[{"oa":1,"publisher":"Public Library of Science","quality_controlled":"1","year":"2020","isi":1,"has_accepted_license":"1","publication":"PLOS Computational Biology","day":"25","date_created":"2020-03-06T07:39:38Z","date_published":"2020-02-25T00:00:00Z","doi":"10.1371/journal.pcbi.1007642","article_number":"e1007642","citation":{"mla":"Grah, Rok, and Tamar Friedlander. “The Relation between Crosstalk and Gene Regulation Form Revisited.” PLOS Computational Biology, vol. 16, no. 2, e1007642, Public Library of Science, 2020, doi:10.1371/journal.pcbi.1007642.","ieee":"R. Grah and T. Friedlander, “The relation between crosstalk and gene regulation form revisited,” PLOS Computational Biology, vol. 16, no. 2. Public Library of Science, 2020.","short":"R. Grah, T. Friedlander, PLOS Computational Biology 16 (2020).","ama":"Grah R, Friedlander T. The relation between crosstalk and gene regulation form revisited. PLOS Computational Biology. 2020;16(2). doi:10.1371/journal.pcbi.1007642","apa":"Grah, R., & Friedlander, T. (2020). The relation between crosstalk and gene regulation form revisited. PLOS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007642","chicago":"Grah, Rok, and Tamar Friedlander. “The Relation between Crosstalk and Gene Regulation Form Revisited.” PLOS Computational Biology. Public Library of Science, 2020. https://doi.org/10.1371/journal.pcbi.1007642.","ista":"Grah R, Friedlander T. 2020. The relation between crosstalk and gene regulation form revisited. PLOS Computational Biology. 16(2), e1007642."},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","article_processing_charge":"No","external_id":{"isi":["000526725200019"]},"author":[{"id":"483E70DE-F248-11E8-B48F-1D18A9856A87","first_name":"Rok","full_name":"Grah, Rok","orcid":"0000-0003-2539-3560","last_name":"Grah"},{"first_name":"Tamar","last_name":"Friedlander","full_name":"Friedlander, Tamar"}],"title":"The relation between crosstalk and gene regulation form revisited","abstract":[{"lang":"eng","text":"Genes differ in the frequency at which they are expressed and in the form of regulation used to control their activity. In particular, positive or negative regulation can lead to activation of a gene in response to an external signal. Previous works proposed that the form of regulation of a gene correlates with its frequency of usage: positive regulation when the gene is frequently expressed and negative regulation when infrequently expressed. Such network design means that, in the absence of their regulators, the genes are found in their least required activity state, hence regulatory intervention is often necessary. Due to the multitude of genes and regulators, spurious binding and unbinding events, called “crosstalk”, could occur. To determine how the form of regulation affects the global crosstalk in the network, we used a mathematical model that includes multiple regulators and multiple target genes. We found that crosstalk depends non-monotonically on the availability of regulators. Our analysis showed that excess use of regulation entailed by the formerly suggested network design caused high crosstalk levels in a large part of the parameter space. We therefore considered the opposite ‘idle’ design, where the default unregulated state of genes is their frequently required activity state. We found, that ‘idle’ design minimized the use of regulation and thus minimized crosstalk. In addition, we estimated global crosstalk of S. cerevisiae using transcription factors binding data. We demonstrated that even partial network data could suffice to estimate its global crosstalk, suggesting its applicability to additional organisms. We found that S. cerevisiae estimated crosstalk is lower than that of a random network, suggesting that natural selection reduces crosstalk. In summary, our study highlights a new type of protein production cost which is typically overlooked: that of regulatory interference caused by the presence of excess regulators in the cell. It demonstrates the importance of whole-network descriptions, which could show effects missed by single-gene models."}],"oa_version":"Published Version","scopus_import":"1","intvolume":" 16","month":"02","publication_status":"published","publication_identifier":{"issn":["1553-7358"]},"language":[{"iso":"eng"}],"file":[{"creator":"dernst","date_updated":"2020-07-14T12:48:00Z","file_size":2209325,"date_created":"2020-03-09T15:12:21Z","file_name":"2020_PlosCompBio_Grah.pdf","access_level":"open_access","relation":"main_file","content_type":"application/pdf","checksum":"5239dd134dc6e1c71fe7b3ce2953da37","file_id":"7579"}],"license":"https://creativecommons.org/licenses/by/4.0/","issue":"2","related_material":{"record":[{"relation":"research_data","id":"9716","status":"deleted"},{"relation":"research_data","status":"public","id":"9776"},{"id":"9779","status":"public","relation":"used_in_publication"},{"relation":"dissertation_contains","id":"8155","status":"public"},{"status":"public","id":"9777","relation":"research_data"}]},"volume":16,"_id":"7569","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"article_type":"original","type":"journal_article","status":"public","date_updated":"2023-09-12T11:02:24Z","ddc":["000","570"],"file_date_updated":"2020-07-14T12:48:00Z","department":[{"_id":"CaGu"},{"_id":"GaTk"}]},{"date_updated":"2023-09-12T11:02:25Z","citation":{"ama":"Grah R, Friedlander T. Maximizing crosstalk. 2020. doi:10.1371/journal.pcbi.1007642.s002","apa":"Grah, R., & Friedlander, T. (2020). Maximizing crosstalk. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007642.s002","ieee":"R. Grah and T. Friedlander, “Maximizing crosstalk.” Public Library of Science, 2020.","short":"R. Grah, T. Friedlander, (2020).","mla":"Grah, Rok, and Tamar Friedlander. Maximizing Crosstalk. Public Library of Science, 2020, doi:10.1371/journal.pcbi.1007642.s002.","ista":"Grah R, Friedlander T. 2020. Maximizing crosstalk, Public Library of Science, 10.1371/journal.pcbi.1007642.s002.","chicago":"Grah, Rok, and Tamar Friedlander. “Maximizing Crosstalk.” Public Library of Science, 2020. https://doi.org/10.1371/journal.pcbi.1007642.s002."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","author":[{"full_name":"Grah, Rok","orcid":"0000-0003-2539-3560","last_name":"Grah","id":"483E70DE-F248-11E8-B48F-1D18A9856A87","first_name":"Rok"},{"last_name":"Friedlander","full_name":"Friedlander, Tamar","first_name":"Tamar"}],"department":[{"_id":"GaTk"}],"title":"Maximizing crosstalk","_id":"9777","type":"research_data_reference","status":"public","year":"2020","day":"25","date_created":"2021-08-06T07:21:51Z","doi":"10.1371/journal.pcbi.1007642.s002","date_published":"2020-02-25T00:00:00Z","related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"7569"}]},"oa_version":"None","oa":1,"main_file_link":[{"url":"https://doi.org/10.1371/journal.pcbi.1007642.s002","open_access":"1"}],"publisher":"Public Library of Science","month":"02"},{"acknowledged_ssus":[{"_id":"LifeSc"}],"abstract":[{"lang":"eng","text":"Antibiotics that interfere with translation, when combined, interact in diverse and difficult-to-predict ways. Here, we explain these interactions by \"translation bottlenecks\": points in the translation cycle where antibiotics block ribosomal progression. To elucidate the underlying mechanisms of drug interactions between translation inhibitors, we generate translation bottlenecks genetically using inducible control of translation factors that regulate well-defined translation cycle steps. These perturbations accurately mimic antibiotic action and drug interactions, supporting that the interplay of different translation bottlenecks causes these interactions. We further show that growth laws, combined with drug uptake and binding kinetics, enable the direct prediction of a large fraction of observed interactions, yet fail to predict suppression. However, varying two translation bottlenecks simultaneously supports that dense traffic of ribosomes and competition for translation factors account for the previously unexplained suppression. These results highlight the importance of \"continuous epistasis\" in bacterial physiology."}],"oa_version":"Published Version","publisher":"Institute of Science and Technology Austria","oa":1,"month":"07","has_accepted_license":"1","year":"2020","day":"15","file":[{"content_type":"application/zip","access_level":"open_access","relation":"main_file","file_id":"8098","checksum":"5c321dbbb6d4b3c85da786fd3ebbdc98","date_updated":"2020-07-14T12:48:09Z","file_size":255770756,"creator":"bkavcic","date_created":"2020-07-06T20:38:27Z","file_name":"natComm_2020_scripts.zip"}],"date_published":"2020-07-15T00:00:00Z","doi":"10.15479/AT:ISTA:8097","date_created":"2020-07-06T20:40:19Z","contributor":[{"last_name":"Tkačik","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","contributor_type":"research_group","first_name":"Gašper"},{"contributor_type":"research_group","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","first_name":"Tobias","last_name":"Bollenbach"}],"_id":"8097","type":"research_data","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"status":"public","keyword":["Escherichia coli","antibiotic combinations","translation","growth laws","drug interactions","bacterial physiology","translation inhibitors"],"date_updated":"2024-02-21T12:40:51Z","citation":{"ista":"Kavcic B. 2020. Analysis scripts and research data for the paper ‘Mechanisms of drug interactions between translation-inhibiting antibiotics’, Institute of Science and Technology Austria, 10.15479/AT:ISTA:8097.","chicago":"Kavcic, Bor. “Analysis Scripts and Research Data for the Paper ‘Mechanisms of Drug Interactions between Translation-Inhibiting Antibiotics.’” Institute of Science and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:8097.","apa":"Kavcic, B. (2020). Analysis scripts and research data for the paper “Mechanisms of drug interactions between translation-inhibiting antibiotics.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8097","ama":"Kavcic B. Analysis scripts and research data for the paper “Mechanisms of drug interactions between translation-inhibiting antibiotics.” 2020. doi:10.15479/AT:ISTA:8097","ieee":"B. Kavcic, “Analysis scripts and research data for the paper ‘Mechanisms of drug interactions between translation-inhibiting antibiotics.’” Institute of Science and Technology Austria, 2020.","short":"B. Kavcic, (2020).","mla":"Kavcic, Bor. Analysis Scripts and Research Data for the Paper “Mechanisms of Drug Interactions between Translation-Inhibiting Antibiotics.” Institute of Science and Technology Austria, 2020, doi:10.15479/AT:ISTA:8097."