Biology subjects

Wei, C.

Publications and source records attributed to Wei, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Spatial profiling of pooled mRNA-LNP delivery in vivo with NanoSTAMP

Existing pooled lipid nanoparticle (LNP) screens lack spatial information on formulation localization, cellular uptake, and associated multicellular tissue responses. Here we introduce NanoSTAMP, a spatially resolved, pooled in vivo screening platform for barcoded LNP libraries that uses fluorescence in situ hybridization (FISH)-based barcode readout and is compatible with spatial omics. NanoSTAMP links LNP formulation to cell-type specific uptake, cargo expression, and nearby multicellular neighborhoods within intact tissue, which enables spatially-informed design of RNA delivery, establishing tissue architecture as a dimension of LNP performance.

bioengineering↗

bioRxiv2026

Pervasive Backdoor Vulnerabilities in Genomic Foundation Models

Genomic foundation models are increasingly used to interpret and design DNA sequences, yet their susceptibility to training-data manipulation remains poorly understood. Here we systematically evaluate backdoor poisoning across three model families, seven parameter scales ranging from 50 million to 7 billion, and 18 genomic classification tasks. We introduce two complementary 48-nucleotide triggers: a composition-matched synthetic sequence and a biologically grounded trigger derived from transposon terminal inverted repeats. Poisoning 5% of the training data induced high attack success rates across all tested models, with model-level median values ranging from 91.4% to 100%. Increasing parameter scale did not consistently improve resistance, whereas poisoning rate and trigger length had stronger effects on attack efficacy. Performance on unmodified sequences was generally preserved, with 79.4% of model - task - trigger configurations changing by no more than two percentage points, although larger task-specific losses occurred. We further developed a two-stage defense that combines single-nucleotide mutation-sensitivity screening with reference-database validation. Across 28 evaluated configurations, the method achieved 100% precision and a median recall of 92.95%, while localizing the trigger in nearly all detected poisoned sequences. These findings establish training-data poisoning as a pervasive and difficult-to-detect vulnerability in genomic foundation models and motivate stronger data-provenance controls, adversarial evaluation and post-training security auditing.

bioinformatics↗

bioRxiv2026

Crystal structures of a far-red photoreceptor in different light-absorbing states: insights into spectral tuning and light signaling

Cyanobacteriochromes (CBCRs) are bilin-binding photoreceptors with remarkable spectral versatility. Using phycocyanobilin (PCB) as a chromophore, CBCRs regulate diverse light-dependent processes in cyanobacteria, ranging from photosynthesis to chromatic acclimation. Although extensive studies have uncovered multiple spectral tuning mechanisms in bilin-binding proteins, recent structural studies of far-red CBCRs suggest the existence of additional tuning strategies in both the 15Z and 15E states. Here we report crystal structures of the representative far-red CBCR Anacy_2551g3 in three distinct light-absorbing states, all of which adopt a compact all-syn PCB conformation. These structures demonstrate that 15Z/15E photoisomerization in Anacy_2551g3 involves minimal chromophore rotation relative to the GAF domain, in stark contrast to other characterized bilin-based photoreceptors. To investigate the molecular basis of its far-red absorption, we examined the protonation and tautomeric states of PCB in the Pfr state using resonance Raman (RR) spectroscopy and quantum mechanics/molecular mechanics (QM/MM) calculations. Comparisons of experimental and calculated RR spectra support a bilin lactam as the predominant tautomeric form in the Pfr state. Integrating structural, spectroscopic, computational and mutational analyses, we propose that specific protein-chromophore interactions play critical roles in modulating chromophore conjugation beyond bilin coplanarity. Structural analyses further suggest a signaling model in which light regulation by Anacy_2551g3 is mediated through reversible switching between a high-affinity Pfr state and a low-affinity Po state that does not involve large chromophore motions. Together, these results provide new insights into how protein-chromophore coupling governs spectral tuning and light signaling in bilin-based photoreceptors. Significance statementBilins are widespread biological pigments that mediate photoreception, light harvesting, and photosynthesis across diverse light environments. In a phenomenon known as spectral tuning, the optical properties of bilin-binding proteins are profoundly influenced by protein-chromophore interactions. Mechanistic understanding of spectral tuning and light signaling is important not only for advancing fundamental knowledge of light-sensitive proteins but also for developing new engineering strategies in synthetic biology and biotechnology. Recently discovered cyanobacteriochromes (CBCRs) exhibit remarkable spectral diversity and structural versatility, providing excellent model systems for dissecting the mechanisms of bilin-based photoreceptors. By integrating crystallography, spectroscopy and computational methods, this work examines three distinct light absorbing states of a representative far-red CBCR. Our findings reveal previously unrecognized mechanisms of spectral tuning and light signaling, highlighting the critical roles of protein-chromophore coupling and electrostatic interactions in regulating photoreceptor function.

