Biology subjects

Tang, D.

Publications and source records attributed to Tang, D..

At least 19 recordsLinked to original sources

bioRxiv2026

Recurrent mitotic error and purifying selection shape chromosomal mosaicism across human tissues

Mosaic chromosomal alterations (mCAs) have been extensively studied in cancer and clonal hematopoiesis but less so in healthy solid tissues. Here, we characterized mCAs in 19 tissues across 25 donors (aged 42-89+ years) by analyzing >200x whole-genome sequencing data generated by the Somatic Mosaicism across Human Tissues (SMaHT) Network. Across 722 tissue samples, we identified 1,008 autosomal mCAs >1 Mb in length and ubiquitous losses of sex chromosomes. Surprisingly, the highest levels of Y chromosome loss in males (5-10% cell fraction in elderly donors) were observed in the lung, adrenal gland, and heart. These tissues also tended to experience more X loss in females, revealing a gradient of mitotic error burden across human tissues. Autosomal aneuploidies displayed distinct tissue-specific patterns indicative of negative selection against most events, except in the adrenal gland, in which low-level aneuploidy was pervasive. In contrast to the adrenal gland, testis rarely harbored aneuploidies but frequently experienced low-level copy-neutral loss of heterozygosity (CN-LOH), suggesting increased mitotic recombination in spermatogonial stem cells. Recurrent X chromosome losses within tissues of female donors exhibited allelic skews explained by a combination of genetic and epigenetic effects. Together, these results show that the chromosomal landscape of aging human tissues is shaped by genetics and recurrent mutations, most but not all of which are held in check by purifying selection.

genomics↗

bioRxiv2026

Oral somatosensation shapes lingual muscle maps in macaque orofacial primary motor cortex

Oral behaviors such as chewing, swallowing, and speech depend on continuous sensory feedback from the tongue and oral tissues. Yet how oral somatosensation shapes motor cortical output to drive individual tongue muscles remains unknown. We combined electrical stimulation of 96 sites in the orofacial primary motor cortex (M1) with electromyographic (EMG) recordings from six tongue muscles in awake rhesus macaques (Macaca mulatta). Cortical motor maps of evoked muscle activity were evaluated under three oral sensory conditions: intact sensation, combined oral sensory nerve block, and selective preservation of tongue sensation. Orofacial M1 has a broadly distributed, strongly overlapping, and bilateral organization of individual tongue muscle representations. Under altered sensation, spatial reorganization, attenuation, and enhancement of cortical-to-muscle output emerged within a fast timescale. Selectively preserving tongue sensation neither restored the intact pattern, nor reproduced the combined nerve block pattern; instead, it generated a spatially distinct configuration of cortical-to-muscle outputs. Together, these findings demonstrate muscle-level, input-specific, and dynamic sensory shaping in orofacial M1, establishing oral somatosensory input as an active determinant of tongue-muscle output, rather than a peripheral modulator. The rapid reorganization suggests that altered sensation qualitatively reweights existing sensorimotor pathways, rather than merely scaling cortical output up or down, such that its disruption could immediately degrade tongue muscle coordination while enabling adaptation to sensory loss.

neuroscience↗

bioRxiv2026

Low Intensity Multi-Channel Steering TMS Array for Network Level Neuromodulation

Objective: Low-intensity transcranial magnetic stimulation (LI-TMS) is being investigated as a gel-free alternative to transcranial electrical stimulation (tES), but existing systems remain almost exclusively single-channel and cannot electronically steer the induced electric field. We present the design, modeling, and experimental measurement of a wearable whole-head, multichannel, steerable LI-TMS array. Methods: The system comprises a 102-channel conformal coil array with independently controlled drivers capable of arbitrary waveform synthesis, together with a boundary element fast multipole method (BEM-FMM) framework that computes the coil currents required to produce prescribed cortical field patterns. A 12-channel prototype was characterized by coil-current, electric-field, and thermal measurements. Results: The prototype produced a peak primary electric field of approximately 1 V/m measured in air 4 cm from the inner helmet surface. Whole-array modeling attained cortical fields of up to 1.5 V/m, reproduced the field distribution of a clinically validated low-intensity stimulator to within 3%-5%, and demonstrated focal targeting of the dorsolateral prefrontal cortex, simultaneous delivery of electric field to the default mode network nodes, and synthesis of electric fields following the traveling alpha wave. Conclusion: Electronically steerable, whole-head LI-TMS is feasible using accessible microprocessor-controlled power electronics. Significance: The array reaches the cortical field regime of tES without scalp contact or the associated shunting of current through the scalp, offering a route to testing network-level, phaselocked weak-field neuromodulation.

