Physical biologyPub Date : 2025-06-12DOI: 10.1088/1478-3975/addf08
Andy Reynolds
{"title":"Why swarming insects have perplexing spatial statistics.","authors":"Andy Reynolds","doi":"10.1088/1478-3975/addf08","DOIUrl":"10.1088/1478-3975/addf08","url":null,"abstract":"<p><p>Unlike flocks of birds and schools of fish that show net motion and synchronized motion, insect mating swarms are stationary and lack velocity ordering. Their collective nature when unperturbed is instead evident in their spatial statistics. In stark contrast with bird flocks, wherein the number density can fluctuate enormously from flock to flock, the number density of individuals in laboratory swarms of the midge<i>Chironomus riparius</i>is approximately constant. Nonetheless, as swarms grow more populous, individuals cluster more and more. Here with the aid of stochastic trajectory models I show that these two seemingly contradictory behaviours can be attributed to the presence of multiplicative noise. The modelling also predicts that swarms are most stable when they are asymptotically large.</p>","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144187805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical biologyPub Date : 2025-06-10DOI: 10.1088/1478-3975/adda85
Luis U Aguilera, Lisa M Weber, Eric Ron, Connor R King, Kaan Öcal, Alex Popinga, Joshua Cook, Michael P May, William S Raymond, Zachary R Fox, Linda S Forero-Quintero, Jack R Forman, Alexandre David, Brian Munsky
{"title":"Methods in quantitative biology-from analysis of single-cell microscopy images to inference of predictive models for stochastic gene expression.","authors":"Luis U Aguilera, Lisa M Weber, Eric Ron, Connor R King, Kaan Öcal, Alex Popinga, Joshua Cook, Michael P May, William S Raymond, Zachary R Fox, Linda S Forero-Quintero, Jack R Forman, Alexandre David, Brian Munsky","doi":"10.1088/1478-3975/adda85","DOIUrl":"10.1088/1478-3975/adda85","url":null,"abstract":"<p><p>The field of quantitative biology (q-bio) seeks to provide precise and testable explanations for observed biological phenomena by applying mathematical and computational methods. The central goals of q-bio are to (1) systematically propose quantitative hypotheses in the form of mathematical models, (2) demonstrate that these models faithfully capture a specific essence of a biological process, and (3) correctly forecast the dynamics of the process in new, and previously untested circumstances. Achieving these goals depends on accurate analysis and incorporating informative experimental data to constrain the set of potential mathematical representations. In this introductory tutorial, we provide an overview of the state of the field and introduce some of the computational methods most commonly used in q-bio. In particular, we examine experimental techniques in single-cell imaging, computational tools to process images and extract quantitative data, various mechanistic modeling approaches used to reproduce these quantitative data, and techniques for data-driven model inference and model-driven experiment design. All topics are presented in the context of additional online resources, including open-source Python notebooks and open-ended practice problems that comprise the technical content of the annual Undergraduate Quantitative Biology Summer School (UQ-Bio).</p>","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12150428/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144102425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical biologyPub Date : 2025-05-30DOI: 10.1088/1478-3975/addc2a
Fang Yu, Mikhail Tikhonov
{"title":"Comparing regression-based approaches for identifying microbial functional groups.","authors":"Fang Yu, Mikhail Tikhonov","doi":"10.1088/1478-3975/addc2a","DOIUrl":"10.1088/1478-3975/addc2a","url":null,"abstract":"<p><p>Microbial communities are composed of functionally integrated taxa, and identifying which taxa contribute to a given ecosystem function is essential for predicting community behaviors. This study compares the effectiveness of a previously proposed method for identifying 'functional taxa,' ensemble quotient optimization (EQO), to a potentially simpler approach based on the least absolute shrinkage and selection operator (LASSO). In contrast to LASSO, EQO uses a binary prior on coefficients, assuming uniform contribution strength across taxa. Using synthetic datasets with increasingly realistic structure, we demonstrate that EQO's strong prior enables it to perform better in low-data regime. However, LASSO's flexibility and efficiency can make it preferable as data complexity increases. Our results detail the favorable conditions for EQO and emphasize LASSO as a viable alternative.</p>","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144128525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical biologyPub Date : 2025-05-06DOI: 10.1088/1478-3975/add071
Marzuk Ahmed, Md Masum Billah, Masahito Yamazaki
