Biology subjects

Shi, W.

Publications and source records attributed to Shi, W..

At least 19 recordsLinked to original sources

bioRxiv2026

Hierarchy of spindle forces in prometaphase

Dramatic movements characterize rapid assembly of mitotic spindle in prometaphase: chromosomes congress to the spindle equator, while spindle poles segregate rapidly elongating the spindle. Direct biophysical measurements of forces driving these movements are lacking, but the forces could be learned from the rapid pole and chromosome movements. We analyzed 3D trajectories of chromosomes and spindle poles in the wild-type and PRC1-depleted cells during early prometaphase and reconstructed the spindle forces. This analysis posits that (i) chromosomes do not interact with each other, except for a short-range steric repulsion, (ii) effective pole-chromosome forces are repulsive at short and attractive at long distances, (iii) dominant forces of spindle poles segregation are interpolar in origin. The important implication of these results is that the pole-pole segregation is robust, largely insensitive to regional variations inside the cell and to complex process of chromosome congression.

biophysics↗

bioRxiv2026

DNA methylation reveals molecular heterogeneity and urate excretion-associated subtypes of gout

Background: The molecular heterogeneity among gout patients remains largely unexplored, hindered the precise treatment for gout. Common indices for gout subtyping are cumbersome to measure, resulting in poor patient compliance. Methods: We elucidated the molecular heterogeneity of gout and developed a simple, reliable classification method for gout subtypes based on genome-wide DNA methylation, to facilitate individualized treatment. Genome-wide DNA methylation profiling was conducted in two independent cohorts, comprising a discovery cohort (n = 108) and a validation cohort (n = 100) representing four clinical gout subtypes. Results: We identified two gout subgroups associated with the fractional excretion of uric acid (FEUA) but not with 24-hour urinary uric acid levels (UUE) based on unsupervised clustering of whole-genome DNA methylation profiles, highlighting the contribution of epigenetic regulation to molecular heterogeneity in urate metabolism. Enrichment analysis links FEUA-associated subtypes to renal cell types, calcium related pathways and extended to the circulating immune compartment, with neutrophil- versus memory B cell-skewed leukocyte composition. A methylation-based classification model using 18 LASSO-selected CpGs with an XGBoost classifier effectively distinguished patients with high and low uric acid excretion, achieving excellent predictive performance (training cohort: AUC = 0.96, AP = 0.91; validation cohort: AUC = 0.86, AP = 0.85), outperforming the published model with clinical characteristics and SNPs. The signature site-associated genes NEK1 and TRPS1 display significant expression differences among urate-stratified patients and immune cells groups. TRPS1 may affect the AP-1/NF-{kappa}B inflammatory programme. Conclusions: These findings reveal distinct DNA methylation signatures underlying gout heterogeneity and demonstrate the feasibility of DNA methylation markers for gout subtype classification. The proposed methylation-based model provides a promising approach for personalized management of gout.

bioinformatics↗

bioRxiv2026

Division of vocal signaling in cooperating marmoset dyads

Communication enables partners to coordinate actions toward shared goals, but how vocal communication is organized during cooperation remains poorly understood. We recorded vocalizations from three common marmoset (Callithrix jacchus) dyads as they learned a mutual cooperation task requiring coordinated lever pulls for reward. Vocal behavior was divided by social hierarchy: dominants produced t-peeps, whereas subordinates produced chirps. Interestingly, dominant t-peeps followed failed cooperative pulls, peaked when cooperative bouts broke down, and declined after learning. By contrast, subordinate chirps followed successful pulls, accumulated during sustained cooperation, and persisted after learning. Each call was linked to the task role of the caller: dominant animals t-peeped more in sessions they led, and subordinates chirped mainly after cooperations they initiated, associations that sharpened with learning. Thus, social rank determined which vocal signal a partner used, whereas task role and the state of cooperation determined when to communicate. These complementary vocal signals of failure and success reveal how hierarchy, task role and task phase organize communication during joint action in cooperating marmosets.

neuroscience↗

bioRxiv2026

SpatialOmicsLab: an integrated research environment for AI co-scientists in spatial transcriptomics

