[{"publication_status":"published","publication_identifier":{"issn":["2050084X"]},"language":[{"iso":"eng"}],"file":[{"date_created":"2018-12-12T10:14:42Z","file_name":"IST-2017-918-v1+1_elife-28921-figures-v3.pdf","date_updated":"2020-07-14T12:47:10Z","file_size":8453470,"creator":"system","file_id":"5096","checksum":"273ab17f33305e4eaafd911ff88e7c5b","content_type":"application/pdf","access_level":"open_access","relation":"main_file"},{"file_id":"5097","checksum":"b433f90576c7be597cd43367946f8e7f","content_type":"application/pdf","access_level":"open_access","relation":"main_file","date_created":"2018-12-12T10:14:43Z","file_name":"IST-2017-918-v1+2_elife-28921-v3.pdf","date_updated":"2020-07-14T12:47:10Z","file_size":1953221,"creator":"system"}],"ec_funded":1,"volume":6,"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"}],"oa_version":"Published Version","scopus_import":1,"intvolume":" 6","month":"11","date_updated":"2021-01-12T08:03:15Z","ddc":["576"],"department":[{"_id":"CaGu"},{"_id":"JoBo"},{"_id":"NiBa"}],"file_date_updated":"2020-07-14T12:47:10Z","_id":"570","tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)"},"type":"journal_article","pubrep_id":"918","status":"public","year":"2017","has_accepted_license":"1","publication":"eLife","day":"13","date_created":"2018-12-11T11:47:14Z","doi":"10.7554/eLife.28921","date_published":"2017-11-13T00:00:00Z","oa":1,"publisher":"eLife Sciences Publications","quality_controlled":"1","citation":{"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.","ista":"Lagator M, Sarikas S, Acar H, Bollback JP, Guet CC. 2017. Regulatory network structure determines patterns of intermolecular epistasis. eLife. 6, e28921.","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.","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","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","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.","short":"M. Lagator, S. Sarikas, H. Acar, J.P. Bollback, C.C. Guet, ELife 6 (2017)."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"id":"345D25EC-F248-11E8-B48F-1D18A9856A87","first_name":"Mato","full_name":"Lagator, Mato","last_name":"Lagator"},{"id":"35F0286E-F248-11E8-B48F-1D18A9856A87","first_name":"Srdjan","full_name":"Sarikas, Srdjan","last_name":"Sarikas"},{"last_name":"Acar","full_name":"Acar, Hande","orcid":"0000-0003-1986-9753","id":"2DDF136A-F248-11E8-B48F-1D18A9856A87","first_name":"Hande"},{"id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87","first_name":"Jonathan P","last_name":"Bollback","full_name":"Bollback, Jonathan P","orcid":"0000-0002-4624-4612"},{"last_name":"Guet","orcid":"0000-0001-6220-2052","full_name":"Guet, Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87","first_name":"Calin C"}],"publist_id":"7244","title":"Regulatory network structure determines patterns of intermolecular epistasis","article_number":"e28921","project":[{"call_identifier":"FP7","_id":"25681D80-B435-11E9-9278-68D0E5697425","name":"International IST Postdoc Fellowship Programme","grant_number":"291734"},{"_id":"2578D616-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"Selective Barriers to Horizontal Gene Transfer","grant_number":"648440"}]},{"project":[{"name":"Selective Barriers to Horizontal Gene Transfer","grant_number":"648440","call_identifier":"H2020","_id":"2578D616-B435-11E9-9278-68D0E5697425"}],"article_processing_charge":"No","author":[{"last_name":"Acar","orcid":"0000-0003-1986-9753","full_name":"Acar, Hande","first_name":"Hande","id":"2DDF136A-F248-11E8-B48F-1D18A9856A87"}],"publist_id":"6239","title":"Selective barriers to horizontal gene transfer","citation":{"mla":"Acar, Hande. Selective Barriers to Horizontal Gene Transfer. Institute of Science and Technology Austria, 2016.","ieee":"H. Acar, “Selective barriers to horizontal gene transfer,” Institute of Science and Technology Austria, 2016.","short":"H. Acar, Selective Barriers to Horizontal Gene Transfer, Institute of Science and Technology Austria, 2016.","apa":"Acar, H. (2016). Selective barriers to horizontal gene transfer. Institute of Science and Technology Austria.","ama":"Acar H. Selective barriers to horizontal gene transfer. 2016.","chicago":"Acar, Hande. “Selective Barriers to Horizontal Gene Transfer.” Institute of Science and Technology Austria, 2016.","ista":"Acar H. 2016. Selective barriers to horizontal gene transfer. Institute of Science and Technology Austria."},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","oa":1,"publisher":"Institute of Science and Technology Austria","acknowledgement":"This study was supported by European Research Council ERC CoG 2014 – EVOLHGT,\r\nunder the grant number 648440.\r\n\r\nIt is a pleasure to thank the many people who made this thesis possible.\r\nI would like to first thank my advisor, Jonathan Paul Bollback for providing guidance in\r\nall aspects of my life, encouragement, sound advice, and good teaching over the last six\r\nyears.