--- _id: '12261' abstract: - lang: eng text: 'Dose–response relationships are a general concept for quantitatively describing biological systems across multiple scales, from the molecular to the whole-cell level. A clinically relevant example is the bacterial growth response to antibiotics, which is routinely characterized by dose–response curves. The shape of the dose–response curve varies drastically between antibiotics and plays a key role in treatment, drug interactions, and resistance evolution. However, the mechanisms shaping the dose–response curve remain largely unclear. Here, we show in Escherichia coli that the distinctively shallow dose–response curve of the antibiotic trimethoprim is caused by a negative growth-mediated feedback loop: Trimethoprim slows growth, which in turn weakens the effect of this antibiotic. At the molecular level, this feedback is caused by the upregulation of the drug target dihydrofolate reductase (FolA/DHFR). We show that this upregulation is not a specific response to trimethoprim but follows a universal trend line that depends primarily on the growth rate, irrespective of its cause. Rewiring the feedback loop alters the dose–response curve in a predictable manner, which we corroborate using a mathematical model of cellular resource allocation and growth. Our results indicate that growth-mediated feedback loops may shape drug responses more generally and could be exploited to design evolutionary traps that enable selection against drug resistance.' acknowledged_ssus: - _id: M-Shop acknowledgement: This work was in part supported by Human Frontier Science Program GrantRGP0042/2013, Marie Curie Career Integration Grant303507, AustrianScience Fund (FWF) Grant P27201-B22, and German Research Foundation(DFG) Collaborative Research Center (SFB)1310to TB. SAA was supportedby the European Union’s Horizon2020Research and Innovation Programunder the Marie Skłodowska-Curie Grant agreement No707352. We wouldlike to thank the Bollenbach group for regular fruitful discussions. We areparticularly thankful for the technical assistance of Booshini Fernando andfor discussions of the theoretical aspects with Gerrit Ansmann. We areindebted to Bor Kavˇciˇc for invaluable advice, help with setting up theluciferase-based growth monitoring system, and for sharing plasmids. Weacknowledge the IST Austria Miba Machine Shop for their support inbuilding a housing for the stacker of the plate reader, which enabled thehigh-throughput luciferase-based experiments. We are grateful to RosalindAllen, Bor Kavˇciˇc and Dor Russ for feedback on the manuscript. Open Accessfunding enabled and organized by Projekt DEAL. article_number: e10490 article_processing_charge: No article_type: original author: - first_name: Andreas full_name: Angermayr, Andreas id: 4677C796-F248-11E8-B48F-1D18A9856A87 last_name: Angermayr orcid: 0000-0001-8619-2223 - first_name: Tin Yau full_name: Pang, Tin Yau last_name: Pang - first_name: Guillaume full_name: Chevereau, Guillaume last_name: Chevereau - first_name: Karin full_name: Mitosch, Karin id: 39B66846-F248-11E8-B48F-1D18A9856A87 last_name: Mitosch - first_name: Martin J full_name: Lercher, Martin J last_name: Lercher - 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: Angermayr A, Pang TY, Chevereau G, Mitosch K, Lercher MJ, Bollenbach MT. Growth‐mediated negative feedback shapes quantitative antibiotic response. Molecular Systems Biology. 2022;18(9). doi:10.15252/msb.202110490 apa: Angermayr, A., Pang, T. Y., Chevereau, G., Mitosch, K., Lercher, M. J., & Bollenbach, M. T. (2022). Growth‐mediated negative feedback shapes quantitative antibiotic response. Molecular Systems Biology. Embo Press. https://doi.org/10.15252/msb.202110490 chicago: Angermayr, Andreas, Tin Yau Pang, Guillaume Chevereau, Karin Mitosch, Martin J Lercher, and Mark Tobias Bollenbach. “Growth‐mediated Negative Feedback Shapes Quantitative Antibiotic Response.” Molecular Systems Biology. Embo Press, 2022. https://doi.org/10.15252/msb.202110490. ieee: A. Angermayr, T. Y. Pang, G. Chevereau, K. Mitosch, M. J. Lercher, and M. T. Bollenbach, “Growth‐mediated negative feedback shapes quantitative antibiotic response,” Molecular Systems Biology, vol. 18, no. 9. Embo Press, 2022. ista: Angermayr A, Pang TY, Chevereau G, Mitosch K, Lercher MJ, Bollenbach MT. 2022. Growth‐mediated negative feedback shapes quantitative antibiotic response. Molecular Systems Biology. 