arXiv - QuanBio - Subcellular Processes最新文献

{"title":"Tube geometry controls protein cluster conformation and stability on the endoplasmic reticulum surface","authors":"Liam T Kischuck, Aidan I Brown","doi":"arxiv-2305.00971","DOIUrl":"https://doi.org/arxiv-2305.00971","url":null,"abstract":"The endoplasmic reticulum (ER), a cellular organelle that forms a\u0000cell-spanning network of tubes and sheets, is an important location of protein\u0000synthesis and folding. When the ER experiences sustained unfolded protein\u0000stress, IRE1 proteins embedded in the ER membrane activate and assemble into\u0000clusters as part of the unfolded protein response (UPR). We use kinetic Monte\u0000Carlo simulations to explore IRE1 clustering dynamics on the surface of ER\u0000tubes. While initially growing clusters are approximately round, once a cluster\u0000is sufficiently large a shorter interface length can be achieved by `wrapping'\u0000around the ER tube. A wrapped cluster can grow without further interface length\u0000increases. Relative to wide tubes, narrower tubes enable cluster wrapping at\u0000smaller cluster sizes. Our simulations show that wrapped clusters on narrower\u0000tubes grow more rapidly, evaporate more slowly, and require a lower protein\u0000concentration to grow compared to equal-area round clusters on wider tubes.\u0000These results suggest that cluster wrapping, facilitated by narrower tubes,\u0000could be an important factor in the growth and stability of IRE1 clusters and\u0000thus impact the persistence of the UPR, connecting geometry to signaling\u0000behavior. This work is consistent with recent experimental observations of IRE1\u0000clusters wrapped around narrow tubes in the ER network.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"85 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532804","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}

{"title":"Self-organization of microtubules: complexity analysis of emergent patterns","authors":"Nikita Frolov, Bram Bijnens, Daniel Ruiz-Reynés, Lendert Gelens","doi":"arxiv-2305.00539","DOIUrl":"https://doi.org/arxiv-2305.00539","url":null,"abstract":"Microtubules self-organize to structure part of the cellular cytoskeleton. As\u0000such they give cells their shape and play a crucial role in cell division and\u0000intracellular transport. Past studies have identified diverse spatio-temporal\u0000patterns into which microtubules can organize when driven by motor proteins.\u0000The question remains if there is an appropriate way to quantify these\u0000structures and gain new knowledge about the physical principles of\u0000self-organization in microtubule-motor mixtures. Here, we aim to approach this\u0000problem from a complexity science perspective. We introduce an entropy-based\u0000measure to evaluate the structural complexity of spatial patterns emerging in a\u0000simplified agent-based computational model of a microtubule-motor interactions.\u0000Our results demonstrate that the proposed quantifier discriminates well between\u0000ordered, disordered, and intermediate structures. Besides, our study indicates\u0000that the transition to steady states in such a system is likely to be\u0000discontinuous and exhibits distinct properties of self-organized criticality.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"75 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532789","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}