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","last_name":"Kavcic","orcid":"0000-0001-6041-254X","full_name":"Kavcic, Bor"}],"article_processing_charge":"No","file_date_updated":"2020-07-14T12:48:09Z","department":[{"_id":"GaTk"}],"title":"Analysis scripts and research data for the paper \"Mechanisms of drug interactions between translation-inhibiting antibiotics\""},{"author":[{"last_name":"Kavcic","full_name":"Kavcic, Bor","orcid":"0000-0001-6041-254X","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","first_name":"Bor"}],"article_processing_charge":"No","title":"Analysis scripts and research data for the paper \"Minimal biophysical model of combined antibiotic action\"","file_date_updated":"2020-12-09T15:00:19Z","department":[{"_id":"GaTk"}],"date_updated":"2024-02-21T12:41:42Z","citation":{"chicago":"Kavcic, Bor. “Analysis Scripts and Research Data for the Paper ‘Minimal Biophysical Model of Combined Antibiotic Action.’” Institute of Science and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:8930.","ista":"Kavcic B. 2020. Analysis scripts and research data for the paper ‘Minimal biophysical model of combined antibiotic action’, Institute of Science and Technology Austria, 10.15479/AT:ISTA:8930.","mla":"Kavcic, Bor. Analysis Scripts and Research Data for the Paper “Minimal Biophysical Model of Combined Antibiotic Action.” Institute of Science and Technology Austria, 2020, doi:10.15479/AT:ISTA:8930.","short":"B. Kavcic, (2020).","ieee":"B. Kavcic, “Analysis scripts and research data for the paper ‘Minimal biophysical model of combined antibiotic action.’” Institute of Science and Technology Austria, 2020.","apa":"Kavcic, B. (2020). Analysis scripts and research data for the paper “Minimal biophysical model of combined antibiotic action.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8930","ama":"Kavcic B. Analysis scripts and research data for the paper “Minimal biophysical model of combined antibiotic action.” 2020. doi:10.15479/AT:ISTA:8930"},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","ddc":["570"],"type":"research_data","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"status":"public","keyword":["Escherichia coli","antibiotic combinations","translation","growth laws","drug interactions","bacterial physiology","translation inhibitors"],"_id":"8930","related_material":{"record":[{"id":"8997","status":"public","relation":"used_in_publication"}]},"date_published":"2020-12-10T00:00:00Z","doi":"10.15479/AT:ISTA:8930","contributor":[{"last_name":"Tkačik","orcid":"0000-0002-6699-1455","first_name":"Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","contributor_type":"supervisor"},{"last_name":"Bollenbach","contributor_type":"supervisor","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","first_name":"Tobias"}],"date_created":"2020-12-09T15:04:02Z","has_accepted_license":"1","year":"2020","file":[{"access_level":"open_access","relation":"main_file","content_type":"application/zip","file_id":"8932","checksum":"60a818edeffaa7da1ebf5f8fbea9ba18","success":1,"creator":"bkavcic","date_updated":"2020-12-09T15:00:19Z","file_size":315494370,"date_created":"2020-12-09T15:00:19Z","file_name":"PLoSCompBiol2020_datarep.zip"}],"day":"10","publisher":"Institute of Science and Technology Austria","oa":1,"month":"12","abstract":[{"lang":"eng","text":"Phenomenological relations such as Ohm’s or Fourier’s law have a venerable history in physics but are still scarce in biology. This situation restrains predictive theory. Here, we build on bacterial “growth laws,” which capture physiological feedback between translation and cell growth, to construct a minimal biophysical model for the combined action of ribosome-targeting antibiotics. Our model predicts drug interactions like antagonism or synergy solely from responses to individual drugs. We provide analytical results for limiting cases, which agree well with numerical results. We systematically refine the model by including direct physical interactions of different antibiotics on the ribosome. In a limiting case, our model provides a mechanistic underpinning for recent predictions of higher-order interactions that were derived using entropy maximization. We further refine the model to include the effects of antibiotics that mimic starvation and the presence of resistance genes. We describe the impact of a starvation-mimicking antibiotic on drug interactions analytically and verify it experimentally. Our extended model suggests a change in the type of drug interaction that depends on the strength of resistance, which challenges established rescaling paradigms. We experimentally show that the presence of unregulated resistance genes can lead to altered drug interaction, which agrees with the prediction of the model. While minimal, the model is readily adaptable and opens the door to predicting interactions of second and higher-order in a broad range of biological systems."}],"oa_version":"Published Version"},{"date_updated":"2024-02-21T12:42:31Z","citation":{"ista":"Grah R. 2020. Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level Gene Expression regulation, Institute of Science and Technology Austria, 10.15479/AT:ISTA:7383.","chicago":"Grah, Rok. “Matlab Scripts for the Paper: Gene Amplification as a Form of Population-Level Gene Expression Regulation.” Institute of Science and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:7383.","short":"R. Grah, (2020).","ieee":"R. Grah, “Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level Gene Expression regulation.” Institute of Science and Technology Austria, 2020.","ama":"Grah R. Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level Gene Expression regulation. 2020. doi:10.15479/AT:ISTA:7383","apa":"Grah, R. (2020). Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level Gene Expression regulation. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:7383","mla":"Grah, Rok. Matlab Scripts for the Paper: Gene Amplification as a Form of Population-Level Gene Expression Regulation. Institute of Science and Technology Austria, 2020, doi:10.15479/AT:ISTA:7383."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","author":[{"last_name":"Grah","full_name":"Grah, Rok","orcid":"0000-0003-2539-3560","id":"483E70DE-F248-11E8-B48F-1D18A9856A87","first_name":"Rok"}],"file_date_updated":"2020-07-14T12:47:57Z","title":"Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level Gene Expression regulation","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"_id":"7383","type":"research_data","keyword":["Matlab scripts","analysis of microfluidics","mathematical model"],"status":"public","year":"2020","has_accepted_license":"1","day":"28","file":[{"file_name":"Scripts.zip","date_created":"2020-01-28T10:39:40Z","file_size":73363365,"date_updated":"2020-07-14T12:47:57Z","creator":"rgrah","checksum":"9d292cf5207b3829225f44c044cdb3fd","file_id":"7384","content_type":"application/zip","relation":"main_file","access_level":"open_access"},{"file_size":962,"date_updated":"2020-07-14T12:47:57Z","creator":"rgrah","file_name":"READ_ME_MAIN.txt","date_created":"2020-01-28T10:39:30Z","content_type":"text/plain","relation":"main_file","access_level":"open_access","file_id":"7385","checksum":"4076ceab32ef588cc233802bab24c1ab"}],"date_created":"2020-01-28T10:41:49Z","contributor":[{"first_name":"Calin C","contributor_type":"project_leader","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","last_name":"Guet","orcid":"0000-0001-6220-2052"}],"date_published":"2020-01-28T00:00:00Z","doi":"10.15479/AT:ISTA:7383","related_material":{"record":[{"id":"7652","status":"public","relation":"used_in_publication"}]},"abstract":[{"lang":"eng","text":"Organisms cope with change by employing transcriptional regulators. However, when faced with rare environments, the evolution of transcriptional regulators and their promoters may be too slow. We ask whether the intrinsic instability of gene duplication and amplification provides a generic alternative to canonical gene regulation. By real-time monitoring of gene copy number mutations in E. coli, we show that gene duplications and amplifications enable adaptation to fluctuating environments by rapidly generating copy number, and hence expression level, polymorphism. This ‘amplification-mediated gene expression tuning’ occurs on timescales similar to canonical gene regulation and can deal with rapid environmental changes. Mathematical modeling shows that amplifications also tune gene expression in stochastic environments where transcription factor-based schemes are hard to evolve or maintain. The fleeting nature of gene amplifications gives rise to a generic population-level mechanism that relies on genetic heterogeneity to rapidly tune expression of any gene, without leaving any genomic signature."}],"oa_version":"Published Version","oa":1,"publisher":"Institute of Science and Technology Austria","month":"01"},{"_id":"8657","status":"public","type":"dissertation","ddc":["571","530","570"],"date_updated":"2023-09-07T13:20:48Z","supervisor":[{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper","last_name":"Tkačik","orcid":"0000-0002-6699-1455","full_name":"Tkačik, Gašper"},{"id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","first_name":"Mark Tobias","orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Mark Tobias","last_name":"Bollenbach"}],"department":[{"_id":"GaTk"}],"file_date_updated":"2021-10-07T22:30:03Z","oa_version":"Published Version","acknowledged_ssus":[{"_id":"LifeSc"},{"_id":"M-Shop"}],"abstract":[{"lang":"eng","text":"Synthesis of proteins – translation – is a fundamental process of life. Quantitative studies anchor translation into the context of bacterial physiology and reveal several mathematical relationships, called “growth laws,” which capture physiological feedbacks between protein synthesis and cell growth. Growth laws describe the dependency of the ribosome abundance as a function of growth rate, which can change depending on the growth conditions. Perturbations of translation reveal that bacteria employ a compensatory strategy in which the reduced translation capability results in increased expression of the translation machinery.\r\nPerturbations of translation are achieved in various ways; clinically interesting is the application of translation-targeting antibiotics – translation inhibitors. The antibiotic effects on bacterial physiology are often poorly understood. Bacterial responses to two or more simultaneously applied antibiotics are even more puzzling. The combined antibiotic effect determines the type of drug interaction, which ranges from synergy (the effect is stronger than expected) to antagonism (the effect is weaker) and suppression (one of the drugs loses its potency).\r\nIn the first part of this work, we systematically measure the pairwise interaction network for translation inhibitors that interfere with different steps in translation. We find that the interactions are surprisingly diverse and tend to be more antagonistic. To explore the underlying mechanisms, we begin with a minimal biophysical model of combined antibiotic action. We base this model on the kinetics of antibiotic uptake and binding together with the physiological response described by the growth laws. The biophysical model explains some drug interactions, but not all; it specifically fails to predict suppression.