[{"related_material":{"record":[{"id":"202","status":"public","relation":"dissertation_contains"}]},"author":[{"id":"4569785E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7460-7479","first_name":"Maros","last_name":"Pleska","full_name":"Pleska, Maros"},{"id":"29E0800A-F248-11E8-B48F-1D18A9856A87","first_name":"Moritz","last_name":"Lang","full_name":"Lang, Moritz"},{"last_name":"Refardt","first_name":"Dominik","full_name":"Refardt, Dominik"},{"full_name":"Levin, Bruce","last_name":"Levin","first_name":"Bruce"},{"first_name":"Calin C","last_name":"Guet","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052","full_name":"Guet, Calin C"}],"volume":2,"date_created":"2018-12-11T11:46:35Z","date_updated":"2023-09-15T12:04:57Z","year":"2018","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publisher":"Springer Nature","publication_status":"published","ec_funded":1,"publist_id":"7364","doi":"10.1038/s41559-017-0424-z","language":[{"iso":"eng"}],"external_id":{"isi":["000426516400027"]},"project":[{"_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"},{"name":"Multi-Level Conflicts in Evolutionary Dynamics of Restriction-Modification Systems (HFSP Young investigators' grant)","_id":"251BCBEC-B435-11E9-9278-68D0E5697425","grant_number":"RGY0079/2011"},{"name":"Effects of Stochasticity on the Function of Restriction-Modi cation Systems at the Single-Cell Level (DOC Fellowship)","_id":"251D65D8-B435-11E9-9278-68D0E5697425","grant_number":"24210"}],"isi":1,"quality_controlled":"1","month":"02","oa_version":"None","_id":"457","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","intvolume":" 2","status":"public","title":"Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity","issue":"2","abstract":[{"lang":"eng","text":"Temperate bacteriophages integrate in bacterial genomes as prophages and represent an important source of genetic variation for bacterial evolution, frequently transmitting fitness-augmenting genes such as toxins responsible for virulence of major pathogens. However, only a fraction of bacteriophage infections are lysogenic and lead to prophage acquisition, whereas the majority are lytic and kill the infected bacteria. Unless able to discriminate lytic from lysogenic infections, mechanisms of immunity to bacteriophages are expected to act as a double-edged sword and increase the odds of survival at the cost of depriving bacteria of potentially beneficial prophages. We show that although restriction-modification systems as mechanisms of innate immunity prevent both lytic and lysogenic infections indiscriminately in individual bacteria, they increase the number of prophage-acquiring individuals at the population level. We find that this counterintuitive result is a consequence of phage-host population dynamics, in which restriction-modification systems delay infection onset until bacteria reach densities at which the probability of lysogeny increases. These results underscore the importance of population-level dynamics as a key factor modulating costs and benefits of immunity to temperate bacteriophages"}],"type":"journal_article","date_published":"2018-02-01T00:00:00Z","citation":{"apa":"Pleska, M., Lang, M., Refardt, D., Levin, B., & Guet, C. C. (2018). Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity. Nature Ecology and Evolution. Springer Nature. https://doi.org/10.1038/s41559-017-0424-z","ieee":"M. Pleska, M. Lang, D. Refardt, B. Levin, and C. C. Guet, “Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity,” Nature Ecology and Evolution, vol. 2, no. 2. Springer Nature, pp. 359–366, 2018.","ista":"Pleska M, Lang M, Refardt D, Levin B, Guet CC. 2018. Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity. Nature Ecology and Evolution. 2(2), 359–366.","ama":"Pleska M, Lang M, Refardt D, Levin B, Guet CC. Phage-host population dynamics promotes prophage acquisition in bacteria with innate immunity. Nature Ecology and Evolution. 2018;2(2):359-366. doi:10.1038/s41559-017-0424-z","chicago":"Pleska, Maros, Moritz Lang, Dominik Refardt, Bruce Levin, and Calin C Guet. “Phage-Host Population Dynamics Promotes Prophage Acquisition in Bacteria with Innate Immunity.” Nature Ecology and Evolution. Springer Nature, 2018. https://doi.org/10.1038/s41559-017-0424-z.","short":"M. Pleska, M. Lang, D. Refardt, B. Levin, C.C. Guet, Nature Ecology and Evolution 2 (2018) 359–366.","mla":"Pleska, Maros, et al. “Phage-Host Population Dynamics Promotes Prophage Acquisition in Bacteria with Innate Immunity.” Nature Ecology and Evolution, vol. 2, no. 2, Springer Nature, 2018, pp. 359–66, doi:10.1038/s41559-017-0424-z."},"publication":"Nature Ecology and Evolution","page":"359 - 366","article_processing_charge":"No","day":"01","scopus_import":"1"},{"project":[{"_id":"25548C20-B435-11E9-9278-68D0E5697425","grant_number":"303564","name":"Microbial Ion Channels for Synthetic Neurobiology","call_identifier":"FP7"},{"grant_number":"W1232-B24","_id":"255A6082-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Molecular Drug Targets"}],"isi":1,"quality_controlled":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"external_id":{"isi":["000432280000006"]},"language":[{"iso":"eng"}],"doi":"10.1038/s41467-018-04342-1","publication_identifier":{"issn":["2041-1723"]},"month":"12","department":[{"_id":"HaJa"},{"_id":"CaGu"},{"_id":"MiSi"}],"publisher":"Springer Nature","publication_status":"published","year":"2018","volume":9,"date_updated":"2023-09-19T14:29:32Z","date_created":"2019-02-14T10:50:24Z","author":[{"id":"4863116E-F248-11E8-B48F-1D18A9856A87","first_name":"Maurizio","last_name":"Morri","full_name":"Morri, Maurizio"},{"id":"3D9C5D30-F248-11E8-B48F-1D18A9856A87","last_name":"Sanchez-Romero","first_name":"Inmaculada","full_name":"Sanchez-Romero, Inmaculada"},{"id":"29D8BB2C-F248-11E8-B48F-1D18A9856A87","last_name":"Tichy","first_name":"Alexandra-Madelaine","full_name":"Tichy, Alexandra-Madelaine"},{"first_name":"Stephanie","last_name":"Kainrath","id":"32CFBA64-F248-11E8-B48F-1D18A9856A87","full_name":"Kainrath, Stephanie"},{"last_name":"Gerrard","first_name":"Elliot J.","full_name":"Gerrard, Elliot J."},{"full_name":"Hirschfeld, Priscila","last_name":"Hirschfeld","first_name":"Priscila","id":"435ACB3A-F248-11E8-B48F-1D18A9856A87"},{"id":"346C1EC6-F248-11E8-B48F-1D18A9856A87","last_name":"Schwarz","first_name":"Jan","full_name":"Schwarz, Jan"},{"id":"33BA6C30-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8023-9315","first_name":"Harald L","last_name":"Janovjak","full_name":"Janovjak, Harald L"}],"article_number":"1950","ec_funded":1,"file_date_updated":"2020-07-14T12:47:14Z","citation":{"ama":"Morri M, Sanchez-Romero I, Tichy A-M, et al. Optical functionalization of human class A orphan G-protein-coupled receptors. Nature Communications. 2018;9(1). doi:10.1038/s41467-018-04342-1","ista":"Morri M, Sanchez-Romero I, Tichy A-M, Kainrath S, Gerrard EJ, Hirschfeld P, Schwarz J, Janovjak HL. 2018. Optical functionalization of human class A orphan G-protein-coupled receptors. Nature Communications. 9(1), 1950.","apa":"Morri, M., Sanchez-Romero, I., Tichy, A.-M., Kainrath, S., Gerrard, E. J., Hirschfeld, P., … Janovjak, H. L. (2018). Optical functionalization of human class A orphan G-protein-coupled receptors. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-018-04342-1","ieee":"M. Morri et al., “Optical functionalization of human class A orphan G-protein-coupled receptors,” Nature Communications, vol. 9, no. 1. Springer Nature, 2018.","mla":"Morri, Maurizio, et al. “Optical Functionalization of Human Class A Orphan G-Protein-Coupled Receptors.” Nature Communications, vol. 9, no. 1, 1950, Springer Nature, 2018, doi:10.1038/s41467-018-04342-1.","short":"M. Morri, I. Sanchez-Romero, A.-M. Tichy, S. Kainrath, E.J. Gerrard, P. Hirschfeld, J. Schwarz, H.L. Janovjak, Nature Communications 9 (2018).","chicago":"Morri, Maurizio, Inmaculada Sanchez-Romero, Alexandra-Madelaine Tichy, Stephanie Kainrath, Elliot J. Gerrard, Priscila Hirschfeld, Jan Schwarz, and Harald L Janovjak. “Optical Functionalization of Human Class A Orphan G-Protein-Coupled Receptors.” Nature Communications. Springer Nature, 2018. https://doi.org/10.1038/s41467-018-04342-1."