--- _id: '666' 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. article_processing_charge: Yes (in subscription journal) author: - first_name: Karin full_name: Mitosch, Karin id: 39B66846-F248-11E8-B48F-1D18A9856A87 last_name: Mitosch - first_name: Georg full_name: Rieckh, Georg id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87 last_name: Rieckh - first_name: Tobias full_name: Bollenbach, Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: Mitosch K, Rieckh G, Bollenbach MT. Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. 2017;4(4):393-403. doi:10.1016/j.cels.2017.03.001 apa: Mitosch, K., Rieckh, G., & Bollenbach, M. T. (2017). Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment. Cell Systems. Cell Press. https://doi.org/10.1016/j.cels.2017.03.001 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. 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. mla: Mitosch, Karin, et al. “Noisy Response to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.” Cell Systems, vol. 4, no. 4, Cell Press, 2017, pp. 393–403, doi:10.1016/j.cels.2017.03.001. short: K. Mitosch, G. Rieckh, M.T. Bollenbach, Cell Systems 4 (2017) 393–403. date_created: 2018-12-11T11:47:48Z date_published: 2017-04-26T00:00:00Z date_updated: 2023-09-07T12:00:25Z day: '26' ddc: - '576' - '610' department: - _id: ToBo - _id: GaTk doi: 10.1016/j.cels.2017.03.001 ec_funded: 1 file: - access_level: open_access checksum: 04ff20011c3d9a601c514aa999a5fe1a content_type: application/pdf creator: system date_created: 2018-12-12T10:13:54Z date_updated: 2020-07-14T12:47:35Z file_id: '5041' file_name: IST-2017-901-v1+1_1-s2.0-S2405471217300868-main.pdf file_size: 2438660 relation: main_file file_date_updated: 2020-07-14T12:47:35Z has_accepted_license: '1' intvolume: ' 4' issue: '4' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '04' oa: 1 oa_version: Published Version page: 393 - 403 project: - _id: 25E83C2C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '303507' name: Optimality principles in responses to antibiotics - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 25EB3A80-B435-11E9-9278-68D0E5697425 grant_number: RGP0042/2013 name: Revealing the fundamental limits of cell growth publication: Cell Systems publication_identifier: issn: - '24054712' publication_status: published publisher: Cell Press publist_id: '7061' pubrep_id: '901' quality_controlled: '1' related_material: record: - id: '818' relation: dissertation_contains status: public scopus_import: 1 status: public title: Noisy response to antibiotic stress predicts subsequent single cell survival in an acidic environment tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 4 year: '2017' ... --- _id: '822' 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. ' article_processing_charge: No author: - first_name: Marjon full_name: De Vos, Marjon id: 3111FFAC-F248-11E8-B48F-1D18A9856A87 last_name: De Vos - first_name: Marcin P full_name: Zagórski, Marcin P id: 343DA0DC-F248-11E8-B48F-1D18A9856A87 last_name: Zagórski orcid: 0000-0001-7896-7762 - first_name: Alan full_name: Mcnally, Alan last_name: Mcnally - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: de Vos M, Zagórski MP, Mcnally A, Bollenbach MT. Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections. PNAS. 2017;114(40):10666-10671. doi:10.1073/pnas.1713372114 apa: de Vos, M., Zagórski, M. P., Mcnally, A., & Bollenbach, M. T. (2017). Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1713372114 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. 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. 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. date_created: 2018-12-11T11:48:41Z date_published: 2017-10-03T00:00:00Z date_updated: 2023-09-26T16:18:48Z day: '03' department: - _id: ToBo doi: 10.1073/pnas.1713372114 ec_funded: 1 external_id: isi: - '000412130500061' pmid: - '28923953' intvolume: ' 114' isi: 1 issue: '40' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635929/ month: '10' oa: 1 oa_version: Submitted Version page: 10666 - 10671 pmid: 1 project: - _id: 25E83C2C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '303507' name: Optimality principles in responses to antibiotics - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions publication: PNAS publication_identifier: issn: - '00278424' publication_status: published publisher: National Academy of Sciences publist_id: '6827' quality_controlled: '1' scopus_import: '1' status: public title: Interaction networks, ecological stability, and collective antibiotic tolerance in polymicrobial infections type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 114 year: '2017' ... --- _id: '5563' abstract: - lang: eng 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" article_processing_charge: No author: - first_name: Martin full_name: Lukacisin, Martin id: 298FFE8C-F248-11E8-B48F-1D18A9856A87 last_name: Lukacisin orcid: 0000-0001-6549-4177 citation: ama: Lukacisin M. MATLAB analysis code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” 2017. doi:10.15479/AT:ISTA:64 apa: Lukacisin, M. (2017). MATLAB analysis code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:64 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. 