--- _id: '12478' abstract: - lang: eng text: In Gram negative bacteria, the multiple antibiotic resistance or mar operon, is known to control the expression of multi-drug efflux genes that protect bacteria from a wide range of drugs. As many different chemical compounds can induce this operon, identifying the parameters that govern the dynamics of its induction is crucial to better characterize the processes of tolerance and resistance. Most experiments have assumed that the properties of the mar transcriptional network can be inferred from population measurements. However, measurements from an asynchronous population of cells can mask underlying phenotypic variations of single cells. We monitored the activity of the mar promoter in single Escherichia coli cells in linear micro-colonies and established that the response to a steady level of inducer was most heterogeneous within individual colonies for an intermediate value of inducer. Specifically, sub-lineages defined by contiguous daughter-cells exhibited similar promoter activity, whereas activity was greatly variable between different sub-lineages. Specific sub-trees of uniform promoter activity persisted over several generations. Statistical analyses of the lineages suggest that the presence of these sub-trees is the signature of an inducible memory of the promoter state that is transmitted from mother to daughter cells. This single-cell study reveals that the degree of epigenetic inheritance changes as a function of inducer concentration, suggesting that phenotypic inheritance may be an inducible phenotype. acknowledgement: This work was supported by NIH P50 award P50GM081892-02 to the University of Chicago, a catalyst grant from the Chicago Biomedical Consortium with support from The Searle Funds at The Chicago Community Trust to PC, and a Yen Fellowship to CCG. MA was partially supported by PAPIIT-UNAM grant IN-11322. article_number: '1049255' article_processing_charge: Yes article_type: original author: - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: L full_name: Bruneaux, L last_name: Bruneaux - first_name: P full_name: Oikonomou, P last_name: Oikonomou - first_name: M full_name: Aldana, M last_name: Aldana - first_name: P full_name: Cluzel, P last_name: Cluzel citation: ama: Guet CC, Bruneaux L, Oikonomou P, Aldana M, Cluzel P. Monitoring lineages of growing and dividing bacteria reveals an inducible memory of mar operon expression. Frontiers in Microbiology. 2023;14. doi:10.3389/fmicb.2023.1049255 apa: Guet, C. C., Bruneaux, L., Oikonomou, P., Aldana, M., & Cluzel, P. (2023). Monitoring lineages of growing and dividing bacteria reveals an inducible memory of mar operon expression. Frontiers in Microbiology. Frontiers. https://doi.org/10.3389/fmicb.2023.1049255 chicago: Guet, Calin C, L Bruneaux, P Oikonomou, M Aldana, and P Cluzel. “Monitoring Lineages of Growing and Dividing Bacteria Reveals an Inducible Memory of Mar Operon Expression.” Frontiers in Microbiology. Frontiers, 2023. https://doi.org/10.3389/fmicb.2023.1049255. ieee: C. C. Guet, L. Bruneaux, P. Oikonomou, M. Aldana, and P. Cluzel, “Monitoring lineages of growing and dividing bacteria reveals an inducible memory of mar operon expression,” Frontiers in Microbiology, vol. 14. Frontiers, 2023. ista: Guet CC, Bruneaux L, Oikonomou P, Aldana M, Cluzel P. 2023. Monitoring lineages of growing and dividing bacteria reveals an inducible memory of mar operon expression. Frontiers in Microbiology. 14, 1049255. mla: Guet, Calin C., et al. “Monitoring Lineages of Growing and Dividing Bacteria Reveals an Inducible Memory of Mar Operon Expression.” Frontiers in Microbiology, vol. 14, 1049255, Frontiers, 2023, doi:10.3389/fmicb.2023.1049255. short: C.C. Guet, L. Bruneaux, P. Oikonomou, M. Aldana, P. Cluzel, Frontiers in Microbiology 14 (2023). date_created: 2023-02-02T08:13:28Z date_published: 2023-06-20T00:00:00Z date_updated: 2023-08-02T06:25:04Z day: '20' ddc: - '570' department: - _id: CaGu doi: 10.3389/fmicb.2023.1049255 external_id: isi: - '001030002600001' pmid: - '37485524' file: - access_level: open_access checksum: 7dd322347512afaa5daf72a0154f2f07 content_type: application/pdf creator: dernst date_created: 2023-07-31T07:16:34Z date_updated: 2023-07-31T07:16:34Z file_id: '13322' file_name: 2023_FrontiersMicrobiology_Guet.pdf file_size: 6452841 relation: main_file success: 1 file_date_updated: 2023-07-31T07:16:34Z has_accepted_license: '1' intvolume: ' 14' isi: 1 language: - iso: eng month: '06' oa: 1 oa_version: Published Version pmid: 1 publication: Frontiers in Microbiology publication_identifier: eissn: - 1664-302X publication_status: published publisher: Frontiers quality_controlled: '1' scopus_import: '1' status: public title: Monitoring lineages of growing and dividing bacteria reveals an inducible memory of mar operon expression 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: 14 year: '2023' ... --- _id: '10939' abstract: - lang: eng text: Understanding and characterising biochemical processes inside single cells requires experimental platforms that allow one to perturb and observe the dynamics of such processes as well as computational methods to build and parameterise models from the collected data. Recent progress with experimental platforms and optogenetics has made it possible to expose each cell in an experiment to an individualised input and automatically record cellular responses over days with fine time resolution. However, methods to infer parameters of stochastic kinetic models from single-cell longitudinal data have generally been developed under the assumption that experimental data is sparse and that responses of cells to at most a few different input perturbations can be observed. Here, we investigate and compare different approaches for calculating parameter likelihoods of single-cell longitudinal data based on approximations