{"title":"The effect of loops on the mean square displacement of Rouse-model chromatin","authors":"Tianyu YuanIntegrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, USADepartment of Physics, Yale University, New Haven, Connecticut, USA, Hao YanIntegrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, USADepartment of Physics, Yale University, New Haven, Connecticut, USA, Mary Lou P. BaileyIntegrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, USADepartment of Applied Physics, Yale University, New Haven, Connecticut, USA, Jessica F. WilliamsDepartment of Cell Biology, Yale School of Medicine, New Haven, Connecticut, USA, Ivan SurovtsevDepartment of Physics, Yale University, New Haven, Connecticut, USADepartment of Cell Biology, Yale School of Medicine, New Haven, Connecticut, USA, Megan C. KingIntegrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, USADepartment of Cell Biology, Yale School of Medicine, New Haven, Connecticut, USADepartment of Molecular, Cell and Developmental Biology, Yale University, New Haven, Connecticut, USA, Simon G. J. MochrieIntegrated Graduate Program in Physical and Engineering Biology, Yale University, New Haven, Connecticut, USADepartment of Physics, Yale University, New Haven, Connecticut, USADepartment of Applied Physics, Yale University, New Haven, Connecticut, USA","doi":"arxiv-2304.11266","DOIUrl":"https://doi.org/arxiv-2304.11266","url":null,"abstract":"Many researchers have been encouraged to describe the dynamics of chromosomal\u0000loci in chromatin using the classical Rouse model of polymer dynamics by the\u0000agreement between the measured mean square displacement (MSD) versus time of\u0000fluorescently-labelled loci and the Rouse-model predictions. However, the\u0000discovery of intermediate-scale chromatin organization, known as topologically\u0000associating domains (TADs), together with the proposed explanation of TADs in\u0000terms of chromatin loops and loop extrusion, is at odds with the classical\u0000Rouse model, which does not contain loops. Accordingly, we introduce an\u0000extended Rouse model that incorporates chromatin loop configurations from\u0000loop-extrusion-factor-model simulations. Specifically, we extend the classical\u0000Rouse model by modifying the polymer's dynamical matrix to incorporate extra\u0000springs that represent loop bases. We also theoretically generalize the\u0000friction coefficient matrix so that the Rouse beads with non-uniform friction\u0000coefficients are compatible with our Rouse model simulation method. This\u0000extended Rouse model allowes us to investigate the impact of loops and loop\u0000extrusion on the dynamics of chromatin. We show that loops significantly\u0000suppress the averaged MSD of a chromosomal locus, consistent with recent\u0000experiments that track fluorescently-labelled chromatin loci in fission yeast\u0000[M. L. P. Bailey, I. Surovtsev, J. F. Williams, H. Yan, T. Yuan, S. G. Mochrie,\u0000and M. C. King, Mol. Biol. Cell (in press)]. We also find that loops slightly\u0000reduce the MSD's stretching exponent from the classical Rouse-model value of\u00000.5 to a loop-density-dependent value in the 0.45-0.40 range. Remarkably,\u0000stretching exponent values in this range have also been reported in recent\u0000experiments [S. C. Weber, A. J. Spakowitz, and J. A. Theriot, Phys. Rev. Lett.\u0000104, 238102 (2010) and Bailey et al., Mol. Biol. Cell (in press)].","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"185 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532787","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}

{"title":"Exclusion model of mRNA translation with collision-induced ribosome drop-off","authors":"Johannes Keisers, Joachim Krug","doi":"arxiv-2304.07156","DOIUrl":"https://doi.org/arxiv-2304.07156","url":null,"abstract":"The translation of messenger RNA transcripts to proteins is commonly modeled\u0000as a one-dimensional totally asymmetric exclusion process with extended\u0000particles. Here we focus on the effects of premature termination of translation\u0000through the irreversible detachment of ribosomes. We consider a model where the\u0000detachment is induced by the unsuccessful attempt to move to an occupied site.\u0000The model is exactly solvable in a simplified geometry consisting of the\u0000translation initiation region followed by a single slow site representing a\u0000translation bottleneck. In agreement with recent experimental and computational\u0000studies we find a non-monotonic dependence of the ribosome current on the\u0000initiation rate, but only if the leading particle in a colliding pair detaches.\u0000Simulations show that the effect persists for larger lattices and extended\u0000bottlenecks. In the homogeneous system the ribosome density decays\u0000asymptotically as the inverse square root of the distance to the initiation\u0000site.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"58 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532814","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}

{"title":"Surface-guided computing to analyze subcellular morphology and membrane-associated signals in 3D","authors":"Felix Y. Zhou, Andrew Weems, Gabriel M. Gihana, Bingying Chen, Bo-Jui Chang, Meghan Driscoll, Gaudenz Danuser","doi":"arxiv-2304.06176","DOIUrl":"https://doi.org/arxiv-2304.06176","url":null,"abstract":"Signal transduction and cell function are governed by the spatiotemporal\u0000organization of membrane-associated molecules. Despite significant advances in\u0000visualizing molecular distributions by 3D light microscopy, cell biologists\u0000still have limited quantitative understanding of the processes implicated in\u0000the regulation of molecular signals at the whole cell scale. In particular,\u0000complex and transient cell surface morphologies challenge the complete sampling\u0000of cell geometry, membrane-associated molecular concentration and activity and\u0000the computing of meaningful parameters such as the cofluctuation between\u0000morphology and signals. Here, we introduce u-Unwrap3D, a framework to remap\u0000arbitrarily complex 3D cell surfaces and membrane-associated signals into\u0000equivalent lower dimensional representations. The mappings are bidirectional,\u0000allowing the application of image processing operations in the data\u0000representation best suited for the task and to subsequently present the results\u0000in any of the other representations, including the original 3D cell surface.\u0000Leveraging this surface-guided computing paradigm, we track segmented surface\u0000motifs in 2D to quantify the recruitment of Septin polymers by blebbing events;\u0000we quantify actin enrichment in peripheral ruffles; and we measure the speed of\u0000ruffle movement along topographically complex cell surfaces. Thus, u-Unwrap3D\u0000provides access to spatiotemporal analyses of cell biological parameters on\u0000unconstrained 3D surface geometries and signals.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532788","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}