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. ista: Lukacisin M. 2017. MATLAB analysis code for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast’, Institute of Science and Technology Austria, 10.15479/AT:ISTA:64. mla: Lukacisin, Martin. MATLAB Analysis Code for “Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:64. short: M. Lukacisin, (2017). datarep_id: '64' date_created: 2018-12-12T12:31:33Z date_published: 2017-03-20T00:00:00Z date_updated: 2024-02-21T13:46:47Z day: '20' ddc: - '571' department: - _id: ToBo doi: 10.15479/AT:ISTA:64 file: - access_level: open_access checksum: ee697f2b1ade4dc14d6ac0334dd832ab content_type: application/zip creator: system date_created: 2018-12-12T13:02:37Z date_updated: 2020-07-14T12:47:03Z file_id: '5602' file_name: IST-2016-45-v1+1_PaperCode.zip file_size: 296722548 relation: main_file file_date_updated: 2020-07-14T12:47:03Z has_accepted_license: '1' license: https://creativecommons.org/licenses/by-sa/4.0/ month: '03' oa: 1 oa_version: Published Version publisher: Institute of Science and Technology Austria status: public title: MATLAB analysis code for 'Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast' tmp: image: /images/cc_by_sa.png legal_code_url: https://creativecommons.org/licenses/by-sa/4.0/legalcode name: Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0) short: CC BY-SA (4.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2017' ... --- _id: '1029' 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. article_number: e0174066 article_processing_charge: Yes author: - first_name: Martin full_name: Lukacisin, Martin id: 298FFE8C-F248-11E8-B48F-1D18A9856A87 last_name: Lukacisin orcid: 0000-0001-6549-4177 - first_name: Matthieu full_name: Landon, Matthieu last_name: Landon - first_name: Rishi full_name: Jajoo, Rishi last_name: Jajoo citation: ama: Lukacisin M, Landon M, Jajoo R. Sequence-specific thermodynamic properties of nucleic acids influence both transcriptional pausing and backtracking in yeast. PLoS One. 2017;12(3). doi:10.1371/journal.pone.0174066 apa: Lukacisin, M., Landon, M., & Jajoo, R. (2017). Sequence-specific thermodynamic properties of nucleic acids influence both transcriptional pausing and backtracking in yeast. PLoS One. Public Library of Science. https://doi.org/10.1371/journal.pone.0174066 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. 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. 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. 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). date_created: 2018-12-11T11:49:46Z date_published: 2017-03-16T00:00:00Z date_updated: 2024-03-27T23:30:05Z day: '16' ddc: - '570' department: - _id: ToBo doi: 10.1371/journal.pone.0174066 external_id: isi: - '000396318300121' file: - access_level: open_access content_type: application/pdf creator: system date_created: 2018-12-12T10:09:47Z date_updated: 2018-12-12T10:09:47Z file_id: '4772' file_name: IST-2017-800-v1+1_journal.pone.0174066.pdf file_size: 3429381 relation: main_file file_date_updated: 2018-12-12T10:09:47Z has_accepted_license: '1' intvolume: ' 12' isi: 1 issue: '3' language: - iso: eng month: '03' oa: 1 oa_version: Published Version publication: PLoS One publication_identifier: issn: - '19326203' publication_status: published publisher: Public Library of Science publist_id: '6361' pubrep_id: '800' quality_controlled: '1' related_material: record: - id: '5556' relation: popular_science status: public - id: '6392' relation: dissertation_contains status: public scopus_import: '1' status: public title: Sequence-specific thermodynamic properties of nucleic acids influence both transcriptional pausing and backtracking in yeast tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 12 year: '2017' ... --- _id: '696' 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. article_number: e1005609 article_type: original author: - first_name: Marta full_name: Lukacisinova, Marta id: 4342E402-F248-11E8-B48F-1D18A9856A87 last_name: Lukacisinova orcid: 0000-0002-2519-8004 - first_name: Sebastian full_name: Novak, Sebastian id: 461468AE-F248-11E8-B48F-1D18A9856A87 last_name: Novak orcid: 0000-0002-2519-824X - first_name: Tiago full_name: Paixao, Tiago id: 2C5658E6-F248-11E8-B48F-1D18A9856A87 last_name: Paixao orcid: 0000-0003-2361-3953 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' 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' 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.' 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.' 