--- _id: '8657' 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." acknowledged_ssus: - _id: LifeSc - _id: M-Shop 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. alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Bor full_name: Kavcic, Bor id: 350F91D2-F248-11E8-B48F-1D18A9856A87 last_name: Kavcic orcid: 0000-0001-6041-254X 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' 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.' 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.' 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.' short: 'B. Kavcic, Perturbations of Protein Synthesis: From Antibiotics to Genetics and Physiology, Institute of Science and Technology Austria, 2020.' date_created: 2020-10-13T16:46:14Z date_published: 2020-10-14T00:00:00Z date_updated: 2023-09-07T13:20:48Z day: '14' ddc: - '571' - '530' - '570' degree_awarded: PhD department: - _id: GaTk doi: 10.15479/AT:ISTA:8657 file: - access_level: open_access checksum: d708ecd62b6fcc3bc1feb483b8dbe9eb content_type: application/pdf creator: bkavcic date_created: 2020-10-15T06:41:20Z date_updated: 2021-10-07T22:30:03Z embargo: 2021-10-06 file_id: '8663' file_name: kavcicB_thesis202009.pdf file_size: 52636162 relation: main_file - access_level: closed checksum: bb35f2352a04db19164da609f00501f3 content_type: application/zip creator: bkavcic date_created: 2020-10-15T06:41:53Z date_updated: 2021-10-07T22:30:03Z embargo_to: open_access file_id: '8664' file_name: 2020b.zip file_size: 321681247 relation: source_file file_date_updated: 2021-10-07T22:30:03Z has_accepted_license: '1' language: - iso: eng month: '10' oa: 1 oa_version: Published Version page: '271' publication_identifier: isbn: - 978-3-99078-011-4 issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '7673' relation: part_of_dissertation status: public - id: '8250' relation: part_of_dissertation status: public status: public supervisor: - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X title: 'Perturbations of protein synthesis: from antibiotics to genetics and physiology' type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2020' ... --- _id: '8250' 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.' 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." article_number: '4013' article_processing_charge: No article_type: original author: - first_name: Bor full_name: Kavcic, Bor id: 350F91D2-F248-11E8-B48F-1D18A9856A87 last_name: Kavcic orcid: 0000-0001-6041-254X - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 - first_name: Tobias full_name: Bollenbach, Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: Kavcic B, Tkačik G, Bollenbach MT. Mechanisms of drug interactions between translation-inhibiting antibiotics. Nature Communications. 2020;11. doi:10.1038/s41467-020-17734-z apa: Kavcic, B., Tkačik, G., & Bollenbach, M. T. (2020). Mechanisms of drug interactions between translation-inhibiting antibiotics. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-020-17734-z 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. ieee: B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Mechanisms of drug interactions between translation-inhibiting antibiotics,” Nature Communications, vol. 11. Springer Nature, 2020. ista: Kavcic B, Tkačik G, Bollenbach MT. 2020. Mechanisms of drug interactions between translation-inhibiting antibiotics. Nature Communications. 11, 4013. 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. short: B. Kavcic, G. Tkačik, M.T. Bollenbach, Nature Communications 11 (2020). date_created: 2020-08-12T09:13:50Z date_published: 2020-08-11T00:00:00Z date_updated: 2024-03-27T23:30:08Z day: '11' ddc: - '570' department: - _id: GaTk doi: 10.1038/s41467-020-17734-z external_id: isi: - '000562769300008' file: - access_level: open_access checksum: 986bebb308850a55850028d3d2b5b664 content_type: application/pdf creator: dernst date_created: 2020-08-17T07:36:57Z date_updated: 2020-08-17T07:36:57Z file_id: '8275' file_name: 2020_NatureComm_Kavcic.pdf file_size: 1965672 relation: main_file success: 1 file_date_updated: 2020-08-17T07:36:57Z has_accepted_license: '1' intvolume: ' 11' isi: 1 language: - iso: eng month: '08' oa: 1 oa_version: Published Version project: - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: Nature Communications publication_identifier: issn: - 2041-1723 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: record: - id: '8657' relation: dissertation_contains status: public status: public title: Mechanisms of drug interactions between translation-inhibiting antibiotics tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 11 year: '2020' ... --- _id: '7673' 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. article_processing_charge: No author: - first_name: Bor full_name: Kavcic, Bor id: 350F91D2-F248-11E8-B48F-1D18A9856A87 last_name: Kavcic orcid: 0000-0001-6041-254X - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 - first_name: Tobias full_name: Bollenbach, Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X 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 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. 