{"title":"Uncovering the effect of RNA polymerase steric interactions on gene expression noise: analytical distributions of nascent and mature RNA numbers","authors":"Juraj Szavits-Nossan, Ramon Grima","doi":"arxiv-2304.05304","DOIUrl":"https://doi.org/arxiv-2304.05304","url":null,"abstract":"The telegraph model is the standard model of stochastic gene expression,\u0000which can be solved exactly to obtain the distribution of mature RNA numbers\u0000per cell. A modification of this model also leads to an analytical distribution\u0000of the nascent RNA numbers. These solutions are routinely used for the analysis\u0000of single-cell data, including the inference of transcriptional parameters.\u0000However, these models neglect important mechanistic features of transcription\u0000elongation, such as the stochastic movement of RNA polymerases and their steric\u0000interactions. Here we construct a model of gene expression describing promoter\u0000switching between inactive and active states, binding of RNA polymerases in the\u0000active state, their stochastic movement including steric interactions along the\u0000gene, and their unbinding leading to a mature transcript that subsequently\u0000decays. We derive the steady-state distributions of the nascent and mature RNA\u0000numbers in two important limiting cases: constitutive expression and slow\u0000promoter switching. We show that RNA fluctuations are suppressed by steric\u0000interactions between RNA polymerases, and that this suppression can even lead\u0000to sub-Poissonian fluctuations; these effects are most pronounced for nascent\u0000RNA and less prominent for mature RNA, since the latter is not a direct sensor\u0000of transcription. We find a relationship between the parameters of our\u0000microscopic mechanistic model and those of the standard models that ensures\u0000excellent consistency in their prediction of the first and second RNA number\u0000moments over vast regions of parameter space, encompassing slow, intermediate,\u0000and rapid promoter switching, provided the RNA number distributions are\u0000Poissonian or super-Poissonian. Furthermore, we identify the limitations of\u0000inference from mature RNA data, specifically showing that it cannot\u0000differentiate between highly distinct RNA polymerase traffic patterns on a\u0000gene.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"85 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532811","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}

{"title":"Artificial intelligence based prediction on lung cancer risk factors using deep learning","authors":"Muhammad Sohaib, Mary Adewunmi","doi":"arxiv-2304.05065","DOIUrl":"https://doi.org/arxiv-2304.05065","url":null,"abstract":"In this proposed work, we identified the significant research issues on lung\u0000cancer risk factors. Capturing and defining symptoms at an early stage is one\u0000of the most difficult phases for patients. Based on the history of patients\u0000records, we reviewed a number of current research studies on lung cancer and\u0000its various stages. We identified that lung cancer is one of the significant\u0000research issues in predicting the early stages of cancer disease. This research\u0000aimed to develop a model that can detect lung cancer with a remarkably high\u0000level of accuracy using the deep learning approach (convolution neural\u0000network). This method considers and resolves significant gaps in previous\u0000studies. We compare the accuracy levels and loss values of our model with\u0000VGG16, InceptionV3, and Resnet50. We found that our model achieved an accuracy\u0000of 94% and a minimum loss of 0.1%. Hence physicians can use our convolution\u0000neural network models for predicting lung cancer risk factors in the real\u0000world. Moreover, this investigation reveals that squamous cell carcinoma,\u0000normal, adenocarcinoma, and large cell carcinoma are the most significant risk\u0000factors. In addition, the remaining attributes are also crucial for achieving\u0000the best performance.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"278 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532859","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}

