The hydrodynamic interactions between bacterial flagella and surrounding boundaries are important for bacterial motility and gait in complex environment. By modeling each flagellar filament that is both thin and long as a string of spheres, we show that such hydrodynamic interactions can be accurately described through a resistance tensor, which can be efficiently evaluated numerically. For the case of close interaction between one bacterium and one passive colloidal sphere, we see notable difference between results from our model and those from the resistive force theory, showing that the error arises from negligence of the width of flagellar filaments in resistive force theory can be strong.
{"title":"Effective and efficient modeling of the hydrodynamics for bacterial flagella","authors":"Baopi Liu, Lu Chen, Ji Zhang, Xinliang Xu","doi":"arxiv-2408.06093","DOIUrl":"https://doi.org/arxiv-2408.06093","url":null,"abstract":"The hydrodynamic interactions between bacterial flagella and surrounding\u0000boundaries are important for bacterial motility and gait in complex\u0000environment. By modeling each flagellar filament that is both thin and long as\u0000a string of spheres, we show that such hydrodynamic interactions can be\u0000accurately described through a resistance tensor, which can be efficiently\u0000evaluated numerically. For the case of close interaction between one bacterium\u0000and one passive colloidal sphere, we see notable difference between results\u0000from our model and those from the resistive force theory, showing that the\u0000error arises from negligence of the width of flagellar filaments in resistive\u0000force theory can be strong.","PeriodicalId":501040,"journal":{"name":"arXiv - PHYS - Biological Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142213230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Debnath, B. N. Narasimhan, S. I. Fraley, P. Rangamani
Collagenolytic degradation is a process fundamental to tissue remodeling. The microarchitecture of collagen fibril networks changes during development, aging, and disease. Such changes to microarchitecture are often accompanied by changes in matrix degradability. In vitro, collagen matrices of the same concentration but different microarchitectures also vary in degradation rate. How do different microarchitectures affect matrix degradation? To answer this question, we developed a computational model of collagen degradation. We first developed a lattice model that describes collagen degradation at the scale of a single fibril. We then extended this model to investigate the role of microarchitecture using Brownian dynamics simulation of enzymes in a multi-fibril three dimensional matrix to predict its degradability. Our simulations predict that the distribution of enzymes around the fibrils is non-uniform and depends on the microarchitecture of the matrix. This non-uniformity in enzyme distribution can lead to different extents of degradability for matrices of different microarchitectures. Our model predictions were tested using in vitro experiments with synthesized collagen gels of different microarchitectures. Experiments showed that indeed degradation of collagen depends on the matrix architecture and fibril thickness. In summary, our study shows that the microarchitecture of the collagen matrix is an important determinant of its degradability.
{"title":"Modeling collagen fibril degradation as a function of matrix microarchitecture","authors":"B. Debnath, B. N. Narasimhan, S. I. Fraley, P. Rangamani","doi":"arxiv-2408.05693","DOIUrl":"https://doi.org/arxiv-2408.05693","url":null,"abstract":"Collagenolytic degradation is a process fundamental to tissue remodeling. The\u0000microarchitecture of collagen fibril networks changes during development,\u0000aging, and disease. Such changes to microarchitecture are often accompanied by\u0000changes in matrix degradability. In vitro, collagen matrices of the same\u0000concentration but different microarchitectures also vary in degradation rate.\u0000How do different microarchitectures affect matrix degradation? To answer this\u0000question, we developed a computational model of collagen degradation. We first\u0000developed a lattice model that describes collagen degradation at the scale of a\u0000single fibril. We then extended this model to investigate the role of\u0000microarchitecture using Brownian dynamics simulation of enzymes in a\u0000multi-fibril three dimensional matrix to predict its degradability. Our\u0000simulations predict that the distribution of enzymes around the fibrils is\u0000non-uniform and depends on the microarchitecture of the matrix. This\u0000non-uniformity in enzyme distribution can lead to different extents of\u0000degradability for matrices of different microarchitectures. Our model\u0000predictions were tested using in vitro experiments with synthesized collagen\u0000gels of different microarchitectures. Experiments showed that indeed\u0000degradation of collagen depends on the matrix architecture and fibril\u0000thickness. In summary, our study shows that the microarchitecture of the\u0000collagen matrix is an important determinant of its degradability.","PeriodicalId":501040,"journal":{"name":"arXiv - PHYS - Biological Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142213255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Collective migration of eukaryotic cells is often guided by chemotaxis, and is critical in several biological processes, such as cancer metastasis, wound healing, and embryogenesis. Understanding collective chemotaxis has challenged experimental, theoretical and computational scientists because cells can sense very small chemoattractant gradients that are tightly controlled by cell-cell interactions and the regulation of the chemoattractant distribution by the cells. Computational models of collective cell migration that offer a high-fidelity resolution of the cell motion and chemoattractant dynamics in the extracellular space have been limited to a small number of cells. Here, we present Dynamic cluster field modeling (DCF), a novel computational method that enables simulations of collective chemotaxis of cellular systems with O(1000) cells and high-resolution transport dynamics of the chemoattractant in the time-evolving extracellular space. We illustrate the efficiency and predictive capabilities of our approach by comparing our numerical simulations with experiments in multiple scenarios that involve chemoattractant secretion and uptake by the migrating cells, regulation of the attractant distribution by cell motion, and interactions of the chemoattractant with an enzyme. The proposed algorithm opens new opportunities to address outstanding problems that involve collective cell migration in the central nervous system, immune response and cancer metastasis.
真核细胞的集体迁移通常由趋化作用引导，在癌症转移、伤口愈合和胚胎发育等多个生物过程中至关重要。由于细胞能感知非常微小的趋化梯度，而这种梯度受细胞-细胞相互作用和细胞对趋化物质分布的调节的严格控制，因此理解集体趋化现象对实验、理论和计算科学家提出了挑战。细胞集体迁移的计算模型能高保真地解析细胞运动和细胞外空间的趋化因子动态，但这种模型仅限于少数细胞。在这里，我们将介绍动态簇场建模（Dynamic cluster field modeling，DCF），这是一种新颖的计算方法，可以模拟细胞数为 O（1000）个的细胞系统的集体趋化以及趋化物质在随时间演变的细胞外空间的高分辨率迁移动力学。我们通过将数值模拟与多种情况下的实验进行比较，包括迁移细胞分泌和吸收趋化吸引剂、细胞运动对吸引剂分布的调节以及趋化吸引剂与酶的相互作用，说明了我们的方法的效率和预测能力。提出的算法为解决涉及中枢神经系统细胞集体迁移、免疫反应和癌症转移等悬而未决的问题提供了新的机遇。
{"title":"Dynamic cluster field modeling of collective chemotaxis","authors":"Aditya Paspunurwar, Adrian Moure, Hector Gomez","doi":"arxiv-2408.04748","DOIUrl":"https://doi.org/arxiv-2408.04748","url":null,"abstract":"Collective migration of eukaryotic cells is often guided by chemotaxis, and\u0000is critical in several biological processes, such as cancer metastasis, wound\u0000healing, and embryogenesis. Understanding collective chemotaxis has challenged\u0000experimental, theoretical and computational scientists because cells can sense\u0000very small chemoattractant gradients that are tightly controlled by cell-cell\u0000interactions and the regulation of the chemoattractant distribution by the\u0000cells. Computational models of collective cell migration that offer a\u0000high-fidelity resolution of the cell motion and chemoattractant dynamics in the\u0000extracellular space have been limited to a small number of cells. Here, we\u0000present Dynamic cluster field modeling (DCF), a novel computational method that\u0000enables simulations of collective chemotaxis of cellular systems with O(1000)\u0000cells and high-resolution transport dynamics of the chemoattractant in the\u0000time-evolving extracellular space. We illustrate the efficiency and predictive\u0000capabilities of our approach by comparing our numerical simulations with\u0000experiments in multiple scenarios that involve chemoattractant secretion and\u0000uptake by the migrating cells, regulation of the attractant distribution by\u0000cell motion, and interactions of the chemoattractant with an enzyme. The\u0000proposed algorithm opens new opportunities to address outstanding problems that\u0000involve collective cell migration in the central nervous system, immune\u0000response and cancer metastasis.","PeriodicalId":501040,"journal":{"name":"arXiv - PHYS - Biological Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141940090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Giovanni Mattiotti, Manuel Micheloni, Lorenzo Petrolli, Luca Tubiana, Samuela Pasquali, Raffaello Potestio
The cowpea chlorotic mottle virus (CCMV) has emerged as an exemplary model system to assess the balance between electrostatic and topological features of ssRNA viruses, specifically in the context of the viral self-assembly process. Yet, in spite of its biophysical significance, little structural data of the RNA content of the CCMV virion is currently available. Here, the conformational dynamics of the RNA2 fragment of CCMV was assessed via coarse-grained molecular dynamics simulations, employing the oxRNA2 model. The behavior of RNA2 has been characterized both as a freely-folding molecule and within a mean-field depiction of a CCMV-like capsid. For the latter, a multi-scale approach was employed, to derive a radial potential profile of the viral cavity, from atomistic structures of the CCMV capsid in solution. The conformational ensembles of the encapsidated RNA2 were significantly altered with respect to the freely-folding counterparts, as shown by the emergence of long-range motifs and pseudoknots in the former case. Finally, the role of the N-terminal tails of the CCMV subunits (and ionic shells thereof) is highlighted as a critical feature in the construction of a proper electrostatic model of the CCMV capsid.