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. mla: Kavcic, Bor, et al. “A Minimal Biophysical Model of Combined Antibiotic Action.” BioRxiv, Cold Spring Harbor Laboratory, 2020, doi:10.1101/2020.04.18.047886. short: B. Kavcic, G. Tkačik, M.T. Bollenbach, BioRxiv (2020). date_created: 2020-04-22T08:27:56Z date_published: 2020-04-18T00:00:00Z date_updated: 2024-03-27T23:30:08Z day: '18' department: - _id: GaTk doi: 10.1101/2020.04.18.047886 language: - iso: eng main_file_link: - open_access: '1' url: 'https://doi.org/10.1101/2020.04.18.047886 ' month: '04' oa: 1 oa_version: Preprint project: - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: bioRxiv publication_status: published publisher: Cold Spring Harbor Laboratory related_material: record: - id: '8997' relation: later_version status: public - id: '8657' relation: dissertation_contains status: public status: public title: A minimal biophysical model of combined antibiotic action type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2020' ... --- _id: '7652' abstract: - lang: eng text: Organisms cope with change by taking advantage of transcriptional regulators. However, when faced with rare environments, the evolution of transcriptional regulators and their promoters may be too slow. Here, we investigate whether the intrinsic instability of gene duplication and amplification provides a generic alternative to canonical gene regulation. Using real-time monitoring of gene-copy-number mutations in Escherichia coli, we show that gene duplications and amplifications enable adaptation to fluctuating environments by rapidly generating copy-number and, therefore, expression-level polymorphisms. This amplification-mediated gene expression tuning (AMGET) occurs on timescales that are similar to canonical gene regulation and can respond to rapid environmental changes. Mathematical modelling shows that amplifications also tune gene expression in stochastic environments in which transcription-factor-based schemes are hard to evolve or maintain. The fleeting nature of gene amplifications gives rise to a generic population-level mechanism that relies on genetic heterogeneity to rapidly tune the expression of any gene, without leaving any genomic signature. 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. article_processing_charge: No article_type: original author: - first_name: Isabella full_name: Tomanek, Isabella id: 3981F020-F248-11E8-B48F-1D18A9856A87 last_name: Tomanek orcid: 0000-0001-6197-363X - first_name: Rok full_name: Grah, Rok id: 483E70DE-F248-11E8-B48F-1D18A9856A87 last_name: Grah orcid: 0000-0003-2539-3560 - first_name: M. full_name: Lagator, M. last_name: Lagator - first_name: A. M. C. full_name: Andersson, A. M. C. last_name: Andersson - first_name: Jonathan P full_name: Bollback, Jonathan P id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87 last_name: Bollback orcid: 0000-0002-4624-4612 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: 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 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 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. 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. 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. 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. date_created: 2020-04-08T15:20:53Z date_published: 2020-04-01T00:00:00Z date_updated: 2024-03-27T23:30:36Z day: '01' ddc: - '570' department: - _id: GaTk - _id: CaGu doi: 10.1038/s41559-020-1132-7 external_id: isi: - '000519008300005' file: - access_level: open_access checksum: ef3bbf42023e30b2c24a6278025d2040 content_type: application/pdf creator: dernst date_created: 2020-10-09T09:56:01Z date_updated: 2020-10-09T09:56:01Z file_id: '8640' file_name: 2020_NatureEcolEvo_Tomanek.pdf file_size: 745242 relation: main_file success: 1 file_date_updated: 2020-10-09T09:56:01Z has_accepted_license: '1' intvolume: ' 4' isi: 1 issue: '4' language: - iso: eng month: '04' oa: 1 oa_version: Submitted Version page: 612-625 project: - _id: 267C84F4-B435-11E9-9278-68D0E5697425 name: Biophysically realistic genotype-phenotype maps for regulatory networks publication: Nature Ecology & Evolution publication_identifier: issn: - 2397-334X publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: link: - description: News on IST Homepage relation: press_release url: https://ist.ac.at/en/news/how-to-thrive-without-gene-regulation/ record: - id: '8155' relation: dissertation_contains status: public - id: '7383' relation: research_data status: public - id: '7016' relation: research_data status: public - id: '8653' relation: used_in_publication status: public scopus_import: '1' status: public title: Gene amplification as a form of population-level gene expression regulation type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 4 year: '2020' ... --- _id: '7552' abstract: - lang: eng 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. ' article_processing_charge: No author: - first_name: William full_name: Bialek, William last_name: Bialek - first_name: Thomas full_name: Gregor, Thomas last_name: Gregor - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Bialek W, Gregor T, Tkačik G. Action at a distance in transcriptional regulation. arXiv:191208579. apa: Bialek, W., Gregor, T., & Tkačik, G. (n.d.). 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. ieee: W. Bialek, T. Gregor, and G. Tkačik, “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, . mla: Bialek, William, et al. “Action at a Distance in Transcriptional Regulation.” ArXiv:1912.08579, ArXiv. short: W. Bialek, T. Gregor, G. Tkačik, ArXiv:1912.08579 (n.d.). date_created: 2020-02-28T10:57:08Z date_published: 2019-12-18T00:00:00Z date_updated: 2021-01-12T08:14:09Z day: '18' department: - _id: GaTk external_id: arxiv: - '1912.08579' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1912.08579 month: '12' oa: 1 oa_version: Preprint page: '5' project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: arXiv:1912.08579 publication_status: submitted publisher: ArXiv status: public title: Action at a distance in transcriptional regulation type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2019' ... --- _id: '5945' abstract: - lang: eng text: In developing organisms, spatially prescribed cell identities are thought to be determined by the expression levels of multiple genes. Quantitative tests of this idea, however, require a theoretical framework capable of exposing the rules and precision of cell specification over developmental time. We use the gap gene network in the early fly embryo as an example to show how expression levels of the four gap genes can be jointly decoded into an optimal specification of position with 1% accuracy. The decoder correctly predicts, with no free parameters, the dynamics of pair-rule expression patterns at different developmental time points and in various mutant backgrounds. Precise cellular identities are thus available at the earliest stages of development, contrasting the prevailing view of positional information being slowly refined across successive layers of the patterning network. Our results suggest that developmental enhancers closely approximate a mathematically optimal decoding strategy. article_processing_charge: No article_type: original author: - first_name: Mariela D. full_name: Petkova, Mariela D. last_name: Petkova - first_name: Gasper full_name: Tkacik, Gasper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkacik orcid: 0000-0002-6699-1455 - first_name: William full_name: Bialek, William last_name: Bialek - first_name: Eric F. full_name: Wieschaus, Eric F. last_name: Wieschaus - first_name: Thomas full_name: Gregor, Thomas last_name: Gregor citation: ama: Petkova MD, Tkačik G, Bialek W, Wieschaus EF, Gregor T. Optimal decoding of cellular identities in a genetic network. Cell. 2019;176(4):844-855.e15. doi:10.1016/j.cell.2019.01.007 apa: Petkova, M. D., Tkačik, G., Bialek, W., Wieschaus, E. F., & Gregor, T. (2019). Optimal decoding of cellular identities in a genetic network. Cell. Cell Press. https://doi.org/10.1016/j.cell.2019.01.007 chicago: Petkova, Mariela D., Gašper Tkačik, William Bialek, Eric F. Wieschaus, and Thomas Gregor. “Optimal Decoding of Cellular Identities in a Genetic Network.” Cell. Cell Press, 2019. https://doi.org/10.1016/j.cell.2019.01.007. ieee: M. D. Petkova, G. Tkačik, W. Bialek, E. F. Wieschaus, and T. Gregor, “Optimal decoding of cellular identities in a genetic network,” Cell, vol. 176, no. 4. Cell Press, p. 844–855.e15, 2019. ista: Petkova MD, Tkačik G, Bialek W, Wieschaus EF, Gregor T. 2019. Optimal decoding of cellular identities in a genetic network. Cell. 176(4), 844–855.e15. mla: Petkova, Mariela D., et al. “Optimal Decoding of Cellular Identities in a Genetic Network.” Cell, vol. 176, no. 4, Cell Press, 2019, p. 844–855.e15, doi:10.1016/j.cell.2019.01.007. short: M.D. Petkova, G. Tkačik, W. Bialek, E.F. Wieschaus, T. Gregor, Cell 176 (2019) 844–855.e15. date_created: 2019-02-10T22:59:16Z date_published: 2019-02-07T00:00:00Z date_updated: 2023-08-24T14:42:47Z day: '07' department: - _id: GaTk doi: 10.1016/j.cell.2019.01.007 external_id: isi: - '000457969200015' pmid: - '30712870' intvolume: ' 176' isi: 1 issue: '4' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1016/j.cell.2019.01.007 