PLoS Computational Biology最新文献

{"title":"Antimony 3: Extending human-readable model definitions for SBML Level 3 Core and Packages.","authors":"Adel Heydarabadipour, Lucian P Smith, Joseph L Hellerstein, Herbert M Sauro","doi":"10.1371/journal.pcbi.1014207","DOIUrl":"10.1371/journal.pcbi.1014207","url":null,"abstract":"<p><p>Antimony is a human-readable language for defining and sharing models developed by the systems biology community. It enables scientists to describe biochemical networks with a simple syntax, while supporting seamless conversion to and from the Systems Biology Markup Language (SBML) community standard. Since Antimony's original release, both SBML and modeling practices have evolved significantly, creating a need to update Antimony to maintain its standards compliance and practical relevance. In this paper, we introduce Antimony 3, a comprehensive update that formalizes its cumulative improvements and extends its support for SBML Level 3 Core and Flux Balance Constraints (FBC), Distributions, Layout, and Render packages. Antimony 3 enables model specifications that combine kinetic reactions with flux balance analysis, represent uncertainty using probability distributions, add biological context through annotations, and define publication-ready visualizations, all within a unified plain-text format. Antimony 3 is delivered as a lightweight C/C++ library with a stable C API. It is available through official bindings for Python, Julia, and JavaScript/WebAssembly, as well as a cross-platform desktop GUI, which enables straightforward use across scripting environments, desktop applications, and browser-based tools. Antimony 3 is released as open-source software under the BSD 3-Clause License and is available at https://github.com/sys-bio/antimony.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014207"},"PeriodicalIF":3.6,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13671645/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149167536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic workforce modulation and foraging efficiency in Eusocial insect colonies.","authors":"Daniel Campos, Javier Cristín, Pol Fernández-López, Roger Lloret-Cabot, Meritxell Genovart, Frederic Bartumeus","doi":"10.1371/journal.pcbi.1014258","DOIUrl":"10.1371/journal.pcbi.1014258","url":null,"abstract":"<p><p>Understanding the fitness advantages conferred by eusociality remains a central challenge in behavioral ecology. One promising approach is to identify collective strategies that shift efficiency within social groups. Here, we explore the hypothesis that reserve workforces in ant colonies represent an adaptive mechanism that enhances flexibility and foraging efficiency under fluctuating environmental conditions. We examine how departure and return rates of foragers modulate such reserve workers and how these time-dependent dynamics shape the colony's overall energetic balance. By integrating an energetic-balance framework with stochastic search simulations inspired by empirical results from four colonies of Aphaenogaster senilis ants, we quantify the energetic requirements for colony viability, incorporating energy intake, search costs, and basal metabolic demands. Our results show that as colonies grow, maintaining a positive energy balance requires a disproportionately larger relative workforce. By modulating departure and return rates over time, colonies control the synchrony of their collective search and efficiently activate or suppress their reserve workforce to scale foraging effort as needed. These findings suggest that the \"lazy\" or weakly engaged workers commonly observed in large colonies function as an essential reserve that stabilizes colony energetics and enhances responsiveness. Together, our results provide a functional explanation for sublinear metabolic scaling in eusocial groups and highlight workforce modulation as a key factor underlying their energetic stability and evolutionary success.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014258"},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13667929/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149148458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A statistical damage model for coupled mechano-electrophysiological axonal injury.","authors":"Zexuan Chen, Liqun Tang, Bao Yang, Yiping Liu, Zhenyu Jiang, Licheng Zhou, Zejia Liu","doi":"10.1371/journal.pcbi.1014837","DOIUrl":"10.1371/journal.pcbi.1014837","url":null,"abstract":"<p><p>Deformation-induced injury of white matter nerve bundles is prevalent in central nervous system injuries, leading to a series of neurological dysfunctions. To describe the effect of deformation injury on the physiological electrical signals of neurons, several axonal electrophysiological damage models based on the Hodgkin-Huxley equations have been proposed. However, none of these models can fully characterize the results of white matter nerve stretching experiments under different rates and amplitudes. Building on previous work by peers, we propose a novel axonal deformation damage model that comprehensively considers the coupled effects of sodium and potassium channel damage on gating variable rate constants, as well as the differences in mechanical properties and injury among individual axons during deformation-with these differences continuously modeled by a statistical distribution. The proposed model can not only reasonably describe the sodium left-shift phenomenon (a key post-injury feature) but also accurately reproduce the neuro-electrophysiological responses of nerve fascicles under various stretching conditions. This new neuro-electrophysiological model for nerve fascicle injury exhibits good universality and provides a mechanical mechanism-based reference for future clinical treatment strategies of nerve injury.