},"publication":"Nature Communications","date_published":"2018-12-01T00:00:00Z","scopus_import":"1","has_accepted_license":"1","article_processing_charge":"No","day":"01","intvolume":" 9","status":"public","ddc":["570"],"title":"Optical functionalization of human class A orphan G-protein-coupled receptors","_id":"5984","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","oa_version":"Published Version","file":[{"file_name":"2018_Springer_Morri.pdf","access_level":"open_access","content_type":"application/pdf","file_size":1349914,"creator":"kschuh","relation":"main_file","file_id":"5985","date_created":"2019-02-14T10:58:29Z","date_updated":"2020-07-14T12:47:14Z","checksum":"8325fcc194264af4749e662a73bf66b5"}],"type":"journal_article","issue":"1","abstract":[{"lang":"eng","text":"G-protein-coupled receptors (GPCRs) form the largest receptor family, relay environmental stimuli to changes in cell behavior and represent prime drug targets. Many GPCRs are classified as orphan receptors because of the limited knowledge on their ligands and coupling to cellular signaling machineries. Here, we engineer a library of 63 chimeric receptors that contain the signaling domains of human orphan and understudied GPCRs functionally linked to the light-sensing domain of rhodopsin. Upon stimulation with visible light, we identify activation of canonical cell signaling pathways, including cAMP-, Ca2+-, MAPK/ERK-, and Rho-dependent pathways, downstream of the engineered receptors. For the human pseudogene GPR33, we resurrect a signaling function that supports its hypothesized role as a pathogen entry site. These results demonstrate that substituting unknown chemical activators with a light switch can reveal information about protein function and provide an optically controlled protein library for exploring the physiology and therapeutic potential of understudied GPCRs."}]},{"language":[{"iso":"eng"}],"doi":"10.1093/molbev/msy163","isi":1,"quality_controlled":"1","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pubmed/30169679","open_access":"1"}],"oa":1,"external_id":{"pmid":["30169679"],"isi":["000452567200006"]},"month":"08","publication_identifier":{"issn":["0737-4038"]},"date_updated":"2023-10-17T11:51:06Z","date_created":"2018-12-11T11:44:11Z","volume":35,"author":[{"first_name":"Adam","last_name":"Palmer","full_name":"Palmer, Adam"},{"last_name":"Chait","first_name":"Remy P","orcid":"0000-0003-0876-3187","id":"3464AE84-F248-11E8-B48F-1D18A9856A87","full_name":"Chait, Remy P"},{"full_name":"Kishony, Roy","first_name":"Roy","last_name":"Kishony"}],"publication_status":"published","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publisher":"Oxford University Press","year":"2018","pmid":1,"publist_id":"8036","date_published":"2018-08-28T00:00:00Z","article_type":"original","page":"2669 - 2684","publication":"Molecular Biology and Evolution","citation":{"chicago":"Palmer, Adam, Remy P Chait, and Roy Kishony. “Nonoptimal Gene Expression Creates Latent Potential for Antibiotic Resistance.” Molecular Biology and Evolution. Oxford University Press, 2018. https://doi.org/10.1093/molbev/msy163.","mla":"Palmer, Adam, et al. “Nonoptimal Gene Expression Creates Latent Potential for Antibiotic Resistance.” Molecular Biology and Evolution, vol. 35, no. 11, Oxford University Press, 2018, pp. 2669–84, doi:10.1093/molbev/msy163.","short":"A. Palmer, R.P. Chait, R. Kishony, Molecular Biology and Evolution 35 (2018) 2669–2684.","ista":"Palmer A, Chait RP, Kishony R. 2018. Nonoptimal gene expression creates latent potential for antibiotic resistance. Molecular Biology and Evolution. 35(11), 2669–2684.","apa":"Palmer, A., Chait, R. P., & Kishony, R. (2018). Nonoptimal gene expression creates latent potential for antibiotic resistance. Molecular Biology and Evolution. Oxford University Press. https://doi.org/10.1093/molbev/msy163","ieee":"A. Palmer, R. P. Chait, and R. Kishony, “Nonoptimal gene expression creates latent potential for antibiotic resistance,” Molecular Biology and Evolution, vol. 35, no. 11. Oxford University Press, pp. 2669–2684, 2018.","ama":"Palmer A, Chait RP, Kishony R. Nonoptimal gene expression creates latent potential for antibiotic resistance. Molecular Biology and Evolution. 2018;35(11):2669-2684. doi:10.1093/molbev/msy163"},"day":"28","article_processing_charge":"No","scopus_import":"1","oa_version":"Submitted Version","title":"Nonoptimal gene expression creates latent potential for antibiotic resistance","status":"public","intvolume":" 35","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"19","abstract":[{"lang":"eng","text":"Bacteria regulate genes to survive antibiotic stress, but regulation can be far from perfect. When regulation is not optimal, mutations that change gene expression can contribute to antibiotic resistance. It is not systematically understood to what extent natural gene regulation is or is not optimal for distinct antibiotics, and how changes in expression of specific genes quantitatively affect antibiotic resistance. Here we discover a simple quantitative relation between fitness, gene expression, and antibiotic potency, which rationalizes our observation that a multitude of genes and even innate antibiotic defense mechanisms have expression that is critically nonoptimal under antibiotic treatment. First, we developed a pooled-strain drug-diffusion assay and screened Escherichia coli overexpression and knockout libraries, finding that resistance to a range of 31 antibiotics could result from changing expression of a large and functionally diverse set of genes, in a primarily but not exclusively drug-specific manner. Second, by synthetically controlling the expression of single-drug and multidrug resistance genes, we observed that their fitness-expression functions changed dramatically under antibiotic treatment in accordance with a log-sensitivity relation. Thus, because many genes are nonoptimally expressed under antibiotic treatment, many regulatory mutations can contribute to resistance by altering expression and by activating latent defenses."}],"issue":"11","type":"journal_article"},{"month":"04","isi":1,"quality_controlled":"1","project":[{"call_identifier":"FWF","name":"FWF Open Access Fund","_id":"3AC91DDA-15DF-11EA-824D-93A3E7B544D1"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"external_id":{"isi":["000429009500021"]},"language":[{"iso":"eng"}],"doi":"10.1093/nar/gky079","file_date_updated":"2020-07-14T12:46:27Z","publication_status":"published","publisher":"Oxford University Press","department":[{"_id":"CaGu"}],"year":"2018","date_created":"2018-12-11T11:46:29Z","date_updated":"2024-02-21T13:44:45Z","volume":46,"author":[{"full_name":"Nikolic, Nela","first_name":"Nela","last_name":"Nikolic","id":"42D9CABC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9068-6090"},{"full_name":"Bergmiller, Tobias","first_name":"Tobias","last_name":"Bergmiller","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5396-4346"},{"first_name":"Alexandra","last_name":"Vandervelde","full_name":"Vandervelde, Alexandra"},{"last_name":"Albanese","first_name":"Tanino","full_name":"Albanese, Tanino"},{"full_name":"Gelens, Lendert","first_name":"Lendert","last_name":"Gelens"},{"first_name":"Isabella","last_name":"Moll","full_name":"Moll, Isabella"}],"related_material":{"record":[{"relation":"popular_science","status":"public","id":"5569"}]},"scopus_import":"1","day":"06","article_processing_charge":"Yes (in subscription journal)","has_accepted_license":"1","page":"2918-2931","publication":"Nucleic Acids Research","citation":{"ama":"Nikolic N, Bergmiller T, Vandervelde A, Albanese T, Gelens L, Moll I. Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations. Nucleic Acids Research. 2018;46(6):2918-2931. doi:10.1093/nar/gky079","ieee":"N. Nikolic, T. Bergmiller, A. Vandervelde, T. Albanese, L. Gelens, and I. Moll, “Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations,” Nucleic Acids Research, vol. 46, no. 6. Oxford University Press, pp. 2918–2931, 2018.","apa":"Nikolic, N., Bergmiller, T., Vandervelde, A., Albanese, T., Gelens, L., & Moll, I. (2018). Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations. Nucleic Acids Research. Oxford University Press. https://doi.org/10.1093/nar/gky079","ista":"Nikolic N, Bergmiller T, Vandervelde A, Albanese T, Gelens L, Moll I. 2018. Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations. Nucleic Acids Research. 