[{"volume":4,"related_material":{"record":[{"status":"public","id":"818","relation":"dissertation_contains"}]},"issue":"4","license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","ec_funded":1,"publication_identifier":{"issn":["24054712"]},"publication_status":"published","file":[{"file_size":2438660,"date_updated":"2020-07-14T12:47:35Z","creator":"system","file_name":"IST-2017-901-v1+1_1-s2.0-S2405471217300868-main.pdf","date_created":"2018-12-12T10:13:54Z","content_type":"application/pdf","relation":"main_file","access_level":"open_access","checksum":"04ff20011c3d9a601c514aa999a5fe1a","file_id":"5041"}],"language":[{"iso":"eng"}],"scopus_import":1,"month":"04","intvolume":" 4","abstract":[{"text":"Antibiotics elicit drastic changes in microbial gene expression, including the induction of stress response genes. While certain stress responses are known to “cross-protect” bacteria from other stressors, it is unclear whether cellular responses to antibiotics have a similar protective role. By measuring the genome-wide transcriptional response dynamics of Escherichia coli to four antibiotics, we found that trimethoprim induces a rapid acid stress response that protects bacteria from subsequent exposure to acid. Combining microfluidics with time-lapse imaging to monitor survival and acid stress response in single cells revealed that the noisy expression of the acid resistance operon gadBC correlates with single-cell survival. Cells with higher gadBC expression following trimethoprim maintain higher intracellular pH and survive the acid stress longer. The seemingly random single-cell survival under acid stress can therefore be predicted from gadBC expression and rationalized in terms of GadB/C molecular function. Overall, we provide a roadmap for identifying the molecular mechanisms of single-cell cross-protection between antibiotics and other stressors.","lang":"eng"}],"oa_version":"Published Version","department":[{"_id":"ToBo"},{"_id":"GaTk"}],"file_date_updated":"2020-07-14T12:47:35Z","date_updated":"2023-09-07T12:00:25Z","ddc":["576","610"],"type":"journal_article","tmp":{"short":"CC BY-NC-ND (4.0)","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","image":"/images/cc_by_nc_nd.png"},"status":"public","pubrep_id":"901","_id":"666","page":"393 - 403","doi":"10.1016/j.cels.2017.03.001","date_published":"2017-04-26T00:00:00Z","date_created":"2018-12-11T11:47:48Z","has_accepted_license":"1","year":"2017","day":"26","publication":"Cell Systems","quality_controlled":"1","publisher":"Cell Press","oa":1,"author":[{"full_name":"Mitosch, Karin","last_name":"Mitosch","id":"39B66846-F248-11E8-B48F-1D18A9856A87","first_name":"Karin"},{"full_name":"Rieckh, Georg","last_name":"Rieckh","first_name":"Georg","id":"34DA8BD6-F248-11E8-B48F-1D18A9856A87"},{"id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","first_name":"Tobias","orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Tobias","last_name":"Bollenbach"}],"publist_id":"7061","article_processing_charge":"Yes (in subscription journal)","title":"Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment","citation":{"ieee":"K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment,” Cell Systems, vol. 4, no. 4. Cell Press, pp. 393–403, 2017.","short":"K. Mitosch, G. Rieckh, M.T. Bollenbach, Cell Systems 4 (2017) 393–403.","ama":"Mitosch K, Rieckh G, Bollenbach MT. Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. 2017;4(4):393-403. doi:10.1016/j.cels.2017.03.001","apa":"Mitosch, K., Rieckh, G., & Bollenbach, M. T. (2017). Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. Cell Press. https://doi.org/10.1016/j.cels.2017.03.001","mla":"Mitosch, Karin, et al. “Noisy Response to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.” Cell Systems, vol. 4, no. 4, Cell Press, 2017, pp. 393–403, doi:10.1016/j.cels.2017.03.001.","ista":"Mitosch K, Rieckh G, Bollenbach MT. 2017. Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. 4(4), 393–403.","chicago":"Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Noisy Response to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.” Cell Systems. Cell Press, 2017. https://doi.org/10.1016/j.cels.2017.03.001."},"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","project":[{"call_identifier":"FP7","_id":"25E83C2C-B435-11E9-9278-68D0E5697425","name":"Optimality principles in responses to antibiotics","grant_number":"303507"},{"_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Revealing the mechanisms underlying drug interactions","grant_number":"P27201-B22"},{"name":"Revealing the fundamental limits of cell growth","grant_number":"RGP0042/2013","_id":"25EB3A80-B435-11E9-9278-68D0E5697425"}]},{"ec_funded":1,"issue":"40","volume":114,"language":[{"iso":"eng"}],"publication_status":"published","publication_identifier":{"issn":["00278424"]},"intvolume":" 114","month":"10","main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635929/"}],"scopus_import":"1","oa_version":"Submitted Version","pmid":1,"abstract":[{"lang":"eng","text":"Polymicrobial infections constitute small ecosystems that accommodate several bacterial species. Commonly, these bacteria are investigated in isolation. However, it is unknown to what extent the isolates interact and whether their interactions alter bacterial growth and ecosystem resilience in the presence and absence of antibiotics. We quantified the complete ecological interaction network for 72 bacterial isolates collected from 23 individuals diagnosed with polymicrobial urinary tract infections and found that most interactions cluster based on evolutionary relatedness. Statistical network analysis revealed that competitive and cooperative reciprocal interactions are enriched in the global network, while cooperative interactions are depleted in the individual host community networks. A population dynamics model parameterized by our measurements suggests that interactions