Biology subjects

Wang, K.

Publications and source records attributed to Wang, K..

At least 127 records · Page 7Linked to original sources

bioRxiv2025

A multisensory, bidirectional, valence encoder guides behavioral decisions

A key function of the brain is to categorize sensory cues as repulsive or attractive and respond accordingly. While we have some understanding of how sensory information is processed in the sensory periphery, the classification of cues according to valence in central brain circuits is less well understood. Here, we addressed this question in the Drosophila larva, where we could leverage the synaptic resolution connectome to determine where innate and learnt information from distinct aversive and appetitive sensory modalities converges; and combine this with imaging and manipulation of neural activity to determine how valence information is encoded and used to guide navigation. We found that information from multiple innately aversive and attractive sensory modalities converges onto a common output neuron of the learning circuit, specifically the Mushroom Body output neuron, MBON-m1. We discovered that this neuron is required for navigating both attractive odor and aversive temperature cues and is activated by attractive cues, such as food odour and sugar, and inhibited by different aversive cues, such as cooling, salt, or non-food odors. Together, our study reveals a neuron that bi-directionally encodes valence and controls actions.

neuroscience↗

bioRxiv2025

Combining brainwide activity imaging and electron microscopy reveals novel nociceptive circuits

To understand how brains work, it is necessary to connect neural activity to synaptic-resolution circuit architecture. Recent advances in light-sheet microscopy (LSM) enable whole-brain, cellular-resolution imaging of activity of all neuronal cell bodies, however, most neurons from such datasets cannot be identified. In most organisms, neurons are identifiable based on their projections (and not based on their cell body position) which, when densely labelled, cannot be resolved using LSM. Here, we present a novel methodology to overcome this by combining whole-brain activity imaging with subsequent volume electron microscopy imaging of the same brain to visualise neuronal projections and identify neurons with interesting activity. We used this approach to identify brain neurons that process input from multisensory (nociceptive and mechanosensory) Basin interneurons that trigger vigorous escape in Drosophila larvae in response to threatening somatosensory stimuli. After whole-brain imaging of neuronal activity during Basin activation, we imaged the same brain with an enhanced focused ion-beam electron microscope (eFIB-SEM). We registered the functional and anatomical volumes and reconstructed (in the eFIB-SEM volume) the projections of neurons that responded to Basin activation to determine their developmental lineage and identity. This revealed a distributed network for processing threatening somatosensory stimuli that trigger vigorous escape spanning 25 distinct lineages and many distinct brain areas, and included direct brain targets of Basin neurons that integrate somatosensory information with other modalities, as well as brain output neurons (descending neurons [DN]) that likely contribute to action-selection. Our workflow provides a powerful framework for mapping neuronal activity onto structure across an entire brain, yielding novel insights into the distributed central processing of noxious stimuli.

neuroscience↗

bioRxiv2025

Evolutionary patterns and repeated adaptive strategies of deep-sea anemones

Sea anemones occupy the full depth of the oceans, yet their evolutionary patterns and adaptive strategies to the enigmatic deep sea have remained contentious and poorly resolved. Here, we assemble genomes (n = 13) and transcriptomes for 15 species collected between 432 and 6,000 m and integrate them with all publicly available actiniarian data. Phylogenomic analyses reveal a mosaic topology among deep-sea and shallow-water clades. Using a novel framework that contrasts convergent gene-loss patterns, we show that a large number of light-associated gene families-- including the complete circadian toolkit--were independently deleted after lineages entered the aphotic realm, whereas comparable loss in shallow taxa is negligible, providing decisive support for a shallow-water origin followed by multiple descents. Intriguingly, some deep-sea lineages further streamline energy budgets by recurrent loss or pseudogenisation of key meiotic genes (e.g., Meiosin, Ythdc2, Spo11, Rad21, Mlh3), indicating a shift towards asexual reproduction. Despite this extensive genomic erosion, deep-sea anemones exhibit sophisticated molecular tuning: specific amino-acid substitutions enhance protein stability and activity under deep-sea conditions, while selective expansions of gene families related to neural excitability, membrane systems, etc., likely mitigate the suppressive environmental effects on vital physiological processes. Enzyme activity assays in the yeast system confirm that the deep-sea variants exhibit superior activity and enhanced growth at 4{degrees}C. These results define a "loss-optimization-innovation" triad that underlies bathymetric adaptations and may apply to other deep-sea fauna worldwide.