of the chemical master equation (CME) with a particular focus on coupling the linear noise approximation (LNA) or moment closure methods to a Kalman filter. We show that, as long as cells are measured sufficiently frequently, coupling the LNA to a Kalman filter allows one to accurately approximate likelihoods and to infer model parameters from data even in cases where the LNA provides poor approximations of the CME. Furthermore, the computational cost of filtering-based iterative likelihood evaluation scales advantageously in the number of measurement times and different input perturbations and is thus ideally suited for data obtained from modern experimental platforms. To demonstrate the practical usefulness of these results, we perform an experiment in which single cells, equipped with an optogenetic gene expression system, are exposed to various different light-input sequences and measured at several hundred time points and use parameter inference based on iterative likelihood evaluation to parameterise a stochastic model of the system. acknowledgement: We thank Virgile Andreani for useful discussions about the model and parameter inference. We thank Johan Paulsson and Jeffrey J Tabor for kind gifts of plasmids. R was supported by the ANR grant CyberCircuits (ANR-18-CE91-0002). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. article_number: e1009950 article_processing_charge: No article_type: original author: - first_name: Anđela full_name: Davidović, Anđela last_name: Davidović - first_name: Remy P full_name: Chait, Remy P id: 3464AE84-F248-11E8-B48F-1D18A9856A87 last_name: Chait orcid: 0000-0003-0876-3187 - first_name: Gregory full_name: Batt, Gregory last_name: Batt - first_name: Jakob full_name: Ruess, Jakob id: 4A245D00-F248-11E8-B48F-1D18A9856A87 last_name: Ruess orcid: 0000-0003-1615-3282 citation: ama: Davidović A, Chait RP, Batt G, Ruess J. Parameter inference for stochastic biochemical models from perturbation experiments parallelised at the single cell level. PLoS Computational Biology. 2022;18(3). doi:10.1371/journal.pcbi.1009950 apa: Davidović, A., Chait, R. P., Batt, G., & Ruess, J. (2022). Parameter inference for stochastic biochemical models from perturbation experiments parallelised at the single cell level. PLoS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1009950 chicago: Davidović, Anđela, Remy P Chait, Gregory Batt, and Jakob Ruess. “Parameter Inference for Stochastic Biochemical Models from Perturbation Experiments Parallelised at the Single Cell Level.” PLoS Computational Biology. Public Library of Science, 2022. https://doi.org/10.1371/journal.pcbi.1009950. ieee: A. Davidović, R. P. Chait, G. Batt, and J. Ruess, “Parameter inference for stochastic biochemical models from perturbation experiments parallelised at the single cell level,” PLoS Computational Biology, vol. 18, no. 3. Public Library of Science, 2022. ista: Davidović A, Chait RP, Batt G, Ruess J. 2022. Parameter inference for stochastic biochemical models from perturbation experiments parallelised at the single cell level. PLoS Computational Biology. 18(3), e1009950. mla: Davidović, Anđela, et al. “Parameter Inference for Stochastic Biochemical Models from Perturbation Experiments Parallelised at the Single Cell Level.” PLoS Computational Biology, vol. 18, no. 3, e1009950, Public Library of Science, 2022, doi:10.1371/journal.pcbi.1009950. short: A. Davidović, R.P. Chait, G. Batt, J. Ruess, PLoS Computational Biology 18 (2022). date_created: 2022-04-03T22:01:42Z date_published: 2022-03-18T00:00:00Z date_updated: 2022-04-04T10:21:53Z day: '18' ddc: - '570' - '000' department: - _id: CaGu doi: 10.1371/journal.pcbi.1009950 file: - access_level: open_access checksum: 458ef542761fb714ced214f240daf6b2 content_type: application/pdf creator: dernst date_created: 2022-04-04T10:14:39Z date_updated: 2022-04-04T10:14:39Z file_id: '10947' file_name: 2022_PLoSCompBio_Davidovic.pdf file_size: 2958642 relation: main_file success: 1 file_date_updated: 2022-04-04T10:14:39Z has_accepted_license: '1' intvolume: ' 18' issue: '3' language: - iso: eng month: '03' oa: 1 oa_version: Published Version publication: PLoS Computational Biology publication_identifier: eissn: - 1553-7358 issn: - 1553-734X publication_status: published publisher: Public Library of Science quality_controlled: '1' related_material: link: - relation: software url: https://gitlab.pasteur.fr/adavidov/inferencelnakf scopus_import: '1' status: public title: Parameter inference for stochastic biochemical models from perturbation experiments parallelised at the single cell level 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: 18 year: '2022' ... --- _id: '11713' abstract: - lang: eng text: "Objective: MazF is a sequence-specific endoribonuclease-toxin of the MazEF toxin–antitoxin system. MazF cleaves single-stranded ribonucleic acid (RNA) regions at adenine–cytosine–adenine (ACA) sequences in the bacterium Escherichia coli. The MazEF system has been used in various biotechnology and synthetic biology applications. In this study, we infer how ectopic mazF overexpression affects production of heterologous proteins. To this end, we quantified the levels of fluorescent proteins expressed in E. coli from reporters translated from the ACA-containing or ACA-less messenger RNAs (mRNAs). Additionally, we addressed the impact of the 5′-untranslated region of these reporter mRNAs under the same conditions by comparing expression from mRNAs that comprise (canonical mRNA) or lack this region (leaderless mRNA).