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). date_created: 2018-12-11T11:47:58Z date_published: 2017-07-18T00:00:00Z date_updated: 2024-03-27T23:30:28Z day: '18' ddc: - '576' department: - _id: ToBo - _id: NiBa - _id: CaGu doi: 10.1371/journal.pcbi.1005609 ec_funded: 1 file: - access_level: open_access checksum: 9143c290fa6458ed2563bff4b295554a content_type: application/pdf creator: system date_created: 2018-12-12T10:15:01Z date_updated: 2020-07-14T12:47:46Z file_id: '5117' file_name: IST-2017-894-v1+1_journal.pcbi.1005609.pdf file_size: 3775716 relation: main_file file_date_updated: 2020-07-14T12:47:46Z has_accepted_license: '1' intvolume: ' 13' issue: '7' language: - iso: eng month: '07' oa: 1 oa_version: Published Version project: - _id: 25B1EC9E-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '618091' name: Speed of Adaptation in Population Genetics and Evolutionary Computation publication: PLoS Computational Biology publication_identifier: issn: - 1553734X publication_status: published publisher: Public Library of Science publist_id: '7004' pubrep_id: '894' quality_controlled: '1' related_material: record: - id: '9849' relation: research_data status: public - 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 scopus_import: 1 status: public title: 'Stress induced mutagenesis: Stress diversity facilitates the persistence of mutator genes' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 13 year: '2017' ... --- _id: '1027' 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. article_processing_charge: Yes (in subscription journal) article_type: original author: - first_name: Marta full_name: Lukacisinova, Marta id: 4342E402-F248-11E8-B48F-1D18A9856A87 last_name: Lukacisinova orcid: 0000-0002-2519-8004 - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X 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 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 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. 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. ista: Lukacisinova M, Bollenbach MT. 2017. Toward a quantitative understanding of antibiotic resistance evolution. Current Opinion in Biotechnology. 46, 90–97. mla: Lukacisinova, Marta, and Mark Tobias Bollenbach. “Toward a Quantitative Understanding of Antibiotic Resistance Evolution.” Current Opinion in Biotechnology, vol. 46, Elsevier, 2017, pp. 90–97, doi:10.1016/j.copbio.2017.02.013. short: M. Lukacisinova, M.T. Bollenbach, Current Opinion in Biotechnology 46 (2017) 90–97. date_created: 2018-12-11T11:49:45Z date_published: 2017-08-01T00:00:00Z date_updated: 2024-03-27T23:30:28Z day: '01' ddc: - '570' department: - _id: ToBo doi: 10.1016/j.copbio.2017.02.013 ec_funded: 1 external_id: isi: - '000408077400015' file: - access_level: open_access content_type: application/pdf creator: dernst date_created: 2019-01-18T09:57:57Z date_updated: 2019-01-18T09:57:57Z file_id: '5846' file_name: 2017_CurrentOpinion_Lukaciinova.pdf file_size: 858338 relation: main_file success: 1 file_date_updated: 2019-01-18T09:57:57Z has_accepted_license: '1' intvolume: ' 46' isi: 1 language: - iso: eng month: '08' oa: 1 oa_version: Published Version page: 90 - 97 project: - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 25E83C2C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '303507' name: Optimality principles in responses to antibiotics - _id: 25EB3A80-B435-11E9-9278-68D0E5697425 grant_number: RGP0042/2013 name: Revealing the fundamental limits of cell growth publication: Current Opinion in Biotechnology publication_status: published publisher: Elsevier publist_id: '6364' pubrep_id: '801' quality_controlled: '1' related_material: record: - id: '6263' relation: dissertation_contains status: public scopus_import: '1' status: public title: Toward a quantitative understanding of antibiotic resistance evolution tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 46 year: '2017' ... --- _id: '1154' abstract: - lang: eng 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" 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' article_number: '36440' author: - first_name: Jan full_name: Schwarz, Jan id: 346C1EC6-F248-11E8-B48F-1D18A9856A87 last_name: Schwarz - first_name: Veronika full_name: Bierbaum, Veronika id: 3FD04378-F248-11E8-B48F-1D18A9856A87 last_name: Bierbaum - first_name: Jack full_name: Merrin, Jack id: 4515C308-F248-11E8-B48F-1D18A9856A87 last_name: Merrin orcid: 0000-0001-5145-4609 - first_name: Tino full_name: Frank, Tino last_name: Frank - first_name: Robert full_name: Hauschild, Robert id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87 last_name: Hauschild orcid: 0000-0001-9843-3522 - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X - first_name: Savaş full_name: Tay, Savaş last_name: Tay - first_name: Michael K full_name: Sixt, Michael K id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87 last_name: Sixt orcid: 0000-0002-6620-9179 - first_name: Matthias full_name: Mehling, Matthias id: 3C23B994-F248-11E8-B48F-1D18A9856A87 last_name: Mehling orcid: 0000-0001-8599-1226 citation: 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 chicago: Schwarz, Jan, Veronika Bierbaum, Jack Merrin, Tino Frank, Robert Hauschild, Mark Tobias Bollenbach, Savaş Tay, Michael K Sixt, and Matthias Mehling. “A Microfluidic Device for Measuring Cell Migration towards Substrate Bound and Soluble Chemokine Gradients.” Scientific Reports. Nature Publishing Group, 2016. https://doi.org/10.1038/srep36440. ieee: J. Schwarz et al., “A microfluidic device for measuring cell migration towards substrate bound and soluble chemokine gradients,” Scientific Reports, vol. 6. Nature Publishing Group, 2016. 