evolutionary biology↗

bioRxiv2025

Single-Cell Integration of Chromatin Accessibility and Transcriptomics Reveals Regulatory Networks in Ovarian Tumor-Infiltrating Adaptive NK Cells

Natural killer (NK) cells are traditionally recognized for their rapid, non-specific responses against virus-infected or malignantly transformed cells, functioning as key effectors of innate immunity. However, a distinct subset known as adaptive NK (aNK) cells has been shown to acquire memory-like properties following viral infections, indicating their capacity for antigen-specific immune recall. Intriguingly, aNK cells have also been identified within the tumor microenvironment, where they can mediate tumor-specific recall responses. Yet, the regulatory mechanisms governing their function in tumor-infiltrating aNK cells remain largely undefined. In this study, we integrated publicly available multiomics datasets from ovarian cancer, including single-cell chromatin accessibility (scATAC-seq) and single-cell RNA sequencing (scRNA-seq), to identify chromatin-accessible regions and construct transcription factors (TF)-gene regulatory networks. To validate and extend these findings, we performed Smart-seq3 on NK cells isolated from ovarian tumors and applied SCENIC analysis to identify TF-driven gene regulation. By integrating results from both analyses, we identified PRDM1 and STAT2 as key TFs, along with their downstream targets CRCP and MTFP1, specifically enriched in tumor-infiltrating aNK cells. The expression levels of CRCP and MTFP1 positively correlated with NK cell infiltration in ovarian cancer tissues, suggesting their potential functions in supporting tumor-specific NK cell memory responses. In addition, external validation using data from the PROMIX clinical trial demonstrated that PRDM1 and STAT2 expression levels are positively associated with both overall survival and aNK cell-associated transcriptional features. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/676040v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@6df026org.highwire.dtl.DTLVardef@1b16dc8org.highwire.dtl.DTLVardef@19e916borg.highwire.dtl.DTLVardef@15d431a_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

Shared molecular consequences of epigenetic machinery disruption in neuronal progenitors

The Mendelian disorders of the epigenetic machinery (MDEMs) are an emerging cause of intellectual disability and growth abnormalities, which commonly disrupt hippocampal function. To investigate consequences of epigenetic machinery (EM) disruption during neurodevelopment, we systematically knocked out (KO) EM factors in neuronal progenitors isolated from the murine hippocampus and established a neurodifferentiation model to interrogate their functions. We then profiled gene expression and DNA methylation (DNAm) in the EM-KOs using RNA sequencing and Nanopore long-read DNA sequencing. While Dnmt1-KO induced extensive DNAm alterations, Kmt2a-KO had little effect on methylation. Nevertheless, the disruption of Kmt2a and Dnmt1 produced strikingly convergent transcriptional changes. Loss of either EM factor led to premature neuronal differentiation, partially explaining this convergence, and MYC appeared as a shared regulatory node linked to downregulation of cell-cycle programs in these cells. Extending our methylation analysis to 46 EM genes, we found that loss of DNA methyltransferases induced the strongest DNAm changes, whereas other EM-KOs had subtle or negligible effects. However, clustering of EM-KOs based on promoter DNAm levels revealed three distinct EM subgroups, of which two were enriched for interactions with the DNAm machinery. Allele-specific analysis of DNAm further identified a single differentially methylated region shared across the 46 EM-KOs, localized to the FVB allele over the Zic4 3UTR. Furthermore, Zic4 overexpression appears to maintain the neuronal progenitor state, suggesting functional relevance of this locus. Taken together, our results reveal both gene-specific and convergent effects across diverse EM-KOs and provide new insight into the molecular etiology of the MDEMs.

genomics↗

bioRxiv2025

A neuroendocrine principle: Pancreatic islets actively shape sympathetic innervation

Survival critically depends on maintaining blood glucose levels to provide essential energy, especially during emergencies such as the fight-or-flight response, when timely glucose control via neural integration is vital. However, pancreatic islets constitute only a small fraction of the pancreas and are dispersed throughout the organ, raising the fundamental question of how the nervous system coordinates synchronized control of multiple islets. Using whole-organ clearing and 3D imaging, we mapped pancreatic sympathetic innervation, revealing specialized anatomical integration between sympathetic nerves and islets. Transplanted islets intrinsically attracted sympathetic nerves independent of their native environment. Chronic islet injury disrupted sympathetic innervation and markedly impaired nerve regeneration after denervation. Sympathetic denervation markedly elevated islet-derived Reg2 and Reg3{beta}; administration of these proteins accelerated sympathetic regeneration and improved islet graft function. Our findings identify an islet-sympathetic architecture actively maintained by islets, uncovering an endocrine-driven mechanism for neural regulation, highlighting Reg2 and Reg3{beta} as therapeutic candidates for diabetes management.