\r\nIn the second part of this work, we hypothesize that elusive suppressive drug interactions result from the interplay between ribosomes halted in different stages of translation. To elucidate this putative mechanism of drug interactions between translation inhibitors, we generate translation bottlenecks genetically using in- ducible control of translation factors that regulate well-defined translation cycle steps. These perturbations accurately mimic antibiotic action and drug interactions, supporting that the interplay of different translation bottlenecks partially causes these interactions.\r\nWe extend this approach by varying two translation bottlenecks simultaneously. This approach reveals the suppression of translocation inhibition by inhibited translation. We rationalize this effect by modeling dense traffic of ribosomes that move on transcripts in a translation factor-mediated manner. This model predicts a dissolution of traffic jams caused by inhibited translocation when the density of ribosome traffic is reduced by lowered initiation. We base this model on the growth laws and quantitative relationships between different translation and growth parameters.\r\nIn the final part of this work, we describe a set of tools aimed at quantification of physiological and translation parameters. We further develop a simple model that directly connects the abundance of a translation factor with the growth rate, which allows us to extract physiological parameters describing initiation. We demonstrate the development of tools for measuring translation rate.\r\nThis thesis showcases how a combination of high-throughput growth rate mea- surements, genetics, and modeling can reveal mechanisms of drug interactions. Furthermore, by a gradual transition from combinations of antibiotics to precise genetic interventions, we demonstrated the equivalency between genetic and chemi- cal perturbations of translation. These findings tile the path for quantitative studies of antibiotic combinations and illustrate future approaches towards the quantitative description of translation."}],"month":"10","alternative_title":["ISTA Thesis"],"language":[{"iso":"eng"}],"file":[{"content_type":"application/pdf","relation":"main_file","access_level":"open_access","embargo":"2021-10-06","checksum":"d708ecd62b6fcc3bc1feb483b8dbe9eb","file_id":"8663","file_size":52636162,"date_updated":"2021-10-07T22:30:03Z","creator":"bkavcic","file_name":"kavcicB_thesis202009.pdf","date_created":"2020-10-15T06:41:20Z"},{"date_created":"2020-10-15T06:41:53Z","file_name":"2020b.zip","creator":"bkavcic","date_updated":"2021-10-07T22:30:03Z","file_size":321681247,"file_id":"8664","checksum":"bb35f2352a04db19164da609f00501f3","access_level":"closed","relation":"source_file","content_type":"application/zip","embargo_to":"open_access"}],"publication_status":"published","degree_awarded":"PhD","publication_identifier":{"isbn":["978-3-99078-011-4"],"issn":["2663-337X"]},"related_material":{"record":[{"relation":"part_of_dissertation","id":"7673","status":"public"},{"id":"8250","status":"public","relation":"part_of_dissertation"}]},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"mla":"Kavcic, Bor. Perturbations of Protein Synthesis: From Antibiotics to Genetics and Physiology. Institute of Science and Technology Austria, 2020, doi:10.15479/AT:ISTA:8657.","apa":"Kavcic, B. (2020). Perturbations of protein synthesis: from antibiotics to genetics and physiology. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8657","ama":"Kavcic B. Perturbations of protein synthesis: from antibiotics to genetics and physiology. 2020. doi:10.15479/AT:ISTA:8657","ieee":"B. Kavcic, “Perturbations of protein synthesis: from antibiotics to genetics and physiology,” Institute of Science and Technology Austria, 2020.","short":"B. Kavcic, Perturbations of Protein Synthesis: From Antibiotics to Genetics and Physiology, Institute of Science and Technology Austria, 2020.","chicago":"Kavcic, Bor. “Perturbations of Protein Synthesis: From Antibiotics to Genetics and Physiology.” Institute of Science and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:8657.","ista":"Kavcic B. 2020. Perturbations of protein synthesis: from antibiotics to genetics and physiology. Institute of Science and Technology Austria."},"title":"Perturbations of protein synthesis: from antibiotics to genetics and physiology","article_processing_charge":"No","author":[{"first_name":"Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6041-254X","full_name":"Kavcic, Bor","last_name":"Kavcic"}],"acknowledgement":"I thank Life Science Facilities for their continuous support with providing top-notch laboratory materials, keeping the devices humming, and coordinating the repairs and building of custom-designed laboratory equipment with the MIBA Machine shop.","oa":1,"publisher":"Institute of Science and Technology Austria","day":"14","year":"2020","has_accepted_license":"1","date_created":"2020-10-13T16:46:14Z","date_published":"2020-10-14T00:00:00Z","doi":"10.15479/AT:ISTA:8657","page":"271"},{"title":"Mechanisms of drug interactions between translation-inhibiting antibiotics","author":[{"id":"350F91D2-F248-11E8-B48F-1D18A9856A87","first_name":"Bor","last_name":"Kavcic","full_name":"Kavcic, Bor","orcid":"0000-0001-6041-254X"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper","last_name":"Tkačik","orcid":"0000-0002-6699-1455","full_name":"Tkačik, Gašper"},{"first_name":"Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","full_name":"Bollenbach, Tobias","orcid":"0000-0003-4398-476X","last_name":"Bollenbach"}],"article_processing_charge":"No","external_id":{"isi":["000562769300008"]},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","citation":{"ista":"Kavcic B, Tkačik G, Bollenbach MT. 2020. Mechanisms of drug interactions between translation-inhibiting antibiotics. Nature Communications. 11, 4013.","chicago":"Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “Mechanisms of Drug Interactions between Translation-Inhibiting Antibiotics.” Nature Communications. Springer Nature, 2020. https://doi.org/10.1038/s41467-020-17734-z.","ama":"Kavcic B, Tkačik G, Bollenbach MT. Mechanisms of drug interactions between translation-inhibiting antibiotics. Nature Communications. 2020;11. doi:10.1038/s41467-020-17734-z","apa":"Kavcic, B., Tkačik, G., & Bollenbach, M. T. (2020). Mechanisms of drug interactions between translation-inhibiting antibiotics. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-020-17734-z","ieee":"B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Mechanisms of drug interactions between translation-inhibiting antibiotics,” Nature Communications, vol. 11. Springer Nature, 2020.","short":"B. Kavcic, G. Tkačik, M.T. Bollenbach, Nature Communications 11 (2020).","mla":"Kavcic, Bor, et al. “Mechanisms of Drug Interactions between Translation-Inhibiting Antibiotics.” Nature Communications, vol. 11, 4013, Springer Nature, 2020, doi:10.1038/s41467-020-17734-z."},"project":[{"call_identifier":"FWF","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","grant_number":"P27201-B22","name":"Revealing the mechanisms underlying drug interactions"},{"_id":"254E9036-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation"}],"article_number":"4013","date_published":"2020-08-11T00:00:00Z","doi":"10.1038/s41467-020-17734-z","date_created":"2020-08-12T09:13:50Z","day":"11","publication":"Nature Communications","has_accepted_license":"1","isi":1,"year":"2020","quality_controlled":"1","publisher":"Springer Nature","oa":1,"acknowledgement":"We thank M. Hennessey-Wesen, I. Tomanek, K. Jain, A. Staron, K. Tomasek, M. Scott,\r\nK.C. Huang, and Z. Gitai for reading the manuscript and constructive comments. B.K. is\r\nindebted to C. Guet for additional guidance and generous support, which rendered this\r\nwork possible. B.K. thanks all members of Guet group for many helpful discussions and\r\nsharing of resources. B.K. additionally acknowledges the tremendous support from A.\r\nAngermayr and K. Mitosch with experimental work. We further thank E. Brown for\r\nhelpful comments regarding lamotrigine, and A. Buskirk for valuable suggestions\r\nregarding the ribosome footprint size. This work was supported in part by Austrian\r\nScience Fund (FWF) standalone grants P 27201-B22 (to T.B.) and P 28844 (to G.T.),\r\nHFSP program Grant RGP0042/2013 (to T.B.), German Research Foundation (DFG)\r\nstandalone grant BO 3502/2-1 (to T.B.), and German Research Foundation (DFG)\r\nCollaborative Research Centre (SFB) 1310 (to T.B.). Open access funding provided by\r\nProjekt DEAL.","department":[{"_id":"GaTk"}],"file_date_updated":"2020-08-17T07:36:57Z","ddc":["570"],"date_updated":"2024-03-27T23:30:08Z","status":"public","type":"journal_article","article_type":"original","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"_id":"8250","related_material":{"record":[{"status":"public","id":"8657","relation":"dissertation_contains"}]},"volume":11,"file":[{"success":1,"file_id":"8275","checksum":"986bebb308850a55850028d3d2b5b664","relation":"main_file","access_level":"open_access","content_type":"application/pdf","file_name":"2020_NatureComm_Kavcic.pdf","date_created":"2020-08-17T07:36:57Z","creator":"dernst","file_size":1965672,"date_updated":"2020-08-17T07:36:57Z"}],"language":[{"iso":"eng"}],"publication_identifier":{"issn":["2041-1723"]},"publication_status":"published","month":"08","intvolume":" 11","oa_version":"Published Version","abstract":[{"lang":"eng","text":"Antibiotics that interfere with translation, when combined, interact in diverse and difficult-to-predict ways. Here, we explain these interactions by “translation bottlenecks”: points in the translation cycle where antibiotics block ribosomal progression. To elucidate the underlying mechanisms of drug interactions between translation inhibitors, we generate translation bottlenecks genetically using inducible control of translation factors that regulate well-defined translation cycle steps. These perturbations accurately mimic antibiotic action and drug interactions, supporting that the interplay of different translation bottlenecks causes these interactions. We further show that growth laws, combined with drug uptake and binding kinetics, enable the direct prediction of a large fraction of observed interactions, yet fail to predict suppression. However, varying two translation bottlenecks simultaneously supports that dense traffic of ribosomes and competition for translation factors account for the previously unexplained suppression. These results highlight the importance of “continuous epistasis” in bacterial physiology."