restrict community stability, explaining the observed species diversity of these communities. We further show that the clinical isolates frequently protect each other from clinically relevant antibiotics. Together, these results highlight that ecological interactions are crucial for the growth and survival of bacteria in polymicrobial infection communities and affect their assembly and resilience. "}],"department":[{"_id":"ToBo"}],"date_updated":"2023-09-26T16:18:48Z","status":"public","type":"journal_article","_id":"822","date_created":"2018-12-11T11:48:41Z","doi":"10.1073/pnas.1713372114","date_published":"2017-10-03T00:00:00Z","page":"10666 - 10671","publication":"PNAS","day":"03","year":"2017","isi":1,"oa":1,"quality_controlled":"1","publisher":"National Academy of Sciences","title":"Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections","external_id":{"isi":["000412130500061"],"pmid":["28923953"]},"article_processing_charge":"No","publist_id":"6827","author":[{"last_name":"De Vos","full_name":"De Vos, Marjon","id":"3111FFAC-F248-11E8-B48F-1D18A9856A87","first_name":"Marjon"},{"first_name":"Marcin P","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","last_name":"Zagórski","orcid":"0000-0001-7896-7762","full_name":"Zagórski, Marcin P"},{"last_name":"Mcnally","full_name":"Mcnally, Alan","first_name":"Alan"},{"last_name":"Bollenbach","orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Mark Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","first_name":"Mark Tobias"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"chicago":"Vos, Marjon de, Marcin P Zagórski, Alan Mcnally, and Mark Tobias Bollenbach. “Interaction Networks, Ecological Stability, and Collective Antibiotic Tolerance in Polymicrobial Infections.” PNAS. National Academy of Sciences, 2017. https://doi.org/10.1073/pnas.1713372114.","ista":"de Vos M, Zagórski MP, Mcnally A, Bollenbach MT. 2017. Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections. PNAS. 114(40), 10666–10671.","mla":"de Vos, Marjon, et al. “Interaction Networks, Ecological Stability, and Collective Antibiotic Tolerance in Polymicrobial Infections.” PNAS, vol. 114, no. 40, National Academy of Sciences, 2017, pp. 10666–71, doi:10.1073/pnas.1713372114.","ieee":"M. de Vos, M. P. Zagórski, A. Mcnally, and M. T. Bollenbach, “Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections,” PNAS, vol. 114, no. 40. National Academy of Sciences, pp. 10666–10671, 2017.","short":"M. de Vos, M.P. Zagórski, A. Mcnally, M.T. Bollenbach, PNAS 114 (2017) 10666–10671.","ama":"de Vos M, Zagórski MP, Mcnally A, Bollenbach MT. Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections. PNAS. 2017;114(40):10666-10671. doi:10.1073/pnas.1713372114","apa":"de Vos, M., Zagórski, M. P., Mcnally, A., & Bollenbach, M. T. (2017). Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1713372114"},"project":[{"name":"Optimality principles in responses to antibiotics","grant_number":"303507","_id":"25E83C2C-B435-11E9-9278-68D0E5697425","call_identifier":"FP7"},{"_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","grant_number":"P27201-B22","name":"Revealing the mechanisms underlying drug interactions"}]},{"title":"MATLAB analysis code for 'Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast'","file_date_updated":"2020-07-14T12:47:03Z","department":[{"_id":"ToBo"}],"article_processing_charge":"No","author":[{"full_name":"Lukacisin, Martin","orcid":"0000-0001-6549-4177","last_name":"Lukacisin","id":"298FFE8C-F248-11E8-B48F-1D18A9856A87","first_name":"Martin"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","ddc":["571"],"citation":{"chicago":"Lukacisin, Martin. “MATLAB Analysis Code for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.’” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:64.","ista":"Lukacisin M. 2017. MATLAB analysis code for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast’, Institute of Science and Technology Austria, 10.15479/AT:ISTA:64.","mla":"Lukacisin, Martin. MATLAB Analysis Code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:64.","ama":"Lukacisin M. MATLAB analysis code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” 2017. doi:10.15479/AT:ISTA:64","apa":"Lukacisin, M. (2017). MATLAB analysis code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:64","ieee":"M. Lukacisin, “MATLAB analysis code for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.’” Institute of Science and Technology Austria, 2017.","short":"M. Lukacisin, (2017)."},"date_updated":"2024-02-21T13:46:47Z","status":"public","tmp":{"short":"CC BY-SA (4.0)","image":"/images/cc_by_sa.png","legal_code_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","name":"Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0)"},"type":"research_data","_id":"5563","date_created":"2018-12-12T12:31:33Z","license":"https://creativecommons.org/licenses/by-sa/4.0/","doi":"10.15479/AT:ISTA:64","date_published":"2017-03-20T00:00:00Z","day":"20","file":[{"date_created":"2018-12-12T13:02:37Z","file_name":"IST-2016-45-v1+1_PaperCode.zip","creator":"system","date_updated":"2020-07-14T12:47:03Z","file_size":296722548,"file_id":"5602","checksum":"ee697f2b1ade4dc14d6ac0334dd832ab","access_level":"open_access","relation":"main_file","content_type":"application/zip"}],"datarep_id":"64","year":"2017","has_accepted_license":"1","month":"03","oa":1,"publisher":"Institute of Science and Technology Austria","oa_version":"Published Version","abstract":[{"text":"MATLAB code and processed datasets available for reproducing the results in: \r\nLukačišin, M.*, Landon, M.*, Jajoo, R*. (2016) Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.