[{"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","_id":"7490","title":"Evolutionarily unique mechanistic framework of clathrin-mediated endocytosis in plants","ddc":["570","580"],"status":"public","intvolume":" 9","file":[{"checksum":"2052daa4be5019534f3a42f200a09f32","date_updated":"2020-07-14T12:47:59Z","date_created":"2020-02-18T07:21:16Z","file_id":"7494","relation":"main_file","creator":"dernst","file_size":7247468,"content_type":"application/pdf","access_level":"open_access","file_name":"2020_eLife_Narasimhan.pdf"}],"oa_version":"Published Version","type":"journal_article","abstract":[{"text":"In plants, clathrin mediated endocytosis (CME) represents the major route for cargo internalisation from the cell surface. It has been assumed to operate in an evolutionary conserved manner as in yeast and animals. Here we report characterisation of ultrastructure, dynamics and mechanisms of plant CME as allowed by our advancement in electron microscopy and quantitative live imaging techniques. Arabidopsis CME appears to follow the constant curvature model and the bona fide CME population generates vesicles of a predominantly hexagonal-basket type; larger and with faster kinetics than in other models. Contrary to the existing paradigm, actin is dispensable for CME events at the plasma membrane but plays a unique role in collecting endocytic vesicles, sorting of internalised cargos and directional endosome movement that itself actively promote CME events. Internalized vesicles display a strongly delayed and sequential uncoating. These unique features highlight the independent evolution of the plant CME mechanism during the autonomous rise of multicellularity in eukaryotes.","lang":"eng"}],"publication":"eLife","citation":{"chicago":"Narasimhan, Madhumitha, Alexander J Johnson, Roshan Prizak, Walter Kaufmann, Shutang Tan, Barbara E Casillas Perez, and Jiří Friml. “Evolutionarily Unique Mechanistic Framework of Clathrin-Mediated Endocytosis in Plants.” ELife. eLife Sciences Publications, 2020. https://doi.org/10.7554/eLife.52067.","short":"M. Narasimhan, A.J. Johnson, R. Prizak, W. Kaufmann, S. Tan, B.E. Casillas Perez, J. Friml, ELife 9 (2020).","mla":"Narasimhan, Madhumitha, et al. “Evolutionarily Unique Mechanistic Framework of Clathrin-Mediated Endocytosis in Plants.” ELife, vol. 9, e52067, eLife Sciences Publications, 2020, doi:10.7554/eLife.52067.","ieee":"M. Narasimhan et al., “Evolutionarily unique mechanistic framework of clathrin-mediated endocytosis in plants,” eLife, vol. 9. eLife Sciences Publications, 2020.","apa":"Narasimhan, M., Johnson, A. J., Prizak, R., Kaufmann, W., Tan, S., Casillas Perez, B. E., & Friml, J. (2020). Evolutionarily unique mechanistic framework of clathrin-mediated endocytosis in plants. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.52067","ista":"Narasimhan M, Johnson AJ, Prizak R, Kaufmann W, Tan S, Casillas Perez BE, Friml J. 2020. Evolutionarily unique mechanistic framework of clathrin-mediated endocytosis in plants. eLife. 9, e52067.","ama":"Narasimhan M, Johnson AJ, Prizak R, et al. Evolutionarily unique mechanistic framework of clathrin-mediated endocytosis in plants. eLife. 2020;9. doi:10.7554/eLife.52067"},"article_type":"original","date_published":"2020-01-23T00:00:00Z","scopus_import":"1","day":"23","article_processing_charge":"No","has_accepted_license":"1","year":"2020","pmid":1,"publication_status":"published","department":[{"_id":"JiFr"},{"_id":"GaTk"},{"_id":"EM-Fac"},{"_id":"SyCr"}],"publisher":"eLife Sciences Publications","author":[{"full_name":"Narasimhan, Madhumitha","orcid":"0000-0002-8600-0671","id":"44BF24D0-F248-11E8-B48F-1D18A9856A87","last_name":"Narasimhan","first_name":"Madhumitha"},{"full_name":"Johnson, Alexander J","last_name":"Johnson","first_name":"Alexander J","orcid":"0000-0002-2739-8843","id":"46A62C3A-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Prizak, Roshan","last_name":"Prizak","first_name":"Roshan","id":"4456104E-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Walter","last_name":"Kaufmann","id":"3F99E422-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9735-5315","full_name":"Kaufmann, Walter"},{"orcid":"0000-0002-0471-8285","id":"2DE75584-F248-11E8-B48F-1D18A9856A87","last_name":"Tan","first_name":"Shutang","full_name":"Tan, Shutang"},{"last_name":"Casillas Perez","first_name":"Barbara E","id":"351ED2AA-F248-11E8-B48F-1D18A9856A87","full_name":"Casillas Perez, Barbara E"},{"full_name":"Friml, Jiří","first_name":"Jiří","last_name":"Friml","id":"4159519E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8302-7596"}],"date_created":"2020-02-16T23:00:50Z","date_updated":"2023-08-18T06:33:07Z","volume":9,"article_number":"e52067","file_date_updated":"2020-07-14T12:47:59Z","ec_funded":1,"external_id":{"pmid":["31971511"],"isi":["000514104100001"]},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"isi":1,"quality_controlled":"1","project":[{"call_identifier":"H2020","name":"Tracing Evolution of Auxin Transport and Polarity in Plants","_id":"261099A6-B435-11E9-9278-68D0E5697425","grant_number":"742985"},{"call_identifier":"FWF","name":"Molecular mechanisms of endocytic cargo recognition in plants","grant_number":"I03630","_id":"26538374-B435-11E9-9278-68D0E5697425"}],"doi":"10.7554/eLife.52067","acknowledged_ssus":[{"_id":"LifeSc"},{"_id":"Bio"},{"_id":"EM-Fac"}],"language":[{"iso":"eng"}],"month":"01","publication_identifier":{"eissn":["2050-084X"]}},{"month":"02","day":"25","article_processing_charge":"No","doi":"10.1371/journal.pcbi.1007642.s003","date_published":"2020-02-25T00:00:00Z","citation":{"ama":"Grah R, Friedlander T. Distribution of crosstalk values. 2020. doi:10.1371/journal.pcbi.1007642.s003","ista":"Grah R, Friedlander T. 2020. Distribution of crosstalk values, Public Library of Science, 10.1371/journal.pcbi.1007642.s003.","ieee":"R. Grah and T. Friedlander, “Distribution of crosstalk values.” Public Library of Science, 2020.","apa":"Grah, R., & Friedlander, T. (2020). Distribution of crosstalk values. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007642.s003","mla":"Grah, Rok, and Tamar Friedlander. Distribution of Crosstalk Values. Public Library of Science, 2020, doi:10.1371/journal.pcbi.1007642.s003.","short":"R. Grah, T. Friedlander, (2020).","chicago":"Grah, Rok, and Tamar Friedlander. “Distribution of Crosstalk Values.” Public Library of Science, 2020. https://doi.org/10.1371/journal.pcbi.1007642.s003."},"type":"research_data_reference","author":[{"full_name":"Grah, Rok","id":"483E70DE-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2539-3560","first_name":"Rok","last_name":"Grah"},{"first_name":"Tamar","last_name":"Friedlander","full_name":"Friedlander, Tamar"}],"related_material":{"record":[{"id":"7569","relation":"research_data","status":"public"}]},"date_updated":"2023-08-18T06:47:47Z","date_created":"2021-08-06T07:24:37Z","oa_version":"Published Version","year":"2020","_id":"9779","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","title":"Distribution of crosstalk values","status":"public","publisher":"Public Library of Science","department":[{"_id":"GaTk"}]},{"type":"research_data_reference","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","_id":"9776","year":"2020","title":"Supporting information","status":"public","publisher":"Public Library of Science","department":[{"_id":"GaTk"}],"author":[{"full_name":"Grah, Rok","orcid":"0000-0003-2539-3560","id":"483E70DE-F248-11E8-B48F-1D18A9856A87","last_name":"Grah","first_name":"Rok"},{"full_name":"Friedlander, Tamar","last_name":"Friedlander","first_name":"Tamar"}],"related_material":{"record":[{"status":"public","relation":"used_in_publication","id":"7569"}]},"date_created":"2021-08-06T07:15:04Z","date_updated":"2023-08-18T06:47:47Z","oa_version":"Published Version","day":"25","month":"02","article_processing_charge":"No","citation":{"ista":"Grah R, Friedlander T. 2020. Supporting information, Public Library of Science, 10.1371/journal.pcbi.1007642.s001.","apa":"Grah, R., & Friedlander, T. (2020). Supporting information. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007642.s001","ieee":"R. Grah and T. Friedlander, “Supporting information.” Public Library of Science, 2020.","ama":"Grah R, Friedlander T. Supporting information. 2020. doi:10.1371/journal.pcbi.1007642.s001","chicago":"Grah, Rok, and Tamar Friedlander. “Supporting Information.” Public Library of Science, 2020. https://doi.org/10.1371/journal.pcbi.1007642.s001.","mla":"Grah, Rok, and Tamar Friedlander. Supporting Information. Public Library of Science, 2020, doi:10.1371/journal.pcbi.1007642.s001.","short":"R. Grah, T. Friedlander, (2020)."