[{"article_number":"e1008529","file":[{"date_updated":"2021-02-04T12:30:48Z","file_size":3690053,"access_level":"open_access","file_name":"2021_PlosComBio_Kavcic.pdf","success":1,"checksum":"e29f2b42651bef8e034781de8781ffac","relation":"main_file","creator":"dernst","content_type":"application/pdf","file_id":"9092","date_created":"2021-02-04T12:30:48Z"}],"oa":1,"quality_controlled":"1","month":"01","publication":"PLOS Computational Biology","date_updated":"2024-02-21T12:41:41Z","publisher":"Public Library of Science","doi":"10.1371/journal.pcbi.1008529","article_processing_charge":"Yes","external_id":{"isi":["000608045000010"]},"article_type":"original","oa_version":"Published Version","volume":17,"date_published":"2021-01-07T00:00:00Z","type":"journal_article","project":[{"call_identifier":"FWF","name":"Revealing the mechanisms underlying drug interactions","grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425"},{"_id":"254E9036-B435-11E9-9278-68D0E5697425","grant_number":"P28844-B27","call_identifier":"FWF","name":"Biophysics of information processing in gene regulation"}],"department":[{"_id":"GaTk"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"year":"2021","ddc":["570"],"language":[{"iso":"eng"}],"related_material":{"record":[{"status":"public","relation":"earlier_version","id":"7673"},{"relation":"research_data","status":"public","id":"8930"}]},"publication_status":"published","day":"07","license":"https://creativecommons.org/licenses/by/4.0/","date_created":"2021-01-08T07:16:18Z","keyword":["Modelling and Simulation","Genetics","Molecular Biology","Antibiotics","Drug interactions"],"author":[{"id":"350F91D2-F248-11E8-B48F-1D18A9856A87","first_name":"Bor","full_name":"Kavcic, Bor","last_name":"Kavcic","orcid":"0000-0001-6041-254X"},{"last_name":"Tkačik","orcid":"0000-0002-6699-1455","first_name":"Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper"},{"first_name":"Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","full_name":"Bollenbach, Tobias","orcid":"0000-0003-4398-476X","last_name":"Bollenbach"}],"acknowledgement":"This work was supported in part by Tum stipend of Knafelj foundation (to B.K.), Austrian Science Fund (FWF) standalone grants P 27201-B22 (to T.B.) and P 28844(to G.T.), HFSP program Grant RGP0042/2013 (to T.B.), German Research Foundation (DFG) individual grant BO 3502/2-1 (to T.B.), and German Research Foundation (DFG) Collaborative Research Centre (SFB) 1310 (to T.B.). ","_id":"8997","title":"Minimal biophysical model of combined antibiotic action","abstract":[{"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.","lang":"eng"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","has_accepted_license":"1","citation":{"mla":"Kavcic, Bor, et al. “Minimal Biophysical Model of Combined Antibiotic Action.” <i>PLOS Computational Biology</i>, vol. 17, e1008529, Public Library of Science, 2021, doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1008529\">10.1371/journal.pcbi.1008529</a>.","ama":"Kavcic B, Tkačik G, Bollenbach MT. Minimal biophysical model of combined antibiotic action. <i>PLOS Computational Biology</i>. 2021;17. doi:<a href=\"https://doi.org/10.1371/journal.pcbi.1008529\">10.1371/journal.pcbi.1008529</a>","chicago":"Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “Minimal Biophysical Model of Combined Antibiotic Action.” <i>PLOS Computational Biology</i>. Public Library of Science, 2021. <a href=\"https://doi.org/10.1371/journal.pcbi.1008529\">https://doi.org/10.1371/journal.pcbi.1008529</a>.","apa":"Kavcic, B., Tkačik, G., &#38; Bollenbach, M. T. (2021). Minimal biophysical model of combined antibiotic action. <i>PLOS Computational Biology</i>. Public Library of Science. <a href=\"https://doi.org/10.1371/journal.pcbi.1008529\">https://doi.org/10.1371/journal.pcbi.1008529</a>","ista":"Kavcic B, Tkačik G, Bollenbach MT. 2021. Minimal biophysical model of combined antibiotic action. PLOS Computational Biology. 17, e1008529.","ieee":"B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Minimal biophysical model of combined antibiotic action,” <i>PLOS Computational Biology</i>, vol. 17. Public Library of Science, 2021.","short":"B. Kavcic, G. Tkačik, M.T. Bollenbach, PLOS Computational Biology 17 (2021)."