}]},{"oa_version":"Preprint","abstract":[{"text":"Combining drugs can improve the efficacy of treatments. However, predicting the effect of drug combinations is still challenging. The combined potency of drugs determines the drug interaction, which is classified as synergistic, additive, antagonistic, or suppressive. While probabilistic, non-mechanistic models exist, there is currently no biophysical model that can predict antibiotic interactions. Here, we present a physiologically relevant model of the combined action of antibiotics that inhibit protein synthesis by targeting the ribosome. This model captures the kinetics of antibiotic binding and transport, and uses bacterial growth laws to predict growth in the presence of antibiotic combinations. We find that this biophysical model can produce all drug interaction types except suppression. We show analytically that antibiotics which cannot bind to the ribosome simultaneously generally act as substitutes for one another, leading to additive drug interactions. Previously proposed null expectations for higher-order drug interactions follow as a limiting case of our model. We further extend the model to include the effects of direct physical or allosteric interactions between individual drugs on the ribosome. Notably, such direct interactions profoundly change the combined drug effect, depending on the kinetic parameters of the drugs used. The model makes additional predictions for the effects of resistance genes on drug interactions and for interactions between ribosome-targeting antibiotics and antibiotics with other targets. These findings enhance our understanding of the interplay between drug action and cell physiology and are a key step toward a general framework for predicting drug interactions.","lang":"eng"}],"month":"04","publisher":"Cold Spring Harbor Laboratory","oa":1,"main_file_link":[{"url":"https://doi.org/10.1101/2020.04.18.047886 ","open_access":"1"}],"day":"18","language":[{"iso":"eng"}],"publication":"bioRxiv","publication_status":"published","year":"2020","doi":"10.1101/2020.04.18.047886","related_material":{"record":[{"status":"public","id":"8997","relation":"later_version"},{"id":"8657","status":"public","relation":"dissertation_contains"}]},"date_published":"2020-04-18T00:00:00Z","date_created":"2020-04-22T08:27:56Z","_id":"7673","project":[{"call_identifier":"FWF","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","name":"Revealing the mechanisms underlying drug interactions","grant_number":"P27201-B22"},{"_id":"254E9036-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27"}],"status":"public","type":"preprint","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"mla":"Kavcic, Bor, et al. “A Minimal Biophysical Model of Combined Antibiotic Action.” BioRxiv, Cold Spring Harbor Laboratory, 2020, doi:10.1101/2020.04.18.047886.","short":"B. Kavcic, G. Tkačik, M.T. Bollenbach, BioRxiv (2020).","ieee":"B. Kavcic, G. Tkačik, and M. T. Bollenbach, “A minimal biophysical model of combined antibiotic action,” bioRxiv. Cold Spring Harbor Laboratory, 2020.","apa":"Kavcic, B., Tkačik, G., & Bollenbach, M. T. (2020). A minimal biophysical model of combined antibiotic action. bioRxiv. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2020.04.18.047886","ama":"Kavcic B, Tkačik G, Bollenbach MT. A minimal biophysical model of combined antibiotic action. bioRxiv. 2020. doi:10.1101/2020.04.18.047886","chicago":"Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “A Minimal Biophysical Model of Combined Antibiotic Action.” BioRxiv. Cold Spring Harbor Laboratory, 2020. https://doi.org/10.1101/2020.04.18.047886.","ista":"Kavcic B, Tkačik G, Bollenbach MT. 2020. A minimal biophysical model of combined antibiotic action. bioRxiv, 10.1101/2020.04.18.047886."},"date_updated":"2024-03-27T23:30:08Z","department":[{"_id":"GaTk"}],"title":"A minimal biophysical model of combined antibiotic action","author":[{"last_name":"Kavcic","full_name":"Kavcic, Bor","orcid":"0000-0001-6041-254X","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","first_name":"Bor"},{"first_name":"Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","full_name":"Tkačik, Gašper","last_name":"Tkačik"},{"id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","first_name":"Tobias","full_name":"Bollenbach, Tobias","orcid":"0000-0003-4398-476X","last_name":"Bollenbach"}],"article_processing_charge":"No"},{"title":"Gene amplification as a form of population-level gene expression regulation","author":[{"orcid":"0000-0001-6197-363X","full_name":"Tomanek, Isabella","last_name":"Tomanek","id":"3981F020-F248-11E8-B48F-1D18A9856A87","first_name":"Isabella"},{"full_name":"Grah, Rok","orcid":"0000-0003-2539-3560","last_name":"Grah","first_name":"Rok","id":"483E70DE-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Lagator, M.","last_name":"Lagator","first_name":"M."},{"last_name":"Andersson","full_name":"Andersson, A. M. C.","first_name":"A. M. C."},{"id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87","first_name":"Jonathan P","last_name":"Bollback","full_name":"Bollback, Jonathan P","orcid":"0000-0002-4624-4612"},{"first_name":"Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkačik","full_name":"Tkačik, Gašper","orcid":"0000-0002-6699-1455"},{"id":"47F8433E-F248-11E8-B48F-1D18A9856A87","first_name":"Calin C","last_name":"Guet","orcid":"0000-0001-6220-2052","full_name":"Guet, Calin C"}],"article_processing_charge":"No","external_id":{"isi":["000519008300005"]},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","citation":{"ista":"Tomanek I, Grah R, Lagator M, Andersson AMC, Bollback JP, Tkačik G, Guet CC. 2020. Gene amplification as a form of population-level gene expression regulation. Nature Ecology & Evolution. 4(4), 612–625.","chicago":"Tomanek, Isabella, Rok Grah, M. Lagator, A. M. C. Andersson, Jonathan P Bollback, Gašper Tkačik, and Calin C Guet. “Gene Amplification as a Form of Population-Level Gene Expression Regulation.” Nature Ecology & Evolution. Springer Nature, 2020. https://doi.org/10.1038/s41559-020-1132-7.","short":"I. Tomanek, R. Grah, M. Lagator, A.M.C. Andersson, J.P. Bollback, G. Tkačik, C.C. Guet, Nature Ecology & Evolution 4 (2020) 612–625.","ieee":"I. Tomanek et al., “Gene amplification as a form of population-level gene expression regulation,” Nature Ecology & Evolution, vol. 4, no. 4. Springer Nature, pp. 612–625, 2020.","apa":"Tomanek, I., Grah, R., Lagator, M., Andersson, A. M. C., Bollback, J. P., Tkačik, G., & Guet, C. C. (2020). Gene amplification as a form of population-level gene expression regulation. Nature Ecology & Evolution. Springer Nature. https://doi.org/10.1038/s41559-020-1132-7","ama":"Tomanek I, Grah R, Lagator M, et al. Gene amplification as a form of population-level gene expression regulation. Nature Ecology & Evolution. 2020;4(4):612-625. doi:10.1038/s41559-020-1132-7","mla":"Tomanek, Isabella, et al. “Gene Amplification as a Form of Population-Level Gene Expression Regulation.” Nature Ecology & Evolution, vol. 4, no. 4, Springer Nature, 2020, pp. 612–25, doi:10.1038/s41559-020-1132-7."},"project":[{"name":"Biophysically realistic genotype-phenotype maps for regulatory networks","_id":"267C84F4-B435-11E9-9278-68D0E5697425"}],"doi":"10.1038/s41559-020-1132-7","date_published":"2020-04-01T00:00:00Z","date_created":"2020-04-08T15:20:53Z","page":"612-625","day":"01","publication":"Nature Ecology & Evolution","has_accepted_license":"1","isi":1,"year":"2020","publisher":"Springer Nature","quality_controlled":"1","oa":1,"acknowledgement":"We thank L. Hurst, N. Barton, M. Pleska, M. Steinrück, B. Kavcic and A. Staron for input on the manuscript, and To. Bergmiller and R. Chait for help with microfluidics experiments. I.T. is a recipient the OMV fellowship. R.G. is a recipient of a DOC (Doctoral Fellowship Programme of the Austrian Academy of Sciences) Fellowship of the Austrian Academy of Sciences.","file_date_updated":"2020-10-09T09:56:01Z","department":[{"_id":"GaTk"},{"_id":"CaGu"}],"ddc":["570"],"date_updated":"2024-03-27T23:30:36Z","status":"public","type":"journal_article","article_type":"original","_id":"7652","volume":4,"related_material":{"link":[{"relation":"press_release","url":"https://ist.ac.at/en/news/how-to-thrive-without-gene-regulation/","description":"News on IST Homepage"}],"record":[{"status":"public","id":"8155","relation":"dissertation_contains"},{"id":"7383","status":"public","relation":"research_data"},{"relation":"research_data","id":"7016","status":"public"},{"id":"8653","status":"public","relation":"used_in_publication"}]},"issue":"4","file":[{"creator":"dernst","date_updated":"2020-10-09T09:56:01Z","file_size":745242,"date_created":"2020-10-09T09:56:01Z","file_name":"2020_NatureEcolEvo_Tomanek.pdf","access_level":"open_access","relation":"main_file","content_type":"application/pdf","checksum":"ef3bbf42023e30b2c24a6278025d2040","file_id":"8640","success":1}],"language":[{"iso":"eng"}],"publication_identifier":{"issn":["2397-334X"]},"publication_status":"published","month":"04","intvolume":" 4","scopus_import":"1","oa_version":"Submitted Version","abstract":[{"lang":"eng","text":"Organisms cope with change by taking advantage of transcriptional regulators. However, when faced with rare environments, the evolution of transcriptional regulators and their promoters may be too slow. Here, we investigate whether the intrinsic instability of gene duplication and amplification provides a generic alternative to canonical gene regulation. Using real-time monitoring of gene-copy-number mutations in Escherichia coli, we show that gene duplications and amplifications enable adaptation to fluctuating environments by rapidly generating copy-number and, therefore, expression-level polymorphisms. This amplification-mediated gene expression tuning (AMGET) occurs on timescales that are similar to canonical gene regulation and can respond to rapid environmental changes. Mathematical modelling shows that amplifications also tune gene expression in stochastic environments in which transcription-factor-based schemes are hard to evolve or maintain. The fleeting nature of gene amplifications gives rise to a generic population-level mechanism that relies on genetic heterogeneity to rapidly tune the expression of any gene, without leaving any genomic signature."}]},{"oa_version":"Preprint","abstract":[{"text":"There is increasing evidence that protein binding to specific sites along DNA can activate the reading out of genetic information without coming into direct physical contact with the gene. There also is evidence that these distant but interacting sites are embedded in a liquid droplet of proteins which condenses out of the surrounding solution. We argue that droplet-mediated interactions can account for crucial features of gene regulation only if the droplet is poised at a non-generic point in its phase diagram. We explore a minimal model that embodies this idea, show that this model has a natural mechanism for self-tuning, and suggest direct experimental tests. ","lang":"eng"}],"month":"12","oa":1,"main_file_link":[{"url":"https://arxiv.org/abs/1912.08579","open_access":"1"}],"publisher":"ArXiv","publication":"arXiv:1912.08579","language":[{"iso":"eng"}],"day":"18","year":"2019","publication_status":"submitted","date_created":"2020-02-28T10:57:08Z","date_published":"2019-12-18T00:00:00Z","page":"5","_id":"7552","status":"public","project":[{"call_identifier":"FWF","_id":"254E9036-B435-11E9-9278-68D0E5697425","grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation"}],"type":"preprint","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"chicago":"Bialek, William, Thomas Gregor, and Gašper Tkačik. “Action at a Distance in Transcriptional Regulation.” ArXiv:1912.08579. ArXiv, n.d.","ista":"Bialek W, Gregor T, Tkačik G. Action at a distance in transcriptional regulation. arXiv:1912.08579, .","mla":"Bialek, William, et al. “Action at a Distance in Transcriptional Regulation.” ArXiv:1912.08579, ArXiv.","apa":"Bialek, W., Gregor, T., & Tkačik, G. (n.d.). Action at a distance in transcriptional regulation. arXiv:1912.08579. ArXiv.","ama":"Bialek W, Gregor T, Tkačik G. Action at a distance in transcriptional regulation. arXiv:191208579.","ieee":"W. Bialek, T. Gregor, and G. Tkačik, “Action at a distance in transcriptional regulation,” arXiv:1912.08579. ArXiv.","short":"W. Bialek, T. Gregor, G. Tkačik, ArXiv:1912.08579 (n.d.)