},"date_published":"2020-02-25T00:00:00Z","doi":"10.1371/journal.pcbi.1007642.s001"},{"_id":"7656","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","intvolume":" 14","status":"public","ddc":["570"],"title":"Clustering of neural activity: A design principle for population codes","file":[{"file_name":"2020_Frontiers_Berry.pdf","access_level":"open_access","file_size":4082937,"content_type":"application/pdf","creator":"dernst","relation":"main_file","file_id":"7659","date_updated":"2020-07-14T12:48:01Z","date_created":"2020-04-14T12:20:39Z","checksum":"2b1da23823eae9cedbb42d701945b61e"}],"oa_version":"Published Version","type":"journal_article","abstract":[{"lang":"eng","text":"We propose that correlations among neurons are generically strong enough to organize neural activity patterns into a discrete set of clusters, which can each be viewed as a population codeword. Our reasoning starts with the analysis of retinal ganglion cell data using maximum entropy models, showing that the population is robustly in a frustrated, marginally sub-critical, or glassy, state. This leads to an argument that neural populations in many other brain areas might share this structure. Next, we use latent variable models to show that this glassy state possesses well-defined clusters of neural activity. Clusters have three appealing properties: (i) clusters exhibit error correction, i.e., they are reproducibly elicited by the same stimulus despite variability at the level of constituent neurons; (ii) clusters encode qualitatively different visual features than their constituent neurons; and (iii) clusters can be learned by downstream neural circuits in an unsupervised fashion. We hypothesize that these properties give rise to a “learnable” neural code which the cortical hierarchy uses to extract increasingly complex features without supervision or reinforcement."}],"citation":{"chicago":"Berry, Michael J., and Gašper Tkačik. “Clustering of Neural Activity: A Design Principle for Population Codes.” Frontiers in Computational Neuroscience. Frontiers, 2020. https://doi.org/10.3389/fncom.2020.00020.","mla":"Berry, Michael J., and Gašper Tkačik. “Clustering of Neural Activity: A Design Principle for Population Codes.” Frontiers in Computational Neuroscience, vol. 14, 20, Frontiers, 2020, doi:10.3389/fncom.2020.00020.","short":"M.J. Berry, G. Tkačik, Frontiers in Computational Neuroscience 14 (2020).","ista":"Berry MJ, Tkačik G. 2020. Clustering of neural activity: A design principle for population codes. Frontiers in Computational Neuroscience. 14, 20.","apa":"Berry, M. J., & Tkačik, G. (2020). Clustering of neural activity: A design principle for population codes. Frontiers in Computational Neuroscience. Frontiers. https://doi.org/10.3389/fncom.2020.00020","ieee":"M. J. Berry and G. Tkačik, “Clustering of neural activity: A design principle for population codes,” Frontiers in Computational Neuroscience, vol. 14. Frontiers, 2020.","ama":"Berry MJ, Tkačik G. Clustering of neural activity: A design principle for population codes. Frontiers in Computational Neuroscience. 2020;14. doi:10.3389/fncom.2020.00020"},"publication":"Frontiers in Computational Neuroscience","article_type":"original","date_published":"2020-03-13T00:00:00Z","scopus_import":"1","has_accepted_license":"1","article_processing_charge":"No","day":"13","pmid":1,"year":"2020","department":[{"_id":"GaTk"}],"publisher":"Frontiers","publication_status":"published","author":[{"last_name":"Berry","first_name":"Michael J.","full_name":"Berry, Michael J."},{"full_name":"Tkačik, Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gašper","last_name":"Tkačik"}],"volume":14,"date_updated":"2023-08-18T10:30:11Z","date_created":"2020-04-12T22:00:40Z","article_number":"20","file_date_updated":"2020-07-14T12:48:01Z","oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"external_id":{"isi":["000525543200001"],"pmid":["32231528"]},"quality_controlled":"1","isi":1,"doi":"10.3389/fncom.2020.00020","language":[{"iso":"eng"}],"publication_identifier":{"eissn":["16625188"]},"month":"03"},{"scopus_import":"1","day":"06","has_accepted_license":"1","article_processing_charge":"No","publication":"Proceedings of the National Academy of Sciences of the United States of America","citation":{"mla":"Maoz, Ori, et al. “Learning Probabilistic Neural Representations with Randomly Connected Circuits.” Proceedings of the National Academy of Sciences of the United States of America, vol. 117, no. 40, National Academy of Sciences, 2020, pp. 25066–73, doi:10.1073/pnas.1912804117.","short":"O. Maoz, G. Tkačik, M.S. Esteki, R. Kiani, E. Schneidman, Proceedings of the National Academy of Sciences of the United States of America 117 (2020) 25066–25073.","chicago":"Maoz, Ori, Gašper Tkačik, Mohamad Saleh Esteki, Roozbeh Kiani, and Elad Schneidman. “Learning Probabilistic Neural Representations with Randomly Connected Circuits.” Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences, 2020. https://doi.org/10.1073/pnas.1912804117.","ama":"Maoz O, Tkačik G, Esteki MS, Kiani R, Schneidman E. Learning probabilistic neural representations with randomly connected circuits. Proceedings of the National Academy of Sciences of the United States of America. 2020;117(40):25066-25073. doi:10.1073/pnas.1912804117","ista":"Maoz O, Tkačik G, Esteki MS, Kiani R, Schneidman E. 2020. Learning probabilistic neural representations with randomly connected circuits. Proceedings of the National Academy of Sciences of the United States of America. 117(40), 25066–25073.","apa":"Maoz, O., Tkačik, G., Esteki, M. S., Kiani, R., & Schneidman, E. (2020). Learning probabilistic neural representations with randomly connected circuits. Proceedings of the National Academy of Sciences of the United States of America. National Academy of Sciences. https://doi.org/10.1073/pnas.1912804117","ieee":"O. Maoz, G. Tkačik, M. S. Esteki, R. Kiani, and E. Schneidman, “Learning probabilistic neural representations with randomly connected circuits,” Proceedings of the National Academy of Sciences of the United States of America, vol. 117, no. 40. National Academy of Sciences, pp. 25066–25073, 2020."},"article_type":"original","page":"25066-25073","date_published":"2020-10-06T00:00:00Z","type":"journal_article","abstract":[{"text":"The brain represents and reasons probabilistically about complex stimuli and motor actions using a noisy, spike-based neural code. A key building block for such neural computations, as well as the basis for supervised and unsupervised learning, is the ability to estimate the surprise or likelihood of incoming high-dimensional neural activity patterns. Despite progress in statistical modeling of neural responses and deep learning, current approaches either do not scale to large neural populations or cannot be implemented using biologically realistic mechanisms. Inspired by the sparse and random connectivity of real neuronal circuits, we present a model for neural codes that accurately estimates the likelihood of individual spiking patterns and has a straightforward, scalable, efficient, learnable, and realistic neural implementation. This model’s performance on simultaneously recorded spiking activity of >100 neurons in the monkey visual and prefrontal cortices is comparable with or better than that of state-of-the-art models. Importantly, the model can be learned using a small number of samples and using a local learning rule that utilizes noise intrinsic to neural circuits. Slower, structural changes in random connectivity, consistent with rewiring and pruning processes, further improve the efficiency and sparseness of the resulting neural representations. Our results merge insights from neuroanatomy, machine learning, and theoretical neuroscience to suggest random sparse connectivity as a key design principle for neuronal computation.","lang":"eng"}],"issue":"40","_id":"8698","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","ddc":["570"],"status":"public","title":"Learning probabilistic neural representations with randomly connected circuits","intvolume":" 117","oa_version":"Published Version","file":[{"date_updated":"2020-10-27T14:57:50Z","date_created":"2020-10-27T14:57:50Z","success":1,"checksum":"c6a24fdecf3f28faf447078e7a274a88","file_id":"8713","relation":"main_file","creator":"cziletti","content_type":"application/pdf","file_size":1755359,"file_name":"2020_PNAS_Maoz.pdf","access_level":"open_access"}],"month":"10","publication_identifier":{"issn":["00278424"],"eissn":["10916490"]},"tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","short":"CC