[{"type":"journal_article","abstract":[{"lang":"eng","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."}],"issue":"4","title":"Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment","ddc":["576","610"],"status":"public","intvolume":" 4","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"666","file":[{"file_id":"5041","relation":"main_file","date_created":"2018-12-12T10:13:54Z","date_updated":"2020-07-14T12:47:35Z","checksum":"04ff20011c3d9a601c514aa999a5fe1a","file_name":"IST-2017-901-v1+1_1-s2.0-S2405471217300868-main.pdf","access_level":"open_access","creator":"system","content_type":"application/pdf","file_size":2438660}],"oa_version":"Published Version","pubrep_id":"901","scopus_import":1,"day":"26","article_processing_charge":"Yes (in subscription journal)","has_accepted_license":"1","page":"393 - 403","publication":"Cell Systems","citation":{"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.","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.","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.","short":"K. Mitosch, G. Rieckh, M.T. Bollenbach, Cell Systems 4 (2017) 393–403.","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."},"date_published":"2017-04-26T00:00:00Z","file_date_updated":"2020-07-14T12:47:35Z","publist_id":"7061","ec_funded":1,"publication_status":"published","department":[{"_id":"ToBo"},{"_id":"GaTk"}],"publisher":"Cell Press","year":"2017","date_created":"2018-12-11T11:47:48Z","date_updated":"2023-09-07T12:00:25Z","volume":4,"author":[{"full_name":"Mitosch, Karin","first_name":"Karin","last_name":"Mitosch","id":"39B66846-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Rieckh, Georg","first_name":"Georg","last_name":"Rieckh","id":"34DA8BD6-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Tobias","last_name":"Bollenbach","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Tobias"}],"related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"818"}]},"month":"04","publication_identifier":{"issn":["24054712"]},"quality_controlled":"1","project":[{"_id":"25E83C2C-B435-11E9-9278-68D0E5697425","grant_number":"303507","name":"Optimality principles in responses to antibiotics","call_identifier":"FP7"},{"name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF","grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425"},{"grant_number":"RGP0042/2013","_id":"25EB3A80-B435-11E9-9278-68D0E5697425","name":"Revealing the fundamental limits of cell growth"}],"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,"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"},{"grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF"}],"quality_controlled":"1","isi":1,"external_id":{"pmid":["28923953"],"isi":["000412130500061"]},"main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635929/"}],"oa":1,"language":[{"iso":"eng"}],"doi":"10.1073/pnas.1713372114","publication_identifier":{"issn":["00278424"]},"month":"10","department":[{"_id":"ToBo"}],"publisher":"National Academy of Sciences","publication_status":"published","pmid":1,"year":"2017","volume":114,"date_updated":"2023-09-26T16:18:48Z","date_created":"2018-12-11T11:48:41Z","author":[{"full_name":"De Vos, Marjon","first_name":"Marjon","last_name":"De Vos","id":"3111FFAC-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Zagórski, Marcin P","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7896-7762","first_name":"Marcin P","last_name":"Zagórski"},{"full_name":"Mcnally, Alan","last_name":"Mcnally","first_name":"Alan"},{"id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X","first_name":"Mark Tobias","last_name":"Bollenbach","full_name":"Bollenbach, Mark Tobias"}],"ec_funded":1,"publist_id":"6827","page":"10666 - 10671","citation":{"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","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.","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.","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","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.","short":"M. de Vos, M.P. Zagórski, A. Mcnally, M.T. Bollenbach, PNAS 114 (2017) 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."},"publication":"PNAS","date_published":"2017-10-03T00:00:00Z","scopus_import":"1","article_processing_charge":"No","day":"03","intvolume":" 114","title":"Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections","status":"public","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"822","oa_version":"Submitted Version","type":"journal_article","issue":"40","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. "}]},{"type":"journal_article","abstract":[{"lang":"eng","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."}],"issue":"3","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"1029","ddc":["570"],"status":"public","title":"Sequence-specific thermodynamic properties of nucleic acids influence both transcriptional pausing and backtracking in yeast","intvolume":" 12","pubrep_id":"800","oa_version":"Published Version","file":[{"creator":"system","content_type":"application/pdf","file_size":3429381,"file_name":"IST-2017-800-v1+1_journal.pone.0174066.pdf","access_level":"open_access","date_created":"2018-12-12T10:09:47Z","date_updated":"2018-12-12T10:09:47Z","file_id":"4772","relation":"main_file"}],"scopus_import":"1","day":"16","article_processing_charge":"Yes","has_accepted_license":"1","publication":"PLoS One","citation":{"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.","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.","short":"M. Lukacisin, M. Landon, R. Jajoo, PLoS One 12 (2017).","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.","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.","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","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"},"date_published":"2017-03-16T00:00:00Z","article_number":"e0174066","file_date_updated":"2018-12-12T10:09:47Z","publist_id":"6361","year":"2017","publication_status":"published","department":[{"_id":"ToBo"}],"publisher":"Public Library of Science","author":[{"first_name":"Martin","last_name":"Lukacisin","id":"298FFE8C-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6549-4177","full_name":"Lukacisin, Martin"},{"last_name":"Landon","first_name":"Matthieu","full_name":"Landon, Matthieu"},{"last_name":"Jajoo","first_name":"Rishi","full_name":"Jajoo, Rishi"}],"related_material":{"record":[{"id":"5556","relation":"popular_science","status":"public"},{"id":"6392","status":"public","relation":"dissertation_contains"}]},"date_created":"2018-12-11T11:49:46Z","date_updated":"2024-03-28T23:30:04Z","volume":12,"month":"03","publication_identifier":{"issn":["19326203"]},"external_id":{"isi":["000396318300121"]},"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,"doi":"10.1371/journal.pone.0174066","language":[{"iso":"eng"}]},{"type":"journal_article","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."}],"issue":"7","status":"public","title":"Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes","ddc":["576"],"intvolume":" 13","_id":"696","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file":[{"access_level":"open_access","file_name":"IST-2017-894-v1+1_journal.pcbi.1005609.pdf","file_size":3775716,"content_type":"application/pdf","creator":"system","relation":"main_file","file_id":"5117","checksum":"9143c290fa6458ed2563bff4b295554a","date_updated":"2020-07-14T12:47:46Z","date_created":"2018-12-12T10:15:01Z"}],"oa_version":"Published Version","pubrep_id":"894","scopus_import":1,"day":"18","has_accepted_license":"1","article_type":"original","publication":"PLoS Computational Biology","citation":{"short":"M. Lukacisinova, S. Novak, T. Paixao, PLoS Computational Biology 13 (2017).","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.","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.","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","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.","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."