\r\nResults: Flow cytometry analysis indicates that during mazF overexpression, fluorescent proteins are translated from the canonical as well as leaderless mRNAs. Our analysis further indicates that longer mazF overexpression generally increases the concentration of fluorescent proteins translated from ACA-less mRNAs, however it also substantially increases bacterial population heterogeneity. Finally, our results suggest that the strength and duration of mazF overexpression should be optimized for each experimental setup, to maximize the heterologous protein production and minimize the amount of phenotypic heterogeneity in bacterial populations, which is unfavorable in biotechnological processes." acknowledgement: "We acknowledge the Max Perutz Labs FACS Facility together with Thomas Sauer. NN is grateful to Călin C. Guet for his support.\r\nThis work was funded by the Elise Richter grant V738 of the Austrian Science Fund (FWF), and the FWF Lise Meitner grant M1697, to NN; and by the FWF grant P22249, FWF Special Research Program RNA-REG F43 (subproject F4316), and FWF doctoral program RNA Biology (W1207), to IM. Open access funding provided by the Austrian Science Fund." article_number: '173' article_processing_charge: No article_type: letter_note author: - first_name: Nela full_name: Nikolic, Nela id: 42D9CABC-F248-11E8-B48F-1D18A9856A87 last_name: Nikolic orcid: 0000-0001-9068-6090 - first_name: Martina full_name: Sauert, Martina last_name: Sauert - first_name: Tanino G. full_name: Albanese, Tanino G. last_name: Albanese - first_name: Isabella full_name: Moll, Isabella last_name: Moll citation: ama: Nikolic N, Sauert M, Albanese TG, Moll I. Quantifying heterologous gene expression during ectopic MazF production in Escherichia coli. BMC Research Notes. 2022;15. doi:10.1186/s13104-022-06061-9 apa: Nikolic, N., Sauert, M., Albanese, T. G., & Moll, I. (2022). Quantifying heterologous gene expression during ectopic MazF production in Escherichia coli. BMC Research Notes. Springer Nature. https://doi.org/10.1186/s13104-022-06061-9 chicago: Nikolic, Nela, Martina Sauert, Tanino G. Albanese, and Isabella Moll. “Quantifying Heterologous Gene Expression during Ectopic MazF Production in Escherichia Coli.” BMC Research Notes. Springer Nature, 2022. https://doi.org/10.1186/s13104-022-06061-9. ieee: N. Nikolic, M. Sauert, T. G. Albanese, and I. Moll, “Quantifying heterologous gene expression during ectopic MazF production in Escherichia coli,” BMC Research Notes, vol. 15. Springer Nature, 2022. ista: Nikolic N, Sauert M, Albanese TG, Moll I. 2022. Quantifying heterologous gene expression during ectopic MazF production in Escherichia coli. BMC Research Notes. 15, 173. mla: Nikolic, Nela, et al. “Quantifying Heterologous Gene Expression during Ectopic MazF Production in Escherichia Coli.” BMC Research Notes, vol. 15, 173, Springer Nature, 2022, doi:10.1186/s13104-022-06061-9. short: N. Nikolic, M. Sauert, T.G. Albanese, I. Moll, BMC Research Notes 15 (2022). date_created: 2022-08-01T09:04:27Z date_published: 2022-05-13T00:00:00Z date_updated: 2022-08-01T09:27:40Z day: '13' ddc: - '570' department: - _id: CaGu doi: 10.1186/s13104-022-06061-9 external_id: pmid: - '35562780' file: - access_level: open_access checksum: 008156e5340e9789f0f6d82bde4d347a content_type: application/pdf creator: dernst date_created: 2022-08-01T09:24:42Z date_updated: 2022-08-01T09:24:42Z file_id: '11714' file_name: 2022_BMCResearchNotes_Nikolic.pdf file_size: 1545310 relation: main_file success: 1 file_date_updated: 2022-08-01T09:24:42Z has_accepted_license: '1' intvolume: ' 15' keyword: - General Biochemistry - Genetics and Molecular Biology - General Medicine language: - iso: eng month: '05' oa: 1 oa_version: Published Version pmid: 1 project: - _id: 26956E74-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: V00738 name: Bacterial toxin-antitoxin systems as antiphage defense mechanisms publication: BMC Research Notes publication_identifier: issn: - 1756-0500 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: link: - relation: erratum url: https://doi.org/10.1186/s13104-022-06152-7 scopus_import: '1' status: public title: Quantifying heterologous gene expression during ectopic MazF production in Escherichia coli 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: 15 year: '2022' ... --- _id: '10736' abstract: - lang: eng text: Predicting function from sequence is a central problem of biology. Currently, this is possible only locally in a narrow mutational neighborhood around a wildtype sequence rather than globally from any sequence. Using random mutant libraries, we developed a biophysical model that accounts for multiple features of σ70 binding bacterial promoters to predict constitutive gene expression levels from any sequence. We experimentally and theoretically estimated that 10–20% of random sequences lead to expression and ~80% of non-expressing sequences are one mutation away from a functional promoter. The potential for generating expression from random sequences is so pervasive that selection acts against σ70-RNA polymerase binding sites even within inter-genic, promoter-containing regions. This pervasiveness of σ70-binding sites implies that emergence of promoters is not the limiting step in gene regulatory evolution. Ultimately, the inclusion of novel features of promoter function into a mechanistic model enabled not only more accurate predictions of gene expression levels, but also identified that promoters evolve more rapidly than previously thought. acknowledgement: 'We thank Hande Acar, Nicholas H Barton, Rok Grah, Tiago Paixao, Maros Pleska, Anna Staron, and Murat Tugrul for insightful comments and input on the manuscript. This work was supported by: Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (grant number 216779/Z/19/Z) to ML; IPC Grant from IST Austria to ML and SS; European Research Council Funding Programme 7 (2007–2013, grant agreement number 648440) to JPB.' article_number: e64543 article_processing_charge: No article_type: original author: - first_name: Mato full_name: Lagator, Mato id: 345D25EC-F248-11E8-B48F-1D18A9856A87 last_name: Lagator - first_name: Srdjan full_name: Sarikas, Srdjan id: 35F0286E-F248-11E8-B48F-1D18A9856A87 last_name: Sarikas - first_name: Magdalena full_name: Steinrueck, Magdalena last_name: Steinrueck - first_name: David full_name: Toledo-Aparicio, David last_name: Toledo-Aparicio - first_name: Jonathan P full_name: Bollback, Jonathan P id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87 last_name: Bollback orcid: 0000-0002-4624-4612 - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: Gašper full_name: Tkačik, Gašper id: 3D494DCA-F248-11E8-B48F-1D18A9856A87 last_name: Tkačik orcid: 0000-0002-6699-1455 citation: ama: Lagator M, Sarikas S, Steinrueck M, et al. Predicting bacterial promoter function and evolution from random sequences. eLife. 