},"intvolume":"        17","status":"public","file_date_updated":"2021-02-04T12:30:48Z","isi":1,"publication_identifier":{"issn":["1553-7358"]}},{"oa":1,"file":[{"creator":"bkavcic","relation":"main_file","content_type":"application/pdf","file_id":"9284","date_created":"2021-03-23T10:12:58Z","date_updated":"2021-03-23T10:12:58Z","file_size":1390469,"access_level":"open_access","file_name":"elife-65993-v2.pdf","success":1,"checksum":"3c2f44058c2dd45a5a1027f09d263f8e"}],"quality_controlled":"1","article_number":"e65993","month":"03","date_updated":"2024-02-21T12:41:57Z","publisher":"eLife Sciences Publications","doi":"10.7554/elife.65993","publication":"eLife","article_processing_charge":"Yes","external_id":{"isi":["000631050900001"]},"article_type":"original","oa_version":"Published Version","type":"journal_article","project":[{"grant_number":"628377","_id":"2517526A-B435-11E9-9278-68D0E5697425","name":"The Systems Biology of Transcriptional Read-Through in Bacteria: from Synthetic Networks to Genomic Studies","call_identifier":"FP7"},{"grant_number":"I03901","_id":"268BFA92-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"CyberCircuits: Cybergenetic circuits to test composability of gene networks"}],"date_published":"2021-03-08T00:00:00Z","volume":10,"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"department":[{"_id":"GaTk"},{"_id":"CaGu"}],"related_material":{"record":[{"status":"public","relation":"research_data","id":"8951"}]},"ddc":["570"],"year":"2021","language":[{"iso":"eng"}],"day":"08","publication_status":"published","date_created":"2021-03-23T10:11:46Z","keyword":["Genetics and Molecular Biology"],"author":[{"last_name":"Nagy-Staron","orcid":"0000-0002-1391-8377","first_name":"Anna A","id":"3ABC5BA6-F248-11E8-B48F-1D18A9856A87","full_name":"Nagy-Staron, Anna A"},{"first_name":"Kathrin","id":"3AEC8556-F248-11E8-B48F-1D18A9856A87","full_name":"Tomasek, Kathrin","last_name":"Tomasek","orcid":"0000-0003-3768-877X"},{"first_name":"Caroline","full_name":"Caruso Carter, Caroline","last_name":"Caruso Carter"},{"full_name":"Sonnleitner, Elisabeth","first_name":"Elisabeth","last_name":"Sonnleitner"},{"full_name":"Kavcic, Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","first_name":"Bor","orcid":"0000-0001-6041-254X","last_name":"Kavcic"},{"last_name":"Paixão","first_name":"Tiago","full_name":"Paixão, Tiago"},{"orcid":"0000-0001-6220-2052","last_name":"Guet","full_name":"Guet, Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","first_name":"Calin C"}],"acknowledgement":"We thank J Bollback, L Hurst, M Lagator, C Nizak, O Rivoire, M Savageau, G Tkacik, and B Vicozo\r\nfor helpful discussions; A Dolinar and A Greshnova for technical assistance; T Bollenbach for supplying the strain JW0336; C Rusnac, and members of the Guet lab for comments. The research leading to these results has received funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement n˚\r\n628377 (ANS) and an Austrian Science Fund (FWF) grant n˚ I 3901-B32 (CCG).","title":"Local genetic context shapes the function of a gene regulatory network","_id":"9283","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","abstract":[{"text":"Gene expression levels are influenced by multiple coexisting molecular mechanisms. Some of these interactions such as those of transcription factors and promoters have been studied extensively. However, predicting phenotypes of gene regulatory networks (GRNs) remains a major challenge. Here, we use a well-defined synthetic GRN to study in Escherichia coli how network phenotypes depend on local genetic context, i.e. the genetic neighborhood of a transcription factor and its relative position. We show that one GRN with fixed topology can display not only quantitatively but also qualitatively different phenotypes, depending solely on the local genetic context of its components. Transcriptional read-through is the main molecular mechanism that places one transcriptional unit (TU) within two separate regulons without the need for complex regulatory sequences. We propose that relative order of individual TUs, with its potential for combinatorial complexity, plays an important role in shaping phenotypes of GRNs.","lang":"eng"}],"citation":{"ama":"Nagy-Staron AA, Tomasek K, Caruso Carter C, et al. Local genetic context shapes the function of a gene regulatory network. <i>eLife</i>. 2021;10. doi:<a href=\"https://doi.org/10.7554/elife.65993\">10.7554/elife.65993</a>","mla":"Nagy-Staron, Anna A., et al. “Local Genetic Context Shapes the Function of a Gene Regulatory Network.” <i>ELife</i>, vol. 10, e65993, eLife Sciences Publications, 2021, doi:<a href=\"https://doi.org/10.7554/elife.65993\">10.7554/elife.65993</a>.","chicago":"Nagy-Staron, Anna A, Kathrin Tomasek, Caroline Caruso Carter, Elisabeth Sonnleitner, Bor Kavcic, Tiago Paixão, and Calin C Guet. “Local Genetic Context Shapes the Function of a Gene Regulatory Network.” <i>ELife</i>. eLife Sciences Publications, 2021. <a href=\"https://doi.org/10.7554/elife.65993\">https://doi.org/10.7554/elife.65993</a>.","ista":"Nagy-Staron AA, Tomasek K, Caruso Carter C, Sonnleitner E, Kavcic B, Paixão T, Guet CC. 2021. Local genetic context shapes the function of a gene regulatory network. eLife. 10, e65993.","apa":"Nagy-Staron, A. A., Tomasek, K., Caruso Carter, C., Sonnleitner, E., Kavcic, B., Paixão, T., &#38; Guet, C. C. (2021). Local genetic context shapes the function of a gene regulatory network. <i>ELife</i>. eLife Sciences Publications. <a href=\"https://doi.org/10.7554/elife.65993\">https://doi.org/10.7554/elife.65993</a>","short":"A.A. Nagy-Staron, K. Tomasek, C. Caruso Carter, E. Sonnleitner, B. Kavcic, T. Paixão, C.C. Guet, ELife 10 (2021).","ieee":"A. A. Nagy-Staron <i>et al.