biochemistry↗

bioRxiv2026

EBD-DTI: Episodic Bridge Diffusion for Zero-Shot Cold-Start Drug-Target Interaction Prediction

Predicting drug-target interactions (DTI) for entirely unseen drugs or proteins--the cold-start problem--remains a critical challenge in computational drug discovery. While sequence-based methods naturally support zero-shot generalization, they often ignore relational topology, and existing graph-based approaches either rely on global diffusion that blurs the boundary between inductive and transductive evaluation or require a few known interaction samples at test time (few-shot). We present EBD-DTI, a framework that enables zero-shot inference in graph-based DTI models without requiring any known interactions for unseen entities. The key innovation is episodic cold-start training : at each epoch, a random subset of training entities is masked and treated as pseudo-cold, forcing the model to learn cold-start inference with explicit gradient supervision. A bridge-conditioned local subgraph, together with multi-hop diffusion, provides cold entities with relational context from their nearest observed neighbors. Experiments on three benchmarks (BioSNAP, BindingDB, and DrugBank) demonstrate that EBD-DTI achieves competitive or superior performance compared to state-of-the-art methods under strict zero-shot evaluation, with episodic training improving AUC by up to 12%.

bioinformatics↗

bioRxiv2026

Partial epithelial-to-mesenchymal transition mediates profound gap closure through growth and fluidization

Epithelial gap closure is essential for maintaining tissue integrity during development and wound healing. Previous studies have shown that closure of small gaps is driven by actomyosin purse-string contraction and traction forces generated at the gap edge. Here, we show that millimeter-scale circular gap closure in mouse epicardial (MEC1) monolayers is driven primarily by growth-mediated compressive stresses. Compared with MDCK monolayers, MEC1 cells close gaps more rapidly with reduced undulation near gap edge through coordinated tissue-wide extension-contraction. The collective closing dynamics can be modulated by partial epithelial-mesenchymal transition induction and Rho kinase inhibition. By integrating tissue and cell kinematic analyses, traction-force mapping, and a continuum framework that decomposes tissue strain rates into growth-, elastic-, and fluidity-related contributions, we reveal that growth-generated compression drives inward tissue flow, while elastic cell elongation and fluid-like tissue remodeling through cell-cell intercalation act synergistically to accommodate deformation and promote robust collective gap closure.

biophysics↗

bioRxiv2026

A brain-tumour axis links chronic stress to gastric cancer progression through NPY signalling

Chronic stress promotes gastric tumour growth, but the central neural pathways remain largely enigmatic. Here, we identify a brain-tumour axis, implicating the central amygdala (CeA) activity in promoting gastric cancer growth through sympathetic neuropeptide Y (NPY) signalling occurring within the tumour. Using clinical datasets, patient samples, pathway tracing, electrophysiology and chemogenetic manipulation, we demonstrate that stress selectively increases NPY Y1 receptor (NPY1R) synthesis in the patients gastric cancer tissue; moreover, the NPY1R density correlates with advanced cancer stage and poor prognosis. In mice, daily constraint chronic stress enhances CeA excitability and promotes sympathetic neurotransmitter norepinephrine release within the tumour microenvironment. Norepinephrine, in turn, increases tumour endogenous NPY/NPY1R production and the activation of downstream MAPK/Erk1/2 signalling pathway, which drives cancer cell proliferation and invasion. Manipulating CeA neuronal activity alone can regulate tumour growth, whereas selectively blocking tumour NPY1R prevents stress-induced tumour progression in vivo and cancer cell migration in vitro. This study identifies a central-to-peripheral circuit linking chronic stress to gastric cancer growth, and highlights NPY1R as a potential therapeutic target.