46(6), 2918–2931.","short":"N. Nikolic, T. Bergmiller, A. Vandervelde, T. Albanese, L. Gelens, I. Moll, Nucleic Acids Research 46 (2018) 2918–2931.","mla":"Nikolic, Nela, et al. “Autoregulation of MazEF Expression Underlies Growth Heterogeneity in Bacterial Populations.” Nucleic Acids Research, vol. 46, no. 6, Oxford University Press, 2018, pp. 2918–31, doi:10.1093/nar/gky079.","chicago":"Nikolic, Nela, Tobias Bergmiller, Alexandra Vandervelde, Tanino Albanese, Lendert Gelens, and Isabella Moll. “Autoregulation of MazEF Expression Underlies Growth Heterogeneity in Bacterial Populations.” Nucleic Acids Research. Oxford University Press, 2018. https://doi.org/10.1093/nar/gky079."},"date_published":"2018-04-06T00:00:00Z","type":"journal_article","abstract":[{"text":"The MazF toxin sequence-specifically cleaves single-stranded RNA upon various stressful conditions, and it is activated as a part of the mazEF toxin–antitoxin module in Escherichia coli. Although autoregulation of mazEF expression through the MazE antitoxin-dependent transcriptional repression has been biochemically characterized, less is known about post-transcriptional autoregulation, as well as how both of these autoregulatory features affect growth of single cells during conditions that promote MazF production. Here, we demonstrate post-transcriptional autoregulation of mazF expression dynamics by MazF cleaving its own transcript. Single-cell analyses of bacterial populations during ectopic MazF production indicated that two-level autoregulation of mazEF expression influences cell-to-cell growth rate heterogeneity. The increase in growth rate heterogeneity is governed by the MazE antitoxin, and tuned by the MazF-dependent mazF mRNA cleavage. Also, both autoregulatory features grant rapid exit from the stress caused by mazF overexpression. Time-lapse microscopy revealed that MazF-mediated cleavage of mazF mRNA leads to increased temporal variability in length of individual cells during ectopic mazF overexpression, as explained by a stochastic model indicating that mazEF mRNA cleavage underlies temporal fluctuations in MazF levels during stress.","lang":"eng"}],"issue":"6","status":"public","title":"Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations","ddc":["576"],"intvolume":" 46","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"438","oa_version":"Published Version","file":[{"access_level":"open_access","file_name":"IST-2018-971-v1+1_2018_Nikoloc_Autoregulation_of.pdf","creator":"system","file_size":5027978,"content_type":"application/pdf","file_id":"5151","relation":"main_file","checksum":"3ff4f545c27e11a4cd20ccb30778793e","date_updated":"2020-07-14T12:46:27Z","date_created":"2018-12-12T10:15:30Z"}],"pubrep_id":"971"},{"related_material":{"record":[{"id":"438","relation":"research_paper","status":"public"}]},"author":[{"orcid":"0000-0001-5396-4346","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","last_name":"Bergmiller","first_name":"Tobias","full_name":"Bergmiller, Tobias"},{"full_name":"Nikolic, Nela","orcid":"0000-0001-9068-6090","id":"42D9CABC-F248-11E8-B48F-1D18A9856A87","last_name":"Nikolic","first_name":"Nela"}],"file":[{"file_name":"IST-2018-74-v1+2_15-11-05.zip","access_level":"open_access","content_type":"application/zip","file_size":3558703796,"creator":"system","relation":"main_file","file_id":"5637","date_updated":"2020-07-14T12:47:04Z","date_created":"2018-12-12T13:04:39Z","checksum":"61ebb92213cfffeba3ddbaff984b81af"},{"creator":"system","file_size":1830422606,"content_type":"application/zip","file_name":"IST-2018-74-v1+3_15-07-31.zip","access_level":"open_access","date_created":"2018-12-12T13:04:55Z","date_updated":"2020-07-14T12:47:04Z","checksum":"bf26649af310ef6892d68576515cde6d","file_id":"5638","relation":"main_file"},{"file_name":"IST-2018-74-v1+4_Images_for_analysis.zip","access_level":"open_access","file_size":2140849248,"content_type":"application/zip","creator":"system","relation":"main_file","file_id":"5639","date_updated":"2020-07-14T12:47:04Z","date_created":"2018-12-12T13:05:11Z","checksum":"8e46eedce06f22acb2be1a9b9d3f56bd"}],"oa_version":"Published Version","date_created":"2018-12-12T12:31:35Z","date_updated":"2024-02-21T13:44:45Z","_id":"5569","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2018","department":[{"_id":"CaGu"}],"publisher":"Institute of Science and Technology Austria","ddc":["579"],"status":"public","title":"Time-lapse microscopy data","publist_id":"7385","abstract":[{"text":"Nela Nikolic, Tobias Bergmiller, Alexandra Vandervelde, Tanino G. Albanese, Lendert Gelens, and Isabella Moll (2018)\r\n“Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations” Nucleic Acids Research, doi: 10.15479/AT:ISTA:74;\r\nmicroscopy experiments by Tobias Bergmiller; image and data analysis by Nela Nikolic.","lang":"eng"}],"file_date_updated":"2020-07-14T12:47:04Z","license":"https://creativecommons.org/publicdomain/zero/1.0/","type":"research_data","datarep_id":"74","date_published":"2018-02-07T00:00:00Z","doi":"10.15479/AT:ISTA:74","oa":1,"tmp":{"short":"CC0 (1.0)","image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","name":"Creative Commons Public Domain Dedication (CC0 1.0)"},"citation":{"ama":"Bergmiller T, Nikolic N. Time-lapse microscopy data. 2018. doi:10.15479/AT:ISTA:74","apa":"Bergmiller, T., & Nikolic, N. (2018). Time-lapse microscopy data. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:74","ieee":"T. Bergmiller and N. Nikolic, “Time-lapse microscopy data.” Institute of Science and Technology Austria, 2018.","ista":"Bergmiller T, Nikolic N. 2018. Time-lapse microscopy data, Institute of Science and Technology Austria, 10.15479/AT:ISTA:74.","short":"T. Bergmiller, N. Nikolic, (2018).","mla":"Bergmiller, Tobias, and Nela Nikolic. Time-Lapse Microscopy Data. Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:74.","chicago":"Bergmiller, Tobias, and Nela Nikolic. “Time-Lapse Microscopy Data.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:74."},"article_processing_charge":"No","has_accepted_license":"1","month":"02","day":"07","keyword":["microscopy","microfluidics"]},{"status":"public","title":"Statistical mechanics for metabolic networks during steady state growth","ddc":["570"],"intvolume":" 9","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"161","file":[{"date_updated":"2020-07-14T12:45:06Z","date_created":"2018-12-17T16:44:28Z","checksum":"3ba7ab27b27723c7dcf633e8fc1f8f18","relation":"main_file","file_id":"5728","content_type":"application/pdf","file_size":1043205,"creator":"dernst","file_name":"2018_NatureComm_DeMartino.pdf","access_level":"open_access"}],"oa_version":"Published Version","type":"journal_article","abstract":[{"text":"Which properties of metabolic networks can be derived solely from stoichiometry? Predictive results have been obtained by flux balance analysis (FBA), by postulating that cells set metabolic fluxes to maximize growth rate. Here we consider a generalization of FBA to single-cell level using maximum entropy modeling, which we extend and test experimentally. Specifically, we define for Escherichia coli metabolism a flux distribution that yields the experimental growth rate: the model, containing FBA as a limit, provides a better match to measured fluxes and it makes a wide range of predictions: on flux variability, regulation, and correlations; on the relative importance of stoichiometry vs. optimization; on scaling relations for growth rate distributions. We validate the latter here with single-cell data at different sub-inhibitory antibiotic concentrations. The model quantifies growth optimization as emerging from the interplay of competitive dynamics in the population and regulation of metabolism at the level of single cells.","lang":"eng"}],"issue":"1","publication":"Nature Communications","citation":{"ama":"De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. Statistical mechanics for metabolic networks during steady state growth. Nature Communications. 2018;9(1). doi:10.1038/s41467-018-05417-9","ista":"De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. 2018. Statistical mechanics for metabolic networks during steady state growth. Nature Communications. 9(1), 2988.","ieee":"D. De Martino, A. A. Mc, T. Bergmiller, C. C. Guet, and G. Tkačik, “Statistical mechanics for metabolic networks during steady state growth,” Nature Communications, vol. 9, no. 1. Springer Nature, 2018.","apa":"De Martino, D., Mc, A. A., Bergmiller, T., Guet, C. C., & Tkačik, G. (2018). Statistical mechanics for metabolic networks during steady state growth. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-018-05417-9","mla":"De Martino, Daniele, et al. “Statistical Mechanics for Metabolic Networks during Steady State Growth.” Nature Communications, vol. 9, no. 1, 2988, Springer Nature, 2018, doi:10.1038/s41467-018-05417-9.","short":"D. De Martino, A.A. Mc, T. Bergmiller, C.C. Guet, G. Tkačik, Nature Communications 9 (2018).","chicago":"De Martino, Daniele, Andersson Anna Mc, Tobias Bergmiller, Calin C Guet, and Gašper Tkačik. “Statistical Mechanics for Metabolic Networks during Steady State Growth.” Nature Communications. Springer Nature, 2018. https://doi.org/10.1038/s41467-018-05417-9."},"date_published":"2018-07-30T00:00:00Z","scopus_import":"1","day":"30","article_processing_charge":"No","has_accepted_license":"1","publication_status":"published","department":[{"_id":"GaTk"},{"_id":"CaGu"}],"publisher":"Springer Nature","year":"2018","date_updated":"2024-02-21T13:45:39Z","date_created":"2018-12-11T11:44:57Z","volume":9,"author":[{"last_name":"De Martino","first_name":"Daniele","orcid":"0000-0002-5214-4706","id":"3FF5848A-F248-11E8-B48F-1D18A9856A87","full_name":"De Martino, Daniele"},{"first_name":"Andersson Anna","last_name":"Mc","full_name":"Mc, Andersson Anna"},{"first_name":"Tobias","last_name":"Bergmiller","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5396-4346","full_name":"Bergmiller, Tobias"},{"full_name":"Guet, Calin C","first_name":"Calin C","last_name":"Guet","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052"},{"orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","last_name":"Tkacik","first_name":"Gasper","full_name":"Tkacik, Gasper"}],"related_material":{"record":[{"relation":"popular_science","status":"public","id":"5587"}]},"article_number":"2988","file_date_updated":"2020-07-14T12:45:06Z","ec_funded":1,"publist_id":"7760","isi":1,"quality_controlled":"1","project":[{"grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF"},{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"}],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"external_id":{"isi":["000440149300021"]},"language":[{"iso":"eng"}],"doi":"10.1038/s41467-018-05417-9","month":"07"},{"file_date_updated":"2021-02-11T11:17:14Z","publist_id":"8029","author":[{"orcid":"0000-0003-1229-9719","id":"2C023F40-F248-11E8-B48F-1D18A9856A87","last_name":"Steinrück","first_name":"Magdalena","full_name":"Steinrück, Magdalena"}],"related_material":{"record":[{"id":"704","status":"public","relation":"part_of_dissertation"}]},"date_updated":"2023-09-07T12:48:43Z","date_created":"2018-12-11T11:44:14Z","year":"2018","publication_status":"published","department":[{"_id":"CaGu"}],"publisher":"Institute of Science and Technology Austria","month":"10","publication_identifier":{"issn":["2663-337X"]},"doi":"10.15479/AT:ISTA:th1059","degree_awarded":"PhD","supervisor":[{"first_name":"Calin C","last_name":"Guet","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052","full_name":"Guet, Calin C"}],"language":[{"iso":"eng"}],"oa":1,"abstract":[{"lang":"eng","text":"Expression of genes is a fundamental molecular phenotype that is subject to evolution by different types of mutations. Both the rate and the effect of mutations may depend on the DNA sequence context of a particular gene or a particular promoter sequence. In this thesis I investigate the nature of this dependence using simple genetic systems in Escherichia coli. With these systems I explore the evolution of constitutive gene expression from random starting sequences at different loci on the chromosome and at different locations in sequence space. First, I dissect chromosomal neighborhood effects that underlie locus-dependent differences in the potential of a gene under selection to become more highly expressed. Next, I find that the effects of point mutations in promoter sequences are dependent on sequence context, and that an existing energy matrix model performs poorly in predicting relative expression of unrelated sequences. Finally, I show that a substantial fraction of random sequences contain functional promoters and I present an extended thermodynamic model that predicts promoter strength in full sequence space. Taken together, these results provide new insights and guides on how to integrate information on sequence context to improve our qualitative and quantitative understanding of bacterial gene expression, with implications for rapid evolution of drug resistance, de novo evolution of genes, and horizontal gene transfer."}],"type":"dissertation","alternative_title":["ISTA Thesis"],"pubrep_id":"1059","file":[{"date_updated":"2020-07-14T12:45:43Z","date_created":"2019-02-08T10:51:22Z","checksum":"413cbce1cd1debeae3abe2a25dbc70d1","relation":"source_file","file_id":"5941","content_type":"application/vnd.openxmlformats-officedocument.wordprocessingml.document","file_size":9190845,"creator":"dernst","embargo_to":"open_access","file_name":"Thesis_Steinrueck_final.docx","access_level":"closed"},{"access_level":"open_access","file_name":"Thesis_Steinrueck_final.pdf","file_size":7521973,"content_type":"application/pdf","creator":"dernst","relation":"main_file","file_id":"5942","embargo":"2019-11-02","checksum":"3def8b7854c8b42d643597ce0215efac","date_updated":"2021-02-11T11:17:14Z","date_created":"2019-02-08T10:51:22Z"}],"oa_version":"Published Version","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"26","title":"The influence of sequence context on the evolution of bacterial gene expression","status":"public","ddc":["576","579"],"day":"30","article_processing_charge":"No","has_accepted_license":"1","date_published":"2018-10-30T00:00:00Z","citation":{"mla":"Steinrück, Magdalena. The Influence of Sequence Context on the Evolution of Bacterial Gene Expression. Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:th1059.","short":"M. Steinrück, The Influence of Sequence Context on the Evolution of Bacterial Gene Expression, Institute of Science and Technology Austria, 2018.","chicago":"Steinrück, Magdalena. “The Influence of Sequence Context on the Evolution of Bacterial Gene Expression.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:th1059.","ama":"Steinrück M. The influence of sequence context on the evolution of bacterial gene expression. 2018. doi:10.15479/AT:ISTA:th1059","ista":"Steinrück M. 2018. The influence of sequence context on the evolution of bacterial gene expression. Institute of Science and Technology Austria.","ieee":"M. Steinrück, “The influence of sequence context on the evolution of bacterial gene expression,” Institute of Science and Technology Austria, 2018.","apa":"Steinrück, M. (2018). The influence of sequence context on the evolution of bacterial gene expression. 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Igler, M. Lagator, G. Tkačik, J.P. Bollback, C.C. Guet, Nature Ecology and Evolution 2 (2018) 1633–1643.","chicago":"Igler, Claudia, Mato Lagator, Gašper Tkačik, Jonathan P Bollback, and Calin C Guet. “Evolutionary Potential of Transcription Factors for Gene Regulatory Rewiring.” Nature Ecology and Evolution. Nature Publishing Group, 2018. https://doi.org/10.1038/s41559-018-0651-y.","ama":"Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. Evolutionary potential of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution. 2018;2(10):1633-1643. doi:10.1038/s41559-018-0651-y","ista":"Igler C, Lagator M, Tkačik G, Bollback JP, Guet CC. 2018. Evolutionary potential of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution. 2(10), 1633–1643.","apa":"Igler, C., Lagator, M., Tkačik, G., Bollback, J. P., & Guet, C. C. (2018). Evolutionary potential of transcription factors for gene regulatory rewiring. Nature Ecology and Evolution. Nature Publishing Group. https://doi.org/10.1038/s41559-018-0651-y","ieee":"C. Igler, M. Lagator, G. Tkačik, J. P. Bollback, and C. C. Guet, “Evolutionary potential of transcription factors for gene regulatory rewiring,” Nature Ecology and Evolution, vol. 2, no. 10. Nature Publishing Group, pp. 1633–1643, 2018."