[{"date_published":"2022-09-01T00:00:00Z","publication":"Molecular Systems Biology","citation":{"ista":"Angermayr A, Pang TY, Chevereau G, Mitosch K, Lercher MJ, Bollenbach MT. 2022. Growth‐mediated negative feedback shapes quantitative antibiotic response. Molecular Systems Biology. 18(9), e10490.","apa":"Angermayr, A., Pang, T. Y., Chevereau, G., Mitosch, K., Lercher, M. J., & Bollenbach, M. T. (2022). Growth‐mediated negative feedback shapes quantitative antibiotic response. Molecular Systems Biology. Embo Press. https://doi.org/10.15252/msb.202110490","ieee":"A. Angermayr, T. Y. Pang, G. Chevereau, K. Mitosch, M. J. Lercher, and M. T. Bollenbach, “Growth‐mediated negative feedback shapes quantitative antibiotic response,” Molecular Systems Biology, vol. 18, no. 9. Embo Press, 2022.","ama":"Angermayr A, Pang TY, Chevereau G, Mitosch K, Lercher MJ, Bollenbach MT. Growth‐mediated negative feedback shapes quantitative antibiotic response. Molecular Systems Biology. 2022;18(9). doi:10.15252/msb.202110490","chicago":"Angermayr, Andreas, Tin Yau Pang, Guillaume Chevereau, Karin Mitosch, Martin J Lercher, and Mark Tobias Bollenbach. “Growth‐mediated Negative Feedback Shapes Quantitative Antibiotic Response.” Molecular Systems Biology. Embo Press, 2022. https://doi.org/10.15252/msb.202110490.","mla":"Angermayr, Andreas, et al. “Growth‐mediated Negative Feedback Shapes Quantitative Antibiotic Response.” Molecular Systems Biology, vol. 18, no. 9, e10490, Embo Press, 2022, doi:10.15252/msb.202110490.","short":"A. Angermayr, T.Y. Pang, G. Chevereau, K. Mitosch, M.J. Lercher, M.T. Bollenbach, Molecular Systems Biology 18 (2022)."},"article_type":"original","day":"01","article_processing_charge":"No","has_accepted_license":"1","scopus_import":"1","keyword":["Applied Mathematics","Computational Theory and Mathematics","General Agricultural and Biological Sciences","General Immunology and Microbiology","General Biochemistry","Genetics and Molecular Biology","Information Systems"],"oa_version":"Published Version","file":[{"access_level":"open_access","file_name":"2022_MolecularSystemsBio_Angermayr.pdf","file_size":1098812,"content_type":"application/pdf","creator":"dernst","relation":"main_file","file_id":"12446","checksum":"8b1d8f5ea20c8408acf466435fb6ae01","success":1,"date_updated":"2023-01-30T09:49:55Z","date_created":"2023-01-30T09:49:55Z"}],"user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","_id":"12261","status":"public","ddc":["570"],"title":"Growth‐mediated negative feedback shapes quantitative antibiotic response","intvolume":" 18","abstract":[{"text":"Dose–response relationships are a general concept for quantitatively describing biological systems across multiple scales, from the molecular to the whole-cell level. A clinically relevant example is the bacterial growth response to antibiotics, which is routinely characterized by dose–response curves. The shape of the dose–response curve varies drastically between antibiotics and plays a key role in treatment, drug interactions, and resistance evolution. However, the mechanisms shaping the dose–response curve remain largely unclear. Here, we show in Escherichia coli that the distinctively shallow dose–response curve of the antibiotic trimethoprim is caused by a negative growth-mediated feedback loop: Trimethoprim slows growth, which in turn weakens the effect of this antibiotic. At the molecular level, this feedback is caused by the upregulation of the drug target dihydrofolate reductase (FolA/DHFR). We show that this upregulation is not a specific response to trimethoprim but follows a universal trend line that depends primarily on the growth rate, irrespective of its cause. Rewiring the feedback loop alters the dose–response curve in a predictable manner, which we corroborate using a mathematical model of cellular resource allocation and growth. Our results indicate that growth-mediated feedback loops may shape drug responses more generally and could be exploited to design evolutionary traps that enable selection against drug resistance.","lang":"eng"}],"issue":"9","type":"journal_article","doi":"10.15252/msb.202110490","acknowledged_ssus":[{"_id":"M-Shop"}],"language":[{"iso":"eng"}],"external_id":{"isi":["000856482800001"]},"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,"quality_controlled":"1","isi":1,"month":"09","publication_identifier":{"eissn":["1744-4292"]},"author":[{"id":"4677C796-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8619-2223","first_name":"Andreas","last_name":"Angermayr","full_name":"Angermayr, Andreas"},{"last_name":"Pang","first_name":"Tin