Cancer Biology↗

bioRxiv2026

Conversion of a Viral Glycan Shield into a Binding Anchor via Causal-Driven Antibody Optimization

Therapeutic antibodies are challenged by rapidly evolving pathogens that exploit glycosylation to shield epitopes. SARS-CoV-2 JN.1 exemplifies this, escaping antibodies through the N354-linked glycan. However, targeting glycosylated epitopes remains vacant, as scarce and heterogeneous glycan structures render existing approaches ineffective. Here, we introduce the Antibody Evolution Nexus with Causal-Driven Simulation (AENCS), integrating molecular simulation with causal inference. Applying AENCS to restore S309 efficacy against JN.1, we identified ACC01, exhibiting [~]24-fold improved neutralization. With limited prior knowledge of the N354 glycosylation site, ACC01 stabilized this glycan conformation, facilitating the determination of its cryo-EM structure. Causal dissection revealed how this glycan shield is functionally inverted into a binding anchor through multi-layered interactions. This mechanistic conversion, combined with the conservation of N354 glycosylation, enabled ACC01 to maintain potent activity against the latest variant NB.1.8.1. Collectively, AENCS demonstrates causal-driven antibody engineering can illuminate cryptic glycosylated epitopes, providing viable paradigms for exploring this vacant frontier.

bioengineering↗

bioRxiv2026

A graph-based pangenome reveals the genetic basis of climate-resilient and horticultural traits in pear

Climate change poses an increasing threat to the cultivation of deciduous fruit trees, placing greater demands on modern pear breeding. Using pear germplasm adapted to diverse environments, we assembled 11 chromosome-level genomes. In combination with 13 publicly accessible pear genomes, we analyzed presence-absence variations (PAVs) and constructed a graph-based pangenome for pear. By performing a PAV-eQTL analysis of the fruit of 123 pear accessions, we identified PAVs significantly associated with expression levels of genes that may be involved in regulating agronomic traits. Population analysis of 268 pear accessions revealed two stop-gained variants in DAM1 of independent origin, which may function in advancing the blooming date and reducing the chilling requirement. We detected complex PAVs at the NOR1 locus, including two copy-number variations and one deletion. These PAVs contributed to the rapid diversification of the NOR1 locus and the fruit development period through regulating ARF5 and other ripening-related genes. We revealed the selection history of the NOR1 locus and developed novel pear individuals that accumulated alleles for low chilling requirement, early blooming date, and short fruit development period. The results provide valuable resources for pear genomics research and offer a guideline for breeding modern pears with climate resilience.

plant biology↗

bioRxiv2026

NeuroCDS: Integrating Local and Global Neural Network Representations via Structural Constrained Viterbi Decoding for Robust CDS Annotation