neuroscience↗

bioRxiv2025

Lifestyle and transcriptional signatures associated with ethnicity/race-related variations in the functional connectome

Understanding the variation of functional architecture across individuals and populations is fundamental to advancing our knowledge of human health and behaviour. Yet, while functional organization differences related to ethnicity/race are consistently reported, their underlying mechanisms remain poorly understood. Here, we apply precision individualized functional mapping to systematically investigate ethnicity/race-related differences in the brains intrinsic organization and their associations with lifestyle and transcriptional signatures. We show that variations in network topography and functional connectivity across ethnic/racial groups follow a hierarchical sensorimotor- association axis and are constrained by brain morphology. Importantly, we identify lifestyle factors-- particularly education and substance use--that significantly mediate these associations between ethnicity/race and functional connectivity. Leveraging human brain gene expression data, we further demonstrate that cortical transcriptional patterns are spatially aligned with ethnicity/race-related variability in functional connectivity. Gene ontology analyses of associated genes reveal significant enrichment in biological processes such as synaptic signalling and neuronal system development. Together, these findings uncover a multi-layered framework linking ethnicity/race-related differences in brain function to structural constraints, lifestyle influences, and molecular signatures, and advance a more comprehensive and equitable understanding of human brain diversity.

neuroscience↗

bioRxiv2025

An Objective Detection Method for Tinnitus using Memristors

Approximately 10-20% of the world population experiences tinnitus, which is increased with age and comorbid with frustration, annoyance, anxiety, depression, cognitive dysfunction, insomnia and stress. The underlying mechanisms of tinnitus remain largely unknown and there are no quantifiable biomarkers, making this prevalent disorder a global burden. There are no FDA-approved therapeutics and the current assessment mainly relies on self-reports (e.g., questionnaires), which underscore the need for diagnostic tools for tinnitus. Memristors, nanoscale electronic components mimicking synaptic plasticity, can monitor and control neuronal activity, hold transformative potential for detecting and characterizing tinnitus objectively. Here, we harvested the blood from human and mice with tinnitus, and engineered memristors via magnetron sputtering and made the functional layer with serum. Its core mechanism lies in regulating the reversible formation and rupture of conductive filaments which is formed by utilizing abnormally elevated glutamate concentrations in serum assisted Ag+ ions. This serum-based memristor achieves unprecedented discrimination between tinnitus and non-tinnitus individuals. Furthermore, this platform provides mechanistic insights into tinnitus pathogenesis, with potential implications in other neurological disorders.

pathology↗

bioRxiv2025

First Whole-Genome Chikungunya Virus Sequence Detected in Mosquitoes during the 2025 Foshan Outbreak: Evidence of Field Vector Infection and Transmission Potential in China