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014837"},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13652255/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149149210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Process bigraphs and the architecture of compositional systems biology.","authors":"Eran Agmon, Ryan K Spangler","doi":"10.1371/journal.pcbi.1014819","DOIUrl":"10.1371/journal.pcbi.1014819","url":null,"abstract":"<p><p>Building multiscale biological models requires the integration of independently developed submodels, which means moving shared variables between them and coordinating when each submodel runs. Existing tools typically address isolated biological mechanisms with specific numerical methods, rarely specify which variables each model reads and writes, how those variables are translated, and how model updates are synchronized. We present Process Bigraph, a framework for composing and simulating multiscale models. Process Bigraph generalizes the architectural ideas previously used in the Vivarium software into a shared specification that describes process interfaces, hierarchical data structures, composition patterns, and orchestration patterns. The paper explains how the framework is organized and why it makes biological models easier to understand, reuse, and build on; S1 Text provides the formal specification. We introduce Vivarium 2.0 as an open-source implementation of the process bigraph framework. We demonstrate its utility with Spatio-Flux, a standalone library of microbial ecosystem simulations that combine kinetic equations, dynamic flux balance analysis, and different spatial processes. These simulations illustrated how the framework effectively integrates diverse biological processes, leading to emergent spatially organized population dynamics. Finally, we discuss implications for emerging multiscale modeling standards. Availability and implementation: Vivarium 2.0 is a suite of software libraries that include: (1) bigraph-schema, for defining and operating on data types within a hierarchical JSON-based format; (2) process-bigraph, for defining process interfaces, composite simulations, and executing them; and (3) viva-superpowers, for AI-assisted construction and composition of process bigraphs. Spatio-Flux is a reference application used in this paper to demonstrate the framework's utility. S1 Text provides detailed descriptions of these software libraries. All software is open-source and available at: https://github.com/vivarium-collective.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014819"},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13652326/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149147412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hyper-mutational processes provide a head-start for weak cancer drivers: Explaining atypical KRAS variants.","authors":"Michael D Nicholson, Ian Tomlinson","doi":"10.1371/journal.pcbi.1014858","DOIUrl":"10.1371/journal.pcbi.1014858","url":null,"abstract":"<p><p>Hypermutant cancers frequently contain atypical driver gene variants, which may provide sub-optimal oncogenic advantages. The reason why weak cancer drivers prevail and are not outcompeted by stronger alternatives is unclear. Here, using mathematical modelling, we show that aberrant mutational processes alone can account for the detection of weak, rather than canonical, driver mutations. We find that simply increasing the mutation rate per cell division, without altering selection or mutational biases, can lead to the dominance of weak drivers due to rapidly occurring further driver events. This effect can be further enhanced by mutational biases towards specific nucleotide sequence contexts. Focusing on POLE-mutant (DNA polymerase epsilon proofreading-deficient) colorectal cancers, we quantify the mutation bias for varied KRAS drivers under both POLE-mutant and non-hypermutant mutational processes. In POLE-mutant cancers, the combination of the bias coupled with an elevated mutation rate is sufficient to explain the enrichment of atypical KRAS drivers. Furthermore, model predictions are consistent with the observed prevalence of atypical KRAS drivers observed in mismatch repair deficient colorectal cancers. Thus, differential selection across these cancer types need not be invoked to explain the variation in driver mutations. Our study clarifies the interplay of mutation and selection during the evolutionary dynamics of tumourigenesis.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014858"},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13674863/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149149029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How does explicit reliability guide choices? Effect of trustworthiness on choice and metacognition.","authors":"Keiji Ota, Anthony Ciston, Patrick Haggard, Thibault Gajdos Preuss, Lucie Charles","doi":"10.1371/journal.pcbi.1014818","DOIUrl":"10.1371/journal.pcbi.1014818","url":null,"abstract":"<p><p>A key challenge in today's fast-paced digital world is to integrate information from various sources, which differ in their reliability. Yet, little is known about how explicit probabilistic information about the likelihood that a source provides correct information is used in decision-making. Here, we investigated how such explicit reliability markers are integrated into decisions and the extent to which individuals have metacognitive insight into this process. We developed a novel paradigm where participants viewed predictions from sources of varying explicit reliability to help them make a choice between two options. After