MotivationRobust annotation of Coding Sequences (CDS) is critical for downstream transcriptomics, yet heavily fragmented de novo RNA-Seq assemblies pose a severe challenge. Traditional computational tools rely on fixed, hand-crafted features that are prone to fail when canonical sequence signals are truncated. While recent deep learning models excel at automatically extracting complex representations, they predominantly treat these as isolated prediction tasks. Lacking a joint inference mechanism to enforce structural constraints, existing models occasionally output biologically invalid predictions. Therefore, a computational framework capable of fusing heterogeneous neural network representations for joint annotation is critically needed. ResultsWe present NeuroCDS, a reliable framework that bridges the effective representation capabilities of deep neural networks with the structural rigor of dynamic programming. NeuroCDS employs a dual-branch architecture: a Convolutional Neural Network (CNN) acts as a local sensor to extract Translation Initiation Sites (TIS), while a Temporal Convolutional Network (TCN) acts as a global sensor to evaluate continuous regional coding potential. The primary contribution of NeuroCDS lies in a structurally constrained Viterbi Decoding algorithm designed to fuse these heterogeneous signals. This joint inference mechanism strictly enforces biological grammars (e.g., reading frame preservation) to dynamically calculate the globally optimal transcript structure via a tripartite state space. Crucially, by introducing a dynamic length normalization mechanism, our formulation adaptively leverages global continuous representations to stably annotate both intact transcripts and highly truncated fragments. Comprehensive evaluations demonstrate that NeuroCDS achieves high F1-scores on full-length transcripts and maintains robust performance on complex Ribo-seq validated datasets, comparing favorably against traditional HMM-based and heuristic methodologies. AvailabilitySource code, pre-trained models, and datasets are freely available at https://github.com/hgcwei/NeuroCDS.

bioinformatics↗

bioRxiv2026

Fibroblast Growth Factor Receptor Signaling in Maturing Osteoblasts Controls Cell-Matrix Interactions Critical for Osteocyte Survival

The terminal differentiation of osteoblasts into osteocytes, the most abundant cell type in cortical bone, is critical for skeletal homeostasis. Osteocyte loss is a hallmark of bone aging and fragility, yet the mechanisms regulating osteocyte formation and survival are poorly understood. We show that inactivation of fibroblast growth factor receptor 1 (Fgfr1) in the mature osteoblast lineage results in extensive osteocyte death, identifying FGFR1 signaling as essential for osteocyte viability and bone integrity. Lineage tracing and analysis of endogenous and induced appositional bone formation revealed that newly embedded osteocytes fail to survive without FGFR1. These osteocytes exhibited ectopic expression of osteocalcin and podoplanin within sclerostin-positive, TUNEL-reactive lacunae, along with defective dendrite formation and disruption of the local lacunocanalicular network. RNA sequencing of cortical bone demonstrated reduced expression of extracellular matrix (ECM) genes and neuronal regulatory genes, while histological and ultrastructural analyses showed disorganized collagen fibrils, diminished osteoid, and abnormal mineralization. In vitro, FGF signaling in Ocy454 cells regulated gene programs involved in development, axon guidance, and bone ECM organization, highlighting a dual function for FGF signaling in which it controls both matrix-dependent and intrinsic cell differentiation mechanisms during the osteoblast-to-osteocyte transition. We propose that FGFR1 deficiency causes ECM disorganization and impaired dendrite formation, disrupting osteocyte communication with neighboring bone and vascular cells, ultimately leading to cell death. These findings establish FGFR signaling as a critical regulator of osteocyte differentiation, viability of bone-embedded osteocytes, and bone homeostasis. Summary StatementFGFR signaling has a profound effect on adult bone extracellular matrix that is vital to maintaining the viability and morphology of newly formed osteocytes, their lacunocanalicular network and the maintenance of bone homeostasis.

developmental biology↗

bioRxiv2026

Aerosol delivery-based serial femtosecond crystallography

Serial femtosecond crystallography (SFX) has revolutionised structural biology by enabling direct visualization of conformational dynamics of biomacromolecules at near-physiological temperatures. However, conventional SFX sample delivery at X-ray free-electron laser (XFEL) facilities introduces a significant X-ray scattering background, which may limit the data quality and resolution. Here, we introduce an aerosol delivery-based method that drastically reduces the back-ground scattering by minimising the liquid environment surrounding the nanocrystals. We validate our method by solving the structure of Cydia pomonella granulovirus nanocrystals at 1.9 [A] resolution, achieving orders-of-magnitude lower background scattering compared to a liquid jet-based method. Structural comparison with the liquid jet-based model revealed similar overall structure, suggesting that the native structure is largely preserved despite dehydration during aerosolisation. Our method enables efficient SFX studies, particularly pump-probe time-resolved SFX on protein nanocrystals with enhanced signal-to-noise ratios, as well as high-throughput small molecule SFX (smSFX) applications for pharmaceuticals and functional materials.

