PLoS Computational Biology最新文献

{"title":"Comparison of sequence- and structure-based antibody clustering approaches on simulated repertoire sequencing data.","authors":"Katharina Waury, Stefan Lelieveld, Sanne Abeln, Henk-Jan van den Ham","doi":"10.1371/journal.pcbi.1013057","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1013057","url":null,"abstract":"<p><p>Repertoire sequencing allows us to investigate the antibody-mediated immune response. The clustering of sequences is a crucial step in the data analysis pipeline, aiding in the identification of functionally related antibodies. The conventional clustering approach of clonotyping relies on sequence information, particularly CDRH3 sequence identity and V/J gene usage, to group sequences into clonotypes. It has been suggested that the limitations of sequence-based approaches to identify sequence-dissimilar but functionally converged antibodies can be overcome by using structure information to group antibodies. Recent advances have made structure-based methods feasible on a repertoire level. However, so far, their performance has only been evaluated on single-antigen sets of antibodies. A comprehensive comparison of the benefits and limitations of structure-based tools on realistic and diverse repertoire data is missing. Here, we aim to explore the promise of structure-based clustering algorithms to replace or augment the standard sequence-based approach, specifically by identifying low-sequence identity groups. Two methods, SAAB+ and SPACE2, are evaluated against clonotyping. We curated a dataset of well-annotated pairs of antibodies that show high overlap in epitope residues and thus bind the same region within their respective antigen. This set of antibodies was introduced into a simulated repertoire to compare the performance of clustering approaches on a diverse antibody set. Our analysis reveals that structure-based methods do group more antibodies together compared to clonotyping. However, it also highlights the limitations associated with the need for same-length CDR regions by SPACE2. This work thoroughly compares the utility of different clustering methods and provides insights into what further steps are required to effectively use antibody structural information to group immune repertoire data.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 5","pages":"e1013057"},"PeriodicalIF":3.8,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144187816","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":"Understanding the hemodynamic changes in fetuses with coarctation of the aorta using a lumped model of fetal circulation.","authors":"Inmaculada Villanueva-Baxarias, Anna Pellisé-Tintoré, María Pérez-Rodríguez, Laura Nogué, Pooja Vaziraani, Iris Soveral, Fàtima Crispi, Olga Gómez, Patricia Garcia-Canadilla, Oscar Camara, Bart Bijnens, Gabriel Bernardino","doi":"10.1371/journal.pcbi.1013096","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1013096","url":null,"abstract":"<p><p>Coarctation of the aorta (CoA) is a common congenital heart defect characterized by aortic narrowing. Prenatally, it has mild hemodynamic effects as right ventricular disproportion and ductus arteriosus (DA) dilation occur as adaptive mechanisms, but their impact on CoA hemodynamics remains poorly understood. To investigate this, we built a closed 0D computational model of fetal circulation and simulated different CoA cardiovascular remodeling patterns, including aortic isthmus (AoI) narrowing, ventricular disproportion, and DA dilation. Our results showed mild AoI narrowing (80% of reference diameter) required up to 1.7 right/left ventricular end-diastolic volume ratio and 115% DA dilation to maintain physiological pressures, wall shear stresses, and organ perfusion. In contrast, severe narrowing (20% of reference AoI diameter) required up to 5 right/left ventricular end-diastolic volume ratio and 125% DA dilation, highlighting the necessity of co-occurrence of prenatal ventricular disproportion and DA dilation to compensate for AoI narrowing. These physiological regions were validated with ultrasonographic measurements from 7 controls and 9 CoA patients. We compared blood pressures, velocities, and volumetric flow rates across different fetoplacental anatomical sites. AoI velocity showed a delayed retrograde flow peak and increased antegrade diastolic velocity with greater AoI narrowing, which may aid in diagnosing CoA. Minimal differences were observed in other velocities and pressures. Volumetric flow rates across varying degrees of AoI narrowing decreased in the AoI and mitral and aortic valves, remained stable in the middle cerebral and umbilical arteries, and increased in the DA and tricuspid and pulmonary valves. Therefore, we corroborated that in fetal CoA a redistribution of blood flow occurs to ensure perfusion of the brain and placenta, without a significant alteration in fetal hemodynamics (blood pressure and velocities) except for increased diastolic velocities in the AoI.