BY-NC-ND (4.0)","image":"/images/cc_by_nc_nd.png"},"oa":1,"external_id":{"isi":["000579045200012"],"pmid":["32948691"]},"quality_controlled":"1","isi":1,"doi":"10.1073/pnas.1912804117","language":[{"iso":"eng"}],"file_date_updated":"2020-10-27T14:57:50Z","acknowledgement":"We thank Udi Karpas, Roy Harpaz, Tal Tamir, Adam Haber, and Amir Bar for discussions and suggestions; and especially Oren Forkosh and Walter Senn for invaluable discussions of the learning rule. This work was supported by European Research Council Grant 311238 (to E.S.) and Israel Science Foundation Grant 1629/12 (to E.S.); as well as research support from Martin Kushner Schnur and Mr. and Mrs. Lawrence Feis (E.S.); National Institute of Mental Health Grant R01MH109180 (to R.K.); a Pew Scholarship in Biomedical Sciences (to R.K.); Simons Collaboration on the Global Brain Grant 542997 (to R.K. and E.S.); and a CRCNS (Collaborative Research in Computational Neuroscience) grant (to R.K. and E.S.).","year":"2020","pmid":1,"publication_status":"published","department":[{"_id":"GaTk"}],"publisher":"National Academy of Sciences","author":[{"last_name":"Maoz","first_name":"Ori","full_name":"Maoz, Ori"},{"full_name":"Tkačik, Gašper","last_name":"Tkačik","first_name":"Gašper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Mohamad Saleh","last_name":"Esteki","full_name":"Esteki, Mohamad Saleh"},{"last_name":"Kiani","first_name":"Roozbeh","full_name":"Kiani, Roozbeh"},{"full_name":"Schneidman, Elad","last_name":"Schneidman","first_name":"Elad"}],"date_created":"2020-10-25T23:01:16Z","date_updated":"2023-08-22T12:11:23Z","volume":117},{"scopus_import":"1","article_processing_charge":"No","has_accepted_license":"1","day":"26","article_type":"original","citation":{"ista":"Rizzo R, Zhang X, Wang JWJL, Lombardi F, Ivanov PC. 2020. Network physiology of cortico–muscular interactions. Frontiers in Physiology. 11, 558070.","apa":"Rizzo, R., Zhang, X., Wang, J. W. J. L., Lombardi, F., & Ivanov, P. C. (2020). Network physiology of cortico–muscular interactions. Frontiers in Physiology. Frontiers. https://doi.org/10.3389/fphys.2020.558070","ieee":"R. Rizzo, X. Zhang, J. W. J. L. Wang, F. Lombardi, and P. C. Ivanov, “Network physiology of cortico–muscular interactions,” Frontiers in Physiology, vol. 11. Frontiers, 2020.","ama":"Rizzo R, Zhang X, Wang JWJL, Lombardi F, Ivanov PC. Network physiology of cortico–muscular interactions. Frontiers in Physiology. 2020;11. doi:10.3389/fphys.2020.558070","chicago":"Rizzo, Rossella, Xiyun Zhang, Jilin W.J.L. Wang, Fabrizio Lombardi, and Plamen Ch Ivanov. “Network Physiology of Cortico–Muscular Interactions.” Frontiers in Physiology. Frontiers, 2020. https://doi.org/10.3389/fphys.2020.558070.","mla":"Rizzo, Rossella, et al. “Network Physiology of Cortico–Muscular Interactions.” Frontiers in Physiology, vol. 11, 558070, Frontiers, 2020, doi:10.3389/fphys.2020.558070.","short":"R. Rizzo, X. Zhang, J.W.J.L. Wang, F. Lombardi, P.C. Ivanov, Frontiers in Physiology 11 (2020)."},"publication":"Frontiers in Physiology","date_published":"2020-11-26T00:00:00Z","type":"journal_article","abstract":[{"text":"Skeletal muscle activity is continuously modulated across physiologic states to provide coordination, flexibility and responsiveness to body tasks and external inputs. Despite the central role the muscular system plays in facilitating vital body functions, the network of brain-muscle interactions required to control hundreds of muscles and synchronize their activation in relation to distinct physiologic states has not been investigated. Recent approaches have focused on general associations between individual brain rhythms and muscle activation during movement tasks. However, the specific forms of coupling, the functional network of cortico-muscular coordination, and how network structure and dynamics are modulated by autonomic regulation across physiologic states remains unknown. To identify and quantify the cortico-muscular interaction network and uncover basic features of neuro-autonomic control of muscle function, we investigate the coupling between synchronous bursts in cortical rhythms and peripheral muscle activation during sleep and wake. Utilizing the concept of time delay stability and a novel network physiology approach, we find that the brain-muscle network exhibits complex dynamic patterns of communication involving multiple brain rhythms across cortical locations and different electromyographic frequency bands. Moreover, our results show that during each physiologic state the cortico-muscular network is characterized by a specific profile of network links strength, where particular brain rhythms play role of main mediators of interaction and control. Further, we discover a hierarchical reorganization in network structure across physiologic states, with high connectivity and network link strength during wake, intermediate during REM and light sleep, and low during deep sleep, a sleep-stage stratification that demonstrates a unique association between physiologic states and cortico-muscular network structure. The reported empirical observations are consistent across individual subjects, indicating universal behavior in network structure and dynamics, and high sensitivity of cortico-muscular control to changes in autonomic regulation, even at low levels of physical activity and muscle tone during sleep. Our findings demonstrate previously unrecognized basic principles of brain-muscle network communication and control, and provide new perspectives on the regulatory mechanisms of brain dynamics and locomotor activation, with potential clinical implications for neurodegenerative, movement and sleep disorders, and for developing efficient treatment strategies.","lang":"eng"}],"intvolume":" 11","ddc":["570"],"title":"Network physiology of cortico–muscular interactions","status":"public","_id":"8955","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","file":[{"access_level":"open_access","file_name":"2020_Frontiers_Rizzo.pdf","creator":"dernst","file_size":13380030,"content_type":"application/pdf","file_id":"8961","relation":"main_file","success":1,"checksum":"ef9515b28c5619b7126c0f347958bcb3","date_updated":"2020-12-21T10:37:50Z","date_created":"2020-12-21T10:37:50Z"}],"oa_version":"Published Version","publication_identifier":{"eissn":["1664042X"]},"month":"11","project":[{"grant_number":"754411","_id":"260C2330-B435-11E9-9278-68D0E5697425","name":"ISTplus - Postdoctoral Fellowships","call_identifier":"H2020"}],"quality_controlled":"1","isi":1,"external_id":{"isi":["000596849400001"],"pmid":["33324233"]},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"language":[{"iso":"eng"}],"doi":"10.3389/fphys.2020.558070","article_number":"558070","ec_funded":1,"file_date_updated":"2020-12-21T10:37:50Z","department":[{"_id":"GaTk"}],"publisher":"Frontiers","publication_status":"published","pmid":1,"year":"2020","acknowledgement":"We acknowledge support from the W. M. Keck Foundation, National Institutes of Health (NIH Grant 1R01-HL098437), the US-Israel Binational Science Foundation (BSF Grant 2012219), and the Office of Naval Research (ONR Grant 000141010078). FL acknowledges support also from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant Agreement No. 754411.","volume":11,"date_updated":"2023-08-24T11:00:45Z","date_created":"2020-12-20T23:01:18Z","author":[{"full_name":"Rizzo, Rossella","last_name":"Rizzo","first_name":"Rossella"},{"full_name":"Zhang, Xiyun","first_name":"Xiyun","last_name":"Zhang"},{"full_name":"Wang, Jilin W.J.L.","last_name":"Wang","first_name":"Jilin W.J.L."},{"first_name":"Fabrizio","last_name":"Lombardi","id":"A057D288-3E88-11E9-986D-0CF4E5697425","orcid":"0000-0003-2623-5249","full_name":"Lombardi, Fabrizio"},{"first_name":"Plamen Ch","last_name":"Ivanov","full_name":"Ivanov, Plamen Ch"}]},{"file_date_updated":"2021-01-11T08:37:31Z","volume":117,"date_updated":"2023-08-24T11:10:22Z","date_created":"2021-01-10T23:01:17Z","related_material":{"link":[{"url":"https://ist.ac.at/en/news/new-compact-model-for-gene-regulation-in-higher-organisms/","description":"News on IST Homepage","relation":"press_release"}]},"author":[{"full_name":"Grah, Rok","last_name":"Grah","first_name":"Rok","orcid":"0000-0003-2539-3560","id":"483E70DE-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Zoller, Benjamin","first_name":"Benjamin","last_name":"Zoller"},{"full_name":"Tkačik, Gašper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkačik","first_name":"Gašper"}],"department":[{"_id":"GaTk"}],"publisher":"National Academy of Sciences","publication_status":"published","pmid":1,"acknowledgement":"G.T. was supported by Human Frontiers Science Program Grant RGP0034/2018. R.G. was supported by the Austrian Academy of Sciences DOC Fellowship. R.G. thanks S. Avvakumov for helpful discussions.","year":"2020","publication_identifier":{"issn":["00278424"],"eissn":["10916490"]},"month":"12","language":[{"iso":"eng"}],"doi":"10.1073/pnas.2006731117","project":[{"grant_number":"RGP0034/2018","_id":"2665AAFE-B435-11E9-9278-68D0E5697425","name":"Can evolution minimize spurious signaling crosstalk to reach optimal performance?"