Yau","full_name":"Pang, Tin Yau"},{"full_name":"Chevereau, Guillaume","first_name":"Guillaume","last_name":"Chevereau"},{"full_name":"Mitosch, Karin","id":"39B66846-F248-11E8-B48F-1D18A9856A87","last_name":"Mitosch","first_name":"Karin"},{"full_name":"Lercher, Martin J","last_name":"Lercher","first_name":"Martin J"},{"full_name":"Bollenbach, Mark Tobias","first_name":"Mark Tobias","last_name":"Bollenbach","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X"}],"date_created":"2023-01-16T09:58:34Z","date_updated":"2023-08-04T09:51:49Z","volume":18,"acknowledgement":"This work was in part supported by Human Frontier Science Program GrantRGP0042/2013, Marie Curie Career Integration Grant303507, AustrianScience Fund (FWF) Grant P27201-B22, and German Research Foundation(DFG) Collaborative Research Center (SFB)1310to TB. SAA was supportedby the European Union’s Horizon2020Research and Innovation Programunder the Marie Skłodowska-Curie Grant agreement No707352. We wouldlike to thank the Bollenbach group for regular fruitful discussions. We areparticularly thankful for the technical assistance of Booshini Fernando andfor discussions of the theoretical aspects with Gerrit Ansmann. We areindebted to Bor Kavˇciˇc for invaluable advice, help with setting up theluciferase-based growth monitoring system, and for sharing plasmids. Weacknowledge the IST Austria Miba Machine Shop for their support inbuilding a housing for the stacker of the plate reader, which enabled thehigh-throughput luciferase-based experiments. We are grateful to RosalindAllen, Bor Kavˇciˇc and Dor Russ for feedback on the manuscript. Open Accessfunding enabled and organized by Projekt DEAL.","year":"2022","publication_status":"published","department":[{"_id":"ToBo"}],"publisher":"Embo Press","file_date_updated":"2023-01-30T09:49:55Z","license":"https://creativecommons.org/licenses/by/4.0/","article_number":"e10490"},{"month":"02","language":[{"iso":"eng"}],"acknowledged_ssus":[{"_id":"Bio"}],"doi":"10.15252/msb.20188470","project":[{"_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","grant_number":"P27201-B22","call_identifier":"FWF","name":"Revealing the mechanisms underlying drug interactions"},{"name":"Revealing the fundamental limits of cell growth","_id":"25EB3A80-B435-11E9-9278-68D0E5697425","grant_number":"RGP0042/2013"}],"isi":1,"quality_controlled":"1","main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pubmed/30765425"}],"oa":1,"external_id":{"isi":["000459628300003"],"pmid":["30765425"]},"article_number":"e8470","volume":15,"date_updated":"2023-08-24T14:49:53Z","date_created":"2019-02-24T22:59:18Z","author":[{"full_name":"Mitosch, Karin","id":"39B66846-F248-11E8-B48F-1D18A9856A87","first_name":"Karin","last_name":"Mitosch"},{"full_name":"Rieckh, Georg","id":"34DA8BD6-F248-11E8-B48F-1D18A9856A87","first_name":"Georg","last_name":"Rieckh"},{"last_name":"Bollenbach","first_name":"Mark Tobias","orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","full_name":"Bollenbach, Mark Tobias"}],"publisher":"Embo Press","department":[{"_id":"GaTk"}],"publication_status":"published","pmid":1,"year":"2019","article_processing_charge":"No","day":"14","scopus_import":"1","date_published":"2019-02-14T00:00:00Z","citation":{"mla":"Mitosch, Karin, et al. “Temporal Order and Precision of Complex Stress Responses in Individual Bacteria.” Molecular Systems Biology, vol. 15, no. 2, e8470, Embo Press, 2019, doi:10.15252/msb.20188470.","short":"K. Mitosch, G. Rieckh, M.T. Bollenbach, Molecular Systems Biology 15 (2019).","chicago":"Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Temporal Order and Precision of Complex Stress Responses in Individual Bacteria.” Molecular Systems Biology. Embo Press, 2019. https://doi.org/10.15252/msb.20188470.","ama":"Mitosch K, Rieckh G, Bollenbach MT. Temporal order and precision of complex stress responses in individual bacteria. Molecular systems biology. 2019;15(2). doi:10.15252/msb.20188470","ista":"Mitosch K, Rieckh G, Bollenbach MT. 2019. Temporal order and precision of complex stress responses in individual bacteria. Molecular systems biology. 