\r\nI would also like to thank the members of my dissertation committee – Călin C. Guet\r\nand John F. Baines – not only for their time and guidance, but for their intellectual\r\ncontributions to my development as a scientist.\r\nI would like to thank Flavia Gama and Rodrigo Redondo who have taught me all the\r\nskills in the laboratory with their graciousness and friendship. Also special thanks to\r\nBollback group for their support and for providing a stimulating and fun environment:\r\nIsabella Tomanek, Fabienne Jesse, Claudia Igler, and Pavel Payne.\r\nJerneja Beslagic is not only an amazing assistant, she also has a smile brighter and\r\nwarmer than the sunshine, bringing happiness to every moment. Always keep your light\r\nNeja, I will miss our invaluable chatters a lot.","page":"75","date_created":"2018-12-11T11:50:16Z","date_published":"2016-12-01T00:00:00Z","year":"2016","has_accepted_license":"1","day":"01","type":"dissertation","status":"public","_id":"1121","department":[{"_id":"JoBo"}],"file_date_updated":"2021-02-22T11:51:13Z","date_updated":"2023-09-07T11:42:26Z","supervisor":[{"last_name":"Bollback","orcid":"0000-0002-4624-4612","full_name":"Bollback, Jonathan P","first_name":"Jonathan P","id":"2C6FA9CC-F248-11E8-B48F-1D18A9856A87"}],"ddc":["570"],"alternative_title":["ISTA Thesis"],"month":"12","abstract":[{"lang":"eng","text":"Horizontal gene transfer (HGT), the lateral acquisition of genes across existing species\r\nboundaries, is a major evolutionary force shaping microbial genomes that facilitates\r\nadaptation to new environments as well as resistance to antimicrobial drugs. As such,\r\nunderstanding the mechanisms and constraints that determine the outcomes of HGT\r\nevents is crucial to understand the dynamics of HGT and to design better strategies to\r\novercome the challenges that originate from it.\r\nFollowing the insertion and expression of a newly transferred gene, the success of an\r\nHGT event will depend on the fitness effect it has on the recipient (host) cell. Therefore,\r\npredicting the impact of HGT on the genetic composition of a population critically\r\ndepends on the distribution of fitness effects (DFE) of horizontally transferred genes.\r\nHowever, to date, we have little knowledge of the DFE of newly transferred genes, and\r\nhence little is known about the shape and scale of this distribution.\r\nIt is particularly important to better understand the selective barriers that determine\r\nthe fitness effects of newly transferred genes. In spite of substantial bioinformatics\r\nefforts to identify horizontally transferred genes and selective barriers, a systematic\r\nexperimental approach to elucidate the roles of different selective barriers in defining\r\nthe fate of a transfer event has largely been absent. Similarly, although the fact that\r\nenvironment might alter the fitness effect of a horizontally transferred gene may seem\r\nobvious, little attention has been given to it in a systematic experimental manner.\r\nIn this study, we developed a systematic experimental approach that consists of\r\ntransferring 44 arbitrarily selected Salmonella typhimurium orthologous genes into an\r\nEscherichia coli host, and estimating the fitness effects of these transferred genes at a\r\nconstant expression level by performing competition assays against the wild type.\r\nIn chapter 2, we performed one-to-one competition assays between a mutant strain\r\ncarrying a transferred gene and the wild type strain. By using flow cytometry we\r\nestimated selection coefficients for the transferred genes with a precision level of 10-3,and obtained the DFE of horizontally transferred genes. We then investigated if these\r\nfitness effects could be predicted by any of the intrinsic properties of the genes, namely,\r\nfunctional category, degree of complexity (protein-protein interactions), GC content,\r\ncodon usage and length. Our analyses revealed that the functional category and length\r\nof the genes act as potential selective barriers. Finally, using the same procedure with\r\nthe endogenous E. coli orthologs of these 44 genes, we demonstrated that gene dosage is\r\nthe most prominent selective barrier to HGT.\r\nIn chapter 3, using the same set of genes we investigated the role of environment on the\r\nsuccess of HGT events. Under six different environments with different levels of stress\r\nwe performed more complex competition assays, where we mixed all 44 mutant strains\r\ncarrying transferred genes with the wild type strain. To estimate the fitness effects of\r\ngenes relative to wild type we used next generation sequencing. We found that the DFEs\r\nof horizontally transferred genes are highly dependent on the environment, with\r\nabundant gene–by-environment interactions. Furthermore, we demonstrated a\r\nrelationship between average fitness effect of a gene across all environments and its\r\nenvironmental variance, and thus its predictability. Finally, in spite of the fitness effects\r\nof genes being highly environment-dependent, we still observed a common shape of\r\nDFEs across all tested environments."