{"title":"Molecular dynamics characterization of the free and encapsidated RNA2 of CCMV with the oxRNA model","authors":"Giovanni Mattiotti, Manuel Micheloni, Lorenzo Petrolli, Luca Tubiana, Samuela Pasquali, Raffaello Potestio","doi":"arxiv-2408.03662","DOIUrl":"https://doi.org/arxiv-2408.03662","url":null,"abstract":"The cowpea chlorotic mottle virus (CCMV) has emerged as an exemplary model\u0000system to assess the balance between electrostatic and topological features of\u0000ssRNA viruses, specifically in the context of the viral self-assembly process.\u0000Yet, in spite of its biophysical significance, little structural data of the\u0000RNA content of the CCMV virion is currently available. Here, the conformational\u0000dynamics of the RNA2 fragment of CCMV was assessed via coarse-grained molecular\u0000dynamics simulations, employing the oxRNA2 model. The behavior of RNA2 has been\u0000characterized both as a freely-folding molecule and within a mean-field\u0000depiction of a CCMV-like capsid. For the latter, a multi-scale approach was\u0000employed, to derive a radial potential profile of the viral cavity, from\u0000atomistic structures of the CCMV capsid in solution. The conformational\u0000ensembles of the encapsidated RNA2 were significantly altered with respect to\u0000the freely-folding counterparts, as shown by the emergence of long-range motifs\u0000and pseudoknots in the former case. Finally, the role of the N-terminal tails\u0000of the CCMV subunits (and ionic shells thereof) is highlighted as a critical\u0000feature in the construction of a proper electrostatic model of the CCMV capsid.","PeriodicalId":501040,"journal":{"name":"arXiv - PHYS - Biological Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lina Yan, Jeffrey Huy Khong, Aleksandar Kostadinov, Jerry Ying Hsi Fuh, Chih-Ming Ho
In the field of complex systems, self-organization magnifies the compounding effects of element interactions by propagating, modifying, and enhancing functionality, ultimately leading to emergent system properties. The intricacies of self-organization make unveiling the elusive link between element interactions and emergent system properties akin to finding the proverbial Holy Grail. In the search for identifying a method to predict system-level properties, we used an inductive approach to bypass the self-organization. By observing drug interactions within biological complex system, system property, efficacy, emerged as a smooth response surface in the multi-dimensional space of drug-system interactions, which can be represented by the Complex System Response (CSR) function. This CSR function has been successfully validated across diverse disease models in cell lines, animals, and clinical trials. Notably, the CSR function reveals that biological complex systems exhibit second-order non-linearity. In this study, we generalized the CSR function to physical complex systems, linking maximum compressive yielding stress to impactful manufacturing parameters of the Selective Laser Melting (SLM) process. Remarkably though anticipated, the CSR function reveals the connection between the macroscale system property (compressive yielding stress) and the microstructure during self-organizing process. In addition, the second-order non-linear CSR functions ensure a single global optimum in complex systems.