},"date_published":"2017-07-18T00:00:00Z","article_number":"e1005609","file_date_updated":"2020-07-14T12:47:46Z","ec_funded":1,"publist_id":"7004","publication_status":"published","publisher":"Public Library of Science","department":[{"_id":"ToBo"},{"_id":"NiBa"},{"_id":"CaGu"}],"year":"2017","date_created":"2018-12-11T11:47:58Z","date_updated":"2024-03-28T23:30:28Z","volume":13,"author":[{"last_name":"Lukacisinova","first_name":"Marta","orcid":"0000-0002-2519-8004","id":"4342E402-F248-11E8-B48F-1D18A9856A87","full_name":"Lukacisinova, Marta"},{"full_name":"Novak, Sebastian","first_name":"Sebastian","last_name":"Novak","id":"461468AE-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2519-824X"},{"full_name":"Paixao, Tiago","orcid":"0000-0003-2361-3953","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao","first_name":"Tiago"}],"related_material":{"record":[{"relation":"research_data","status":"public","id":"9849"},{"id":"9850","relation":"research_data","status":"public"},{"status":"public","relation":"research_data","id":"9851"},{"id":"9852","relation":"research_data","status":"public"},{"id":"6263","status":"public","relation":"dissertation_contains"}]},"month":"07","publication_identifier":{"issn":["1553734X"]},"quality_controlled":"1","project":[{"grant_number":"618091","_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation"}],"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,"language":[{"iso":"eng"}],"doi":"10.1371/journal.pcbi.1005609"},{"date_published":"2017-08-01T00:00:00Z","publication":"Current Opinion in Biotechnology","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.","short":"M. Lukacisinova, M.T. Bollenbach, Current Opinion in Biotechnology 46 (2017) 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.","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","ista":"Lukacisinova M, Bollenbach MT. 2017. Toward a quantitative understanding of antibiotic resistance evolution. Current Opinion in Biotechnology. 46, 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"},"article_type":"original","page":"90 - 97","day":"01","article_processing_charge":"Yes (in subscription journal)","has_accepted_license":"1","scopus_import":"1","pubrep_id":"801","oa_version":"Published Version","file":[{"success":1,"date_created":"2019-01-18T09:57:57Z","date_updated":"2019-01-18T09:57:57Z","relation":"main_file","file_id":"5846","content_type":"application/pdf","file_size":858338,"creator":"dernst","access_level":"open_access","file_name":"2017_CurrentOpinion_Lukaciinova.pdf"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"1027","ddc":["570"],"status":"public","title":"Toward a quantitative understanding of antibiotic resistance evolution","intvolume":" 46","abstract":[{"lang":"eng","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."}],"type":"journal_article","doi":"10.1016/j.copbio.2017.02.013","language":[{"iso":"eng"}],"oa":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"},"external_id":{"isi":["000408077400015"]},"isi":1,"quality_controlled":"1","project":[{"name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF","grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425"},{"grant_number":"303507","_id":"25E83C2C-B435-11E9-9278-68D0E5697425","call_identifier":"FP7","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"}],"month":"08","author":[{"id":"4342E402-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2519-8004","first_name":"Marta","last_name":"Lukacisinova","full_name":"Lukacisinova, Marta"},{"full_name":"Bollenbach, Mark Tobias","orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach","first_name":"Mark Tobias"}],"related_material":{"record":[{"id":"6263","relation":"dissertation_contains","status":"public"}]},"date_created":"2018-12-11T11:49:45Z","date_updated":"2024-03-28T23:30:29Z","volume":46,"year":"2017","publication_status":"published","department":[{"_id":"ToBo"}],"publisher":"Elsevier","file_date_updated":"2019-01-18T09:57:57Z","publist_id":"6364","ec_funded":1},{"date_published":"2016-11-07T00:00:00Z","citation":{"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","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.","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.","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","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.","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).","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."},"publication":"Scientific Reports","has_accepted_license":"1","day":"07","scopus_import":1,"oa_version":"Published Version","file":[{"relation":"main_file","file_id":"4756","date_updated":"2018-12-12T10:09:32Z","date_created":"2018-12-12T10:09:32Z","access_level":"open_access","file_name":"IST-2017-744-v1+1_srep36440.pdf","file_size":2353456,"content_type":"application/pdf","creator":"system"}],"pubrep_id":"744","intvolume":" 6","status":"public","title":"A microfluidic device for measuring cell migration towards substrate bound and soluble chemokine gradients","ddc":["579"],"_id":"1154","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","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"}],"type":"journal_article","language":[{"iso":"eng"}],"doi":"10.1038/srep36440","project":[{"_id":"25A603A2-B435-11E9-9278-68D0E5697425","grant_number":"281556","call_identifier":"FP7","name":"Cytoskeletal force generation and force transduction of migrating leukocytes (EU)"},{"call_identifier":"FWF","name":"Cytoskeletal force generation and transduction of leukocytes (FWF)","grant_number":"Y 564-B12","_id":"25A8E5EA-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"month":"11","volume":6,"date_updated":"2021-01-12T06:48:41Z","date_created":"2018-12-11T11:50:27Z","author":[{"last_name":"Schwarz","first_name":"Jan","id":"346C1EC6-F248-11E8-B48F-1D18A9856A87","full_name":"Schwarz, Jan"},{"id":"3FD04378-F248-11E8-B48F-1D18A9856A87","last_name":"Bierbaum","first_name":"Veronika","full_name":"Bierbaum, Veronika"},{"full_name":"Merrin, Jack","id":"4515C308-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-5145-4609","first_name":"Jack","last_name":"Merrin"},{"last_name":"Frank","first_name":"Tino","full_name":"Frank, Tino"},{"first_name":"Robert","last_name":"Hauschild","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9843-3522","full_name":"Hauschild, Robert"},{"orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach","first_name":"Mark Tobias","full_name":"Bollenbach, Mark Tobias"},{"full_name":"Tay, Savaş","first_name":"Savaş","last_name":"Tay"},{"first_name":"Michael K","last_name":"Sixt","id":"41E9FBEA-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6620-9179","full_name":"Sixt, Michael K"},{"full_name":"Mehling, Matthias","id":"3C23B994-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8599-1226","first_name":"Matthias","last_name":"Mehling"}],"department":[{"_id":"MiSi"},{"_id":"NanoFab"},{"_id":"Bio"},{"_id":"ToBo"}],"publisher":"Nature Publishing Group","publication_status":"published","year":"2016","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","publist_id":"6204","ec_funded":1,"file_date_updated":"2018-12-12T10:09:32Z","article_number":"36440"},{"date_updated":"2021-01-12T06:49:10Z","date_created":"2018-12-11T11:50:46Z","volume":82,"author":[{"orcid":"0000-0001-8619-2223","id":"4677C796-F248-11E8-B48F-1D18A9856A87","last_name":"Angermayr","first_name":"Andreas","full_name":"Angermayr, Andreas"},{"full_name":"Van Alphen, Pascal","first_name":"Pascal","last_name":"Van Alphen"},{"full_name":"Hasdemir, Dicle","first_name":"Dicle","last_name":"Hasdemir"},{"last_name":"Kramer","first_name":"Gertjan","full_name":"Kramer, Gertjan"},{"last_name":"Iqbal","first_name":"Muzamal","full_name":"Iqbal, Muzamal"},{"first_name":"Wilmar","last_name":"Van Grondelle","full_name":"Van Grondelle, Wilmar"},{"first_name":"Huub","last_name":"Hoefsloot","full_name":"Hoefsloot, Huub"},{"full_name":"Choi, Younghae","last_name":"Choi","first_name":"Younghae"},{"first_name":"Klaas","last_name":"Hellingwerf","full_name":"Hellingwerf, Klaas"}],"publication_status":"published","department":[{"_id":"ToBo"}],"publisher":"American Society for Microbiology","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.","year":"2016","publist_id":"6117","language":[{"iso":"eng"}],"doi":"10.1128/AEM.00256-16","quality_controlled":"1","oa":1,"main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959195/","open_access":"1"}],"month":"07","oa_version":"Submitted Version","title":"Culturing synechocystis sp. Strain pcc 6803 with N2 and CO2 in a diel regime reveals multiphase glycogen dynamics with low maintenance costs","status":"public","intvolume":" 82","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1218","abstract":[{"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.","lang":"eng"}],"issue":"14","type":"journal_article","date_published":"2016-07-01T00:00:00Z","page":"4180 - 4189","publication":"Applied and Environmental Microbiology","citation":{"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.","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.","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.","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.","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.","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"},"day":"01","scopus_import":1},{"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.","year":"2016","department":[{"_id":"ToBo"}],"publisher":"Royal Society, The","publication_status":"published","author":[{"full_name":"Qi, Qin","orcid":"0000-0002-6148-2416","id":"3B22D412-F248-11E8-B48F-1D18A9856A87","last_name":"Qi","first_name":"Qin"},{"first_name":"Macarena","last_name":"Toll Riera","full_name":"Toll Riera, Macarena"},{"last_name":"Heilbron","first_name":"Karl","full_name":"Heilbron, Karl"},{"last_name":"Preston","first_name":"Gail","full_name":"Preston, Gail"},{"last_name":"Maclean","first_name":"R Craig","full_name":"Maclean, R Craig"}],"volume":283,"date_created":"2018-12-11T11:52:40Z","date_updated":"2021-01-12T06:51:33Z","article_number":"20152452","publist_id":"5619","file_date_updated":"2020-07-14T12:45:02Z","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","doi":"10.1098/rspb.2015.2452","language":[{"iso":"eng"}],"month":"01","_id":"1552","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","intvolume":" 283","title":"The genomic basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa","ddc":["570"],"status":"public","pubrep_id":"488","file":[{"date_updated":"2020-07-14T12:45:02Z","date_created":"2018-12-12T10:11:43Z","checksum":"78ffe70c1c88af3856d31ca6b7195a27","relation":"main_file","file_id":"4899","file_size":626804,"content_type":"application/pdf","creator":"system","file_name":"IST-2016-488-v1+1_20152452.full.pdf","access_level":"open_access"}],"oa_version":"Published Version","type":"journal_article","issue":"1822","abstract":[{"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.","lang":"eng"}],"citation":{"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).","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.","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.","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","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.","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","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."},"publication":"Proceedings of the Royal Society of London Series B Biological Sciences","date_published":"2016-01-13T00:00:00Z","scopus_import":1,"has_accepted_license":"1","day":"13"},{"scopus_import":1,"day":"01","month":"12","publication":"PNAS","citation":{"ama":"de Vos M, Dawid A, Šunderlíková V, Tans S. Breaking evolutionary constraint with a tradeoff ratchet. PNAS. 2015;112(48):14906-14911. doi:10.1073/pnas.1510282112","ista":"de Vos M, Dawid A, Šunderlíková V, Tans S. 2015. Breaking evolutionary constraint with a tradeoff ratchet. PNAS. 112(48), 14906–14911.","apa":"de Vos, M., Dawid, A., Šunderlíková, V., & Tans, S. (2015). Breaking evolutionary constraint with a tradeoff ratchet. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1510282112","ieee":"M. de Vos, A. Dawid, V. Šunderlíková, and S. Tans, “Breaking evolutionary constraint with a tradeoff ratchet,” PNAS, vol. 112, no. 48. National Academy of Sciences, pp. 14906–14911, 2015.","mla":"de Vos, Marjon, et al. “Breaking Evolutionary Constraint with a Tradeoff Ratchet.” PNAS, vol. 112, no. 48, National Academy of Sciences, 2015, pp. 14906–11, doi:10.1073/pnas.1510282112.","short":"M. de Vos, A. Dawid, V. Šunderlíková, S. Tans, PNAS 112 (2015) 14906–14911.","chicago":"Vos, Marjon de, Alexandre Dawid, Vanda Šunderlíková, and Sander Tans. “Breaking Evolutionary Constraint with a Tradeoff Ratchet.” PNAS. National Academy of Sciences, 2015. https://doi.org/10.1073/pnas.1510282112."},"quality_controlled":"1","page":"14906 - 14911","doi":"10.1073/pnas.1510282112","date_published":"2015-12-01T00:00:00Z","language":[{"iso":"eng"}],"type":"journal_article","abstract":[{"text":"Epistatic interactions can frustrate and shape evolutionary change. Indeed, phenotypes may fail to evolve when essential mutations are only accessible through positive selection if they are fixed simultaneously. How environmental variability affects such constraints is poorly understood. Here, we studied genetic constraints in fixed and fluctuating environments using the Escherichia coli lac operon as a model system for genotype-environment interactions. We found that, in different fixed environments, all trajectories that were reconstructed by applying point mutations within the transcription factor-operator interface became trapped at suboptima, where no additional improvements were possible. Paradoxically, repeated switching between these same environments allows unconstrained adaptation by continuous improvements. This evolutionary mode is explained by pervasive cross-environmental tradeoffs that reposition the peaks in such a way that trapped genotypes can repeatedly climb ascending slopes and hence, escape adaptive stasis. Using a Markov approach, we developed a mathematical framework to quantify the landscape-crossing rates and show that this ratchet-like adaptive mechanism is robust in a wide spectrum of fluctuating environments. Overall, this study shows that genetic constraints can be overcome by environmental change and that crossenvironmental tradeoffs do not necessarily impede but also, can facilitate adaptive evolution. Because tradeoffs and environmental variability are ubiquitous in nature, we speculate this evolutionary mode to be of general relevance.","lang":"eng"}],"publist_id":"5600","issue":"48","_id":"1571","acknowledgement":"This work is part of the research program of the Foundation for Fundamental Research on Matter, which is part of the Netherlands Organization for Scientific Research (NWO). M.G.J.d.V. was (partially) funded by NWO Earth and Life Sciences (ALW), project 863.14.015. We thank D. M. Weinreich, J. A. G. M. de Visser, T. Paixão, J. Polechová, T. Friedlander, and A. E. Mayo for reading and commenting on earlier versions of the manuscript and B. Houchmandzadeh, O. Rivoire, and M. Hemery for discussions and suggestions on the Markov computation. Furthermore, we thank F. J. Poelwijk for sharing plasmid pCascade5 and pRD007 and Y. Yokobayashi for sharing plasmid pINV-110. We also thank the anonymous reviewers for remarks on the initial version of the manuscript.","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","year":"2015","publication_status":"published","title":"Breaking evolutionary constraint with a tradeoff ratchet","status":"public","department":[{"_id":"ToBo"}],"publisher":"National Academy of Sciences","intvolume":" 112","author":[{"last_name":"De Vos","first_name":"Marjon","id":"3111FFAC-F248-11E8-B48F-1D18A9856A87","full_name":"De Vos, Marjon"},{"first_name":"Alexandre","last_name":"Dawid","full_name":"Dawid, Alexandre"},{"first_name":"Vanda","last_name":"Šunderlíková","full_name":"Šunderlíková, Vanda"},{"full_name":"Tans, Sander","last_name":"Tans","first_name":"Sander"}],"date_updated":"2021-01-12T06:51:40Z","date_created":"2018-12-11T11:52:47Z","volume":112,"oa_version":"None"},{"scopus_import":"1","day":"23","month":"04","article_processing_charge":"No","publication":"Cell","citation":{"ista":"Bollenbach MT, Heisenberg C-PJ. 2015. Gradients are shaping up. Cell. 161(3), 431–432.","ieee":"M. T. Bollenbach and C.-P. J. Heisenberg, “Gradients are shaping up,” Cell, vol. 161, no. 3. Cell Press, pp. 431–432, 2015.","apa":"Bollenbach, M. T., & Heisenberg, C.-P. J. (2015). Gradients are shaping up. Cell. Cell Press. https://doi.org/10.1016/j.cell.2015.04.009","ama":"Bollenbach MT, Heisenberg C-PJ. Gradients are shaping up. Cell. 2015;161(3):431-432. doi:10.1016/j.cell.2015.04.009","chicago":"Bollenbach, Mark Tobias, and Carl-Philipp J Heisenberg. “Gradients Are Shaping Up.” Cell. Cell Press, 2015. https://doi.org/10.1016/j.cell.2015.04.009.","mla":"Bollenbach, Mark Tobias, and Carl-Philipp J. Heisenberg. “Gradients Are Shaping Up.” Cell, vol. 161, no. 3, Cell Press, 2015, pp. 431–32, doi:10.1016/j.cell.2015.04.009.","short":"M.T. Bollenbach, C.-P.J. Heisenberg, Cell 161 (2015) 431–432."