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 5","pages":"e1013096"},"PeriodicalIF":3.8,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144187817","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":"Cellular morphodynamics as quantifiers for functional states of resident tissue macrophages in vivo.","authors":"Miriam Schnitzerlein, Eric Greto, Anja Wegner, Anna Möller, Oliver Aust, Oumaima Ben Brahim, David B Blumenthal, Vasily Zaburdaev, Stefan Uderhardt","doi":"10.1371/journal.pcbi.1011859","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1011859","url":null,"abstract":"<p><p>Resident tissue macrophages (RTMs) are essential for tissue homeostasis. Their diverse functions, from monitoring interstitial fluids to clearing cellular debris, are accompanied by characteristic morphological changes that reflect their functional status. While current knowledge of macrophage behaviour comes primarily from in vitro studies, their dynamic behavior in vivo is fundamentally different, necessitating a more physiologically relevant approach to their understanding. In this study, we employed intravital imaging to generate dynamic data from peritoneal RTMs in mice under various conditions and developed a comprehensive image processing pipeline to quantify RTM morphodynamics over time, defining human-interpretable cell size and shape features. These features allowed for the quantitative and qualitative differentiation of cell populations in various functional states, including pro- and anti-inflammatory activation and endosomal dysfunction. The study revealed that under steady-state conditions, RTMs exhibit a wide range of morphodynamical phenotypes, constituting a naïve morphospace of behavioral motifs. Upon challenge, morphodynamic patterns changed uniformly at the population level but predominantly within the constraints of this naïve morphospace. Notably, aged animals displayed a markedly shifted naïve morphospace, indicating drastically different behavioral patterns compared to their young counterparts. The developed method also proved valuable in optimizing explanted tissue setups, bringing RTM behavior closer to the physiological native state. Our versatile approach thus provides novel insights into the dynamic behavior of bona fide macrophages in vivo, enabling the distinction between physiological and pathological cell states and the assessment of functional tissue age on a population level.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 5","pages":"e1011859"},"PeriodicalIF":3.8,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144182502","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":"Accounting for contact tracing in epidemiological birth-death models.","authors":"Anna Zhukova, Olivier Gascuel","doi":"10.1371/journal.pcbi.1012461","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1012461","url":null,"abstract":"<p><p>Phylodynamics bridges the gap between classical epidemiology and pathogen genome sequence data by estimating epidemiological parameters from time-scaled pathogen phylogenetic trees. The models used in phylodynamics typically assume that the sampling procedure is independent between infected individuals. However, this assumption does not hold for many epidemics, in particular for such sexually transmitted infections as HIV-1, for which contact tracing schemes are included in health policies of many countries. We extended phylodynamic multi-type birth-death (MTBD) models with contact tracing (CT), and developed a simulator to generate trees under MTBD and MTBD-CT models. We proposed a non-parametric test for detecting contact tracing in pathogen phylogenetic trees. Its application to simulated data showed that it is both highly specific and sensitive. For the simplest representative of the MTBD-CT family, the BD-CT(1) model, where only the last contact can be notified, we solved the differential equations and proposed a closed form solution for the likelihood function. We implemented a maximum-likelihood program, which estimates the BD-CT(1) model parameters and their confidence intervals from phylogenetic trees. It performed accurate parameter inference on BD and BD-CT(1) simulated data, and detected contact tracing in HIV-1 B epidemics in Zurich and the UK. Importantly, we showed that not accounting for contact tracing when it is present, leads to bias in parameter estimation with the BD model (overestimation of the becoming-non-infectious rate). This bias is also present, but greatly reduced, when the BD-CT(1) model is used on data where multiple contacts can be notified. Our CT test, MTBD-CT tree simulator and BD-CT(1) parameter estimator are freely available at GitHub (evolbioinfo/treesimulator and evolbioinfo/bdct).</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 5","pages":"e1012461"},"PeriodicalIF":3.8,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144182196","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":"RETINA: Reconstruction-based pre-trained enhanced TransUNet for electron microscopy segmentation on the CEM500K dataset.","authors":"Cheng Xing, Ronald Xie, Gary D Bader","doi":"10.1371/journal.pcbi.1013115","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1013115","url":null,"abstract":"<p><p>Electron microscopy (EM) has revolutionized our understanding of cellular structures at the nanoscale. Accurate image segmentation is required for analyzing EM images. While manual segmentation is reliable, it is labor-intensive, incentivizing the development of automated segmentation methods. Although deep learning-based segmentation has demonstrated expert-level performance, it lacks generalizable performance across diverse EM datasets. Current approaches usually use either convolutional or transformer-based neural networks for image feature extraction. We developed the RETINA method, which combines pre-training on the large, unlabeled CEM500K EM image dataset with a hybrid neural-network model architecture that integrates both local (convolutional layer) and global (transformer layer) image processing to learn from manual image annotations. RETINA outperformed existing models on cellular structure segmentation on five public EM datasets. This improvement works toward automated cellular structure segmentation for the EM community.