."},"date_updated":"2021-01-12T08:14:09Z","title":"Action at a distance in transcriptional regulation","department":[{"_id":"GaTk"}],"external_id":{"arxiv":["1912.08579"]},"article_processing_charge":"No","author":[{"first_name":"William","full_name":"Bialek, William","last_name":"Bialek"},{"first_name":"Thomas","full_name":"Gregor, Thomas","last_name":"Gregor"},{"full_name":"Tkačik, Gašper","orcid":"0000-0002-6699-1455","last_name":"Tkačik","first_name":"Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"}]},{"citation":{"ista":"Petkova MD, Tkačik G, Bialek W, Wieschaus EF, Gregor T. 2019. Optimal decoding of cellular identities in a genetic network. Cell. 176(4), 844–855.e15.","chicago":"Petkova, Mariela D., Gašper Tkačik, William Bialek, Eric F. Wieschaus, and Thomas Gregor. “Optimal Decoding of Cellular Identities in a Genetic Network.” Cell. Cell Press, 2019. https://doi.org/10.1016/j.cell.2019.01.007.","ama":"Petkova MD, Tkačik G, Bialek W, Wieschaus EF, Gregor T. Optimal decoding of cellular identities in a genetic network. Cell. 2019;176(4):844-855.e15. doi:10.1016/j.cell.2019.01.007","apa":"Petkova, M. D., Tkačik, G., Bialek, W., Wieschaus, E. F., & Gregor, T. (2019). Optimal decoding of cellular identities in a genetic network. Cell. Cell Press. https://doi.org/10.1016/j.cell.2019.01.007","ieee":"M. D. Petkova, G. Tkačik, W. Bialek, E. F. Wieschaus, and T. Gregor, “Optimal decoding of cellular identities in a genetic network,” Cell, vol. 176, no. 4. Cell Press, p. 844–855.e15, 2019.","short":"M.D. Petkova, G. Tkačik, W. Bialek, E.F. Wieschaus, T. Gregor, Cell 176 (2019) 844–855.e15.","mla":"Petkova, Mariela D., et al. “Optimal Decoding of Cellular Identities in a Genetic Network.” Cell, vol. 176, no. 4, Cell Press, 2019, p. 844–855.e15, doi:10.1016/j.cell.2019.01.007."},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","author":[{"last_name":"Petkova","full_name":"Petkova, Mariela D.","first_name":"Mariela D."},{"first_name":"Gasper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","full_name":"Tkacik, Gasper","last_name":"Tkacik"},{"full_name":"Bialek, William","last_name":"Bialek","first_name":"William"},{"full_name":"Wieschaus, Eric F.","last_name":"Wieschaus","first_name":"Eric F."},{"first_name":"Thomas","last_name":"Gregor","full_name":"Gregor, Thomas"}],"external_id":{"pmid":["30712870"],"isi":["000457969200015"]},"article_processing_charge":"No","title":"Optimal decoding of cellular identities in a genetic network","project":[{"name":"Biophysics of information processing in gene regulation","grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425","call_identifier":"FWF"}],"isi":1,"year":"2019","day":"07","publication":"Cell","page":"844-855.e15","doi":"10.1016/j.cell.2019.01.007","date_published":"2019-02-07T00:00:00Z","date_created":"2019-02-10T22:59:16Z","quality_controlled":"1","publisher":"Cell Press","oa":1,"date_updated":"2023-08-24T14:42:47Z","department":[{"_id":"GaTk"}],"_id":"5945","type":"journal_article","article_type":"original","status":"public","publication_status":"published","language":[{"iso":"eng"}],"related_material":{"link":[{"url":"https://ist.ac.at/en/news/cells-find-their-identity-using-a-mathematically-optimal-strategy/","relation":"press_release","description":"News on IST Homepage"}]},"volume":176,"issue":"4","abstract":[{"lang":"eng","text":"In developing organisms, spatially prescribed cell identities are thought to be determined by the expression levels of multiple genes. Quantitative tests of this idea, however, require a theoretical framework capable of exposing the rules and precision of cell specification over developmental time. We use the gap gene network in the early fly embryo as an example to show how expression levels of the four gap genes can be jointly decoded into an optimal specification of position with 1% accuracy. The decoder correctly predicts, with no free parameters, the dynamics of pair-rule expression patterns at different developmental time points and in various mutant backgrounds. Precise cellular identities are thus available at the earliest stages of development, contrasting the prevailing view of positional information being slowly refined across successive layers of the patterning network. Our results suggest that developmental enhancers closely approximate a mathematically optimal decoding strategy."}],"oa_version":"Published Version","pmid":1,"scopus_import":"1","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1016/j.cell.2019.01.007"}],"month":"02","intvolume":" 176"},{"abstract":[{"lang":"eng","text":"In this article it is shown that large systems with many interacting units endowing multiple phases display self-oscillations in the presence of linear feedback between the control and order parameters, where an Andronov–Hopf bifurcation takes over the phase transition. This is simply illustrated through the mean field Landau theory whose feedback dynamics turn out to be described by the Van der Pol equation and it is then validated for the fully connected Ising model following heat bath dynamics. Despite its simplicity, this theory accounts potentially for a rich range of phenomena: here it is applied to describe in a stylized way (i) excess demand-price cycles due to strong herding in a simple agent-based market model; (ii) congestion waves in queuing networks triggered by user feedback to delays in overloaded conditions; and (iii) metabolic network oscillations resulting from cell growth control in a bistable phenotypic landscape."}],"oa_version":"Published Version","scopus_import":"1","intvolume":" 52","month":"01","publication_status":"published","language":[{"iso":"eng"}],"file":[{"access_level":"open_access","relation":"main_file","content_type":"application/pdf","file_id":"6344","checksum":"1112304ad363a6d8afaeccece36473cf","creator":"kschuh","date_updated":"2020-07-14T12:47:17Z","file_size":1804557,"date_created":"2019-04-19T12:18:57Z","file_name":"2019_IOP_DeMartino.pdf"}],"ec_funded":1,"issue":"4","volume":52,"_id":"6049","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"type":"journal_article","status":"public","date_updated":"2023-08-24T14:49:23Z","ddc":["570"],"file_date_updated":"2020-07-14T12:47:17Z","department":[{"_id":"GaTk"}],"oa":1,"publisher":"IOP Publishing","quality_controlled":"1","year":"2019","isi":1,"has_accepted_license":"1","publication":"Journal of Physics A: Mathematical and Theoretical","day":"07","date_created":"2019-02-24T22:59:19Z","date_published":"2019-01-07T00:00:00Z","doi":"10.1088/1751-8121/aaf2dd","article_number":"045002","project":[{"call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","name":"International IST Postdoc Fellowship Programme"}],"citation":{"chicago":"De Martino, Daniele. “Feedback-Induced Self-Oscillations in Large Interacting Systems Subjected to Phase Transitions.” Journal of Physics A: Mathematical and Theoretical. IOP Publishing, 2019. https://doi.org/10.1088/1751-8121/aaf2dd.","ista":"De Martino D. 2019. Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. 52(4), 045002.","mla":"De Martino, Daniele. “Feedback-Induced Self-Oscillations in Large Interacting Systems Subjected to Phase Transitions.” Journal of Physics A: Mathematical and Theoretical, vol. 52, no. 4, 045002, IOP Publishing, 2019, doi:10.1088/1751-8121/aaf2dd.","ama":"De Martino D. Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. 2019;52(4). doi:10.1088/1751-8121/aaf2dd","apa":"De Martino, D. (2019). Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. IOP Publishing. https://doi.org/10.1088/1751-8121/aaf2dd","ieee":"D. De Martino, “Feedback-induced self-oscillations in large interacting systems subjected to phase transitions,” Journal of Physics A: Mathematical and Theoretical, vol. 52, no. 4. IOP Publishing, 2019.","short":"D. De Martino, Journal of Physics A: Mathematical and Theoretical 52 (2019)."},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","external_id":{"isi":["000455379500001"]},"article_processing_charge":"Yes (in subscription journal)","author":[{"orcid":"0000-0002-5214-4706","full_name":"De Martino, Daniele","last_name":"De Martino","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","first_name":"Daniele"}],"title":"Feedback-induced self-oscillations in large interacting systems subjected to phase transitions"},{"quality_controlled":"1","publisher":"Embo Press","oa":1,"isi":1,"year":"2019","day":"14","publication":"Molecular systems biology","doi":"10.15252/msb.20188470","date_published":"2019-02-14T00:00:00Z","date_created":"2019-02-24T22:59:18Z","article_number":"e8470","project":[{"call_identifier":"FWF","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","grant_number":"P27201-B22","name":"Revealing the mechanisms underlying drug interactions"},{"_id":"25EB3A80-B435-11E9-9278-68D0E5697425","grant_number":"RGP0042/2013","name":"Revealing the fundamental limits of cell growth"}],"citation":{"chicago":"Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Temporal Order and Precision of Complex Stress Responses in Individual Bacteria.” Molecular Systems Biology. Embo Press, 2019. https://doi.org/10.15252/msb.20188470.","ista":"Mitosch K, Rieckh G, Bollenbach MT. 2019. Temporal order and precision of complex stress responses in individual bacteria. Molecular systems biology. 15(2), e8470.","mla":"Mitosch, Karin, et al. “Temporal Order and Precision of Complex Stress Responses in Individual Bacteria.” Molecular Systems Biology, vol. 15, no. 2, e8470, Embo Press, 2019, doi:10.15252/msb.20188470.","ama":"Mitosch K, Rieckh G, Bollenbach MT. Temporal order and precision of complex stress responses in individual bacteria. Molecular systems biology. 2019;15(2). doi:10.15252/msb.20188470","apa":"Mitosch, K., Rieckh, G., & Bollenbach, M. T. (2019). Temporal order and precision of complex stress responses in individual bacteria. Molecular Systems Biology. Embo Press. https://doi.org/10.15252/msb.20188470","ieee":"K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Temporal order and precision of complex stress responses in individual bacteria,” Molecular systems biology, vol. 15, no. 2. Embo Press, 2019.","short":"K. Mitosch, G. Rieckh, M.T. Bollenbach, Molecular Systems Biology 15 (2019)."