arXiv - QuanBio - Subcellular Processes最新文献

{"title":"Comparison of different versions of SignalP and TargetP for diatom plastid protein predictions with ASAFind","authors":"Ansgar GruberBiology Centre, Institute of Parasitology, Czech Academy of Sciences, Cedar McKaySchool of Oceanography, University of Washington, Gabrielle RocapSchool of Oceanography, University of Washington, Miroslav OborníkBiology Centre, Institute of Parasitology, Czech Academy of SciencesUniversity of South Bohemia","doi":"arxiv-2303.02509","DOIUrl":"https://doi.org/arxiv-2303.02509","url":null,"abstract":"Plastid targeted proteins of diatoms and related algae can be predicted with\u0000high sensitivity and specificity using the ASAFind method published in 2015.\u0000ASAFind predictions rely on SignalP predictions of endoplasmic reticulum (ER)\u0000targeting signal peptides. Recently (in 2019), a new version of SignalP was\u0000released, SignalP 5.0. We tested the ability of SignalP 5.0 to recognize signal\u0000peptides of nucleus-encoded, plastid-targeted diatom pre-proteins, and to\u0000identify the signal peptide cleavage site. The results were compared to manual\u0000predictions of the characteristic cleavage site motif, and to previous versions\u0000of SignalP. SignalP 5.0 is less sensitive than the previous versions of SignalP\u0000in this specific task, and also in the detection of signal peptides of\u0000non-plastid proteins in diatoms. However, in combination with ASAFind, the\u0000resulting prediction performance for plastid proteins is high. In addition, we\u0000tested the multi-location prediction tool TargetP for its suitability to\u0000provide signal peptide information to ASAFind. The newest version, TargetP 2.0,\u0000had the highest prediction performances for diatom signal peptides and\u0000mitochondrial transit peptides compared to other versions of SignalP and\u0000TargetP, thus it provides a good basis for ASAFind predictions.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532807","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":"Multi class intracellular protein targeting predictions in diatoms and other algae with complex plastids: ASAFind 2.0","authors":"Ansgar GruberBiology Centre, Institute of Parasitology, Czech Academy of Sciences, Czech RepublicFaculty of Science, University of South Bohemia, Czech Republic, Cedar McKaySchool of Oceanography, University of Washington, United States of America, Miroslav OborníkBiology Centre, Institute of Parasitology, Czech Academy of Sciences, Czech RepublicFaculty of Science, University of South Bohemia, Czech Republic, Gabrielle RocapSchool of Oceanography, University of Washington, United States of America","doi":"arxiv-2303.02488","DOIUrl":"https://doi.org/arxiv-2303.02488","url":null,"abstract":"Cells of diatoms and related algae with complex plastids of red algal origin\u0000are highly compartmentalized. These plastids are surrounded by four envelope\u0000membranes, which also define the periplastidic compartment (PPC), the space\u0000between the second and third membranes. The PPC corresponds to the cytosol of\u0000the eukaryotic alga that was the ancestor of the complex plastid. Metabolic\u0000reactions as well as cell biological processes take place in this compartment;\u0000however, its exact function remains elusive. Automated predictions of protein\u0000locations proved useful for genome wide explorations of metabolism in the case\u0000of plastid proteins, but until now, no automated method for the prediction of\u0000PPC proteins was available. Here, we present an updated version of the plastid\u0000protein predictor ASAFind, which includes optional prediction of PPC proteins.\u0000The new ASAFind version also accepts the output of the most recent versions of\u0000SignalP (5.0) and TargetP (2.0) input data. Furthermore, we release a Python\u0000script to calculate custom scoring matrices for adjustment of the ASAFind\u0000method to other groups of algae, and included the option to run the predictions\u0000with custom scoring matrices in a simplified score cut-off mode.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"82 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532827","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":"Interface Self-Referenced Dynamic Full-Field Optical Coherence Tomography","authors":"Tual Monfort, Salvatore Azzollini, Tasnim Ben Yacoub, Isabelle Audo, Sacha Reichman, Kate Grieve, Olivier Thouvenin","doi":"arxiv-2302.08839","DOIUrl":"https://doi.org/arxiv-2302.08839","url":null,"abstract":"Dynamic full-field optical coherence tomography (D-FFOCT) has recently\u0000emerged as an invaluable live label-free and non-invasive imaging modality able\u0000to image subcellular biological structures and their metabolic activity within\u0000complex 3D samples. However, D-FFOCT suffers from fringe artefacts when imaging\u0000nearby reflective surfaces and is highly sensitive to vibrations. Here, we\u0000present interface Self-Referenced (iSR) D-FFOCT, an alternative configuration\u0000to D-FFOCT that takes advantage of the presence of the sample coverslip in\u0000between the sample and the objective by using it as a defocused reference arm,\u0000thus avoiding the aforementioned artefacts. We demonstrate the ability of iSR\u0000D-FFOCT to image 2D fibroblast cell cultures, which are among the flattest\u0000mammalian cells.