Biology subjects

Guan, X.

Publications and source records attributed to Guan, X..

At least 19 recordsLinked to original sources

bioRxiv2026

Metabolite-centric Knowledge Graph Unveils Predictive and Mechanistic Insights through Self-supervised Multimodal Learning

Metabolomics research is advancing toward a comprehensive view of metabolites and their biological functions, yet conventional, dictionary-like databases fall short of presenting these complexities. To overcome this limitation, we developed MetaKG, a metabolite-centric knowledge graph that integrates diverse chemical, biological, and semantic data, coupled with a global self-supervised multimodal learning framework that generates advanced embeddings (MetaKGE) for both predictive and mechanistic analyses. MetaKG outperforms existing models in standard representation learning metrics and across 12 external datasets. Furthermore, MetaKG refines existing database information by detecting misannotated labels and uncovering previously overlooked biochemical relationships. Its predictive capability naturally yields testable biochemical hypotheses, as demonstrated in studies of G6PD deficiency and colorectal cancer. By transforming passive, database-scale information into extractable knowledge and actionable insights, MetaKG paves the way for hypothesis-driven discovery in metabolomics and holds promise for informing future research in clinical biomarker identification and therapeutic development.

bioinformatics↗

bioRxiv2026

Deciphering Spatial Cellular Organization through RNA-Anchored Multi-Omics Deconvolution

Spatial technologies that jointly profile RNA and additional molecular layers provide a comprehensive view of tissue organization, yet their limited resolution results in measurements that reflect mixtures of multiple cell types. While RNA-based deconvolution methods are well established, incorporating co-profiled non-transcriptomic modalities without compromising cell-type identifiability remains an open challenge, as reliable references are largely restricted to transcriptomic data. Here we present SMODER, an RNA-anchored framework for spatial multi-omics deconvolution that treats transcriptomes as the primary determinant of cell identity while incorporating complementary molecular modalities in a constrained manner. By adopting an asymmetric integration strategy, SMODER preserves RNA-driven cell-type resolution and enables robust estimation of cell-type compositions across spatial locations. Across simulations and diverse spatial multi-omics datasets spanning protein, chromatin accessibility and histone modification assays, SMODER consistently outperforms existing methods in both accuracy and spatial coherence. Beyond deconvolution, SMODER denoises multi-omic signals and enables cell-type-aware analysis of regulatory programs. Application to spatial CUT\&Tag--RNA-seq and {RNA--ATAC-seq} data reveals spatially resolved epigenetic repression and cis-regulatory relationships linked to gene expression.

bioinformatics↗

bioRxiv2026

Benchmarking interface confidence as a selection criterion for computational nanobody design against survivin's BIR-domain groove

Designed binders are routinely filtered on predicted interface confidence, which reports how self-consistently a model places an interface, not where it lies. We designed 200 nanobody loops against the survivin BIR-domain groove, co-folded 196, and checked epitope contact in every predicted complex. Confidence showed no detectable association with epitope engagement ({rho} = +0.100, 95% CI -0.04 to +0.24, n = 196); its highest and lowest quartiles failed alike (odds ratio 0.97, 95% CI 0.41 to 2.26). It tracked instead the run's other confidence estimates ({rho} = +0.61). Twelve-seed replication separated two candidates the criteria had not: one reached the complete epitope in 10 of 12 runs, the other never. Across 155 predictions the top-ranked model was no better than one drawn at random from its five (P = 0.610), though only 3 of 31 failed on every model. Nothing was assayed; nb_cand_057 is an in silico candidate only.

bioinformatics↗

bioRxiv2026

Long-range transport of biomolecular condensates by Marangoni effect

How mesoscale cargos such as biomolecular condensates are transported and spatially positioned within cells remains a fundamental question in cell biology. During Caenorhabditis elegans zygote polarization, a substantial fraction of P granules undergoes persistent anterior-to-posterior motion that cannot be fully explained by dissolution-recondensation. Here, combining microfluidic reconstitution, quantitative micropipette aspiration and live-cell imaging, we show that a MEG-3 concentration gradient generates interfacial-tension asymmetry and drives the directed transport of PGL-3-RNA co-condensates in vitro and P granules in vivo through the Marangoni effect. This framework enables parameter-free quantitative predictions of condensate transport. Orthogonal molecular perturbations abolish or reverse directional migration, directly linking interfacial properties to transport behavior and establishing the specificity of this mechanism. Together, our findings identify the Marangoni effect as a previously unrecognized mechanism for intracellular transport of biomolecular condensates and provide direct causal evidence that condensate emergent properties can contribute to physiological organization.