Spatial profiling is moving from method development into a central platform for biological discovery and clinical translation, but analyzing such complex data has become the bottleneck of scientific discovery. Translating spatial transcriptomic measurements into biological insight requires reproducible workflows that integrate diverse analytical methods. Although language-model agents can plan and execute multistep analyses, fragmented data and software ecosystems hinder their use as reliable research assistants. In this study, we introduce SpatialOmicsLab, an integrated research environment for spatial transcriptomics comprising 113 curated computational tools, 63 reference datasets and 4,614 task specifications. We also introduce ST-Coscientist, an AI co-scientist that uses this environment to assemble, execute and refine spatial transcriptomic analyses. Within SpatialOmicsLab, ST-Coscientist outperformed expert-led workflows and other scientific agents across six benchmark settings spanning spatial clustering, cell-type deconvolution and spatially variable gene detection. It constructed alignment-aware workflows for three-dimensional MERFISH data and addressed biological questions by selecting and analysing relevant reference datasets. Procedural memory increased the success rate of integrating and validating additional analytical tools from 48% to 95%. Together, SpatialOmicsLab and ST-Coscientist establish an extensible ecosystem for reproducible spatial transcriptomic research, enabling AI co-scientists to address evolving biological questions with an expanding analytical repertoire.

bioinformatics↗

bioRxiv2026

Genetic dissection of the obesity paradox in carotid atherosclerosis using a hyperlipidemic mouse cohort

BackgroundOverweight and obese individuals often exhibit lower mortality rates or better prognoses than lean or normal-weight individuals with stroke and other diseases, a phenomenon called the "obesity paradox". Carotid atherosclerosis is the primary cause of ischemic stroke, and body weight serves as a reliable surrogate for adiposity in mice. MethodsPhenotypic and genetic connections of carotid atherosclerosis with body weight were evaluated in 299 F2 mice derived from BALB/cJ and LP/J Apoe knockout (Apoe-/-) mice. F2 mice were fed a Western diet for 12 weeks. Atherosclerotic lesion sizes in left carotid arteries, body weight, coat color, plasma lipids, glucose, small dense LDL ApoB, and malondialdehyde were measured, and 11,000 single nucleotide polymorphism (SNP) markers were genotyped. ResultsCarotid lesion sizes inversely correlated with body weight in both sexes. Genome-wide scans identified two significant quantitative trait loci (QTLs) for carotid atherosclerosis on chromosomes (Chr) 6 and 15 in an additive sex model, and five QTLs on Chr 6, 7, 12, 13, and 15 in an interactive sex model. Adjusting for body weight variation downgraded Chr 15 QTL (Cath5) in both models, whereas other QTLs upgraded in the additive sex model and downgraded in the interactive sex model. Human syntenic region of Cath5 associated with carotid intima-medial thickness (cIMT) and waist-to-hip ratio (WHR). ConclusionsThese findings indicate that the obesity paradox in carotid atherosclerosis is partially driven by shared genetic components that exert opposing effects on adiposity and plaque development and act through sex-dependent mechanisms.

genetics↗

bioRxiv2026

A modular architecture of human cellular aging across organs and diseases

Aging is a heterogeneous biological process in which different cellular systems undergo molecular remodeling at distinct rates, yet whether human cellular aging follows an organized architecture across organs remains unclear. Here, we integrate a multi-organ human single-cell transcriptomic atlas with plasma proteomic profiles from approximately 50,000 participants to reconstruct cellular aging states at population scale. By projecting cell-type-enriched molecular signatures onto circulating proteins, we characterize aging patterns across 128 organ-cell type pairs and identify 14 cellular aging modules comprising conserved cross-organ programs and organ-specific aging states. These modules reveal cellular identity as a dominant organizing axis of human aging that transcends anatomical boundaries. Module-level aging states uncover substantial inter-individual heterogeneity, with 34% of individuals exhibiting extreme aging deviation in at least one cellular module. Cellular aging modules exhibit distinct temporal trajectories, with structural and tissue-resident modules showing earlier remodeling than immune lineages. The modular organization of cellular aging is reflected in disease susceptibility, with accelerated aging of specific modules, particularly epithelial aging, showing broad associations with disease burden and mortality. Longitudinal analyses further demonstrate the stability and clinical relevance of cellular aging states, whereas lifestyle, metabolic and pharmacological factors show selective relationships with individual aging programs. Together, our study establishes a modular framework for understanding human cellular aging and reveals an organization of biological aging that may help explain individual differences in healthspan.

cell biology↗

bioRxiv2026

Spatial Topology Reveals Biologically Distinct Recurrent Motifs in Colorectal Cancer