2022;11. doi:10.7554/eLife.64543 apa: Lagator, M., Sarikas, S., Steinrueck, M., Toledo-Aparicio, D., Bollback, J. P., Guet, C. C., & Tkačik, G. (2022). Predicting bacterial promoter function and evolution from random sequences. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.64543 chicago: Lagator, Mato, Srdjan Sarikas, Magdalena Steinrueck, David Toledo-Aparicio, Jonathan P Bollback, Calin C Guet, and Gašper Tkačik. “Predicting Bacterial Promoter Function and Evolution from Random Sequences.” ELife. eLife Sciences Publications, 2022. https://doi.org/10.7554/eLife.64543. ieee: M. Lagator et al., “Predicting bacterial promoter function and evolution from random sequences,” eLife, vol. 11. eLife Sciences Publications, 2022. ista: Lagator M, Sarikas S, Steinrueck M, Toledo-Aparicio D, Bollback JP, Guet CC, Tkačik G. 2022. Predicting bacterial promoter function and evolution from random sequences. eLife. 11, e64543. mla: Lagator, Mato, et al. “Predicting Bacterial Promoter Function and Evolution from Random Sequences.” ELife, vol. 11, e64543, eLife Sciences Publications, 2022, doi:10.7554/eLife.64543. short: M. Lagator, S. Sarikas, M. Steinrueck, D. Toledo-Aparicio, J.P. Bollback, C.C. Guet, G. Tkačik, ELife 11 (2022). date_created: 2022-02-06T23:01:32Z date_published: 2022-01-26T00:00:00Z date_updated: 2023-08-02T14:09:02Z day: '26' ddc: - '576' department: - _id: CaGu - _id: GaTk - _id: NiBa doi: 10.7554/eLife.64543 ec_funded: 1 external_id: isi: - '000751104400001' pmid: - '35080492' file: - access_level: open_access checksum: decdcdf600ff51e9a9703b49ca114170 content_type: application/pdf creator: cchlebak date_created: 2022-02-07T07:14:09Z date_updated: 2022-02-07T07:14:09Z file_id: '10739' file_name: 2022_ELife_Lagator.pdf file_size: 5604343 relation: main_file success: 1 file_date_updated: 2022-02-07T07:14:09Z has_accepted_license: '1' intvolume: ' 11' isi: 1 language: - iso: eng month: '01' oa: 1 oa_version: Published Version pmid: 1 project: - _id: 2578D616-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '648440' name: Selective Barriers to Horizontal Gene Transfer publication: eLife publication_identifier: eissn: - 2050-084X publication_status: published publisher: eLife Sciences Publications quality_controlled: '1' scopus_import: '1' status: public title: Predicting bacterial promoter function and evolution from random sequences 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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 11 year: '2022' ... --- _id: '10812' abstract: - lang: eng text: Several promising strategies based on combining or cycling different antibiotics have been proposed to increase efficacy and counteract resistance evolution, but we still lack a deep understanding of the physiological responses and genetic mechanisms that underlie antibiotic interactions and the clinical applicability of these strategies. In antibiotic-exposed bacteria, the combined effects of physiological stress responses and emerging resistance mutations (occurring at different time scales) generate complex and often unpredictable dynamics. In this Review, we present our current understanding of bacterial cell physiology and genetics of responses to antibiotics. We emphasize recently discovered mechanisms of synergistic and antagonistic drug interactions, hysteresis in temporal interactions between antibiotics that arise from microbial physiology and interactions between antibiotics and resistance mutations that can cause collateral sensitivity or cross-resistance. We discuss possible connections between the different phenomena and indicate relevant research directions. A better and more unified understanding of drug and genetic interactions is likely to advance antibiotic therapy. acknowledgement: The authors thank B. Kavčič and H. Schulenburg for constructive feedback on the manuscript. article_processing_charge: No article_type: review author: - first_name: Roderich full_name: Römhild, Roderich id: 68E56E44-62B0-11EA-B963-444F3DDC885E last_name: Römhild orcid: 0000-0001-9480-5261 - 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: Dan I. full_name: Andersson, Dan I. last_name: Andersson citation: ama: Römhild R, Bollenbach MT, Andersson DI. The physiology and genetics of bacterial responses to antibiotic combinations. Nature Reviews Microbiology. 2022;20:478-490. doi:10.1038/s41579-022-00700-5 apa: Römhild, R., Bollenbach, M. T., & Andersson, D. I. (2022). The physiology and genetics of bacterial responses to antibiotic combinations. Nature Reviews Microbiology. Springer Nature. https://doi.org/10.1038/s41579-022-00700-5 chicago: Römhild, Roderich, Mark Tobias Bollenbach, and Dan I. Andersson. “The Physiology and Genetics of Bacterial Responses to Antibiotic Combinations.” Nature Reviews Microbiology. Springer Nature, 2022. https://doi.org/10.1038/s41579-022-00700-5. ieee: R. Römhild, M. T. Bollenbach, and D. I. Andersson, “The physiology and genetics of bacterial responses to antibiotic combinations,” Nature Reviews Microbiology, vol. 20. Springer Nature, pp. 478–490, 2022. ista: Römhild R, Bollenbach MT, Andersson DI. 2022. The physiology and genetics of bacterial responses to antibiotic combinations. Nature Reviews Microbiology. 