18(9), e10490. mla: Angermayr, Andreas, et al. “Growth‐mediated Negative Feedback Shapes Quantitative Antibiotic Response.” Molecular Systems Biology, vol. 18, no. 9, e10490, Embo Press, 2022, doi:10.15252/msb.202110490. short: A. Angermayr, T.Y. Pang, G. Chevereau, K. Mitosch, M.J. Lercher, M.T. Bollenbach, Molecular Systems Biology 18 (2022). date_created: 2023-01-16T09:58:34Z date_published: 2022-09-01T00:00:00Z date_updated: 2023-08-04T09:51:49Z day: '01' ddc: - '570' department: - _id: ToBo doi: 10.15252/msb.202110490 external_id: isi: - '000856482800001' file: - access_level: open_access checksum: 8b1d8f5ea20c8408acf466435fb6ae01 content_type: application/pdf creator: dernst date_created: 2023-01-30T09:49:55Z date_updated: 2023-01-30T09:49:55Z file_id: '12446' file_name: 2022_MolecularSystemsBio_Angermayr.pdf file_size: 1098812 relation: main_file success: 1 file_date_updated: 2023-01-30T09:49:55Z has_accepted_license: '1' intvolume: ' 18' isi: 1 issue: '9' keyword: - Applied Mathematics - Computational Theory and Mathematics - General Agricultural and Biological Sciences - General Immunology and Microbiology - General Biochemistry - Genetics and Molecular Biology - Information Systems language: - iso: eng month: '09' oa: 1 oa_version: Published Version publication: Molecular Systems Biology publication_identifier: eissn: - 1744-4292 publication_status: published publisher: Embo Press quality_controlled: '1' scopus_import: '1' status: public title: Growth‐mediated negative feedback shapes quantitative antibiotic response 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: 18 year: '2022' ... --- _id: '7026' abstract: - lang: eng text: Effective design of combination therapies requires understanding the changes in cell physiology that result from drug interactions. Here, we show that the genome-wide transcriptional response to combinations of two drugs, measured at a rigorously controlled growth rate, can predict higher-order antagonism with a third drug in Saccharomyces cerevisiae. Using isogrowth profiling, over 90% of the variation in cellular response can be decomposed into three principal components (PCs) that have clear biological interpretations. We demonstrate that the third PC captures emergent transcriptional programs that are dependent on both drugs and can predict antagonism with a third drug targeting the emergent pathway. We further show that emergent gene expression patterns are most pronounced at a drug ratio where the drug interaction is strongest, providing a guideline for future measurements. Our results provide a readily applicable recipe for uncovering emergent responses in other systems and for higher-order drug combinations. A record of this paper’s transparent peer review process is included in the Supplemental Information. acknowledged_ssus: - _id: LifeSc article_processing_charge: No article_type: original author: - first_name: Martin full_name: Lukacisin, Martin id: 298FFE8C-F248-11E8-B48F-1D18A9856A87 last_name: Lukacisin orcid: 0000-0001-6549-4177 - first_name: Tobias full_name: Bollenbach, Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: Lukacisin M, Bollenbach MT. Emergent gene expression responses to drug combinations predict higher-order drug interactions. Cell Systems. 2019;9(5):423-433.e1-e3. doi:10.1016/j.cels.2019.10.004 apa: Lukacisin, M., & Bollenbach, M. T. (2019). Emergent gene expression responses to drug combinations predict higher-order drug interactions. Cell Systems. Cell Press. https://doi.org/10.1016/j.cels.2019.10.004 chicago: Lukacisin, Martin, and Mark Tobias Bollenbach. “Emergent Gene Expression Responses to Drug Combinations Predict Higher-Order Drug Interactions.” Cell Systems. Cell Press, 2019. https://doi.org/10.1016/j.cels.2019.10.004. ieee: M. Lukacisin and M. T. Bollenbach, “Emergent gene expression responses to drug combinations predict higher-order drug interactions,” Cell Systems, vol. 9, no. 5. Cell Press, pp. 423-433.e1-e3, 2019. ista: Lukacisin M, Bollenbach MT. 2019. Emergent gene expression responses to drug combinations predict higher-order drug interactions. Cell Systems. 