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. 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. 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). date_created: 2018-12-11T11:50:27Z date_published: 2016-11-07T00:00:00Z date_updated: 2021-01-12T06:48:41Z day: '07' ddc: - '579' department: - _id: MiSi - _id: NanoFab - _id: Bio - _id: ToBo doi: 10.1038/srep36440 ec_funded: 1 file: - access_level: open_access content_type: application/pdf creator: system date_created: 2018-12-12T10:09:32Z date_updated: 2018-12-12T10:09:32Z file_id: '4756' file_name: IST-2017-744-v1+1_srep36440.pdf file_size: 2353456 relation: main_file file_date_updated: 2018-12-12T10:09:32Z has_accepted_license: '1' intvolume: ' 6' language: - iso: eng month: '11' oa: 1 oa_version: Published Version project: - _id: 25A603A2-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '281556' name: Cytoskeletal force generation and force transduction of migrating leukocytes (EU) - _id: 25A8E5EA-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Y 564-B12 name: Cytoskeletal force generation and transduction of leukocytes (FWF) publication: Scientific Reports publication_status: published publisher: Nature Publishing Group publist_id: '6204' pubrep_id: '744' quality_controlled: '1' scopus_import: 1 status: public title: A microfluidic device for measuring cell migration towards substrate bound and soluble chemokine gradients tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 6 year: '2016' ... --- _id: '1218' 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. 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." author: - first_name: Andreas full_name: Angermayr, Andreas id: 4677C796-F248-11E8-B48F-1D18A9856A87 last_name: Angermayr orcid: 0000-0001-8619-2223 - first_name: Pascal full_name: Van Alphen, Pascal last_name: Van Alphen - first_name: Dicle full_name: Hasdemir, Dicle last_name: Hasdemir - first_name: Gertjan full_name: Kramer, Gertjan last_name: Kramer - first_name: Muzamal full_name: Iqbal, Muzamal last_name: Iqbal - first_name: Wilmar full_name: Van Grondelle, Wilmar last_name: Van Grondelle - first_name: Huub full_name: Hoefsloot, Huub last_name: Hoefsloot - first_name: Younghae full_name: Choi, Younghae last_name: Choi - first_name: Klaas full_name: Hellingwerf, Klaas last_name: Hellingwerf citation: 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 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 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. 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. 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. 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. date_created: 2018-12-11T11:50:46Z date_published: 2016-07-01T00:00:00Z date_updated: 2021-01-12T06:49:10Z day: '01' department: - _id: ToBo doi: 10.1128/AEM.00256-16 intvolume: ' 82' issue: '14' language: - iso: eng main_file_link: - open_access: '1' url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959195/ month: '07' oa: 1 oa_version: Submitted Version page: 4180 - 4189 publication: Applied and Environmental Microbiology publication_status: published publisher: American Society for Microbiology publist_id: '6117' quality_controlled: '1' scopus_import: 1 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 type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 82 year: '2016' ... --- _id: '1552' 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. 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." article_number: '20152452' author: - first_name: Qin full_name: Qi, Qin id: 3B22D412-F248-11E8-B48F-1D18A9856A87 last_name: Qi orcid: 0000-0002-6148-2416 - first_name: Macarena full_name: Toll Riera, Macarena last_name: Toll Riera - first_name: Karl full_name: Heilbron, Karl last_name: Heilbron - first_name: Gail full_name: Preston, Gail last_name: Preston - first_name: R Craig full_name: Maclean, R Craig last_name: Maclean citation: ama: Qi Q, Toll Riera M, Heilbron K, Preston G, Maclean RC. The genomic basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa. Proceedings of the Royal Society of London Series B Biological Sciences. 2016;283(1822). doi:10.1098/rspb.2015.2452 apa: Qi, Q., Toll Riera, M., Heilbron, K., Preston, G., & Maclean, R. C. (2016). The genomic basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa. Proceedings of the Royal Society of London Series B Biological Sciences. Royal Society, The. https://doi.org/10.1098/rspb.2015.2452 chicago: Qi, Qin, Macarena Toll Riera, Karl Heilbron, Gail Preston, and R Craig Maclean. “The Genomic Basis of Adaptation to the Fitness Cost of Rifampicin Resistance in Pseudomonas Aeruginosa.” Proceedings of the Royal Society of London Series B Biological Sciences. Royal Society, The, 2016. https://doi.org/10.1098/rspb.2015.2452. 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. 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. 