bioengineering↗

bioRxiv2026

STAG2 Maintains Chromatin Compartmentalization and Represses Regulatory Element Contact to Promote Oncogenic Signaling in Muscle Invasive Bladder Cancer

Contrary to other cancer types, stromal antigen 2 (STAG2) expression is associated with shorter survival and an invasive phenotype in muscle invasive bladder cancer (MIBC). As a cohesin complex component, STAG2 regulates genome organization and cell type-specific transcription, yet its mechanistic role in MIBC remains unclear. Here, we uncover mechanisms through which STAG2 coordinates chromatin architecture and gene regulation in MIBC. Modulation of STAG2 rewired chromatin architecture, altering chromatin contacts and compartmentalization, increasing promoter-enhancer interactions, and reducing short-ranged chromatin loops. At specific gene loci, we discovered that STAG2 has context-specific activating and repressive regulatory functions. At the STAG2-activated gene ABCA1, STAG2 maintained A-compartment chromatin and high levels of promoter acetylation, indicators of active transcription. STAG2 KO resulted in loss of promoter acetylation, a shift from A to B compartment chromatin, and increased occupancy of the co-repressor TRIM28, resulting in ABCA1 downregulation and diminished invasive potential. Conversely, at the STAG2-repressed gene SPOCK3, STAG2 KO resulted in B to A compartment switching, aberrant formation of chromatin loops, and SPOCK3 upregulation. Treatment with EZH2 inhibitor tazemetostat augmented STAG2-KO induced SPOCK3 upregulation, suggesting a collaborative role of STAG2 and EZH2 in repressing Polycomb Repressive Complex 2 (PRC2) target genes. Altogether, our results indicate that STAG2 plays a multifaceted role in regulating gene expression in bladder cancer that is dictated by the epigenetic and chromatin landscape of the cells. These findings identify STAG2-dependent vulnerabilities and provide a rationale for therapeutic targeting of chromatin regulators in MIBC.

Cancer Biology↗

bioRxiv2026

Experimental Validation of Finite Element Models for Directional DBS: The Critical Role of Boundary Conditions on VTA Accuracy

ObjectiveComputational models and visualization toolboxes for Deep Brain Stimulation (DBS) increasingly rely on pre-computed electric field libraries to estimate the Volume of Tissue Activated (VTA). However, the boundary conditions (BCs) and source models used to generate these fields vary widely across studies, and there is currently no experimental consensus regarding which parameters most accurately reflect the physical device output. The objective of this study was to experimentally validate the electric potential distribution of directional DBS leads in order to determine the optimal Finite Element Method (FEM) configuration. ApproachThe voltage distribution surrounding a Boston Scientific Vercise Gevia directional lead was mapped in a saline phantom using a custom high-precision robotic scanning system. Experimental measurements were compared against six FEM configurations that varied in source formulation (Dirichlet vs. Neumann boundary conditions) and ground definitions. For each configuration, the resulting VTA volume was computed to assess the clinical impact of modeling assumptions. ResultsThe FEM configuration implementing a Dirichlet (voltage) boundary condition on the active contact with a grounded implantable pulse generator (IPG) surface demonstrated the highest accuracy, achieving a Symmetric Mean Absolute Percent Error (SMAPE) of less than 9% across all contact levels. In contrast, conventional current-controlled simulations employing Neumann boundary conditions with disparate ground definitions substantially overestimated electric field spread. Suboptimal boundary condition selection resulted in an approximate 67% overestimation of VTA volume (137 mm3 vs. 82 mm3) relative to the experimentally validated model. SignificanceAlthough clinical DBS systems operate as current sources, standard Neumann (current density) boundary conditions do not adequately represent the equipotential behavior of the electrode-tissue interface, resulting in nearly a two-fold error in predicted VTA volume. To improve the validity of predictive clinical models, we recommend the use of Dirichlet boundary conditions derived from the device operating impedance (V = Itarget x Zmeasured) rather than conventional current density specifications.

