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Resistance Frequencies for Different Combination Strategies. Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005609.s004.","short":"M. Lukacisinova, S. Novak, T. Paixao, (2017).","chicago":"Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Resistance Frequencies for Different Combination Strategies.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005609.s004.","ama":"Lukacisinova M, Novak S, Paixao T. Resistance frequencies for different combination strategies. 2017. doi:10.1371/journal.pcbi.1005609.s004","ista":"Lukacisinova M, Novak S, Paixao T. 2017. Resistance frequencies for different combination strategies, Public Library of Science, 10.1371/journal.pcbi.1005609.s004.","apa":"Lukacisinova, M., Novak, S., & Paixao, T. (2017). Resistance frequencies for different combination strategies. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005609.s004","ieee":"M. Lukacisinova, S. Novak, and T. Paixao, “Resistance frequencies for different combination strategies.” Public Library of Science, 2017."},"article_processing_charge":"No","day":"18","month":"07"},{"publist_id":"6831","file_date_updated":"2020-07-14T12:48:09Z","date_updated":"2023-09-07T12:00:26Z","date_created":"2018-12-11T11:48:40Z","related_material":{"record":[{"id":"2001","relation":"part_of_dissertation","status":"public"},{"id":"666","relation":"part_of_dissertation","status":"public"}]},"author":[{"full_name":"Mitosch, Karin","first_name":"Karin","last_name":"Mitosch","id":"39B66846-F248-11E8-B48F-1D18A9856A87"}],"department":[{"_id":"ToBo"}],"publisher":"Institute of Science and Technology Austria","publication_status":"published","year":"2017","acknowledgement":"First of all, I would like to express great gratitude to my PhD supervisor Tobias Bollenbach. Through his open and trusting attitude I had the freedom to explore different scientific directions during this project, and follow the research lines of my interest. I am thankful for constructive and often extensive discussions and his support and commitment during the different stages of my PhD. I want to thank my committee members, Călin Guet, Terry Hwa and Nassos Typas for their interest and their valuable input to this project. Special thanks to Nassos for career guidance, and for accepting me in his lab. A big thank you goes to the past, present and affiliated members of the Bollenbach group: Guillaume Chevereau, Marjon de Vos, Marta Lukačišinová, Veronika Bierbaum, Qi Qin, Marcin Zagórski, Martin Lukačišin, Andreas Angermayr, Bor Kavčič, Julia Tischler, Dilay Ayhan, Jaroslav Ferenc, and Georg Rieckh. I enjoyed working and discussing with you very much and I will miss our lengthy group meetings, our inspiring journal clubs, and our common lunches. Special thanks to Bor for great mental and professional support during the hard months of thesis writing, and to Marta for very creative times during the beginning of our PhDs. May the ‘Bacterial Survival Guide’ decorate the walls of IST forever! A great thanks to my friend and collaborator Georg Rieckh for his enthusiasm and for getting so involved in these projects, for his endurance and for his company throughout the years. Thanks to the FriSBi crowd at IST Austria for interesting meetings and discussions. In particular I want to thank Magdalena Steinrück, and Anna Andersson for inspiring exchange, and enjoyable time together. Thanks to everybody who contributed to the cover for Cell Systems: The constructive input from Tobias Bollenbach, Bor Kavčič, Georg Rieckh, Marta Lukačišinová, and Sebastian Nozzi, and the professional implementation by the graphic designer Martina Markus from the University of Cologne. Thanks to all my office mates in the first floor Bertalanffy building throughout the years: for ensuring a pleasant working atmosphere, and for your company! In general, I want to thank all the people that make IST such a great environment, with the many possibilities to shape our own social and research environment. I want to thank my family for all kind of practical support during the years, and my second family in Argentina for their enthusiasm. Thanks to my brother Bernhard and my sister Martina for being great siblings, and to Helena and Valentin for the joy you brought to my life. My deep gratitude goes to Sebastian Nozzi, for constant support, patience, love and for believing in me. ","publication_identifier":{"issn":["2663-337X"]},"month":"09","language":[{"iso":"eng"}],"degree_awarded":"PhD","supervisor":[{"last_name":"Bollenbach","first_name":"Mark Tobias","orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","full_name":"Bollenbach, Mark Tobias"}],"doi":"10.15479/AT:ISTA:th_862","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"},"abstract":[{"text":"Antibiotics have diverse effects on bacteria, including massive changes in bacterial gene expression. Whereas the gene expression changes under many antibiotics have been measured, the temporal organization of these responses and their dependence on the bacterial growth rate are unclear. As described in Chapter 1, we quantified the temporal gene expression changes in the bacterium Escherichia coli in response to the sudden exposure to antibiotics using a fluorescent reporter library and a robotic system. Our data show temporally structured gene expression responses, with response times for individual genes ranging from tens of minutes to several hours. We observed that many stress response genes were activated in response to antibiotics. As certain stress responses cross-protect bacteria from other stressors, we then asked whether cellular responses to antibiotics have a similar protective role in Chapter 2. Indeed, we found that the trimethoprim-induced acid stress response protects bacteria from subsequent acid stress. We combined microfluidics with time-lapse imaging to monitor survival, intracellular