20, 478–490. mla: Römhild, Roderich, et al. “The Physiology and Genetics of Bacterial Responses to Antibiotic Combinations.” Nature Reviews Microbiology, vol. 20, Springer Nature, 2022, pp. 478–90, doi:10.1038/s41579-022-00700-5. short: R. Römhild, M.T. Bollenbach, D.I. Andersson, Nature Reviews Microbiology 20 (2022) 478–490. date_created: 2022-03-04T04:33:49Z date_published: 2022-08-01T00:00:00Z date_updated: 2023-08-02T14:41:44Z day: '01' department: - _id: CaGu doi: 10.1038/s41579-022-00700-5 external_id: isi: - '000763891900001' pmid: - '35241807' intvolume: ' 20' isi: 1 keyword: - General Immunology and Microbiology - Microbiology - Infectious Diseases language: - iso: eng month: '08' oa_version: None page: 478-490 pmid: 1 publication: Nature Reviews Microbiology publication_identifier: eissn: - 1740-1534 issn: - 1740-1526 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: The physiology and genetics of bacterial responses to antibiotic combinations type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 20 year: '2022' ... --- _id: '11339' abstract: - lang: eng text: The interaction between a cell and its environment shapes fundamental intracellular processes such as cellular metabolism. In most cases growth rate is treated as a proximal metric for understanding the cellular metabolic status. However, changes in growth rate might not reflect metabolic variations in individuals responding to environmental fluctuations. Here we use single-cell microfluidics-microscopy combined with transcriptomics, proteomics and mathematical modelling to quantify the accumulation of glucose within Escherichia coli cells. In contrast to the current consensus, we reveal that environmental conditions which are comparatively unfavourable for growth, where both nutrients and salinity are depleted, increase glucose accumulation rates in individual bacteria and population subsets. We find that these changes in metabolic function are underpinned by variations at the translational and posttranslational level but not at the transcriptional level and are not dictated by changes in cell size. The metabolic response-characteristics identified greatly advance our fundamental understanding of the interactions between bacteria and their environment and have important ramifications when investigating cellular processes where salinity plays an important role. acknowledgement: G.G. was supported by an EPSRC DTP PhD studentship (EP/M506527/1). M.V. and K.T.A. gratefully acknowledge financial support from the EPSRC (EP/N014391/1). U.L. was supported through a BBSRC grant (BB/V008021/1) and an MRC Proximity to Discovery EXCITEME2 grant (MCPC17189). This work was further supported by a Royal Society Research Grant (RG180007) awarded to S.P. and a QUEX Initiator grant awarded to S.P. and K.T.A.. D.S.M., T.A.R. and S.P.’s work in this area is also supported by a Marie Skłodowska-Curie project SINGEK (H2020-MSCA-ITN-2015-675752) and the Gordon and Betty Moore Foundation Marine Microbiology Initiative (GBMF5514). B.M.I. acknowledges support from a Wellcome Trust Institutional Strategic Support Award to the University of Exeter (204909/Z/16/Z). This project utilised equipment funded by the Wellcome Trust Institutional Strategic Support Fund (WT097835MF), Wellcome Trust Multi User Equipment Award (WT101650MA) and BBSRC LOLA award (BB/K003240/1). article_number: '385' article_processing_charge: No article_type: original author: - first_name: Georgina full_name: Glover, Georgina last_name: Glover - first_name: Margaritis full_name: Voliotis, Margaritis last_name: Voliotis - first_name: Urszula full_name: Łapińska, Urszula last_name: Łapińska - first_name: Brandon M. full_name: Invergo, Brandon M. last_name: Invergo - first_name: Darren full_name: Soanes, Darren last_name: Soanes - first_name: Paul full_name: O’Neill, Paul last_name: O’Neill - first_name: Karen full_name: Moore, Karen last_name: Moore - first_name: Nela full_name: Nikolic, Nela id: 42D9CABC-F248-11E8-B48F-1D18A9856A87 last_name: Nikolic orcid: 0000-0001-9068-6090 - first_name: Peter full_name: Petrov, Peter last_name: Petrov - first_name: David S. full_name: Milner, David S. last_name: Milner - first_name: Sumita full_name: Roy, Sumita last_name: Roy - first_name: Kate full_name: Heesom, Kate last_name: Heesom - first_name: Thomas A. full_name: Richards, Thomas A. last_name: Richards - first_name: Krasimira full_name: Tsaneva-Atanasova, Krasimira last_name: Tsaneva-Atanasova - first_name: Stefano full_name: Pagliara, Stefano last_name: Pagliara citation: ama: Glover G, Voliotis M, Łapińska U, et al. Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells. Communications Biology. 2022;5. doi:10.1038/s42003-022-03336-6 apa: Glover, G., Voliotis, M., Łapińska, U., Invergo, B. M., Soanes, D., O’Neill, P., … Pagliara, S. (2022). Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells. Communications Biology. Springer Nature. https://doi.org/10.1038/s42003-022-03336-6 chicago: Glover, Georgina, Margaritis Voliotis, Urszula Łapińska, Brandon M. Invergo, Darren Soanes, Paul O’Neill, Karen Moore, et al. “Nutrient and Salt Depletion Synergistically Boosts Glucose Metabolism in Individual Escherichia Coli Cells.” Communications Biology. Springer Nature, 2022. https://doi.org/10.1038/s42003-022-03336-6. ieee: G. Glover et al., “Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells,” Communications Biology, vol. 5. Springer Nature, 2022. ista: Glover G, Voliotis M, Łapińska U, Invergo BM, Soanes D, O’Neill P, Moore K, Nikolic N, Petrov P, Milner DS, Roy S, Heesom K, Richards TA, Tsaneva-Atanasova K, Pagliara S. 2022. Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells. Communications Biology. 