biophysics↗

bioRxiv2026

Engineering age-adaptive mRNA lipid nanoparticle cancer vaccines via reprogramming systemic gene expression

Lipid nanoparticle (LNP)-based mRNA vaccines have transformed cancer immunotherapy, yet their efficacy in older individuals, who represent the majority of cancer patients, remains poorly understood. Here, we uncover a critical and previously underappreciated barrier to mRNA LNP cancer vaccine performance in aged hosts: impaired systemic transgene expression. Using the SM-102 mRNA LNPs as a benchmark formulation, we show that while local immune activation and antigen presentation at the injection site and draining lymph nodes remain largely intact with age, transgene expression in peripheral organs, including the liver, lungs, and spleen, is markedly reduced. This deficit limits the magnitude and durability of CD8 and CD4 T cell responses and substantially compromises tumour control. Transcriptomic profiling further reveals that attenuated transgene expression parallels broad attenuation of antigen processing, presentation, and activation pathways in immune cells from aged animals, implicating impaired systemic mRNA translation as a central driver of the downstream immune defects and antitumour efficacy loss. Building on these insights, we identify a rationally selected LNP formulation that reestablishes distal antigen expression across age groups as an engineering strategy to revive T cell immunity, achieving full rescue of therapeutic efficacy in aged mice without additional intervention. Together, these findings establish systemic mRNA translation as a tuneable lever of vaccine performance and highlight that optimizing LNP formulations to sustain systemic transgene expression across age groups may enable next-generation, age-adaptive mRNA vaccines for cancer and other diseases of aging.

bioengineering↗

bioRxiv2026

ProteinConformers: large-scale and energetically profiled descriptions of protein conformational landscapes

Modeling protein conformational landscapes is essential for understanding dynamics, allostery, and drug discovery, yet existing resources lack diverse conformational coverage, energetic annotations, or benchmarking standards. ProteinConformers (https://zhanggroup.org/ProteinConformers) provides 2.7 million geometry-optimized conformations generated with a multi-seed molecular dynamics strategy, paired with 13.7 million energy evaluations and 5.5 million similarity annotations. It delivers continuous landscapes from non-native to near-native states, benchmarking framework for multi-conformation generators, and an interactive analysis platform.

bioinformatics↗

bioRxiv2025

Spatiotemporal control of PIWI compartmentalization by mitochondrial scaffolds defines pachytene piRNA pathway organization

Pachytene piRNAs are the least understood class of piRNAs in the mammalian male germ line. During meiosis, their biogenesis occurs near mitochondrial outer membrane in germ granules known as intermitochondrial cement (IMC). However, how mitochondrial factors regulate the trafficking of PIWI proteins into and out of the IMC remain poorly understood. Here we show that the cytoplasmic PIWI proteins MILI and MIWI are recruited for pachytene piRNA biogenesis via distinct mitochondrial membrane proteins. Loss of the mitochondrial scaffold protein ASZ1 during meiosis in mice disrupts multiple downstream biogenesis steps, leading to misregulation of MILI and MIWI, failure of IMC formation, and a near-complete loss of mature pachytene piRNAs. Strikingly, despite the drastic depletion of pachytene piRNAs, LINE1 transposon silencing remains unaffected. We identify three classes of pachytene piRNA pathway components that coordinate piRNA production and compartmentalization. Our findings reveal that chromatoid body precursors serve as a central hub for the accumulation of pachytene PIWI-piRNA complexes, thus establishing a connection between IMC-based biogenesis and downstream piRNA function.

developmental biology↗

bioRxiv2025

Physics-Diffusion-Driven Multiscale Aggregation for Drug-Target Interaction Prediction