},{"_id":"267C84F4-B435-11E9-9278-68D0E5697425","name":"Biophysically realistic genotype-phenotype maps for regulatory networks"}],"isi":1,"quality_controlled":"1","oa":1,"tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","short":"CC BY-NC-ND (4.0)","image":"/images/cc_by_nc_nd.png"},"external_id":{"isi":["000600608300015"],"pmid":["33268497"]},"issue":"50","abstract":[{"lang":"eng","text":"In prokaryotes, thermodynamic models of gene regulation provide a highly quantitative mapping from promoter sequences to gene-expression levels that is compatible with in vivo and in vitro biophysical measurements. Such concordance has not been achieved for models of enhancer function in eukaryotes. In equilibrium models, it is difficult to reconcile the reported short transcription factor (TF) residence times on the DNA with the high specificity of regulation. In nonequilibrium models, progress is difficult due to an explosion in the number of parameters. Here, we navigate this complexity by looking for minimal nonequilibrium enhancer models that yield desired regulatory phenotypes: low TF residence time, high specificity, and tunable cooperativity. We find that a single extra parameter, interpretable as the “linking rate,” by which bound TFs interact with Mediator components, enables our models to escape equilibrium bounds and access optimal regulatory phenotypes, while remaining consistent with the reported phenomenology and simple enough to be inferred from upcoming experiments. We further find that high specificity in nonequilibrium models is in a trade-off with gene-expression noise, predicting bursty dynamics—an experimentally observed hallmark of eukaryotic transcription. By drastically reducing the vast parameter space of nonequilibrium enhancer models to a much smaller subspace that optimally realizes biological function, we deliver a rich class of models that could be tractably inferred from data in the near future."}],"type":"journal_article","file":[{"date_updated":"2021-01-11T08:37:31Z","date_created":"2021-01-11T08:37:31Z","checksum":"69039cd402a571983aa6cb4815ffa863","success":1,"relation":"main_file","file_id":"9004","content_type":"application/pdf","file_size":1199247,"creator":"dernst","file_name":"2020_PNAS_Grah.pdf","access_level":"open_access"}],"oa_version":"Published Version","intvolume":" 117","title":"Nonequilibrium models of optimal enhancer function","status":"public","ddc":["570"],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","_id":"9000","article_processing_charge":"No","has_accepted_license":"1","day":"15","scopus_import":"1","date_published":"2020-12-15T00:00:00Z","page":"31614-31622","article_type":"original","citation":{"ista":"Grah R, Zoller B, Tkačik G. 2020. Nonequilibrium models of optimal enhancer function. PNAS. 117(50), 31614–31622.","apa":"Grah, R., Zoller, B., & Tkačik, G. (2020). Nonequilibrium models of optimal enhancer function. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.2006731117","ieee":"R. Grah, B. Zoller, and G. Tkačik, “Nonequilibrium models of optimal enhancer function,” PNAS, vol. 117, no. 50. National Academy of Sciences, pp. 31614–31622, 2020.","ama":"Grah R, Zoller B, Tkačik G. Nonequilibrium models of optimal enhancer function. PNAS. 2020;117(50):31614-31622. doi:10.1073/pnas.2006731117","chicago":"Grah, Rok, Benjamin Zoller, and Gašper Tkačik. “Nonequilibrium Models of Optimal Enhancer Function.” PNAS. National Academy of Sciences, 2020. https://doi.org/10.1073/pnas.2006731117.","mla":"Grah, Rok, et al. “Nonequilibrium Models of Optimal Enhancer Function.” PNAS, vol. 117, no. 50, National Academy of Sciences, 2020, pp. 31614–22, doi:10.1073/pnas.2006731117.","short":"R. Grah, B. Zoller, G. Tkačik, PNAS 117 (2020) 31614–31622."},"publication":"PNAS"},{"external_id":{"pmid":["31694962"],"isi":["000505167600016"]},"oa":1,"quality_controlled":"1","isi":1,"project":[{"name":"ISTplus - Postdoctoral Fellowships","call_identifier":"H2020","grant_number":"754411","_id":"260C2330-B435-11E9-9278-68D0E5697425"}],"doi":"10.1523/jneurosci.1278-19.2019","language":[{"iso":"eng"}],"month":"01","publication_identifier":{"eissn":["1529-2401"],"issn":["0270-6474"]},"year":"2020","pmid":1,"publication_status":"published","department":[{"_id":"GaTk"}],"publisher":"Society for Neuroscience","author":[{"orcid":"0000-0003-2623-5249","id":"A057D288-3E88-11E9-986D-0CF4E5697425","last_name":"Lombardi","first_name":"Fabrizio","full_name":"Lombardi, Fabrizio"},{"full_name":"Gómez-Extremera, Manuel","last_name":"Gómez-Extremera","first_name":"Manuel"},{"full_name":"Bernaola-Galván, Pedro","last_name":"Bernaola-Galván","first_name":"Pedro"},{"last_name":"Vetrivelan","first_name":"Ramalingam","full_name":"Vetrivelan, Ramalingam"},{"full_name":"Saper, Clifford B.","first_name":"Clifford B.","last_name":"Saper"},{"last_name":"Scammell","first_name":"Thomas E.","full_name":"Scammell, Thomas E."},{"first_name":"Plamen Ch.","last_name":"Ivanov","full_name":"Ivanov, Plamen Ch."}],"date_created":"2020-07-05T15:24:51Z","date_updated":"2023-09-05T14:02:55Z","volume":40,"file_date_updated":"2020-07-22T11:44:48Z","ec_funded":1,"publication":"Journal of Neuroscience","citation":{"ieee":"F. Lombardi et al., “Critical dynamics and coupling in bursts of cortical rhythms indicate non-homeostatic mechanism for sleep-stage transitions and dual role of VLPO neurons in both sleep and wake,” Journal of Neuroscience, vol. 40, no. 1. Society for Neuroscience, pp. 171–190, 2020.","apa":"Lombardi, F., Gómez-Extremera, M., Bernaola-Galván, P., Vetrivelan, R., Saper, C. B., Scammell, T. E., & Ivanov, P. C. (2020). Critical dynamics and coupling in bursts of cortical rhythms indicate non-homeostatic mechanism for sleep-stage transitions and dual role of VLPO neurons in both sleep and wake. Journal of Neuroscience. Society for Neuroscience. https://doi.org/10.1523/jneurosci.1278-19.2019","ista":"Lombardi F, Gómez-Extremera M, Bernaola-Galván P, Vetrivelan R, Saper CB, Scammell TE, Ivanov PC. 2020. Critical dynamics and coupling in bursts of cortical rhythms indicate non-homeostatic mechanism for sleep-stage transitions and dual role of VLPO neurons in both sleep and wake. Journal of Neuroscience. 40(1), 171–190.","ama":"Lombardi F, Gómez-Extremera M, Bernaola-Galván P, et al. Critical dynamics and coupling in bursts of cortical rhythms indicate non-homeostatic mechanism for sleep-stage transitions and dual role of VLPO neurons in both sleep and wake. Journal of Neuroscience. 2020;40(1):171-190. doi:10.1523/jneurosci.1278-19.2019","chicago":"Lombardi, Fabrizio, Manuel Gómez-Extremera, Pedro Bernaola-Galván, Ramalingam Vetrivelan, Clifford B. Saper, Thomas E. Scammell, and Plamen Ch. Ivanov. “Critical Dynamics and Coupling in Bursts of Cortical Rhythms Indicate Non-Homeostatic Mechanism for Sleep-Stage Transitions and Dual Role of VLPO Neurons in Both Sleep and Wake.” Journal of Neuroscience. Society for Neuroscience, 2020. https://doi.org/10.1523/jneurosci.1278-19.2019.","short":"F. Lombardi, M. Gómez-Extremera, P. Bernaola-Galván, R. Vetrivelan, C.B. Saper, T.E. Scammell, P.C. Ivanov, Journal of Neuroscience 40 (2020) 171–190.","mla":"Lombardi, Fabrizio, et al. “Critical Dynamics and Coupling in Bursts of Cortical Rhythms Indicate Non-Homeostatic Mechanism for Sleep-Stage Transitions and Dual Role of VLPO Neurons in Both Sleep and Wake.” Journal of Neuroscience, vol. 40, no. 1, Society for Neuroscience, 2020, pp. 171–90, doi:10.1523/jneurosci.1278-19.2019."