month: '02' oa: 1 oa_version: Published Version page: 844-855.e15 pmid: 1 project: - _id: 254E9036-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P28844-B27 name: Biophysics of information processing in gene regulation publication: Cell publication_status: published publisher: Cell Press quality_controlled: '1' related_material: link: - description: News on IST Homepage relation: press_release url: https://ist.ac.at/en/news/cells-find-their-identity-using-a-mathematically-optimal-strategy/ scopus_import: '1' status: public title: Optimal decoding of cellular identities in a genetic network type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 176 year: '2019' ... --- _id: '6049' abstract: - lang: eng text: 'In this article it is shown that large systems with many interacting units endowing multiple phases display self-oscillations in the presence of linear feedback between the control and order parameters, where an Andronov–Hopf bifurcation takes over the phase transition. This is simply illustrated through the mean field Landau theory whose feedback dynamics turn out to be described by the Van der Pol equation and it is then validated for the fully connected Ising model following heat bath dynamics. Despite its simplicity, this theory accounts potentially for a rich range of phenomena: here it is applied to describe in a stylized way (i) excess demand-price cycles due to strong herding in a simple agent-based market model; (ii) congestion waves in queuing networks triggered by user feedback to delays in overloaded conditions; and (iii) metabolic network oscillations resulting from cell growth control in a bistable phenotypic landscape.' article_number: '045002' article_processing_charge: Yes (in subscription journal) author: - first_name: Daniele full_name: De Martino, Daniele id: 3FF5848A-F248-11E8-B48F-1D18A9856A87 last_name: De Martino orcid: 0000-0002-5214-4706 citation: ama: 'De Martino D. Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. 2019;52(4). doi:10.1088/1751-8121/aaf2dd' apa: 'De Martino, D. (2019). Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. IOP Publishing. https://doi.org/10.1088/1751-8121/aaf2dd' chicago: 'De Martino, Daniele. “Feedback-Induced Self-Oscillations in Large Interacting Systems Subjected to Phase Transitions.” Journal of Physics A: Mathematical and Theoretical. IOP Publishing, 2019. https://doi.org/10.1088/1751-8121/aaf2dd.' ieee: 'D. De Martino, “Feedback-induced self-oscillations in large interacting systems subjected to phase transitions,” Journal of Physics A: Mathematical and Theoretical, vol. 52, no. 4. IOP Publishing, 2019.' ista: 'De Martino D. 2019. Feedback-induced self-oscillations in large interacting systems subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical. 52(4), 045002.' mla: 'De Martino, Daniele. “Feedback-Induced Self-Oscillations in Large Interacting Systems Subjected to Phase Transitions.” Journal of Physics A: Mathematical and Theoretical, vol. 52, no. 4, 045002, IOP Publishing, 2019, doi:10.1088/1751-8121/aaf2dd.' short: 'D. De Martino, Journal of Physics A: Mathematical and Theoretical 52 (2019).' date_created: 2019-02-24T22:59:19Z date_published: 2019-01-07T00:00:00Z date_updated: 2023-08-24T14:49:23Z day: '07' ddc: - '570' department: - _id: GaTk doi: 10.1088/1751-8121/aaf2dd ec_funded: 1 external_id: isi: - '000455379500001' file: - access_level: open_access checksum: 1112304ad363a6d8afaeccece36473cf content_type: application/pdf creator: kschuh date_created: 2019-04-19T12:18:57Z date_updated: 2020-07-14T12:47:17Z file_id: '6344' file_name: 2019_IOP_DeMartino.pdf file_size: 1804557 relation: main_file file_date_updated: 2020-07-14T12:47:17Z has_accepted_license: '1' intvolume: ' 52' isi: 1 issue: '4' language: - iso: eng month: '01' oa: 1 oa_version: Published Version project: - _id: 25681D80-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '291734' name: International IST Postdoc Fellowship Programme publication: 'Journal of Physics A: Mathematical and Theoretical' publication_status: published publisher: IOP Publishing quality_controlled: '1' scopus_import: '1' status: public title: Feedback-induced self-oscillations in large interacting systems subjected to phase transitions tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 52 year: '2019' ... --- _id: '6046' abstract: - lang: eng text: Sudden stress often triggers diverse, temporally structured gene expression responses in microbes, but it is largely unknown how variable in time such responses are and if genes respond in the same temporal order in every single cell. Here, we quantified timing variability of individual promoters responding to sublethal antibiotic stress using fluorescent reporters, microfluidics, and time‐lapse microscopy. We identified lower and upper