},"quality_controlled":"1","page":"431 - 432","date_published":"2015-04-23T00:00:00Z","doi":"10.1016/j.cell.2015.04.009","language":[{"iso":"eng"}],"type":"journal_article","abstract":[{"text":"In animal embryos, morphogen gradients determine tissue patterning and morphogenesis. Shyer et al. provide evidence that, during vertebrate gut formation, tissue folding generates graded activity of signals required for subsequent steps of gut growth and differentiation, thereby revealing an intriguing link between tissue morphogenesis and morphogen gradient formation.","lang":"eng"}],"publist_id":"5590","issue":"3","_id":"1581","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","year":"2015","title":"Gradients are shaping up","publication_status":"published","status":"public","publisher":"Cell Press","department":[{"_id":"ToBo"},{"_id":"CaHe"}],"intvolume":" 161","author":[{"full_name":"Bollenbach, Mark Tobias","orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach","first_name":"Mark Tobias"},{"orcid":"0000-0002-0912-4566","id":"39427864-F248-11E8-B48F-1D18A9856A87","last_name":"Heisenberg","first_name":"Carl-Philipp J","full_name":"Heisenberg, Carl-Philipp J"}],"date_updated":"2022-08-25T13:56:10Z","date_created":"2018-12-11T11:52:50Z","oa_version":"None","volume":161},{"author":[{"id":"4677C796-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8619-2223","first_name":"Andreas","last_name":"Angermayr","full_name":"Angermayr, Andreas"},{"first_name":"Aleix","last_name":"Gorchs","full_name":"Gorchs, Aleix"},{"first_name":"Klaas","last_name":"Hellingwerf","full_name":"Hellingwerf, Klaas"}],"date_updated":"2021-01-12T06:51:46Z","date_created":"2018-12-11T11:52:52Z","volume":33,"oa_version":"None","year":"2015","_id":"1586","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","title":"Metabolic engineering of cyanobacteria for the synthesis of commodity products","publication_status":"published","status":"public","publisher":"Elsevier","intvolume":" 33","department":[{"_id":"ToBo"}],"abstract":[{"lang":"eng","text":"Through metabolic engineering cyanobacteria can be employed in biotechnology. Combining the capacity for oxygenic photosynthesis and carbon fixation with an engineered metabolic pathway allows carbon-based product formation from CO2, light, and water directly. Such cyanobacterial 'cell factories' are constructed to produce biofuels, bioplastics, and commodity chemicals. Efforts of metabolic engineers and synthetic biologists allow the modification of the intermediary metabolism at various branching points, expanding the product range. The new biosynthesis routes 'tap' the metabolism ever more efficiently, particularly through the engineering of driving forces and utilization of cofactors generated during the light reactions of photosynthesis, resulting in higher product titers. High rates of carbon rechanneling ultimately allow an almost-complete allocation of fixed carbon to product above biomass."}],"publist_id":"5585","issue":"6","type":"journal_article","doi":"10.1016/j.tibtech.2015.03.009","date_published":"2015-06-01T00:00:00Z","language":[{"iso":"eng"}],"publication":"Trends in Biotechnology","citation":{"ama":"Angermayr A, Gorchs A, Hellingwerf K. Metabolic engineering of cyanobacteria for the synthesis of commodity products. Trends in Biotechnology. 2015;33(6):352-361. doi:10.1016/j.tibtech.2015.03.009","ista":"Angermayr A, Gorchs A, Hellingwerf K. 2015. Metabolic engineering of cyanobacteria for the synthesis of commodity products. Trends in Biotechnology. 33(6), 352–361.","ieee":"A. Angermayr, A. Gorchs, and K. Hellingwerf, “Metabolic engineering of cyanobacteria for the synthesis of commodity products,” Trends in Biotechnology, vol. 33, no. 6. Elsevier, pp. 352–361, 2015.","apa":"Angermayr, A., Gorchs, A., & Hellingwerf, K. (2015). Metabolic engineering of cyanobacteria for the synthesis of commodity products. Trends in Biotechnology. Elsevier. https://doi.org/10.1016/j.tibtech.2015.03.009","mla":"Angermayr, Andreas, et al. “Metabolic Engineering of Cyanobacteria for the Synthesis of Commodity Products.” Trends in Biotechnology, vol. 33, no. 6, Elsevier, 2015, pp. 352–61, doi:10.1016/j.tibtech.2015.03.009.","short":"A. Angermayr, A. Gorchs, K. Hellingwerf, Trends in Biotechnology 33 (2015) 352–361.","chicago":"Angermayr, Andreas, Aleix Gorchs, and Klaas Hellingwerf. “Metabolic Engineering of Cyanobacteria for the Synthesis of Commodity Products.” Trends in Biotechnology. Elsevier, 2015. https://doi.org/10.1016/j.tibtech.2015.03.009."},"quality_controlled":"1","page":"352 - 361","month":"06","day":"01","scopus_import":1},{"author":[{"full_name":"Hammar, Petter","last_name":"Hammar","first_name":"Petter"},{"orcid":"0000-0001-8619-2223","id":"4677C796-F248-11E8-B48F-1D18A9856A87","last_name":"Angermayr","first_name":"Andreas","full_name":"Angermayr, Andreas"},{"full_name":"Sjostrom, Staffan","first_name":"Staffan","last_name":"Sjostrom"},{"first_name":"Josefin","last_name":"Van Der Meer","full_name":"Van Der Meer, Josefin"},{"last_name":"Hellingwerf","first_name":"Klaas","full_name":"Hellingwerf, Klaas"},{"full_name":"Hudson, Elton","last_name":"Hudson","first_name":"Elton"},{"full_name":"Joensson, Hakaan","last_name":"Joensson","first_name":"Hakaan"}],"volume":8,"date_created":"2018-12-11T11:53:05Z","date_updated":"2021-01-12T06:52:04Z","year":"2015","publisher":"BioMed Central","department":[{"_id":"ToBo"}],"publication_status":"published","publist_id":"5537","file_date_updated":"2020-07-14T12:45:07Z","article_number":"193","doi":"10.1186/s13068-015-0380-2","language":[{"iso":"eng"}],"oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"quality_controlled":"1","month":"11","pubrep_id":"467","oa_version":"Published Version","file":[{"date_created":"2018-12-12T10:10:11Z","date_updated":"2020-07-14T12:45:07Z","checksum":"172b0b6f4eb2e5c22b7cec1d57dc0107","relation":"main_file","file_id":"4796","content_type":"application/pdf","file_size":2914089,"creator":"system","file_name":"IST-2016-467-v1+1_s13068-015-0380-2.pdf","access_level":"open_access"}],"_id":"1623","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","intvolume":" 8","ddc":["570"],"status":"public","title":"Single-cell screening of photosynthetic growth and lactate production by cyanobacteria","issue":"1","abstract":[{"lang":"eng","text":"Background\r\nPhotosynthetic cyanobacteria are attractive for a range of biotechnological applications including biofuel production. However, due to slow growth, screening of mutant libraries using microtiter plates is not feasible.\r\nResults\r\nWe present a method for high-throughput, single-cell analysis and sorting of genetically engineered l-lactate-producing strains of Synechocystis sp. PCC6803. A microfluidic device is used to encapsulate single cells in picoliter droplets, assay the droplets for l-lactate production, and sort strains with high productivity. We demonstrate the separation of low- and high-producing reference strains, as well as enrichment of a more productive l-lactate-synthesizing population after UV-induced mutagenesis. The droplet platform also revealed population heterogeneity in photosynthetic growth and lactate production, as well as the presence of metabolically stalled cells.\r\nConclusions\r\nThe workflow will facilitate metabolic engineering and directed evolution studies and will be useful in studies of cyanobacteria biochemistry and physiology.\r\n"}],"type":"journal_article","date_published":"2015-11-25T00:00:00Z","citation":{"ista":"Hammar P, Angermayr A, Sjostrom S, Van Der Meer J, Hellingwerf K, Hudson E, Joensson H. 2015. Single-cell screening of photosynthetic growth and lactate production by cyanobacteria. Biotechnology for Biofuels. 8(1), 193.","apa":"Hammar, P., Angermayr, A., Sjostrom, S., Van Der Meer, J., Hellingwerf, K., Hudson, E., & Joensson, H. (2015). Single-cell screening of photosynthetic growth and lactate production by cyanobacteria. Biotechnology for Biofuels. BioMed Central. https://doi.org/10.1186/s13068-015-0380-2","ieee":"P. Hammar et al., “Single-cell screening of photosynthetic growth and lactate production by cyanobacteria,” Biotechnology for Biofuels, vol. 8, no. 1. BioMed Central, 2015.","ama":"Hammar P, Angermayr A, Sjostrom S, et al. Single-cell screening of photosynthetic growth and lactate production by cyanobacteria. Biotechnology for Biofuels. 