15(2), e8470.","ieee":"K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Temporal order and precision of complex stress responses in individual bacteria,” Molecular systems biology, vol. 15, no. 2. Embo Press, 2019.","apa":"Mitosch, K., Rieckh, G., & Bollenbach, M. T. (2019). Temporal order and precision of complex stress responses in individual bacteria. Molecular Systems Biology. Embo Press. https://doi.org/10.15252/msb.20188470"},"publication":"Molecular systems biology","issue":"2","abstract":[{"lang":"eng","text":"Sudden stress often triggers diverse, temporally structured gene expression responses in microbes, but it is largely unknown how variable in time such responses are and if genes respond in the same temporal order in every single cell. Here, we quantified timing variability of individual promoters responding to sublethal antibiotic stress using fluorescent reporters, microfluidics, and time‐lapse microscopy. We identified lower and upper bounds that put definite constraints on timing variability, which varies strongly among promoters and conditions. Timing variability can be interpreted using results from statistical kinetics, which enable us to estimate the number of rate‐limiting molecular steps underlying different responses. We found that just a few critical steps control some responses while others rely on dozens of steps. To probe connections between different stress responses, we then tracked the temporal order and response time correlations of promoter pairs in individual cells. Our results support that, when bacteria are exposed to the antibiotic nitrofurantoin, the ensuing oxidative stress and SOS responses are part of the same causal chain of molecular events. In contrast, under trimethoprim, the acid stress response and the SOS response are part of different chains of events running in parallel. Our approach reveals fundamental constraints on gene expression timing and provides new insights into the molecular events that underlie the timing of stress responses."}],"type":"journal_article","oa_version":"Submitted Version","intvolume":" 15","title":"Temporal order and precision of complex stress responses in individual bacteria","status":"public","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","_id":"6046"},{"article_processing_charge":"No","has_accepted_license":"1","day":"27","citation":{"ista":"Mitosch K. 2017. Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics. Institute of Science and Technology Austria.","ieee":"K. Mitosch, “Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics,” Institute of Science and Technology Austria, 2017.","apa":"Mitosch, K. (2017). Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th_862","ama":"Mitosch K. Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics. 2017. doi:10.15479/AT:ISTA:th_862","chicago":"Mitosch, Karin. “Timing, Variability and Cross-Protection in Bacteria – Insights from Dynamic Gene Expression Responses to Antibiotics.” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:th_862.","mla":"Mitosch, Karin. Timing, Variability and Cross-Protection in Bacteria – Insights from Dynamic Gene Expression Responses to Antibiotics. Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:th_862.","short":"K. Mitosch, Timing, Variability and Cross-Protection in Bacteria – Insights from Dynamic Gene Expression Responses to Antibiotics, Institute of Science and Technology Austria, 2017."},"page":"113","date_published":"2017-09-27T00:00:00Z","type":"dissertation","alternative_title":["ISTA Thesis"],"abstract":[{"lang":"eng","text":"Antibiotics have diverse effects on bacteria, including massive changes in bacterial gene expression. Whereas the gene expression changes under many antibiotics have been measured, the temporal organization of these responses and their dependence on the bacterial growth rate are unclear. As described in Chapter 1, we quantified the temporal gene expression changes in the bacterium Escherichia coli in response to the sudden exposure to antibiotics using a fluorescent reporter library and a robotic system. Our data show temporally structured gene expression responses, with response times for individual genes ranging from tens of minutes to several hours. We observed that many stress response genes were activated in response to antibiotics. As certain stress responses cross-protect bacteria from other stressors, we then asked whether cellular responses to antibiotics have a similar protective role in Chapter 2. Indeed, we found that the trimethoprim-induced acid stress response protects bacteria from subsequent