</i>, “Local genetic context shapes the function of a gene regulatory network,” <i>eLife</i>, vol. 10. eLife Sciences Publications, 2021."},"intvolume":"        10","has_accepted_license":"1","status":"public","ec_funded":1,"file_date_updated":"2021-03-23T10:12:58Z","isi":1,"publication_identifier":{"issn":["2050-084X"]}},{"has_accepted_license":"1","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2112.13558"}],"citation":{"apa":"Kavcic, B., &#38; Tkačik, G. (n.d.). Token-driven totally asymmetric simple exclusion process. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2112.13558\">https://doi.org/10.48550/arXiv.2112.13558</a>","ista":"Kavcic B, Tkačik G. Token-driven totally asymmetric simple exclusion process. arXiv, 2112.13558.","ieee":"B. Kavcic and G. Tkačik, “Token-driven totally asymmetric simple exclusion process,” <i>arXiv</i>. .","short":"B. Kavcic, G. Tkačik, ArXiv (n.d.).","mla":"Kavcic, Bor, and Gašper Tkačik. “Token-Driven Totally Asymmetric Simple Exclusion Process.” <i>ArXiv</i>, 2112.13558, doi:<a href=\"https://doi.org/10.48550/arXiv.2112.13558\">10.48550/arXiv.2112.13558</a>.","ama":"Kavcic B, Tkačik G. Token-driven totally asymmetric simple exclusion process. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2112.13558\">10.48550/arXiv.2112.13558</a>","chicago":"Kavcic, Bor, and Gašper Tkačik. “Token-Driven Totally Asymmetric Simple Exclusion Process.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2112.13558\">https://doi.org/10.48550/arXiv.2112.13558</a>."},"status":"public","acknowledgement":"B.K. thanks Stefano Elefante, Simon Rella, and Michal Hledík for their help with the usage of the cluster. B.K. additionally thanks Călin Guet and his group for help and advice. We thank M. Hennessey-Wesen for constructive comments on the manuscript. We thank Ankita Gupta (Indian Institute of Technology) for spotting a typographical error in Eq. (49) in the preprint version of this paper.","abstract":[{"lang":"eng","text":"We consider a totally asymmetric simple exclusion process (TASEP) consisting of particles on a lattice that require binding by a \"token\" to move. Using a combination of theory and simulations, we address the following questions: (i) How token binding kinetics affects the current-density relation; (ii) How the current-density relation depends on the scarcity of tokens; (iii) How tokens propagate the effects of the locally-imposed disorder (such a slow site) over the entire lattice; (iv) How a shared pool of tokens couples concurrent TASEPs running on multiple lattices; (v) How our results translate to TASEPs with open boundaries that exchange particles with the reservoir. Since real particle motion (including in systems that inspired the standard TASEP model, e.g., protein synthesis or movement of molecular motors) is often catalyzed, regulated, actuated, or otherwise mediated, the token-driven TASEP dynamics analyzed in this paper should allow for a better understanding of real systems and enable a closer match between TASEP theory and experimental observations."}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"10579","title":"Token-driven totally asymmetric simple exclusion process","license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","date_created":"2021-12-28T06:52:09Z","arxiv":1,"publication_status":"submitted","day":"27","author":[{"orcid":"0000-0001-6041-254X","last_name":"Kavcic","full_name":"Kavcic, Bor","first_name":"Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Tkačik, Gašper","first_name":"Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6699-1455","last_name":"Tkačik"}],"tmp":{"image":"/images/cc_by_nc_nd.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","short":"CC BY-NC-ND (4.0)"},"department":[{"_id":"GaTk"}],"language":[{"iso":"eng"}],"ddc":["530"],"year":"2021","external_id":{"arxiv":["2112.13558"]},"oa_version":"Preprint","type":"preprint","date_published":"2021-12-27T00:00:00Z","month":"12","article_number":"2112.13558","oa":1,"article_processing_charge":"No","publication":"arXiv","doi":"10.48550/arXiv.2112.13558","date_updated":"2023-05-03T10:54:05Z"},{"external_id":{"isi":["000562769300008"]},"article_type":"original","oa_version":"Published Version","date_published":"2020-08-11T00:00:00Z","project":[{"call_identifier":"FWF","name":"Revealing the mechanisms underlying drug interactions","grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FWF","name":"Biophysics of information processing in gene regulation","_id":"254E9036-B435-11E9-9278-68D0E5697425","grant_number":"P28844-B27"}],"type":"journal_article","volume":11,"file":[{"file_size":1965672,"date_updated":"2020-08-17T07:36:57Z","checksum":"986bebb308850a55850028d3d2b5b664","success":1,"access_level":"open_access","file_name":"2020_NatureComm_Kavcic.pdf","relation":"main_file","creator":"dernst","date_created":"2020-08-17T07:36:57Z","file_id":"8275","content_type":"application/pdf"}],"quality_controlled":"1","oa":1,"article_number":"4013","month":"08","date_updated":"2024-03-25T23:30:05Z","publisher":"Springer