bioengineering↗

bioRxiv2026

Automated Knowledge Graph Construction for CAR T Cell Receptor Design via Hybrid Text Mining

Designing next-generation Chimeric Antigen Receptors (CARs) requires a systematic understanding of intracellular signaling domains and their downstream biological effects, yet no comprehensive knowledge resource currently exists for this purpose. Here, we present an automated workflow that integrates multiple natural language processing and large language model tools to extract biomolecular interactions from PubMed literature and assemble them into a CAR T cell signaling knowledge graph. Our pipeline combines REACH, INDRA, and Llama 3 across 15 targeted search queries, yielding a directed multi-relational graph of [~]7,500 unique interactions among [~]1,800 entities, including proteins, biological processes, and chemicals. We further demonstrate that queries incorporating biological process ontology terms retrieve more interaction-rich papers than protein-name-only searches, offering practical guidance for future literature mining efforts. The resulting knowledge base provides a structured foundation for predicting T cell phenotypes and prioritizing intracellular domain candidates for CAR design, with broader applicability to knowledge-driven inference in immunotherapy research.

synthetic biology↗

bioRxiv2026

Direct Reconstruction of DC Cortical Conductivity from Large-Scale Electron Microscopy Data

Electrical conductivity of cortical gray matter governs the magnitude and spatial distribution of electric fields generated by brain stimulation and intrinsic neuronal activity measured with M/EEG and intracortical recordings. However, reported macroscopic conductivity values vary by more than threefold, limiting the fidelity of bioelectromagnetic models and leaving unresolved whether this variability reflects measurement uncertainty or genuine structural heterogeneity of cortical tissue. Here, we present a multiscale computational framework that, for the first time, attempts to derive mesoscale conductivity maps of mouse visual cortex at 50-{micro}m resolution directly from large-volume, segmented nanometer-scale electron microscopy data. The Minnie 65 subvolume of the MICrONS dataset is accurately subdivided into 1,224 50-{micro}m cubic blocks. Each block contains, on average, 40-50 million membrane facets of a highly convoluted and dense cellular structure. Three orthogonal electrode pairs are applied to each isolated block to estimate the three principal components of the conductivity tensor. Quasistatic electric modeling is enabled by an iterative boundary-element fast multipole method (BEM-FMM) under the approximation of non-conducting membranes (DC conductivity). Spatially averaged conductivity values predicted by our framework agree well with prior low-resolution measurements in rats, validating the approach. At the same time, the resulting mesoscale maps reveal pronounced conductivity granularity at 50-100 {micro}m scales as well as significant variations in both radial and tangential directions. These results indicate that mesoscale conductivity heterogeneity could be an intrinsic structural property of the cortex. Limitations and extensions of this study are discussed in detail.

neuroscience↗

bioRxiv2026

Structural profiling of the pneumolysin epitope landscape uncovers a cross-species neutralising site across cholesterol-dependent cytolysins

Streptococcus pneumoniae remains a major public health concern, largely due to the limited serotype coverage and other constraints of pneumococcal conjugate vaccines, as well as the increasing antimicrobial resistance among circulating strains. In the pursuit of protein-based pneumococcal vaccines, pneumolysin (PLY), a secreted multifunctional cholesterol-dependent cytolysin, represents a promising target. To date, the relationship between the B-cell epitope landscape and neutralising PLY-specific antibody responses has remained elusive, hindering the rational design of effective PLY-based vaccines. Using a panel of PLY-specific monoclonal antibodies, functional assays, multimodal protein mass spectrometry and data-driven computational modelling, we mapped the structural epitope landscape of native PLY and linked epitope-paratope interactions to neutralising potency. We further refined and structurally characterised a protective cross-species epitope conserved among homologous cholesterol-dependent cytolysins (CDC). This epitope provides a promising foundation for rational, epitope-focused vaccine design, offering a pathway toward species-independent vaccines targeting the CDC protein superfamily.

immunology↗

bioRxiv2026

Are Synaptic Clefts Directionally Oriented?