bounds that put definite constraints on timing variability, which varies strongly among promoters and conditions. Timing variability can be interpreted using results from statistical kinetics, which enable us to estimate the number of rate‐limiting molecular steps underlying different responses. We found that just a few critical steps control some responses while others rely on dozens of steps. To probe connections between different stress responses, we then tracked the temporal order and response time correlations of promoter pairs in individual cells. Our results support that, when bacteria are exposed to the antibiotic nitrofurantoin, the ensuing oxidative stress and SOS responses are part of the same causal chain of molecular events. In contrast, under trimethoprim, the acid stress response and the SOS response are part of different chains of events running in parallel. Our approach reveals fundamental constraints on gene expression timing and provides new insights into the molecular events that underlie the timing of stress responses. acknowledged_ssus: - _id: Bio article_number: e8470 article_processing_charge: No author: - first_name: Karin full_name: Mitosch, Karin id: 39B66846-F248-11E8-B48F-1D18A9856A87 last_name: Mitosch - first_name: Georg full_name: Rieckh, Georg id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87 last_name: Rieckh - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: Mitosch K, Rieckh G, Bollenbach MT. Temporal order and precision of complex stress responses in individual bacteria. Molecular systems biology. 2019;15(2). doi:10.15252/msb.20188470 apa: Mitosch, K., Rieckh, G., & Bollenbach, M. T. (2019). Temporal order and precision of complex stress responses in individual bacteria. Molecular Systems Biology. Embo Press. https://doi.org/10.15252/msb.20188470 chicago: Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Temporal Order and Precision of Complex Stress Responses in Individual Bacteria.” Molecular Systems Biology. Embo Press, 2019. https://doi.org/10.15252/msb.20188470. ieee: K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Temporal order and precision of complex stress responses in individual bacteria,” Molecular systems biology, vol. 15, no. 2. Embo Press, 2019. ista: Mitosch K, Rieckh G, Bollenbach MT. 2019. Temporal order and precision of complex stress responses in individual bacteria. Molecular systems biology. 15(2), e8470. mla: Mitosch, Karin, et al. “Temporal Order and Precision of Complex Stress Responses in Individual Bacteria.” Molecular Systems Biology, vol. 15, no. 2, e8470, Embo Press, 2019, doi:10.15252/msb.20188470. short: K. Mitosch, G. Rieckh, M.T. Bollenbach, Molecular Systems Biology 15 (2019). date_created: 2019-02-24T22:59:18Z date_published: 2019-02-14T00:00:00Z date_updated: 2023-08-24T14:49:53Z day: '14' department: - _id: GaTk doi: 10.15252/msb.20188470 external_id: isi: - '000459628300003' pmid: - '30765425' intvolume: ' 15' isi: 1 issue: '2' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pubmed/30765425 month: '02' oa: 1 oa_version: Submitted Version pmid: 1 project: - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 25EB3A80-B435-11E9-9278-68D0E5697425 grant_number: RGP0042/2013 name: Revealing the fundamental limits of cell growth publication: Molecular systems biology publication_status: published publisher: Embo Press quality_controlled: '1' scopus_import: '1' status: public title: Temporal order and precision of complex stress responses in individual bacteria type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 15 year: '2019' ... --- _id: '6784' abstract: - lang: eng text: Mathematical models have been used successfully at diverse scales of biological organization, ranging from ecology and population dynamics to stochastic reaction events occurring between individual molecules in single cells. Generally, many biological processes unfold across multiple scales, with mutations being the best studied example of how stochasticity at the molecular scale can influence outcomes at the population scale. In many other contexts, however, an analogous link between micro- and macro-scale remains elusive, primarily due to the challenges involved in setting up and analyzing multi-scale models. Here, we employ such a model to investigate how stochasticity propagates from individual biochemical reaction events in the bacterial innate immune system to the ecology of bacteria and bacterial viruses. We show analytically how the dynamics of bacterial populations are shaped by the activities of immunity-conferring enzymes in single cells and how the ecological consequences imply optimal bacterial defense strategies against viruses. Our results suggest that bacterial populations in the presence of viruses can either optimize their initial growth rate or their population size, with the first strategy favoring simple immunity featuring a single restriction modification system and the second strategy favoring complex bacterial innate immunity featuring several simultaneously active restriction modification systems. article_number: e1007168 article_processing_charge: No article_type: original author: - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Maros full_name: Pleska, Maros id: 4569785E-F248-11E8-B48F-1D18A9856A87 last_name: Pleska orcid: 0000-0001-7460-7479 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Ruess J, Pleska M, Guet CC, Tkačik G. Molecular noise of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology. 