\r\n*equal contributions","lang":"eng"}]},{"date_published":"2017-03-16T00:00:00Z","doi":"10.1371/journal.pone.0174066","date_created":"2018-12-11T11:49:46Z","isi":1,"has_accepted_license":"1","year":"2017","day":"16","publication":"PLoS One","publisher":"Public Library of Science","quality_controlled":"1","oa":1,"author":[{"first_name":"Martin","id":"298FFE8C-F248-11E8-B48F-1D18A9856A87","last_name":"Lukacisin","orcid":"0000-0001-6549-4177","full_name":"Lukacisin, Martin"},{"first_name":"Matthieu","last_name":"Landon","full_name":"Landon, Matthieu"},{"full_name":"Jajoo, Rishi","last_name":"Jajoo","first_name":"Rishi"}],"publist_id":"6361","external_id":{"isi":["000396318300121"]},"article_processing_charge":"Yes","title":"Sequence-specific thermodynamic properties of nucleic acids influence both transcriptional pausing and backtracking in yeast","citation":{"mla":"Lukacisin, Martin, et al. “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” PLoS One, vol. 12, no. 3, e0174066, Public Library of Science, 2017, doi:10.1371/journal.pone.0174066.","ama":"Lukacisin M, Landon M, Jajoo R. Sequence-specific thermodynamic properties of nucleic acids influence both transcriptional pausing and backtracking in yeast. PLoS One. 2017;12(3). doi:10.1371/journal.pone.0174066","apa":"Lukacisin, M., Landon, M., & Jajoo, R. (2017). Sequence-specific thermodynamic properties of nucleic acids influence both transcriptional pausing and backtracking in yeast. PLoS One. Public Library of Science. https://doi.org/10.1371/journal.pone.0174066","ieee":"M. Lukacisin, M. Landon, and R. Jajoo, “Sequence-specific thermodynamic properties of nucleic acids influence both transcriptional pausing and backtracking in yeast,” PLoS One, vol. 12, no. 3. Public Library of Science, 2017.","short":"M. Lukacisin, M. Landon, R. Jajoo, PLoS One 12 (2017).","chicago":"Lukacisin, Martin, Matthieu Landon, and Rishi Jajoo. “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” PLoS One. Public Library of Science, 2017. https://doi.org/10.1371/journal.pone.0174066.","ista":"Lukacisin M, Landon M, Jajoo R. 2017. Sequence-specific thermodynamic properties of nucleic acids influence both transcriptional pausing and backtracking in yeast. PLoS One. 12(3), e0174066."},"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","article_number":"e0174066","issue":"3","related_material":{"record":[{"relation":"popular_science","status":"public","id":"5556"},{"id":"6392","status":"public","relation":"dissertation_contains"}]},"volume":12,"license":"https://creativecommons.org/licenses/by/4.0/","publication_identifier":{"issn":["19326203"]},"publication_status":"published","file":[{"file_size":3429381,"date_updated":"2018-12-12T10:09:47Z","creator":"system","file_name":"IST-2017-800-v1+1_journal.pone.0174066.pdf","date_created":"2018-12-12T10:09:47Z","content_type":"application/pdf","relation":"main_file","access_level":"open_access","file_id":"4772"}],"language":[{"iso":"eng"}],"scopus_import":"1","month":"03","intvolume":" 12","abstract":[{"text":"RNA Polymerase II pauses and backtracks during transcription, with many consequences for gene expression and cellular physiology. Here, we show that the energy required to melt double-stranded nucleic acids in the transcription bubble predicts pausing in Saccharomyces cerevisiae far more accurately than nucleosome roadblocks do. In addition, the same energy difference also determines when the RNA polymerase backtracks instead of continuing to move forward. This data-driven model corroborates—in a genome wide and quantitative manner—previous evidence that sequence-dependent thermodynamic features of nucleic acids influence both transcriptional pausing and backtracking.","lang":"eng"}],"oa_version":"Published Version","file_date_updated":"2018-12-12T10:09:47Z","department":[{"_id":"ToBo"}],"date_updated":"2024-03-27T23:30:05Z","ddc":["570"],"type":"journal_article","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)"},"status":"public","pubrep_id":"800","_id":"1029"},{"type":"journal_article","article_type":"original","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)"},"status":"public","pubrep_id":"894","_id":"696","department":[{"_id":"ToBo"},{"_id":"NiBa"},{"_id":"CaGu"}],"file_date_updated":"2020-07-14T12:47:46Z","date_updated":"2024-03-27T23:30:28Z","ddc":["576"],"scopus_import":1,"month":"07","intvolume":" 13","abstract":[{"lang":"eng","text":"Mutator strains are expected to evolve when the availability and effect of beneficial mutations are high enough to counteract the disadvantage from deleterious mutations that will inevitably accumulate. As the population becomes more adapted to its environment, both availability and effect of beneficial mutations necessarily decrease and mutation rates are predicted to decrease. It has been shown that certain molecular mechanisms can lead to increased mutation rates when the organism finds itself in a stressful environment. While this may be a correlated response to other functions, it could also be an adaptive mechanism, raising mutation rates only when it is most advantageous. Here, we use a mathematical model to investigate the plausibility of the adaptive hypothesis. We show that such a mechanism can be mantained if the population is subjected to diverse stresses. By simulating various antibiotic treatment schemes, we find that combination treatments can reduce the effectiveness of second-order selection on stress-induced mutagenesis. We discuss the implications of our results to strategies of antibiotic therapy."