{"title":"A ubiquitous transfer function links interacting elements to emerging property of complex systems","authors":"Lina Yan, Jeffrey Huy Khong, Aleksandar Kostadinov, Jerry Ying Hsi Fuh, Chih-Ming Ho","doi":"arxiv-2408.03347","DOIUrl":"https://doi.org/arxiv-2408.03347","url":null,"abstract":"In the field of complex systems, self-organization magnifies the compounding\u0000effects of element interactions by propagating, modifying, and enhancing\u0000functionality, ultimately leading to emergent system properties. The\u0000intricacies of self-organization make unveiling the elusive link between\u0000element interactions and emergent system properties akin to finding the\u0000proverbial Holy Grail. In the search for identifying a method to predict\u0000system-level properties, we used an inductive approach to bypass the\u0000self-organization. By observing drug interactions within biological complex\u0000system, system property, efficacy, emerged as a smooth response surface in the\u0000multi-dimensional space of drug-system interactions, which can be represented\u0000by the Complex System Response (CSR) function. This CSR function has been\u0000successfully validated across diverse disease models in cell lines, animals,\u0000and clinical trials. Notably, the CSR function reveals that biological complex\u0000systems exhibit second-order non-linearity. In this study, we generalized the\u0000CSR function to physical complex systems, linking maximum compressive yielding\u0000stress to impactful manufacturing parameters of the Selective Laser Melting\u0000(SLM) process. Remarkably though anticipated, the CSR function reveals the\u0000connection between the macroscale system property (compressive yielding stress)\u0000and the microstructure during self-organizing process. In addition, the\u0000second-order non-linear CSR functions ensure a single global optimum in complex\u0000systems.","PeriodicalId":501040,"journal":{"name":"arXiv - PHYS - Biological Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939927","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Agniva Datta, Sönke Beier, Veronika Pfeifer, Robert Großmann, Carsten Beta
While bacterial swimming has been well characterized in uniform liquid environments, only little is known about how bacteria propagate through complex environments, such as gel-like matrices or porous media that are typically encountered in tissue or soil. Here, we study swimming motility of the soil bacterium Pseudomonas putida (P. putida) in polysaccharide matrices formed by different concentrations of agar. P. putida cells display intermittent run-motility in the gel, where run times are exponentially distributed and intermittently occurring dwell times follow a waiting-time distribution with a power-law decay. An analysis of the turn angle distribution suggests that both, flagella mediated turning as well as mechanical trapping in the agar matrix play a role in the overall swimming pattern. Based on the experimentally observed motility pattern and measured waiting-time distributions, we propose a minimal active particle model which correctly describes the observed time dependence of the mean square displacement of the bacterial swimmers.
{"title":"Intermittent Run Motility of Bacteria in Gels Exhibits Power-Law Distributed Dwell Times","authors":"Agniva Datta, Sönke Beier, Veronika Pfeifer, Robert Großmann, Carsten Beta","doi":"arxiv-2408.02317","DOIUrl":"https://doi.org/arxiv-2408.02317","url":null,"abstract":"While bacterial swimming has been well characterized in uniform liquid\u0000environments, only little is known about how bacteria propagate through complex\u0000environments, such as gel-like matrices or porous media that are typically\u0000encountered in tissue or soil. Here, we study swimming motility of the soil\u0000bacterium Pseudomonas putida (P. putida) in polysaccharide matrices formed by\u0000different concentrations of agar. P. putida cells display intermittent\u0000run-motility in the gel, where run times are exponentially distributed and\u0000intermittently occurring dwell times follow a waiting-time distribution with a\u0000power-law decay. An analysis of the turn angle distribution suggests that both,\u0000flagella mediated turning as well as mechanical trapping in the agar matrix\u0000play a role in the overall swimming pattern. Based on the experimentally\u0000observed motility pattern and measured waiting-time distributions, we propose a\u0000minimal active particle model which correctly describes the observed time\u0000dependence of the mean square displacement of the bacterial swimmers.","PeriodicalId":501040,"journal":{"name":"arXiv - PHYS - Biological Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Toshi Parmar, Liam P. Dow, beth L. Pruitt, M. Cristina Marchetti
The feedback between mechanical and chemical signals plays a key role in controlling many biological processes and collective cell behavior. Here we focus on the emergence of spatiotemporal density waves in a one-dimensional "cell train." Combining a minimal theoretical model with observations in an in vitro experimental system of MDCK epithelial cells confined to a linear pattern, we examine the spontaneous oscillations driven by the feedback between myosin activation and mechanical deformations and their effect on the response of the tissue to externally applied deformations. We show that the nature and frequency of spontaneous oscillations is controlled by the size of the cell train, with a transition from size-dependent standing waves to intrinsic spontaneous waves at the natural frequency of the tissue. The response to external boundary perturbations exhibit a resonance at this natural frequency, providing a possible venue for inferring the mechanochemical couplings that control the tissue behavior from rheological experiments.