},"publication":"Nature Ecology and Evolution","issue":"10","abstract":[{"text":"Gene regulatory networks evolve through rewiring of individual components—that is, through changes in regulatory connections. However, the mechanistic basis of regulatory rewiring is poorly understood. Using a canonical gene regulatory system, we quantify the properties of transcription factors that determine the evolutionary potential for rewiring of regulatory connections: robustness, tunability and evolvability. In vivo repression measurements of two repressors at mutated operator sites reveal their contrasting evolutionary potential: while robustness and evolvability were positively correlated, both were in trade-off with tunability. Epistatic interactions between adjacent operators alleviated this trade-off. A thermodynamic model explains how the differences in robustness, tunability and evolvability arise from biophysical characteristics of repressor–DNA binding. The model also uncovers that the energy matrix, which describes how mutations affect repressor–DNA binding, encodes crucial information about the evolutionary potential of a repressor. The biophysical determinants of evolutionary potential for regulatory rewiring constitute a mechanistic framework for understanding network evolution.","lang":"eng"}],"type":"journal_article","file":[{"file_name":"2018_NatureEcology_Igler.pdf","access_level":"open_access","file_size":1135973,"content_type":"application/pdf","creator":"dernst","relation":"main_file","file_id":"7830","date_created":"2020-05-14T11:28:52Z","date_updated":"2020-07-14T12:47:37Z","checksum":"383a2e2c944a856e2e821ec8e7bf71b6"}],"oa_version":"Submitted Version","intvolume":" 2","title":"Evolutionary potential of transcription factors for gene regulatory rewiring","ddc":["570"],"status":"public","_id":"67","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1"},{"project":[{"call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734"},{"_id":"2578D616-B435-11E9-9278-68D0E5697425","grant_number":"648440","call_identifier":"H2020","name":"Selective Barriers to Horizontal Gene Transfer"},{"name":"Design principles underlying genetic switch architecture (DOC Fellowship)","grant_number":"24573","_id":"251EE76E-B435-11E9-9278-68D0E5697425"}],"oa":1,"tmp":{"short":"CC0 (1.0)","image":"/images/cc_0.png","legal_code_url":"https://creativecommons.org/publicdomain/zero/1.0/legalcode","name":"Creative Commons Public Domain Dedication (CC0 1.0)"},"citation":{"ieee":"C. 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Optogenetische Methoden, die auf grünes Licht ansprechen und zum Trennen von Proteinkomplexen geeignet sind, sind nichtweitläufig verfügbar, würden jedoch mehrfarbige Experimente zur Beantwortung von biologischen Fragestellungen ermöglichen. Hier demonstrieren wir die Verwendung von Cobalamin(Vitamin B12)-bindenden Domänen von bakteriellen CarH-Transkriptionsfaktoren zur Grünlicht-induzierten Dissoziation von Rezeptoren. Fusioniert mit dem Fibroblasten-W achstumsfaktor-Rezeptor 1 führten diese im Dunkeln in kultivierten Zellen zu Signalaktivität durch Oligomerisierung, welche durch Beleuchten umgehend aufgehoben wurde. In Zebrafischembryonen, die einen derartigen Rezeptor exprimieren, ermöglichte grünes Licht die Kontrolle über abnormale Signalaktivität während der Embryonalentwicklung. "}],"type":"journal_article","oa_version":"Published Version","file":[{"date_updated":"2020-07-14T12:46:39Z","date_created":"2018-12-12T10:13:24Z","checksum":"d66fee867e7cdbfa3fe276c2fb0778bb","relation":"main_file","file_id":"5007","file_size":1668557,"content_type":"application/pdf","creator":"system","file_name":"IST-2018-932-v1+1_Kainrath_et_al-2017-Angewandte_Chemie.pdf","access_level":"open_access"}],"pubrep_id":"932","intvolume":" 129","title":"Grünlicht-induzierte Rezeptorinaktivierung durch Cobalamin-bindende Domänen","ddc":["571"],"status":"public","_id":"538","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","has_accepted_license":"1","day":"20","date_published":"2017-05-20T00:00:00Z","page":"4679 - 4682","citation":{"chicago":"Kainrath, Stephanie, Manuela Stadler, Eva Gschaider-Reichhart, Martin Distel, and Harald L Janovjak. “Grünlicht-Induzierte Rezeptorinaktivierung Durch Cobalamin-Bindende Domänen.” Angewandte Chemie. Wiley, 2017. https://doi.org/10.1002/ange.201611998.","mla":"Kainrath, Stephanie, et al. “Grünlicht-Induzierte Rezeptorinaktivierung Durch Cobalamin-Bindende Domänen.” Angewandte Chemie, vol. 129, no. 16, Wiley, 2017, pp. 4679–82, doi:10.1002/ange.201611998.","short":"S. Kainrath, M. Stadler, E. Gschaider-Reichhart, M. Distel, H.L. Janovjak, Angewandte Chemie 129 (2017) 4679–4682.","ista":"Kainrath S, Stadler M, Gschaider-Reichhart E, Distel M, Janovjak HL. 2017. Grünlicht-induzierte Rezeptorinaktivierung durch Cobalamin-bindende Domänen. Angewandte Chemie. 129(16), 4679–4682.","apa":"Kainrath, S., Stadler, M., Gschaider-Reichhart, E., Distel, M., & Janovjak, H. L. (2017). Grünlicht-induzierte Rezeptorinaktivierung durch Cobalamin-bindende Domänen. Angewandte Chemie. Wiley. https://doi.org/10.1002/ange.201611998","ieee":"S. Kainrath, M. Stadler, E. Gschaider-Reichhart, M. Distel, and H. L. 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Angewandte Chemie. 2017;129(16):4679-4682. doi:10.1002/ange.201611998"},"publication":"Angewandte Chemie","publist_id":"7279","ec_funded":1,"file_date_updated":"2020-07-14T12:46:39Z","volume":129,"date_created":"2018-12-11T11:47:02Z","date_updated":"2021-01-12T08:01:33Z","author":[{"last_name":"Kainrath","first_name":"Stephanie","id":"32CFBA64-F248-11E8-B48F-1D18A9856A87","full_name":"Kainrath, Stephanie"},{"first_name":"Manuela","last_name":"Stadler","full_name":"Stadler, Manuela"},{"full_name":"Gschaider-Reichhart, Eva","id":"3FEE232A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-7218-7738","first_name":"Eva","last_name":"Gschaider-Reichhart"},{"full_name":"Distel, Martin","last_name":"Distel","first_name":"Martin"},{"full_name":"Janovjak, Harald L","id":"33BA6C30-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-8023-9315","first_name":"Harald L","last_name":"Janovjak"}],"department":[{"_id":"CaGu"},{"_id":"HaJa"}],"publisher":"Wiley","publication_status":"published","year":"2017","month":"05","language":[{"iso":"eng"}],"doi":"10.1002/ange.201611998","project":[{"_id":"25548C20-B435-11E9-9278-68D0E5697425","grant_number":"303564","name":"Microbial Ion Channels for Synthetic Neurobiology","call_identifier":"FP7"},{"name":"Molecular Drug Targets","call_identifier":"FWF","grant_number":"W1232-B24","_id":"255A6082-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"}},{"file":[{"file_name":"IST-2017-918-v1+1_elife-28921-figures-v3.pdf","access_level":"open_access","creator":"system","content_type":"application/pdf","file_size":8453470,"file_id":"5096","relation":"main_file","date_created":"2018-12-12T10:14:42Z","date_updated":"2020-07-14T12:47:10Z","checksum":"273ab17f33305e4eaafd911ff88e7c5b"},{"file_id":"5097","relation":"main_file","date_updated":"2020-07-14T12:47:10Z","date_created":"2018-12-12T10:14:43Z","checksum":"b433f90576c7be597cd43367946f8e7f","file_name":"IST-2017-918-v1+2_elife-28921-v3.pdf","access_level":"open_access","creator":"system","content_type":"application/pdf","file_size":1953221}],"oa_version":"Published Version","pubrep_id":"918","intvolume":" 6","title":"Regulatory network structure determines patterns of intermolecular epistasis","status":"public","ddc":["576"],"_id":"570","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","abstract":[{"text":"Most phenotypes are determined by molecular systems composed of specifically interacting molecules. However, unlike for individual components, little is known about the distributions of mutational effects of molecular systems as a whole. We ask how the distribution of mutational effects of a transcriptional regulatory system differs from the distributions of its components, by first independently, and then simultaneously, mutating a transcription factor and the associated promoter it represses. We find that the system distribution exhibits increased phenotypic variation compared to individual component distributions - an effect arising from intermolecular epistasis between the transcription factor and its DNA-binding site. In large part, this epistasis can be qualitatively attributed to the structure of the transcriptional regulatory system and could therefore be a common feature in prokaryotes. Counter-intuitively, intermolecular epistasis can alleviate the constraints of individual components, thereby increasing phenotypic variation that selection could act on and facilitating adaptive evolution. ","lang":"eng"}],"type":"journal_article","date_published":"2017-11-13T00:00:00Z","citation":{"ieee":"M. Lagator, S. Sarikas, H. Acar, J. P. Bollback, and C. C. Guet, “Regulatory network structure determines patterns of intermolecular epistasis,” eLife, vol. 6. eLife Sciences Publications, 2017.","apa":"Lagator, M., Sarikas, S., Acar, H., Bollback, J. P., & Guet, C. C. (2017). Regulatory network structure determines patterns of intermolecular epistasis. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.28921","ista":"Lagator M, Sarikas S, Acar H, Bollback JP, Guet CC. 2017. Regulatory network structure determines patterns of intermolecular epistasis. eLife. 6, e28921.","ama":"Lagator M, Sarikas S, Acar H, Bollback JP, Guet CC. Regulatory network structure determines patterns of intermolecular epistasis. eLife. 2017;6. doi:10.7554/eLife.28921","chicago":"Lagator, Mato, Srdjan Sarikas, Hande Acar, Jonathan P Bollback, and Calin C Guet. “Regulatory Network Structure Determines Patterns of Intermolecular Epistasis.” ELife. eLife Sciences Publications, 2017. https://doi.org/10.7554/eLife.28921.","short":"M. Lagator, S. Sarikas, H. Acar, J.P. Bollback, C.C. Guet, ELife 6 (2017).","mla":"Lagator, Mato, et al. “Regulatory Network Structure Determines Patterns of Intermolecular Epistasis.” ELife, vol. 6, e28921, eLife Sciences Publications, 2017, doi:10.7554/eLife.28921."},"publication":"eLife","has_accepted_license":"1","day":"13","scopus_import":1,"volume":6,"date_updated":"2021-01-12T08:03:15Z","date_created":"2018-12-11T11:47:14Z","author":[{"full_name":"Lagator, Mato","id":"345D25EC-F248-11E8-B48F-1D18A9856A87","first_name":"Mato","last_name":"Lagator"},{"id":"35F0286E-F248-11E8-B48F-1D18A9856A87","last_name":"Sarikas","first_name":"Srdjan","full_name":"Sarikas, Srdjan"},{"orcid":"0000-0003-1986-9753","id":"2DDF136A-F248-11E8-B48F-1D18A9856A87","last_name":"Acar","first_name":"Hande","full_name":"Acar, Hande"},{"orcid":"0000-0002-4624-4612","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87","last_name":"Bollback","first_name":"Jonathan P","full_name":"Bollback, Jonathan P"},{"full_name":"Guet, Calin C","orcid":"0000-0001-6220-2052","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","last_name":"Guet","first_name":"Calin C"}],"department":[{"_id":"CaGu"},{"_id":"JoBo"},{"_id":"NiBa"}],"publisher":"eLife Sciences Publications","publication_status":"published","year":"2017","ec_funded":1,"publist_id":"7244","file_date_updated":"2020-07-14T12:47:10Z","article_number":"e28921","language":[{"iso":"eng"}],"doi":"10.7554/eLife.28921","project":[{"_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"},{"_id":"2578D616-B435-11E9-9278-68D0E5697425","grant_number":"648440","call_identifier":"H2020","name":"Selective Barriers to Horizontal Gene Transfer"}],"quality_controlled":"1","oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"publication_identifier":{"issn":["2050084X"]},"month":"11"},{"volume":8,"date_updated":"2021-01-12T08:06:15Z","date_created":"2018-12-11T11:47:30Z","author":[{"full_name":"Chait, Remy P","orcid":"0000-0003-0876-3187","id":"3464AE84-F248-11E8-B48F-1D18A9856A87","last_name":"Chait","first_name":"Remy P"},{"id":"4A245D00-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-1615-3282","first_name":"Jakob","last_name":"Ruess","full_name":"Ruess, Jakob"},{"full_name":"Bergmiller, Tobias","last_name":"Bergmiller","first_name":"Tobias","orcid":"0000-0001-5396-4346","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87"},{"last_name":"Tkacik","first_name":"Gasper","orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Tkacik, Gasper"},{"full_name":"Guet, Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052","first_name":"Calin C","last_name":"Guet"}],"publisher":"Nature Publishing Group","department":[{"_id":"CaGu"},{"_id":"GaTk"}],"publication_status":"published","year":"2017","acknowledgement":"We are grateful to M. Lang, H. Janovjak, M. Khammash, A. Milias-Argeitis, M. Rullan, G. Batt, A. Bosma-Moody, Aryan, S. Leibler, and members of the Guet and Tkačik groups for helpful discussion, comments, and suggestions. We thank A. Moglich, T. Mathes, J. Tabor, and S. Schmidl for kind gifts of strains, and R. Hauschild, B. Knep, M. Lang, T. Asenov, E. Papusheva, T. Menner, T. Adletzberger, and J. Merrin for technical assistance. 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 no. [291734]. (to R.C. and J.R.), Austrian Science Fund grant FWF P28844 (to G.T.), and internal IST Austria Interdisciplinary Project Support. J.R. acknowledges support from the Agence Nationale de la Recherche (ANR) under Grant Nos. ANR-16-CE33-0018 (MEMIP), ANR-16-CE12-0025 (COGEX) and ANR-10-BINF-06-01 (ICEBERG).","ec_funded":1,"publist_id":"7191","file_date_updated":"2020-07-14T12:47:20Z","article_number":"1535","language":[{"iso":"eng"}],"doi":"10.1038/s41467-017-01683-1","project":[{"grant_number":"291734","_id":"25681D80-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"International IST Postdoc Fellowship Programme"},{"grant_number":"P28844-B27","_id":"254E9036-B435-11E9-9278-68D0E5697425","name":"Biophysics of information processing in gene regulation","call_identifier":"FWF"}],"quality_controlled":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"publication_identifier":{"issn":["20411723"]},"month":"12","oa_version":"Published Version","file":[{"file_name":"IST-2017-911-v1+1_s41467-017-01683-1.pdf","access_level":"open_access","creator":"system","file_size":1951699,"content_type":"application/pdf","file_id":"5190","relation":"main_file","date_created":"2018-12-12T10:16:05Z","date_updated":"2020-07-14T12:47:20Z","checksum":"44bb5d0229926c23a9955d9fe0f9723f"}],"pubrep_id":"911","intvolume":" 8","ddc":["576","579"],"title":"Shaping bacterial population behavior through computer interfaced control of individual cells","status":"public","_id":"613","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","issue":"1","abstract":[{"text":"Bacteria in groups vary individually, and interact with other bacteria and the environment to produce population-level patterns of gene expression. Investigating such behavior in detail requires measuring and controlling populations at the single-cell level alongside precisely specified interactions and environmental characteristics. Here we present an automated, programmable platform that combines image-based gene expression and growth measurements with on-line optogenetic expression control for hundreds of individual Escherichia coli cells over days, in a dynamically adjustable environment. This integrated platform broadly enables experiments that bridge individual and population behaviors. We demonstrate: (i) population structuring by independent closed-loop control of gene expression in many individual cells, (ii) cell-cell variation control during antibiotic perturbation, (iii) hybrid bio-digital circuits in single cells, and freely specifiable digital communication between individual bacteria. These examples showcase the potential for real-time integration of theoretical models with measurement and control of many individual cells to investigate and engineer microbial population behavior.","lang":"eng"}],"type":"journal_article","date_published":"2017-12-01T00:00:00Z","citation":{"mla":"Chait, Remy P., et al. “Shaping Bacterial Population Behavior through Computer Interfaced Control of Individual Cells.” Nature Communications, vol. 8, no. 1, 1535, Nature Publishing Group, 2017, doi:10.1038/s41467-017-01683-1.","short":"R.P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, C.C. Guet, Nature Communications 8 (2017).","chicago":"Chait, Remy P, Jakob Ruess, Tobias Bergmiller, Gašper Tkačik, and Calin C Guet. “Shaping Bacterial Population Behavior through Computer Interfaced Control of Individual Cells.” Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/s41467-017-01683-1.","ama":"Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. Shaping bacterial population behavior through computer interfaced control of individual cells. Nature Communications. 2017;8(1). doi:10.1038/s41467-017-01683-1","ista":"Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. 2017. Shaping bacterial population behavior through computer interfaced control of individual cells. Nature Communications. 