Drug-target interaction prediction is an important task in computational drug discovery. To address the limitations of existing graph neural network approaches in propagation depth and robustness, we propose PDDMA-DTI (Physics-Diffusion-Driven Multiscale Aggregation for Drug-Target Interaction Prediction), a physics-inspired, multiscale adaptive aggregation framework. PDDMA-DTI injects a physics-motivated diffusion operator into a heterogeneous drug-target network: global diffusion models cross-modal information propagation via the graph Laplacian, while local diffusion performs neighborhood smoothing in the low-dimensional embedding space. Both processes are solved with the implicit Euler scheme to ensure numerical stability. For each node, we introduce an adaptive stopping rule based on steady-state convergence and a weighted fusion strategy. This strategy leverages hop counts and node degrees to aggregate multi-step diffusion snapshots into a final representation that preserves original features while capturing multi-scale context. To emphasize strong interaction pathways, we further propose a Physical Interaction Summation Enhancement module that augments pairwise interaction features with a linear plus quadratic energy term, thereby amplifying highly correlated drug-target pairs. Extensive experiments on multiple benchmark datasets show that PDDMA-DTI consistently outperforms representative baselines in accuracy and robustness.

bioinformatics↗

bioRxiv2025

Simple, Fast and Highly Efficient One-or Two-step Proteomic Preparation Enables Deep Profiling of Microgram-level FF and FFPE Tissues

Large-scale tissue proteomics requires workflows that are efficient, rapid, and repeatable across diverse samples. Herein, we present Simple Workflow for Integrated and Fast Tissue-preparation (SWIFT), which enables complete processing of fresh- frozen (FF) and formalin-fixed, paraffin-embedded (FFPE) tissues in either one- or two-step formats, while maintaining deep proteome coverage with high repeatability from low to microgram-level tissues. For FF tissues, an incubation process integrating lysis, reduction, alkylation, and digestion generates peptide samples directly from tissues in [≤] 1.5 h. For FFPE tissues, concurrent deparaffinization, rehydration, and de- crosslinking is achieved within 0.5 h, followed by one-step peptide preparation. Furthermore, our workflows eliminate desalting and offline cleanup steps, thereby reducing variability and total processing time. Using our methods, we identified up to [~]10,000 protein groups and [~]150,000 peptides across multiple mouse organs on timsTOF Pro. Repeatability was high (pairwise Pearsons r > 0.96 across six experimental replicates), with dynamic ranges spanning 6-7 orders of magnitude. Organ-enriched protein analysis identified functionally distinct proteins unique to each tissue Paired FF and FFPE analyses revealed preservation-induced shifts, with FFPE tissues showing reduced detection of membrane-associated and respiratory proteins, including mitochondrial Complex I. Together, our fast and simplified workflows enable deep tissue proteomics for large-scale clinical and translational studies in a cost- effective and widely-accessible manner.

biochemistry↗

bioRxiv2025

Meningeal macrophages exhibit diverse calcium signaling at steady-state and in response to aberrant cortical hyperexcitability in awake mice

The meninges, which envelop and protect the brain, host a dense network of resident macrophages with diverse roles in regulating homeostasis and neuroinflammation. Despite their importance, we have a limited understanding of their behavior in vivo. Many dynamic cellular functions of macrophages involve intracellular Ca2+ signaling. However, virtually nothing is known about the spatiotemporal Ca2+ dynamics of meningeal macrophages in vivo. We developed a chronic intravital two-photon imaging approach and related computational analysis tools to interrogate meningeal macrophage Ca2+ dynamics, at subcellular resolution, in a novel Pf4Cre:TIGRE2.0GCaMP6s/wt reporter mouse model. Using imaging in awake mice, we characterized Ca2+ activity in meningeal macrophages at steady state and in response to cortical spreading depolarization (CSD), an aberrant pro-inflammatory brain hyperexcitability event implicated in migraine, traumatic brain injury, and stroke. In homeostatic meninges, macrophages in the dural perivascular niche exhibited several Ca2+ dynamic features, including event duration and signal frequency spectrum, distinct from those of localized to the interstitial, non-perivascular niche. Simultaneous tracking of macrophage Ca2+ dynamics and local vasomotion revealed a subset of dural perivascular macrophages whose activity was coupled to locomotion-driven diameter fluctuations of their associated vessels. Most perivascular and non-perivascular meningeal macrophages displayed propagating intracellular Ca2+ activity and synchronized intercellular Ca2+ elevations, potentially driven by extrinsic factors. In response to CSD, the majority of perivascular and non-perivascular meningeal macrophages showed a persistent decrease in Ca2+ activity, while a smaller subset displayed Ca2+ elevations. Mechanistically, CGRP/RAMP1 signaling mediated the increase but not the decrease in CSD-mediated Ca2+ signaling. Collectively, our results highlight a previously unknown diversity of Ca2+ dynamics in meningeal macrophages at steady state and in response to an aberrant brain hyperexcitability event linked to neuroinflammation.