Most spatial transcriptomic analyses of solid tumors focus on individual cell states or single-sample spatial domains rather than on recurrent multicellular tissue architectures shared across patients, and typically depend on predefined cell-type annotations or compartment definitions. We developed STORM (Spatial Topology analysis of Recurrent Motifs), an unsupervised graph-attention variational autoencoder that learns recurrent spatial motifs directly from cell-level graph structure and molecular profiles without cell-type labels, manual annotation, or predefined compartments. We applied to 32 Xenium sections from 16 patients with paired early-onset (EOCRC) and average-onset (AOCRC) colorectal cancer, STORM identified 10 recurrent motifs that self-organized into tumor-parenchymal, stromal, and immune macro-compartments. Among these, the Desmoplastic Fibrotic Barrier (DFB) motif, a CAF- and ECM-rich boundary architecture, was associated with restricted CD8+ T-cell geodesic access to tumor cores independently of CD8+ abundance, as demonstrated by abundance-normalized neighborhood enrichment statistics and within-sample mixed-effects models. EOCRC selectively amplified this barrier-exclusion architecture, exhibiting tighter tumor parenchyma, denser DFB shells, and a DFB-specific ECM activation program that yielded an age-specific prognostic signature in TCGA-COAD. Translation of motif macro-classes to H&E images via a Vision Transformer classifier produced an image-derived DFB-barrier composite that predicted overall survival in advanced-stage TCGA colorectal cancer. STORM provides an annotation-free framework for discovering recurrent spatial motifs and identifies a fibroblast barrier architecture whose topological association with immune exclusion is independent of effector abundance, amplified in early-onset disease, and translatable to a deployable pathology-based prognostic biomarker.

bioinformatics↗

bioRxiv2026

Astrocyte-to-microglia purinergic signaling mediates synaptic shielding and promotes neuronal activity

How glial cells sense and regulate neuronal hypoactivity remains poorly understood. Using in vivo imaging in anesthetized, sleeping, and behaving mice, we identified a glial purinergic signaling mechanism that converts neuronal hypoactivity into local circuit regulation. Cortical hypoactivity increased spatially confined ATP release through astrocytic pannexin-1 hemichannels, which were structurally enriched near perisomatic parvalbumin-positive boutons. Local ATP release directed microglial process movement and stabilized bulbous endings through microglial P2Y12 signaling, accompanied by localized Ca{superscript 2} activity in microglial processes. Disruption of astrocytic pannexin-1 or microglial P2Y12 impaired bulbous-ending stabilization and abolished rebound increases in neuronal activity during emergence from anesthesia. Similar ATP release and bulbous-ending formation were observed during chemogenetic neuronal silencing or natural sleep in freely behaving mice. These findings identify astrocyte-to-microglia purinergic signaling as a mechanism that converts neuronal hypoactivity into synapse-selective microglial regulation of circuit activity.

neuroscience↗

bioRxiv2026

BoltzProt-1: Towards Efficient De Novo Binder Design with Good Developability

Designing binders against novel protein targets remains a central challenge in computational drug discovery. Here we introduce BoltzProt-1, a pipeline for generating protein binders, including nanobodies, with improved hit rates and favorable developability properties. At its core lie a refined iteration of BoltzGens generative model and a novel protein-protein interaction prediction model, BoltzPPI. Employing BoltzPPI instead of BoltzGens standard structure-prediction confidence metrics to rank nanobody (VHH) designs increases the confirmed-binder hit rate from 3.3% to 8.0% across 10 novel targets. Assessed on 10 additional targets used in prior literature, the BoltzProt-1 pipeline obtains nanobody screening hits for 7 of 10 targets, surpassing the 6 of 10 previously reported by Chai-2. Finally, evaluating the developability of BoltzProt-1-designed nanobodies in terms of stability, aggregation, purity, polyspecificity and hydrophobicity reveals that 58% of its confirmed binders pass every criterion, exceeding both BoltzGen (40%) and clinical-stage VHH controls (21%). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/733997v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@d86de1org.highwire.dtl.DTLVardef@115da7eorg.highwire.dtl.DTLVardef@1bbb4e9org.highwire.dtl.DTLVardef@626a68_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

Spatiotemporal unfolding of prefrontal neural response divergence in adolescent depression during naturalistic experience