9(5), 423-433.e1-e3. mla: Lukacisin, Martin, and Mark Tobias Bollenbach. “Emergent Gene Expression Responses to Drug Combinations Predict Higher-Order Drug Interactions.” Cell Systems, vol. 9, no. 5, Cell Press, 2019, pp. 423-433.e1-e3, doi:10.1016/j.cels.2019.10.004. short: M. Lukacisin, M.T. Bollenbach, Cell Systems 9 (2019) 423-433.e1-e3. date_created: 2019-11-15T10:51:42Z date_published: 2019-11-27T00:00:00Z date_updated: 2023-08-30T07:24:58Z day: '27' ddc: - '570' department: - _id: ToBo doi: 10.1016/j.cels.2019.10.004 external_id: isi: - '000499495400003' file: - access_level: open_access checksum: 7a11d6c2f9523d65b049512d61733178 content_type: application/pdf creator: dernst date_created: 2019-11-15T10:57:42Z date_updated: 2020-07-14T12:47:48Z file_id: '7027' file_name: 2019_CellSystems_Lukacisin.pdf file_size: 4238460 relation: main_file file_date_updated: 2020-07-14T12:47:48Z has_accepted_license: '1' intvolume: ' 9' isi: 1 issue: '5' language: - iso: eng month: '11' oa: 1 oa_version: Published Version page: 423-433.e1-e3 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 publication: Cell Systems publication_identifier: issn: - 2405-4712 publication_status: published publisher: Cell Press quality_controlled: '1' scopus_import: '1' status: public title: Emergent gene expression responses to drug combinations predict higher-order drug interactions 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: 9 year: '2019' ... --- _id: '6392' abstract: - lang: eng text: "The regulation of gene expression is one of the most fundamental processes in living systems. In recent years, thanks to advances in sequencing technology and automation, it has become possible to study gene expression quantitatively, genome-wide and in high-throughput. This leads to the possibility of exploring changes in gene expression in the context of many external perturbations and their combinations, and thus of characterising the basic principles governing gene regulation. In this thesis, I present quantitative experimental approaches to studying transcriptional and protein level changes in response to combinatorial drug treatment, as well as a theoretical data-driven approach to analysing thermodynamic principles guiding transcription of protein coding genes. \r\nIn the first part of this work, I present a novel methodological framework for quantifying gene expression changes in drug combinations, termed isogrowth profiling. External perturbations through small molecule drugs influence the growth rate of the cell, leading to wide-ranging changes in cellular physiology and gene expression. This confounds the gene expression changes specifically elicited by the particular drug. Combinatorial perturbations, owing to the increased stress they exert, influence the growth rate even more strongly and hence suffer the convolution problem to a greater extent when measuring gene expression changes. Isogrowth profiling is a way to experimentally abstract non-specific, growth rate related changes, by performing the measurement using varying ratios of two drugs at such concentrations that the overall inhibition rate is constant. Using a robotic setup for automated high-throughput re-dilution culture of Saccharomyces cerevisiae, the budding yeast, I investigate all pairwise interactions of four small molecule drugs through sequencing RNA along a growth isobole. Through principal component analysis, I demonstrate here that isogrowth profiling can uncover drug-specific as well as drug-interaction-specific gene expression changes. I show that drug-interaction-specific gene expression changes can be used for prediction of higher-order drug interactions. I propose a simplified generalised framework of isogrowth profiling, with few measurements needed for each drug pair, enabling the broad application of isogrowth profiling to high-throughput screening of inhibitors of cellular growth and beyond. Such high-throughput screenings of gene expression changes specific to pairwise drug interactions will be instrumental for predicting the higher-order interactions of the drugs.