Synapses are fundamental building blocks of cortical circuits, yet their geometry is typically regarded as a local property, independent of mesoscale architecture. The prevailing assumption is that synaptic clefts are isotropically oriented in space. Here, we test this assumption by analyzing approximately 117 million synaptic clefts from two independent 1 mm3 electron microscopy datasets: the human H01 middle temporal gyrus and the mouse MICrONS primary visual cortex, using three independent cleft-extraction methods. Across both volumes, we observe that synaptic cleft orientations are not randomly distributed, but instead show statistically significant and spatially coherent directional biases across cortical layers. This mesoscale anisotropy is conserved across species, yet is stronger and more consistent in human association cortex than in mouse sensory cortex, a difference that may reflect the expanded dendritic arbors and greater integrative demands of human pyramidal neurons. We propose that cleft orientation bias is a geometric consequence of the axonal and dendritic architecture that shapes synapse formation, representing a new candidate organizational feature of cortical microarchitecture with potential implications for circuit computation and neuromodulation. These findings motivate targeted physiological studies to determine whether synaptic orientation contributes causally to cortical function.

neuroscience↗

bioRxiv2025

EEG-based analyses reveal different temporal processing patterns in aesthetic evaluation

BackgroundExisting studies estimate harmony values using the color harmony model, but how these values are reflected in distinct neural stages (early automatic vs. late evaluative) and shape subjective preferences remains unexamined. MethodsTo fill this gap, we recorded behavioral and event-related potential data (N=30 adults, age: 29.20{+/-}2.38 years old) to examine whether the predictions of color harmony theory regarding harmonious vs. disharmonious color combinations align with neural activity from a color perception paradigm. ResultsBehavioral results showed that two-color combinations received higher aesthetic pleasantness ratings than three-color combinations, while the ratings for color harmony were relatively smaller than for disharmony. Univariate ERP analysis revealed that P1 amplitude for harmonious color was significantly higher than for disharmonious color, particularly when three colors were present. In contrast, the amplitude and latency of P2 were significantly impacted by the number of colors. Additionally, multivariate pattern analysis further demonstrated that neural activity reliably differentiated between harmonious vs. disharmonious color combinations and two-color vs. three-color combinations during both P1 and P2 time window. ConclusionsThese findings indicate that harmonious versus disharmonious color combinations subtly influenced early visual processing, while the number of colors used in the design had a stronger influence on aesthetic judgments.

neuroscience↗

bioRxiv2025

ppIRIS: deep learning for proteome-wide prediction of bacterial protein-protein interactions

Protein-protein interactions (PPIs) are central to cellular processes and host-pathogen dynamics, yet bacterial interactomes remain poorly mapped, especially for extracellular effectors and cross-species interactions. Experimental approaches provide only partial coverage, while existing computational methods often lack generalizability or are too resource-intensive for proteome-scale application. Here, we introduce ppIRIS (protein-protein Interaction Regression via Iterative Siamese networks), a lightweight deep learning model that integrates evolutionary and structural embeddings to predict PPIs directly from sequence. Trained on curated bacterial datasets, ppIRIS achieves state-of-the-art accuracy across benchmarks while enabling proteome-wide screening in minutes. Applied to Group A Streptococcus (GAS), ppIRIS revealed functional clusters linked to virulence pathways, including nutrient transport, stress response, and metal scavenging. For host-pathogen predictions, ppIRIS recovered 56.2% of known GAS-human plasma interactions with enrichment in complement, coagulation, and protease inhibition pathways. Experimental validation confirmed novel predictions, demonstrating the applicability of ppIRIS for systematic discovery of bacterial and cross-species PPIs. The software is freely available at github.com/lupiochi/ppIRIS.