each decision, they rated how much they felt a given source influenced their choice. Using computational modelling, we estimated the effective reliability that participants assigned to each source. Overall, we found that participants did not take source reliability at face value, inappropriately using the stated probabilities of source correctness to make a choice. Interestingly, even sources that were explicitly labelled as unreliable biased choices, as if these were treated as moderately reliable. Additionally, the presence of sources flagged as lying ones and known to be reliably predicting the incorrect answer impaired performance by increasing leakiness in evidence accumulation. Despite these biases, participants showed some metacognitive awareness of what influenced their choices: they were aware of the impact unreliable sources had on their decisions and could evaluate how much a given source had increased the likelihood of their response. These results suggest that people distort explicit source reliability but have some awareness of this process.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014818"},"PeriodicalIF":3.6,"publicationDate":"2026-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13652329/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149148956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Awake alpha bursting emerges as the dynamic working state in a lateral geniculate thalamocortical cell model.","authors":"Kees McGahan, Michelle McCarthy, Nancy Kopell","doi":"10.1371/journal.pcbi.1014654","DOIUrl":"10.1371/journal.pcbi.1014654","url":null,"abstract":"<p><p>The awake thalamus is known to be able to filter primary sensory input with and without external modulation. Through the construction and analysis of a novel computational model of a lateral geniculate thalamocortical neuron, we demonstrate how the processing of sensory retinal input is influenced by the underlying thalamic dynamic state. Our model, using only currents verified against expression data from publicly available datasets, is the first to produce five experimentally established distinct dynamic firing regimes. We demonstrate that the thalamocortical cell transitions between these dynamic states in response to glutamatergic signals from the cortex or cholinergic arousal signals coming from the brainstem. We focus on signal processing in the model dynamic states associated with the awake thalamic alpha rhythm where we find that the ability of retinal inputs to generate thalamic spikes is a balance between the timing of retinal spikes, the excitability break imposed by the M-current, and the decay time of the L-type calcium current. Finally, we explore how these two currents help the thalamus process extra-retinal rhythmic inputs, showing the model produces entrainment to slower inhibitory and excitatory rhythms, as well as detailing the importance of nesting faster frequency rhythms within slow cycles for successful thalamic transmission. Our results suggest that the awake alpha rhythm is indirectly causal by acting as a marker for the interaction of these two currents. This biophysically-constrained lateral geniculate thalamocortical cell model generates predictions regarding rhythmic dynamics under different arousal states, thalamic control of retinogeniculate transmission, and the possible impacts neurological disorders, like schizophrenia, have on thalamic processing. Variations of this model could be used to explore the functions of higher order thalamic nuclei, thereby extending its use to investigating more complex cognitive processes.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014654"},"PeriodicalIF":3.6,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13649143/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149138028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DyME: An MD-based engine exploiting HTP mutagenesis for protein engineering and recognition mimicry.","authors":"Pedro M Guillem-Gloria, Gloria Ruiz-Gómez, M Teresa Pisabarro","doi":"10.1371/journal.pcbi.1014221","DOIUrl":"10.1371/journal.pcbi.1014221","url":null,"abstract":"<p><p>Protein recognition mimicry (PRM) is of great interest in the field of molecular bioengineering and rational design, with mutagenesis frequently employed to analyze the effects of altering amino acids involved in molecular recognition. The conformational and energetic effects of such alterations can be investigated in detail with the help of molecular dynamics (MD) methodologies. While existing MD-based computational tools can be used to explore a particular set of mutations at a time, suitable for small-scale studies, high-throughput (HTP) exploration of protein recognition for engineering purposes would greatly benefit from an integrative platform that streamlines preparation, mutagenesis, simulation and post-processing of up to several thousand molecular systems, along with robust tools for comprehensive and straightforward comparative analysis. DyME (Dynamic Mutagenesis Engine) is a distributed platform that enables systematic investigations of protein recognition mimicry by combining HTP mutagenesis, solvated MD simulations and a Toolbox for comparative analysis (TCA), including interfacial water-site mapping. DyME uses 3D structural information of any protein-protein or protein-DNA complex as input. Its automated MD-based mutagenesis engine facilitates systematic investigation of how site-specific alterations affect recognition, enabling the organization of single, double and triple modifications into combinatorial libraries for comprehensive comparative analysis. In DyME, relevant MD trajectory-derived data is scavenged and stored into a central database, providing aggregation capabilities that ease multi-feature analysis across an extensive collection of simulations. An interactive web-GUI and specialized widgets simplify preparation and efficient molecular and numerical comparative exploration. DyME's capabilities are evaluated using available experimental data. Its source code is available at https://github.com/pisabarro-group/DYME.