},"article_type":"original","page":"171-190","date_published":"2020-01-02T00:00:00Z","scopus_import":"1","day":"02","has_accepted_license":"1","article_processing_charge":"No","_id":"8084","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","status":"public","ddc":["570"],"title":"Critical dynamics and coupling in bursts of cortical rhythms indicate non-homeostatic mechanism for sleep-stage transitions and dual role of VLPO neurons in both sleep and wake","intvolume":" 40","file":[{"file_id":"8150","relation":"main_file","date_created":"2020-07-22T11:44:48Z","date_updated":"2020-07-22T11:44:48Z","success":1,"file_name":"2020_JournNeuroscience_Lombardi.pdf","access_level":"open_access","creator":"dernst","file_size":6646046,"content_type":"application/pdf"}],"oa_version":"Published Version","type":"journal_article","abstract":[{"text":"Origin and functions of intermittent transitions among sleep stages, including brief awakenings and arousals, constitute a challenge to the current homeostatic framework for sleep regulation, focusing on factors modulating sleep over large time scales. Here we propose that the complex micro-architecture characterizing sleep on scales of seconds and minutes results from intrinsic non-equilibrium critical dynamics. We investigate θ- and δ-wave dynamics in control rats and in rats where the sleep-promoting ventrolateral preoptic nucleus (VLPO) is lesioned (male Sprague-Dawley rats). We demonstrate that bursts in θ and δ cortical rhythms exhibit complex temporal organization, with long-range correlations and robust duality of power-law (θ-bursts, active phase) and exponential-like (δ-bursts, quiescent phase) duration distributions, features typical of non-equilibrium systems self-organizing at criticality. We show that such non-equilibrium behavior relates to anti-correlated coupling between θ- and δ-bursts, persists across a range of time scales, and is independent of the dominant physiologic state; indications of a basic principle in sleep regulation. Further, we find that VLPO lesions lead to a modulation of cortical dynamics resulting in altered dynamical parameters of θ- and δ-bursts and significant reduction in θ–δ coupling. Our empirical findings and model simulations demonstrate that θ–δ coupling is essential for the emerging non-equilibrium critical dynamics observed across the sleep–wake cycle, and indicate that VLPO neurons may have dual role for both sleep and arousal/brief wake activation. The uncovered critical behavior in sleep- and wake-related cortical rhythms indicates a mechanism essential for the micro-architecture of spontaneous sleep-stage and arousal transitions within a novel, non-homeostatic paradigm of sleep regulation.","lang":"eng"}],"issue":"1"},{"date_published":"2020-07-24T00:00:00Z","citation":{"ieee":"R. Grah, “Gene regulation across scales – how biophysical constraints shape evolution,” Institute of Science and Technology Austria, 2020.","apa":"Grah, R. (2020). Gene regulation across scales – how biophysical constraints shape evolution. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8155","ista":"Grah R. 2020. Gene regulation across scales – how biophysical constraints shape evolution. Institute of Science and Technology Austria.","ama":"Grah R. Gene regulation across scales – how biophysical constraints shape evolution. 2020. doi:10.15479/AT:ISTA:8155","chicago":"Grah, Rok. “Gene Regulation across Scales – How Biophysical Constraints Shape Evolution.” Institute of Science and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:8155.","short":"R. Grah, Gene Regulation across Scales – How Biophysical Constraints Shape Evolution, Institute of Science and Technology Austria, 2020.","mla":"Grah, Rok. Gene Regulation across Scales – How Biophysical Constraints Shape Evolution. Institute of Science and Technology Austria, 2020, doi:10.15479/AT:ISTA:8155."},"page":"310","day":"24","has_accepted_license":"1","article_processing_charge":"No","file":[{"creator":"rgrah","content_type":"application/pdf","file_size":16638998,"file_name":"Thesis_RokGrah_200727_convertedNew.pdf","access_level":"open_access","date_created":"2020-07-27T12:00:07Z","date_updated":"2020-07-27T12:00:07Z","success":1,"file_id":"8176","relation":"main_file"},{"creator":"rgrah","content_type":"application/zip","file_size":347459978,"file_name":"Thesis_new.zip","access_level":"closed","date_updated":"2020-07-30T13:04:55Z","date_created":"2020-07-27T12:02:23Z","file_id":"8177","relation":"main_file"}],"oa_version":"Published Version","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"8155","title":"Gene regulation across scales – how biophysical constraints shape evolution","status":"public","ddc":["530","570"],"abstract":[{"text":"In the thesis we focus on the interplay of the biophysics and evolution of gene regulation. We start by addressing how the type of prokaryotic gene regulation – activation and repression – affects spurious binding to DNA, also known as\r\ntranscriptional crosstalk. We propose that regulatory interference caused by excess regulatory proteins in the dense cellular medium – global crosstalk – could be a factor in determining which type of gene regulatory network is evolutionarily preferred. Next,we use a normative approach in eukaryotic gene regulation to describe minimal\r\nnon-equilibrium enhancer models that optimize so-called regulatory phenotypes. We find a class of models that differ from standard thermodynamic equilibrium models by a single parameter that notably increases the regulatory performance. Next chapter addresses the question of genotype-phenotype-fitness maps of higher dimensional phenotypes. We show that our biophysically realistic approach allows us to understand how the mechanisms of promoter function constrain genotypephenotype maps, and how they affect the evolutionary trajectories of promoters.\r\nIn the last chapter we ask whether the intrinsic instability of gene duplication and amplification provides a generic alternative to canonical gene regulation. Using mathematical modeling, we show that amplifications can tune gene expression in many environments, including those where transcription factor-based schemes are\r\nhard to evolve or maintain. ","lang":"eng"}],"type":"dissertation","alternative_title":["ISTA Thesis"],"doi":"10.15479/AT:ISTA:8155","degree_awarded":"PhD","supervisor":[{"full_name":"Guet, Calin C","first_name":"Calin C","last_name":"Guet","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052"},{"first_name":"Gašper","last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","full_name":"Tkačik, Gašper"}],"language":[{"iso":"eng"}],"oa":1,"project":[{"_id":"267C84F4-B435-11E9-9278-68D0E5697425","name":"Biophysically realistic genotype-phenotype maps for regulatory networks"}],"month":"07","publication_identifier":{"issn":["2663-337X"]},"author":[{"full_name":"Grah, Rok","orcid":"0000-0003-2539-3560","id":"483E70DE-F248-11E8-B48F-1D18A9856A87","last_name":"Grah","first_name":"Rok"}],"related_material":{"record":[{"relation":"part_of_dissertation","status":"public","id":"7675"},{"relation":"part_of_dissertation","status":"public","id":"7569"},{"id":"7652","status":"public","relation":"part_of_dissertation"}]},"date_updated":"2023-09-07T13:13:27Z","date_created":"2020-07-23T09:51:28Z","acknowledgement":"For the duration of his PhD, Rok was a recipient of a DOC fellowship of the Austrian Academy of Sciences.","year":"2020","publication_status":"published","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publisher":"Institute of Science and Technology Austria","file_date_updated":"2020-07-30T13:04:55Z"},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"7675","year":"2020","publisher":"Cold Spring Harbor Laboratory","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"status":"public","publication_status":"published","title":"Normative models of enhancer function","related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"8155"}]},"author":[{"id":"483E70DE-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2539-3560","first_name":"Rok","last_name":"Grah","full_name":"Grah, Rok"},{"full_name":"Zoller, Benjamin","last_name":"Zoller","first_name":"Benjamin"},{"orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkačik","first_name":"Gašper","full_name":"Tkačik, Gašper"}],"oa_version":"Preprint","date_updated":"2023-09-07T13:13:26Z","date_created":"2020-04-23T10:12:51Z","type":"preprint","abstract":[{"lang":"eng","text":"In prokaryotes, thermodynamic models of gene regulation provide a highly quantitative mapping from promoter sequences to gene expression levels that is compatible with in vivo and in vitro bio-physical measurements. Such concordance has not been achieved for models of enhancer function in eukaryotes. In equilibrium models, it is difficult to reconcile the reported short transcription factor (TF) residence times on the DNA with the high specificity of regulation. In non-equilibrium models, progress is difficult due to an explosion in the number of parameters. Here, we navigate this complexity by looking for minimal non-equilibrium enhancer models that yield desired regulatory phenotypes: low TF residence time, high specificity and tunable cooperativity. We find that a single extra parameter, interpretable as the “linking rate” by which bound TFs interact with Mediator components, enables our models to escape equilibrium bounds and access optimal regulatory phenotypes, while remaining consistent with the reported phenomenology and simple enough to be inferred from upcoming experiments. We further find that high specificity in non-equilibrium models is in a tradeoff with gene expression noise, predicting bursty dynamics — an experimentally-observed hallmark of eukaryotic transcription. By drastically reducing the vast parameter space to a much smaller subspace that optimally realizes biological function prior to inference from data, our normative approach holds promise for mathematical models in systems biology."