Depression alters how emotional experience is interpreted and regulated, yet how depression-related neural divergence unfolds during ongoing experience remains poorly understood, leaving unresolved whether such divergence reflects stable trait-like abnormalities or state-dependent responses that emerge only at particular moments. This question is especially consequential in adolescence, when depression often emerges amid heightened social sensitivity and continuing maturation of prefrontal regulatory systems. Here, we used naturalistic film watching fMRI data of 36 adolescents with depression and 36 matched controls to map where, how, and when neural responses diverge between diagnostic groups. Neural polarization analysis localized group-level divergence to two prefrontal hubs, the dmPFC-rACC and left dlPFC, where individual similarity to the depression-group response pattern was associated with depressive symptom severity across the cohort. These local divergence sites were not spatially isolated. Seed-based inter-subject functional connectivity showed that they were embedded within distributed stimulus-locked coupling patterns spanning prefrontal control, salience, and subcortical reward circuits. Time-resolved phase synchrony further revealed that this divergence was not continuous, but arose at specific narrative moments, with the dmPFC-rACC diverging during socio-emotional events and the left dlPFC during cognitively demanding ones. Together, these findings move beyond static localization to reveal depression-related neural divergence as a spatially organized, network-embedded, and temporally gated response pattern shaped by the unfolding content of naturalistic experience.

neuroscience↗

bioRxiv2026

Heterogeneity-driven adaptive scale graph learning for subcellular spatial transcriptomics

MotivationSpatial transcriptomics enables gene expression profiling within intact tissue sections, providing an important basis for analyzing tissue organization, cellular heterogeneity, and microenvironmental interactions. However, existing spatial structure identification methods often integrate spatial information using fixed neighborhoods or predefined smoothing scales, which limits their ability to adapt to region-specific structural heterogeneity. In homogeneous regions, broader spatial smoothing can help preserve continuous tissue structures, whereas in regions with complex boundaries or mixed cell populations, excessive smoothing may obscure local expression differences and fine-scale structural changes. Therefore, it is necessary to develop an adaptive graph learning framework that can adjust the range of spatial information integration according to tissue structural heterogeneity. ResultsIn this study, we propose HAST, a heterogeneity-driven adaptive-scale graph learning framework for spatial transcriptomics. HAST adaptively determines graph filtering scales according to spatial structural heterogeneity, enabling flexible information aggregation across different tissue regions. It further decomposes gene expression signals into low-frequency structural components and high-frequency residual components, thereby jointly modeling global spatial continuity and local expression variations. Experiments on high-resolution spatial transcriptomics datasets show that HAST improves spatial structure identification and cross-section generalization. Tumor-enriched cluster identification and neighborhood enrichment analysis further demonstrate its ability to characterize tumor-associated spatial regions and microenvironmental organization.

bioinformatics↗

bioRxiv2026

Improve the Efficacy of B7-H3-Targeting Antibody-Drug Conjugate DS-7300a in TP53-deficient Tumors by Inducing Ferroptosis

Immune checkpoint B7-H3 is an emerging target for immunotherapy. DS-7300a is an advanced B7-H3-targeting antibody-drug conjugate (ADC) warheaded with the topoisomerase I inhibitor DXd. DS-7300a has demonstrated clinical activity, but molecular biomarkers to predict its therapeutic response remain elusive. TP53 is one of the most mutated tumor suppressor genes across cancers, and effective therapies are urgently needed for TP53-deficient cancers. Using prostate cancer (PCa) as a model system, we reported that DS-7300as anti-tumor efficacy is highly dependent on functional p53 in cancer cells, and TP53 defects confer resistance to DS-7300a. Mechanistically, we found that DS-7300a and its payload, DXd, induce DNA damage and activate the ATM/ATR/CHK signaling cascade, thereby stabilizing p53 and inducing a pro-apoptotic and senescence-associated transcriptome. In contrast, TP53-deficient cells fail to detect DXd-induced DNA damage, maintain a high proliferation rate, and exhibit low levels of apoptosis and senescence, thereby conferring resistance to DS-7300a. Ferroptosis is an iron-dependent form of regulated cell death triggered by lipid peroxidation, which is mechanistically and morphologically distinct from apoptosis. Interestingly, DS-7300a treatment elevates lipid peroxidation in TP53-deficient cancer cells and upregulates glutathione peroxidase 4 (GPX4), an antioxidant enzyme that mitigates lipid peroxidation. Using isogeneic xenograft models and a newly developed humanized B7-H3 PCa model, we demonstrated that inducing ferroptosis by pharmacological inhibition of GPX4 enhances DS-7300as efficacy in TP53-deficient tumors. Our studies demonstrate that TP53 status dictates anti-tumor responses to DS-7300a, and ferroptosis induction represents a promising therapeutic approach to overcome resistance to DS-7300a in malignancies harboring TP53 defects.