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532803","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":"High efficient cyclic electron flow and functional supercomplexes in Chlamydomonas cells","authors":"Pierre Joliot, Julien Sellés, Françis-André Wollman, André Verméglio","doi":"arxiv-2302.05205","DOIUrl":"https://doi.org/arxiv-2302.05205","url":null,"abstract":"A very high rate for cyclic electron flow (CEF) around PSI (~180 s-1 or 210\u0000s-1 in minimum medium or in the presence of a carbon source respectively) is\u0000measured in the presence of methyl viologen (MV) in intact cells of\u0000Chlamydomonas reinhardtii under anaerobic conditions. The observation of an\u0000efficient CEF in the presence of methyl viologen is in agreement with the\u0000previous results reports of Asada et al in broken chloroplasts (Plant Cell\u0000Physiol. 31(4) (1990) 557-564). From the analysis of the P700 and PC absorbance\u0000changes, we propose that a confinement between 2 PC molecules, 1 PSI and 1\u0000cytb6f corresponding to a functional supercomplex is responsible for these high\u0000rates of CEF. Supercomplex formation is also observed in the absence of methyl\u0000viologen, but with lower maximal CEF rate (about 100 s-1) suggesting that this\u0000compound facilitates the mediation of electron transfer from PSI acceptors to\u0000the stromal side of cytb6f. Further analysis of CEF in mutants of Chlamydomonas\u0000defective in state transitions shows the requirement of a kinase-driven\u0000transition to state 2 to establish this functional supercomplex configuration.\u0000However, a movement of the LHCII antennae is not involved in this process. We\u0000discuss the possible involvement of auxiliary proteins, among which is a small\u0000cytb6f-associated polypeptide, the PETO protein, which is one of the targets of\u0000the STT7 kinase.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532801","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":"Modelling spatial constraints and scaling effects of catalyst phase separation on linear pathway kinetics","authors":"Nino Lauber, Ondrej Tichacek, Krishnadev Narayanankutty, Daniele De Martino, Kepa Ruiz-Mirazo","doi":"arxiv-2302.05315","DOIUrl":"https://doi.org/arxiv-2302.05315","url":null,"abstract":"Chemical reactions are usually studied under the assumption that both\u0000substrates and catalysts are well mixed (WM) throughout the system. Although\u0000this is often applicable to test-tube experimental conditions, it is not\u0000realistic in cellular environments, where biomolecules can undergo\u0000liquid-liquid phase separation (LLPS) and form condensates, leading to\u0000important functional outcomes, including the modulation of catalytic action.\u0000Similar processes may also play a role in protocellular systems, like primitive\u0000coacervates, or in membrane-assisted prebiotic pathways. Here we explore\u0000whether the de-mixing of catalysts could lead to the formation of\u0000micro-environments that influence the kinetics of a linear (multi-step)\u0000reaction pathway, as compared to a WM system. We implemented a general lattice\u0000model to simulate LLPS of an ensemble of different catalysts and extended it to\u0000include diffusion and a sequence of reactions of small substrates. We carried\u0000out a quantitative analysis of how the phase separation of the catalysts\u0000affects reaction times depending on the affinity between substrates and\u0000catalysts, the length of the reaction pathway, the system size, and the degree\u0000of homogeneity of the condensate. A key aspect underlying the differences\u0000reported between the two scenarios is that the scale invariance observed in the\u0000WM system is broken by condensation processes. The main theoretical\u0000implications of our results for mean-field chemistry are drawn, extending the\u0000mass action kinetics scheme to include substrate initial hitting times to reach\u0000the catalysts condensate. We finally test this approach by considering open\u0000non-linear conditions, where we successfully predict, through microscopic\u0000simulations, that phase separation inhibits chemical oscillatory behaviour,\u0000providing a possible explanation for the marginal role that this complex\u0000dynamic behaviour plays in real metabolisms.