}],"oa_version":"Published Version","volume":13,"related_material":{"record":[{"relation":"research_data","id":"9849","status":"public"},{"relation":"research_data","id":"9850","status":"public"},{"relation":"research_data","id":"9851","status":"public"},{"status":"public","id":"9852","relation":"research_data"},{"relation":"dissertation_contains","status":"public","id":"6263"}]},"issue":"7","ec_funded":1,"publication_identifier":{"issn":["1553734X"]},"publication_status":"published","file":[{"file_name":"IST-2017-894-v1+1_journal.pcbi.1005609.pdf","date_created":"2018-12-12T10:15:01Z","creator":"system","file_size":3775716,"date_updated":"2020-07-14T12:47:46Z","checksum":"9143c290fa6458ed2563bff4b295554a","file_id":"5117","relation":"main_file","access_level":"open_access","content_type":"application/pdf"}],"language":[{"iso":"eng"}],"project":[{"grant_number":"618091","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation","call_identifier":"FP7","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425"}],"article_number":"e1005609","publist_id":"7004","author":[{"last_name":"Lukacisinova","full_name":"Lukacisinova, Marta","orcid":"0000-0002-2519-8004","first_name":"Marta","id":"4342E402-F248-11E8-B48F-1D18A9856A87"},{"orcid":"0000-0002-2519-824X","full_name":"Novak, Sebastian","last_name":"Novak","id":"461468AE-F248-11E8-B48F-1D18A9856A87","first_name":"Sebastian"},{"orcid":"0000-0003-2361-3953","full_name":"Paixao, Tiago","last_name":"Paixao","first_name":"Tiago","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87"}],"title":"Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes","citation":{"ista":"Lukacisinova M, Novak S, Paixao T. 2017. Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes. PLoS Computational Biology. 13(7), e1005609.","chicago":"Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Stress Induced Mutagenesis: Stress Diversity Facilitates the Persistence of Mutator Genes.” PLoS Computational Biology. Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005609.","short":"M. Lukacisinova, S. Novak, T. Paixao, PLoS Computational Biology 13 (2017).","ieee":"M. Lukacisinova, S. Novak, and T. Paixao, “Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes,” PLoS Computational Biology, vol. 13, no. 7. Public Library of Science, 2017.","ama":"Lukacisinova M, Novak S, Paixao T. Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes. PLoS Computational Biology. 2017;13(7). doi:10.1371/journal.pcbi.1005609","apa":"Lukacisinova, M., Novak, S., & Paixao, T. (2017). Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005609","mla":"Lukacisinova, Marta, et al. “Stress Induced Mutagenesis: Stress Diversity Facilitates the Persistence of Mutator Genes.” PLoS Computational Biology, vol. 13, no. 7, e1005609, Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005609."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","quality_controlled":"1","publisher":"Public Library of Science","oa":1,"date_published":"2017-07-18T00:00:00Z","doi":"10.1371/journal.pcbi.1005609","date_created":"2018-12-11T11:47:58Z","has_accepted_license":"1","year":"2017","day":"18","publication":"PLoS Computational Biology"},{"pubrep_id":"801","status":"public","tmp":{"short":"CC BY-NC-ND (4.0)","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","image":"/images/cc_by_nc_nd.png"},"type":"journal_article","article_type":"original","_id":"1027","file_date_updated":"2019-01-18T09:57:57Z","department":[{"_id":"ToBo"}],"ddc":["570"],"date_updated":"2024-03-27T23:30:28Z","intvolume":" 46","month":"08","scopus_import":"1","oa_version":"Published Version","abstract":[{"text":"The rising prevalence of antibiotic resistant bacteria is an increasingly serious public health challenge. To address this problem, recent work ranging from clinical studies to theoretical modeling has provided valuable insights into the mechanisms of resistance, its emergence and spread, and ways to counteract it. A deeper understanding of the underlying dynamics of resistance evolution will require a combination of experimental and theoretical expertise from different disciplines and new technology for studying evolution in the laboratory. Here, we review recent advances in the quantitative understanding of the mechanisms and evolution of antibiotic resistance. We focus on key theoretical concepts and new technology that enables well-controlled experiments. We further highlight key challenges that can be met in the near future to ultimately develop effective strategies for combating resistance.","lang":"eng"}],"ec_funded":1,"related_material":{"record":[{"id":"6263","status":"public","relation":"dissertation_contains"}]},"volume":46,"language":[{"iso":"eng"}],"file":[{"creator":"dernst","file_size":858338,"date_updated":"2019-01-18T09:57:57Z","file_name":"2017_CurrentOpinion_Lukaciinova.pdf","date_created":"2019-01-18T09:57:57Z","relation":"main_file","access_level":"open_access","content_type":"application/pdf","success":1,"file_id":"5846"}],"publication_status":"published","project":[{"call_identifier":"FWF","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","name":"Revealing the mechanisms underlying drug interactions","grant_number":"P27201-B22"},{"_id":"25E83C2C-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","grant_number":"303507","name":"Optimality principles in responses to antibiotics"},{"name":"Revealing the fundamental limits of cell growth","grant_number":"RGP0042/2013","_id":"25EB3A80-B435-11E9-9278-68D0E5697425"}],"title":"Toward a quantitative understanding of antibiotic resistance evolution","external_id":{"isi":["000408077400015"]},"article_processing_charge":"Yes (in subscription journal)","publist_id":"6364","author":[{"last_name":"Lukacisinova","orcid":"0000-0002-2519-8004","full_name":"Lukacisinova, Marta","id":"4342E402-F248-11E8-B48F-1D18A9856A87","first_name":"Marta"},{"full_name":"Bollenbach, Mark Tobias","orcid":"0000-0003-4398-476X","last_name":"Bollenbach","first_name":"Mark Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","citation":{"chicago":"Lukacisinova, Marta, and Mark Tobias Bollenbach. “Toward a Quantitative Understanding of Antibiotic Resistance Evolution.” Current Opinion in Biotechnology. Elsevier, 2017. https://doi.org/10.1016/j.copbio.2017.02.013.","ista":"Lukacisinova M, Bollenbach MT. 2017. Toward a quantitative understanding of antibiotic resistance evolution. Current Opinion in Biotechnology. 