2015;8(1). doi:10.1186/s13068-015-0380-2","chicago":"Hammar, Petter, Andreas Angermayr, Staffan Sjostrom, Josefin Van Der Meer, Klaas Hellingwerf, Elton Hudson, and Hakaan Joensson. “Single-Cell Screening of Photosynthetic Growth and Lactate Production by Cyanobacteria.” Biotechnology for Biofuels. BioMed Central, 2015. https://doi.org/10.1186/s13068-015-0380-2.","mla":"Hammar, Petter, et al. “Single-Cell Screening of Photosynthetic Growth and Lactate Production by Cyanobacteria.” Biotechnology for Biofuels, vol. 8, no. 1, 193, BioMed Central, 2015, doi:10.1186/s13068-015-0380-2.","short":"P. Hammar, A. Angermayr, S. Sjostrom, J. Van Der Meer, K. Hellingwerf, E. Hudson, H. Joensson, Biotechnology for Biofuels 8 (2015)."},"publication":"Biotechnology for Biofuels","has_accepted_license":"1","day":"25","scopus_import":1},{"publist_id":"5298","ec_funded":1,"file_date_updated":"2020-07-14T12:45:17Z","volume":27,"date_updated":"2021-01-12T06:53:21Z","date_created":"2018-12-11T11:54:08Z","author":[{"full_name":"Bollenbach, Mark Tobias","orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach","first_name":"Mark Tobias"}],"department":[{"_id":"ToBo"}],"publisher":"Elsevier","publication_status":"published","year":"2015","month":"06","language":[{"iso":"eng"}],"doi":"10.1016/j.mib.2015.05.008","project":[{"name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","grant_number":"P27201-B22"},{"name":"Optimality principles in responses to antibiotics","call_identifier":"FP7","grant_number":"303507","_id":"25E83C2C-B435-11E9-9278-68D0E5697425"},{"name":"Revealing the fundamental limits of cell growth","_id":"25EB3A80-B435-11E9-9278-68D0E5697425","grant_number":"RGP0042/2013"}],"quality_controlled":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"abstract":[{"lang":"eng","text":"Combining antibiotics is a promising strategy for increasing treatment efficacy and for controlling resistance evolution. When drugs are combined, their effects on cells may be amplified or weakened, that is the drugs may show synergistic or antagonistic interactions. Recent work revealed the underlying mechanisms of such drug interactions by elucidating the drugs'; joint effects on cell physiology. Moreover, new treatment strategies that use drug combinations to exploit evolutionary tradeoffs were shown to affect the rate of resistance evolution in predictable ways. High throughput studies have further identified drug candidates based on their interactions with established antibiotics and general principles that enable the prediction of drug interactions were suggested. Overall, the conceptual and technical foundation for the rational design of potent drug combinations is rapidly developing."}],"type":"journal_article","file":[{"creator":"system","content_type":"application/pdf","file_size":1047255,"file_name":"IST-2016-493-v1+1_1-s2.0-S1369527415000594-main.pdf","access_level":"open_access","date_updated":"2020-07-14T12:45:17Z","date_created":"2018-12-12T10:17:23Z","checksum":"1683bb0f42ef892a5b3b71a050d65d25","file_id":"5277","relation":"main_file"}],"oa_version":"Published Version","pubrep_id":"493","intvolume":" 27","status":"public","title":"Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution","ddc":["570"],"_id":"1810","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","has_accepted_license":"1","day":"01","scopus_import":1,"date_published":"2015-06-01T00:00:00Z","page":"1 - 9","citation":{"ama":"Bollenbach MT. Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution. Current Opinion in Microbiology. 2015;27:1-9. doi:10.1016/j.mib.2015.05.008","ieee":"M. T. Bollenbach, “Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution,” Current Opinion in Microbiology, vol. 27. Elsevier, pp. 1–9, 2015.","apa":"Bollenbach, M. T. (2015). Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution. Current Opinion in Microbiology. Elsevier. https://doi.org/10.1016/j.mib.2015.05.008","ista":"Bollenbach MT. 2015. Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution. Current Opinion in Microbiology. 27, 1–9.","short":"M.T. Bollenbach, Current Opinion in Microbiology 27 (2015) 1–9.","mla":"Bollenbach, Mark Tobias. “Antimicrobial Interactions: Mechanisms and Implications for Drug Discovery and Resistance Evolution.” Current Opinion in Microbiology, vol. 27, Elsevier, 2015, pp. 1–9, doi:10.1016/j.mib.2015.05.008.","chicago":"Bollenbach, Mark Tobias. “Antimicrobial Interactions: Mechanisms and Implications for Drug Discovery and Resistance Evolution.” Current Opinion in Microbiology. Elsevier, 2015. https://doi.org/10.1016/j.mib.2015.05.008."},"publication":"Current Opinion in Microbiology"},{"publist_id":"5283","ec_funded":1,"file_date_updated":"2020-07-14T12:45:17Z","article_number":"807","volume":11,"date_updated":"2021-01-12T06:53:26Z","date_created":"2018-12-11T11:54:12Z","author":[{"full_name":"Chevereau, Guillaume","first_name":"Guillaume","last_name":"Chevereau","id":"424D78A0-F248-11E8-B48F-1D18A9856A87"},{"first_name":"Mark Tobias","last_name":"Bollenbach","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Mark Tobias"}],"department":[{"_id":"ToBo"}],"publisher":"Nature Publishing Group","publication_status":"published","year":"2015","month":"04","language":[{"iso":"eng"}],"doi":"10.15252/msb.20156098","project":[{"name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF","grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425"},{"_id":"25EB3A80-B435-11E9-9278-68D0E5697425","grant_number":"RGP0042/2013","name":"Revealing the fundamental limits of cell growth"},{"name":"Optimality principles in responses to antibiotics","call_identifier":"FP7","grant_number":"303507","_id":"25E83C2C-B435-11E9-9278-68D0E5697425"}],"quality_controlled":"1","oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"issue":"4","abstract":[{"lang":"eng","text":"Abstract Drug combinations are increasingly important in disease treatments, for combating drug resistance, and for elucidating fundamental relationships in cell physiology. When drugs are combined, their individual effects on cells may be amplified or weakened. Such drug interactions are crucial for treatment efficacy, but their underlying mechanisms remain largely unknown. To uncover the causes of drug interactions, we developed a systematic approach based on precise quantification of the individual and joint effects of antibiotics on growth of genome-wide Escherichia coli gene deletion strains. We found that drug interactions between antibiotics representing the main modes of action are highly robust to genetic perturbation. This robustness is encapsulated in a general principle of bacterial growth, which enables the quantitative prediction of mutant growth rates under drug combinations. Rare violations of this principle exposed recurring cellular functions controlling drug interactions. In particular, we found that polysaccharide and ATP synthesis control multiple drug interactions with previously unexplained mechanisms, and small molecule adjuvants targeting these functions synthetically reshape drug interactions in predictable ways. These results provide a new conceptual framework for the design of multidrug combinations and suggest that there are universal mechanisms at the heart of most drug interactions. Synopsis A general principle of bacterial growth enables the prediction of mutant growth rates under drug combinations. Rare violations of this principle expose cellular functions that control drug interactions and can be targeted by small molecules to alter drug interactions in predictable ways. Drug interactions between antibiotics are highly robust to genetic perturbations. A general principle of bacterial growth enables the prediction of mutant growth rates under drug combinations. Rare violations of this principle expose cellular functions that control drug interactions. Diverse drug interactions are controlled by recurring cellular functions, including LPS synthesis and ATP synthesis. A general principle of bacterial growth enables the prediction of mutant growth rates under drug combinations. Rare violations of this principle expose cellular functions that control drug interactions and can be targeted by small molecules to alter drug interactions in predictable ways."