acid stress. We combined microfluidics with time-lapse imaging to monitor survival, intracellular pH, and acid stress response in single cells. This approach revealed that the variable expression of the acid resistance operon gadBC strongly correlates with single-cell survival time. Cells with higher gadBC expression following trimethoprim maintain higher intracellular pH and survive the acid stress longer. Overall, we provide a way to identify single-cell cross-protection between antibiotics and environmental stressors from temporal gene expression data, and show how antibiotics can increase bacterial fitness in changing environments. While gene expression changes to antibiotics show a clear temporal structure at the population-level, it is unclear whether this clear temporal order is followed by every single cell. Using dual-reporter strains described in Chapter 3, we measured gene expression dynamics of promoter pairs in the same cells using microfluidics and microscopy. Chapter 4 shows that the oxidative stress response and the DNA stress response showed little timing variability and a clear temporal order under the antibiotic nitrofurantoin. In contrast, the acid stress response under trimethoprim ran independently from all other activated response programs including the DNA stress response, which showed particularly high timing variability in this stress condition. In summary, this approach provides insight into the temporal organization of gene expression programs at the single-cell level and suggests dependencies between response programs and the underlying variability-introducing mechanisms. Altogether, this work advances our understanding of the diverse effects that antibiotics have on bacteria. These results were obtained by taking into account gene expression dynamics, which allowed us to identify general principles, molecular mechanisms, and dependencies between genes. Our findings may have implications for infectious disease treatments, and microbial communities in the human body and in nature. "}],"_id":"818","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","ddc":["571","579"],"status":"public","title":"Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics","pubrep_id":"862","file":[{"checksum":"da3993c5f90f59a8e8623cc31ad501dd","date_updated":"2020-07-14T12:48:09Z","date_created":"2019-04-05T08:48:51Z","relation":"source_file","file_id":"6210","content_type":"application/vnd.openxmlformats-officedocument.wordprocessingml.document","file_size":6331071,"creator":"dernst","access_level":"closed","file_name":"Thesis_KarinMitosch.docx"},{"creator":"dernst","content_type":"application/pdf","file_size":9289852,"file_name":"Thesis_KarinMitosch.pdf","access_level":"open_access","date_created":"2019-04-05T08:48:51Z","date_updated":"2020-07-14T12:48:09Z","checksum":"24c3d9e51992f1b721f3df55aa13fcb8","file_id":"6211","relation":"main_file"}],"oa_version":"Published Version","publication_identifier":{"issn":["2663-337X"]},"month":"09","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"},"doi":"10.15479/AT:ISTA:th_862","language":[{"iso":"eng"}],"supervisor":[{"full_name":"Bollenbach, Mark Tobias","orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach","first_name":"Mark Tobias"}],"degree_awarded":"PhD","publist_id":"6831","file_date_updated":"2020-07-14T12:48:09Z","acknowledgement":"First of all, I would like to express great gratitude to my PhD supervisor Tobias Bollenbach. Through his open and trusting attitude I had the freedom to explore different scientific directions during this project, and follow the research lines of my interest. I am thankful for constructive and often extensive discussions and his support and commitment during the different stages of my PhD. I want to thank my committee members, Călin Guet, Terry Hwa and Nassos Typas for their interest and their valuable input to this project. Special thanks to Nassos for career guidance, and for accepting me in his lab. A big thank you goes to the past, present and affiliated members of the Bollenbach group: Guillaume Chevereau, Marjon de Vos, Marta Lukačišinová, Veronika Bierbaum, Qi Qin, Marcin Zagórski, Martin Lukačišin, Andreas Angermayr, Bor Kavčič, Julia Tischler, Dilay Ayhan, Jaroslav Ferenc, and Georg Rieckh. I enjoyed working and discussing with you very much and I will miss our lengthy group meetings, our inspiring journal clubs, and our common lunches. Special thanks to Bor