2019;15(7). doi:10.1371/journal.pcbi.1007168 apa: Ruess, J., Pleska, M., Guet, C. C., & Tkačik, G. (2019). Molecular noise of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007168 chicago: Ruess, Jakob, Maros Pleska, Calin C Guet, and Gašper Tkačik. “Molecular Noise of Innate Immunity Shapes Bacteria-Phage Ecologies.” PLoS Computational Biology. Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007168. ieee: J. Ruess, M. Pleska, C. C. Guet, and G. Tkačik, “Molecular noise of innate immunity shapes bacteria-phage ecologies,” PLoS Computational Biology, vol. 15, no. 7. Public Library of Science, 2019. ista: Ruess J, Pleska M, Guet CC, Tkačik G. 2019. Molecular noise of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology. 15(7), e1007168. mla: Ruess, Jakob, et al. “Molecular Noise of Innate Immunity Shapes Bacteria-Phage Ecologies.” PLoS Computational Biology, vol. 15, no. 7, e1007168, Public Library of Science, 2019, doi:10.1371/journal.pcbi.1007168. short: J. Ruess, M. Pleska, C.C. Guet, G. Tkačik, PLoS Computational Biology 15 (2019). date_created: 2019-08-11T21:59:19Z date_published: 2019-07-02T00:00:00Z date_updated: 2023-08-29T07:10:06Z day: '02' ddc: - '570' department: - _id: CaGu - _id: GaTk doi: 10.1371/journal.pcbi.1007168 external_id: isi: - '000481577700032' file: - access_level: open_access checksum: 7ded4721b41c2a0fc66a1c634540416a content_type: application/pdf creator: dernst date_created: 2019-08-12T12:27:26Z date_updated: 2020-07-14T12:47:40Z file_id: '6803' file_name: 2019_PlosComputBiology_Ruess.pdf file_size: 2200003 relation: main_file file_date_updated: 2020-07-14T12:47:40Z has_accepted_license: '1' intvolume: ' 15' isi: 1 issue: '7' language: - iso: eng month: '07' oa: 1 oa_version: Published Version project: - _id: 251D65D8-B435-11E9-9278-68D0E5697425 grant_number: '24210' name: Effects of Stochasticity on the Function of Restriction-Modi cation Systems at the Single-Cell Level - _id: 251BCBEC-B435-11E9-9278-68D0E5697425 grant_number: RGY0079/2011 name: Multi-Level Conflicts in Evolutionary Dynamics of Restriction-Modification Systems publication: PLoS Computational Biology publication_identifier: eissn: - 1553-7358 publication_status: published publisher: Public Library of Science quality_controlled: '1' related_material: record: - id: '9786' relation: research_data status: public scopus_import: '1' status: public title: Molecular noise of innate immunity shapes bacteria-phage ecologies tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 15 year: '2019' ... --- _id: '9786' article_processing_charge: No author: - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 - first_name: Maros full_name: Pleska, Maros id: 4569785E-F248-11E8-B48F-1D18A9856A87 last_name: Pleska orcid: 0000-0001-7460-7479 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Ruess J, Pleska M, Guet CC, Tkačik G. Supporting text and results. 2019. doi:10.1371/journal.pcbi.1007168.s001 apa: Ruess, J., Pleska, M., Guet, C. C., & Tkačik, G. (2019). Supporting text and results. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007168.s001 chicago: Ruess, Jakob, Maros Pleska, Calin C Guet, and Gašper Tkačik. “Supporting Text and Results.” Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007168.s001. ieee: J. Ruess, M. Pleska, C. C. Guet, and G. Tkačik, “Supporting text and results.” Public Library of Science, 2019. ista: Ruess J, Pleska M, Guet CC, Tkačik G. 2019. Supporting text and results, Public Library of Science, 10.1371/journal.pcbi.1007168.s001. mla: Ruess, Jakob, et al. Supporting Text and Results. Public Library of Science, 2019, doi:10.1371/journal.pcbi.1007168.s001. short: J. Ruess, M. Pleska, C.C. Guet, G. Tkačik, (2019). date_created: 2021-08-06T08:23:43Z date_published: 2019-07-02T00:00:00Z date_updated: 2023-08-29T07:10:05Z day: '02' department: - _id: CaGu - _id: GaTk doi: 10.1371/journal.pcbi.1007168.s001 month: '07' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '6784' relation: used_in_publication status: public status: public title: Supporting text and results type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2019' ...