pH, and acid stress response in single cells. This approach revealed that the variable expression of the acid resistance operon gadBC strongly correlates with single-cell survival time. Cells with higher gadBC expression following trimethoprim maintain higher intracellular pH and survive the acid stress longer. Overall, we provide a way to identify single-cell cross-protection between antibiotics and environmental stressors from temporal gene expression data, and show how antibiotics can increase bacterial fitness in changing environments. While gene expression changes to antibiotics show a clear temporal structure at the population-level, it is unclear whether this clear temporal order is followed by every single cell. Using dual-reporter strains described in Chapter 3, we measured gene expression dynamics of promoter pairs in the same cells using microfluidics and microscopy. Chapter 4 shows that the oxidative stress response and the DNA stress response showed little timing variability and a clear temporal order under the antibiotic nitrofurantoin. In contrast, the acid stress response under trimethoprim ran independently from all other activated response programs including the DNA stress response, which showed particularly high timing variability in this stress condition. In summary, this approach provides insight into the temporal organization of gene expression programs at the single-cell level and suggests dependencies between response programs and the underlying variability-introducing mechanisms. Altogether, this work advances our understanding of the diverse effects that antibiotics have on bacteria. These results were obtained by taking into account gene expression dynamics, which allowed us to identify general principles, molecular mechanisms, and dependencies between genes. Our findings may have implications for infectious disease treatments, and microbial communities in the human body and in nature. ","lang":"eng"}],"alternative_title":["ISTA Thesis"],"type":"dissertation","oa_version":"Published Version","file":[{"checksum":"da3993c5f90f59a8e8623cc31ad501dd","date_created":"2019-04-05T08:48:51Z","date_updated":"2020-07-14T12:48:09Z","file_id":"6210","relation":"source_file","creator":"dernst","content_type":"application/vnd.openxmlformats-officedocument.wordprocessingml.document","file_size":6331071,"access_level":"closed","file_name":"Thesis_KarinMitosch.docx"},{"creator":"dernst","file_size":9289852,"content_type":"application/pdf","file_name":"Thesis_KarinMitosch.pdf","access_level":"open_access","date_created":"2019-04-05T08:48:51Z","date_updated":"2020-07-14T12:48:09Z","checksum":"24c3d9e51992f1b721f3df55aa13fcb8","file_id":"6211","relation":"main_file"}],"pubrep_id":"862","status":"public","ddc":["571","579"],"title":"Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"818","has_accepted_license":"1","article_processing_charge":"No","day":"27","date_published":"2017-09-27T00:00:00Z","page":"113","citation":{"ama":"Mitosch K. Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics. 2017. doi:10.15479/AT:ISTA:th_862","ista":"Mitosch K. 2017. Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics. Institute of Science and Technology Austria.","apa":"Mitosch, K. (2017). Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th_862","ieee":"K. Mitosch, “Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics,” Institute of Science and Technology Austria, 2017.","mla":"Mitosch, Karin. Timing, Variability and Cross-Protection in Bacteria – Insights from Dynamic Gene Expression Responses to Antibiotics. Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:th_862.","short":"K. Mitosch, Timing, Variability and Cross-Protection in Bacteria – Insights from Dynamic Gene Expression Responses to Antibiotics, Institute of Science and Technology Austria, 2017.","chicago":"Mitosch, Karin. “Timing, Variability and Cross-Protection in Bacteria – Insights from Dynamic Gene Expression Responses to Antibiotics.” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:th_862."}},{"file":[{"file_size":2438660,"content_type":"application/pdf","creator":"system","file_name":"IST-2017-901-v1+1_1-s2.0-S2405471217300868-main.pdf","access_level":"open_access","date_created":"2018-12-12T10:13:54Z","date_updated":"2020-07-14T12:47:35Z","checksum":"04ff20011c3d9a601c514aa999a5fe1a","relation":"main_file","file_id":"5041"}],"oa_version":"Published Version","pubrep_id":"901","intvolume":" 4","title":"Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment","status":"public","ddc":["576","610"],"user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"666","issue":"4","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."}],"type":"journal_article","date_published":"2017-04-26T00:00:00Z","page":"393 - 403","citation":{"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.","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.","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","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"},"publication":"Cell Systems","has_accepted_license":"1","article_processing_charge":"Yes (in subscription journal)","day":"26","scopus_import":1,"volume":4,"date_created":"2018-12-11T11:47:48Z","date_updated":"2023-09-07T12:00:25Z","related_material":{"record":[{"id":"818","status":"public","relation":"dissertation_contains"}]},"author":[{"id":"39B66846-F248-11E8-B48F-1D18A9856A87","first_name":"Karin","last_name":"Mitosch","full_name":"Mitosch, Karin"},{"id":"34DA8BD6-F248-11E8-B48F-1D18A9856A87","first_name":"Georg","last_name":"Rieckh","full_name":"Rieckh, Georg"},{"last_name":"Bollenbach","first_name":"Tobias","orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","full_name":"Bollenbach, Tobias"}],"publisher":"Cell