46, 90–97.","mla":"Lukacisinova, Marta, and Mark Tobias Bollenbach. “Toward a Quantitative Understanding of Antibiotic Resistance Evolution.” Current Opinion in Biotechnology, vol. 46, Elsevier, 2017, pp. 90–97, doi:10.1016/j.copbio.2017.02.013.","ieee":"M. Lukacisinova and M. T. Bollenbach, “Toward a quantitative understanding of antibiotic resistance evolution,” Current Opinion in Biotechnology, vol. 46. Elsevier, pp. 90–97, 2017.","short":"M. Lukacisinova, M.T. Bollenbach, Current Opinion in Biotechnology 46 (2017) 90–97.","ama":"Lukacisinova M, Bollenbach MT. Toward a quantitative understanding of antibiotic resistance evolution. Current Opinion in Biotechnology. 2017;46:90-97. doi:10.1016/j.copbio.2017.02.013","apa":"Lukacisinova, M., & Bollenbach, M. T. (2017). Toward a quantitative understanding of antibiotic resistance evolution. Current Opinion in Biotechnology. Elsevier. https://doi.org/10.1016/j.copbio.2017.02.013"},"oa":1,"quality_controlled":"1","publisher":"Elsevier","date_created":"2018-12-11T11:49:45Z","doi":"10.1016/j.copbio.2017.02.013","date_published":"2017-08-01T00:00:00Z","page":"90 - 97","publication":"Current Opinion in Biotechnology","day":"01","year":"2017","has_accepted_license":"1","isi":1},{"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":"744","status":"public","_id":"1154","file_date_updated":"2018-12-12T10:09:32Z","department":[{"_id":"MiSi"},{"_id":"NanoFab"},{"_id":"Bio"},{"_id":"ToBo"}],"date_updated":"2021-01-12T06:48:41Z","ddc":["579"],"scopus_import":1,"intvolume":" 6","month":"11","abstract":[{"text":"Cellular locomotion is a central hallmark of eukaryotic life. It is governed by cell-extrinsic molecular factors, which can either emerge in the soluble phase or as immobilized, often adhesive ligands. To encode for direction, every cue must be present as a spatial or temporal gradient. Here, we developed a microfluidic chamber that allows measurement of cell migration in combined response to surface immobilized and soluble molecular gradients. As a proof of principle we study the response of dendritic cells to their major guidance cues, chemokines. The majority of data on chemokine gradient sensing is based on in vitro studies employing soluble gradients. Despite evidence suggesting that in vivo chemokines are often immobilized to sugar residues, limited information is available how cells respond to immobilized chemokines. We tracked migration of dendritic cells towards immobilized gradients of the chemokine CCL21 and varying superimposed soluble gradients of CCL19. Differential migratory patterns illustrate the potential of our setup to quantitatively study the competitive response to both types of gradients. Beyond chemokines our approach is broadly applicable to alternative systems of chemo- and haptotaxis such as cells migrating along gradients of adhesion receptor ligands vs. any soluble cue. \r\n","lang":"eng"}],"oa_version":"Published Version","ec_funded":1,"volume":6,"publication_status":"published","language":[{"iso":"eng"}],"file":[{"file_id":"4756","access_level":"open_access","relation":"main_file","content_type":"application/pdf","date_created":"2018-12-12T10:09:32Z","file_name":"IST-2017-744-v1+1_srep36440.pdf","creator":"system","date_updated":"2018-12-12T10:09:32Z","file_size":2353456}],"project":[{"_id":"25A603A2-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Cytoskeletal force generation and force transduction of migrating leukocytes (EU)","grant_number":"281556"},{"_id":"25A8E5EA-B435-11E9-9278-68D0E5697425","call_identifier":"FWF","name":"Cytoskeletal force generation and transduction of leukocytes (FWF)","grant_number":"Y 564-B12"}],"article_number":"36440","author":[{"last_name":"Schwarz","full_name":"Schwarz, Jan","id":"346C1EC6-F248-11E8-B48F-1D18A9856A87","first_name":"Jan"},{"first_name":"Veronika","id":"3FD04378-F248-11E8-B48F-1D18A9856A87","full_name":"Bierbaum, Veronika","last_name":"Bierbaum"},{"first_name":"Jack","id":"4515C308-F248-11E8-B48F-1D18A9856A87","last_name":"Merrin","orcid":"0000-0001-5145-4609","full_name":"Merrin, Jack"},{"last_name":"Frank","full_name":"Frank, Tino","first_name":"Tino"},{"full_name":"Hauschild, Robert","orcid":"0000-0001-9843-3522","last_name":"Hauschild","first_name":"Robert","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Mark Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach","orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Mark Tobias"},{"first_name":"Savaş","last_name":"Tay","full_name":"Tay, Savaş"},{"first_name":"Michael K","id":"41E9FBEA-F248-11E8-B48F-1D18A9856A87","last_name":"Sixt","full_name":"Sixt, Michael K","orcid":"0000-0002-6620-9179"},{"orcid":"0000-0001-8599-1226","full_name":"Mehling, Matthias","last_name":"Mehling","first_name":"Matthias","id":"3C23B994-F248-11E8-B48F-1D18A9856A87"}],"publist_id":"6204","title":"A microfluidic device for measuring cell migration towards substrate bound and soluble chemokine gradients","citation":{"ista":"Schwarz J, Bierbaum V, Merrin J, Frank T, Hauschild R, Bollenbach MT, Tay S, Sixt MK, Mehling M. 2016. A microfluidic device for measuring cell migration towards substrate bound and soluble chemokine gradients. Scientific Reports. 6, 36440.","chicago":"Schwarz, Jan, Veronika Bierbaum, Jack Merrin, Tino Frank, Robert Hauschild, Mark Tobias Bollenbach, Savaş Tay, Michael K Sixt, and Matthias Mehling. “A Microfluidic Device for Measuring Cell Migration towards Substrate Bound and Soluble Chemokine Gradients.” Scientific Reports. Nature Publishing Group, 2016. https://doi.org/10.1038/srep36440.","ieee":"J. Schwarz et al., “A microfluidic device for measuring cell migration towards substrate bound and soluble chemokine gradients,” Scientific Reports, vol. 6. Nature Publishing Group, 2016.","short":"J. Schwarz, V. Bierbaum, J. Merrin, T. Frank, R. Hauschild, M.T. Bollenbach, S. Tay, M.K. Sixt, M. Mehling, Scientific Reports 6 (2016).","ama":"Schwarz J, Bierbaum V, Merrin J, et al. A microfluidic device for measuring cell migration towards substrate bound and soluble chemokine gradients. Scientific Reports. 