\r\n\r\nIn the second part of this work, I extend isogrowth profiling to single-cell measurements of gene expression, characterising population heterogeneity in the budding yeast in response to combinatorial drug perturbation while controlling for non-specific growth rate effects. Through flow cytometry of strains with protein products fused to green fluorescent protein, I discover multiple proteins with bi-modally distributed expression levels in the population in response to drug treatment. I characterize more closely the effect of an ionic stressor, lithium chloride, and find that it inhibits the splicing of mRNA, most strongly affecting ribosomal protein transcripts and leading to a bi-stable behaviour of a small ribosomal subunit protein Rps22B. Time-lapse microscopy of a microfluidic culture system revealed that the induced Rps22B heterogeneity leads to preferential survival of Rps22B-low cells after long starvation, but to preferential proliferation of Rps22B-high cells after short starvation. Overall, this suggests that yeast cells might use splicing of ribosomal genes for bet-hedging in fluctuating environments. I give specific examples of how further exploration of cellular heterogeneity in yeast in response to external perturbation has the potential to reveal yet-undiscovered gene regulation circuitry.\r\n\r\nIn the last part of this thesis, a re-analysis of a published sequencing dataset of nascent elongating transcripts is used to characterise the thermodynamic constraints for RNA polymerase II (RNAP) elongation. Population-level data on RNAP position throughout the transcribed genome with single nucleotide resolution are used to infer the sequence specific thermodynamic determinants of RNAP pausing and backtracking. This analysis reveals that the basepairing strength of the eight nucleotide-long RNA:DNA duplex relative to the basepairing strength of the same sequence when in DNA:DNA duplex, and the change in this quantity during RNA polymerase movement, is the key determinant of RNAP pausing. This is true for RNAP pausing while elongating, but also of RNAP pausing while backtracking and of the backtracking length. The quantitative dependence of RNAP pausing on basepairing energetics is used to infer the increase in pausing due to transcriptional mismatches, leading to a hypothesis that pervasive RNA polymerase II pausing is due to basepairing energetics, as an evolutionary cost for increased RNA polymerase II fidelity.\r\n\r\nThis work advances our understanding of the general principles governing gene expression, with the goal of making computational predictions of single-cell gene expression responses to combinatorial perturbations based on the individual perturbations possible. This ability would substantially facilitate the design of drug combination treatments and, in the long term, lead to our increased ability to more generally design targeted manipulations to any biological system. " acknowledged_ssus: - _id: LifeSc - _id: M-Shop - _id: Bio alternative_title: - IST Austria Thesis 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. Quantitative investigation of gene expression principles through combinatorial drug perturbation and theory. 2019. doi:10.15479/AT:ISTA:6392 apa: Lukacisin, M. (2019). Quantitative investigation of gene expression principles through combinatorial drug perturbation and theory. IST Austria. https://doi.org/10.15479/AT:ISTA:6392 chicago: Lukacisin, Martin. “Quantitative Investigation of Gene Expression Principles through Combinatorial Drug Perturbation and Theory.” IST Austria, 2019. https://doi.org/10.15479/AT:ISTA:6392. ieee: M. Lukacisin, “Quantitative investigation of gene expression principles through combinatorial drug perturbation and theory,” IST Austria, 2019. ista: Lukacisin M. 2019. Quantitative investigation of gene expression principles through combinatorial drug perturbation and theory. IST Austria. mla: Lukacisin, Martin. Quantitative Investigation of Gene Expression Principles