}],"main_file_link":[{"url":"https://doi.org/10.1101/2020.04.08.029405 ","open_access":"1"}],"citation":{"ista":"Grah R, Zoller B, Tkačik G. 2020. Normative models of enhancer function. bioRxiv, 10.1101/2020.04.08.029405.","apa":"Grah, R., Zoller, B., & Tkačik, G. (2020). Normative models of enhancer function. bioRxiv. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2020.04.08.029405","ieee":"R. Grah, B. Zoller, and G. Tkačik, “Normative models of enhancer function,” bioRxiv. Cold Spring Harbor Laboratory, 2020.","ama":"Grah R, Zoller B, Tkačik G. Normative models of enhancer function. bioRxiv. 2020. doi:10.1101/2020.04.08.029405","chicago":"Grah, Rok, Benjamin Zoller, and Gašper Tkačik. “Normative Models of Enhancer Function.” BioRxiv. Cold Spring Harbor Laboratory, 2020. https://doi.org/10.1101/2020.04.08.029405.","mla":"Grah, Rok, et al. “Normative Models of Enhancer Function.” BioRxiv, Cold Spring Harbor Laboratory, 2020, doi:10.1101/2020.04.08.029405.","short":"R. Grah, B. Zoller, G. Tkačik, BioRxiv (2020)."},"oa":1,"publication":"bioRxiv","project":[{"_id":"2665AAFE-B435-11E9-9278-68D0E5697425","grant_number":"RGP0034/2018","name":"Can evolution minimize spurious signaling crosstalk to reach optimal performance?"},{"name":"Biophysically realistic genotype-phenotype maps for regulatory networks","_id":"267C84F4-B435-11E9-9278-68D0E5697425"}],"doi":"10.1101/2020.04.08.029405","date_published":"2020-04-09T00:00:00Z","language":[{"iso":"eng"}],"article_processing_charge":"No","day":"09","month":"04"},{"date_updated":"2023-09-12T11:02:24Z","date_created":"2020-03-06T07:39:38Z","volume":16,"author":[{"last_name":"Grah","first_name":"Rok","orcid":"0000-0003-2539-3560","id":"483E70DE-F248-11E8-B48F-1D18A9856A87","full_name":"Grah, Rok"},{"full_name":"Friedlander, Tamar","first_name":"Tamar","last_name":"Friedlander"}],"related_material":{"record":[{"id":"9716","status":"deleted","relation":"research_data"},{"id":"9776","relation":"research_data","status":"public"},{"id":"9779","relation":"used_in_publication","status":"public"},{"id":"8155","relation":"dissertation_contains","status":"public"},{"relation":"research_data","status":"public","id":"9777"}]},"publication_status":"published","publisher":"Public Library of Science","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"year":"2020","file_date_updated":"2020-07-14T12:48:00Z","article_number":"e1007642","language":[{"iso":"eng"}],"doi":"10.1371/journal.pcbi.1007642","isi":1,"quality_controlled":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"external_id":{"isi":["000526725200019"]},"oa":1,"month":"02","publication_identifier":{"issn":["1553-7358"]},"file":[{"date_created":"2020-03-09T15:12:21Z","date_updated":"2020-07-14T12:48:00Z","checksum":"5239dd134dc6e1c71fe7b3ce2953da37","file_id":"7579","relation":"main_file","creator":"dernst","file_size":2209325,"content_type":"application/pdf","file_name":"2020_PlosCompBio_Grah.pdf","access_level":"open_access"}],"oa_version":"Published Version","title":"The relation between crosstalk and gene regulation form revisited","status":"public","ddc":["000","570"],"intvolume":" 16","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","_id":"7569","abstract":[{"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.","lang":"eng"}],"issue":"2","type":"journal_article","date_published":"2020-02-25T00:00:00Z","article_type":"original","publication":"PLOS Computational Biology","citation":{"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.","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","ista":"Grah R, Friedlander T. 2020. The relation between crosstalk and gene regulation form revisited. PLOS Computational Biology. 16(2), e1007642.","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","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.","short":"R. Grah, T. Friedlander, PLOS Computational Biology 16 (2020).","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."},"day":"25","article_processing_charge":"No","has_accepted_license":"1","scopus_import":"1"},{"type":"research_data_reference","date_created":"2021-08-06T07:21:51Z","date_updated":"2023-09-12T11:02:25Z","oa_version":"None","author":[{"last_name":"Grah","first_name":"Rok","orcid":"0000-0003-2539-3560","id":"483E70DE-F248-11E8-B48F-1D18A9856A87","full_name":"Grah, Rok"},{"full_name":"Friedlander, Tamar","last_name":"Friedlander","first_name":"Tamar"}],"related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"7569"}]},"status":"public","title":"Maximizing crosstalk","publisher":"Public Library of Science","department":[{"_id":"GaTk"}],"_id":"9777","year":"2020","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","month":"02","day":"25","article_processing_charge":"No","doi":"10.1371/journal.pcbi.1007642.s002","date_published":"2020-02-25T00:00:00Z","main_file_link":[{"url":"https://doi.org/10.1371/journal.pcbi.1007642.s002","open_access":"1"}],"citation":{"ista":"Grah R, Friedlander T. 2020. Maximizing crosstalk, Public Library of Science, 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.","ama":"Grah R, Friedlander T. Maximizing crosstalk. 2020. doi: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.","mla":"Grah, Rok, and Tamar Friedlander. Maximizing Crosstalk. Public Library of Science, 2020, doi:10.1371/journal.pcbi.1007642.s002.","short":"R. Grah, T. Friedlander, (2020)."},"oa":1},{"author":[{"full_name":"Kavcic, Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6041-254X","first_name":"Bor","last_name":"Kavcic"}],"contributor":[{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gašper","last_name":"Tkačik","contributor_type":"research_group"},{"first_name":"Tobias","last_name":"Bollenbach","contributor_type":"research_group","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87"}],"date_updated":"2024-02-21T12:40:51Z","date_created":"2020-07-06T20:40:19Z","file":[{"creator":"bkavcic","file_size":255770756,"content_type":"application/zip","file_name":"natComm_2020_scripts.zip","access_level":"open_access","date_created":"2020-07-06T20:38:27Z","date_updated":"2020-07-14T12:48:09Z","checksum":"5c321dbbb6d4b3c85da786fd3ebbdc98","file_id":"8098","relation":"main_file"}],"oa_version":"Published Version","_id":"8097","year":"2020","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Analysis scripts and research data for the paper \"Mechanisms of drug interactions between translation-inhibiting antibiotics\"","status":"public","publisher":"Institute of Science and Technology Austria","department":[{"_id":"GaTk"}],"file_date_updated":"2020-07-14T12:48:09Z","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."