},"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","author":[{"last_name":"Mitosch","full_name":"Mitosch, Karin","id":"39B66846-F248-11E8-B48F-1D18A9856A87","first_name":"Karin"},{"full_name":"Rieckh, Georg","last_name":"Rieckh","id":"34DA8BD6-F248-11E8-B48F-1D18A9856A87","first_name":"Georg"},{"first_name":"Mark Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach","full_name":"Bollenbach, Mark Tobias","orcid":"0000-0003-4398-476X"}],"article_processing_charge":"No","external_id":{"isi":["000459628300003"],"pmid":["30765425"]},"title":"Temporal order and precision of complex stress responses in individual bacteria","abstract":[{"text":"Sudden stress often triggers diverse, temporally structured gene expression responses in microbes, but it is largely unknown how variable in time such responses are and if genes respond in the same temporal order in every single cell. Here, we quantified timing variability of individual promoters responding to sublethal antibiotic stress using fluorescent reporters, microfluidics, and time‐lapse microscopy. We identified lower and upper bounds that put definite constraints on timing variability, which varies strongly among promoters and conditions. Timing variability can be interpreted using results from statistical kinetics, which enable us to estimate the number of rate‐limiting molecular steps underlying different responses. We found that just a few critical steps control some responses while others rely on dozens of steps. To probe connections between different stress responses, we then tracked the temporal order and response time correlations of promoter pairs in individual cells. Our results support that, when bacteria are exposed to the antibiotic nitrofurantoin, the ensuing oxidative stress and SOS responses are part of the same causal chain of molecular events. In contrast, under trimethoprim, the acid stress response and the SOS response are part of different chains of events running in parallel. Our approach reveals fundamental constraints on gene expression timing and provides new insights into the molecular events that underlie the timing of stress responses.","lang":"eng"}],"acknowledged_ssus":[{"_id":"Bio"}],"oa_version":"Submitted Version","pmid":1,"scopus_import":"1","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pubmed/30765425","open_access":"1"}],"month":"02","intvolume":" 15","publication_status":"published","language":[{"iso":"eng"}],"issue":"2","volume":15,"_id":"6046","type":"journal_article","status":"public","date_updated":"2023-08-24T14:49:53Z","department":[{"_id":"GaTk"}]},{"quality_controlled":"1","publisher":"Public Library of Science","oa":1,"day":"02","publication":"PLoS Computational Biology","isi":1,"has_accepted_license":"1","year":"2019","doi":"10.1371/journal.pcbi.1007168","date_published":"2019-07-02T00:00:00Z","date_created":"2019-08-11T21:59:19Z","article_number":"e1007168","project":[{"_id":"251D65D8-B435-11E9-9278-68D0E5697425","name":"Effects of Stochasticity on the Function of Restriction-Modi cation Systems at the Single-Cell Level","grant_number":"24210"},{"grant_number":"RGY0079/2011","name":"Multi-Level Conflicts in Evolutionary Dynamics of Restriction-Modification Systems","_id":"251BCBEC-B435-11E9-9278-68D0E5697425"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","citation":{"short":"J. Ruess, M. Pleska, C.C. Guet, G. Tkačik, PLoS Computational Biology 15 (2019).","ieee":"J. Ruess, M. Pleska, C. C. Guet, and G. Tkačik, “Molecular noise of innate immunity shapes bacteria-phage ecologies,” PLoS Computational Biology, vol. 15, no. 7. Public Library of Science, 2019.","apa":"Ruess, J., Pleska, M., Guet, C. C., & Tkačik, G. (2019). Molecular noise of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007168","ama":"Ruess J, Pleska M, Guet CC, Tkačik G. Molecular noise of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology. 2019;15(7). doi:10.1371/journal.pcbi.1007168","mla":"Ruess, Jakob, et al. “Molecular Noise of Innate Immunity Shapes Bacteria-Phage Ecologies.” PLoS Computational Biology, vol. 15, no. 7, e1007168, Public Library of Science, 2019, doi:10.1371/journal.pcbi.1007168.","ista":"Ruess J, Pleska M, Guet CC, Tkačik G. 2019. Molecular noise of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology. 15(7), e1007168.","chicago":"Ruess, Jakob, Maros Pleska, Calin C Guet, and Gašper Tkačik. “Molecular Noise of Innate Immunity Shapes Bacteria-Phage Ecologies.” PLoS Computational Biology. Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007168."},"title":"Molecular noise of innate immunity shapes bacteria-phage ecologies","author":[{"last_name":"Ruess","orcid":"0000-0003-1615-3282","full_name":"Ruess, Jakob","id":"4A245D00-F248-11E8-B48F-1D18A9856A87","first_name":"Jakob"},{"last_name":"Pleska","orcid":"0000-0001-7460-7479","full_name":"Pleska, Maros","id":"4569785E-F248-11E8-B48F-1D18A9856A87","first_name":"Maros"},{"full_name":"Guet, Calin C","orcid":"0000-0001-6220-2052","last_name":"Guet","first_name":"Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper","last_name":"Tkačik","orcid":"0000-0002-6699-1455","full_name":"Tkačik, Gašper"}],"article_processing_charge":"No","external_id":{"isi":["000481577700032"]},"oa_version":"Published Version","abstract":[{"text":"Mathematical models have been used successfully at diverse scales of biological organization, ranging from ecology and population dynamics to stochastic reaction events occurring between individual molecules in single cells. Generally, many biological processes unfold across multiple scales, with mutations being the best studied example of how stochasticity at the molecular scale can influence outcomes at the population scale. In many other contexts, however, an analogous link between micro- and macro-scale remains elusive, primarily due to the challenges involved in setting up and analyzing multi-scale models. Here, we employ such a model to investigate how stochasticity propagates from individual biochemical reaction events in the bacterial innate immune system to the ecology of bacteria and bacterial viruses. We show analytically how the dynamics of bacterial populations are shaped by the activities of immunity-conferring enzymes in single cells and how the ecological consequences imply optimal bacterial defense strategies against viruses. Our results suggest that bacterial populations in the presence of viruses can either optimize their initial growth rate or their population size, with the first strategy favoring simple immunity featuring a single restriction modification system and the second strategy favoring complex bacterial innate immunity featuring several simultaneously active restriction modification systems.","lang":"eng"}],"month":"07","intvolume":" 15","scopus_import":"1","file":[{"content_type":"application/pdf","relation":"main_file","access_level":"open_access","file_id":"6803","checksum":"7ded4721b41c2a0fc66a1c634540416a","file_size":2200003,"date_updated":"2020-07-14T12:47:40Z","creator":"dernst","file_name":"2019_PlosComputBiology_Ruess.pdf","date_created":"2019-08-12T12:27:26Z"}],"language":[{"iso":"eng"}],"publication_identifier":{"eissn":["1553-7358"]},"publication_status":"published","issue":"7","volume":15,"related_material":{"record":[{"relation":"research_data","id":"9786","status":"public"}]},"_id":"6784","status":"public","type":"journal_article","article_type":"original","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"ddc":["570"],"date_updated":"2023-08-29T07:10:06Z","file_date_updated":"2020-07-14T12:47:40Z","department":[{"_id":"CaGu"},{"_id":"GaTk"}]},{"type":"research_data_reference","status":"public","_id":"9786","article_processing_charge":"No","author":[{"first_name":"Jakob","id":"4A245D00-F248-11E8-B48F-1D18A9856A87","last_name":"Ruess","orcid":"0000-0003-1615-3282","full_name":"Ruess, Jakob"},{"id":"4569785E-F248-11E8-B48F-1D18A9856A87","first_name":"Maros","last_name":"Pleska","orcid":"0000-0001-7460-7479","full_name":"Pleska, Maros"},{"full_name":"Guet, Calin C","orcid":"0000-0001-6220-2052","last_name":"Guet","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","first_name":"Calin C"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper","full_name":"Tkačik, Gašper","orcid":"0000-0002-6699-1455","last_name":"Tkačik"}],"title":"Supporting text and results","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"citation":{"mla":"Ruess, Jakob, et al. Supporting Text and Results. Public Library of Science, 2019, doi:10.1371/journal.pcbi.1007168.s001.","ama":"Ruess J, Pleska M, Guet CC, Tkačik G. Supporting text and results. 2019. doi:10.1371/journal.pcbi.1007168.s001","apa":"Ruess, J., Pleska, M., Guet, C. C., & Tkačik, G. (2019). Supporting text and results. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007168.s001","ieee":"J. Ruess, M. Pleska, C. C. Guet, and G. Tkačik, “Supporting text and results.” Public Library of Science, 2019.","short":"J. Ruess, M. Pleska, C.C. Guet, G. Tkačik, (2019).","chicago":"Ruess, Jakob, Maros Pleska, Calin C Guet, and Gašper Tkačik. “Supporting Text and Results.” Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007168.s001.","ista":"Ruess J, Pleska M, Guet CC, Tkačik G. 2019. Supporting text and results, Public Library of Science, 10.1371/journal.pcbi.1007168.s001."},"date_updated":"2023-08-29T07:10:05Z","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","publisher":"Public Library of Science","month":"07","oa_version":"Published Version","date_created":"2021-08-06T08:23:43Z","date_published":"2019-07-02T00:00:00Z","related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"6784"}]},"doi":"10.1371/journal.pcbi.1007168.s001","year":"2019","day":"02"},{"department":[{"_id":"GaTk"}],"date_updated":"2023-09-06T14:59:28Z","type":"journal_article","article_type":"original","status":"public","_id":"7422","volume":150,"issue":"5","publication_identifier":{"issn":["0021-9606"],"eissn":["1089-7690"]},"publication_status":"published","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://arxiv.org/abs/1708.09364","open_access":"1"}],"month":"02","intvolume":" 150","abstract":[{"lang":"eng","text":"Biochemical reactions often occur at low copy numbers but at once in crowded and diverse environments. Space and stochasticity therefore play an essential role in biochemical networks. Spatial-stochastic simulations have become a prominent tool for understanding how stochasticity at the microscopic level influences the macroscopic behavior of such systems. While particle-based models guarantee the level of detail necessary to accurately describe the microscopic dynamics at very low copy numbers, the algorithms used to simulate them typically imply trade-offs between computational efficiency and biochemical accuracy. eGFRD (enhanced Green’s Function Reaction Dynamics) is an exact algorithm that evades such trade-offs by partitioning the N-particle system into M ≤ N analytically tractable one- and two-particle systems; the analytical solutions (Green’s functions) then are used to implement an event-driven particle-based scheme that allows particles to make large jumps in time and space while retaining access to their state variables at arbitrary simulation times. Here we present “eGFRD2,” a new eGFRD version that implements the principle of eGFRD in all dimensions, thus enabling efficient particle-based simulation of biochemical reaction-diffusion processes in the 3D cytoplasm, on 2D planes representing membranes, and on 1D elongated cylinders representative of, e.g., cytoskeletal tracks or DNA; in 1D, it also incorporates convective motion used to model active transport. We find that, for low particle densities, eGFRD2 is up to 6 orders of magnitude faster than conventional Brownian dynamics. We exemplify the capabilities of eGFRD2 by simulating an idealized model of Pom1 gradient formation, which involves 3D diffusion, active transport on microtubules, and autophosphorylation on the membrane, confirming recent experimental and theoretical results on this system to hold under genuinely stochastic conditions."