through Combinatorial Drug Perturbation and Theory. IST Austria, 2019, doi:10.15479/AT:ISTA:6392. short: M. Lukacisin, Quantitative Investigation of Gene Expression Principles through Combinatorial Drug Perturbation and Theory, IST Austria, 2019. date_created: 2019-05-09T19:53:00Z date_published: 2019-05-09T00:00:00Z date_updated: 2023-09-22T09:19:41Z day: '09' ddc: - '570' department: - _id: ToBo doi: 10.15479/AT:ISTA:6392 extern: '1' file: - access_level: closed checksum: 829bda074444857c7935171237bb7c0c content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: mlukacisin date_created: 2019-05-10T13:51:49Z date_updated: 2020-07-14T12:47:29Z embargo_to: open_access file_id: '6409' file_name: Thesis_Draft_v3.4Final.docx file_size: 43740796 relation: hidden - access_level: open_access checksum: 56cb5e97f5f8fc41692401b53832d8e0 content_type: application/pdf creator: mlukacisin date_created: 2019-05-10T14:13:42Z date_updated: 2021-02-11T11:17:16Z embargo: 2020-04-17 file_id: '6410' file_name: Thesis_Draft_v3.4FinalA.pdf file_size: 35228388 relation: main_file file_date_updated: 2021-02-11T11:17:16Z has_accepted_license: '1' language: - iso: eng month: '05' oa: 1 oa_version: Published Version page: '103' publication_identifier: isbn: - 978-3-99078-001-5 issn: - 2663-337X publication_status: published publisher: IST Austria related_material: record: - id: '1029' relation: part_of_dissertation status: public status: public supervisor: - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X title: Quantitative investigation of gene expression principles through combinatorial drug perturbation and theory type: dissertation user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2019' ... --- _id: '6263' abstract: - lang: eng text: 'Antibiotic resistance can emerge spontaneously through genomic mutation and render treatment ineffective. To counteract this process, in addition to the discovery and description of resistance mechanisms,a deeper understanding of resistanceevolvabilityand its determinantsis needed. To address this challenge, this thesisuncoversnew genetic determinants of resistance evolvability using a customized robotic setup, exploressystematic ways in which resistance evolution is perturbed due to dose-responsecharacteristics of drugs and mutation rate differences,and mathematically investigates the evolutionary fate of one specific type of evolvability modifier -a stress-induced mutagenesis allele.We find severalgenes which strongly inhibit or potentiate resistance evolution. In order to identify them, we first developedan automated high-throughput feedback-controlled protocol whichkeeps the population size and selection pressure approximately constant for hundreds of cultures by dynamically re-diluting the cultures and adjusting the antibiotic concentration. We implementedthis protocol on a customized liquid handling robot and propagated 100 different gene deletion strains of Escherichia coliin triplicate for over 100 generations in tetracycline and in chloramphenicol, and comparedtheir adaptation rates.We find a diminishing returns pattern, where initially sensitive strains adapted more compared to less sensitive ones. Our data uncover that deletions of certain genes which do not affect mutation rate,including efflux pump components, a chaperone and severalstructural and regulatory genes can strongly and reproducibly alterresistance evolution. Sequencing analysis of evolved populations indicates that epistasis with resistance mutations is the most likelyexplanation. This work could inspire treatment strategies in which targeted inhibitors of evolvability mechanisms will be given alongside antibiotics to slow down resistance evolution and extend theefficacy of antibiotics.We implemented astochasticpopulation genetics model, toverifyways in which general properties, namely, dose-response characteristics of drugs and mutation rates, influence evolutionary dynamics. In particular, under the exposure to antibiotics with shallow dose-response curves,bacteria have narrower distributions of fitness effects of new mutations. We show that in silicothis also leads to slower resistance evolution. We