Nature","doi":"10.1038/s41467-020-17734-z","publication":"Nature Communications","article_processing_charge":"No","day":"11","publication_status":"published","date_created":"2020-08-12T09:13:50Z","author":[{"id":"350F91D2-F248-11E8-B48F-1D18A9856A87","first_name":"Bor","full_name":"Kavcic, Bor","orcid":"0000-0001-6041-254X","last_name":"Kavcic"},{"first_name":"Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper","orcid":"0000-0002-6699-1455","last_name":"Tkačik"},{"last_name":"Bollenbach","orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Tobias","first_name":"Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87"}],"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"department":[{"_id":"GaTk"}],"related_material":{"record":[{"status":"public","relation":"dissertation_contains","id":"8657"}]},"language":[{"iso":"eng"}],"year":"2020","ddc":["570"],"citation":{"ama":"Kavcic B, Tkačik G, Bollenbach MT. Mechanisms of drug interactions between translation-inhibiting antibiotics. <i>Nature Communications</i>. 2020;11. doi:<a href=\"https://doi.org/10.1038/s41467-020-17734-z\">10.1038/s41467-020-17734-z</a>","mla":"Kavcic, Bor, et al. “Mechanisms of Drug Interactions between Translation-Inhibiting Antibiotics.” <i>Nature Communications</i>, vol. 11, 4013, Springer Nature, 2020, doi:<a href=\"https://doi.org/10.1038/s41467-020-17734-z\">10.1038/s41467-020-17734-z</a>.","chicago":"Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “Mechanisms of Drug Interactions between Translation-Inhibiting Antibiotics.” <i>Nature Communications</i>. Springer Nature, 2020. <a href=\"https://doi.org/10.1038/s41467-020-17734-z\">https://doi.org/10.1038/s41467-020-17734-z</a>.","ista":"Kavcic B, Tkačik G, Bollenbach MT. 2020. Mechanisms of drug interactions between translation-inhibiting antibiotics. Nature Communications. 11, 4013.","apa":"Kavcic, B., Tkačik, G., &#38; Bollenbach, M. T. (2020). Mechanisms of drug interactions between translation-inhibiting antibiotics. <i>Nature Communications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41467-020-17734-z\">https://doi.org/10.1038/s41467-020-17734-z</a>","short":"B. Kavcic, G. Tkačik, M.T. Bollenbach, Nature Communications 11 (2020).","ieee":"B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Mechanisms of drug interactions between translation-inhibiting antibiotics,” <i>Nature Communications</i>, vol. 11. Springer Nature, 2020."},"intvolume":"        11","has_accepted_license":"1","status":"public","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.","title":"Mechanisms of drug interactions between translation-inhibiting antibiotics","_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."}],"publication_identifier":{"issn":["2041-1723"]},"file_date_updated":"2020-08-17T07:36:57Z","isi":1},{"oa_version":"Published Version","type":"dissertation","date_published":"2020-10-14T00:00:00Z","file":[{"access_level":"open_access","file_name":"kavcicB_thesis202009.pdf","checksum":"d708ecd62b6fcc3bc1feb483b8dbe9eb","date_updated":"2021-10-07T22:30:03Z","file_size":52636162,"content_type":"application/pdf","embargo":"2021-10-06","file_id":"8663","date_created":"2020-10-15T06:41:20Z","creator":"bkavcic","relation":"main_file"},{"relation":"source_file","creator":"bkavcic","content_type":"application/zip","date_created":"2020-10-15T06:41:53Z","file_id":"8664","date_updated":"2021-10-07T22:30:03Z","file_size":321681247,"embargo_to":"open_access","file_name":"2020b.zip","access_level":"closed","checksum":"bb35f2352a04db19164da609f00501f3"}],"oa":1,"month":"10","publisher":"Institute of Science and Technology Austria","date_updated":"2023-09-07T13:20:48Z","doi":"10.15479/AT:ISTA:8657","article_processing_charge":"No","day":"14","publication_status":"published","date_created":"2020-10-13T16:46:14Z","degree_awarded":"PhD","acknowledged_ssus":[{"_id":"LifeSc"},{"_id":"M-Shop"}],"alternative_title":["ISTA Thesis"],"page":"271","author":[{"id":"350F91D2-F248-11E8-B48F-1D18A9856A87","first_name":"Bor","full_name":"Kavcic, Bor","last_name":"Kavcic","orcid":"0000-0001-6041-254X"}],"supervisor":[{"id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper","full_name":"Tkačik, Gašper","last_name":"Tkačik","orcid":"0000-0002-6699-1455"},{"full_name":"Bollenbach, Mark Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","first_name":"Mark Tobias","orcid":"0000-0003-4398-476X","last_name":"Bollenbach"}],"department":[{"_id":"GaTk"}],"related_material":{"record":[{"relation":"part_of_dissertation","status":"public","id":"7673"},{"relation":"part_of_dissertation","status":"public","id":"8250"}]},"ddc":["571","530","570"],"year":"2020","language":[{"iso":"eng"}],"citation":{"ista":"Kavcic B. 2020. Perturbations of protein synthesis: from antibiotics to genetics and physiology. Institute of Science and Technology Austria.","apa":"Kavcic, B. (2020). <i>Perturbations of protein synthesis: from antibiotics to genetics and physiology</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:8657\">https://doi.org/10.15479/AT:ISTA:8657</a>","short":"B. Kavcic, Perturbations of Protein Synthesis: From Antibiotics to Genetics and Physiology, Institute of Science and Technology Austria, 2020.","ieee":"B. Kavcic, “Perturbations of protein synthesis: from antibiotics to genetics and physiology,” Institute of Science and Technology Austria, 2020.","ama":"Kavcic B. Perturbations of protein synthesis: from antibiotics to genetics and physiology. 