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). date_created: 2018-12-11T11:52:40Z date_published: 2016-01-13T00:00:00Z date_updated: 2021-01-12T06:51:33Z day: '13' ddc: - '570' department: - _id: ToBo doi: 10.1098/rspb.2015.2452 file: - access_level: open_access checksum: 78ffe70c1c88af3856d31ca6b7195a27 content_type: application/pdf creator: system date_created: 2018-12-12T10:11:43Z date_updated: 2020-07-14T12:45:02Z file_id: '4899' file_name: IST-2016-488-v1+1_20152452.full.pdf file_size: 626804 relation: main_file file_date_updated: 2020-07-14T12:45:02Z has_accepted_license: '1' intvolume: ' 283' issue: '1822' language: - iso: eng month: '01' oa: 1 oa_version: Published Version publication: Proceedings of the Royal Society of London Series B Biological Sciences publication_status: published publisher: Royal Society, The publist_id: '5619' pubrep_id: '488' quality_controlled: '1' scopus_import: 1 status: public title: The genomic basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 283 year: '2016' ... --- _id: '5556' abstract: - lang: eng 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" article_processing_charge: No author: - first_name: Martin full_name: Lukacisin, Martin id: 298FFE8C-F248-11E8-B48F-1D18A9856A87 last_name: Lukacisin orcid: 0000-0001-6549-4177 - first_name: Matthieu full_name: Landon, Matthieu last_name: Landon - first_name: Rishi full_name: Jajoo, Rishi last_name: Jajoo 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 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 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. 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. 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. 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. short: M. Lukacisin, M. Landon, R. Jajoo, (2016). datarep_id: '45' date_created: 2018-12-12T12:31:31Z date_published: 2016-08-25T00:00:00Z date_updated: 2024-02-21T13:51:53Z day: '25' ddc: - '571' department: - _id: ToBo doi: 10.15479/AT:ISTA:45 file: - access_level: open_access checksum: ee697f2b1ade4dc14d6ac0334dd832ab content_type: application/zip creator: system date_created: 2018-12-12T13:02:58Z date_updated: 2020-07-14T12:47:02Z file_id: '5616' file_name: IST-2016-45-v1+1_PaperCode.zip file_size: 296722548 relation: main_file file_date_updated: 2020-07-14T12:47:02Z has_accepted_license: '1' keyword: - transcription - pausing - backtracking - polymerase - RNA - NET-seq - nucleosome - basepairing month: '08' oa: 1 oa_version: Published Version publisher: Institute of Science and Technology Austria related_material: record: - id: '8431' relation: used_in_publication status: deleted - id: '1029' relation: research_paper status: public status: public title: MATLAB analysis code for 'Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast' tmp: image: /images/cc_by_sa.png legal_code_url: https://creativecommons.org/licenses/by-sa/4.0/legalcode name: Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0) short: CC BY-SA (4.0) type: research_data user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2016' ... --- _id: '1571' 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. 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. author: - first_name: Marjon full_name: De Vos, Marjon id: 3111FFAC-F248-11E8-B48F-1D18A9856A87 last_name: De Vos - first_name: Alexandre full_name: Dawid, Alexandre last_name: Dawid - first_name: Vanda full_name: Šunderlíková, Vanda last_name: Šunderlíková - first_name: Sander full_name: Tans, Sander last_name: Tans 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 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 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. 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. ista: de Vos M, Dawid A, Šunderlíková V, Tans S. 2015. Breaking evolutionary constraint with a tradeoff ratchet. PNAS. 112(48), 14906–14911. 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. date_created: 2018-12-11T11:52:47Z date_published: 2015-12-01T00:00:00Z date_updated: 2021-01-12T06:51:40Z day: '01' department: - _id: ToBo doi: 10.1073/pnas.1510282112 intvolume: ' 112' issue: '48' language: - iso: eng month: '12' oa_version: None page: 14906 - 14911 publication: PNAS publication_status: published publisher: National Academy of Sciences publist_id: '5600' quality_controlled: '1' scopus_import: 1 status: public title: Breaking evolutionary constraint with a tradeoff ratchet type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 112 year: '2015' ... --- _id: '1581' 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. article_processing_charge: No author: - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X - first_name: Carl-Philipp J full_name: Heisenberg, Carl-Philipp J id: 39427864-F248-11E8-B48F-1D18A9856A87 last_name: Heisenberg orcid: 0000-0002-0912-4566 citation: ama: Bollenbach MT, Heisenberg C-PJ. Gradients are shaping up. Cell. 2015;161(3):431-432. doi:10.1016/j.cell.2015.04.009 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 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. ieee: M. T. Bollenbach and C.-P. J. Heisenberg, “Gradients are shaping up,” Cell, vol. 161, no. 3. Cell Press, pp. 431–432, 2015. ista: Bollenbach MT, Heisenberg C-PJ. 2015. Gradients are shaping up. Cell. 161(3), 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. short: M.T. Bollenbach, C.