{"title":"Spontaneous and Induced Oscillations in Confined Epithelia","authors":"Toshi Parmar, Liam P. Dow, beth L. Pruitt, M. Cristina Marchetti","doi":"arxiv-2408.02806","DOIUrl":"https://doi.org/arxiv-2408.02806","url":null,"abstract":"The feedback between mechanical and chemical signals plays a key role in\u0000controlling many biological processes and collective cell behavior. Here we\u0000focus on the emergence of spatiotemporal density waves in a one-dimensional\u0000\"cell train.\" Combining a minimal theoretical model with observations in an in\u0000vitro experimental system of MDCK epithelial cells confined to a linear\u0000pattern, we examine the spontaneous oscillations driven by the feedback between\u0000myosin activation and mechanical deformations and their effect on the response\u0000of the tissue to externally applied deformations. We show that the nature and\u0000frequency of spontaneous oscillations is controlled by the size of the cell\u0000train, with a transition from size-dependent standing waves to intrinsic\u0000spontaneous waves at the natural frequency of the tissue. The response to\u0000external boundary perturbations exhibit a resonance at this natural frequency,\u0000providing a possible venue for inferring the mechanochemical couplings that\u0000control the tissue behavior from rheological experiments.","PeriodicalId":501040,"journal":{"name":"arXiv - PHYS - Biological Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Molecular rotors form twisted conformations upon photoexcitation, with their fluorescent relaxation time serving as a measure of viscosity. They have been used to assess membrane viscosities but yield higher values compared to other methods. Here, we show that the rotor's relaxation time is influenced by a combination of membrane viscosity and interleaflet friction. We present a theory for the relaxation time and obtain a correction factor that accounts for the discrepancy. If the membrane's viscosity is known, molecular rotors may enable the extraction of the elusive interleaflet friction.
{"title":"Effect of interleaflet friction on the dynamics of molecular rotors in lipid membranes","authors":"Naomi Oppenheimer, Vinny C. Suja, Howard A. Stone","doi":"arxiv-2408.01280","DOIUrl":"https://doi.org/arxiv-2408.01280","url":null,"abstract":"Molecular rotors form twisted conformations upon photoexcitation, with their\u0000fluorescent relaxation time serving as a measure of viscosity. They have been\u0000used to assess membrane viscosities but yield higher values compared to other\u0000methods. Here, we show that the rotor's relaxation time is influenced by a\u0000combination of membrane viscosity and interleaflet friction. We present a\u0000theory for the relaxation time and obtain a correction factor that accounts for\u0000the discrepancy. If the membrane's viscosity is known, molecular rotors may\u0000enable the extraction of the elusive interleaflet friction.","PeriodicalId":501040,"journal":{"name":"arXiv - PHYS - Biological Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141939926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Extreme value analysis (EVA) is a statistical method that studies the properties of extreme values of datasets, crucial for fields like engineering, meteorology, finance, insurance, and environmental science. EVA models extreme events using distributions such as Fr'echet, Weibull, or Gumbel, aiding in risk prediction and management. This review explores EVA's application to nanoscale biosystems. Traditionally, biological research focuses on average values from repeated experiments. However, EVA offers insights into molecular mechanisms by examining extreme data points. We introduce EVA's concepts with simulations and review its use in studying motor protein movements within cells, highlighting the importance of in vivo analysis due to the complex intracellular environment. We suggest EVA as a tool for extracting motor proteins' physical properties in vivo and discuss its potential in other biological systems. While EVA's use in nanoscale biological systems is limited, it holds promise for uncovering hidden properties in extreme data, promoting its broader application in life sciences.