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532823","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":"ER network heterogeneity guides diffusive transport and kinetics","authors":"Zubenelgenubi C. Scott, Katherine Koning, Molly Vanderwerp, Lorna Cohen, Laura M. Westrate, Elena F. Koslover","doi":"arxiv-2302.04377","DOIUrl":"https://doi.org/arxiv-2302.04377","url":null,"abstract":"The endoplasmic reticulum (ER) is a dynamic network of interconnected sheets\u0000and tubules that orchestrates the distribution of lipids, ions, and proteins\u0000throughout the cell. The impact of its complex, dynamic morphology on its\u0000function as an intracellular transport hub remains poorly understood. To\u0000elucidate the functional consequences of ER network structure and dynamics, we\u0000quantify how the heterogeneity of the peripheral ER in COS7 cells affects\u0000diffusive protein transport. In vivo imaging of photoactivated ER membrane\u0000proteins demonstrates their non-uniform spreading to adjacent regions, in a\u0000manner consistent with simulations of diffusing particles on extracted network\u0000structures. Using a minimal network model to represent tubule rearrangements,\u0000we demonstrate that ER network dynamics are sufficiently slow to have little\u0000effect on diffusive protein transport. Furthermore, stochastic simulations\u0000reveal a novel consequence of ER network heterogeneity: the existence of 'hot\u0000spots' where sparse diffusive reactants are more likely to find one another.\u0000Intriguingly, ER exit sites are disproportionately found in these highly\u0000accessible regions. Combining in vivo experiments with analytic calculations,\u0000quantitative image analysis, and computational modeling, we demonstrate how\u0000structure guides diffusive protein transport and reactions in the ER.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532820","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":"Tree-Based Learning on Amperometric Time Series Data Demonstrates High Accuracy for Classification","authors":"Jeyashree Krishnan, Zeyu Lian, Pieter E. Oomen, Xiulan He, Soodabeh Majdi, Andreas Schuppert, Andrew Ewing","doi":"arxiv-2302.02650","DOIUrl":"https://doi.org/arxiv-2302.02650","url":null,"abstract":"Elucidating exocytosis processes provide insights into cellular\u0000neurotransmission mechanisms, and may have potential in neurodegenerative\u0000diseases research. Amperometry is an established electrochemical method for the\u0000detection of neurotransmitters released from and stored inside cells. An\u0000important aspect of the amperometry method is the sub-millisecond temporal\u0000resolution of the current recordings which leads to several hundreds of\u0000gigabytes of high-quality data. In this study, we present a universal method\u0000for the classification with respect to diverse amperometric datasets using\u0000data-driven approaches in computational science. We demonstrate a very high\u0000prediction accuracy (greater than or equal to 95%). This includes an end-to-end\u0000systematic machine learning workflow for amperometric time series datasets\u0000consisting of pre-processing; feature extraction; model identification;\u0000training and testing; followed by feature importance evaluation - all\u0000implemented. We tested the method on heterogeneous amperometric time series\u0000datasets generated using different experimental approaches, chemical\u0000stimulations, electrode types, and varying recording times. We identified a\u0000certain overarching set of common features across these datasets which enables\u0000accurate predictions. Further, we showed that information relevant for the\u0000classification of amperometric traces are neither in the spiky segments alone,\u0000nor can it be retrieved from just the temporal structure of spikes. In fact,\u0000the transients between spikes and the trace baselines carry essential\u0000information for a successful classification, thereby strongly demonstrating\u0000that an effective feature representation of amperometric time series requires\u0000the full time series. To our knowledge, this is one of the first studies that\u0000propose a scheme for machine learning, and in particular, supervised learning\u0000on full amperometry time series data.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"82 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532802","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":"Spike-by-Spike Frequency Analysis of Amperometry Traces Provides Statistical Validation of Observations in the Time Domain","authors":"Jeyashree Krishnan, Zeyu Lian, Pieter E. Oomen, Xiulan He, Soodabeh Majdi, Andreas Schuppert, Andrew Ewing","doi":"arxiv-2302.02692","DOIUrl":"https://doi.org/arxiv-2302.02692","url":null,"abstract":"Amperometry is a commonly used electrochemical method for studying the\u0000process of exocytosis in real-time. Given the high precision of recording that\u0000amperometry procedures offer, the volume of data generated can span over\u0000several hundreds of megabytes to a few gigabytes and therefore necessitates\u0000systematic and reproducible methods for analysis. Though the spike\u0000characteristics of amperometry traces in the time domain hold information about\u0000the dynamics of exocytosis, these biochemical signals are, more often than not,\u0000characterized by time-varying signal properties. Such signals with time-variant\u0000properties may occur at different frequencies and therefore analyzing them in\u0000the frequency domain may provide statistical validation for observations\u0000already established in