biophysics↗

bioRxiv2026

Head-level lesion-symptom mapping of picture naming in vision-language models

Researchers in artificial intelligence increasingly intervene on language models to study how their functions are organized, silencing weights and attention components in ways reminiscent of the brain lesions long used to map language in post-stroke aphasia. Under this program of mechanistic interpretability, a common move is to ablate an attention head and read the resulting drop in a behavior as evidence that the head implements it. How much that move can establish about where a behavior is computed remains unclear, because a head whose removal disrupts a behavior is necessary for it but need not be the site where it is computed. We examined this question for the picture naming task, taking the loss of naming (anomia) that defines aphasia as the behavior of interest. Across six vision-language models, spanning three language backbones and a range of parameter scales, we ablated each attention head in turn during single-word picture naming and measured accuracy before and after. The degree of localization varied widely across models. In LLaVA-1.6-Vicuna-13B, a single early head (layer 0, head 20) was necessary: removing it alone reduced naming accuracy from 0.99 to 0.006. The same head was not sufficient, because retaining it while ablating the other 1{,}599 heads also produced 0\% accuracy. Two Mistral-backbone models (LLaVA-Mistral-7B and Idefics2-8B) had no critical head. An early-layer dependence was present in every model but varied in strength, whereas dependence on any single head ranged from dominant to absent. Within Qwen2.5-VL, a dominant head was present in the 7B model but not the 3B model, indicating that this concentration emerged with scale rather than being fixed across a model family, and it was not explained by attention type. These results show that ablating the head whose removal disrupts naming does not establish that the head computes the behavior, that the result generalizes across models, or that the behavior localizes to a head at all.

neuroscience↗

bioRxiv2026

Impaired proteostasis is an early feature of the diabetic heart in humans and mice

Diabetes and obesity increase cardiac lipid levels leading to cardiomyopathy and heart failure. We hypothesized that intermittent fasting would reduce cardiac lipid levels. Surprisingly, intermittent fasting increased myocardial triglyceride content, but rescued mortality and attenuated cardiomyopathy in mice overexpressing cardiomyocyte acyl-CoA synthetase 1 (MHC-ACSL1). Lipid overload caused cardiomyocyte accumulation of polyubiquitinated protein aggregates containing desmin, a scaffolding intermediate filament protein, which intermittent fasting prevented. Furthermore, intermittent fasting reversed elevated myocardial C16:0 ceramide content, and knockdown of ceramide synthase CerS5 and CerS6 reduced palmitate-induced protein aggregation, highlighting a role for C16:0 ceramides in this pathology. Conversely, impairing aggrephagy with cardiomyocyte-specific p62 ablation induced heart failure in mice fed a high-fat diet, with paradoxically reduced cardiac lipid content. Crucially, non-failing diabetic human hearts also exhibited protein aggregate pathology. Taken together, these results demonstrate that impaired proteostasis characterizes cardiomyopathy from cardiac lipid overload and identify a promising new therapeutic target for this condition.

molecular biology↗

bioRxiv2026

Foundation Model RNAGAN Enhances Biomedical Insight of Nasopharyngeal Carcinoma Metastasis