极值分析（EVA）是一种研究数据集极值特性的统计方法，对工程、气象、金融、保险和环境科学等领域至关重要。EVA 使用 Fr'echet 、Weibull 或 Gumbel 等分布对极端事件进行建模，有助于风险预测和管理。这篇综述探讨了 EVA 在小尺度生物系统中的应用。传统上，生物研究侧重于重复实验的平均值。然而，EVA 可通过研究极端数据点深入了解分子机制。我们通过模拟介绍了 EVA 的概念，并回顾了它在研究细胞内运动蛋白运动中的应用，强调了由于细胞内环境复杂而进行活体分析的重要性。我们建议将 EVA 作为提取体内运动蛋白物理特性的工具，并讨论了它在其他生物系统中的应用潜力。虽然 EVA 在纳米级生物系统中的应用有限，但它有望揭示极端数据中隐藏的特性，从而促进其在生命科学领域的更广泛应用。
{"title":"Extreme-value analysis in nano-biological systems: Applications and Implications","authors":"Kumiko Hayashi, Nobumichi Takamatsu, Shunki Takaramoto","doi":"arxiv-2408.01007","DOIUrl":"https://doi.org/arxiv-2408.01007","url":null,"abstract":"Extreme value analysis (EVA) is a statistical method that studies the\u0000properties of extreme values of datasets, crucial for fields like engineering,\u0000meteorology, finance, insurance, and environmental science. EVA models extreme\u0000events using distributions such as Fr'echet, Weibull, or Gumbel, aiding in\u0000risk prediction and management. This review explores EVA's application to\u0000nanoscale biosystems. Traditionally, biological research focuses on average\u0000values from repeated experiments. However, EVA offers insights into molecular\u0000mechanisms by examining extreme data points. We introduce EVA's concepts with\u0000simulations and review its use in studying motor protein movements within\u0000cells, highlighting the importance of in vivo analysis due to the complex\u0000intracellular environment. We suggest EVA as a tool for extracting motor\u0000proteins' physical properties in vivo and discuss its potential in other\u0000biological systems. While EVA's use in nanoscale biological systems is limited,\u0000it holds promise for uncovering hidden properties in extreme data, promoting\u0000its broader application in life sciences.","PeriodicalId":501040,"journal":{"name":"arXiv - PHYS - Biological Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141940099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rik Chakraborty, Arnab Maiti, Diptangshu Paul, Rajnandan Borthakur, K. R. Jayaprakash, Uddipta Ghosh, Krishna Kanti Dey
We investigated the energy transfer from active enzymes to their surroundings in crowded environments by measuring the diffusion of passive microscopic tracers in active solutions of ficoll and glycerol. Despite observing lower rates of substrate turnover and relatively smaller enhancement of passive tracer diffusion in artificial crowded media compared to those in aqueous solutions, we found a significantly higher relative diffusion enhancement in crowded environments in the presence of enzymatic activity. Our experimental observations, coupled with supporting analytical estimations, underscored the critical role of the intervening media in facilitating mechanical energy distribution around active enzymes.
{"title":"Propagation of Enzyme-driven Active Fluctuations in Crowded Milieu","authors":"Rik Chakraborty, Arnab Maiti, Diptangshu Paul, Rajnandan Borthakur, K. R. Jayaprakash, Uddipta Ghosh, Krishna Kanti Dey","doi":"arxiv-2408.00578","DOIUrl":"https://doi.org/arxiv-2408.00578","url":null,"abstract":"We investigated the energy transfer from active enzymes to their surroundings\u0000in crowded environments by measuring the diffusion of passive microscopic\u0000tracers in active solutions of ficoll and glycerol. Despite observing lower\u0000rates of substrate turnover and relatively smaller enhancement of passive\u0000tracer diffusion in artificial crowded media compared to those in aqueous\u0000solutions, we found a significantly higher relative diffusion enhancement in\u0000crowded environments in the presence of enzymatic activity. Our experimental\u0000observations, coupled with supporting analytical estimations, underscored the\u0000critical role of the intervening media in facilitating mechanical energy\u0000distribution around active enzymes.","PeriodicalId":501040,"journal":{"name":"arXiv - PHYS - Biological Physics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141882372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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