2020. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8657\">10.15479/AT:ISTA:8657</a>","mla":"Kavcic, Bor. <i>Perturbations of Protein Synthesis: From Antibiotics to Genetics and Physiology</i>. Institute of Science and Technology Austria, 2020, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8657\">10.15479/AT:ISTA:8657</a>.","chicago":"Kavcic, Bor. “Perturbations of Protein Synthesis: From Antibiotics to Genetics and Physiology.” Institute of Science and Technology Austria, 2020. <a href=\"https://doi.org/10.15479/AT:ISTA:8657\">https://doi.org/10.15479/AT:ISTA:8657</a>."},"has_accepted_license":"1","status":"public","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.","title":"Perturbations of protein synthesis: from antibiotics to genetics and physiology","_id":"8657","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","abstract":[{"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.","lang":"eng"}],"publication_identifier":{"issn":["2663-337X"],"isbn":["978-3-99078-011-4"]},"file_date_updated":"2021-10-07T22:30:03Z"},{"oa":1,"file":[{"file_id":"8932","date_created":"2020-12-09T15:00:19Z","content_type":"application/zip","creator":"bkavcic","relation":"main_file","checksum":"60a818edeffaa7da1ebf5f8fbea9ba18","file_name":"PLoSCompBiol2020_datarep.zip","access_level":"open_access","success":1,"file_size":315494370,"date_updated":"2020-12-09T15:00:19Z"}],"month":"12","_id":"8930","publisher":"Institute of Science and Technology Austria","date_updated":"2024-02-21T12:41:42Z","title":"Analysis scripts and research data for the paper \"Minimal biophysical model of combined antibiotic action\"","doi":"10.15479/AT:ISTA:8930","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."}],"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","has_accepted_license":"1","citation":{"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.","short":"B. Kavcic, (2020).","apa":"Kavcic, B. (2020). Analysis scripts and research data for the paper “Minimal biophysical model of combined antibiotic action.” Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/AT:ISTA:8930\">https://doi.org/10.15479/AT:ISTA:8930</a>","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, <a href=\"https://doi.org/10.15479/AT:ISTA:8930\">10.15479/AT:ISTA:8930</a>.","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. <a href=\"https://doi.org/10.15479/AT:ISTA:8930\">https://doi.org/10.15479/AT:ISTA:8930</a>.","mla":"Kavcic, Bor. <i>Analysis Scripts and Research Data for the Paper “Minimal Biophysical Model of Combined Antibiotic Action.”</i> Institute of Science and Technology Austria, 2020, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8930\">10.15479/AT:ISTA:8930</a>.","ama":"Kavcic B. Analysis scripts and research data for the paper “Minimal biophysical model of combined antibiotic action.” 2020. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8930\">10.15479/AT:ISTA:8930</a>"},"oa_version":"Published Version","contributor":[{"contributor_type":"supervisor","orcid":"0000-0002-6699-1455","last_name":"Tkačik","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","first_name":"Gašper"},{"contributor_type":"supervisor","last_name":"Bollenbach","first_name":"Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87"}],"status":"public","date_published":"2020-12-10T00:00:00Z","type":"research_data","file_date_updated":"2020-12-09T15:00:19Z","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"department":[{"_id":"GaTk"}],"ddc":["570"],"year":"2020","related_material":{"record":[{"id":"8997","relation":"used_in_publication","status":"public"}]},"day":"10","date_created":"2020-12-09T15:04:02Z","keyword":["Escherichia coli","antibiotic combinations","translation","growth laws","drug interactions","bacterial physiology","translation inhibitors"],"author":[{"orcid":"0000-0001-6041-254X","last_name":"Kavcic","full_name":"Kavcic, Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","first_name":"Bor"}]},{"related_material":{"record":[{"id":"8997","relation":"later_version","status":"public"},{"status":"public","relation":"dissertation_contains","id":"8657"}]},"language":[{"iso":"eng"}],"year":"2020","department":[{"_id":"GaTk"}],"author":[{"orcid":"0000-0001-6041-254X","last_name":"Kavcic","full_name":"Kavcic, Bor","first_name":"Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkačik, Gašper","last_name":"Tkačik","orcid":"0000-0002-6699-1455"},{"orcid":"0000-0003-4398-476X","last_name":"Bollenbach","full_name":"Bollenbach, Tobias","first_name":"Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87"}],"day":"18","publication_status":"published","date_created":"2020-04-22T08:27:56Z","title":"A