{"title":"Immune recognition dynamics of a primary infection","authors":"Roberto Morán-Tovar, Michael Lässig","doi":"arxiv-2304.02794","DOIUrl":"https://doi.org/arxiv-2304.02794","url":null,"abstract":"The immune response to an acute primary infection is a coupled process of\u0000antigen proliferation, molecular recognition by naive B-cells, and their\u0000subsequent proliferation and antibody shedding. Here we show B-cells can\u0000efficiently recognise new antigens by a tuned kinetic proofreading mechanism,\u0000where the number of proofreading steps and the characteristic rate of each step\u0000are set by the complexity of the immune repertoire. This process produces\u0000potent, specific and fast recognition of antigens, maintaining a spectrum of\u0000genetically distinct B-cell lineages as input for affinity maturation. We show\u0000that the proliferation-recognition dynamics of a primary infection can me\u0000mapped onto a generalised Luria-Delbr\"uck process, akin to the dynamics of the\u0000classic fluctuation experiment. We derive the resulting statistics of the\u0000activated immune repertoire: antigen binding affinity, expected size, and\u0000frequency of active B-cell clones are related by power laws. Their exponents\u0000depend on the antigen and B-cell proliferation rate, the number of proofreading\u0000steps, and the lineage density of the naive repertoire. Empirical data of mouse\u0000immune repertoires are found to be consistent with activation involving at\u0000least three proofreading steps. Our model predicts key clinical characteristics\u0000of acute infections. The primary immune response to a given antigen is strongly\u0000heterogeneous across individuals; few elite responders are distinguished by\u0000early activation of high-affinity clones. Conversely, ageing of the immune\u0000system, by reducing the density of naive clones, degrades potency and speed of\u0000pathogen recognition.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"67 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532812","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}

{"title":"Self-organization of primitive metabolic cycles due to non-reciprocal interactions","authors":"Vincent Ouazan-Reboul, Jaime Agudo-Canalejo, Ramin Golestanian","doi":"arxiv-2303.09832","DOIUrl":"https://doi.org/arxiv-2303.09832","url":null,"abstract":"We study analytically and numerically a model metabolic cycle composed of an\u0000arbitrary number of species of catalytically active particles. Each species\u0000converts a substrate into a product, the latter being used as the substrate by\u0000the next species in the cycle. Through a combination of catalytic activity and\u0000chemotactic mobility, the active particles develop effective non-reciprocal\u0000interactions with particles belonging to neighbouring species in the cycle. We\u0000find that such model metabolic cycles are able to self-organize through a\u0000macroscopic instability, with a strong dependence on the number of species they\u0000incorporate. The parity of that number has a key influence: cycles containing\u0000an even number of species are able to minimize repulsion between their\u0000component particles by aggregating all even-numbered species in one cluster,\u0000and all odd-numbered species in another. Such a grouping is not possible if the\u0000cycle contains an odd number of species, which can lead to oscillatory steady\u0000states in the case of chasing interactions.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532810","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}

{"title":"Bidirectional allostery mechanism of catch-bond effect in cell adhesion","authors":"Xingyue Guan, Yunqiang Bian, Yi Cao, Wenfei Li, Wei Wang","doi":"arxiv-2303.04443","DOIUrl":"https://doi.org/arxiv-2303.04443","url":null,"abstract":"Catch-bonds, whereby noncovalent ligand-receptor interactions are\u0000counterintuitively reinforced by tensile forces, play a major role in cell\u0000adhesion under mechanical stress. A basic prerequisite for catch-bond formation\u0000is that force-induced remodeling of ligand binding interface occurs prior to\u0000bond rupture. However, what strategy receptor proteins utilize to meet such\u0000specific kinetic control is still unclear, rendering the mechanistic\u0000understanding of catch-bond an open question. Here we report a bidirectional\u0000allostery mechanism of catch-bond for the hyaluronan (HA) receptor CD44 which\u0000is responsible for rolling adhesion of lymphocytes and circulating tumor cells.\u0000Binding of ligand HA allosterically reduces the threshold force for unlocking\u0000of otherwise stably folded force-sensing element (i.e., forward allostery), so\u0000that much smaller tensile force can trigger the conformational switching of\u0000receptor protein to high binding-strength state via backward allosteric\u0000coupling before bond rupture. The effect of forward allostery was further\u0000supported by performing atomistic molecular dynamics simulations. Such\u0000bidirectional allostery mechanism fulfills the specific kinetic control\u0000required by catch-bond and is likely to be commonly utilized in cell adhesion.\u0000We also revealed a slip-catch-slip triphasic pattern in force response of\u0000CD44-HA bond arising from force-induced repartitioning of parallel dissociation\u0000pathways. The essential thermodynamic and kinetic features of receptor proteins\u0000for shaping the catch-bond were identified.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"71 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532809","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}