-P.J. Heisenberg, Cell 161 (2015) 431–432. date_created: 2018-12-11T11:52:50Z date_published: 2015-04-23T00:00:00Z date_updated: 2022-08-25T13:56:10Z day: '23' department: - _id: ToBo - _id: CaHe doi: 10.1016/j.cell.2015.04.009 intvolume: ' 161' issue: '3' language: - iso: eng month: '04' oa_version: None page: 431 - 432 publication: Cell publication_status: published publisher: Cell Press publist_id: '5590' quality_controlled: '1' scopus_import: '1' status: public title: Gradients are shaping up type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 161 year: '2015' ... --- _id: '1586' 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. author: - first_name: Andreas full_name: Angermayr, Andreas id: 4677C796-F248-11E8-B48F-1D18A9856A87 last_name: Angermayr orcid: 0000-0001-8619-2223 - first_name: Aleix full_name: Gorchs, Aleix last_name: Gorchs - first_name: Klaas full_name: Hellingwerf, Klaas last_name: Hellingwerf 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 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 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. 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. 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. 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. date_created: 2018-12-11T11:52:52Z date_published: 2015-06-01T00:00:00Z date_updated: 2021-01-12T06:51:46Z day: '01' department: - _id: ToBo doi: 10.1016/j.tibtech.2015.03.009 intvolume: ' 33' issue: '6' language: - iso: eng month: '06' oa_version: None page: 352 - 361 publication: Trends in Biotechnology publication_status: published publisher: Elsevier publist_id: '5585' quality_controlled: '1' scopus_import: 1 status: public title: Metabolic engineering of cyanobacteria for the synthesis of commodity products type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 33 year: '2015' ... --- _id: '1623' 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" article_number: '193' author: - first_name: Petter full_name: Hammar, Petter last_name: Hammar - first_name: Andreas full_name: Angermayr, Andreas id: 4677C796-F248-11E8-B48F-1D18A9856A87 last_name: Angermayr orcid: 0000-0001-8619-2223 - first_name: Staffan full_name: Sjostrom, Staffan last_name: Sjostrom - first_name: Josefin full_name: Van Der Meer, Josefin last_name: Van Der Meer - first_name: Klaas full_name: Hellingwerf, Klaas last_name: Hellingwerf - first_name: Elton full_name: Hudson, Elton last_name: Hudson - first_name: Hakaan full_name: Joensson, Hakaan last_name: Joensson citation: 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 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 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. 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. 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. 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). date_created: 2018-12-11T11:53:05Z date_published: 2015-11-25T00:00:00Z date_updated: 2021-01-12T06:52:04Z day: '25' ddc: - '570' department: - _id: ToBo doi: 10.1186/s13068-015-0380-2 file: - access_level: open_access checksum: 172b0b6f4eb2e5c22b7cec1d57dc0107 content_type: application/pdf creator: system date_created: 2018-12-12T10:10:11Z date_updated: 2020-07-14T12:45:07Z file_id: '4796' file_name: IST-2016-467-v1+1_s13068-015-0380-2.pdf file_size: 2914089 relation: main_file file_date_updated: 2020-07-14T12:45:07Z has_accepted_license: '1' intvolume: ' 8' issue: '1' language: - iso: eng month: '11' oa: 1 oa_version: Published Version publication: Biotechnology for Biofuels publication_status: published publisher: BioMed Central publist_id: '5537' pubrep_id: '467' quality_controlled: '1' scopus_import: 1 status: public title: Single-cell screening of photosynthetic growth and lactate production by cyanobacteria tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 8 year: '2015' ... --- _id: '1810' 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. author: - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X 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' 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' 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.' 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.' ista: 'Bollenbach MT. 2015. Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution. Current Opinion in Microbiology. 