minimal biophysical model of combined antibiotic action","doi":"10.1101/2020.04.18.047886","date_updated":"2024-03-25T23:30:05Z","publisher":"Cold Spring Harbor Laboratory","publication":"bioRxiv","_id":"7673","article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"text":"Combining drugs can improve the efficacy of treatments. However, predicting the effect of drug combinations is still challenging. The combined potency of drugs determines the drug interaction, which is classified as synergistic, additive, antagonistic, or suppressive. While probabilistic, non-mechanistic models exist, there is currently no biophysical model that can predict antibiotic interactions. Here, we present a physiologically relevant model of the combined action of antibiotics that inhibit protein synthesis by targeting the ribosome. This model captures the kinetics of antibiotic binding and transport, and uses bacterial growth laws to predict growth in the presence of antibiotic combinations. We find that this biophysical model can produce all drug interaction types except suppression. We show analytically that antibiotics which cannot bind to the ribosome simultaneously generally act as substitutes for one another, leading to additive drug interactions. Previously proposed null expectations for higher-order drug interactions follow as a limiting case of our model. We further extend the model to include the effects of direct physical or allosteric interactions between individual drugs on the ribosome. Notably, such direct interactions profoundly change the combined drug effect, depending on the kinetic parameters of the drugs used. The model makes additional predictions for the effects of resistance genes on drug interactions and for interactions between ribosome-targeting antibiotics and antibiotics with other targets. These findings enhance our understanding of the interplay between drug action and cell physiology and are a key step toward a general framework for predicting drug interactions.","lang":"eng"}],"oa":1,"month":"04","status":"public","date_published":"2020-04-18T00:00:00Z","project":[{"name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF","grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425"},{"grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF"}],"type":"preprint","citation":{"ista":"Kavcic B, Tkačik G, Bollenbach MT. 2020. A minimal biophysical model of combined antibiotic action. bioRxiv, <a href=\"https://doi.org/10.1101/2020.04.18.047886\">10.1101/2020.04.18.047886</a>.","apa":"Kavcic, B., Tkačik, G., &#38; Bollenbach, M. T. (2020). A minimal biophysical model of combined antibiotic action. <i>bioRxiv</i>. Cold Spring Harbor Laboratory. <a href=\"https://doi.org/10.1101/2020.04.18.047886\">https://doi.org/10.1101/2020.04.18.047886</a>","ieee":"B. Kavcic, G. Tkačik, and M. T. Bollenbach, “A minimal biophysical model of combined antibiotic action,” <i>bioRxiv</i>. Cold Spring Harbor Laboratory, 2020.","short":"B. Kavcic, G. Tkačik, M.T. Bollenbach, BioRxiv (2020).","ama":"Kavcic B, Tkačik G, Bollenbach MT. A minimal biophysical model of combined antibiotic action. <i>bioRxiv</i>. 2020. doi:<a href=\"https://doi.org/10.1101/2020.04.18.047886\">10.1101/2020.04.18.047886</a>","mla":"Kavcic, Bor, et al. “A Minimal Biophysical Model of Combined Antibiotic Action.” <i>BioRxiv</i>, Cold Spring Harbor Laboratory, 2020, doi:<a href=\"https://doi.org/10.1101/2020.04.18.047886\">10.1101/2020.04.18.047886</a>.","chicago":"Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “A Minimal Biophysical Model of Combined Antibiotic Action.” <i>BioRxiv</i>. Cold Spring Harbor Laboratory, 2020. <a href=\"https://doi.org/10.1101/2020.04.18.047886\">https://doi.org/10.1101/2020.04.18.047886</a>."},"main_file_link":[{"url":"https://doi.org/10.1101/2020.04.18.047886 ","open_access":"1"}],"oa_version":"Preprint"},{"article_processing_charge":"No","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"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.","lang":"eng"}],"date_updated":"2024-02-21T12:40:51Z","title":"Analysis scripts and research data for the paper \"Mechanisms of drug interactions between translation-inhibiting antibiotics\"","doi":"10.15479/AT:ISTA:8097","publisher":"Institute of Science and Technology Austria","_id":"8097","month":"07","oa":1,"file":[{"date_updated":"2020-07-14T12:48:09Z","file_size":255770756,"file_name":"natComm_2020_scripts.zip","access_level":"open_access","checksum":"5c321dbbb6d4b3c85da786fd3ebbdc98","creator":"bkavcic","relation":"main_file","content_type":"application/zip","date_created":"2020-07-06T20:38:27Z","file_id":"8098"}],"type":"research_data","date_published":"2020-07-15T00:00:00Z","status":"public","contributor":[{"first_name":"Gašper","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkačik","orcid":"0000-0002-6699-1455","contributor_type":"research_group"},{"contributor_type":"research_group","last_name":"Bollenbach","first_name":"Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87"}],"oa_version":"Published Version","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. <a href=\"https://doi.org/10.15479/AT:ISTA:8097\">https://doi.org/10.15479/AT:ISTA:8097</a>.","ama":"Kavcic B. Analysis scripts and research data for the paper “Mechanisms of drug interactions between translation-inhibiting antibiotics.” 