for great mental and professional support during the hard months of thesis writing, and to Marta for very creative times during the beginning of our PhDs. May the ‘Bacterial Survival Guide’ decorate the walls of IST forever! A great thanks to my friend and collaborator Georg Rieckh for his enthusiasm and for getting so involved in these projects, for his endurance and for his company throughout the years. Thanks to the FriSBi crowd at IST Austria for interesting meetings and discussions. In particular I want to thank Magdalena Steinrück, and Anna Andersson for inspiring exchange, and enjoyable time together. Thanks to everybody who contributed to the cover for Cell Systems: The constructive input from Tobias Bollenbach, Bor Kavčič, Georg Rieckh, Marta Lukačišinová, and Sebastian Nozzi, and the professional implementation by the graphic designer Martina Markus from the University of Cologne. Thanks to all my office mates in the first floor Bertalanffy building throughout the years: for ensuring a pleasant working atmosphere, and for your company! In general, I want to thank all the people that make IST such a great environment, with the many possibilities to shape our own social and research environment. I want to thank my family for all kind of practical support during the years, and my second family in Argentina for their enthusiasm. Thanks to my brother Bernhard and my sister Martina for being great siblings, and to Helena and Valentin for the joy you brought to my life. My deep gratitude goes to Sebastian Nozzi, for constant support, patience, love and for believing in me. ","year":"2017","department":[{"_id":"ToBo"}],"publisher":"Institute of Science and Technology Austria","publication_status":"published","related_material":{"record":[{"id":"2001","status":"public","relation":"part_of_dissertation"},{"id":"666","relation":"part_of_dissertation","status":"public"}]},"author":[{"full_name":"Mitosch, Karin","id":"39B66846-F248-11E8-B48F-1D18A9856A87","last_name":"Mitosch","first_name":"Karin"}],"date_created":"2018-12-11T11:48:40Z","date_updated":"2023-09-07T12:00:26Z"},{"has_accepted_license":"1","article_processing_charge":"Yes (in subscription journal)","day":"26","scopus_import":1,"date_published":"2017-04-26T00:00:00Z","page":"393 - 403","citation":{"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.","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","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.","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","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.","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.","short":"K. Mitosch, G. Rieckh, M.T. Bollenbach, Cell Systems 4 (2017) 393–403."},"publication":"Cell Systems","issue":"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"}],"type":"journal_article","file":[{"relation":"main_file","file_id":"5041","date_updated":"2020-07-14T12:47:35Z","date_created":"2018-12-12T10:13:54Z","checksum":"04ff20011c3d9a601c514aa999a5fe1a","file_name":"IST-2017-901-v1+1_1-s2.0-S2405471217300868-main.pdf","access_level":"open_access","content_type":"application/pdf","file_size":2438660,"creator":"system"}],"oa_version":"Published Version","pubrep_id":"901","intvolume":" 4","title":"Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment","ddc":["576","610"],"status":"public","_id":"666","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","publication_identifier":{"issn":["24054712"]},"month":"04","language":[{"iso":"eng"}],"doi":"10.1016/j.cels.2017.03.001","project":[{"grant_number":"303507","_id":"25E83C2C-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Optimality principles in responses to antibiotics"},{"name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","grant_number":"P27201-B22"},{"grant_number":"RGP0042/2013","_id":"25EB3A80-B435-11E9-9278-68D0E5697425","name":"Revealing the fundamental limits of cell growth"}],"quality_controlled":"1","tmp":{"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","short":"CC BY-NC-ND (4.0)","image":"/images/cc_by_nc_nd.png"},"oa":1,"license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","publist_id":"7061","ec_funded":1,"file_date_updated":"2020-07-14T12:47:35Z","volume":4,"date_created":"2018-12-11T11:47:48Z","date_updated":"2023-09-07T12:00:25Z","related_material":{"record":[{"id":"818","relation":"dissertation_contains","status":"public"}]},"author":[{"full_name":"Mitosch, Karin","id":"39B66846-F248-11E8-B48F-1D18A9856A87","last_name":"Mitosch","first_name":"Karin"},{"first_name":"Georg","last_name":"Rieckh","id":"34DA8BD6-F248-11E8-B48F-1D18A9856A87","full_name":"Rieckh, Georg"},{"last_name":"Bollenbach","first_name":"Tobias","orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","full_name":"Bollenbach, Tobias"}],"department":[{"_id":"ToBo"},{"_id":"GaTk"}],"publisher":"Cell