RNAGAN (version 2.0, https://github.com/ZhaozhengHou-HKU/RNAGAN-2.0.git) is a published foundation model that analyzes single-cell and bulk-level RNA sequencing samples and enables multiple applications that enhance medical insights. Here we applied this model to Nasopharyngeal Carcinoma (NPC) as in-context few-short format (i.e., the model was never trained with any NPC data). We conducted all four supported functions, which include sample stratification, vectorization, pseudo data generation, and marker identification. The results were then used for identifying metastatic NPC and to investigate mechanisms associated with NPC metastasis. Examination with stratification showed that the accuracy of RNAGAN results for evaluating the metastasis risk in NPC patients are comparable to or outcompeted recently published risk estimation linear prediction model. Vectorization results present consistency across multiple cohorts and RNAGAN model versions. In the task of identifying markers and mechanisms related to NPC metastasis, incorporating pseudo data substantially enhanced the representativeness of single-cohort-based differential expression (DE) analysis. Moreover, RNAGAN identified metastasis-related marker genes based on single cohort, were concordant with the ground truth obtained across multiple cohorts (p=1.05e-9). Regarding biomedical mechanisms, RNAGAN enabled second-order feature extraction, unveiling a remarkable domination of the protective function of adaptive immune responses (as indicated by IL21R levels) over the hazardous function of chronic, non-resolving innate inflammation (as indicated by S100A8 levels) against NPC metastasis after first-line treatment. This association demonstrates a high degree of consistency with the external cohort. This study demonstrates the utility of the foundation model RNAGAN in uncovering therapeutic insights for novel cancer types without extra training. We reveal a critical spatial mechanism preventing distant metastasis via humoral anti-tumor immunity in NPC. High S100A8 expression by innate antigen-presenting cells (APCs) triggers an inflammatory cascade promoting epithelial-mesenchymal transition (EMT) and metastasis. However, when germinal center IL21R+ B cells simultaneously colocalize with these innate signals, they override this suppressive tissue stress. Spatial analysis shows that a high S100A8/IL21R intersection within tumor regions strictly distinguishes treatment responders, whereas non-responders display spatial mismatch or S100A8+ hyper-infiltration. This coordinated innate-adaptive cross-talk sustains functional tertiary lymphoid structures (TLS) that mature IgG-secreting plasma cells, which opsonize and eliminate emerging EMT tumor cells before systemic escape. Consequently, while S100A8 alone is an unreliable prognosticator, its spatial colocalization with IL21R is a robust protective indicator overlooked by conventional bulk analysis methods.

cancer biology↗

bioRxiv2026

The HOG MAPK - Transcription Factor CsAtf1 - CsErg5B Regulatory Module Mediates Conidial Germination and Fludioxonil Sensitivity in Colletotrichum siamense

Colletotrichum siamense is a predominant causal agent of anthracnose in rubber tree and numerous economically important crops, causing severe yield losses worldwide. Conidial germination represents a critical early step for successful infection, while the high-osmolarity glycerol (HOG) MAPK pathway and ergosterol biosynthesis individually govern fungal development, stress adaptation and fungicide responses. However, the molecular crosstalk between these two modules remains largely elusive in phytopathogenic fungi. Here, we identified CsErg5B, a sterol C-22 desaturase homolog, as a direct target of the HOG- regulated transcription factor CsAtf1 in C. siamense. CsErg5B was indispensable for ergosterol biosynthesis, conidial germination, appressorium formation, and full virulence. The {Delta}CsErg5B mutant showed increased conidiation but severely impaired germination, and exhibited elevated resistance to fludioxonil while hypersensitivity to azole fungicides. Epistasis analysis using the {Delta}CsErg5B/{Delta}CsCyp51G1 double mutant - where CsCyp51G1 serves as another downstream target of CsAtf1 - revealed that CsErg5B functions as the predominant downstream effector of CsAtf1 in modulating conidial development and fludioxonil sensitivity. Furthermore, overexpression of CsErg5B significantly rescued the defects in conidial germination and fludioxonil sensitivity in both {Delta}CsAtf1 and {Delta}CsPbs2 mutants. Taken together, our findings uncover a HOG MAPK - CsAtf1 - CsErg5B regulatory axis that connects HOG MAPK signaling to ergosterol homeostasis, thereby governing conidial germination and fungicide sensitivity in C. siamense. This study provides novel insights into the regulatory network underlying fungal development and fungicide response, and offers promising molecular targets for the integrated management of plant anthracnose.

microbiology↗

bioRxiv2026

NAADP elicits two-pore channel currents by lifting Lsm12-mediated inhibition of PI(3,5)P2 activation