BackgroundSince July 2025, an outbreak of mosquito-borne chikungunya fever occurred in Foshan City, Guangdong Province, China. This was the second outbreak in China following the one that occurred in Dongguan City, Guangdong Province, in 2010. Moreover, the intensity of this outbreak was significantly greater than that of the previous one. Updates to 23 August, more than 10,000 human cases had been reported. Here, we present the first full genome sequence of the chikungunya virus (CHIKV) derived from field-trapped mosquitoes during the outbreak. MethodsAdult Aedes albopictus were BG-trap captured from residences and parklands in three hotspot towns with high density of confirmed human cases. Mosquitoes were morphologically identified and pooled by species, sex and environment types. RNA was extracted, screened by CHIKV RT-qPCR, then positive pools underwent sanger and whole-genome sequencing for complete sequences. Lineage and mutational profiles were inferred by maximum likelihood phylogenetic and comparison against human and mosquito genomes. The distribution of amino acid site mutations in different protein coding regions was also analyzed. ResultThrough 11 days of collection using 10 BG-traps, 2,803 mosquitoes were captured. 1569 (55.97%) female Ae. albopictus were divided into 77 pools and 9.09% (7/77) of the pools tested positive for CHIKV. The local Ae. albopictus minimum infection rate (MIR, per 1000 females) was 4.46, while the MIR for residences in Lecong Town was the highest at 9.17. The MIR for parklands was slight higher than for residences (4.60 vs. 4.30). All the 5 Ae. albopictus-derived complete CHIKV genome clustered within ECSA-Indian Ocean lineage genotype, closely related to human-derived genomes on 2025 Reunion Island. Amino-acid mutations E1-A226V/E2-L210Q were detected in the strains, which enhanced adaptability to Ae. albopictus and increased the transmission capacity. Novel mutation observed on E1 and E2 were totally consist to the patient-derived CHIKV in 2025 Reunion Island. ConclusionsIt was the first mosquito-derived CHIKV whole-genome during the 2025 Foshan outbreak, filling a critical gap between human case and entomological surveillance. Ae. albopictus was confirmed as the primary vector during the outbreak. The current outbreak CHIKV strain with particular amino-acid mutations had adapted to Ae. albopictus transmission. Compared to previous Chikungunya outbreaks over the past decade, the Foshan outbreak occurred earlier (early July), in a larger urban area (with a population of over 9.5 million), and with abundant breeding sites for the vector mosquito Ae. albopictus. However, the outbreak was quickly brought under control, with daily case numbers consistently decreasing, which is closely linked to the strong vector control measures implemented by the Chinese government in the early stages of the outbreak. Moreover, this event once again underscores the necessity of early monitoring of vector mosquitoes and the importance of implementing highly effective vector intervention measures as soon as possible after an outbreak occurs.

microbiology↗

bioRxiv2025

Structural connectome architecture and biological vulnerability shape cortical atrophy in cocaine use disorder

Cocaine use disorder (CUD) is prevalent and characterized by widespread gray matter atrophy across the cerebral cortex. However, it remains unclear whether and how connectome-based circuits and biological features shape these structural abnormalities. Here, we show that CUD-associated regional atrophy is constrained by the white matter (WM) structural connectome. Along these WM pathways, regions that share similar haemodynamic activity and molecular profiles are more likely to exhibit analogous atrophy patterns. By integrating the structural connectome with these multiple connectivity blueprints, we subsequently identify CUD epicenters and reveal that the prefrontal and visual cortices serve as core systems. Furthermore, we link these epicenters to cortical gene expression patterns and delineate CUD-related transcriptomic enrichment in biological processes, including inter-neuronal communication, synaptic function and neural homeostasis. Finally, we demonstrate that the spatial distribution of these epicenters correlates with cocaine craving-response maps derived from repeated transcranial magnetic stimulation and can track individual variations in clinical behavioural representations, suggesting their potential as key targets for therapeutic intervention. Together, our findings establish a structurally constrained framework for the spread of pathology underlying cortical atrophy in CUD, where initial perturbations propagate via structural connectome pathways to vulnerable regions shaped by neural activity and molecular landscapes.

neuroscience↗

bioRxiv2025

Spatiotemporal lineage mapping of tumor immune escape with eTRACER

The plasticity-first hypothesis posits that phenotypic plasticity emerges first in novel environments, followed by (epi)genetic changes that stabilize adaptive phenotypes. Whether tumor evolution follows this model, and how non-genetic mechanisms sustain long-term therapeutic resistance, remain unclear. Here, we develop eTRACER, an endogenously targeted, high-resolution and spatially-resolved CRISPR-Cas9 lineage-tracing system, to study tumor adaptation during longitudinal CD8+ T cell-mediated immunotherapy. Integrated clonal and single-cell transcriptomic analyses show that tumor immune evasion is governed by clonal state composition rather than clonal identity, arguing against selection from pre-existing genetic heterogeneity. Spatiotemporal lineage tracing reveals highly reversible state transitions prior to therapy, followed by consolidated epithelial-mesenchymal transition (EMT) during therapy. Single-cell multiomics identifies AP-1 as a key regulator of EMT stabilization and its inhibition enhances tumor sensitivity to immune killing. Together, these findings show that tumor plasticity precedes stable immune evasion, revealing an AP-1-centered mechanism underlying plasticity-first tumor evolution.

cancer biology↗

bioRxiv2025

GeoGAT-site: A Face-Centered Geometric Graph Attention Network for Protein-Protein Interface Prediction