}],"type":"research_data","date_published":"2020-07-15T00:00:00Z","doi":"10.15479/AT:ISTA:8097","acknowledged_ssus":[{"_id":"LifeSc"}],"citation":{"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.","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.","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.","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","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.","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"},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"month":"07","day":"15","has_accepted_license":"1","article_processing_charge":"No","keyword":["Escherichia coli","antibiotic combinations","translation","growth laws","drug interactions","bacterial physiology","translation inhibitors"]},{"related_material":{"record":[{"id":"8997","relation":"used_in_publication","status":"public"}]},"contributor":[{"last_name":"Tkačik","contributor_type":"supervisor","first_name":"Gašper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87"},{"id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach","contributor_type":"supervisor","first_name":"Tobias"}],"author":[{"full_name":"Kavcic, Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6041-254X","first_name":"Bor","last_name":"Kavcic"}],"file":[{"success":1,"checksum":"60a818edeffaa7da1ebf5f8fbea9ba18","date_created":"2020-12-09T15:00:19Z","date_updated":"2020-12-09T15:00:19Z","file_id":"8932","relation":"main_file","creator":"bkavcic","content_type":"application/zip","file_size":315494370,"access_level":"open_access","file_name":"PLoSCompBiol2020_datarep.zip"}],"oa_version":"Published Version","date_created":"2020-12-09T15:04:02Z","date_updated":"2024-02-21T12:41:42Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"8930","year":"2020","publisher":"Institute of Science and Technology Austria","department":[{"_id":"GaTk"}],"title":"Analysis scripts and research data for the paper \"Minimal biophysical model of combined antibiotic action\"","ddc":["570"],"status":"public","file_date_updated":"2020-12-09T15:00:19Z","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."}],"type":"research_data","date_published":"2020-12-10T00:00:00Z","doi":"10.15479/AT:ISTA:8930","citation":{"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","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","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.","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.","short":"B. Kavcic, (2020).","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.","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."},"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"has_accepted_license":"1","article_processing_charge":"No","day":"10","month":"12","keyword":["Escherichia coli","antibiotic combinations","translation","growth laws","drug interactions","bacterial physiology","translation inhibitors"]},{"date_published":"2020-01-28T00:00:00Z","doi":"10.15479/AT:ISTA:7383","oa":1,"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.","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","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","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.","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.","short":"R. Grah, (2020)."},"article_processing_charge":"No","has_accepted_license":"1","month":"01","day":"28","keyword":["Matlab scripts","analysis of microfluidics","mathematical model"],"oa_version":"Published Version","file":[{"file_name":"Scripts.zip","access_level":"open_access","file_size":73363365,"content_type":"application/zip","creator":"rgrah","relation":"main_file","file_id":"7384","date_created":"2020-01-28T10:39:40Z","date_updated":"2020-07-14T12:47:57Z","checksum":"9d292cf5207b3829225f44c044cdb3fd"},{"file_id":"7385","relation":"main_file","checksum":"4076ceab32ef588cc233802bab24c1ab","date_updated":"2020-07-14T12:47:57Z","date_created":"2020-01-28T10:39:30Z","access_level":"open_access","file_name":"READ_ME_MAIN.txt","creator":"rgrah","file_size":962,"content_type":"text/plain"}],"date_updated":"2024-02-21T12:42:31Z","date_created":"2020-01-28T10:41:49Z","contributor":[{"id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052","first_name":"Calin C","contributor_type":"project_leader","last_name":"Guet"}],"related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"7652"}]},"author":[{"orcid":"0000-0003-2539-3560","id":"483E70DE-F248-11E8-B48F-1D18A9856A87","last_name":"Grah","first_name":"Rok","full_name":"Grah, Rok"}],"publisher":"Institute of Science and Technology Austria","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"status":"public","title":"Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level Gene Expression regulation","_id":"7383","year":"2020","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"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.","lang":"eng"}],"file_date_updated":"2020-07-14T12:47:57Z","type":"research_data"},{"type":"dissertation","alternative_title":["ISTA Thesis"],"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."}],"_id":"8657","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","status":"public","ddc":["571","530","570"],"title":"Perturbations of protein synthesis: from antibiotics to genetics and physiology","oa_version":"Published Version","file":[{"date_created":"2020-10-15T06:41:20Z","date_updated":"2021-10-07T22:30:03Z","checksum":"d708ecd62b6fcc3bc1feb483b8dbe9eb","relation":"main_file","file_id":"8663","embargo":"2021-10-06","file_size":52636162,"content_type":"application/pdf","creator":"bkavcic","file_name":"kavcicB_thesis202009.pdf","access_level":"open_access"},{"creator":"bkavcic","file_size":321681247,"content_type":"application/zip","file_name":"2020b.zip","embargo_to":"open_access","access_level":"closed","date_created":"2020-10-15T06:41:53Z","date_updated":"2021-10-07T22:30:03Z","checksum":"bb35f2352a04db19164da609f00501f3","file_id":"8664","relation":"source_file"}],"day":"14","article_processing_charge":"No","has_accepted_license":"1","citation":{"ama":"Kavcic B. Perturbations of protein synthesis: from antibiotics to genetics and physiology. 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","ieee":"B. Kavcic, “Perturbations of protein synthesis: from antibiotics to genetics and physiology,” Institute of Science and Technology Austria, 2020.","ista":"Kavcic B. 2020. Perturbations of protein synthesis: from antibiotics to genetics and physiology. Institute of Science and Technology Austria.","short":"B. Kavcic, Perturbations of Protein Synthesis: From Antibiotics to Genetics and Physiology, Institute of Science and Technology Austria, 2020.","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.","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."},"page":"271","date_published":"2020-10-14T00:00:00Z","file_date_updated":"2021-10-07T22:30:03Z","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.","year":"2020","publication_status":"published","publisher":"Institute of Science and Technology Austria","department":[{"_id":"GaTk"}],"author":[{"orcid":"0000-0001-6041-254X","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","last_name":"Kavcic","first_name":"Bor","full_name":"Kavcic, Bor"}],"related_material":{"record":[{"id":"7673","status":"public","relation":"part_of_dissertation"},{"relation":"part_of_dissertation","status":"public","id":"8250"}]},"date_created":"2020-10-13T16:46:14Z","date_updated":"2023-09-07T13:20:48Z","month":"10","publication_identifier":{"issn":["2663-337X"],"isbn":["978-3-99078-011-4"]},"oa":1,"doi":"10.15479/AT:ISTA:8657","supervisor":[{"first_name":"Gašper","last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","full_name":"Tkačik, Gašper"},{"id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X","first_name":"Mark Tobias","last_name":"Bollenbach","full_name":"Bollenbach, Mark Tobias"}],"acknowledged_ssus":[{"_id":"LifeSc"},{"_id":"M-Shop"}],"degree_awarded":"PhD","language":[{"iso":"eng"}]},{"oa_version":"Published Version","file":[{"creator":"dernst","file_size":1965672,"content_type":"application/pdf","access_level":"open_access","file_name":"2020_NatureComm_Kavcic.pdf","success":1,"checksum":"986bebb308850a55850028d3d2b5b664","date_updated":"2020-08-17T07:36:57Z","date_created":"2020-08-17T07:36:57Z","file_id":"8275","relation":"main_file"}],"title":"Mechanisms of drug interactions between translation-inhibiting antibiotics","status":"public","ddc":["570"],"intvolume":" 11","_id":"8250","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","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."}],"type":"journal_article","date_published":"2020-08-11T00:00:00Z","article_type":"original","publication":"Nature Communications","citation":{"ieee":"B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Mechanisms of drug interactions between translation-inhibiting antibiotics,” Nature Communications, vol. 11. Springer Nature, 2020.","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","ista":"Kavcic B, Tkačik G, Bollenbach MT. 2020. Mechanisms of drug interactions between translation-inhibiting antibiotics. Nature Communications. 11, 4013.","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","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.","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."