}],"oa_version":"Preprint","author":[{"orcid":"0000-0002-1287-3779","full_name":"Sokolowski, Thomas R","last_name":"Sokolowski","id":"3E999752-F248-11E8-B48F-1D18A9856A87","first_name":"Thomas R"},{"last_name":"Paijmans","full_name":"Paijmans, Joris","first_name":"Joris"},{"first_name":"Laurens","last_name":"Bossen","full_name":"Bossen, Laurens"},{"first_name":"Thomas","last_name":"Miedema","full_name":"Miedema, Thomas"},{"full_name":"Wehrens, Martijn","last_name":"Wehrens","first_name":"Martijn"},{"first_name":"Nils B.","full_name":"Becker, Nils B.","last_name":"Becker"},{"first_name":"Kazunari","full_name":"Kaizu, Kazunari","last_name":"Kaizu"},{"first_name":"Koichi","full_name":"Takahashi, Koichi","last_name":"Takahashi"},{"last_name":"Dogterom","full_name":"Dogterom, Marileen","first_name":"Marileen"},{"first_name":"Pieter Rein","full_name":"ten Wolde, Pieter Rein","last_name":"ten Wolde"}],"external_id":{"arxiv":["1708.09364"],"isi":["000458109300009"]},"article_processing_charge":"No","title":"eGFRD in all dimensions","citation":{"apa":"Sokolowski, T. R., Paijmans, J., Bossen, L., Miedema, T., Wehrens, M., Becker, N. B., … ten Wolde, P. R. (2019). eGFRD in all dimensions. The Journal of Chemical Physics. AIP Publishing. https://doi.org/10.1063/1.5064867","ama":"Sokolowski TR, Paijmans J, Bossen L, et al. eGFRD in all dimensions. The Journal of Chemical Physics. 2019;150(5). doi:10.1063/1.5064867","short":"T.R. Sokolowski, J. Paijmans, L. Bossen, T. Miedema, M. Wehrens, N.B. Becker, K. Kaizu, K. Takahashi, M. Dogterom, P.R. ten Wolde, The Journal of Chemical Physics 150 (2019).","ieee":"T. R. Sokolowski et al., “eGFRD in all dimensions,” The Journal of Chemical Physics, vol. 150, no. 5. AIP Publishing, 2019.","mla":"Sokolowski, Thomas R., et al. “EGFRD in All Dimensions.” The Journal of Chemical Physics, vol. 150, no. 5, 054108, AIP Publishing, 2019, doi:10.1063/1.5064867.","ista":"Sokolowski TR, Paijmans J, Bossen L, Miedema T, Wehrens M, Becker NB, Kaizu K, Takahashi K, Dogterom M, ten Wolde PR. 2019. eGFRD in all dimensions. The Journal of Chemical Physics. 150(5), 054108.","chicago":"Sokolowski, Thomas R, Joris Paijmans, Laurens Bossen, Thomas Miedema, Martijn Wehrens, Nils B. Becker, Kazunari Kaizu, Koichi Takahashi, Marileen Dogterom, and Pieter Rein ten Wolde. “EGFRD in All Dimensions.” The Journal of Chemical Physics. AIP Publishing, 2019. https://doi.org/10.1063/1.5064867."},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","article_number":"054108","doi":"10.1063/1.5064867","date_published":"2019-02-07T00:00:00Z","date_created":"2020-01-30T10:34:36Z","isi":1,"year":"2019","day":"07","publication":"The Journal of Chemical Physics","publisher":"AIP Publishing","quality_controlled":"1","oa":1},{"department":[{"_id":"GaTk"}],"file_date_updated":"2020-07-14T12:47:44Z","ddc":["570"],"date_updated":"2023-09-07T12:55:21Z","status":"public","type":"journal_article","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"_id":"6900","volume":15,"issue":"9","related_material":{"record":[{"relation":"part_of_dissertation","id":"6473","status":"public"}]},"file":[{"date_updated":"2020-07-14T12:47:44Z","file_size":3081855,"creator":"kschuh","date_created":"2019-10-01T10:53:45Z","file_name":"2019_PLoS_Cepeda-Humerez.pdf","content_type":"application/pdf","access_level":"open_access","relation":"main_file","file_id":"6925","checksum":"81bdce1361c9aa8395d6fa635fb6ab47"}],"language":[{"iso":"eng"}],"publication_identifier":{"eissn":["15537358"]},"publication_status":"published","month":"09","intvolume":" 15","scopus_import":"1","pmid":1,"oa_version":"Published Version","abstract":[{"text":"Across diverse biological systems—ranging from neural networks to intracellular signaling and genetic regulatory networks—the information about changes in the environment is frequently encoded in the full temporal dynamics of the network nodes. A pressing data-analysis challenge has thus been to efficiently estimate the amount of information that these dynamics convey from experimental data. Here we develop and evaluate decoding-based estimation methods to lower bound the mutual information about a finite set of inputs, encoded in single-cell high-dimensional time series data. For biological reaction networks governed by the chemical Master equation, we derive model-based information approximations and analytical upper bounds, against which we benchmark our proposed model-free decoding estimators. In contrast to the frequently-used k-nearest-neighbor estimator, decoding-based estimators robustly extract a large fraction of the available information from high-dimensional trajectories with a realistic number of data samples. We apply these estimators to previously published data on Erk and Ca2+ signaling in mammalian cells and to yeast stress-response, and find that substantial amount of information about environmental state can be encoded by non-trivial response statistics even in stationary signals. We argue that these single-cell, decoding-based information estimates, rather than the commonly-used tests for significant differences between selected population response statistics, provide a proper and unbiased measure for the performance of biological signaling networks.","lang":"eng"}],"title":"Estimating information in time-varying signals","author":[{"last_name":"Cepeda Humerez","full_name":"Cepeda Humerez, Sarah A","first_name":"Sarah A","id":"3DEE19A4-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Jakob","orcid":"0000-0003-1615-3282","full_name":"Ruess, Jakob","last_name":"Ruess"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper","orcid":"0000-0002-6699-1455","full_name":"Tkačik, Gašper","last_name":"Tkačik"}],"external_id":{"isi":["000489741800021"],"pmid":["31479447"]},"article_processing_charge":"No","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","citation":{"mla":"Cepeda Humerez, Sarah A., et al. “Estimating Information in Time-Varying Signals.” PLoS Computational Biology, vol. 15, no. 9, Public Library of Science, 2019, p. e1007290, doi:10.1371/journal.pcbi.1007290.","ieee":"S. A. Cepeda Humerez, J. Ruess, and G. Tkačik, “Estimating information in time-varying signals,” PLoS computational biology, vol. 15, no. 9. Public Library of Science, p. e1007290, 2019.","short":"S.A. Cepeda Humerez, J. Ruess, G. Tkačik, PLoS Computational Biology 15 (2019) e1007290.","apa":"Cepeda Humerez, S. A., Ruess, J., & Tkačik, G. (2019). Estimating information in time-varying signals. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007290","ama":"Cepeda Humerez SA, Ruess J, Tkačik G. Estimating information in time-varying signals. PLoS computational biology. 2019;15(9):e1007290. doi:10.1371/journal.pcbi.1007290","chicago":"Cepeda Humerez, Sarah A, Jakob Ruess, and Gašper Tkačik. “Estimating Information in Time-Varying Signals.” PLoS Computational Biology. Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007290.","ista":"Cepeda Humerez SA, Ruess J, Tkačik G. 2019. Estimating information in time-varying signals. PLoS computational biology. 15(9), e1007290."},"project":[{"_id":"254E9036-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation"}],"doi":"10.1371/journal.pcbi.1007290","date_published":"2019-09-03T00:00:00Z","date_created":"2019-09-22T22:00:37Z","page":"e1007290","day":"03","publication":"PLoS computational biology","has_accepted_license":"1","isi":1,"year":"2019","quality_controlled":"1","publisher":"Public Library of Science","oa":1},{"acknowledgement":"M.L. is grateful to the members of the C Guet and G Tkacik groups for valuable comments and support. M.S. is grateful to Nikita Kalinin for inspiring communications.\r\n","oa":1,"quality_controlled":"1","publisher":"National Academy of Sciences","publication":"Proceedings of the National Academy of Sciences","day":"19","year":"2019","isi":1,"date_created":"2018-12-11T11:45:08Z","doi":"10.1073/pnas.1812015116","date_published":"2019-02-19T00:00:00Z","page":"2821-2830","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"ista":"Lang M, Shkolnikov M. 2019. Harmonic dynamics of the Abelian sandpile. Proceedings of the National Academy of Sciences. 116(8), 2821–2830.","chicago":"Lang, Moritz, and Mikhail Shkolnikov. “Harmonic Dynamics of the Abelian Sandpile.” Proceedings of the National Academy of Sciences. National Academy of Sciences, 2019. https://doi.org/10.1073/pnas.1812015116.","apa":"Lang, M., & Shkolnikov, M. (2019). Harmonic dynamics of the Abelian sandpile. Proceedings of the National Academy of Sciences. National Academy of Sciences. https://doi.org/10.1073/pnas.1812015116","ama":"Lang M, Shkolnikov M. Harmonic dynamics of the Abelian sandpile. Proceedings of the National Academy of Sciences. 2019;116(8):2821-2830. doi:10.1073/pnas.1812015116","ieee":"M. Lang and M. Shkolnikov, “Harmonic dynamics of the Abelian sandpile,” Proceedings of the National Academy of Sciences, vol. 116, no. 8. National Academy of Sciences, pp. 2821–2830, 2019.","short":"M. Lang, M. Shkolnikov, Proceedings of the National Academy of Sciences 116 (2019) 2821–2830.","mla":"Lang, Moritz, and Mikhail Shkolnikov. “Harmonic Dynamics of the Abelian Sandpile.” Proceedings of the National Academy of Sciences, vol. 116, no. 8, National Academy of Sciences, 2019, pp. 2821–30, doi:10.1073/pnas.1812015116."