bioinformatics↗

bioRxiv2025

Genes and environment profoundly affect the human virome

Many viruses have adapted to persist in infected humans for life1,2. Variable host control of their ongoing abundance ("load") can lead to clearance or disease3-5. We analyzed the viral DNA load of 31 common viruses in human blood and saliva using whole-genome sequencing data from UK Biobank (n=490,401), All of Us (n=414,817), and SPARK (n=12,519). Viral DNA load varied markedly with age, time of day, and season; most viruses were also present at greater abundance in men than in women. Human genetic variation at dozens of loci associated with DNA load of seven viruses: Epstein-Barr virus (EBV, 45 loci), human herpesvirus 7 (HHV-7, 37 loci), HHV-6B, Merkel cell polyomavirus, and three anelloviruses. Variation at the major histocompatibility complex (MHC) locus generated the strongest associations (p = 5.8x10-9 to 2.5x10-1459), which were specific to each virus. The HLA-B*08:01 allele also exhibited a host-virus genetic interaction with EBV subtype (p = 7.4x10-70). Other human genetic effects implicated genes encoding proteins that process peptides for antigen presentation, such as ERAP1 (HHV-7, p = 2.7x10-78) and ERAP2 (EBV, p = 4.6x10-111). Mendelian randomization analyses supported a strong causal effect of EBV DNA load on increased risk of Hodgkin lymphoma (p = 1.8x10-3) but not multiple sclerosis (p = 0.52). This suggests that higher chronic EBV load increases lymphoma risk, whereas associations of EBV infection with autoimmune conditions reflect host immune responses to particular viral epitopes.

genetics↗

bioRxiv2025

RNADecayCafe, a uniformly processed atlas of RNA half-life estimates across multiple human cell lines

RNA expression levels are partially determined by RNA stabilities. Long-lived RNAs accumulate to higher levels than rapidly degraded RNAs when transcribed at the same rate. The extent to which RNA decay contributes to differences in gene expression between genes in the same cell or between different cell types has not been extensively examined. This is in part because reproducible RNA half-life estimates from different biological contexts have not been broadly collected and curated. To address this, we have developed RNAdecayCafe, a database of high-quality RNA half-life estimates in multiple human cell lines. RNAdecayCafe makes use of pulse-label nucleotide recoding RNA-seq data (namely SLAM-seq and TimeLapse-seq), which we found to provide consistent and orthogonally validated half-life estimates. In total, RNAdecayCafe provides half-life estimates from 11 different human cell lines across 15 datasets and a total of 64 samples that were uniformly processed with a set of optimized bioinformatic tools we recently developed (the EZbakR suite). We showcase how this resource reveals the previously underappreciated role of RNA stability in shaping gene expression. RNAdecayCafe will provide a robust database for future studies of RNA decay.

bioinformatics↗

bioRxiv2025

Generating Bounded Linear Temporal Logic in Systems Biology with Large Language Models

Motivation: Translating natural language biological discoveries into formal temporal logic specifications for model verification demands expertise most experimentalists lack. Bounded Linear Temporal Logic (BLTL), which attaches explicit time bounds to temporal operators, is well suited for capturing biological dynamics. However, no automated solution exists for this translation, limiting the broader adoption of statistical model checking in systems biology. Results: We present NL2BLTL, the first framework to automate natural language to BLTL translation for systems biology. NL2BLTL combines a synthetic dataset of 5,000 NL-BLTL pairs built via grammar-guided generation, Chain-of-Thought preprocessing to resolve linguistic ambiguity in biological hypotheses, and grammar-constrained decoding to enforce syntactic validity and prevent hallucinated variables or time bounds. Evaluated on a newly curated biomedical NL-BLTL dataset drawn from published T cell and pancreatic cancer models, NL2BLTL framework achieves 84.62% exact match and 100% syntactic validity, outperforming GPT-4 by over 16 points and improving 14 points over the base fine-tuned model.

systems biology↗

bioRxiv2025

Ultra-high field strength electroporation enables efficient DNA transformation and genome editing in nontuberculous mycobacteria

