CBSS), a scalable framework for anatomically aligned and functionally informed quantification of white-matter microstructure that yields atlas-defined pathways organized into 13 functional networks. Using data from 56,510 UK Biobank participants together with five independent lifespan cohorts, we evaluated the streamline-, voxel- and network-level measures in the aspects of reliability, heritability, structure-function coupling, cognitive and behavioral prediction, brain aging patterns and lifespan trajectories across cohorts. The systematic evaluation workflow compares population-level white-matter representations across methods, spatial scales, tasks and datasets. The results support CBSS as a common connectome reference for large-scale, cross-cohort diffusion MRI studies.

neuroscience↗