5, 385. mla: Glover, Georgina, et al. “Nutrient and Salt Depletion Synergistically Boosts Glucose Metabolism in Individual Escherichia Coli Cells.” Communications Biology, vol. 5, 385, Springer Nature, 2022, doi:10.1038/s42003-022-03336-6. short: G. Glover, M. Voliotis, U. Łapińska, B.M. Invergo, D. Soanes, P. O’Neill, K. Moore, N. Nikolic, P. Petrov, D.S. Milner, S. Roy, K. Heesom, T.A. Richards, K. Tsaneva-Atanasova, S. Pagliara, Communications Biology 5 (2022). date_created: 2022-05-01T22:01:41Z date_published: 2022-04-20T00:00:00Z date_updated: 2023-08-03T06:45:26Z day: '20' ddc: - '570' department: - _id: CaGu doi: 10.1038/s42003-022-03336-6 external_id: isi: - '000784143400001' pmid: - '35444215' file: - access_level: open_access checksum: 7c6f76ab17393d650825cc240edc84b3 content_type: application/pdf creator: dernst date_created: 2022-05-02T06:26:26Z date_updated: 2022-05-02T06:26:26Z file_id: '11342' file_name: 2022_CommBiology_Glover.pdf file_size: 2827723 relation: main_file success: 1 file_date_updated: 2022-05-02T06:26:26Z has_accepted_license: '1' intvolume: ' 5' isi: 1 language: - iso: eng month: '04' oa: 1 oa_version: Published Version pmid: 1 publication: Communications Biology publication_identifier: eissn: - 2399-3642 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Nutrient and salt depletion synergistically boosts glucose metabolism in individual Escherichia coli cells 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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 5 year: '2022' ... --- _id: '11843' abstract: - lang: eng text: A key attribute of persistent or recurring bacterial infections is the ability of the pathogen to evade the host’s immune response. Many Enterobacteriaceae express type 1 pili, a pre-adapted virulence trait, to invade host epithelial cells and establish persistent infections. However, the molecular mechanisms and strategies by which bacteria actively circumvent the immune response of the host remain poorly understood. Here, we identified CD14, the major co-receptor for lipopolysaccharide detection, on mouse dendritic cells (DCs) as a binding partner of FimH, the protein located at the tip of the type 1 pilus of Escherichia coli. The FimH amino acids involved in CD14 binding are highly conserved across pathogenic and non-pathogenic strains. Binding of the pathogenic strain CFT073 to CD14 reduced DC migration by overactivation of integrins and blunted expression of co-stimulatory molecules by overactivating the NFAT (nuclear factor of activated T-cells) pathway, both rate-limiting factors of T cell activation. This response was binary at the single-cell level, but averaged in larger populations exposed to both piliated and non-piliated pathogens, presumably via the exchange of immunomodulatory cytokines. While defining an active molecular mechanism of immune evasion by pathogens, the interaction between FimH and CD14 represents a potential target to interfere with persistent and recurrent infections, such as urinary tract infections or Crohn’s disease. acknowledged_ssus: - _id: Bio - _id: PreCl - _id: EM-Fac acknowledgement: We thank Ulrich Dobrindt for providing UPEC strains CFT073, UTI89, and 536, Frank Assen, Vlad Gavra, Maximilian Götz, Bor Kavčič, Jonna Alanko, and Eva Kiermaier for help with experiments and Robert Hauschild, Julian Stopp, and Saren Tasciyan for help with data analysis. We thank the IST Austria Scientific Service Units, especially the Bioimaging facility, the Preclinical facility and the Electron microscopy facility for technical support, Jakob Wallner and all members of the Guet and Sixt lab for fruitful discussions and Daria Siekhaus for critically reading the manuscript. This work was supported by grants from the Austrian Research Promotion Agency (FEMtech 868984) to IG, the European Research Council (CoG 724373), and the Austrian Science Fund (FWF P29911) to MS. article_number: e78995 article_processing_charge: Yes article_type: original author: - first_name: Kathrin full_name: Tomasek, Kathrin id: 3AEC8556-F248-11E8-B48F-1D18A9856A87 last_name: Tomasek - first_name: Alexander F full_name: Leithner, Alexander F id: 3B1B77E4-F248-11E8-B48F-1D18A9856A87 last_name: Leithner - first_name: Ivana full_name: Glatzová, Ivana id: 727b3c7d-4939-11ec-89b3-b9b0750ab74d last_name: Glatzová - first_name: Michael S. full_name: Lukesch, Michael S. last_name: Lukesch - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 - first_name: Michael K full_name: Sixt, Michael K id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87 last_name: Sixt orcid: 0000-0002-6620-9179 citation: ama: Tomasek K, Leithner AF, Glatzová I, Lukesch MS, Guet CC, Sixt MK. Type 1 piliated uropathogenic Escherichia coli hijack the host immune response by binding to CD14. eLife. 2022;11. doi:10.7554/eLife.78995 apa: Tomasek, K., Leithner, A. F., Glatzová, I., Lukesch, M. S., Guet, C. C., & Sixt, M. K. (2022). Type 1 piliated uropathogenic Escherichia coli hijack the host immune response by binding to CD14. ELife. eLife Sciences Publications. https://doi.org/10.7554/eLife.78995 chicago: Tomasek, Kathrin, Alexander F Leithner, Ivana Glatzová, Michael S. Lukesch, Calin C Guet, and Michael K Sixt. “Type 1 Piliated Uropathogenic Escherichia Coli Hijack the Host Immune Response by Binding to CD14.” ELife. eLife Sciences Publications, 2022. https://doi.org/10.7554/eLife.78995. ieee: K. Tomasek, A. F. Leithner, I. Glatzová, M. S. Lukesch, C. C. Guet, and M. K. Sixt, “Type 1 piliated uropathogenic Escherichia coli hijack the host immune response by binding to CD14,” eLife, vol. 11. eLife Sciences Publications, 2022. ista: Tomasek K, Leithner AF, Glatzová I, Lukesch MS, Guet CC, Sixt MK. 2022. Type 1 piliated uropathogenic Escherichia coli hijack the host immune response by binding to CD14. eLife. 