Efficient DNA delivery is essential for genetic manipulation of mycobacteria and for dissecting their physiology, pathogenesis, and drug resistance. Although electroporation enables transformation efficiencies exceeding 105 CFU per {micro}g DNA in Mycobacterium smegmatis and Mycobacterium tuberculosis, it remains highly inefficient in many non-tuberculous mycobacteria (NTM), including Mycobacterium abscessus. Here, we discovered that NTM such as M. abscessus exhibit exceptional tolerance to ultra-high electric field strengths, and that hypertonic preconditioning partially protects cells from electroporation-induced damage. Using ultra-high electric field strength (3kV/mm) electroporation, we achieved dramatic improvements in plasmid transformation efficiency--up to 106-fold in M. abscessus, 83-fold in Mycobacterium marinum, and 24-fold in Mycobacterium kansasii--compared to standard conditions (1.25 kV/ mm). Transformation efficiency was further influenced by the choice of selectable marker. Ultra-high field strength electroporation also markedly enhanced allelic exchange in M. abscessus expressing Che9c RecET recombinases, increasing recovery of gene deletion mutants by over 1,000-fold relative to conventional electroporation. In parallel, oligonucleotide-mediated recombineering for targeted point mutations produced nearly 10,000-fold more mutants under ultra-high field conditions. Together, these findings establish ultra-high field electroporation as a robust, broadly applicable platform for genetic engineering of NTMs. This method substantially enhances transformation efficiency and enables construction of advanced genetic tools--including expression libraries and CRISPRi knockdown libraries--in species that have historically resisted genetic manipulation. ImportanceInfections caused by non-tuberculous mycobacteria (NTM), including Mycobacterium abscessus, are increasing globally, yet genetic manipulation of these pathogens remains technically challenging due to inefficient DNA delivery and low gene editing success. The ultra-high electric field strength electroporation strategy described here overcomes these barriers, enabling dramatic improvements in both transformation and genome editing efficiency. This advance paves the way for high-throughput functional genomics in NTMs, including the construction of genome-wide knockout, CRISPRi knockdown, and expression libraries. Broad adoption of this approach will accelerate discovery of genetic determinants of virulence and drug resistance, facilitating the development of antimicrobials and vaccines.

microbiology↗

bioRxiv2025

Design of a Streptolysin O Epitope-Centric Nanoparticle Vaccine Against Streptococcus pyogenes

Streptococcus pyogenes (Group A Streptococcus, GAS) is a significant human pathogen for which no licensed vaccine is currently available. Here, we report a de novo designed epitope-centric protein-based nanoparticle vaccine against GAS. By integrating structural mass spectrometry techniques and deep learning approaches, we re-engineered a protective epitope (D3m) present in domain 3 of streptolysin O, a prominent pore-forming toxin produced by GAS. D3m was displayed on the surface of a self-assembling icosahedral nanoparticle (D3m-NP) to enhance epitope presentation and immunogenicity. Mice immunised with D3m-NP mounted haemolysis-neutralising titres and displayed a more uniform, epitope-centric antibody response than those receiving the community-standard detoxified full-length streptolysin O. Our findings highlight a promising strategy for GAS vaccine development by combining multimodal protein mass spectrometry, protein design and a versatile protein-based nanoparticle vaccine platform.

immunology↗

bioRxiv2025

Cumulating MS Signal enables polyclonal antibody analysis

Unraveling the complexities of protein systems via Mass Spectrometry (MS), particularly polyclonal antibodies, demands innovative analytical strategies. Here, we introduce the cumulative MS score (cMS), a novel mathematical framework that transcends traditional spectrum-matching, integrating MS evidence across multiple sample injections to achieve robust de novo peptide sequencing annotation. This approach, shifting from isolated spectrum analysis to a holistic MS signal-based methodology, was rigorously evaluated and validated across diverse sample types and experimental conditions. We applied this framework to characterize a complex polyclonal antibody mixture of Streptococcus pyogenes M1 protein binders derived from intravenous immunoglobulin (IVIG), revealing predominant variable heavy (VH) and light (VL) chain subgroups consistent with established genetic studies. Furthermore, we successfully identified conserved complementarity-determining region (CDR) features and predicted stable antibody-antigen interactions through molecular dynamics simulations, demonstrating the methods potential for dissecting intricate antibody responses. This work establishes a powerful alternative to conventional tandem mass spectrometry MS/MS data analysis, enabling deeper insights into protein systems and paving the way for targeted therapeutic development.

bioinformatics↗

bioRxiv2025

GBM model refinement with literature curation, rule-based NLP, and LLMs

In this work, our goal was twofold: (1) improve an existing glioblastoma multiforme (GBM) executable mechanistic model and (2) evaluate the effectiveness traditional natural language processing (NLP) pipeline and the generative AI approach in the process of model improvement. We used a suite of graph metrics and tools for interaction filtering and classification to collect data and conduct the analysis. Our results suggest that a more comprehensive literature search is necessary to collect enough information through automated paper retrieval and interaction extraction. Additionally, we found that graph metrics present a promising approach for model refinement, as they can provide useful insights and guidance when selecting new information to be added to a mechanistic model.

systems biology↗