Press","department":[{"_id":"ToBo"},{"_id":"GaTk"}],"publication_status":"published","year":"2017","publist_id":"7061","ec_funded":1,"file_date_updated":"2020-07-14T12:47:35Z","language":[{"iso":"eng"}],"doi":"10.1016/j.cels.2017.03.001","project":[{"_id":"25E83C2C-B435-11E9-9278-68D0E5697425","grant_number":"303507","name":"Optimality principles in responses to antibiotics","call_identifier":"FP7"},{"_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","grant_number":"P27201-B22","call_identifier":"FWF","name":"Revealing the mechanisms underlying drug interactions"},{"name":"Revealing the fundamental limits of cell growth","_id":"25EB3A80-B435-11E9-9278-68D0E5697425","grant_number":"RGP0042/2013"}],"quality_controlled":"1","tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","short":"CC BY-NC-ND (4.0)","image":"/images/cc_by_nc_nd.png"},"oa":1,"publication_identifier":{"issn":["24054712"]},"month":"04"},{"page":"10666 - 10671","publication":"PNAS","citation":{"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.","short":"M. de Vos, M.P. Zagórski, A. Mcnally, M.T. Bollenbach, PNAS 114 (2017) 10666–10671.","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.","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","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.","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.","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"},"date_published":"2017-10-03T00:00:00Z","scopus_import":"1","day":"03","article_processing_charge":"No","status":"public","title":"Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections","intvolume":" 114","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"822","oa_version":"Submitted Version","type":"journal_article","abstract":[{"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. ","lang":"eng"}],"issue":"40","quality_controlled":"1","isi":1,"project":[{"name":"Optimality principles in responses to antibiotics","call_identifier":"FP7","grant_number":"303507","_id":"25E83C2C-B435-11E9-9278-68D0E5697425"},{"name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","grant_number":"P27201-B22"}],"main_file_link":[{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635929/","open_access":"1"}],"oa":1,"external_id":{"pmid":["28923953"],"isi":["000412130500061"]},"language":[{"iso":"eng"}],"doi":"10.1073/pnas.1713372114","month":"10","publication_identifier":{"issn":["00278424"]},"publication_status":"published","department":[{"_id":"ToBo"}],"publisher":"National Academy of Sciences","year":"2017","pmid":1,"date_created":"2018-12-11T11:48:41Z","date_updated":"2023-09-26T16:18:48Z","volume":114,"author":[{"id":"3111FFAC-F248-11E8-B48F-1D18A9856A87","first_name":"Marjon","last_name":"De Vos","full_name":"De Vos, Marjon"},{"first_name":"Marcin P","last_name":"Zagórski","id":"343DA0DC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-7896-7762","full_name":"Zagórski, Marcin P"},{"full_name":"Mcnally, Alan","last_name":"Mcnally","first_name":"Alan"},{"orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach","first_name":"Mark Tobias","full_name":"Bollenbach, Mark Tobias"}],"ec_funded":1,"publist_id":"6827"},{"tmp":{"short":"CC BY-SA (4.0)","image":"/images/cc_by_sa.png","name":"Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode"},"citation":{"mla":"Lukacisin, Martin. MATLAB Analysis Code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:64.","short":"M. Lukacisin, (2017).","chicago":"Lukacisin, Martin. “MATLAB Analysis Code for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.’” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:64.","ama":"Lukacisin M. MATLAB analysis code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” 2017. doi:10.15479/AT:ISTA:64","ista":"Lukacisin M. 2017. MATLAB analysis code for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast’, Institute of Science and Technology Austria, 10.15479/AT:ISTA:64.","ieee":"M. Lukacisin, “MATLAB analysis code for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.’” Institute of Science and Technology Austria, 2017.","apa":"Lukacisin, M. (2017). MATLAB analysis code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:64"},"oa":1,"doi":"10.15479/AT:ISTA:64","date_published":"2017-03-20T00:00:00Z","month":"03","day":"20","has_accepted_license":"1","article_processing_charge":"No","year":"2017","_id":"5563","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"MATLAB analysis code for 'Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast'","status":"public","ddc":["571"],"publisher":"Institute of Science and Technology Austria","department":[{"_id":"ToBo"}],"author":[{"full_name":"Lukacisin, Martin","last_name":"Lukacisin","first_name":"Martin","orcid":"0000-0001-6549-4177","id":"298FFE8C-F248-11E8-B48F-1D18A9856A87"}],"date_updated":"2024-02-21T13:46:47Z","date_created":"2018-12-12T12:31:33Z","file":[{"checksum":"ee697f2b1ade4dc14d6ac0334dd832ab","date_updated":"2020-07-14T12:47:03Z","date_created":"2018-12-12T13:02:37Z","file_id":"5602","relation":"main_file","creator":"system","file_size":296722548,"content_type":"application/zip","access_level":"open_access","file_name":"IST-2016-45-v1+1_PaperCode.zip"}],"oa_version":"Published Version","datarep_id":"64","type":"research_data","file_date_updated":"2020-07-14T12:47:03Z","abstract":[{"text":"MATLAB code and processed datasets available for reproducing the results in: \r\nLukačišin, M.*, Landon, M.*, Jajoo, R*. (2016) Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.\r\n*equal contributions","lang":"eng"}],"license":"https://creativecommons.org/licenses/by-sa/4.0/"},{"scopus_import":"1","day":"16","article_processing_charge":"Yes","has_accepted_license":"1","publication":"PLoS One","citation":{"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","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.","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","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.","short":"M. Lukacisin, M. Landon, R. Jajoo, PLoS One 12 (2017).","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."