the time domain. This necessitates the use of\u0000time-variant, frequency-selective signal processing methods as well, which can\u0000adeptly quantify the dominant or mean frequencies in the signal. The Fast\u0000Fourier Transform (FFT) is a well-established computational tool that is\u0000commonly used to find the frequency components of a signal buried in noise. In\u0000this work, we outline a method for spike-based frequency analysis of\u0000amperometry traces using FFT that also provides statistical validation of\u0000observations on spike characteristics in the time domain. We demonstrate the\u0000method by utilizing simulated signals and by subsequently testing it on diverse\u0000amperometry datasets generated from different experiments with various chemical\u0000stimulations. To our knowledge, this is the first fully automated open-source\u0000tool available dedicated to the analysis of spikes extracted from amperometry\u0000signals in the frequency domain.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"24 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532808","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":"Monitoring oligomerization dynamics of individual human neurotensin receptors 1 in living cells and in SMALP nanodiscs","authors":"Lukas Spantzel, Iván Pérez, Thomas Heitkamp, Anika Westphal, Stefanie Reuter, Ralf Mrowka, Michael Börsch","doi":"arxiv-2302.02416","DOIUrl":"https://doi.org/arxiv-2302.02416","url":null,"abstract":"The human neurotensin receptor 1 (NTSR1) is a G protein-coupled receptor. The\u0000receptor is activated by a small peptide ligand neurotensin. NTSR1 can be\u0000expressed in HEK cells by stable transfection. Previously we used the\u0000fluorescent protein markers mRuby3 or mNeonGreen fused to NTSR1 for EMCCD-based\u0000structured illumination microscopy (SIM) in living HEK cells. Ligand binding\u0000induced conformational changes in NTSR1 which triggered the intracellular\u0000signaling processes. Recent single-molecule studies revealed a dynamic\u0000monomer/dimer equilibrium of this receptor in artificial lipid bilayers. Here\u0000we report on the oligomerization state of human NTSR1 from living cells by\u0000trapping them into lipid nanodiscs. Briefly, SMALPs (styrene-maleic acid\u0000copolymer lipid nanoparticles) were produced directly from the plasma membranes\u0000of living HEK293T FlpIn cells. SMALPs with a diameter of 15 nm were soluble and\u0000stable. NTSR1 in SMALPs were analyzed by single-molecule intensity measurements\u0000one membrane patch at a time using a custom-built confocal anti-Brownian\u0000electrokinetic trap (ABEL trap) microscope. We found oligomerization changes\u0000before and after stimulation of the receptor with its ligand neurotensin.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532852","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":"Are physiological oscillations physiological?","authors":"LingyunIvy, Xiong, Alan Garfinkel","doi":"arxiv-2301.08996","DOIUrl":"https://doi.org/arxiv-2301.08996","url":null,"abstract":"Despite widespread and striking examples of physiological oscillations, their\u0000functional role is often unclear. Even glycolysis, the paradigm example of\u0000oscillatory biochemistry, has seen questions about its function. Here, we take\u0000a systems approach to summarize evidence that oscillations play critical\u0000physiological roles. Oscillatory behavior enables systems to avoid\u0000desensitization, to avoid chronically high and therefore toxic levels of\u0000chemicals, and to become more resistant to noise. Oscillation also enables\u0000complex physiological systems to reconcile incompatible conditions such as\u0000oxidation and reduction, by cycling between them, and to synchronize the\u0000oscillations of many small units into one large effect. In pancreatic b cells,\u0000we show that glycolytic oscillations are in synchrony with calcium and\u0000mitochondrial oscillations to drive pulsatile insulin release, which is pivotal\u0000for the liver to regulate blood glucose dynamics. In addition, oscillation can\u0000keep biological time, essential for embryonic development in promoting cell\u0000diversity and pattern formation. The functional importance of oscillatory\u0000processes requires a rethinking of the traditional doctrine of homeostasis,\u0000holding that physiological quantities are maintained at constant equilibrium\u0000values, which has largely failed us in the clinic. A more dynamic approach will\u0000enable us to view health and disease through a new light and initiate a\u0000paradigm shift in treating diseases, including depression and cancer. This\u0000modern synthesis also takes a deeper look into the mechanisms that create and\u0000sustain oscillatory processes, which requires the language of nonlinear\u0000dynamics, well beyond the linearization techniques of equilibrium control\u0000theory.","PeriodicalId":501170,"journal":{"name":"arXiv - QuanBio - Subcellular Processes","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138532800","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}