}],"type":"journal_article","file":[{"file_size":1273573,"content_type":"application/pdf","creator":"system","file_name":"IST-2015-395-v1+1_807.full.pdf","access_level":"open_access","date_updated":"2020-07-14T12:45:17Z","date_created":"2018-12-12T10:14:34Z","checksum":"4289b518fbe2166682fb1a1ef9b405f3","relation":"main_file","file_id":"5087"}],"oa_version":"Published Version","pubrep_id":"395","intvolume":" 11","status":"public","title":"Systematic discovery of drug interaction mechanisms","ddc":["570"],"_id":"1823","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","has_accepted_license":"1","day":"01","scopus_import":1,"date_published":"2015-04-01T00:00:00Z","citation":{"apa":"Chevereau, G., & Bollenbach, M. T. (2015). Systematic discovery of drug interaction mechanisms. Molecular Systems Biology. Nature Publishing Group. https://doi.org/10.15252/msb.20156098","ieee":"G. Chevereau and M. T. Bollenbach, “Systematic discovery of drug interaction mechanisms,” Molecular Systems Biology, vol. 11, no. 4. Nature Publishing Group, 2015.","ista":"Chevereau G, Bollenbach MT. 2015. Systematic discovery of drug interaction mechanisms. Molecular Systems Biology. 11(4), 807.","ama":"Chevereau G, Bollenbach MT. Systematic discovery of drug interaction mechanisms. Molecular Systems Biology. 2015;11(4). doi:10.15252/msb.20156098","chicago":"Chevereau, Guillaume, and Mark Tobias Bollenbach. “Systematic Discovery of Drug Interaction Mechanisms.” Molecular Systems Biology. Nature Publishing Group, 2015. https://doi.org/10.15252/msb.20156098.","short":"G. Chevereau, M.T. Bollenbach, Molecular Systems Biology 11 (2015).","mla":"Chevereau, Guillaume, and Mark Tobias Bollenbach. “Systematic Discovery of Drug Interaction Mechanisms.” Molecular Systems Biology, vol. 11, no. 4, 807, Nature Publishing Group, 2015, doi:10.15252/msb.20156098."},"publication":"Molecular Systems Biology"},{"related_material":{"record":[{"id":"1619","relation":"used_in_publication","status":"public"}]},"author":[{"id":"424D78A0-F248-11E8-B48F-1D18A9856A87","first_name":"Guillaume","last_name":"Chevereau","full_name":"Chevereau, Guillaume"},{"full_name":"Lukacisinova, Marta","first_name":"Marta","last_name":"Lukacisinova","id":"4342E402-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2519-8004"},{"full_name":"Batur, Tugce","first_name":"Tugce","last_name":"Batur"},{"full_name":"Guvenek, Aysegul","last_name":"Guvenek","first_name":"Aysegul"},{"last_name":"Ayhan","first_name":"Dilay Hazal","full_name":"Ayhan, Dilay Hazal"},{"first_name":"Erdal","last_name":"Toprak","full_name":"Toprak, Erdal"},{"full_name":"Bollenbach, Mark Tobias","orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach","first_name":"Mark Tobias"}],"oa_version":"Published Version","date_updated":"2023-02-23T10:07:02Z","date_created":"2021-07-23T11:53:50Z","_id":"9711","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","year":"2015","department":[{"_id":"ToBo"}],"publisher":"Public Library of Science","status":"public","title":"Excel file containing the raw data for all figures","type":"research_data_reference","date_published":"2015-11-18T00:00:00Z","doi":"10.1371/journal.pbio.1002299.s001","citation":{"ama":"Chevereau G, Lukacisinova M, Batur T, et al. Excel file containing the raw data for all figures. 2015. doi:10.1371/journal.pbio.1002299.s001","ista":"Chevereau G, Lukacisinova M, Batur T, Guvenek A, Ayhan DH, Toprak E, Bollenbach MT. 2015. Excel file containing the raw data for all figures, Public Library of Science, 10.1371/journal.pbio.1002299.s001.","apa":"Chevereau, G., Lukacisinova, M., Batur, T., Guvenek, A., Ayhan, D. H., Toprak, E., & Bollenbach, M. T. (2015). Excel file containing the raw data for all figures. Public Library of Science. https://doi.org/10.1371/journal.pbio.1002299.s001","ieee":"G. Chevereau et al., “Excel file containing the raw data for all figures.” Public Library of Science, 2015.","mla":"Chevereau, Guillaume, et al. Excel File Containing the Raw Data for All Figures. Public Library of Science, 2015, doi:10.1371/journal.pbio.1002299.s001.","short":"G. Chevereau, M. Lukacisinova, T. Batur, A. Guvenek, D.H. Ayhan, E. Toprak, M.T. Bollenbach, (2015).","chicago":"Chevereau, Guillaume, Marta Lukacisinova, Tugce Batur, Aysegul Guvenek, Dilay Hazal Ayhan, Erdal Toprak, and Mark Tobias Bollenbach. “Excel File Containing the Raw Data for All Figures.” Public Library of Science, 2015. https://doi.org/10.1371/journal.pbio.1002299.s001."},"article_processing_charge":"No","day":"18","month":"11"},{"article_processing_charge":"No","day":"18","month":"11","citation":{"short":"G. Chevereau, M. Lukacisinova, T. Batur, A. Guvenek, D.H. Ayhan, E. Toprak, M.T. Bollenbach, (2015).","mla":"Chevereau, Guillaume, et al. Gene Ontology Enrichment Analysis for the Most Sensitive Gene Deletion Strains for All Drugs. Public Library of Science, 2015, doi:10.1371/journal.pbio.1002299.s008.","chicago":"Chevereau, Guillaume, Marta Lukacisinova, Tugce Batur, Aysegul Guvenek, Dilay Hazal Ayhan, Erdal Toprak, and Mark Tobias Bollenbach. “Gene Ontology Enrichment Analysis for the Most Sensitive Gene Deletion Strains for All Drugs.” Public Library of Science, 2015. https://doi.org/10.1371/journal.pbio.1002299.s008.","ama":"Chevereau G, Lukacisinova M, Batur T, et al. Gene ontology enrichment analysis for the most sensitive gene deletion strains for all drugs. 2015. doi:10.1371/journal.pbio.1002299.s008","apa":"Chevereau, G., Lukacisinova, M., Batur, T., Guvenek, A., Ayhan, D. H., Toprak, E., & Bollenbach, M. T. (2015). Gene ontology enrichment analysis for the most sensitive gene deletion strains for all drugs. Public Library of Science. https://doi.org/10.1371/journal.pbio.1002299.s008","ieee":"G. Chevereau et al., “Gene ontology enrichment analysis for the most sensitive gene deletion strains for all drugs.” Public Library of Science, 2015.","ista":"Chevereau G, Lukacisinova M, Batur T, Guvenek A, Ayhan DH, Toprak E, Bollenbach MT. 2015. Gene ontology enrichment analysis for the most sensitive gene deletion strains for all drugs, Public Library of Science, 10.1371/journal.pbio.1002299.s008."},"doi":"10.1371/journal.pbio.1002299.s008","date_published":"2015-11-18T00:00:00Z","type":"research_data_reference","publisher":"Public Library of Science","department":[{"_id":"ToBo"}],"status":"public","title":"Gene ontology enrichment analysis for the most sensitive gene deletion strains for all drugs","year":"2015","_id":"9765","user_id":"6785fbc1-c503-11eb-8a32-93094b40e1cf","oa_version":"Published Version","date_created":"2021-08-03T07:05:16Z","date_updated":"2023-02-23T10:07:02Z","related_material":{"record":[{"relation":"used_in_publication","status":"public","id":"1619"}]},"author":[{"id":"424D78A0-F248-11E8-B48F-1D18A9856A87","last_name":"Chevereau","first_name":"Guillaume","full_name":"Chevereau, Guillaume"},{"full_name":"Lukacisinova, Marta","first_name":"Marta","last_name":"Lukacisinova","id":"4342E402-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2519-8004"},{"last_name":"Batur","first_name":"Tugce","full_name":"Batur, Tugce"},{"first_name":"Aysegul","last_name":"Guvenek","full_name":"Guvenek, Aysegul"},{"full_name":"Ayhan, Dilay Hazal","first_name":"Dilay Hazal","last_name":"Ayhan"},{"full_name":"Toprak, Erdal","last_name":"Toprak","first_name":"Erdal"},{"first_name":"Mark Tobias","last_name":"Bollenbach","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Mark Tobias"}]},{"scopus_import":"1","day":"01","has_accepted_license":"1","article_processing_charge":"No","publication":"F1000 Research ","citation":{"chicago":"Michalko, Jaroslav, Marta Lukacisinova, Mark Tobias Bollenbach, and Jiří Friml. “Embryo-Lethal Phenotypes in Early Abp1 Mutants Are Due to Disruption of the Neighboring BSM Gene.” F1000 Research . F1000 Research, 2015. https://doi.org/10.12688/f1000research.7143.1.","mla":"Michalko, Jaroslav, et al. “Embryo-Lethal Phenotypes in Early Abp1 Mutants Are Due to Disruption of the Neighboring BSM Gene.” F1000 Research , vol. 4, F1000 Research, 2015, doi:10.12688/f1000research.7143.1.","short":"J. Michalko, M. Lukacisinova, M.T. Bollenbach, J. Friml, F1000 Research 4 (2015).","ista":"Michalko J, Lukacisinova M, Bollenbach MT, Friml J. 2015. Embryo-lethal phenotypes in early abp1 mutants are due to disruption of the neighboring BSM gene. F1000 Research . 4.","ieee":"J. Michalko, M. Lukacisinova, M. T. Bollenbach, and J. Friml, “Embryo-lethal phenotypes in early abp1 mutants are due to disruption of the neighboring BSM gene,” F1000 Research , vol. 4. F1000 Research, 2015.","apa":"Michalko, J., Lukacisinova, M., Bollenbach, M. T., & Friml, J. (2015). Embryo-lethal phenotypes in early abp1 mutants are due to disruption of the neighboring BSM gene. F1000 Research . F1000 Research. https://doi.org/10.12688/f1000research.7143.1","ama":"Michalko J, Lukacisinova M, Bollenbach MT, Friml J. Embryo-lethal phenotypes in early abp1 mutants are due to disruption of the neighboring BSM gene. F1000 Research . 