},"date_published":"2017-03-16T00:00:00Z","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","_id":"1029","user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","status":"public","title":"Sequence-specific thermodynamic properties of nucleic acids influence both transcriptional pausing and backtracking in yeast","ddc":["570"],"intvolume":" 12","pubrep_id":"800","file":[{"access_level":"open_access","file_name":"IST-2017-800-v1+1_journal.pone.0174066.pdf","creator":"system","file_size":3429381,"content_type":"application/pdf","file_id":"4772","relation":"main_file","date_updated":"2018-12-12T10:09:47Z","date_created":"2018-12-12T10:09:47Z"}],"oa_version":"Published Version","month":"03","publication_identifier":{"issn":["19326203"]},"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"},"external_id":{"isi":["000396318300121"]},"oa":1,"isi":1,"quality_controlled":"1","doi":"10.1371/journal.pone.0174066","language":[{"iso":"eng"}],"article_number":"e0174066","file_date_updated":"2018-12-12T10:09:47Z","publist_id":"6361","year":"2017","publication_status":"published","publisher":"Public Library of Science","department":[{"_id":"ToBo"}],"author":[{"full_name":"Lukacisin, Martin","first_name":"Martin","last_name":"Lukacisin","id":"298FFE8C-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6549-4177"},{"full_name":"Landon, Matthieu","last_name":"Landon","first_name":"Matthieu"},{"full_name":"Jajoo, Rishi","last_name":"Jajoo","first_name":"Rishi"}],"related_material":{"record":[{"relation":"popular_science","status":"public","id":"5556"},{"status":"public","relation":"dissertation_contains","id":"6392"}]},"date_created":"2018-12-11T11:49:46Z","date_updated":"2024-03-28T23:30:04Z","volume":12},{"language":[{"iso":"eng"}],"doi":"10.1371/journal.pcbi.1005609","project":[{"_id":"25B1EC9E-B435-11E9-9278-68D0E5697425","grant_number":"618091","call_identifier":"FP7","name":"Speed of Adaptation in Population Genetics and Evolutionary Computation"}],"quality_controlled":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","image":"/images/cc_by.png"},"oa":1,"publication_identifier":{"issn":["1553734X"]},"month":"07","volume":13,"date_updated":"2024-03-28T23:30:28Z","date_created":"2018-12-11T11:47:58Z","related_material":{"record":[{"relation":"research_data","status":"public","id":"9849"},{"id":"9850","relation":"research_data","status":"public"},{"id":"9851","relation":"research_data","status":"public"},{"id":"9852","relation":"research_data","status":"public"},{"id":"6263","relation":"dissertation_contains","status":"public"}]},"author":[{"orcid":"0000-0002-2519-8004","id":"4342E402-F248-11E8-B48F-1D18A9856A87","last_name":"Lukacisinova","first_name":"Marta","full_name":"Lukacisinova, Marta"},{"full_name":"Novak, Sebastian","orcid":"0000-0002-2519-824X","id":"461468AE-F248-11E8-B48F-1D18A9856A87","last_name":"Novak","first_name":"Sebastian"},{"full_name":"Paixao, Tiago","orcid":"0000-0003-2361-3953","id":"2C5658E6-F248-11E8-B48F-1D18A9856A87","last_name":"Paixao","first_name":"Tiago"}],"publisher":"Public Library of Science","department":[{"_id":"ToBo"},{"_id":"NiBa"},{"_id":"CaGu"}],"publication_status":"published","year":"2017","ec_funded":1,"publist_id":"7004","file_date_updated":"2020-07-14T12:47:46Z","article_number":"e1005609","date_published":"2017-07-18T00:00:00Z","article_type":"original","citation":{"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","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.","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.","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.","short":"M. Lukacisinova, S. Novak, T. Paixao, PLoS Computational Biology 13 (2017).","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."},"publication":"PLoS Computational Biology","has_accepted_license":"1","day":"18","scopus_import":1,"oa_version":"Published Version","file":[{"creator":"system","file_size":3775716,"content_type":"application/pdf","access_level":"open_access","file_name":"IST-2017-894-v1+1_journal.pcbi.1005609.pdf","checksum":"9143c290fa6458ed2563bff4b295554a","date_updated":"2020-07-14T12:47:46Z","date_created":"2018-12-12T10:15:01Z","file_id":"5117","relation":"main_file"}],"pubrep_id":"894","intvolume":" 13","title":"Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes","ddc":["576"],"status":"public","_id":"696","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"7","abstract":[{"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.","lang":"eng"}],"type":"journal_article"},{"article_processing_charge":"Yes (in subscription journal)","has_accepted_license":"1","day":"01","scopus_import":"1","date_published":"2017-08-01T00:00:00Z","citation":{"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","ista":"Lukacisinova M, Bollenbach MT. 2017. Toward a quantitative understanding of antibiotic resistance evolution. Current Opinion in Biotechnology. 46, 90–97.","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","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.","short":"M. Lukacisinova, M.T. Bollenbach, Current Opinion in Biotechnology 46 (2017) 90–97.","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."