Mammalian two-pore channels (TPCs) are endolysosomal cation channels that regulate membrane trafficking and ionic homeostasis and have been strongly implicated in nicotinic acid adenine dinucleotide phosphate (NAADP) signaling. We previously identified Lsm12 as an NAADP receptor and TPC-interacting protein required for NAADP-evoked Ca2+ mobilization from acidic organelles; however, how NAADP-Lsm12 coupling regulates TPC gating has remained unclear. Here, we show that Lsm12 acts as a potent antagonist of phosphatidylinositol 3,5-bisphosphate [PI(3,5)P2]-dependent TPC activation. Purified Lsm12 strongly inhibited PI(3,5)P2-evoked currents of TPC1 and TPC2, and endogenous Lsm12 similarly suppressed TPC2 activity in cells. Mechanistically, Lsm12 reduces the apparent sensitivity of TPC2 to PI(3,5)P2 through a competitive mechanism that depends on the concentrations of both Lsm12 and PI(3,5)P2, as well as on Lsm12-TPC interaction. Importantly, NAADP specifically and dose-dependently reverses Lsm12-mediated inhibition, restoring TPC currents only in the presence of PI(3,5)P2 or an intact PI(3,5)P2-binding site on TPCs. Consistently, acute sequestration of endogenous PI(3,5)P2 reduces NAADP-evoked cytosolic Ca2+ signals. These findings support a model in which Lsm12 tonically restrains PI(3,5)P2-dependent TPC gating, whereas NAADP binding to Lsm12 relieves this inhibition to permit channel activation. Our study therefore establishes a mechanistic link between NAADP signaling and phosphoinositide-dependent TPC gating and provides a working model for understanding NAADP-evoked Ca2+ release from acidic stores.

cell biology↗

bioRxiv2026

RNAGAN: Train One and Get Four, Multipurpose Human RNA-Seq Analysis Tool with Enhanced Interpretability and Small Data Size Capability

The advent of artificial intelligence (AI) has brought revolutionary tools for biomedical transcriptomic (RNA-level) research. However, there are persistent constraints including limited interpretations with biomedical concepts such as functional pathways, small sample sizes and substantial time and computing power requirements for AI training. To overcome these limitations, we developed RNAGAN (https://github.com/ZhaozhengHou-HKU/RNAGAN-1.0.git), an AI tool with a generative adversarial network (GAN) structure with the objective of enhancing transcriptomic analysis. The network was established based on public human datasets comprising 4.6 million single cells from multiple organs and 5,900 sequenced samples of various cancer types with normal references. A specialized pathway neural layer was embedded to extract activities of predefined pathways from the Human Molecular Signatures Database (MSigDB), or newly learned pathways from single-cell data. The structure of RNAGAN (generator and discriminator) enables four applications after one shared training procedure: 1. single-cell and bulk-level patient stratification or differential diagnosis; 2. analysis of the gene and pathway markers in a selected disease; 3. pseudo data generation when sample size is limited for downstream analysis; 4. vectorization with gene and pathway-level features learned from multiple data sets. RNGAN contributes to the efficient utilization of limited data for transcriptomic studies.

bioinformatics↗

bioRxiv2026

Integrative Multi-Omics Analysis Identifies a Functional Enhancer Driving Tumorigenesis in Head and Neck Squamous Cell Carcinoma

Enhancer is a critical epigenetic feature in head and neck squamous cell carcinoma (HNSCC), yet the functional roles of individual enhancers remain poorly understood. Here, we conducted an integrative multi-omics analysis based on publicly available ATAC-seq, H3K27ac ChIP-seq, transcriptomic profiling, and genetic association datasets to systematically map HNSCC-associated enhancers and their target genes. Integrating ATAC-seq and H3K27ac ChIP-seq, we identified 20,362 enhancers and 18,040 enhancer-associated genes, highlighting widespread regulatory complexity. Functional characterization of the TERT-associated enhancer GH05J001312 (GRCh38/hg38: chr5:1312099-1317743) revealed strong transcriptional activity in HNSCC. CRISPR-mediated deletion of a core sequence significantly reduced TERT expression, impaired cellular proliferation in vitro, and suppressed tumor growth in vivo, confirming its role as a key cis-regulatory element. RNA-seq analysis of enhancer-edited cells uncovered 742 differentially expressed genes enriched in cancer-related pathways, including MAPK and IL-17 signaling, indicating a broad transcriptional impact. Collectively, our findings establish GH05J001312 as a functional enhancer driving oncogenic programs in HNSCC and suggest enhancer-targeted strategies as a potential therapeutic avenue.

cancer biology↗

bioRxiv2026

LRRC55 modulates BK channels to support Purkinje cell plasticity and motor coordination