Press","publication_status":"published","year":"2017"},{"language":[{"iso":"eng"}],"doi":"10.1111/1758-2229.12190","project":[{"name":"Revealing the fundamental limits of cell growth","grant_number":"RGP0042/2013","_id":"25EB3A80-B435-11E9-9278-68D0E5697425"},{"name":"Optimality principles in responses to antibiotics","call_identifier":"FP7","_id":"25E83C2C-B435-11E9-9278-68D0E5697425","grant_number":"303507"}],"quality_controlled":"1","month":"06","volume":6,"date_created":"2018-12-11T11:55:08Z","date_updated":"2023-09-07T12:00:25Z","related_material":{"record":[{"status":"public","relation":"dissertation_contains","id":"818"}]},"author":[{"id":"39B66846-F248-11E8-B48F-1D18A9856A87","first_name":"Karin","last_name":"Mitosch","full_name":"Mitosch, Karin"},{"full_name":"Bollenbach, Tobias","last_name":"Bollenbach","first_name":"Tobias","orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87"}],"department":[{"_id":"ToBo"}],"publisher":"Wiley","publication_status":"published","year":"2014","ec_funded":1,"publist_id":"5076","date_published":"2014-06-22T00:00:00Z","page":"545 - 557","citation":{"ama":"Mitosch K, Bollenbach MT. Bacterial responses to antibiotics and their combinations. Environmental Microbiology Reports. 2014;6(6):545-557. doi:10.1111/1758-2229.12190","ista":"Mitosch K, Bollenbach MT. 2014. Bacterial responses to antibiotics and their combinations. Environmental Microbiology Reports. 6(6), 545–557.","ieee":"K. Mitosch and M. T. Bollenbach, “Bacterial responses to antibiotics and their combinations,” Environmental Microbiology Reports, vol. 6, no. 6. Wiley, pp. 545–557, 2014.","apa":"Mitosch, K., & Bollenbach, M. T. (2014). Bacterial responses to antibiotics and their combinations. Environmental Microbiology Reports. Wiley. https://doi.org/10.1111/1758-2229.12190","mla":"Mitosch, Karin, and Mark Tobias Bollenbach. “Bacterial Responses to Antibiotics and Their Combinations.” Environmental Microbiology Reports, vol. 6, no. 6, Wiley, 2014, pp. 545–57, doi:10.1111/1758-2229.12190.","short":"K. Mitosch, M.T. Bollenbach, Environmental Microbiology Reports 6 (2014) 545–557.","chicago":"Mitosch, Karin, and Mark Tobias Bollenbach. “Bacterial Responses to Antibiotics and Their Combinations.” Environmental Microbiology Reports. Wiley, 2014. https://doi.org/10.1111/1758-2229.12190."},"publication":"Environmental Microbiology Reports","day":"22","scopus_import":1,"oa_version":"None","intvolume":" 6","title":"Bacterial responses to antibiotics and their combinations","status":"public","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"2001","issue":"6","abstract":[{"lang":"eng","text":"Antibiotics affect bacterial cell physiology at many levels. Rather than just compensating for the direct cellular defects caused by the drug, bacteria respond to antibiotics by changing their morphology, macromolecular composition, metabolism, gene expression and possibly even their mutation rate. Inevitably, these processes affect each other, resulting in a complex response with changes in the expression of numerous genes. Genome‐wide approaches can thus help in gaining a comprehensive understanding of bacterial responses to antibiotics. In addition, a combination of experimental and theoretical approaches is needed for identifying general principles that underlie these responses. Here, we review recent progress in our understanding of bacterial responses to antibiotics and their combinations, focusing on effects at the levels of growth rate and gene expression. We concentrate on studies performed in controlled laboratory conditions, which combine promising experimental techniques with quantitative data analysis and mathematical modeling. While these basic research approaches are not immediately applicable in the clinic, uncovering the principles and mechanisms underlying bacterial responses to antibiotics may, in the long term, contribute to the development of new treatment strategies to cope with and prevent the rise of resistant pathogenic bacteria."}],"type":"journal_article"}]