},"publication":"Current Opinion in Biotechnology","page":"90 - 97","article_type":"original","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","pubrep_id":"801","oa_version":"Published Version","file":[{"relation":"main_file","file_id":"5846","success":1,"date_created":"2019-01-18T09:57:57Z","date_updated":"2019-01-18T09:57:57Z","access_level":"open_access","file_name":"2017_CurrentOpinion_Lukaciinova.pdf","content_type":"application/pdf","file_size":858338,"creator":"dernst"}],"user_id":"c635000d-4b10-11ee-a964-aac5a93f6ac1","_id":"1027","intvolume":" 46","title":"Toward a quantitative understanding of antibiotic resistance evolution","ddc":["570"],"status":"public","month":"08","doi":"10.1016/j.copbio.2017.02.013","language":[{"iso":"eng"}],"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,"external_id":{"isi":["000408077400015"]},"project":[{"grant_number":"P27201-B22","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF"},{"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"}],"isi":1,"quality_controlled":"1","ec_funded":1,"publist_id":"6364","file_date_updated":"2019-01-18T09:57:57Z","related_material":{"record":[{"relation":"dissertation_contains","status":"public","id":"6263"}]},"author":[{"full_name":"Lukacisinova, Marta","id":"4342E402-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-2519-8004","first_name":"Marta","last_name":"Lukacisinova"},{"first_name":"Mark Tobias","last_name":"Bollenbach","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Mark Tobias"}],"volume":46,"date_created":"2018-12-11T11:49:45Z","date_updated":"2024-03-28T23:30:29Z","year":"2017","department":[{"_id":"ToBo"}],"publisher":"Elsevier","publication_status":"published"},{"scopus_import":1,"day":"07","has_accepted_license":"1","publication":"Scientific Reports","citation":{"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.","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.","ama":"Schwarz J, Bierbaum V, Merrin J, et al. A microfluidic device for measuring cell migration towards substrate bound and soluble chemokine gradients. Scientific Reports. 2016;6. doi:10.1038/srep36440","apa":"Schwarz, J., Bierbaum, V., Merrin, J., Frank, T., Hauschild, R., Bollenbach, M. T., … Mehling, M. (2016). A microfluidic device for measuring cell migration towards substrate bound and soluble chemokine gradients. Scientific Reports. Nature Publishing Group. https://doi.org/10.1038/srep36440","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."},"date_published":"2016-11-07T00:00:00Z","type":"journal_article","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"}],"status":"public","title":"A microfluidic device for measuring cell migration towards substrate bound and soluble chemokine gradients","ddc":["579"],"intvolume":" 6","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1154","file":[{"date_updated":"2018-12-12T10:09:32Z","date_created":"2018-12-12T10:09:32Z","file_id":"4756","relation":"main_file","creator":"system","content_type":"application/pdf","file_size":2353456,"file_name":"IST-2017-744-v1+1_srep36440.pdf","access_level":"open_access"}],"oa_version":"Published Version","pubrep_id":"744","month":"11","quality_controlled":"1","project":[{"_id":"25A603A2-B435-11E9-9278-68D0E5697425","grant_number":"281556","call_identifier":"FP7","name":"Cytoskeletal force generation and force transduction of migrating leukocytes (EU)"},{"_id":"25A8E5EA-B435-11E9-9278-68D0E5697425","grant_number":"Y 564-B12","call_identifier":"FWF","name":"Cytoskeletal force generation and transduction of leukocytes (FWF)"}],"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"},"language":[{"iso":"eng"}],"doi":"10.1038/srep36440","article_number":"36440","file_date_updated":"2018-12-12T10:09:32Z","publist_id":"6204","ec_funded":1,"publication_status":"published","department":[{"_id":"MiSi"},{"_id":"NanoFab"},{"_id":"Bio"},{"_id":"ToBo"}],"publisher":"Nature Publishing Group","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","date_created":"2018-12-11T11:50:27Z","date_updated":"2021-01-12T06:48:41Z","volume":6,"author":[{"full_name":"Schwarz, Jan","id":"346C1EC6-F248-11E8-B48F-1D18A9856A87","first_name":"Jan","last_name":"Schwarz"},{"last_name":"Bierbaum","first_name":"Veronika","id":"3FD04378-F248-11E8-B48F-1D18A9856A87","full_name":"Bierbaum, Veronika"},{"full_name":"Merrin, Jack","orcid":"0000-0001-5145-4609","id":"4515C308-F248-11E8-B48F-1D18A9856A87","last_name":"Merrin","first_name":"Jack"},{"full_name":"Frank, Tino","last_name":"Frank","first_name":"Tino"},{"full_name":"Hauschild, Robert","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9843-3522","first_name":"Robert","last_name":"Hauschild"},{"id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-4398-476X","first_name":"Mark Tobias","last_name":"Bollenbach","full_name":"Bollenbach, Mark Tobias"},{"full_name":"Tay, Savaş","last_name":"Tay","first_name":"Savaş"},{"full_name":"Sixt, Michael K","orcid":"0000-0002-6620-9179","id":"41E9FBEA-F248-11E8-B48F-1D18A9856A87","last_name":"Sixt","first_name":"Michael K"},{"orcid":"0000-0001-8599-1226","id":"3C23B994-F248-11E8-B48F-1D18A9856A87","last_name":"Mehling","first_name":"Matthias","full_name":"Mehling, Matthias"}]},{"oa_version":"Submitted Version","_id":"1218","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","intvolume":" 82","status":"public","title":"Culturing synechocystis sp. Strain pcc 6803 with N2 and CO2 in a diel regime reveals multiphase glycogen dynamics with low maintenance costs","issue":"14","abstract":[{"lang":"eng","text":"Investigating the physiology of cyanobacteria cultured under a diel light regime is relevant for a better understanding of the resulting growth characteristics and for specific biotechnological applications that are foreseen for these photosynthetic organisms. Here, we present the results of a multiomics study of the model cyanobacterium Synechocystis sp. strain PCC 6803, cultured in a lab-scale photobioreactor in physiological conditions relevant for large-scale culturing. The culture was sparged withN2 andCO2, leading to an anoxic environment during the dark period. Growth followed the availability of light. Metabolite analysis performed with 1Hnuclear magnetic resonance analysis showed that amino acids involved in nitrogen and sulfur assimilation showed elevated levels in the light. Most protein levels, analyzed through mass spectrometry, remained rather stable. However, several high-light-response proteins and stress-response proteins showed distinct changes at the onset of the light period. Microarray-based transcript analysis found common patterns of~56% of the transcriptome following the diel regime. These oscillating transcripts could be grouped coarsely into genes that were upregulated and downregulated in the dark period. The accumulated glycogen was degraded in the anaerobic environment in the dark. A small part was degraded gradually, reflecting basic maintenance requirements of the cells in darkness. Surprisingly, the largest part was degraded rapidly in a short time span at the end of the dark period. This degradation could allow rapid formation of metabolic intermediates at the end of the dark period, preparing the cells for the resumption of growth at the start of the light period."