2020. doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8097\">10.15479/AT:ISTA:8097</a>","mla":"Kavcic, Bor. <i>Analysis Scripts and Research Data for the Paper “Mechanisms of Drug Interactions between Translation-Inhibiting Antibiotics.”</i> Institute of Science and Technology Austria, 2020, doi:<a href=\"https://doi.org/10.15479/AT:ISTA:8097\">10.15479/AT:ISTA:8097</a>.","short":"B. Kavcic, (2020).","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.","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, <a href=\"https://doi.org/10.15479/AT:ISTA:8097\">10.15479/AT:ISTA:8097</a>.","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. <a href=\"https://doi.org/10.15479/AT:ISTA:8097\">https://doi.org/10.15479/AT:ISTA:8097</a>"},"has_accepted_license":"1","year":"2020","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"file_date_updated":"2020-07-14T12:48:09Z","department":[{"_id":"GaTk"}],"author":[{"orcid":"0000-0001-6041-254X","last_name":"Kavcic","full_name":"Kavcic, Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","first_name":"Bor"}],"keyword":["Escherichia coli","antibiotic combinations","translation","growth laws","drug interactions","bacterial physiology","translation inhibitors"],"date_created":"2020-07-06T20:40:19Z","acknowledged_ssus":[{"_id":"LifeSc"}],"day":"15"},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","abstract":[{"text":"The main idea behind the Core Project is to teach first year students at IST scientific communication skills and let them practice by presenting their research within an interdisciplinary environment. Over the course of the first semester, students participated in seminars, where they shared their results with the colleagues from other fields and took part in discussions on relevant subjects. The main focus during this sessions was on delivering the information in a simplified and comprehensible way, going into the very basics of a subject if necessary. At the end, the students were asked to present their research in the written form to exercise their writing skills. The reports were gathered in this document. All of them were reviewed by the  teaching assistants and write-ups illustrating unique stylistic features and, in general, an outstanding level of writing skills, were honorably mentioned in the section \"Selected Reports\".","lang":"eng"}],"publisher":"IST Austria","date_updated":"2023-02-23T13:26:00Z","title":"Core Project Proceedings","_id":"8151","month":"06","file":[{"file_size":169620437,"date_updated":"2020-07-22T14:45:07Z","file_name":"Core_Project_Proceedings_mod.pdf","access_level":"local","creator":"dernst","relation":"main_file","date_created":"2020-07-22T14:45:07Z","file_id":"8152","content_type":"application/pdf"}],"extern":"1","type":"report","date_published":"2020-06-01T00:00:00Z","status":"public","oa_version":"None","citation":{"ama":"Maslov M, Kondrashov F, Artner C, et al. <i>Core Project Proceedings</i>. IST Austria; 2020.","mla":"Maslov, Mikhail, et al. <i>Core Project Proceedings</i>. IST Austria, 2020.","chicago":"Maslov, Mikhail, Fyodor Kondrashov, Christina Artner, Mike Hennessey-Wesen, Bor Kavcic, Nick N Machnik, Roshan K Satapathy, and Isabella Tomanek. <i>Core Project Proceedings</i>. IST Austria, 2020.","ista":"Maslov M, Kondrashov F, Artner C, Hennessey-Wesen M, Kavcic B, Machnik NN, Satapathy RK, Tomanek I. 2020. Core Project Proceedings, IST Austria, 425p.","apa":"Maslov, M., Kondrashov, F., Artner, C., Hennessey-Wesen, M., Kavcic, B., Machnik, N. N., … Tomanek, I. (2020). <i>Core Project Proceedings</i>. IST Austria.","short":"M. Maslov, F. Kondrashov, C. Artner, M. Hennessey-Wesen, B. Kavcic, N.N. Machnik, R.K. Satapathy, I. Tomanek, Core Project Proceedings, IST Austria, 2020.","ieee":"M. Maslov <i>et al.</i>, <i>Core Project Proceedings</i>. IST Austria, 2020."