cancer biology↗

bioRxiv2026

A Haplotype-resolved Telomere-to-Telomere Pig Genome

Haplotype-resolved telomere-to-telomere (T2T) pig genomes have not been reported, but may be essential for xenotransplantation and interspecies chimerism. Here we describe fully phased paternal and maternal T2T assemblies of an Erhualian pig (Ssc_EHL), enabling chromosome-scale reconstruction at base resolution. We uncover 2,498 (paternal haplotype) and 2,577 (maternal haplotype) protein-coding loci previously unresolved in Sscrofa11.1, while maintaining high concordance for anchored gene models between haplotypes. Applying this haplotype-resolved T2T annotation to publicly available pig-to-human kidney xenograft transcriptomes further allows the resolution of xenograft cell states and reveals newly resolved, cell-type-enriched genes. Cross-species synteny and orthology analyses against human identified a subset of high-confidence pig-specific genes with limited human counterparts, thus, refining the genomic basis of interspecies divergence. By integrating these orthology features with organ transcriptomes, we further defined an Interspecies Chimerism Compatibility score to prioritize organ-enriched, highly conserved loci with minimal redundancy imbalance, providing haplotype consistent targets for engineering organ-deficient pigs. Together, this haplotype-resolved T2T pig genome provides a foundational resource for mechanistic studies and rational genome engineering in xenotransplantation and interspecies chimerism.

genomics↗

bioRxiv2026

Non-invasive MRI mapping of tissue-CSF water exchange reveals glymphatic fluid movement in live human cortex

Efficient metabolic waste clearance, via the postulated glymphatic system, is essential for neural homeostasis. However, direct visualization of tissue-cerebrospinal fluid (CSF) exchange remains limited, leading to ongoing debate in the neuroscientific field. The present work revealed evidence of tissue-CSF water exchange in the live human cortex, by employing a novel MRI technique demonstrating the flux of water molecules across the perivascular interface. We observed robust water exchange inside the cortical ribbon, which was more prominent than white matter and deep brain tissue. We validated that the signal originates from CSF and is independent of cerebral perfusion. Water exchange between tissue and CSF declined with age. Furthermore, we demonstrated for the first time that tissue-CSF exchange was impaired in Alzheimers disease (AD), in particular in regions where the perivascular space is clogged by anti-amyloid immunotherapy.

bioengineering↗

bioRxiv2026

Paired in situ and molecular analyses identify mechanisms of pathogen persistence within environmental communities

Natural environments are a key reservoir for many opportunistic pathogens, yet mechanisms enabling persistence within complex microbial communities remain poorly defined. Current methods do not adequately link molecular and functional understanding of bacterial persistence to the activities of bacteria within their natural microbial community. Here we combine in situ culture-independent techniques, including metagenomics and metatranscriptomics, with isolate-level functional genomics and mutant studies to understand how opportunistic pathogens from the genera Escherichia, Klebsiella, and Enterococcus survive in urban-adjacent freshwater ecosystems. . Our results show that potential pathogens from each of these genera are both present and active within freshwater microbial communities. We further investigate a mouse-virulent isolate of the E. coli UPEC lineage ST73 isolated directly from this ecosystem, showing that this isolate persists in freshwater microcosms for at least one month. Paired transcriptomics and genome-scale fitness screening in creek water containing autochthonous microbiota identified E. coli genes required for persistence, including those involved in amino acid metabolism, nucleotide biosynthesis and biogenesis of curli. Isolate-resolved metatranscriptomics analysis supported these findings by revealing that many of these genes were highly expressed in situ. Deletion of curli structural genes resulted in reduced biofilm formation and a fitness defect specifically in the presence of freshwater microbiota, indicating that these structures promote environmental survival by improving E. coli competitiveness. Our study deepens our understanding of E. coli survival in waterways, while providing a broadly applicable framework for interrogating mechanisms of pathogen persistence in complex environments and communities.

microbiology↗

bioRxiv2026

RVPSD: A comprehensive and user-friendly web database for RNA viral protein structures