}],"type":"journal_article","date_published":"2016-07-01T00:00:00Z","citation":{"mla":"Angermayr, Andreas, et al. “Culturing Synechocystis Sp. Strain Pcc 6803 with N2 and CO2 in a Diel Regime Reveals Multiphase Glycogen Dynamics with Low Maintenance Costs.” Applied and Environmental Microbiology, vol. 82, no. 14, American Society for Microbiology, 2016, pp. 4180–89, doi:10.1128/AEM.00256-16.","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.","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.","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","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.","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","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."},"publication":"Applied and Environmental Microbiology","page":"4180 - 4189","day":"01","scopus_import":1,"author":[{"full_name":"Angermayr, Andreas","id":"4677C796-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8619-2223","first_name":"Andreas","last_name":"Angermayr"},{"full_name":"Van Alphen, Pascal","first_name":"Pascal","last_name":"Van Alphen"},{"last_name":"Hasdemir","first_name":"Dicle","full_name":"Hasdemir, Dicle"},{"last_name":"Kramer","first_name":"Gertjan","full_name":"Kramer, Gertjan"},{"last_name":"Iqbal","first_name":"Muzamal","full_name":"Iqbal, Muzamal"},{"full_name":"Van Grondelle, Wilmar","last_name":"Van Grondelle","first_name":"Wilmar"},{"last_name":"Hoefsloot","first_name":"Huub","full_name":"Hoefsloot, Huub"},{"first_name":"Younghae","last_name":"Choi","full_name":"Choi, Younghae"},{"full_name":"Hellingwerf, Klaas","first_name":"Klaas","last_name":"Hellingwerf"}],"volume":82,"date_updated":"2021-01-12T06:49:10Z","date_created":"2018-12-11T11:50:46Z","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","publisher":"American Society for Microbiology","department":[{"_id":"ToBo"}],"publication_status":"published","publist_id":"6117","doi":"10.1128/AEM.00256-16","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959195/"}],"oa":1,"quality_controlled":"1","month":"07"},{"abstract":[{"lang":"eng","text":"Antibiotic resistance carries a fitness cost that must be overcome in order for resistance to persist over the long term. Compensatory mutations that recover the functional defects associated with resistance mutations have been argued to play a key role in overcoming the cost of resistance, but compensatory mutations are expected to be rare relative to generally beneficial mutations that increase fitness, irrespective of antibiotic resistance. Given this asymmetry, population genetics theory predicts that populations should adapt by compensatory mutations when the cost of resistance is large, whereas generally beneficial mutations should drive adaptation when the cost of resistance is small. We tested this prediction by determining the genomic mechanisms underpinning adaptation to antibiotic-free conditions in populations of the pathogenic bacterium Pseudomonas aeruginosa that carry costly antibiotic resistance mutations. Whole-genome sequencing revealed that populations founded by high-cost rifampicin-resistant mutants adapted via compensatory mutations in three genes of the RNA polymerase core enzyme, whereas populations founded by low-cost mutants adapted by generally beneficial mutations, predominantly in the quorum-sensing transcriptional regulator gene lasR. Even though the importance of compensatory evolution in maintaining resistance has been widely recognized, our study shows that the roles of general adaptation in maintaining resistance should not be underestimated and highlights the need to understand how selection at other sites in the genome influences the dynamics of resistance alleles in clinical settings."}],"issue":"1822","type":"journal_article","file":[{"creator":"system","content_type":"application/pdf","file_size":626804,"file_name":"IST-2016-488-v1+1_20152452.full.pdf","access_level":"open_access","date_updated":"2020-07-14T12:45:02Z","date_created":"2018-12-12T10:11:43Z","checksum":"78ffe70c1c88af3856d31ca6b7195a27","file_id":"4899","relation":"main_file"}],"oa_version":"Published Version","pubrep_id":"488","ddc":["570"],"title":"The genomic basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa","status":"public","intvolume":" 283","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","_id":"1552","day":"13","has_accepted_license":"1","scopus_import":1,"date_published":"2016-01-13T00:00:00Z","publication":"Proceedings of the Royal Society of London Series B Biological Sciences","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","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","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.","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."