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014221"},"PeriodicalIF":3.6,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13671646/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149128629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A physiologically constrained calibration framework for cardiovascular models applied to a paediatric synthetic sepsis population.","authors":"Manuel T Cabeleira, Samiran Ray, Nicholas C Ovenden, Vanessa Díaz-Zuccarini","doi":"10.1371/journal.pcbi.1014847","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1014847","url":null,"abstract":"<p><p>Calibration of mechanistic cardiovascular models is a central barrier to their use in population analysis and patient-specific simulation, particularly in settings where key physiological variables are unobservable and multiple parameter combinations can reproduce the same haemodynamic targets. In this work, we present Embedded Feedback Controller (EFC), a calibration framework for ODE-based lumped-parameter cardiovascular models in which selected physiological parameters are promoted to dynamic states and driven toward prescribed targets through embedded controller equations. By exploiting the qualitative structure of the governing equations, EFC enforces physiologically consistent parameter-variable relationships and converges to the single solution admitted by an over-determined set of targets, reproducibly and independently of the initial conditions, at a cost that scales efficiently with model complexity. The framework is demonstrated in silico, using a mechanistic cardiovascular model to generate virtual paediatric populations spanning normal physiology and two septic shock phenotypes (warm and cold shock) from literature-derived target ranges, achieving <1% residual error across pressures, flows, and compartmental volumes. The resulting parameter distributions are consistent, by construction with theoretical haemodynamic adaptations in paediatric sepsis, including alterations in vascular resistance, compliance, cardiac elastance, and effective blood volume. Importantly, persistent calibration residuals arise when target combinations are structurally incompatible with the model and the parameter carrying the residual is held at a bound, providing an explicit and interpretable diagnostic of feasibility limits. These results establish EFC as a general, scalable calibration strategy for mechanistic cardiovascular models and a practical foundation for virtual population generation and future patient-specific digital twin applications in critical care.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014847"},"PeriodicalIF":3.6,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149128546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A joint mixture Tobit method with latent microbial abundance improves detection of microbiome-disease associations in zero-inflated data.","authors":"Junrong Deng, Dong Chen, Siyuan Shen, Yuyang Zhou, Hanyu Cui, Yu Qiu, Qiming Li, Yue-Qing Hu","doi":"10.1371/journal.pcbi.1014844","DOIUrl":"10.1371/journal.pcbi.1014844","url":null,"abstract":"<p><p>Zero inflation remains a major challenge in microbiome differential abundance analysis, often resulting in inflated type I error rates or reduced statistical power. Although numerous methods have been proposed to address excess zeros, many existing approaches do not explicitly distinguish between distinct zero-generating mechanisms, and censoring-based modeling perspectives remain relatively underexplored in microbiome data analysis. To advance methodological development in this area, we introduce a novel censoring-based modeling perspective for microbiome differential abundance analysis. Specifically, we develop a joint mixture Tobit (joint mTobit) method for zero-inflated microbiome data. Building on a mixture Tobit formulation, the model incorporates a point-mass component to represent structural zeros, while modeling latent microbial abundance via a Tobit regression component. The proposed framework jointly links disease status, latent true microbial abundance, and relevant covariates within a unified probabilistic model, allowing appropriate adjustment for confounding factors and facilitating more reliable statistical inference. By explicitly modeling the latent abundance underlying observed counts, the joint mTobit method improves estimation stability and enhances detection power under zero inflation. Extensive simulation studies demonstrate that the joint mTobit method achieves effective type I error control while maintaining high statistical power and stable coefficient estimation across a wide range of settings. Application to a real-world colorectal cancer and adenoma microbiome dataset further illustrates its ability to identify biologically meaningful differentially abundant taxa. Overall, this work develops a joint mTobit modeling framework for zero-inflated microbiome data, enabling inference on latent microbial abundance and providing a censoring-based statistical framework for investigating disease-microbiome associations in differential abundance analysis.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014844"},"PeriodicalIF":3.6,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13671660/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149128554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}