2016;6. doi:10.1038/srep36440","apa":"Schwarz, J., Bierbaum, V., Merrin, J., Frank, T., Hauschild, R., Bollenbach, M. T., … Mehling, M. (2016). A microfluidic device for measuring cell migration towards substrate bound and soluble chemokine gradients. Scientific Reports. Nature Publishing Group. https://doi.org/10.1038/srep36440","mla":"Schwarz, Jan, et al. “A Microfluidic Device for Measuring Cell Migration towards Substrate Bound and Soluble Chemokine Gradients.” Scientific Reports, vol. 6, 36440, Nature Publishing Group, 2016, doi:10.1038/srep36440."},"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","oa":1,"quality_controlled":"1","publisher":"Nature Publishing Group","acknowledgement":"This work was supported by the Swiss National Science Foundation (Ambizione fellowship; PZ00P3-154733 to M.M.), the Swiss Multiple Sclerosis Society (research support to M.M.), a fellowship from the Boehringer Ingelheim Fonds (BIF) to J.S., the European Research Council (grant ERC GA 281556) and a START award from the Austrian Science Foundation (FWF) to M.S. #BioimagingFacility","date_created":"2018-12-11T11:50:27Z","date_published":"2016-11-07T00:00:00Z","doi":"10.1038/srep36440","year":"2016","has_accepted_license":"1","publication":"Scientific Reports","day":"07"},{"type":"journal_article","status":"public","_id":"1218","department":[{"_id":"ToBo"}],"date_updated":"2021-01-12T06:49:10Z","main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959195/","open_access":"1"}],"scopus_import":1,"intvolume":" 82","month":"07","abstract":[{"lang":"eng","text":"Investigating the physiology of cyanobacteria cultured under a diel light regime is relevant for a better understanding of the resulting growth characteristics and for specific biotechnological applications that are foreseen for these photosynthetic organisms. Here, we present the results of a multiomics study of the model cyanobacterium Synechocystis sp. strain PCC 6803, cultured in a lab-scale photobioreactor in physiological conditions relevant for large-scale culturing. The culture was sparged withN2 andCO2, leading to an anoxic environment during the dark period. Growth followed the availability of light. Metabolite analysis performed with 1Hnuclear magnetic resonance analysis showed that amino acids involved in nitrogen and sulfur assimilation showed elevated levels in the light. Most protein levels, analyzed through mass spectrometry, remained rather stable. However, several high-light-response proteins and stress-response proteins showed distinct changes at the onset of the light period. Microarray-based transcript analysis found common patterns of~56% of the transcriptome following the diel regime. These oscillating transcripts could be grouped coarsely into genes that were upregulated and downregulated in the dark period. The accumulated glycogen was degraded in the anaerobic environment in the dark. A small part was degraded gradually, reflecting basic maintenance requirements of the cells in darkness. Surprisingly, the largest part was degraded rapidly in a short time span at the end of the dark period. This degradation could allow rapid formation of metabolic intermediates at the end of the dark period, preparing the cells for the resumption of growth at the start of the light period."}],"oa_version":"Submitted Version","issue":"14","volume":82,"publication_status":"published","language":[{"iso":"eng"}],"publist_id":"6117","author":[{"id":"4677C796-F248-11E8-B48F-1D18A9856A87","first_name":"Andreas","last_name":"Angermayr","full_name":"Angermayr, Andreas","orcid":"0000-0001-8619-2223"},{"full_name":"Van Alphen, Pascal","last_name":"Van Alphen","first_name":"Pascal"},{"last_name":"Hasdemir","full_name":"Hasdemir, Dicle","first_name":"Dicle"},{"last_name":"Kramer","full_name":"Kramer, Gertjan","first_name":"Gertjan"},{"last_name":"Iqbal","full_name":"Iqbal, Muzamal","first_name":"Muzamal"},{"first_name":"Wilmar","full_name":"Van Grondelle, Wilmar","last_name":"Van Grondelle"},{"last_name":"Hoefsloot","full_name":"Hoefsloot, Huub","first_name":"Huub"},{"first_name":"Younghae","full_name":"Choi, Younghae","last_name":"Choi"},{"first_name":"Klaas","last_name":"Hellingwerf","full_name":"Hellingwerf, Klaas"}],"title":"Culturing synechocystis sp. Strain pcc 6803 with N2 and CO2 in a diel regime reveals multiphase glycogen dynamics with low maintenance costs","citation":{"mla":"Angermayr, Andreas, et al. “Culturing Synechocystis Sp. Strain Pcc 6803 with N2 and CO2 in a Diel Regime Reveals Multiphase Glycogen Dynamics with Low Maintenance Costs.” Applied and Environmental Microbiology, vol. 82, no. 14, American Society for Microbiology, 2016, pp. 4180–89, doi:10.1128/AEM.00256-16.","apa":"Angermayr, A., Van Alphen, P., Hasdemir, D., Kramer, G., Iqbal, M., Van Grondelle, W., … Hellingwerf, K. (2016). Culturing synechocystis sp. Strain pcc 6803 with N2 and CO2 in a diel regime reveals multiphase glycogen dynamics with low maintenance costs. Applied and Environmental Microbiology. American Society for Microbiology. https://doi.org/10.1128/AEM.00256-16","ama":"Angermayr A, Van Alphen P, Hasdemir D, et al. Culturing synechocystis sp. Strain pcc 6803 with N2 and CO2 in a diel regime reveals multiphase glycogen dynamics with low maintenance costs. Applied and Environmental Microbiology. 