see and confirm with experiments that increased mutation rates, apart from speeding up evolution, also leadto high reproducibility of phenotypic adaptation in a context of continually strong selection pressure.Knowledge of these patterns can aid in predicting the dynamics of antibiotic resistance evolutionand adapting treatment schemes accordingly.Focusing on a previously described type of evolvability modifier –a stress-induced mutagenesis allele –we find conditions under which it can persist in a population under periodic selectionakin to clinical treatment. We set up a deterministic infinite populationcontinuous time model tracking the frequencies of a mutator and resistance allele and evaluate various treatment schemes in how well they maintain a stress-induced mutator allele. In particular,a high diversity of stresses is crucial for the persistence of the mutator allele. This leads to a general trade-off where exactly those diversifying treatment schemes which are likely to decrease levels of resistance could lead to stronger selection of highly evolvable genotypes.In the long run, this work will lead to a deeper understanding of the genetic and cellular mechanisms involved in antibiotic resistance evolution and could inspire new strategies for slowing down its rate. ' acknowledged_ssus: - _id: M-Shop - _id: LifeSc alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Marta full_name: Lukacisinova, Marta id: 4342E402-F248-11E8-B48F-1D18A9856A87 last_name: Lukacisinova orcid: 0000-0002-2519-8004 citation: ama: Lukacisinova M. Genetic determinants of antibiotic resistance evolution. 2018. doi:10.15479/AT:ISTA:th1072 apa: Lukacisinova, M. (2018). Genetic determinants of antibiotic resistance evolution. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th1072 chicago: Lukacisinova, Marta. “Genetic Determinants of Antibiotic Resistance Evolution.” Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:th1072. ieee: M. Lukacisinova, “Genetic determinants of antibiotic resistance evolution,” Institute of Science and Technology Austria, 2018. ista: Lukacisinova M. 2018. Genetic determinants of antibiotic resistance evolution. Institute of Science and Technology Austria. mla: Lukacisinova, Marta. Genetic Determinants of Antibiotic Resistance Evolution. Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:th1072. short: M. Lukacisinova, Genetic Determinants of Antibiotic Resistance Evolution, Institute of Science and Technology Austria, 2018. date_created: 2019-04-09T13:57:15Z date_published: 2018-12-28T00:00:00Z date_updated: 2023-09-22T09:20:37Z day: '28' ddc: - '570' - '576' - '579' degree_awarded: PhD department: - _id: ToBo doi: 10.15479/AT:ISTA:th1072 file: - access_level: open_access checksum: fc60585c9eaad868ac007004ef130908 content_type: application/pdf creator: dernst date_created: 2019-04-09T13:49:24Z date_updated: 2021-02-11T11:17:17Z embargo: 2020-01-25 file_id: '6264' file_name: 2018_Thesis_Lukacisinova.pdf file_size: 5656866 relation: main_file - access_level: closed checksum: 264057ec0a92ab348cc83b41f021ba92 content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: dernst date_created: 2019-04-09T13:49:23Z date_updated: 2020-07-14T12:47:25Z embargo_to: open_access file_id: '6265' file_name: 2018_Thesis_Lukacisinova_source.docx file_size: 5168054 relation: source_file file_date_updated: 2021-02-11T11:17:17Z has_accepted_license: '1' language: - iso: eng month: '12' oa: 1 oa_version: Published Version page: '91' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '1619' relation: part_of_dissertation status: public - id: '696' relation: part_of_dissertation status: public - id: '1027' relation: part_of_dissertation status: public status: public supervisor: - first_name: Tobias full_name: Bollenbach, Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X title: Genetic determinants of antibiotic resistance evolution type: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2018' ... --- _id: '520' abstract: - lang: eng text: Cyanobacteria are mostly engineered to be sustainable cell-factories by genetic manipulations alone. Here, by modulating the concentration of allosteric