11, e78995. mla: Tomasek, Kathrin, et al. “Type 1 Piliated Uropathogenic Escherichia Coli Hijack the Host Immune Response by Binding to CD14.” ELife, vol. 11, e78995, eLife Sciences Publications, 2022, doi:10.7554/eLife.78995. short: K. Tomasek, A.F. Leithner, I. Glatzová, M.S. Lukesch, C.C. Guet, M.K. Sixt, ELife 11 (2022). date_created: 2022-08-14T22:01:46Z date_published: 2022-07-26T00:00:00Z date_updated: 2023-08-03T12:54:21Z day: '26' ddc: - '570' department: - _id: MiSi - _id: CaGu doi: 10.7554/eLife.78995 ec_funded: 1 external_id: isi: - '000838410200001' file: - access_level: open_access checksum: 002a3c7c7ea5caa9af9cfbea308f6ea4 content_type: application/pdf creator: cchlebak date_created: 2022-08-16T08:57:37Z date_updated: 2022-08-16T08:57:37Z file_id: '11861' file_name: 2022_eLife_Tomasek.pdf file_size: 2057577 relation: main_file success: 1 file_date_updated: 2022-08-16T08:57:37Z has_accepted_license: '1' intvolume: ' 11' isi: 1 language: - iso: eng month: '07' oa: 1 oa_version: Published Version project: - _id: 25FE9508-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '724373' name: Cellular navigation along spatial gradients - _id: 26018E70-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P29911 name: Mechanical adaptation of lamellipodial actin publication: eLife publication_identifier: eissn: - 2050-084X publication_status: published publisher: eLife Sciences Publications quality_controlled: '1' related_material: record: - id: '10316' relation: earlier_version status: public scopus_import: '1' status: public title: Type 1 piliated uropathogenic Escherichia coli hijack the host immune response by binding to CD14 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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 11 year: '2022' ... --- _id: '12333' abstract: - lang: eng text: Together, copy-number and point mutations form the basis for most evolutionary novelty, through the process of gene duplication and divergence. While a plethora of genomic data reveals the long-term fate of diverging coding sequences and their cis-regulatory elements, little is known about the early dynamics around the duplication event itself. In microorganisms, selection for increased gene expression often drives the expansion of gene copy-number mutations, which serves as a crude adaptation, prior to divergence through refining point mutations. Using a simple synthetic genetic reporter system that can distinguish between copy-number and point mutations, we study their early and transient adaptive dynamics in real time in Escherichia coli. We find two qualitatively different routes of adaptation, depending on the level of functional improvement needed. In conditions of high gene expression demand, the two mutation types occur as a combination. However, under low gene expression demand, copy-number and point mutations are mutually exclusive; here, owing to their higher frequency, adaptation is dominated by copy-number mutations, in a process we term amplification hindrance. Ultimately, due to high reversal rates and pleiotropic cost, copy-number mutations may not only serve as a crude and transient adaptation, but also constrain sequence divergence over evolutionary time scales. acknowledgement: "We are grateful to N Barton, F Kondrashov, M Lagator, M Pleska, R Roemhild, D Siekhaus, and G\r\nTkacik for input on the manuscript and to K Tomasek for help with flow cytometry." article_number: e82240 article_processing_charge: No article_type: original author: - first_name: Isabella full_name: Tomanek, Isabella id: 3981F020-F248-11E8-B48F-1D18A9856A87 last_name: Tomanek orcid: 0000-0001-6197-363X - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: ama: Tomanek I, Guet CC. Adaptation dynamics between copynumber and point mutations. eLife. 2022;11. doi:10.7554/ELIFE.82240 apa: Tomanek, I., & Guet, C. C. (2022). Adaptation dynamics between copynumber and point mutations. ELife. eLife Sciences Publications. https://doi.org/10.7554/ELIFE.82240 chicago: Tomanek, Isabella, and Calin C Guet. “Adaptation Dynamics between Copynumber and Point Mutations.” ELife. eLife Sciences Publications, 2022. https://doi.org/10.7554/ELIFE.82240. ieee: I. Tomanek and C. C. Guet, “Adaptation dynamics between copynumber and point mutations,” eLife, vol. 11. eLife Sciences Publications, 2022. ista: Tomanek I, Guet CC. 2022. Adaptation dynamics between copynumber and point mutations. eLife. 11, e82240. mla: Tomanek, Isabella, and Calin C. Guet. “Adaptation Dynamics between Copynumber and Point Mutations.” ELife, vol. 11, e82240, eLife Sciences Publications, 2022, doi:10.7554/ELIFE.82240. short: I. Tomanek, C.C. Guet, ELife 11 (2022). date_created: 2023-01-22T23:00:55Z date_published: 2022-12-22T00:00:00Z date_updated: 2023-08-03T14:23:07Z day: '22' ddc: - '570' department: - _id: CaGu doi: 10.7554/ELIFE.82240 external_id: isi: - '000912674700001' file: - access_level: open_access checksum: 9321fd5f06ff59d5e2d33daee84b3da1 content_type: application/pdf creator: dernst date_created: 2023-01-23T08:56:21Z date_updated: 2023-01-23T08:56:21Z file_id: '12338' file_name: 2022_eLife_Tomanek.pdf file_size: 8835954 relation: main_file success: 1 file_date_updated: 2023-01-23T08:56:21Z has_accepted_license: '1' intvolume: ' 11' isi: 1 language: - iso: eng month: '12' oa: 1 oa_version: Published Version publication: eLife publication_identifier: eissn: - 2050-084X publication_status: published publisher: eLife Sciences Publications quality_controlled: '1' related_material: link: - relation: software url: https://doi.org/10.5281/zenodo.6974122 record: - id: '12339' relation: research_data status: public scopus_import: '1' status: public title: Adaptation dynamics between copynumber and point mutations 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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 11 year: '2022' ... --- _id: '12339' abstract: - lang: eng text: 'Copy-number and point mutations form the basis for most evolutionary novelty through the process of gene duplication and