2016;82(14):4180-4189. doi:10.1128/AEM.00256-16","short":"A. Angermayr, P. Van Alphen, D. Hasdemir, G. Kramer, M. Iqbal, W. Van Grondelle, H. Hoefsloot, Y. Choi, K. Hellingwerf, Applied and Environmental Microbiology 82 (2016) 4180–4189.","ieee":"A. Angermayr et al., “Culturing synechocystis sp. Strain pcc 6803 with N2 and CO2 in a diel regime reveals multiphase glycogen dynamics with low maintenance costs,” Applied and Environmental Microbiology, vol. 82, no. 14. American Society for Microbiology, pp. 4180–4189, 2016.","chicago":"Angermayr, Andreas, Pascal Van Alphen, Dicle Hasdemir, Gertjan Kramer, Muzamal Iqbal, Wilmar Van Grondelle, Huub Hoefsloot, Younghae Choi, and Klaas Hellingwerf. “Culturing Synechocystis Sp. Strain Pcc 6803 with N2 and CO2 in a Diel Regime Reveals Multiphase Glycogen Dynamics with Low Maintenance Costs.” Applied and Environmental Microbiology. American Society for Microbiology, 2016. https://doi.org/10.1128/AEM.00256-16.","ista":"Angermayr A, Van Alphen P, Hasdemir D, Kramer G, Iqbal M, Van Grondelle W, Hoefsloot H, Choi Y, Hellingwerf K. 2016. Culturing synechocystis sp. Strain pcc 6803 with N2 and CO2 in a diel regime reveals multiphase glycogen dynamics with low maintenance costs. Applied and Environmental Microbiology. 82(14), 4180–4189."},"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","oa":1,"publisher":"American Society for Microbiology","quality_controlled":"1","acknowledgement":"Dutch Ministry of Economic Affairs, Agriculture, and Innovation through the program BioSolar CellsS. Andreas Angermayr,Pascal van Alphen, Klaas J. Hellingwerf\r\nWe thank Naira Quintana (presently at Rousselot, Belgium) for the ini-\r\ntiative at the 10th Cyanobacterial Molecular Biology Workshop\r\n(CMBW), June 2010, Lake Arrowhead, Los Angeles, CA, USA, to start the\r\ncollaborative endeavor reported here. We thank Timo Maarleveld from\r\nCWI/VU (Amsterdam) for a custom-made Python script handling the output from the NMR analysis and for evaluating and visualizing the\r\nseparate metabolites for their evaluation. We thank Rob Verpoorte from\r\nLeiden University (metabolome analysis) and Hans Aerts from the AMC\r\n(proteome analysis) for lab space and equipment. We thank Robert Leh-\r\nmann (Humboldt University Berlin) and Ilka Axmann (University of\r\nDüsseldorf) for sharing the R-code for the LOS transformation of the\r\ntranscript data. We thank Hans C. P. Matthijs from IBED for inspiring\r\ndialogues and insightful thoughts on continuous culturing of cyanobac-\r\nteria. We thank Sandra Waaijenborg for performing the transcript nor-\r\nmalization and Johan Westerhuis from BDA, Jeroen van der Steen and\r\nFilipe Branco dos Santos from MMP, and Lucas Stal from IBED/NIOZ for\r\nhelpful discussions. We thank Milou Schuurmans from MMP for help\r\nwith sampling and glycogen determination. We thank the members of the\r\nRNA Biology & Applied Bioinformatics group at SILS, in particular Selina\r\nvan Leeuwen, Elisa Hoekstra, and Martijs Jonker, for the microarray anal-\r\nysis. We thank the reviewers of this work for their insightful comments\r\nwhich improved the quality of the manuscript. This work, including the efforts of S. Andreas Angermayr, Pascal van\r\nAlphen, and Klaas J. Hellingwerf, was funded by Dutch Ministry of Eco-\r\nnomic Affairs, Agriculture, and Innovation through the program BioSolar\r\nCells.","page":"4180 - 4189","date_created":"2018-12-11T11:50:46Z","doi":"10.1128/AEM.00256-16","date_published":"2016-07-01T00:00:00Z","year":"2016","publication":"Applied and Environmental Microbiology","day":"01"},{"_id":"1552","status":"public","pubrep_id":"488","type":"journal_article","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)"},"ddc":["570"],"date_updated":"2021-01-12T06:51:33Z","department":[{"_id":"ToBo"}],"file_date_updated":"2020-07-14T12:45:02Z","oa_version":"Published Version","abstract":[{"lang":"eng","text":"Antibiotic resistance carries a fitness cost that must be overcome in order for resistance to persist over the long term. Compensatory mutations that recover the functional defects associated with resistance mutations have been argued to play a key role in overcoming the cost of resistance, but compensatory mutations are expected to be rare relative to generally beneficial mutations that increase fitness, irrespective of antibiotic resistance. Given this asymmetry, population genetics theory predicts that populations should adapt by compensatory mutations when the cost of resistance is large, whereas generally beneficial mutations should drive adaptation when the cost of resistance is small. We tested this prediction by determining the genomic mechanisms underpinning adaptation to antibiotic-free conditions in populations of the pathogenic bacterium Pseudomonas aeruginosa that carry costly antibiotic resistance mutations. Whole-genome sequencing revealed that populations founded by high-cost rifampicin-resistant mutants adapted via compensatory mutations in three genes of the RNA polymerase core enzyme, whereas populations founded by low-cost mutants adapted by generally beneficial mutations, predominantly in the quorum-sensing transcriptional regulator gene lasR. Even though the importance of compensatory evolution in maintaining resistance has been widely recognized, our study shows that the roles of general adaptation in maintaining resistance should not be underestimated and highlights the need to understand how selection at other sites in the genome influences the dynamics of resistance alleles in clinical settings."}],"month":"01","intvolume":" 283","scopus_import":1,"file":[{"content_type":"application/pdf","relation":"main_file","access_level":"open_access","file_id":"4899","checksum":"78ffe70c1c88af3856d31ca6b7195a27","file_size":626804,"date_updated":"2020-07-14T12:45:02Z","creator":"system","file_name":"IST-2016-488-v1+1_20152452.full.pdf","date_created":"2018-12-12T10:11:43Z"}],"language":[{"iso":"eng"}],"publication_status":"published","issue":"1822","volume":283,"article_number":"20152452","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","citation":{"mla":"Qi, Qin, et al. “The Genomic Basis of Adaptation to the Fitness Cost of Rifampicin Resistance in Pseudomonas Aeruginosa.” Proceedings of the Royal Society of London Series B Biological Sciences, vol. 283, no. 1822, 20152452, Royal Society, The, 2016, doi:10.1098/rspb.2015.2452.","ieee":"Q. Qi, M. Toll Riera, K. Heilbron, G. Preston, and R. C. Maclean, “The genomic basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa,” Proceedings of the Royal Society of London Series B Biological Sciences, vol. 283, no. 1822. Royal Society, The, 2016.","short":"Q. Qi, M. Toll Riera, K. Heilbron, G. Preston, R.C. Maclean, Proceedings of the Royal Society of London Series B Biological Sciences 283 (2016).","ama":"Qi Q, Toll Riera M, Heilbron K, Preston G, Maclean RC. The genomic basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa. Proceedings of the Royal Society of London Series B Biological Sciences. 