8(1), 1535.","apa":"Chait, R. P., Ruess, J., Bergmiller, T., Tkačik, G., & Guet, C. C. (2017). Shaping bacterial population behavior through computer interfaced control of individual cells. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-01683-1","ieee":"R. P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, and C. C. Guet, “Shaping bacterial population behavior through computer interfaced control of individual cells,” Nature Communications, vol. 8, no. 1. Nature Publishing Group, 2017."},"publication":"Nature Communications","has_accepted_license":"1","article_processing_charge":"Yes (in subscription journal)","day":"01","scopus_import":1},{"pubrep_id":"909","file":[{"content_type":"application/pdf","file_size":682064,"creator":"system","file_name":"IST-2017-909-v1+1_peerj-3830.pdf","access_level":"open_access","date_updated":"2020-07-14T12:47:24Z","date_created":"2018-12-12T10:11:51Z","checksum":"3d79ae6b6eabc90b0eaaed82ff3493b0","relation":"main_file","file_id":"4908"}],"oa_version":"Published Version","_id":"624","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","intvolume":" 2017","status":"public","title":"MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations","ddc":["579"],"issue":"9","abstract":[{"lang":"eng","text":"Bacteria adapt to adverse environmental conditions by altering gene expression patterns. Recently, a novel stress adaptation mechanism has been described that allows Escherichia coli to alter gene expression at the post-transcriptional level. The key player in this regulatory pathway is the endoribonuclease MazF, the toxin component of the toxin-antitoxin module mazEF that is triggered by various stressful conditions. In general, MazF degrades the majority of transcripts by cleaving at ACA sites, which results in the retardation of bacterial growth. Furthermore, MazF can process a small subset of mRNAs and render them leaderless by removing their ribosome binding site. MazF concomitantly modifies ribosomes, making them selective for the translation of leaderless mRNAs. In this study, we employed fluorescent reporter-systems to investigate mazEF expression during stressful conditions, and to infer consequences of the mRNA processing mediated by MazF on gene expression at the single-cell level. Our results suggest that mazEF transcription is maintained at low levels in single cells encountering adverse conditions, such as antibiotic stress or amino acid starvation. Moreover, using the grcA mRNA as a model for MazF-mediated mRNA processing, we found that MazF activation promotes heterogeneity in the grcA reporter expression, resulting in a subpopulation of cells with increased levels of GrcA reporter protein."}],"type":"journal_article","date_published":"2017-09-21T00:00:00Z","citation":{"mla":"Nikolic, Nela, et al. “MazF Activation Promotes Translational Heterogeneity of the GrcA MRNA in Escherichia Coli Populations.” PeerJ, vol. 2017, no. 9, 3830, PeerJ, 2017, doi:10.7717/peerj.3830.","short":"N. Nikolic, Z. Didara, I. Moll, PeerJ 2017 (2017).","chicago":"Nikolic, Nela, Zrinka Didara, and Isabella Moll. “MazF Activation Promotes Translational Heterogeneity of the GrcA MRNA in Escherichia Coli Populations.” PeerJ. PeerJ, 2017. https://doi.org/10.7717/peerj.3830.","ama":"Nikolic N, Didara Z, Moll I. MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations. PeerJ. 2017;2017(9). doi:10.7717/peerj.3830","ista":"Nikolic N, Didara Z, Moll I. 2017. MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations. PeerJ. 2017(9), 3830.","ieee":"N. Nikolic, Z. Didara, and I. Moll, “MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations,” PeerJ, vol. 2017, no. 9. PeerJ, 2017.","apa":"Nikolic, N., Didara, Z., & Moll, I. (2017). MazF activation promotes translational heterogeneity of the grcA mRNA in Escherichia coli populations. PeerJ. PeerJ. https://doi.org/10.7717/peerj.3830"},"publication":"PeerJ","has_accepted_license":"1","day":"21","scopus_import":1,"author":[{"id":"42D9CABC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9068-6090","first_name":"Nela","last_name":"Nikolic","full_name":"Nikolic, Nela"},{"last_name":"Didara","first_name":"Zrinka","full_name":"Didara, Zrinka"},{"full_name":"Moll, Isabella","first_name":"Isabella","last_name":"Moll"}],"volume":2017,"date_created":"2018-12-11T11:47:33Z","date_updated":"2021-01-12T08:06:48Z","acknowledgement":"Austrian Science Fund (FWF): M1697, P22249; Swiss National Science Foundation (SNF): 145706; European Commission;FWF Special Research Program: RNA-REG F43","year":"2017","department":[{"_id":"CaGu"}],"publisher":"PeerJ","publication_status":"published","publist_id":"7172","file_date_updated":"2020-07-14T12:47:24Z","article_number":"3830","doi":"10.7717/peerj.3830","language":[{"iso":"eng"}],"oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"quality_controlled":"1","publication_identifier":{"issn":["21678359"]},"month":"09"},{"has_accepted_license":"1","day":"06","scopus_import":1,"date_published":"2017-03-06T00:00:00Z","citation":{"ama":"Renault T, Abraham A, Bergmiller T, et al. Bacterial flagella grow through an injection diffusion mechanism. eLife. 2017;6. doi:10.7554/eLife.23136","apa":"Renault, T., Abraham, A., Bergmiller, T., Paradis, G., Rainville, S., Charpentier, E., … Erhardt, M. (2017). Bacterial flagella grow through an injection diffusion mechanism. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.23136","ieee":"T. Renault et al., “Bacterial flagella grow through an injection diffusion mechanism,” eLife, vol. 6. eLife Sciences Publications, 2017.","ista":"Renault T, Abraham A, Bergmiller T, Paradis G, Rainville S, Charpentier E, Guet CC, Tu Y, Namba K, Keener J, Minamino T, Erhardt M. 2017. Bacterial flagella grow through an injection diffusion mechanism. eLife. 6, e23136.","short":"T. Renault, A. Abraham, T. Bergmiller, G. Paradis, S. Rainville, E. Charpentier, C.C. Guet, Y. Tu, K. Namba, J. Keener, T. Minamino, M. Erhardt, ELife 6 (2017).","mla":"Renault, Thibaud, et al. “Bacterial Flagella Grow through an Injection Diffusion Mechanism.” ELife, vol. 6, e23136, eLife Sciences Publications, 2017, doi:10.7554/eLife.23136.","chicago":"Renault, Thibaud, Anthony Abraham, Tobias Bergmiller, Guillaume Paradis, Simon Rainville, Emmanuelle Charpentier, Calin C Guet, et al. “Bacterial Flagella Grow through an Injection Diffusion Mechanism.” ELife. eLife Sciences Publications, 2017. https://doi.org/10.7554/eLife.23136."},"publication":"eLife","abstract":[{"lang":"eng","text":"The bacterial flagellum is a self-assembling nanomachine. The external flagellar filament, several times longer than a bacterial cell body, is made of a few tens of thousands subunits of a single protein: flagellin. A fundamental problem concerns the molecular mechanism of how the flagellum grows outside the cell, where no discernible energy source is available. Here, we monitored the dynamic assembly of individual flagella using in situ labelling and real-time immunostaining of elongating flagellar filaments. We report that the rate of flagellum growth, initially ~1,700 amino acids per second, decreases with length and that the previously proposed chain mechanism does not contribute to the filament elongation dynamics. Inhibition of the proton motive force-dependent export apparatus revealed a major contribution of substrate injection in driving filament elongation. The combination of experimental and mathematical evidence demonstrates that a simple, injection-diffusion mechanism controls bacterial flagella growth outside the cell."