27, 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.' short: M.T. Bollenbach, Current Opinion in Microbiology 27 (2015) 1–9. date_created: 2018-12-11T11:54:08Z date_published: 2015-06-01T00:00:00Z date_updated: 2021-01-12T06:53:21Z day: '01' ddc: - '570' department: - _id: ToBo doi: 10.1016/j.mib.2015.05.008 ec_funded: 1 file: - access_level: open_access checksum: 1683bb0f42ef892a5b3b71a050d65d25 content_type: application/pdf creator: system date_created: 2018-12-12T10:17:23Z date_updated: 2020-07-14T12:45:17Z file_id: '5277' file_name: IST-2016-493-v1+1_1-s2.0-S1369527415000594-main.pdf file_size: 1047255 relation: main_file file_date_updated: 2020-07-14T12:45:17Z has_accepted_license: '1' intvolume: ' 27' language: - iso: eng month: '06' oa: 1 oa_version: Published Version page: 1 - 9 project: - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 25E83C2C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '303507' name: Optimality principles in responses to antibiotics - _id: 25EB3A80-B435-11E9-9278-68D0E5697425 grant_number: RGP0042/2013 name: Revealing the fundamental limits of cell growth publication: Current Opinion in Microbiology publication_status: published publisher: Elsevier publist_id: '5298' pubrep_id: '493' quality_controlled: '1' scopus_import: 1 status: public title: 'Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 27 year: '2015' ... --- _id: '1823' 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. article_number: '807' author: - first_name: Guillaume full_name: Chevereau, Guillaume id: 424D78A0-F248-11E8-B48F-1D18A9856A87 last_name: Chevereau - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: Chevereau G, Bollenbach MT. Systematic discovery of drug interaction mechanisms. Molecular Systems Biology. 2015;11(4). doi:10.15252/msb.20156098 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 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. 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. 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. short: G. Chevereau, M.T. Bollenbach, Molecular Systems Biology 11 (2015). date_created: 2018-12-11T11:54:12Z date_published: 2015-04-01T00:00:00Z date_updated: 2021-01-12T06:53:26Z day: '01' ddc: - '570' department: - _id: ToBo doi: 10.15252/msb.20156098 ec_funded: 1 file: - access_level: open_access checksum: 4289b518fbe2166682fb1a1ef9b405f3 content_type: application/pdf creator: system date_created: 2018-12-12T10:14:34Z date_updated: 2020-07-14T12:45:17Z file_id: '5087' file_name: IST-2015-395-v1+1_807.full.pdf file_size: 1273573 relation: main_file file_date_updated: 2020-07-14T12:45:17Z has_accepted_license: '1' intvolume: ' 11' issue: '4' language: - iso: eng month: '04' oa: 1 oa_version: Published Version project: - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 25EB3A80-B435-11E9-9278-68D0E5697425 grant_number: RGP0042/2013 name: Revealing the fundamental limits of cell growth - _id: 25E83C2C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '303507' name: Optimality principles in responses to antibiotics publication: Molecular Systems Biology publication_status: published publisher: Nature Publishing Group publist_id: '5283' pubrep_id: '395' quality_controlled: '1' scopus_import: 1 status: public title: Systematic discovery of drug interaction mechanisms tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 11 year: '2015' ... --- _id: '9711' article_processing_charge: No author: - first_name: Guillaume full_name: Chevereau, Guillaume id: 424D78A0-F248-11E8-B48F-1D18A9856A87 last_name: Chevereau - first_name: Marta full_name: Lukacisinova, Marta id: 4342E402-F248-11E8-B48F-1D18A9856A87 last_name: Lukacisinova orcid: 0000-0002-2519-8004 - first_name: Tugce full_name: Batur, Tugce last_name: Batur - first_name: Aysegul full_name: Guvenek, Aysegul last_name: Guvenek - first_name: Dilay Hazal full_name: Ayhan, Dilay Hazal last_name: Ayhan - first_name: Erdal full_name: Toprak, Erdal last_name: Toprak - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X 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 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 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. ieee: G. Chevereau et al., “Excel file containing the raw data for all figures.” Public Library of Science, 2015. 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. 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). date_created: 2021-07-23T11:53:50Z date_published: 2015-11-18T00:00:00Z date_updated: 2023-02-23T10:07:02Z day: '18' department: - _id: ToBo doi: 10.1371/journal.pbio.1002299.s001 month: '11' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '1619' relation: used_in_publication status: public status: public title: Excel file containing the raw data for all figures type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2015' ... --- _id: '9765' article_processing_charge: No author: - first_name: Guillaume full_name: Chevereau, Guillaume id: 424D78A0-F248-11E8-B48F-1D18A9856A87 last_name: Chevereau - first_name: Marta full_name: Lukacisinova, Marta id: 4342E402-F248-11E8-B48F-1D18A9856A87 last_name: Lukacisinova orcid: 0000-0002-2519-8004 - first_name: Tugce full_name: Batur, Tugce last_name: Batur - first_name: Aysegul full_name: Guvenek, Aysegul last_name: Guvenek - first_name: Dilay Hazal full_name: Ayhan, Dilay Hazal last_name: Ayhan - first_name: Erdal full_name: Toprak, Erdal last_name: Toprak - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: 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 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. 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. 