},"title":"Harmonic dynamics of the Abelian sandpile","article_processing_charge":"No","external_id":{"isi":["000459074400013"],"pmid":[" 30728300"],"arxiv":["1806.10823"]},"author":[{"first_name":"Moritz","id":"29E0800A-F248-11E8-B48F-1D18A9856A87","full_name":"Lang, Moritz","last_name":"Lang"},{"last_name":"Shkolnikov","full_name":"Shkolnikov, Mikhail","orcid":"0000-0002-4310-178X","first_name":"Mikhail","id":"35084A62-F248-11E8-B48F-1D18A9856A87"}],"oa_version":"Published Version","pmid":1,"abstract":[{"lang":"eng","text":"The abelian sandpile serves as a model to study self-organized criticality, a phenomenon occurring in biological, physical and social processes. The identity of the abelian group is a fractal composed of self-similar patches, and its limit is subject of extensive collaborative research. Here, we analyze the evolution of the sandpile identity under harmonic fields of different orders. We show that this evolution corresponds to periodic cycles through the abelian group characterized by the smooth transformation and apparent conservation of the patches constituting the identity. The dynamics induced by second and third order harmonics resemble smooth stretchings, respectively translations, of the identity, while the ones induced by fourth order harmonics resemble magnifications and rotations. Starting with order three, the dynamics pass through extended regions of seemingly random configurations which spontaneously reassemble into accentuated patterns. We show that the space of harmonic functions projects to the extended analogue of the sandpile group, thus providing a set of universal coordinates identifying configurations between different domains. Since the original sandpile group is a subgroup of the extended one, this directly implies that it admits a natural renormalization. Furthermore, we show that the harmonic fields can be induced by simple Markov processes, and that the corresponding stochastic dynamics show remarkable robustness over hundreds of periods. Finally, we encode information into seemingly random configurations, and decode this information with an algorithm requiring minimal prior knowledge. Our results suggest that harmonic fields might split the sandpile group into sub-sets showing different critical coefficients, and that it might be possible to extend the fractal structure of the identity beyond the boundaries of its domain. "}],"intvolume":" 116","month":"02","main_file_link":[{"url":"https://doi.org/10.1073/pnas.1812015116","open_access":"1"}],"scopus_import":"1","language":[{"iso":"eng"}],"publication_status":"published","publication_identifier":{"eissn":["1091-6490"]},"related_material":{"link":[{"description":"News on IST Webpage","relation":"press_release","url":"https://ist.ac.at/en/news/famous-sandpile-model-shown-to-move-like-a-traveling-sand-dune/"}]},"issue":"8","volume":116,"_id":"196","status":"public","article_type":"original","type":"journal_article","date_updated":"2023-09-11T14:09:34Z","department":[{"_id":"CaGu"},{"_id":"GaTk"},{"_id":"TaHa"}]},{"file":[{"relation":"main_file","access_level":"open_access","content_type":"application/pdf","success":1,"checksum":"614c337d6424ccd3d48d1b1f9513510d","file_id":"8641","creator":"bkavcic","file_size":5370762,"date_updated":"2020-10-09T11:00:05Z","file_name":"lmt_sftmtr_V8.pdf","date_created":"2020-10-09T11:00:05Z"}],"language":[{"iso":"eng"}],"publication_identifier":{"issn":["1744-683X"],"eissn":["1744-6848"]},"publication_status":"published","volume":15,"issue":"4","license":"https://creativecommons.org/licenses/by-nc-nd/3.0/","oa_version":"Submitted Version","pmid":1,"abstract":[{"text":"We theoretically study the shapes of lipid vesicles confined to a spherical cavity, elaborating a framework based on the so-called limiting shapes constructed from geometrically simple structural elements such as double-membrane walls and edges. Partly inspired by numerical results, the proposed non-compartmentalized and compartmentalized limiting shapes are arranged in the bilayer-couple phase diagram which is then compared to its free-vesicle counterpart. We also compute the area-difference-elasticity phase diagram of the limiting shapes and we use it to interpret shape transitions experimentally observed in vesicles confined within another vesicle. The limiting-shape framework may be generalized to theoretically investigate the structure of certain cell organelles such as the mitochondrion.","lang":"eng"}],"month":"01","intvolume":" 15","scopus_import":"1","ddc":["530"],"date_updated":"2023-09-13T08:47:16Z","department":[{"_id":"GaTk"}],"file_date_updated":"2020-10-09T11:00:05Z","_id":"5817","status":"public","article_type":"original","type":"journal_article","tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)","image":"/images/cc_by_nc_nd.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode","short":"CC BY-NC-ND (3.0)"},"day":"10","publication":"Soft Matter","isi":1,"has_accepted_license":"1","year":"2019","date_published":"2019-01-10T00:00:00Z","doi":"10.1039/c8sm01956h","date_created":"2019-01-11T07:37:47Z","page":"602-614","publisher":"Royal Society of Chemistry","quality_controlled":"1","oa":1,"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"mla":"Kavcic, Bor, et al. “Limiting Shapes of Confined Lipid Vesicles.” Soft Matter, vol. 15, no. 4, Royal Society of Chemistry, 2019, pp. 602–14, doi:10.1039/c8sm01956h.","short":"B. Kavcic, A. Sakashita, H. Noguchi, P. Ziherl, Soft Matter 15 (2019) 602–614.","ieee":"B. Kavcic, A. Sakashita, H. Noguchi, and P. Ziherl, “Limiting shapes of confined lipid vesicles,” Soft Matter, vol. 15, no. 4. Royal Society of Chemistry, pp. 602–614, 2019.","ama":"Kavcic B, Sakashita A, Noguchi H, Ziherl P. Limiting shapes of confined lipid vesicles. Soft Matter. 2019;15(4):602-614. doi:10.1039/c8sm01956h","apa":"Kavcic, B., Sakashita, A., Noguchi, H., & Ziherl, P. (2019). Limiting shapes of confined lipid vesicles. Soft Matter. Royal Society of Chemistry. https://doi.org/10.1039/c8sm01956h","chicago":"Kavcic, Bor, A. Sakashita, H. Noguchi, and P. Ziherl. “Limiting Shapes of Confined Lipid Vesicles.” Soft Matter. Royal Society of Chemistry, 2019. https://doi.org/10.1039/c8sm01956h.","ista":"Kavcic B, Sakashita A, Noguchi H, Ziherl P. 2019. Limiting shapes of confined lipid vesicles. Soft Matter. 15(4), 602–614."},"title":"Limiting shapes of confined lipid vesicles","author":[{"full_name":"Kavcic, Bor","orcid":"0000-0001-6041-254X","last_name":"Kavcic","first_name":"Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87"},{"first_name":"A.","last_name":"Sakashita","full_name":"Sakashita, A."},{"first_name":"H.","last_name":"Noguchi","full_name":"Noguchi, H."},{"last_name":"Ziherl","full_name":"Ziherl, P.","first_name":"P."}],"article_processing_charge":"No","external_id":{"isi":["000457329700003"],"pmid":["30629082"]}},{"title":"Estimating information flow in single cells","article_processing_charge":"No","author":[{"id":"3DEE19A4-F248-11E8-B48F-1D18A9856A87","first_name":"Sarah A","full_name":"Cepeda Humerez, Sarah A","last_name":"Cepeda Humerez"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"chicago":"Cepeda Humerez, Sarah A. “Estimating Information Flow in Single Cells.” Institute of Science and Technology Austria, 2019. https://doi.org/10.15479/AT:ISTA:6473.","ista":"Cepeda Humerez SA. 2019. Estimating information flow in single cells. Institute of Science and Technology Austria.","mla":"Cepeda Humerez, Sarah A. Estimating Information Flow in Single Cells. Institute of Science and Technology Austria, 2019, doi:10.15479/AT:ISTA:6473.","apa":"Cepeda Humerez, S. A. (2019). Estimating information flow in single cells. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:6473","ama":"Cepeda Humerez SA. Estimating information flow in single cells. 2019. doi:10.15479/AT:ISTA:6473","ieee":"S. A. Cepeda Humerez, “Estimating information flow in single cells,” Institute of Science and Technology Austria, 2019.","short":"S.A. Cepeda Humerez, Estimating Information Flow in Single Cells, Institute of Science and Technology Austria, 2019."},"date_created":"2019-05-21T00:11:23Z","doi":"10.15479/AT:ISTA:6473","date_published":"2019-05-23T00:00:00Z","page":"135","day":"23","year":"2019","has_accepted_license":"1","oa":1,"publisher":"Institute of Science and Technology Austria","department":[{"_id":"GaTk"}],"file_date_updated":"2020-07-14T12:47:31Z","ddc":["004"],"date_updated":"2023-09-19T15:13:26Z","supervisor":[{"last_name":"Tkačik","full_name":"Tkačik, Gašper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper"}],"keyword":["Information estimation","Time-series","data analysis"],"status":"public","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"type":"dissertation","_id":"6473","related_material":{"record":[{"relation":"dissertation_contains","id":"1576","status":"public"},{"status":"public","id":"6900","relation":"dissertation_contains"},{"relation":"dissertation_contains","id":"281","status":"public"},{"relation":"dissertation_contains","id":"2016","status":"public"}]},"language":[{"iso":"eng"}],"file":[{"checksum":"75f9184c1346e10a5de5f9cc7338309a","file_id":"6480","access_level":"closed","relation":"source_file","content_type":"application/zip","date_created":"2019-05-23T11:18:16Z","file_name":"Thesis_Cepeda.zip","creator":"scepeda","date_updated":"2020-07-14T12:47:31Z","file_size":23937464},{"file_size":16646985,"date_updated":"2020-07-14T12:47:31Z","creator":"scepeda","file_name":"CepedaThesis.pdf","date_created":"2019-05-23T11:18:13Z","content_type":"application/pdf","relation":"main_file","access_level":"open_access","file_id":"6481","checksum":"afdc0633ddbd71d5b13550d7fb4f4454"}],"degree_awarded":"PhD","publication_status":"published","publication_identifier":{"issn":["2663-337X"]},"month":"05","alternative_title":["ISTA Thesis"],"oa_version":"Published Version","abstract":[{"text":"Single cells are constantly interacting with their environment and each other, more importantly, the accurate perception of environmental cues is crucial for growth, survival, and reproduction. This communication between cells and their environment can be formalized in mathematical terms and be quantified as the information flow between them, as prescribed by information theory. \r\nThe recent availability of real–time dynamical patterns of signaling molecules in single cells has allowed us to identify encoding about the identity of the environment in the time–series. However, efficient estimation of the information transmitted by these signals has been a data–analysis challenge due to the high dimensionality of the trajectories and the limited number of samples. In the first part of this thesis, we develop and evaluate decoding–based estimation methods to lower bound the mutual information and derive model–based precise information estimates for biological reaction networks governed by the chemical master equation. This is followed by applying the decoding-based methods to study the intracellular representation of extracellular changes in budding yeast, by observing the transient dynamics of nuclear translocation of 10 transcription factors in response to 3 stress conditions. Additionally, we apply these estimators to previously published data on ERK and Ca2+ signaling and yeast stress response. We argue that this single cell decoding-based measure of information provides an unbiased, quantitative and interpretable measure for the fidelity of biological signaling processes. \r\nFinally, in the last section, we deal with gene regulation which is primarily controlled by transcription factors (TFs) that bind to the DNA to activate gene expression. The possibility that non-cognate TFs activate transcription diminishes the accuracy of regulation with potentially disastrous effects for the cell. This ’crosstalk’ acts as a previously unexplored source of noise in biochemical networks and puts a strong constraint on their performance. To mitigate erroneous initiation we propose an out of equilibrium scheme that implements kinetic proofreading. We show that such architectures are favored over their equilibrium counterparts for complex organisms despite introducing noise in gene expression. ","lang":"eng"}]}]