}],"type":"journal_article","file":[{"date_created":"2018-12-12T10:08:53Z","date_updated":"2020-07-14T12:47:33Z","checksum":"39e1c3e82ddac83a30422fa72fa1a383","relation":"main_file","file_id":"4716","content_type":"application/pdf","file_size":5520359,"creator":"system","file_name":"IST-2017-904-v1+1_elife-23136-v2.pdf","access_level":"open_access"},{"checksum":"a6d542253028f52e00aa29739ddffe8f","date_updated":"2020-07-14T12:47:33Z","date_created":"2018-12-12T10:08:54Z","relation":"main_file","file_id":"4717","file_size":11242920,"content_type":"application/pdf","creator":"system","access_level":"open_access","file_name":"IST-2017-904-v1+2_elife-23136-figures-v2.pdf"}],"oa_version":"Published Version","pubrep_id":"904","intvolume":" 6","ddc":["579"],"title":"Bacterial flagella grow through an injection diffusion mechanism","status":"public","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"655","publication_identifier":{"issn":["2050084X"]},"month":"03","language":[{"iso":"eng"}],"doi":"10.7554/eLife.23136","quality_controlled":"1","oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"publist_id":"7082","file_date_updated":"2020-07-14T12:47:33Z","article_number":"e23136","volume":6,"date_created":"2018-12-11T11:47:44Z","date_updated":"2021-01-12T08:07:55Z","author":[{"last_name":"Renault","first_name":"Thibaud","full_name":"Renault, Thibaud"},{"full_name":"Abraham, Anthony","last_name":"Abraham","first_name":"Anthony"},{"full_name":"Bergmiller, Tobias","first_name":"Tobias","last_name":"Bergmiller","id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5396-4346"},{"first_name":"Guillaume","last_name":"Paradis","full_name":"Paradis, Guillaume"},{"full_name":"Rainville, Simon","first_name":"Simon","last_name":"Rainville"},{"last_name":"Charpentier","first_name":"Emmanuelle","full_name":"Charpentier, Emmanuelle"},{"id":"47F8433E-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6220-2052","first_name":"Calin C","last_name":"Guet","full_name":"Guet, Calin C"},{"full_name":"Tu, Yuhai","first_name":"Yuhai","last_name":"Tu"},{"full_name":"Namba, Keiichi","first_name":"Keiichi","last_name":"Namba"},{"first_name":"James","last_name":"Keener","full_name":"Keener, James"},{"last_name":"Minamino","first_name":"Tohru","full_name":"Minamino, Tohru"},{"last_name":"Erhardt","first_name":"Marc","full_name":"Erhardt, Marc"}],"publisher":"eLife Sciences Publications","department":[{"_id":"CaGu"}],"publication_status":"published","year":"2017"},{"publication":"PLoS Genetics","citation":{"chicago":"Nikolic, Nela, Frank Schreiber, Alma Dal Co, Daniel Kiviet, Tobias Bergmiller, Sten Littmann, Marcel Kuypers, and Martin Ackermann. “Cell-to-Cell Variation and Specialization in Sugar Metabolism in Clonal Bacterial Populations.” PLoS Genetics. Public Library of Science, 2017. https://doi.org/10.1371/journal.pgen.1007122.","mla":"Nikolic, Nela, et al. “Cell-to-Cell Variation and Specialization in Sugar Metabolism in Clonal Bacterial Populations.” PLoS Genetics, vol. 13, no. 12, e1007122, Public Library of Science, 2017, doi:10.1371/journal.pgen.1007122.","short":"N. Nikolic, F. Schreiber, A. Dal Co, D. Kiviet, T. Bergmiller, S. Littmann, M. Kuypers, M. Ackermann, PLoS Genetics 13 (2017).","ista":"Nikolic N, Schreiber F, Dal Co A, Kiviet D, Bergmiller T, Littmann S, Kuypers M, Ackermann M. 2017. Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations. PLoS Genetics. 13(12), e1007122.","apa":"Nikolic, N., Schreiber, F., Dal Co, A., Kiviet, D., Bergmiller, T., Littmann, S., … Ackermann, M. (2017). Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations. PLoS Genetics. Public Library of Science. https://doi.org/10.1371/journal.pgen.1007122","ieee":"N. Nikolic et al., “Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations,” PLoS Genetics, vol. 13, no. 12. Public Library of Science, 2017.","ama":"Nikolic N, Schreiber F, Dal Co A, et al. Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations. PLoS Genetics. 2017;13(12). doi:10.1371/journal.pgen.1007122"},"date_published":"2017-12-18T00:00:00Z","scopus_import":1,"day":"18","has_accepted_license":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"541","status":"public","title":"Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations","ddc":["576","579"],"intvolume":" 13","pubrep_id":"959","file":[{"creator":"system","file_size":1308475,"content_type":"application/pdf","access_level":"open_access","file_name":"IST-2018-959-v1+1_2017_Nikolic_Cell-to-cell.pdf","checksum":"22426d9382f21554bad5fa5967afcfd0","date_updated":"2020-07-14T12:46:46Z","date_created":"2018-12-12T10:14:35Z","file_id":"5088","relation":"main_file"}],"oa_version":"Published Version","type":"journal_article","abstract":[{"text":"While we have good understanding of bacterial metabolism at the population level, we know little about the metabolic behavior of individual cells: do single cells in clonal populations sometimes specialize on different metabolic pathways? Such metabolic specialization could be driven by stochastic gene expression and could provide individual cells with growth benefits of specialization. We measured the degree of phenotypic specialization in two parallel metabolic pathways, the assimilation of glucose and arabinose. We grew Escherichia coli in chemostats, and used isotope-labeled sugars in combination with nanometer-scale secondary ion mass spectrometry and mathematical modeling to quantify sugar assimilation at the single-cell level. We found large variation in metabolic activities between single cells, both in absolute assimilation and in the degree to which individual cells specialize in the assimilation of different sugars. Analysis of transcriptional reporters indicated that this variation was at least partially based on cell-to-cell variation in gene expression. Metabolic differences between cells in clonal populations could potentially reduce metabolic incompatibilities between different pathways, and increase the rate at which parallel reactions can be performed.","lang":"eng"}],"issue":"12","oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"quality_controlled":"1","project":[{"name":"International IST Postdoc Fellowship Programme","call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","grant_number":"291734"}],"doi":"10.1371/journal.pgen.1007122","language":[{"iso":"eng"}],"month":"12","publication_identifier":{"issn":["15537390"]},"year":"2017","publication_status":"published","department":[{"_id":"CaGu"}],"publisher":"Public Library of Science","author":[{"full_name":"Nikolic, Nela","first_name":"Nela","last_name":"Nikolic","id":"42D9CABC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9068-6090"},{"full_name":"Schreiber, Frank","last_name":"Schreiber","first_name":"Frank"},{"full_name":"Dal Co, Alma","first_name":"Alma","last_name":"Dal Co"},{"last_name":"Kiviet","first_name":"Daniel","full_name":"Kiviet, Daniel"},{"id":"2C471CFA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5396-4346","first_name":"Tobias","last_name":"Bergmiller","full_name":"Bergmiller, Tobias"},{"last_name":"Littmann","first_name":"Sten","full_name":"Littmann, Sten"},{"first_name":"Marcel","last_name":"Kuypers","full_name":"Kuypers, Marcel"},{"full_name":"Ackermann, Martin","first_name":"Martin","last_name":"Ackermann"}],"related_material":{"record":[{"relation":"research_data","status":"public","id":"9844"},{"id":"9845","status":"public","relation":"research_data"},{"status":"public","relation":"research_data","id":"9846"}]},"date_created":"2018-12-11T11:47:04Z","date_updated":"2023-02-23T14:10:34Z","volume":13,"article_number":"e1007122","file_date_updated":"2020-07-14T12:46:46Z","publist_id":"7275","ec_funded":1},{"article_processing_charge":"No","month":"11","day":"27","oa":1,"citation":{"ista":"Pleska M, Guet CC. 2017. Supplementary materials and methods; Full data set from effects of mutations in phage restriction sites during escape from restriction–modification, The Royal Society, 10.6084/m9.figshare.5633917.v1.","apa":"Pleska, M., & Guet, C. C. (2017). Supplementary materials and methods; Full data set from effects of mutations in phage restriction sites during escape from restriction–modification. The Royal Society. https://doi.org/10.6084/m9.figshare.5633917.v1","ieee":"M. Pleska and C. C. Guet, “Supplementary materials and methods; Full data set from effects of mutations in phage restriction sites during escape from restriction–modification.” The Royal Society, 2017.","ama":"Pleska M, Guet CC. Supplementary materials and methods; Full data set from effects of mutations in phage restriction sites during escape from restriction–modification. 2017. doi:10.6084/m9.figshare.5633917.v1","chicago":"Pleska, Maros, and Calin C Guet. “Supplementary Materials and Methods; Full Data Set from Effects of Mutations in Phage Restriction Sites during Escape from Restriction–Modification.” The Royal Society, 2017. https://doi.org/10.6084/m9.figshare.5633917.v1.","mla":"Pleska, Maros, and Calin C. Guet. Supplementary Materials and Methods; Full Data Set from Effects of Mutations in Phage Restriction Sites during Escape from Restriction–Modification. The Royal Society, 2017, doi:10.6084/m9.figshare.5633917.v1.","short":"M. Pleska, C.C. 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