Large-conductance Ca2+- and voltage-activated K+ (BK) channels are widely expressed, including in the brain where they shape neuronal excitability. Their physiological functions are strongly influenced by cell-type-specific auxiliary subunits. The auxiliary {gamma}3 subunit (LRRC55) enhances BK-channel activation by shifting voltage-dependent gating toward more negative potentials; however, its protein distribution and in vivo function remain unclear. Here, we generated knock-in mice carrying a C-terminal epitope tag on endogenous LRRC55 to map its expression, and Lrrc55 knockout mice to test its function. LRRC55 protein was selectively enriched in cerebellar Purkinje cells. Lrrc55 deletion produced ataxia-like impairments in gait, balance, and coordination. In acute slices, pharmacological BK-channel block with paxilline altered Purkinje cell simple- and complex-spike firing in wild-type mice, whereas these BK-dependent effects were largely absent in Lrrc55 knockouts, indicating that LRRC55 is required for BK channels to shape Purkinje cell firing under these conditions. Moreover, LRRC55 loss disrupted cerebellar synaptic plasticity, abolishing parallel fiber-Purkinje cell long-term potentiation and eliminating climbing fiber-Purkinje cell long-term depression, phenocopying paxilline in wild-type cells. Together, these results identify LRRC55 as a Purkinje-cell-enriched auxiliary subunit that is essential for BK-dependent excitability and plasticity and that supports normal cerebellar motor function.

neuroscience↗

bioRxiv2026

TCRAD: An End-to-End Framework for Antigen-Targeted T Cell Receptor Design

Understanding and engineering T-cell receptor (TCR) specificity is central to personalized immunotherapy and antigen discovery. However, while antigen-conditioned TCR design approaches have begun to emerge, most frameworks still focus on scoring candidate TCR-pMHC pairs, and achieving high hit rates in designing functional, target-reactive TCRs remains a key bottleneck. Here, we present TCRAD, a deep learning pipeline that performs de novo design of TCR CDR3{beta} sequences conditioned on antigenic peptides. TCRAD comprises three modules: Sequence Generation, Sequence Filtration, and Structure Prediction. TCRAD can effectively generate antigen-specific CDR3{beta} sequences, discriminate functional binders with high accuracy, and predict bound and unbound structures with performance comparable to or exceeding state-of-art methods. Experimental validation using the 1G4/NY-ESO-1 system demonstrated that the model can design novel functional TCRs capable of surface expression, specific pMHC binding, and that 17.2% candidates (5 of 29) elicit antigen-induced activation. Together, these results establish TCRAD as a powerful framework for TCR sequence design, offering a scalable path toward rational engineering of antigen-specific TCRs for cancer immunotherapy, vaccine development, and personalized immunotherapeutics.

bioinformatics↗

bioRxiv2026

Unifying constraints linking protein folding and native dynamics decoded from AlphaFold

The interplay between protein folding and native dynamics remains a central question in biophysics. Analyzing an extensive set of AlphaFold-predicted structures, we uncover a robust relationship between folding topology (contact order) and native dynamics (fluctuation entropy), showing that long-range contacts that slow folding also restrict conformational flexibility across protein sizes and taxonomic groups. Scaling analysis reveals that this relationship, together with its chain-length dependence, is consistent with power-law-like trends, reflecting common organizing constraints of protein architecture. Across species, increasing organismal complexity is associated with proteome-wide shifts toward lower contact order and higher fluctuation entropy. Together, evidence from folding, stability, and functional dynamics converges on unifying constraints, revealing an intrinsic physical organizing principle captured by AI models.

bioinformatics↗

bioRxiv2026

Natural variation of gibberellin levels in maize tissues across North America

Gibberellins (GA) are endogenous phytohormones that regulate growth and development throughout the plant lifecycle. While GA has been extensively studied under controlled conditions for their fundamental role in plant adaptation and agronomic trait development, field-based data on their natural variation across diverse agricultural genotypes and environments remains limited. To address this knowledge gap, we analyzed bioactive gibberellin A1 (GA1) and gibberellin A4 (GA4) across multiple maize hybrids grown in diverse field environments using high-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS). This study provides comprehensive quantitation of GA1 and GA4 levels in maize tissues across diverse commercial hybrids grown under standard agricultural practices, revealing hormonal variation due to genetic background and environmental conditions. Our findings demonstrate that GA1 and GA4 concentrations from conventional maize samples varied across tissue types and field sites. Analysis of variance components indicated that the site variation was statistically significant at the 5% significance level in five out of ten GA and tissue combinations, while the genetic component was significant only for GA4 in grain samples. Notably, significant interaction between hybrid and site was observed for both GA1 and GA4 in stalk tissue. Positive correlations between GA1 and GA4 were observed consistently across tissues except root. These results underscore the common metabolic pathways involved in regulating GA levels in maize and provide the first comprehensive dataset of GA1 and GA4 variation under real-world agricultural conditions. Our findings offer insights into the interplay between genetics, environment, and hormonal regulation in maize and suggest potential targets for breeding programs aimed at improving agronomic traits such as yield.