divergence. While a plethora of genomic sequence data reveals the long-term fate of diverging coding sequences and their cis-regulatory elements, little is known about the early dynamics around the duplication event itself. In microorganisms, selection for increased gene expression often drives the expansion of gene copy-number mutations, which serves as a crude adaptation, prior to divergence through refining point mutations. Using a simple synthetic genetic system that allows us to distinguish copy-number and point mutations, we study their early and transient adaptive dynamics in real-time in Escherichia coli. We find two qualitatively different routes of adaptation depending on the level of functional improvement selected for: In conditions of high gene expression demand, the two types of mutations occur as a combination. Under low gene expression demand, negative epistasis between the two types of mutations renders them mutually exclusive. Thus, owing to their higher frequency, adaptation is dominated by copy-number mutations. Ultimately, due to high rates of reversal and pleiotropic cost, copy-number mutations may not only serve as a crude and transient adaptation but also constrain sequence divergence over evolutionary time scales.' article_processing_charge: No author: - first_name: Isabella full_name: Tomanek, Isabella id: 3981F020-F248-11E8-B48F-1D18A9856A87 last_name: Tomanek orcid: 0000-0001-6197-363X - first_name: Calin C full_name: Guet, Calin C id: 47F8433E-F248-11E8-B48F-1D18A9856A87 last_name: Guet orcid: 0000-0001-6220-2052 citation: ama: Tomanek I, Guet CC. Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose. 2022. doi:10.5061/dryad.rfj6q57ds apa: Tomanek, I., & Guet, C. C. (2022). Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose. Dryad. https://doi.org/10.5061/dryad.rfj6q57ds chicago: Tomanek, Isabella, and Calin C Guet. “Flow Cytometry YFP and CFP Data and Deep Sequencing Data of Populations Evolving in Galactose.” Dryad, 2022. https://doi.org/10.5061/dryad.rfj6q57ds. ieee: I. Tomanek and C. C. Guet, “Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose.” Dryad, 2022. ista: Tomanek I, Guet CC. 2022. Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose, Dryad, 10.5061/dryad.rfj6q57ds. mla: Tomanek, Isabella, and Calin C. Guet. Flow Cytometry YFP and CFP Data and Deep Sequencing Data of Populations Evolving in Galactose. Dryad, 2022, doi:10.5061/dryad.rfj6q57ds. short: I. Tomanek, C.C. Guet, (2022). date_created: 2023-01-23T09:00:37Z date_published: 2022-12-23T00:00:00Z date_updated: 2023-08-03T14:23:06Z day: '23' ddc: - '570' department: - _id: CaGu doi: 10.5061/dryad.rfj6q57ds main_file_link: - open_access: '1' url: https://doi.org/10.5061/dryad.rfj6q57ds month: '12' oa: 1 oa_version: Published Version publisher: Dryad related_material: record: - id: '12333' relation: used_in_publication status: public status: public title: Flow cytometry YFP and CFP data and deep sequencing data of populations evolving in galactose type: research_data_reference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '9046' acknowledgement: Our work was supported by the Swedish Research Council (grant 2017-01527) to DIA article_number: e1009172 article_processing_charge: No article_type: original author: - first_name: Roderich full_name: Römhild, Roderich id: 68E56E44-62B0-11EA-B963-444F3DDC885E last_name: Römhild orcid: 0000-0001-9480-5261 - first_name: Dan I. full_name: Andersson, Dan I. last_name: Andersson citation: ama: Römhild R, Andersson DI. Mechanisms and therapeutic potential of collateral sensitivity to antibiotics. PLoS Pathogens. 2021;17(1). doi:10.1371/journal.ppat.1009172 apa: Römhild, R., & Andersson, D. I. (2021). Mechanisms and therapeutic potential of collateral sensitivity to antibiotics. PLoS Pathogens. Public Library of Science. https://doi.org/10.1371/journal.ppat.1009172 chicago: Römhild, Roderich, and Dan I. Andersson. “Mechanisms and Therapeutic Potential of Collateral Sensitivity to Antibiotics.” PLoS Pathogens. Public Library of Science, 2021. https://doi.org/10.1371/journal.ppat.1009172. ieee: R. Römhild and D. I. Andersson, “Mechanisms and therapeutic potential of collateral sensitivity to antibiotics,” PLoS Pathogens, vol. 17, no. 1. Public Library of Science, 2021. ista: Römhild R, Andersson DI. 2021. Mechanisms and therapeutic potential of collateral sensitivity to antibiotics. PLoS Pathogens. 17(1), e1009172. mla: Römhild, Roderich, and Dan I. Andersson. “Mechanisms and Therapeutic Potential of Collateral Sensitivity to Antibiotics.” PLoS Pathogens, vol. 17, no. 1, e1009172, Public Library of Science, 2021, doi:10.1371/journal.ppat.1009172. short: R. Römhild, D.I. Andersson, PLoS Pathogens 17 (2021). date_created: 2021-01-31T23:01:21Z date_published: 2021-01-14T00:00:00Z date_updated: 2023-08-07T13:36:55Z day: '14' ddc: - '570' department: - _id: CaGu doi: 10.1371/journal.ppat.1009172 external_id: isi: - '000610190400007' pmid: - '33444399' file: - access_level: open_access checksum: d745d7f8fcbb9b95fea16a36f94dee31 content_type: application/pdf creator: dernst date_created: 2021-02-03T12:13:03Z date_updated: 2021-02-03T12:13:03Z file_id: '9070' file_name: 2021_PlosPathogens_Roemhild.pdf file_size: 570066 relation: main_file success: 1 file_date_updated: 2021-02-03T12:13:03Z has_accepted_license: '1' intvolume: ' 17' isi: 1 issue: '1' language: - iso: eng month: '01' oa: 1 oa_version: Published Version pmid: 1 publication: PLoS Pathogens publication_identifier: eissn: - '15537374' issn: - '15537366' publication_status: published publisher: Public Library of Science quality_controlled: '1' scopus_import: '1' status: public title: Mechanisms and therapeutic potential of collateral sensitivity to antibiotics 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: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 17 year: '2021' ...