{"title":"Effect of membrane tension on pore formation induced by antimicrobial peptides and other membrane-active peptides.","authors":"Marzuk Ahmed, Md Masum Billah, Masahito Yamazaki","doi":"10.1088/1478-3975/add071","DOIUrl":"https://doi.org/10.1088/1478-3975/add071","url":null,"abstract":"<p><p>Membrane tension plays an important role in various aspects of the dynamics and functions of cells. Here, we review recent studies of the effect of membrane tension on pore formation in lipid bilayers and pore formation induced by membrane-active peptides (MAPs) including antimicrobial peptides (AMPs). For this purpose, the micropipette aspiration method using a patch of cell membrane/lipid bilayers and a giant unilamellar vesicle (GUV)/a total cell, and the application of osmotic pressure (Π) to suspensions of large unilamellar vesicles (LUVs) have been used. However, these conventional methods have some drawbacks for the investigation of the effect of membrane tension on the actions of MAPs such as AMPs. Recently, to overcome these drawbacks, a new Π method using GUVs has been developed. Here, we focus on this Π method as a new technique for revealing the effect of membrane tension on the MAPs-induced pore formation. Firstly, we review studies of the effect of membrane tension on pore formation in lipid bilayers as determined by conventional methods. Secondly, after a brief review of studies of the effect of Π on LUVs, we describe the estimation of membrane tension in GUVs induced by Π and the Π-induced pore formation. Thirdly, after a review of the effect of membrane tension on the MAPs-induced pore formation as obtained by the conventional methods, we describe an application of the Π method to studies of the effect of membrane tension on AMP-induced pore formation. Finally, we discuss the advantages of the Π method over conventional methods and consider future perspectives.</p>","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":"22 3","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144040789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical biologyPub Date : 2025-04-24DOI: 10.1088/1478-3975/adcd37
Christian Cunningham, Bo Sun
{"title":"Representation of high-dimensional cell morphology and morphodynamics in 2D latent space.","authors":"Christian Cunningham, Bo Sun","doi":"10.1088/1478-3975/adcd37","DOIUrl":"10.1088/1478-3975/adcd37","url":null,"abstract":"<p><p>The morphology and morphodynamics of cells as important biomarkers of the cellular state are widely appreciated in both fundamental research and clinical applications. Quantification of cell morphology often requires a large number of geometric measures that form a high-dimensional feature vector. This mathematical representation creates barriers to communicating, interpreting, and visualizing data. Here, we develop a deep learning-based algorithm to project 13-dimensional (13D) morphological feature vectors into 2-dimensional (2D) morphological latent space (MLS). We show that the projection has less than 5% information loss and separates the different migration phenotypes of metastatic breast cancer cells. Using the projection, we demonstrate the phenotype-dependent motility of breast cancer cells in the 3D extracellular matrix, and the continuous cell state change upon drug treatment. We also find that dynamics in the 2D MLS quantitatively agrees with the morphodynamics of cells in the 13D feature space, preserving the diffusive power and the Lyapunov exponent of cell shape fluctuations even though the dimensional reduction projection is highly nonlinear. Our results suggest that MLS is a powerful tool to represent and understand the cell morphology and morphodynamics.</p>","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":"22 3","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12083545/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143977000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical biologyPub Date : 2025-03-05DOI: 10.1088/1478-3975/adb9af
Burak Erman
{"title":"Fluctuation-driven synergy, redundancy, signal to noise ratio and error correction in protein allostery.","authors":"Burak Erman","doi":"10.1088/1478-3975/adb9af","DOIUrl":"10.1088/1478-3975/adb9af","url":null,"abstract":"<p><p>This study explores the relationship between residue fluctuations and molecular communication in proteins, emphasizing the role of these dynamics in allosteric regulation. We employ computational tools including the Gaussian network model, mutual information, and interaction information, to analyze how stochastic interactions among residues contribute to functional interactions while also introducing noise. Our approach is based on the postulate that residues experience continuous stochastic bombardment from impulses generated by their neighbors, forming a complex network characterized by small-world scaling topology. By mapping these interactions through the Kirchhoff matrix framework, we demonstrate how conserved correlations enhance signaling pathways and provide stability against noise-like fluctuations. Notably, we highlight the importance of selecting relevant eigenvalues to optimize the signal-to-noise ratio in our analyses, a topic that has yet to be thoroughly investigated in the context of residue fluctuations. This work underscores the significance of viewing proteins as adaptive information processing systems, and emphasizes the fundamental mechanisms of biological information processing. The basic idea of this paper is the following: given two interacting residues on an allosteric path, what are the contributions of the remaining residues on this interaction. This naturally leads to the concept of synergy, redundancy and noise in proteins, which we analyze in detail for three proteins CheY, tyrosine phosphatase and<i>β</i>-lactoglobulin.</p>","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143493393","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical biologyPub Date : 2025-02-03DOI: 10.1088/1478-3975/ada862
Rajasekaran Bhavna, Mahendra Sonawane