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. short: G. Chevereau, M. Lukacisinova, T. Batur, A. Guvenek, D.H. Ayhan, E. Toprak, M.T. Bollenbach, (2015). date_created: 2021-08-03T07:05:16Z date_published: 2015-11-18T00:00:00Z date_updated: 2023-02-23T10:07:02Z day: '18' department: - _id: ToBo doi: 10.1371/journal.pbio.1002299.s008 month: '11' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '1619' relation: used_in_publication status: public status: public title: Gene ontology enrichment analysis for the most sensitive gene deletion strains for all drugs type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2015' ... --- _id: '1509' 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. 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" article_processing_charge: No author: - first_name: Jaroslav full_name: Michalko, Jaroslav id: 483727CA-F248-11E8-B48F-1D18A9856A87 last_name: Michalko - first_name: Marta full_name: Dravecka, Marta id: 4342E402-F248-11E8-B48F-1D18A9856A87 last_name: Dravecka orcid: 0000-0002-2519-8004 - first_name: Tobias full_name: Bollenbach, Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X - first_name: Jirí full_name: Friml, Jirí id: 4159519E-F248-11E8-B48F-1D18A9856A87 last_name: Friml orcid: 0000-0002-8302-7596 citation: 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 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 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. 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. 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. 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). date_created: 2018-12-11T11:52:26Z date_published: 2015-10-01T00:00:00Z date_updated: 2023-10-10T14:10:24Z day: '01' ddc: - '570' department: - _id: JiFr - _id: ToBo doi: 10.12688/f1000research.7143.1 ec_funded: 1 file: - access_level: open_access checksum: 8beae5cbe988e1060265ae7de2ee8306 content_type: application/pdf creator: system date_created: 2018-12-12T10:16:12Z date_updated: 2020-07-14T12:44:59Z file_id: '5198' file_name: IST-2016-497-v1+1_10.12688_f1000research.7143.1_20151102.pdf file_size: 4414248 relation: main_file file_date_updated: 2020-07-14T12:44:59Z has_accepted_license: '1' intvolume: ' 4' language: - iso: eng month: '10' oa: 1 oa_version: Published Version project: - _id: 25716A02-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '282300' name: Polarity and subcellular dynamics in plants publication: 'F1000 Research ' publication_status: published publisher: F1000 Research publist_id: '5668' pubrep_id: '497' quality_controlled: '1' scopus_import: '1' status: public title: Embryo-lethal phenotypes in early abp1 mutants are due to disruption of the neighboring BSM gene tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 4 year: '2015' ... --- _id: '1619' abstract: - lang: eng 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. article_number: e1002299 author: - first_name: Guillaume full_name: Chevereau, Guillaume id: 424D78A0-F248-11E8-B48F-1D18A9856A87 last_name: Chevereau - first_name: Marta full_name: Dravecka, Marta id: 4342E402-F248-11E8-B48F-1D18A9856A87 last_name: Dravecka orcid: 0000-0002-2519-8004 - first_name: Tugce full_name: Batur, Tugce last_name: Batur - first_name: Aysegul full_name: Guvenek, Aysegul last_name: Guvenek - first_name: Dilay full_name: Ayhan, Dilay last_name: Ayhan - first_name: Erdal full_name: Toprak, Erdal last_name: Toprak - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: 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 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 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. 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. 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. 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). date_created: 2018-12-11T11:53:04Z date_published: 2015-11-18T00:00:00Z date_updated: 2024-03-27T23:30:28Z day: '18' ddc: - '570' department: - _id: ToBo doi: 10.1371/journal.pbio.1002299 ec_funded: 1 file: - access_level: open_access checksum: 0e82e3279f50b15c6c170c042627802b content_type: application/pdf creator: system date_created: 2018-12-12T10:09:00Z date_updated: 2020-07-14T12:45:07Z file_id: '4723' file_name: IST-2016-468-v1+1_journal.pbio.1002299.pdf file_size: 1387760 relation: main_file file_date_updated: 2020-07-14T12:45:07Z has_accepted_license: '1' intvolume: ' 13' issue: '11' language: - iso: eng month: '11' oa: 1 oa_version: Published Version project: - _id: 25EB3A80-B435-11E9-9278-68D0E5697425 grant_number: RGP0042/2013 name: Revealing the fundamental limits of cell growth - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 25E83C2C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '303507' name: Optimality principles in responses to antibiotics publication: PLoS Biology publication_status: published publisher: Public Library of Science publist_id: '5547' pubrep_id: '468' quality_controlled: '1' related_material: record: - id: '9711' relation: research_data status: public - id: '9765' relation: research_data status: public - id: '6263' relation: dissertation_contains status: public scopus_import: 1 status: public title: Quantifying the determinants of evolutionary dynamics leading to drug resistance tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 13 year: '2015' ...