},"file_date_updated":"2020-07-14T12:45:02Z","publist_id":"5619","article_number":"20152452","date_updated":"2021-01-12T06:51:33Z","date_created":"2018-12-11T11:52:40Z","volume":283,"author":[{"first_name":"Qin","last_name":"Qi","id":"3B22D412-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6148-2416","full_name":"Qi, Qin"},{"last_name":"Toll Riera","first_name":"Macarena","full_name":"Toll Riera, Macarena"},{"last_name":"Heilbron","first_name":"Karl","full_name":"Heilbron, Karl"},{"full_name":"Preston, Gail","last_name":"Preston","first_name":"Gail"},{"full_name":"Maclean, R Craig","first_name":"R Craig","last_name":"Maclean"}],"publication_status":"published","department":[{"_id":"ToBo"}],"publisher":"Royal Society, The","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","month":"01","language":[{"iso":"eng"}],"doi":"10.1098/rspb.2015.2452","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},{"type":"research_data","datarep_id":"45","abstract":[{"text":"MATLAB code and processed datasets available for reproducing the results in: \r\nLukačišin, M.*, Landon, M.*, Jajoo, R*. (2016) Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.\r\n*equal contributions","lang":"eng"}],"file_date_updated":"2020-07-14T12:47:02Z","publisher":"Institute of Science and Technology Austria","department":[{"_id":"ToBo"}],"title":"MATLAB analysis code for 'Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast'","ddc":["571"],"status":"public","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"5556","year":"2016","file":[{"file_name":"IST-2016-45-v1+1_PaperCode.zip","access_level":"open_access","creator":"system","file_size":296722548,"content_type":"application/zip","file_id":"5616","relation":"main_file","date_updated":"2020-07-14T12:47:02Z","date_created":"2018-12-12T13:02:58Z","checksum":"ee697f2b1ade4dc14d6ac0334dd832ab"}],"oa_version":"Published Version","date_created":"2018-12-12T12:31:31Z","date_updated":"2024-02-21T13:51:53Z","related_material":{"record":[{"id":"8431","relation":"used_in_publication","status":"deleted"},{"status":"public","relation":"research_paper","id":"1029"}]},"author":[{"id":"298FFE8C-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-6549-4177","first_name":"Martin","last_name":"Lukacisin","full_name":"Lukacisin, Martin"},{"full_name":"Landon, Matthieu","first_name":"Matthieu","last_name":"Landon"},{"first_name":"Rishi","last_name":"Jajoo","full_name":"Jajoo, Rishi"}],"keyword":["transcription","pausing","backtracking","polymerase","RNA","NET-seq","nucleosome","basepairing"],"article_processing_charge":"No","has_accepted_license":"1","month":"08","day":"25","oa":1,"tmp":{"short":"CC BY-SA (4.0)","image":"/images/cc_by_sa.png","name":"Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode"},"citation":{"ama":"Lukacisin M, Landon M, Jajoo R. MATLAB analysis code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” 2016. doi:10.15479/AT:ISTA:45","ieee":"M. Lukacisin, M. Landon, and R. Jajoo, “MATLAB analysis code for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.’” Institute of Science and Technology Austria, 2016.","apa":"Lukacisin, M., Landon, M., & Jajoo, R. (2016). MATLAB analysis code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:45","ista":"Lukacisin M, Landon M, Jajoo R. 2016. MATLAB analysis code for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast’, Institute of Science and Technology Austria, 10.15479/AT:ISTA:45.","short":"M. Lukacisin, M. Landon, R. Jajoo, (2016).","mla":"Lukacisin, Martin, et al. MATLAB Analysis Code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” Institute of Science and Technology Austria, 2016, doi:10.15479/AT:ISTA:45.","chicago":"Lukacisin, Martin, Matthieu Landon, and Rishi Jajoo. “MATLAB Analysis Code for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.’” Institute of Science and Technology Austria, 2016. https://doi.org/10.15479/AT:ISTA:45."},"date_published":"2016-08-25T00:00:00Z","doi":"10.15479/AT:ISTA:45"},{"day":"01","month":"12","scopus_import":1,"doi":"10.1073/pnas.1510282112","date_published":"2015-12-01T00:00:00Z","language":[{"iso":"eng"}],"citation":{"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.","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.","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.","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"},"publication":"PNAS","page":"14906 - 14911","quality_controlled":"1","publist_id":"5600","issue":"48","abstract":[{"lang":"eng","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."}],"type":"journal_article","author":[{"first_name":"Marjon","last_name":"De Vos","id":"3111FFAC-F248-11E8-B48F-1D18A9856A87","full_name":"De Vos, Marjon"},{"full_name":"Dawid, Alexandre","first_name":"Alexandre","last_name":"Dawid"},{"last_name":"Šunderlíková","first_name":"Vanda","full_name":"Šunderlíková, Vanda"},{"first_name":"Sander","last_name":"Tans","full_name":"Tans, Sander"}],"oa_version":"None","volume":112,"date_created":"2018-12-11T11:52:47Z","date_updated":"2021-01-12T06:51:40Z","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.","_id":"1571","year":"2015","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"National Academy of Sciences","intvolume":" 112","department":[{"_id":"ToBo"}],"publication_status":"published","title":"Breaking evolutionary constraint with a tradeoff ratchet","status":"public"},{"scopus_import":"1","day":"23","month":"04","article_processing_charge":"No","quality_controlled":"1","page":"431 - 432","publication":"Cell","citation":{"short":"M.T. Bollenbach, C.-P.J. Heisenberg, Cell 161 (2015) 431–432.","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.","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.","ama":"Bollenbach MT, Heisenberg C-PJ. Gradients are shaping up. Cell. 2015;161(3):431-432. doi:10.1016/j.cell.2015.04.009","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","ista":"Bollenbach MT, Heisenberg C-PJ. 2015. Gradients are shaping up. Cell. 161(3), 431–432."},"language":[{"iso":"eng"}],"date_published":"2015-04-23T00:00:00Z","doi":"10.1016/j.cell.2015.04.009","type":"journal_article","abstract":[{"lang":"eng","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."