{"title":"STIPS algorithm enables tracking labyrinthine patterns and reveals distinct rhythmic dynamics of actin microridges.","authors":"Rajasekaran Bhavna, Mahendra Sonawane","doi":"10.1088/1478-3975/ada862","DOIUrl":"10.1088/1478-3975/ada862","url":null,"abstract":"<p><p>Tracking and motion analyses of semi-flexible biopolymer networks from time-lapse microscopy images are important tools that enable quantitative measurements to unravel the dynamic and mechanical properties of biopolymers in living tissues, crucial for understanding their organization and function. Biopolymer networks are challenging to track due to continuous stochastic transitions, such as merges and splits, which cause local neighborhood rearrangements over short time and length scales. To address this, we propose the Spatio Temporal Information on Pixel Subsets algorithm to track these events by creating pixel subsets that link trajectories across frames. Using this method, we analyzed actin-enriched protrusions, or 'microridges,' which form dynamic labyrinthine patterns on squamous cell epithelial surfaces, mimicking 'active Turing-patterns.' Our results reveal two distinct actomyosin-based rhythmic dynamics in neighboring cells: a common pulsatile mechanism between 2 and 6.25 min period governing both fusion and fission events contributing to pattern maintenance, and cell area pulses predominantly exhibiting 10 min period.</p>","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142953504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical biologyPub Date : 2025-01-31DOI: 10.1088/1478-3975/adaa47
Peyman Fahimi, Lázaro A M Castanedo, P Thomas Vernier, Chérif F Matta
{"title":"Electrical homeostasis of the inner mitochondrial membrane potential.","authors":"Peyman Fahimi, Lázaro A M Castanedo, P Thomas Vernier, Chérif F Matta","doi":"10.1088/1478-3975/adaa47","DOIUrl":"10.1088/1478-3975/adaa47","url":null,"abstract":"<p><p>The electric potential across the inner mitochondrial membrane must be maintained within certain bounds for the proper functioning of the cell. A feedback control mechanism for the homeostasis of this membrane potential is proposed whereby an increase in the electric field decreases the rate-limiting steps of the electron transport chain (ETC). An increase in trans-membrane electric field limits the rate of proton pumping to the inter-membrane gap by slowing the ETC reactions and by intrinsically induced electroporation that depolarizes the inner membrane. The proposed feedback mechanism is akin to a Le Chatelier's-type principle of trans-membrane potential feedback control.</p>","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":"22 2","pages":""},"PeriodicalIF":2.0,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143067061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical biologyPub Date : 2024-12-27DOI: 10.1088/1478-3975/ad9cde
Mateusz Polakowski, Miłosz Panfil
{"title":"Quantum features of the transport through ion channels in the soft knock-on model.","authors":"Mateusz Polakowski, Miłosz Panfil","doi":"10.1088/1478-3975/ad9cde","DOIUrl":"https://doi.org/10.1088/1478-3975/ad9cde","url":null,"abstract":"<p><p>Ion channels are protein structures that facilitate the selective passage of ions across the membrane cells of living organisms. They are known for their high conductance and high selectivity. The precise mechanism between these two seemingly contradicting features is not yet firmly established. One possible candidate is the quantum coherence. In this work we study the quantum model of the soft knock-on conduction using the Lindblad equation taking into account the non-hermiticity of the model. We show that the model exhibits a regime in which high conductance coexists with high coherence. Our findings second the role of quantum effects in the transport properties of the ion channels.</p>","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":"22 1","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142896877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Physical biologyPub Date : 2024-12-05DOI: 10.1088/1478-3975/ad9792
Mintu Nandi
{"title":"Emergence of temporal noise hierarchy in co-regulated genes of multi-output feed-forward loop.","authors":"Mintu Nandi","doi":"10.1088/1478-3975/ad9792","DOIUrl":"10.1088/1478-3975/ad9792","url":null,"abstract":"<p><p>Natural variations in gene expression, called noise, are fundamental to biological systems. The expression noise can be beneficial or detrimental to cellular functions. While the impact of noise on individual genes is well-established, our understanding of how noise behaves when multiple genes are co-expressed by shared regulatory elements within transcription networks remains elusive. This lack of understanding extends to how the architecture and regulatory features of these networks influence noise. To address this gap, we study the multi-output feed-forward loop motif. The motif is prevalent in bacteria and yeast and influences co-expression of multiple genes by shared transcription factors (TFs). Focusing on a two-output variant of the motif, the present study explores the interplay between its architecture, co-expression (symmetric and asymmetric) patterns of the two genes, and the associated noise dynamics. We employ a stochastic modeling approach to investigate how the binding affinities of the TFs influence symmetric and asymmetric expression patterns and the resulting noise dynamics in the co-expressed genes. This knowledge could guide the development of strategies for manipulating gene expression patterns through targeted modulation of TF binding affinities.</p>","PeriodicalId":20207,"journal":{"name":"Physical biology","volume":" ","pages":""},"PeriodicalIF":2.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142732078","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}