},"has_accepted_license":"1","year":"2020","ddc":["510","530","570"],"language":[{"iso":"eng"}],"file_date_updated":"2020-07-22T14:45:07Z","author":[{"full_name":"Maslov, Mikhail","first_name":"Mikhail","id":"2E65BB0E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4074-2570","last_name":"Maslov"},{"last_name":"Kondrashov","orcid":"0000-0001-8243-4694","full_name":"Kondrashov, Fyodor","first_name":"Fyodor","id":"44FDEF62-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Artner","id":"45DF286A-F248-11E8-B48F-1D18A9856A87","first_name":"Christina","full_name":"Artner, Christina"},{"last_name":"Hennessey-Wesen","id":"3F338C72-F248-11E8-B48F-1D18A9856A87","first_name":"Mike","full_name":"Hennessey-Wesen, Mike"},{"id":"350F91D2-F248-11E8-B48F-1D18A9856A87","first_name":"Bor","full_name":"Kavcic, Bor","orcid":"0000-0001-6041-254X","last_name":"Kavcic"},{"first_name":"Nick N","id":"3591A0AA-F248-11E8-B48F-1D18A9856A87","full_name":"Machnik, Nick N","last_name":"Machnik"},{"id":"46046B7A-F248-11E8-B48F-1D18A9856A87","first_name":"Roshan K","full_name":"Satapathy, Roshan K","last_name":"Satapathy"},{"first_name":"Isabella","id":"3981F020-F248-11E8-B48F-1D18A9856A87","full_name":"Tomanek, Isabella","orcid":"0000-0001-6197-363X","last_name":"Tomanek"}],"page":"425","date_created":"2020-07-22T14:48:14Z","day":"01","publication_status":"published"},{"publication_identifier":{"issn":["1744-683X"],"eissn":["1744-6848"]},"issue":"4","file_date_updated":"2020-10-09T11:00:05Z","isi":1,"scopus_import":"1","has_accepted_license":"1","intvolume":"        15","citation":{"ieee":"B. Kavcic, A. Sakashita, H. Noguchi, and P. Ziherl, “Limiting shapes of confined lipid vesicles,” <i>Soft Matter</i>, vol. 15, no. 4. Royal Society of Chemistry, pp. 602–614, 2019.","short":"B. Kavcic, A. Sakashita, H. Noguchi, P. Ziherl, Soft Matter 15 (2019) 602–614.","apa":"Kavcic, B., Sakashita, A., Noguchi, H., &#38; Ziherl, P. (2019). Limiting shapes of confined lipid vesicles. <i>Soft Matter</i>. Royal Society of Chemistry. <a href=\"https://doi.org/10.1039/c8sm01956h\">https://doi.org/10.1039/c8sm01956h</a>","ista":"Kavcic B, Sakashita A, Noguchi H, Ziherl P. 2019. Limiting shapes of confined lipid vesicles. Soft Matter. 15(4), 602–614.","chicago":"Kavcic, Bor, A. Sakashita, H. Noguchi, and P. Ziherl. “Limiting Shapes of Confined Lipid Vesicles.” <i>Soft Matter</i>. Royal Society of Chemistry, 2019. <a href=\"https://doi.org/10.1039/c8sm01956h\">https://doi.org/10.1039/c8sm01956h</a>.","mla":"Kavcic, Bor, et al. “Limiting Shapes of Confined Lipid Vesicles.” <i>Soft Matter</i>, vol. 15, no. 4, Royal Society of Chemistry, 2019, pp. 602–14, doi:<a href=\"https://doi.org/10.1039/c8sm01956h\">10.1039/c8sm01956h</a>.","ama":"Kavcic B, Sakashita A, Noguchi H, Ziherl P. Limiting shapes of confined lipid vesicles. <i>Soft Matter</i>. 2019;15(4):602-614. doi:<a href=\"https://doi.org/10.1039/c8sm01956h\">10.1039/c8sm01956h</a>"},"status":"public","pmid":1,"_id":"5817","title":"Limiting shapes of confined lipid vesicles","abstract":[{"text":"We theoretically study the shapes of lipid vesicles confined to a spherical cavity, elaborating a framework based on the so-called limiting shapes constructed from geometrically simple structural elements such as double-membrane walls and edges. Partly inspired by numerical results, the proposed non-compartmentalized and compartmentalized limiting shapes are arranged in the bilayer-couple phase diagram which is then compared to its free-vesicle counterpart. We also compute the area-difference-elasticity phase diagram of the limiting shapes and we use it to interpret shape transitions experimentally observed in vesicles confined within another vesicle. The limiting-shape framework may be generalized to theoretically investigate the structure of certain cell organelles such as the mitochondrion.","lang":"eng"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","publication_status":"published","day":"10","license":"https://creativecommons.org/licenses/by-nc-nd/3.0/","date_created":"2019-01-11T07:37:47Z","page":"602-614","author":[{"first_name":"Bor","id":"350F91D2-F248-11E8-B48F-1D18A9856A87","full_name":"Kavcic, Bor","last_name":"Kavcic","orcid":"0000-0001-6041-254X"},{"last_name":"Sakashita","first_name":"A.","full_name":"Sakashita, A."},{"first_name":"H.","full_name":"Noguchi, H.","last_name":"Noguchi"},{"last_name":"Ziherl","full_name":"Ziherl, P.","first_name":"P."}],"tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0)","short":"CC BY-NC-ND (3.0)","image":"/images/cc_by_nc_nd.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode"},"department":[{"_id":"GaTk"}],"language":[{"iso":"eng"}],"year":"2019","ddc":["530"],"article_type":"original","external_id":{"isi":["000457329700003"],"pmid":["30629082"]},"oa_version":"Submitted Version","volume":15,"type":"journal_article","date_published":"2019-01-10T00:00:00Z","oa":1,"quality_controlled":"1","file":[{"checksum":"614c337d6424ccd3d48d1b1f9513510d","success":1,"file_name":"lmt_sftmtr_V8.pdf","access_level":"open_access","file_size":5370762,"date_updated":"2020-10-09T11:00:05Z","date_created":"2020-10-09T11:00:05Z","file_id":"8641","content_type":"application/pdf","relation":"main_file","creator":"bkavcic"}],"month":"01","publication":"Soft Matter","date_updated":"2023-09-13T08:47:16Z","doi":"10.1039/c8sm01956h","publisher":"Royal Society of Chemistry","article_processing_charge":"No"}]