}],"publist_id":"5590","issue":"3","publication_status":"published","title":"Gradients are shaping up","status":"public","department":[{"_id":"ToBo"},{"_id":"CaHe"}],"publisher":"Cell Press","intvolume":" 161","_id":"1581","year":"2015","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","date_created":"2018-12-11T11:52:50Z","date_updated":"2022-08-25T13:56:10Z","oa_version":"None","volume":161,"author":[{"orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach","first_name":"Mark Tobias","full_name":"Bollenbach, Mark Tobias"},{"last_name":"Heisenberg","first_name":"Carl-Philipp J","orcid":"0000-0002-0912-4566","id":"39427864-F248-11E8-B48F-1D18A9856A87","full_name":"Heisenberg, Carl-Philipp J"}]},{"oa_version":"None","volume":33,"date_created":"2018-12-11T11:52:52Z","date_updated":"2021-01-12T06:51:46Z","author":[{"full_name":"Angermayr, Andreas","orcid":"0000-0001-8619-2223","id":"4677C796-F248-11E8-B48F-1D18A9856A87","last_name":"Angermayr","first_name":"Andreas"},{"last_name":"Gorchs","first_name":"Aleix","full_name":"Gorchs, Aleix"},{"first_name":"Klaas","last_name":"Hellingwerf","full_name":"Hellingwerf, Klaas"}],"intvolume":" 33","department":[{"_id":"ToBo"}],"publisher":"Elsevier","publication_status":"published","title":"Metabolic engineering of cyanobacteria for the synthesis of commodity products","status":"public","_id":"1586","user_id":"3E5EF7F0-F248-11E8-B48F-1D18A9856A87","year":"2015","publist_id":"5585","issue":"6","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."}],"type":"journal_article","language":[{"iso":"eng"}],"doi":"10.1016/j.tibtech.2015.03.009","date_published":"2015-06-01T00:00:00Z","page":"352 - 361","quality_controlled":"1","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."},"publication":"Trends in Biotechnology","month":"06","day":"01","scopus_import":1},{"month":"11","language":[{"iso":"eng"}],"doi":"10.1186/s13068-015-0380-2","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,"publist_id":"5537","file_date_updated":"2020-07-14T12:45:07Z","article_number":"193","volume":8,"date_updated":"2021-01-12T06:52:04Z","date_created":"2018-12-11T11:53:05Z","author":[{"last_name":"Hammar","first_name":"Petter","full_name":"Hammar, Petter"},{"full_name":"Angermayr, Andreas","id":"4677C796-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-8619-2223","first_name":"Andreas","last_name":"Angermayr"},{"last_name":"Sjostrom","first_name":"Staffan","full_name":"Sjostrom, Staffan"},{"full_name":"Van Der Meer, Josefin","last_name":"Van Der Meer","first_name":"Josefin"},{"full_name":"Hellingwerf, Klaas","first_name":"Klaas","last_name":"Hellingwerf"},{"last_name":"Hudson","first_name":"Elton","full_name":"Hudson, Elton"},{"full_name":"Joensson, Hakaan","first_name":"Hakaan","last_name":"Joensson"}],"department":[{"_id":"ToBo"}],"publisher":"BioMed Central","publication_status":"published","year":"2015","has_accepted_license":"1","day":"25","scopus_import":1,"date_published":"2015-11-25T00:00:00Z","citation":{"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).","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.","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.","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","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"},"publication":"Biotechnology for Biofuels","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","oa_version":"Published Version","file":[{"relation":"main_file","file_id":"4796","date_created":"2018-12-12T10:10:11Z","date_updated":"2020-07-14T12:45:07Z","checksum":"172b0b6f4eb2e5c22b7cec1d57dc0107","file_name":"IST-2016-467-v1+1_s13068-015-0380-2.pdf","access_level":"open_access","content_type":"application/pdf","file_size":2914089,"creator":"system"}],"pubrep_id":"467","intvolume":" 8","title":"Single-cell screening of photosynthetic growth and lactate production by cyanobacteria","status":"public","ddc":["570"],"_id":"1623","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87"},{"doi":"10.1016/j.mib.2015.05.008","language":[{"iso":"eng"}],"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","project":[{"call_identifier":"FWF","name":"Revealing the mechanisms underlying drug interactions","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","grant_number":"P27201-B22"},{"_id":"25E83C2C-B435-11E9-9278-68D0E5697425","grant_number":"303507","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":"06","author":[{"orcid":"0000-0003-4398-476X","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87","last_name":"Bollenbach","first_name":"Mark Tobias","full_name":"Bollenbach, Mark Tobias"}],"date_updated":"2021-01-12T06:53:21Z","date_created":"2018-12-11T11:54:08Z","volume":27,"year":"2015","publication_status":"published","publisher":"Elsevier","department":[{"_id":"ToBo"}],"file_date_updated":"2020-07-14T12:45:17Z","ec_funded":1,"publist_id":"5298","date_published":"2015-06-01T00:00:00Z","publication":"Current Opinion in Microbiology","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","ista":"Bollenbach MT. 2015. Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution. Current Opinion in Microbiology. 27, 1–9.","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","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.","short":"M.T. Bollenbach, Current Opinion in Microbiology 27 (2015) 1–9.","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."},"page":"1 - 9","day":"01","has_accepted_license":"1","scopus_import":1,"pubrep_id":"493","file":[{"creator":"system","file_size":1047255,"content_type":"application/pdf","access_level":"open_access","file_name":"IST-2016-493-v1+1_1-s2.0-S1369527415000594-main.pdf","checksum":"1683bb0f42ef892a5b3b71a050d65d25","date_updated":"2020-07-14T12:45:17Z","date_created":"2018-12-12T10:17:23Z","file_id":"5277","relation":"main_file"}],"oa_version":"Published Version","_id":"1810","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","ddc":["570"],"title":"Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution","intvolume":" 27","abstract":[{"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.","lang":"eng"}],"type":"journal_article"}]