2016;283(1822). doi:10.1098/rspb.2015.2452","apa":"Qi, Q., Toll Riera, M., Heilbron, K., Preston, G., & Maclean, R. C. (2016). The genomic basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa. Proceedings of the Royal Society of London Series B Biological Sciences. Royal Society, The. https://doi.org/10.1098/rspb.2015.2452","chicago":"Qi, Qin, Macarena Toll Riera, Karl Heilbron, Gail Preston, and R Craig Maclean. “The Genomic Basis of Adaptation to the Fitness Cost of Rifampicin Resistance in Pseudomonas Aeruginosa.” Proceedings of the Royal Society of London Series B Biological Sciences. Royal Society, The, 2016. https://doi.org/10.1098/rspb.2015.2452.","ista":"Qi Q, Toll Riera M, Heilbron K, Preston G, Maclean RC. 2016. The genomic basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa. Proceedings of the Royal Society of London Series B Biological Sciences. 283(1822), 20152452."},"title":"The genomic basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa","publist_id":"5619","author":[{"first_name":"Qin","id":"3B22D412-F248-11E8-B48F-1D18A9856A87","full_name":"Qi, Qin","orcid":"0000-0002-6148-2416","last_name":"Qi"},{"last_name":"Toll Riera","full_name":"Toll Riera, Macarena","first_name":"Macarena"},{"full_name":"Heilbron, Karl","last_name":"Heilbron","first_name":"Karl"},{"last_name":"Preston","full_name":"Preston, Gail","first_name":"Gail"},{"first_name":"R Craig","last_name":"Maclean","full_name":"Maclean, R Craig"}],"acknowledgement":"We thank the High-Throughput Genomics Group at the Wellcome Trust Centre for Human Genetics funded by Wellcome\r\nTrust grant reference 090532/Z/09/Z and Medical Research Council Hub grant no. G0900747 91070 for generation of the high-throughput sequencing data. We thank Wook Kim and two anonymous reviewers for their constructive feedback on previous versions of our manuscript.","publisher":"Royal Society, The","quality_controlled":"1","oa":1,"day":"13","publication":"Proceedings of the Royal Society of London Series B Biological Sciences","has_accepted_license":"1","year":"2016","doi":"10.1098/rspb.2015.2452","date_published":"2016-01-13T00:00:00Z","date_created":"2018-12-11T11:52:40Z"},{"citation":{"apa":"Lukacisin, M., Landon, M., & Jajoo, R. (2016). MATLAB analysis code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:45","ama":"Lukacisin M, Landon M, Jajoo R. MATLAB analysis code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” 2016. doi:10.15479/AT:ISTA:45","short":"M. Lukacisin, M. Landon, R. Jajoo, (2016).","ieee":"M. Lukacisin, M. Landon, and R. Jajoo, “MATLAB analysis code for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.’” Institute of Science and Technology Austria, 2016.","mla":"Lukacisin, Martin, et al. MATLAB Analysis Code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” Institute of Science and Technology Austria, 2016, doi:10.15479/AT:ISTA:45.","ista":"Lukacisin M, Landon M, Jajoo R. 2016. MATLAB analysis code for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast’, Institute of Science and Technology Austria, 10.15479/AT:ISTA:45.","chicago":"Lukacisin, Martin, Matthieu Landon, and Rishi Jajoo. “MATLAB Analysis Code for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.’” Institute of Science and Technology Austria, 2016. https://doi.org/10.15479/AT:ISTA:45."},"date_updated":"2024-02-21T13:51:53Z","ddc":["571"],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","author":[{"first_name":"Martin","id":"298FFE8C-F248-11E8-B48F-1D18A9856A87","last_name":"Lukacisin","orcid":"0000-0001-6549-4177","full_name":"Lukacisin, Martin"},{"first_name":"Matthieu","last_name":"Landon","full_name":"Landon, Matthieu"},{"first_name":"Rishi","full_name":"Jajoo, Rishi","last_name":"Jajoo"}],"article_processing_charge":"No","title":"MATLAB analysis code for 'Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast'","file_date_updated":"2020-07-14T12:47:02Z","department":[{"_id":"ToBo"}],"_id":"5556","type":"research_data","tmp":{"short":"CC BY-SA (4.0)","image":"/images/cc_by_sa.png","legal_code_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","name":"Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0)"},"status":"public","keyword":["transcription","pausing","backtracking","polymerase","RNA","NET-seq","nucleosome","basepairing"],"has_accepted_license":"1","datarep_id":"45","year":"2016","day":"25","file":[{"content_type":"application/zip","access_level":"open_access","relation":"main_file","checksum":"ee697f2b1ade4dc14d6ac0334dd832ab","file_id":"5616","date_updated":"2020-07-14T12:47:02Z","file_size":296722548,"creator":"system","date_created":"2018-12-12T13:02:58Z","file_name":"IST-2016-45-v1+1_PaperCode.zip"}],"date_published":"2016-08-25T00:00:00Z","doi":"10.15479/AT:ISTA:45","related_material":{"record":[{"id":"8431","status":"deleted","relation":"used_in_publication"},{"relation":"research_paper","status":"public","id":"1029"}]},"date_created":"2018-12-12T12:31:31Z","abstract":[{"text":"MATLAB code and processed datasets available for reproducing the results in: \r\nLukačišin, M.*, Landon, M.*, Jajoo, R*. (2016) Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.\r\n*equal contributions","lang":"eng"}],"oa_version":"Published Version","publisher":"Institute of Science and Technology Austria","oa":1,"month":"08"}]