},"day":"11","has_accepted_license":"1","article_processing_charge":"No","date_created":"2020-08-12T09:13:50Z","date_updated":"2024-03-28T23:30:08Z","volume":11,"author":[{"orcid":"0000-0001-6041-254X","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","last_name":"Kavcic","first_name":"Bor","full_name":"Kavcic, Bor"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gašper","last_name":"Tkačik","full_name":"Tkačik, Gašper"},{"full_name":"Bollenbach, Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X","first_name":"Tobias","last_name":"Bollenbach"}],"related_material":{"record":[{"id":"8657","status":"public","relation":"dissertation_contains"}]},"publication_status":"published","department":[{"_id":"GaTk"}],"publisher":"Springer Nature","year":"2020","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.","file_date_updated":"2020-08-17T07:36:57Z","article_number":"4013","language":[{"iso":"eng"}],"doi":"10.1038/s41467-020-17734-z","isi":1,"quality_controlled":"1","project":[{"grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF"},{"_id":"254E9036-B435-11E9-9278-68D0E5697425","grant_number":"P28844-B27","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF"}],"oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"external_id":{"isi":["000562769300008"]},"month":"08","publication_identifier":{"issn":["2041-1723"]}},{"related_material":{"record":[{"status":"public","relation":"later_version","id":"8997"},{"relation":"dissertation_contains","status":"public","id":"8657"}]},"author":[{"full_name":"Kavcic, Bor","first_name":"Bor","last_name":"Kavcic","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6041-254X"},{"orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkačik","first_name":"Gašper","full_name":"Tkačik, Gašper"},{"full_name":"Bollenbach, Tobias","first_name":"Tobias","last_name":"Bollenbach","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X"}],"oa_version":"Preprint","date_updated":"2024-03-28T23:30:08Z","date_created":"2020-04-22T08:27:56Z","_id":"7673","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2020","department":[{"_id":"GaTk"}],"publisher":"Cold Spring Harbor Laboratory","status":"public","title":"A minimal biophysical model of combined antibiotic action","publication_status":"published","abstract":[{"lang":"eng","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."}],"type":"preprint","doi":"10.1101/2020.04.18.047886","date_published":"2020-04-18T00:00:00Z","language":[{"iso":"eng"}],"oa":1,"main_file_link":[{"url":"https://doi.org/10.1101/2020.04.18.047886 ","open_access":"1"}],"citation":{"ama":"Kavcic B, Tkačik G, Bollenbach MT. A minimal biophysical model of combined antibiotic action. bioRxiv. 2020. doi:10.1101/2020.04.18.047886","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","ieee":"B. Kavcic, G. Tkačik, and M. T. Bollenbach, “A minimal biophysical model of combined antibiotic action,” bioRxiv. Cold Spring Harbor Laboratory, 2020.","ista":"Kavcic B, Tkačik G, Bollenbach MT. 2020. A minimal biophysical model of combined antibiotic action. bioRxiv, 10.1101/2020.04.18.047886.","short":"B. Kavcic, G. Tkačik, M.T. Bollenbach, BioRxiv (2020).","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.","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."},"publication":"bioRxiv","project":[{"_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","grant_number":"P27201-B22","name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF"},{"call_identifier":"FWF","name":"Biophysics of information processing in gene regulation","_id":"254E9036-B435-11E9-9278-68D0E5697425","grant_number":"P28844-B27"}],"article_processing_charge":"No","day":"18","month":"04"},{"publication_identifier":{"issn":["2397-334X"]},"month":"04","doi":"10.1038/s41559-020-1132-7","language":[{"iso":"eng"}],"external_id":{"isi":["000519008300005"]},"oa":1,"project":[{"_id":"267C84F4-B435-11E9-9278-68D0E5697425","name":"Biophysically realistic genotype-phenotype maps for regulatory networks"}],"isi":1,"quality_controlled":"1","file_date_updated":"2020-10-09T09:56:01Z","related_material":{"record":[{"id":"8155","relation":"dissertation_contains","status":"public"},{"id":"7383","status":"public","relation":"research_data"},{"relation":"research_data","status":"public","id":"7016"},{"id":"8653","status":"public","relation":"used_in_publication"}],"link":[{"description":"News on IST Homepage","relation":"press_release","url":"https://ist.ac.at/en/news/how-to-thrive-without-gene-regulation/"}]},"author":[{"full_name":"Tomanek, Isabella","orcid":"0000-0001-6197-363X","id":"3981F020-F248-11E8-B48F-1D18A9856A87","last_name":"Tomanek","first_name":"Isabella"},{"full_name":"Grah, Rok","id":"483E70DE-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-2539-3560","first_name":"Rok","last_name":"Grah"},{"last_name":"Lagator","first_name":"M.","full_name":"Lagator, M."},{"first_name":"A. M. C.","last_name":"Andersson","full_name":"Andersson, A. M. C."},{"full_name":"Bollback, Jonathan P","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-4624-4612","first_name":"Jonathan P","last_name":"Bollback"},{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","first_name":"Gašper","last_name":"Tkačik","full_name":"Tkačik, Gašper"},{"id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052","first_name":"Calin C","last_name":"Guet","full_name":"Guet, Calin C"}],"volume":4,"date_created":"2020-04-08T15:20:53Z","date_updated":"2024-03-28T23:30:37Z","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.","year":"2020","publisher":"Springer Nature","department":[{"_id":"GaTk"},{"_id":"CaGu"}],"publication_status":"published","article_processing_charge":"No","has_accepted_license":"1","day":"01","scopus_import":"1","date_published":"2020-04-01T00:00:00Z","citation":{"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.","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.","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.","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","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.","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","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."},"publication":"Nature Ecology & Evolution","page":"612-625","article_type":"original","issue":"4","abstract":[{"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.","lang":"eng"}],"type":"journal_article","file":[{"creator":"dernst","file_size":745242,"content_type":"application/pdf","file_name":"2020_NatureEcolEvo_Tomanek.pdf","access_level":"open_access","date_created":"2020-10-09T09:56:01Z","date_updated":"2020-10-09T09:56:01Z","success":1,"checksum":"ef3bbf42023e30b2c24a6278025d2040","file_id":"8640","relation":"main_file"}],"oa_version":"Submitted Version","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","_id":"7652","intvolume":" 4","status":"public","ddc":["570"],"title":"Gene amplification as a form of population-level gene expression regulation"},{"day":"18","month":"12","article_processing_charge":"No","date_published":"2019-12-18T00:00:00Z","language":[{"iso":"eng"}],"publication":"arXiv:1912.08579","citation":{"short":"W. Bialek, T. Gregor, G. Tkačik, ArXiv:1912.08579 (n.d.).","mla":"Bialek, William, et al. “Action at a Distance in Transcriptional Regulation.” ArXiv:1912.08579, ArXiv.","chicago":"Bialek, William, Thomas Gregor, and Gašper Tkačik. “Action at a Distance in Transcriptional Regulation.” ArXiv:1912.08579. ArXiv, n.d.","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.","apa":"Bialek, W., Gregor, T., & Tkačik, G. (n.d.). Action at a distance in transcriptional regulation. arXiv:1912.08579. ArXiv.","ista":"Bialek W, Gregor T, Tkačik G. Action at a distance in transcriptional regulation. arXiv:1912.08579, ."},"main_file_link":[{"url":"https://arxiv.org/abs/1912.08579","open_access":"1"}],"external_id":{"arxiv":["1912.08579"]},"oa":1,"page":"5","project":[{"grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF"}],"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"}],"type":"preprint","author":[{"last_name":"Bialek","first_name":"William","full_name":"Bialek, William"},{"full_name":"Gregor, Thomas","first_name":"Thomas","last_name":"Gregor"},{"full_name":"Tkačik, Gašper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkačik","first_name":"Gašper"}],"date_updated":"2021-01-12T08:14:09Z","date_created":"2020-02-28T10:57:08Z","oa_version":"Preprint","year":"2019","_id":"7552","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_status":"submitted","title":"Action at a distance in transcriptional regulation","status":"public","publisher":"ArXiv","department":[{"_id":"GaTk"}]}]