plant biology↗

bioRxiv2025

Developing a versatile technology for agroinfiltration in multiple plants

Agrobacterium-mediated transient transformation methods are widely used in plant science and molecular pharming. However, plant immune response and post-transcriptional gene silencing (PTGS) can compromise gene expression, limiting the adaptability of these methods across plant species. The lack of a robust reporter system further hinders advancements in agroinfiltration technology. To address these challenges, we developed a fungal bioluminescence pathway (FBP)-based reporter system that utilizes caffeic acid to generate self-sustained luminescence. By incorporating NahG and P19, our FBP assay enhances transient transformation efficiency in over 20 plant families, including major crops, vegetables, ornamental plants, and trees. Furthermore, we demonstrate its utility for assessing protein localization, interactions, and transcriptional regulation in multiple plant species, thereby broadening our understanding of gene function throughout the plant kingdom.

plant biology↗

bioRxiv2025

Enhance Memory CD8+ T Cell Formation via Downregulation of Hematopoietic Progenitor Kinase 1 and Sustained Mitochondrial Fitness

Memory CD8+ T cells are pivotal for long-term anti-tumor immunity due to their longevity and rapid response upon encountering tumor cells. Hematopoietic progenitor kinase 1 (HPK1), a member of the Ste20 family of kinases, restricts proximal T cell receptor (TCR) signaling and plays critical roles in T cell priming and activation. However, the impact of HPK1 on CD8+ T cell differentiation is not well understood. Here, we demonstrate that chimeric antigen receptor (CAR) T cells derived from patients lacking HPK1 exhibit a stronger memory phenotype. HPK1 deletion promotes the formation of precursor and central memory CD8+ T cells, resulting in superior and long-lasting antitumor activity in murine cancer models compared to WT mice. Additionally, HPK1 knockout induces metabolic reprogramming by enhancing oxidative phosphorylation (OXPHOS) and mitochondrial respiration complex activity. Mechanistically, HPK1 deletion downregulates mTOR signaling by reducing the phosphorylation of mTOR and S6. Increased mitophagy activity is observed in HPK1-depleted cells, with upregulation of key mitophagy regulators, including Pink1 and Bnip3l, maintaining mitochondrial fitness. Our study reveals that HPK1 regulates CD8+ T cell metabolic reprogramming, guiding cell differentiation and antitumor responses.

immunology↗

bioRxiv2025

Lamin A/C safeguards replication initiation by orchestrating chromatin accessibility and PCNA recruitment

Lamin A/C, a nuclear lamina protein, is essential for maintaining nuclear architecture, organizing chromatin and preserving genomic stability. However, its role in regulating DNA replication remains unclear. This study investigates how Lamin A/C regulates proper activation of replication origins by orchestrating the chromatin structure and recruitment of proliferating cell nuclear antigen (PCNA). We demonstrate that Lamin A/C stabilizes replication domains (RDs) by restricting chromatin mobility, preserving spatial organization, and maintaining accessibility. Furthermore, Lamin A/C interacts with PCNA and sequesters a pool of PCNA, to regulate its recruitment to replication machinery. The loss of Lamin A/C leads to an increase in chromatin dynamics, RD accessibility, and PCNA availability at RDs, which together trigger excessive activation of replication origins, leading to replication stress and DNA damage. These disruptions prolong the S phase and compromise genome stability, highlighting Lamin A/C as a critical gatekeeper of balanced replication initiation. Our findings reveal Lamin A/Cs dual role in chromatin organization and replication machinery regulation, offering valuable insights into its involvement in replication-associated diseases and potential therapeutic opportunities through targeting replication dynamics.

biophysics↗