Protein structures are central to understanding the diversity and biological function of RNA viruses. However, few experimentally validated structures of RNA viruses are currently available. To address this gap, we established the RNA Viral Protein Structure Database (RVPSD) that comprises diverse RNA viral protein structures predicted using AlphaFold2. RVPSD integrates taxonomic classification, viral nucleotide and protein sequences, functional annotations, and predicted three-dimensional protein structures to support a systematic exploration of the RNA viral proteomes. Currently, RVPSD comprises a total of 154,716 AlphaFold2-predicted RNA viral protein structures from 5,263 RNA virus species, with 84.9% exhibiting high pLDDT scores (>70) and representing a large-scale and comprehensive resource for RNA viral protein structures. RVPSD also provides a user-friendly web interface, with advanced search, sequence- and structure-based retrieval, interactive 3D visualization, and access and downloading structural data, enabling researchers to perform comparative structural analyses and functional annotation of viral "dark matter".

microbiology↗

bioRxiv2026

PRDM1 Drives Chemoradiotherapy-associated Enrichment of Adaptive NK Cells in Cervical Cancer

Chemoradiotherapy (CRT) induces not only direct tumor cell death but also extensive remodeling of the tumor immune microenvironment. Adaptive natural killer (aNK) cells, initially characterized in chronic viral infection, are increasingly recognized as functionally relevant immune populations in solid tumors, where they may contribute to antitumor immunity and immune memory. However, how aNK cells dynamically respond to chemoradiotherapy and the regulatory mechanisms underlying their activation in solid tumors remain poorly defined. To address this, we analyzed single-cell RNA sequencing data from cervical cancer patients collected before CRT, after the first CRT fraction, and after the second fraction. Single-cell profiling revealed a significant enrichment of aNK cells following CRT. Differential gene expression and pathway enrichment analyses demonstrated that CRT-associated aNK cells exhibit enhanced virus-defending programs with increased cytotoxicity. Among the differentially expressed genes, the transcription factor PRDM1 was consistently and robustly upregulated in aNK cells after both the first and second rounds of CRT. To investigate the functional role of PRDM1, we applied in silico perturbation analyses using scTenifoldKnk and CellOracle. Virtual knockout of PRDM1 resulted in a marked attenuation of effector programs and disruption of metabolic networks in aNK cells. Moreover, PRDM1 perturbation altered inferred cellular trajectories, reversing the progression toward the aNK cell state, suggesting a requirement for PRDM1 in maintaining aNK identity and functional maturation within the CRT-conditioned tumor microenvironment. Together, these findings identify PRDM1 as a key regulatory factor associated with the enrichment, functional activation, and trajectory stabilization of aNK cells following CRT in cervical cancer, providing insight into innate immune remodeling during CRT and highlighting PRDM1 as a potential target for enhancing radiotherapy-induced antitumor immunity.

immunology↗

bioRxiv2026

Reconstructing Actin Dynamics of the Leading Edge from Observational Data

Mesenchymal cell migration starts with the protrusion of the cells leading edge, enabled by the branching growth of the actin network. Two crucial molecular players in protrusion are actin filaments and the Arp2/3 protein complex, the branching agent. Traditionally, protrusion models are intuited from several perturbative experiments. Recent multiplex microscopy imaging data promise to drastically change this paradigm by providing measurements of naturally fluctuating densities of key proteins at the leading edge of unperturbed cells. We report the first attempt to reconstruct the mechanistic protrusion model from such data. We analyze fluctuations of F-actin and Arp2/3 densities and cell edge velocity using phase space and regression analysis to reconstruct linearized stochastic actin-Arp2/3-velocity coupled dynamics. We then build a nonlinear partial differential equation model of these dynamics based on previous knowledge of this system and parsimony. The resulting model recovers the rates of reactions and mechanical and transport processes in the lamellipodium from a single non-perturbative experiment. The model posits that the only essential nonlinearities in the lamellipodial dynamics stem from the retrograde flow of F-actin. The model suggests that the protrusion is dominated by a damped oscillatory cycle resulting from a combination of positive feedback from Arp2/3 to protrusion velocity and negative feedback from F-actin to the velocity. Significance statementTraditionally, models of intracellular mechanochemistry are intuited from perturbative experiments. Multiplex microscopy imaging changes this by providing measurements of naturally fluctuating densities of key proteins in unperturbed cells. We use such data to reconstruct a mechanistic model of cell leading edge. We build equations for actin system and edge velocity using data, previous knowledge and parsimony. The resulting model recovers the rates of reactions and mechanical and transport processes at the leading edge. The model suggests that the protrusion is dominated by a damped oscillatory cycle resulting from a combination of positive feedback from Arp2/3 to protrusion velocity and negative feedback from F-actin to the velocity.

biophysics↗