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 5","pages":"e1013115"},"PeriodicalIF":3.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144174704","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":"OmniSegger: A time-lapse image analysis pipeline for bacterial cells.","authors":"Teresa W Lo, Kevin J Cutler, H James Choi, Paul A Wiggins","doi":"10.1371/journal.pcbi.1013088","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1013088","url":null,"abstract":"<p><p>Time-lapse [-50mm][-4mm]Please expand the first name for author \"H. James Choi\".microscopy is a powerful tool to study the biology of bacterial cells. The development of pipelines that facilitate the automated analysis of these datasets is a long-standing goal of the field. In this paper, we describe the OmniSegger pipeline developed as an open-source, modular, and holistic suite of algorithms whose input is raw microscopy images and whose output is a wide range of quantitative cellular analyses, including dynamical cell cytometry data and cellular visualizations. The updated version described in this paper introduces two principal refinements: (i) robustness to cell morphologies and (ii) support for a range of common imaging modalities. To demonstrate robustness to cell morphology, we present an analysis of the proliferation dynamics of Escherchia coli treated with a drug that induces filamentation. To demonstrate extended support for new image modalities, we analyze cells imaged by five distinct modalities: phase-contrast, two brightfield modalities, and cytoplasmic and membrane fluorescence. Together, this pipeline should greatly increase the scope of tractable analyses for bacterial microscopists.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 5","pages":"e1013088"},"PeriodicalIF":3.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144174703","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":"Ten simple rules for queer data collection and analysis by STEM researchers.","authors":"Dori M Grijseels, M Banqueri, Keerthana Iyer, Lee Hanlin, Melanie Ortiz Alvarez de la Campa, David Pagliaccio, Bittu K Rajaraman, Eitan Schechtman","doi":"10.1371/journal.pcbi.1013091","DOIUrl":"10.1371/journal.pcbi.1013091","url":null,"abstract":"<p><p>Queer people are still underrepresented both as STEM researchers and participants, partially due to a dearth of accurate data on this demographic. The lack of consideration for queer identities in data collection and dissemination causes a vicious cycle of exclusion. To address this invisibility, it is important to collect and report data in an inclusive and accurate manner across all areas of research, including in studies that are not specifically focused on queer populations. However, STEM researchers are often unsure of how to properly collect data in a manner that fairly represents queer people. We have developed a list of Ten Simple rules to aid researchers to perform data collection on queer individuals, focusing on study design and data dissemination. We address several issues in queer data, such as language use, dealing with small populations, and balancing demands. We also discuss how to extend this inclusive practice for studies on animal populations. These rules are aimed at anybody surveying populations which may contain queer individuals, including for example research studies and inclusivity surveys for conferences. By providing practical tips, we hope to alleviate insecurity and confusion around this topic.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 5","pages":"e1013091"},"PeriodicalIF":3.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12118915/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144174707","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":"Stimulus uncertainty and relative reward rates determine adaptive responding in perceptual decision-making.","authors":"Luis de la Cuesta-Ferrer, Christina Koß, Sarah Starosta, Nils Kasties, Daniel Lengersdorf, Frank Jäkel, Maik C Stüttgen","doi":"10.1371/journal.pcbi.1012636","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1012636","url":null,"abstract":"<p><p>In dynamic environments, animals must select actions based on sensory input as well as expected positive and negative consequences. This type of behavior is typically studied using perceptual decision making (PDM) tasks. The arguably most influential framework for describing the cognitive processes underlying PDM is signal detection theory (SDT). One central assumption of SDT is that observers make perceptual decisions by comparing sensory evidence to a static decision criterion. However, mounting evidence suggests that the criterion is in fact highly dynamic and that observers adjust it flexibly according to task demands. Nevertheless, the mechanisms by which observers integrate stimulus and reward information for adaptive criterion learning remain not well understood. Here, we systematically investigated the factors influencing criterion setting at the single-trial level. To that end, we first specified three SDT-based models that learn either from