neuroscience↗

bioRxiv2025

Computational modeling of optogenetic control in human atrial tissue: The role of fibrosis type and illumination strategy

Atrial fibrosis promotes atrial fibrillation by stabilizing spiral waves, with focal fibrosis causing strong anchoring that resists termination. Optogenetics offers a low-energy alternative for rhythm control, but its efficacy in human atrial tissue remains under investigation. Here, we developed a two-dimensional computational model of human atrial tissue expressing the light-sensitive protein GtACR1, coupled with fibroblasts, to simulate spiral wave dynamics under varying degrees (0%-100%) and types (focal vs. diffuse) of fibrosis. We examined the effects of subthreshold illumination area (0%-100%) and spatial intensity profiles (uniform, parabolic, linear, exponential) on termination efficiency, and tested low-intensity periodic stimulation for wave drift induction. Results show that the minimum light area required for termination increases with fibrosis degree. At 25%-50% fibrosis, focal substrates require larger illumination areas than diffuse ones, confirming stronger anchoring. Crucially, the relationship between illumination area and termination time is non-monotonic. An "optimal light range" exists: smaller areas fail to eliminate the wave, while excessively large areas suppress wavefront collisions, prolonging termination. In diffuse fibrosis, low-intensity periodic illumination successfully induces drift and boundary collision, enabling self-termination. In contrast, in focal fibrosis, the spiral wave core remains anchored, and drift cannot be initiated by modulating stimulation frequency or intensity alone. Our findings demonstrate that fibrosis type and extent critically influence optogenetic control efficacy. The existence of an optimal illumination strategy highlights the need for spatially tailored interventions. These results provide a mechanistic basis for developing individualized, low-energy optogenetic defibrillation protocols. Author summaryAtrial fibrillation, a common heart rhythm disorder, is often sustained by rotating electrical waves in the heart muscle. Scarring (fibrosis) in the atria can anchor these waves, making them harder to eliminate. Optogenetics -- a technique that uses light to control genetically modified heart cells--offers a promising low-energy approach to stop these dangerous rhythms. However, how different patterns of scarring affect the success of optical interventions remains unclear. In this study, we developed a computational model of human atrial tissue expressing a light-sensitive protein (GtACR1) to investigate how two major types of fibrosis--localized "focal" scars versus widespread "diffuse" scarring -- influence the effectiveness of light-based rhythm control. We found that focal fibrosis strongly anchors spiral waves, requiring larger illuminated areas for termination, while diffuse fibrosis allows more efficient disruption with smaller light zones. Crucially, we discovered an "optimal light range": too little light fails to stop the wave, but too much can paradoxically prolong termination by suppressing wavefront collisions. Furthermore, we show that low-intensity periodic light can induce drift and self-termination in diffuse fibrotic tissue, but fails in focal substrates due to structural anchoring. Our findings highlight that one-size-fits-all optical strategies are suboptimal, and that personalized illumination protocols--tailored to individual fibrosis patterns--could enable safer, lower-energy defibrillation in the future.

physiology↗