2015;4. doi:10.12688/f1000research.7143.1"},"date_published":"2015-10-01T00:00:00Z","type":"journal_article","abstract":[{"lang":"eng","text":"The Auxin Binding Protein1 (ABP1) has been identified based on its ability to bind auxin with high affinity and studied for a long time as a prime candidate for the extracellular auxin receptor responsible for mediating in particular the fast non-transcriptional auxin responses. However, the contradiction between the embryo-lethal phenotypes of the originally described Arabidopsis T-DNA insertional knock-out alleles (abp1-1 and abp1-1s) and the wild type-like phenotypes of other recently described loss-of-function alleles (abp1-c1 and abp1-TD1) questions the biological importance of ABP1 and relevance of the previous genetic studies. Here we show that there is no hidden copy of the ABP1 gene in the Arabidopsis genome but the embryo-lethal phenotypes of abp1-1 and abp1-1s alleles are very similar to the knock-out phenotypes of the neighboring gene, BELAYA SMERT (BSM). Furthermore, the allelic complementation test between bsm and abp1 alleles shows that the embryo-lethality in the abp1-1 and abp1-1s alleles is caused by the off-target disruption of the BSM locus by the T-DNA insertions. This clarifies the controversy of different phenotypes among published abp1 knock-out alleles and asks for reflections on the developmental role of ABP1."}],"_id":"1509","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Embryo-lethal phenotypes in early abp1 mutants are due to disruption of the neighboring BSM gene","ddc":["570"],"status":"public","intvolume":" 4","pubrep_id":"497","file":[{"content_type":"application/pdf","file_size":4414248,"creator":"system","access_level":"open_access","file_name":"IST-2016-497-v1+1_10.12688_f1000research.7143.1_20151102.pdf","checksum":"8beae5cbe988e1060265ae7de2ee8306","date_created":"2018-12-12T10:16:12Z","date_updated":"2020-07-14T12:44:59Z","relation":"main_file","file_id":"5198"}],"oa_version":"Published Version","month":"10","oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"quality_controlled":"1","project":[{"name":"Polarity and subcellular dynamics in plants","call_identifier":"FP7","grant_number":"282300","_id":"25716A02-B435-11E9-9278-68D0E5697425"}],"doi":"10.12688/f1000research.7143.1","language":[{"iso":"eng"}],"file_date_updated":"2020-07-14T12:44:59Z","ec_funded":1,"publist_id":"5668","year":"2015","acknowledgement":"This work was supported by ERC Independent Research grant (ERC-2011-StG-20101109-PSDP to JF). JM internship was supported by the grant “Action Austria – Slovakia”.\r\nData associated with the article are available under the terms of the Creative Commons Zero \"No rights reserved\" data waiver (CC0 1.0 Public domain dedication). \r\n\r\nData availability: \r\nF1000Research: Dataset 1. Dataset 1, 10.5256/f1000research.7143.d104552\r\n\r\nF1000Research: Dataset 2. Dataset 2, 10.5256/f1000research.7143.d104553\r\n\r\nF1000Research: Dataset 3. Dataset 3, 10.5256/f1000research.7143.d104554","publication_status":"published","department":[{"_id":"JiFr"},{"_id":"ToBo"}],"publisher":"F1000 Research","author":[{"id":"483727CA-F248-11E8-B48F-1D18A9856A87","last_name":"Michalko","first_name":"Jaroslav","full_name":"Michalko, Jaroslav"},{"orcid":"0000-0002-2519-8004","id":"4342E402-F248-11E8-B48F-1D18A9856A87","last_name":"Dravecka","first_name":"Marta","full_name":"Dravecka, Marta"},{"id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X","first_name":"Tobias","last_name":"Bollenbach","full_name":"Bollenbach, Tobias"},{"full_name":"Friml, Jirí","orcid":"0000-0002-8302-7596","id":"4159519E-F248-11E8-B48F-1D18A9856A87","last_name":"Friml","first_name":"Jirí"}],"date_created":"2018-12-11T11:52:26Z","date_updated":"2023-10-10T14:10:24Z","volume":4},{"date_published":"2015-11-18T00:00:00Z","publication":"PLoS Biology","citation":{"ista":"Chevereau G, Lukacisinova M, Batur T, Guvenek A, Ayhan D, Toprak E, Bollenbach MT. 2015. Quantifying the determinants of evolutionary dynamics leading to drug resistance. PLoS Biology. 13(11), e1002299.","apa":"Chevereau, G., Lukacisinova, M., Batur, T., Guvenek, A., Ayhan, D., Toprak, E., & Bollenbach, M. T. (2015). Quantifying the determinants of evolutionary dynamics leading to drug resistance. PLoS Biology. Public Library of Science. https://doi.org/10.1371/journal.pbio.1002299","ieee":"G. Chevereau et al., “Quantifying the determinants of evolutionary dynamics leading to drug resistance,” PLoS Biology, vol. 13, no. 11. Public Library of Science, 2015.","ama":"Chevereau G, Lukacisinova M, Batur T, et al. Quantifying the determinants of evolutionary dynamics leading to drug resistance. PLoS Biology. 2015;13(11). doi:10.1371/journal.pbio.1002299","chicago":"Chevereau, Guillaume, Marta Lukacisinova, Tugce Batur, Aysegul Guvenek, Dilay Ayhan, Erdal Toprak, and Mark Tobias Bollenbach. “Quantifying the Determinants of Evolutionary Dynamics Leading to Drug Resistance.” PLoS Biology. Public Library of Science, 2015. https://doi.org/10.1371/journal.pbio.1002299.","mla":"Chevereau, Guillaume, et al. “Quantifying the Determinants of Evolutionary Dynamics Leading to Drug Resistance.” PLoS Biology, vol. 13, no. 11, e1002299, Public Library of Science, 2015, doi:10.1371/journal.pbio.1002299.","short":"G. Chevereau, M. Lukacisinova, T. Batur, A. Guvenek, D. Ayhan, E. Toprak, M.T. Bollenbach, PLoS Biology 13 (2015)."},"day":"18","has_accepted_license":"1","scopus_import":1,"pubrep_id":"468","file":[{"file_id":"4723","relation":"main_file","checksum":"0e82e3279f50b15c6c170c042627802b","date_updated":"2020-07-14T12:45:07Z","date_created":"2018-12-12T10:09:00Z","access_level":"open_access","file_name":"IST-2016-468-v1+1_journal.pbio.1002299.pdf","creator":"system","content_type":"application/pdf","file_size":1387760}],"oa_version":"Published Version","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"1619","title":"Quantifying the determinants of evolutionary dynamics leading to drug resistance","ddc":["570"],"status":"public","intvolume":" 13","abstract":[{"text":"The emergence of drug resistant pathogens is a serious public health problem. It is a long-standing goal to predict rates of resistance evolution and design optimal treatment strategies accordingly. To this end, it is crucial to reveal the underlying causes of drug-specific differences in the evolutionary dynamics leading to resistance. However, it remains largely unknown why the rates of resistance evolution via spontaneous mutations and the diversity of mutational paths vary substantially between drugs. Here we comprehensively quantify the distribution of fitness effects (DFE) of mutations, a key determinant of evolutionary dynamics, in the presence of eight antibiotics representing the main modes of action. Using precise high-throughput fitness measurements for genome-wide Escherichia coli gene deletion strains, we find that the width of the DFE varies dramatically between antibiotics and, contrary to conventional wisdom, for some drugs the DFE width is lower than in the absence of stress. We show that this previously underappreciated divergence in DFE width among antibiotics is largely caused by their distinct drug-specific dose-response characteristics. Unlike the DFE, the magnitude of the changes in tolerated drug concentration resulting from genome-wide mutations is similar for most drugs but exceptionally small for the antibiotic nitrofurantoin, i.e., mutations generally have considerably smaller resistance effects for nitrofurantoin than for other drugs. A population genetics model predicts that resistance evolution for drugs with this property is severely limited and confined to reproducible mutational paths. We tested this prediction in laboratory evolution experiments using the “morbidostat”, a device for evolving bacteria in well-controlled drug environments. Nitrofurantoin resistance indeed evolved extremely slowly via reproducible mutations—an almost paradoxical behavior since this drug causes DNA damage and increases the mutation rate. Overall, we identified novel quantitative characteristics of the evolutionary landscape that provide the conceptual foundation for predicting the dynamics of drug