Protein-protein interactions (PPIs) underpin the intricate machinery of cellular life, orchestrating processes from signal transduction to metabolic regulation, yet their precise interface prediction remains a cornerstone challenge in structural biology, demanding scalable computational paradigms that balance accuracy and efficiency. Herein, we present GeoGAT-site, a pioneering geometric graph attention network that leverages face-centered surface fingerprints extracted from three-dimensional protein architectures to forecast interaction sites. Diverging from conventional vertex-centric approaches, our face-centered methodology achieves a 3.64-fold acceleration in patch generation, mitigating computational bottlenecks while preserving granular surface descriptors. At its core, GeoGAT-site incorporates a bespoke attention mechanism that adaptively modulates inter-facial distances and normal vector orientations, synergistically integrating spatial geometries with physicochemical attributes for nuanced interface delineation. Harnessing a meticulously curated dataset of 150 million face-centered fingerprints from over 20,000 structurally diverse proteins, the model attains robust generalization across heterogeneous interaction motifs. Empirical validation on an independent cohort of 167 protein complexes yields a ROC AUC of 0.89, surpassing established benchmarks including MaSIF-site (0.845), SPPIDER (0.65), and PSIVER (0.63). By furnishing high-fidelity interface annotations, GeoGAT-site augments downstream structural modeling paradigms through targeted constraints, thereby providing a versatile scaffold for unraveling PPI dynamics with profound implications for therapeutic discovery, protein redesign, and molecular epistemology.

bioinformatics↗

bioRxiv2025

Evaluating Molecular Docking Programs for RNA-Targeted Ligand Screening: Influence of Binding Modes and Ligand Types

Structured RNAs are critical regulators of gene expression and represent promising targets for drug discovery. Despite this potential, structure-based virtual screening approaches--in particular, molecular docking--have been underutilized for RNA targets, largely due to the intrinsic conformational flexibility of RNA and the limited docking methods specifically optimized for RNA. In our study, we evaluated the efficacy of three widely used docking programs for RNA-ligand docking screens. The performance of these programs -- Glide, Gold, and rDock, were evaluated with the dataset of 25 diverse RNA targets with 432 small molecule RNA binders. We found that the performance was similar across docking methods, but consistent differences emerged among RNA classes. We further explored consensus scoring across both receptor conformations and docking methods, finding that selecting the average scores across docking programs and RNA structures yielded stable performance when compared to individual methods. Finally, clustering analysis of RNA binders revealed distinct scoring function preferences for different chemotypes of RNA binders, underscoring the potential for tailored scoring strategies in RNA-targeted drug discovery. Together, this work provides a comprehensive evaluation of the performance of available docking methods in different cases of RNA-ligand docking and offers practical guidance for improving virtual screening against structured RNAs.

bioinformatics↗

bioRxiv2025

Intravital Multimodal Imaging of Human Cortical Organoids for Chronic Stroke Treatment in Mice

Chronic stroke leads to enduring neurological deficits and remains a major clinical challenge. Human induced pluripotent stem cell (hiPSC)-derived cortical organoids (COs) offer promise for regenerative therapies, yet their application in chronic stroke remains understudied, in part due to limited tools for monitoring graft in vivo. Here, we present a Multimodal Imaging Platform for Organoid Tracking (MIPOT), which integrates MRI, bioluminescence imaging, light microscopy, and two-photon fluorescence microscopy to noninvasively track transplanted COs in the post-stroke brain over time. Using MIPOT, we verified precise delivery of COs into cleaned stroke cavities, observed progressive declines in viability within the first 10 days, and introduced labeling methods for functional in vivo tracking of COs at subcellular resolution. By 4 weeks post-transplantation, histological analysis revealed survival of COs in the cerebral cortex. Notably, COs engrafted into the hippocampus displayed enhanced maturation, underscoring the role of local microenvironments in graft integration. MIPOT enables dynamic, noninvasive evaluation of hiPSC COs in chronic stroke, providing a foundation for mechanistic studies and translational development of organoid-based therapies.