}],"oa_version":"Published Version","ec_funded":1,"publication_status":"published","degree_awarded":"PhD","publication_identifier":{"issn":["2663-337X"]},"language":[{"iso":"eng"}],"file":[{"creator":"dernst","file_size":3682711,"date_updated":"2019-08-13T11:17:50Z","file_name":"PhDThesis_HandeAcar_1230.pdf","date_created":"2019-08-13T11:17:50Z","relation":"main_file","access_level":"closed","content_type":"application/pdf","checksum":"94bbbc754c36115bf37f8fc11fad43c4","file_id":"6814"},{"content_type":"application/pdf","relation":"main_file","access_level":"open_access","success":1,"checksum":"94bbbc754c36115bf37f8fc11fad43c4","file_id":"9184","file_size":3682711,"date_updated":"2021-02-22T11:51:13Z","creator":"dernst","file_name":"2016_Thesis_HandeAcar.pdf","date_created":"2021-02-22T11:51:13Z"}]},{"pmid":1,"oa_version":"None","abstract":[{"lang":"eng","text":"In the 1960s-1980s, determination of bacterial growth rates was an important tool in microbial genetics, biochemistry, molecular biology, and microbial physiology. The exciting technical developments of the 1990s and the 2000s eclipsed that tool; as a result, many investigators today lack experience with growth rate measurements. Recently, investigators in a number of areas have started to use measurements of bacterial growth rates for a variety of purposes. Those measurements have been greatly facilitated by the availability of microwell plate readers that permit the simultaneous measurements on up to 384 different cultures. Only the exponential (logarithmic) portions of the resulting growth curves are useful for determining growth rates, and manual determination of that portion and calculation of growth rates can be tedious for high-throughput purposes. Here, we introduce the program GrowthRates that uses plate reader output files to automatically determine the exponential portion of the curve and to automatically calculate the growth rate, the maximum culture density, and the duration of the growth lag phase. GrowthRates is freely available for Macintosh, Windows, and Linux.We discuss the effects of culture volume, the classical bacterial growth curve, and the differences between determinations in rich media and minimal (mineral salts) media. This protocol covers calibration of the plate reader, growth of culture inocula for both rich and minimal media, and experimental setup. As a guide to reliability, we report typical day-to-day variation in growth rates and variation within experiments with respect to position of wells within the plates."}],"intvolume":" 31","month":"01","scopus_import":"1","language":[{"iso":"eng"}],"publication_status":"published","publication_identifier":{"issn":["0737-4038"],"eissn":["1537-1719"]},"volume":31,"issue":"1","_id":"1902","status":"public","type":"journal_article","article_type":"original","date_updated":"2022-06-07T11:08:13Z","department":[{"_id":"JoBo"}],"quality_controlled":"1","publisher":"Oxford University Press","publication":"Molecular Biology and Evolution","day":"01","year":"2014","date_created":"2018-12-11T11:54:37Z","doi":"10.1093/molbev/mst187","date_published":"2014-01-01T00:00:00Z","page":"232 - 238","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"chicago":"Hall, Barry, Hande Acar, Anna Nandipati, and Miriam Barlow. “Growth Rates Made Easy.” Molecular Biology and Evolution. Oxford University Press, 2014. https://doi.org/10.1093/molbev/mst187.","ista":"Hall B, Acar H, Nandipati A, Barlow M. 2014. Growth rates made easy. Molecular Biology and Evolution. 31(1), 232–238.","mla":"Hall, Barry, et al. “Growth Rates Made Easy.” Molecular Biology and Evolution, vol. 31, no. 1, Oxford University Press, 2014, pp. 232–38, doi:10.1093/molbev/mst187.","ama":"Hall B, Acar H, Nandipati A, Barlow M. Growth rates made easy. Molecular Biology and Evolution. 2014;31(1):232-238. doi:10.1093/molbev/mst187","apa":"Hall, B., Acar, H., Nandipati, A., & Barlow, M. (2014). Growth rates made easy. Molecular Biology and Evolution. Oxford University Press. https://doi.org/10.1093/molbev/mst187","short":"B. Hall, H. Acar, A. Nandipati, M. Barlow, Molecular Biology and Evolution 31 (2014) 232–238.","ieee":"B. Hall, H. Acar, A. Nandipati, and M. Barlow, “Growth rates made easy,” Molecular Biology and Evolution, vol. 31, no. 1. Oxford University Press, pp. 232–238, 2014."},"title":"Growth rates made easy","article_processing_charge":"No","external_id":{"pmid":["24170494"]},"publist_id":"5193","author":[{"first_name":"Barry","full_name":"Hall, Barry","last_name":"Hall"},{"first_name":"Hande","id":"2DDF136A-F248-11E8-B48F-1D18A9856A87","last_name":"Acar","orcid":"0000-0003-1986-9753","full_name":"Acar, Hande"},{"last_name":"Nandipati","full_name":"Nandipati, Anna","first_name":"Anna"},{"first_name":"Miriam","last_name":"Barlow","full_name":"Barlow, Miriam"}]}]