resistance evolution.","lang":"eng"}],"issue":"11","type":"journal_article","doi":"10.1371/journal.pbio.1002299","language":[{"iso":"eng"}],"oa":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"quality_controlled":"1","project":[{"grant_number":"RGP0042/2013","_id":"25EB3A80-B435-11E9-9278-68D0E5697425","name":"Revealing the fundamental limits of cell growth"},{"name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF","grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425"},{"grant_number":"303507","_id":"25E83C2C-B435-11E9-9278-68D0E5697425","name":"Optimality principles in responses to antibiotics","call_identifier":"FP7"}],"month":"11","author":[{"last_name":"Chevereau","first_name":"Guillaume","id":"424D78A0-F248-11E8-B48F-1D18A9856A87","full_name":"Chevereau, Guillaume"},{"full_name":"Dravecka, Marta","last_name":"Dravecka","first_name":"Marta","orcid":"0000-0002-2519-8004","id":"4342E402-F248-11E8-B48F-1D18A9856A87"},{"full_name":"Batur, Tugce","first_name":"Tugce","last_name":"Batur"},{"full_name":"Guvenek, Aysegul","first_name":"Aysegul","last_name":"Guvenek"},{"full_name":"Ayhan, Dilay","last_name":"Ayhan","first_name":"Dilay"},{"full_name":"Toprak, Erdal","last_name":"Toprak","first_name":"Erdal"},{"first_name":"Mark Tobias","last_name":"Bollenbach","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Mark Tobias"}],"related_material":{"record":[{"relation":"research_data","status":"public","id":"9711"},{"id":"9765","relation":"research_data","status":"public"},{"status":"public","relation":"dissertation_contains","id":"6263"}]},"date_updated":"2024-03-28T23:30:28Z","date_created":"2018-12-11T11:53:04Z","volume":13,"year":"2015","publication_status":"published","department":[{"_id":"ToBo"}],"publisher":"Public Library of Science","file_date_updated":"2020-07-14T12:45:07Z","publist_id":"5547","ec_funded":1,"article_number":"e1002299"},{"date_published":"2014-09-26T00:00:00Z","doi":"10.1126/science.1254927","language":[{"iso":"eng"}],"publication":"Science","main_file_link":[{"url":"http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4228193/","open_access":"1"}],"citation":{"ista":"Kicheva A, Bollenbach MT, Ribeiro A, Pérez Valle H, Lovell Badge R, Episkopou V, Briscoe J. 2014. Coordination of progenitor specification and growth in mouse and chick spinal cord. Science. 345(6204), 1254927.","ieee":"A. Kicheva et al., “Coordination of progenitor specification and growth in mouse and chick spinal cord,” Science, vol. 345, no. 6204. American Association for the Advancement of Science, 2014.","apa":"Kicheva, A., Bollenbach, M. T., Ribeiro, A., Pérez Valle, H., Lovell Badge, R., Episkopou, V., & Briscoe, J. (2014). Coordination of progenitor specification and growth in mouse and chick spinal cord. Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.1254927","ama":"Kicheva A, Bollenbach MT, Ribeiro A, et al. Coordination of progenitor specification and growth in mouse and chick spinal cord. Science. 2014;345(6204). doi:10.1126/science.1254927","chicago":"Kicheva, Anna, Mark Tobias Bollenbach, Ana Ribeiro, Helena Pérez Valle, Robin Lovell Badge, Vasso Episkopou, and James Briscoe. “Coordination of Progenitor Specification and Growth in Mouse and Chick Spinal Cord.” Science. American Association for the Advancement of Science, 2014. https://doi.org/10.1126/science.1254927.","mla":"Kicheva, Anna, et al. “Coordination of Progenitor Specification and Growth in Mouse and Chick Spinal Cord.” Science, vol. 345, no. 6204, 1254927, American Association for the Advancement of Science, 2014, doi:10.1126/science.1254927.","short":"A. Kicheva, M.T. Bollenbach, A. Ribeiro, H. Pérez Valle, R. Lovell Badge, V. Episkopou, J. Briscoe, Science 345 (2014)."},"oa":1,"quality_controlled":"1","day":"26","month":"09","scopus_import":1,"author":[{"first_name":"Anna","last_name":"Kicheva","full_name":"Kicheva, Anna"},{"last_name":"Bollenbach","first_name":"Mark Tobias","orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","full_name":"Bollenbach, Mark Tobias"},{"last_name":"Ribeiro","first_name":"Ana","full_name":"Ribeiro, Ana"},{"full_name":"Pérez Valle, Helena","last_name":"Pérez Valle","first_name":"Helena"},{"last_name":"Lovell Badge","first_name":"Robin","full_name":"Lovell Badge, Robin"},{"full_name":"Episkopou, Vasso","first_name":"Vasso","last_name":"Episkopou"},{"full_name":"Briscoe, James","last_name":"Briscoe","first_name":"James"}],"date_updated":"2021-01-12T06:54:55Z","date_created":"2018-12-11T11:55:22Z","volume":345,"oa_version":"Submitted Version","_id":"2040","year":"2014","user_id":"4435EBFC-F248-11E8-B48F-1D18A9856A87","title":"Coordination of progenitor specification and growth in mouse and chick spinal cord","status":"public","publication_status":"published","department":[{"_id":"ToBo"}],"intvolume":" 345","publisher":"American Association for the Advancement of Science","abstract":[{"text":"Development requires tissue growth as well as cell diversification. To address how these processes are coordinated, we analyzed the development of molecularly distinct domains of neural progenitors in the mouse and chick neural tube. We show that during development, these domains undergo changes in size that do not scale with changes in overall tissue size. Our data show that domain proportions are first established by opposing morphogen gradients and subsequently controlled by domain-specific regulation of differentiation rate but not differences in proliferation rate. Regulation of differentiation rate is key to maintaining domain proportions while accommodating both intra- and interspecies variations in size. Thus, the sequential control of progenitor specification and differentiation elaborates pattern without requiring that signaling gradients grow as tissues expand. ","lang":"eng"}],"publist_id":"5011","issue":"6204","article_number":"1254927","type":"journal_article"},{"publication":"Chemistry and Biology","citation":{"ista":"de Vos M, Bollenbach MT. 2014. Suppressive drug interactions between antifungals. Chemistry and Biology. 21(4), 439–440.","apa":"de Vos, M., & Bollenbach, M. T. (2014). Suppressive drug interactions between antifungals. Chemistry and Biology. Cell Press. https://doi.org/10.1016/j.chembiol.2014.04.004","ieee":"M. de Vos and M. T. Bollenbach, “Suppressive drug interactions between antifungals,” Chemistry and Biology, vol. 21, no. 4. Cell Press, pp. 439–440, 2014.","ama":"de Vos M, Bollenbach MT. Suppressive drug interactions between antifungals. Chemistry and Biology. 2014;21(4):439-440. doi:10.1016/j.chembiol.2014.04.004","chicago":"Vos, Marjon de, and Mark Tobias Bollenbach. “Suppressive Drug Interactions between Antifungals.” Chemistry and Biology. Cell Press, 2014. https://doi.org/10.1016/j.chembiol.2014.04.004.","mla":"de Vos, Marjon, and Mark Tobias Bollenbach. “Suppressive Drug Interactions between Antifungals.” Chemistry and Biology, vol. 21, no. 4, Cell Press, 2014, pp. 439–40, doi:10.1016/j.chembiol.2014.04.004.","short":"M. de Vos, M.T. Bollenbach, Chemistry and Biology 21 (2014) 439–440."},"page":"439 - 440","date_published":"2014-04-24T00:00:00Z","scopus_import":1,"day":"24","_id":"2220","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","status":"public","title":"Suppressive drug interactions between antifungals","intvolume":" 21","oa_version":"Published Version","type":"journal_article","abstract":[{"text":"In this issue of Chemistry & Biology, Cokol and colleagues report a systematic study of drug interactions between antifungal compounds. Suppressive drug interactions occur more frequently than previously realized and come in different flavors with interesting implications.","lang":"eng"}],"issue":"4","external_id":{"pmid":["24766845"]},"main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pubmed/24766845","open_access":"1"}],"oa":1,"quality_controlled":"1","doi":"10.1016/j.chembiol.2014.04.004","language":[{"iso":"eng"}],"month":"04","publication_identifier":{"issn":["10745521"]},"year":"2014","pmid":1,"publication_status":"published","publisher":"Cell Press","department":[{"_id":"ToBo"}],"author":[{"id":"3111FFAC-F248-11E8-B48F-1D18A9856A87","last_name":"De Vos","first_name":"Marjon","full_name":"De Vos, Marjon"},{"first_name":"Mark Tobias","last_name":"Bollenbach","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Mark Tobias"}],"date_created":"2018-12-11T11:56:24Z","date_updated":"2021-01-12T06:56:06Z","volume":21,"publist_id":"4747"}]