neuroscience↗

bioRxiv2025

BiGER: Bayesian Rank Aggregation in Genomics with Extended Ranking Schemes

With the rise of large-scale genomic studies, large gene lists targeting important diseases are increasingly common. While evaluating each study individually gives valuable insights on specific samples and study designs, the wealth of available evidence in the literature calls for robust and efficient meta-analytic methods. Crucially, the diverse assumptions and experimental protocols underlying different studies require a flexible but rigorous method for aggregation. To address these issues, we propose BiGER, a fast and accurate Bayesian rank aggregation method for the inference of latent global rankings. Unlike existing methods in the field, BiGER accommodates mixed gene lists with top-ranked and top-unranked genes as well as bottom-tied and missing genes, by design. Using a Bayesian hierarchical framework combined with variational inference, BiGER efficiently aggregates large-scale gene lists with high accuracy, while providing valuable insights into source-specific reliability for researchers. Through both simulated and real datasets, we show that BiGER is a useful tool for reliable meta-analysis in genomic studies.

genomics↗

bioRxiv2025

Sexually-dimorphic neurons in the Drosophila whole-brain connectome

Sexual dimorphisms in the brain arise from differences in cell number, morphology, and connectivity, and underlie sex-specific behaviors. In Drosophila, these differences are largely governed by the transcription factors Fruitless (Fru) and Doublesex (Dsx), expressed in neurons implicated in reproductive and social behaviors. However, how these neurons are integrated into the connectome to drive different behaviors in different sexes remains unclear. Here, we identify 98 putative Fru- or Dsx-expressing cell types ([~]1700 neurons) in the female whole-brain connectome by matching electron microscopy reconstructions to light microscopy images. We then analyze their connectivity within the whole-brain network. Fru/Dsx neurons are strongly interconnected, but are not part of a private network. We measure distances to the sensory periphery to examine multisensory interactions, and map connections to descending neurons that drive behavior. We further cluster Fru/Dsx neurons based on whole-brain connectivity, and uncover functional groupings. We analyze a subset of strongly connected Fru/Dsx neurons to make functional predictions, and test some of these with experiments. Together, this work provides a brain-wide framework for understanding the organization of sexually dimorphic circuits and establishes a resource for dissecting the neural basis of social and sexual behaviors.

neuroscience↗

bioRxiv2025

Towards Unified Neural Decoding with Brain Functional Network Modeling

Recent achievements in implantable brain-computer interfaces (iBCIs) have demonstrated the potential to decode cognitive and motor behaviors with intracranial brain recordings; however, individual physiological and electrode implantation heterogeneities have constrained current approaches to neural decoding within single individuals, rendering interindividual neural decoding elusive. Here, we present Multi-individual Brain Region-Aggregated Network (MIBRAIN), a neural decoding framework that constructs a whole functional brain network model by integrating intracranial neurophysiological recordings across multiple individuals. MIBRAIN leverages self-supervised learning to derive generalized neural prototypes and supports group-level analysis of brain-region interactions and inter-subject neural synchrony. To validate our framework, we recorded stereoelectroencephalography (sEEG) signals from a cohort of individuals performing Mandarin syllable articulation. Both real-time online and offline decoding experiments demonstrated significant improvements in both audible and silent articulation decoding, enhanced decoding accuracy with increased multi-subject data integration, and effective generalization to unseen subjects. Furthermore, neural predictions for regions without direct electrode coverage were validated against authentic neural data. Overall, this framework paves the way for robust neural decoding across individuals and offers insights for practical clinical applications.

neuroscience↗

bioRxiv2025

Multiomics Reveals Compartmentalized Immune Responses and Tissue-Vascular Signatures in Lyme Disease

Lyme disease (LD) is growing in incidence, with nearly 500,000 cases diagnosed annually in the United States. Despite treatment, some patients experience persistent symptoms. The immune mechanisms underlying LD remain poorly understood. We conducted a multiomic longitudinal analysis of 49 LD patients and matched controls, integrating plasma proteomics, metabolomics, PBMC immunophenotyping, and a meta-analysis of skin lesions. We identified compartmentalized immune responses in acute LD, with coordinated alterations in circulating plasma proteins and metabolites linked to endothelial barrier stability, metabolic reprogramming, and symptom severity, predominantly traced to tissue and vascular immune processes at the site of infection. In contrast, PBMCs remained largely quiescent, revealing a disconnect between localized tissue responses and systemic immunity. These findings provide novel insights into LD pathophysiology and highlight the potential for diagnostics leveraging tissue and vascular immune markers detectable in blood. They also provide a resource for biomarker discovery and predictive modeling to improve LD management.

immunology↗