reward, reward omission, or both. Next, by concomitantly manipulating stimulus and reward probabilities, we constructed experimental conditions in which these models make divergent predictions. Finally, we subjected rats and pigeons to a PDM task comprising these conditions. We find that subjects adopted decision criteria that maximize total reward in all experimental conditions. Detailed behavioral analyses reveal that criterion learning is driven by the integration of rewards, not reward omissions, and that reward integration is influenced by two additional factors: first, the degree of stimulus uncertainty, and second, the difference in the relative reward rates (rather than the absolute reward rates) between the choice alternatives. A model incorporating these factors accounts well for criterion dynamics across experimental conditions for both species and links signal detection theory to a learning mechanism operating at the level of single trials which, in the steady state, produces behavior similar to the matching law, a central tenet of learning theory.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 5","pages":"e1012636"},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144161080","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":"Relating sparse and predictive coding to divisive normalization.","authors":"Yanbo Lian, Anthony N Burkitt","doi":"10.1371/journal.pcbi.1013059","DOIUrl":"10.1371/journal.pcbi.1013059","url":null,"abstract":"<p><p>Sparse coding, predictive coding and divisive normalization have each been found to be principles that underlie the function of neural circuits in many parts of the brain, supported by substantial experimental evidence. However, the connections between these related principles are still poorly understood. Sparse coding and predictive coding can be reconciled into a learning framework with predictive structure and sparse responses, termed as sparse/predictive coding. However, how sparse/predictive coding (a learning model) is connected with divisive normalization (not a learning model) is still not well investigated. In this paper, we show how sparse coding, predictive coding, and divisive normalization can be described within a unified framework, and illustrate this explicitly within the context of a two-layer neural learning model of sparse/predictive coding. This two-layer model is constructed in a way that implements sparse coding with a network structure that is constructed by implementing predictive coding. We demonstrate how a homeostatic function that regulates neural responses in the model can shape the nonlinearity of neural responses in a way that replicates different forms of divisive normalization. Simulations show that the model can learn simple cells in the primary visual cortex with the property of contrast saturation, which has previously been explained by divisive normalization. In summary, the study demonstrates that the three principles of sparse coding, predictive coding, and divisive normalization can be connected to provide a learning framework based on biophysical properties, such as Hebbian learning and homeostasis, and this framework incorporates both learning and more diverse response nonlinearities observed experimentally. This framework has the potential to also be used to explain how the brain learns to integrate input from different sensory modalities.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 5","pages":"e1013059"},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12112309/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144161064","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":"The respiratory cycle modulates distinct dynamics of affective and perceptual decision-making.","authors":"Malthe Brændholt, Niia Nikolova, Melina Vejlø, Leah Banellis, Francesca Fardo, Daniel S Kluger, Micah Allen","doi":"10.1371/journal.pcbi.1013086","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1013086","url":null,"abstract":"<p><p>Breathing plays a critical role not only in homeostatic survival, but also in modulating other non-interoceptive perceptual and affective processes. Recent evidence from both human and rodent models indicates that neural and behavioural oscillations are influenced by respiratory state as breathing cycles from inspiration to expiration. To explore the mechanisms behind these effects, we carried out a psychophysical experiment where 41 participants categorised dot motion and facial emotion stimuli in a standardised discrimination task. When comparing behaviour across respiratory states, we found that inspiration accelerated responses in both domains. We applied a hierarchical evidence accumulation model to determine which aspects of the latent decision process best explained this acceleration. Computational modelling showed that inspiration reduced evidential decision boundaries, such that participants prioritised speed over accuracy in the motion task. In contrast, inspiration shifted the starting point of affective evidence accumulation, inducing a bias towards categorising facial expressions as more positive. These findings provide a novel computational account of how breathing modulate distinct aspects of perceptual and affective decision-dynamics.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 5","pages":"e1013086"},"PeriodicalIF":3.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144161098","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}