effectors, we focus on increasing product formation without further burdening the cells with increased expression of enzymes. Resorting to a novel 96-well microplate cultivation system for cyanobacteria, and using lactate-producing strains of Synechocystis PCC6803 expressing different l-lactate dehydrogenases (LDH), we titrated the effect of 2,5-anhydro-mannitol supplementation. The latter acts in cells as a nonmetabolizable analogue of fructose 1,6-bisphosphate, a known allosteric regulator of one of the tested LDHs. In this strain (SAA023), we achieved over 2-fold increase of lactate productivity. Furthermore, we observed that as carbon is increasingly deviated during growth toward product formation, there is an increased fixation rate in the population of spontaneous mutants harboring an impaired production pathway. This is a challenge in the development of green cell factories, which may be countered by the incorporation in biotechnological processes of strategies such as the one pioneered here. article_type: letter_note author: - first_name: Wei full_name: Du, Wei last_name: Du - first_name: Andreas full_name: Angermayr, Andreas id: 4677C796-F248-11E8-B48F-1D18A9856A87 last_name: Angermayr orcid: 0000-0001-8619-2223 - first_name: Joeri full_name: Jongbloets, Joeri last_name: Jongbloets - first_name: Douwe full_name: Molenaar, Douwe last_name: Molenaar - first_name: Herwig full_name: Bachmann, Herwig last_name: Bachmann - first_name: Klaas full_name: Hellingwerf, Klaas last_name: Hellingwerf - first_name: Filipe full_name: Branco Dos Santos, Filipe last_name: Branco Dos Santos citation: ama: Du W, Angermayr A, Jongbloets J, et al. Nonhierarchical flux regulation exposes the fitness burden associated with lactate production in Synechocystis sp. PCC6803. ACS Synthetic Biology. 2017;6(3):395-401. doi:10.1021/acssynbio.6b00235 apa: Du, W., Angermayr, A., Jongbloets, J., Molenaar, D., Bachmann, H., Hellingwerf, K., & Branco Dos Santos, F. (2017). Nonhierarchical flux regulation exposes the fitness burden associated with lactate production in Synechocystis sp. PCC6803. ACS Synthetic Biology. American Chemical Society. https://doi.org/10.1021/acssynbio.6b00235 chicago: Du, Wei, Andreas Angermayr, Joeri Jongbloets, Douwe Molenaar, Herwig Bachmann, Klaas Hellingwerf, and Filipe Branco Dos Santos. “Nonhierarchical Flux Regulation Exposes the Fitness Burden Associated with Lactate Production in Synechocystis Sp. PCC6803.” ACS Synthetic Biology. American Chemical Society, 2017. https://doi.org/10.1021/acssynbio.6b00235. ieee: W. Du et al., “Nonhierarchical flux regulation exposes the fitness burden associated with lactate production in Synechocystis sp. PCC6803,” ACS Synthetic Biology, vol. 6, no. 3. American Chemical Society, pp. 395–401, 2017. ista: Du W, Angermayr A, Jongbloets J, Molenaar D, Bachmann H, Hellingwerf K, Branco Dos Santos F. 2017. Nonhierarchical flux regulation exposes the fitness burden associated with lactate production in Synechocystis sp. PCC6803. ACS Synthetic Biology. 6(3), 395–401. mla: Du, Wei, et al. “Nonhierarchical Flux Regulation Exposes the Fitness Burden Associated with Lactate Production in Synechocystis Sp. PCC6803.” ACS Synthetic Biology, vol. 6, no. 3, American Chemical Society, 2017, pp. 395–401, doi:10.1021/acssynbio.6b00235. short: W. Du, A. Angermayr, J. Jongbloets, D. Molenaar, H. Bachmann, K. Hellingwerf, F. Branco Dos Santos, ACS Synthetic Biology 6 (2017) 395–401. date_created: 2018-12-11T11:46:56Z date_published: 2017-03-17T00:00:00Z date_updated: 2021-01-12T08:01:21Z day: '17' department: - _id: ToBo doi: 10.1021/acssynbio.6b00235 external_id: pmid: - '27936615' intvolume: ' 6' issue: '3' language: - iso: eng month: '03' oa_version: None page: 395 - 401 pmid: 1 publication: ACS Synthetic Biology publication_identifier: issn: - '21615063' publication_status: published publisher: American Chemical Society publist_id: '7298' quality_controlled: '1' scopus_import: 1 status: public title: Nonhierarchical flux regulation exposes the fitness burden associated with lactate production in Synechocystis sp. PCC6803 type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 6 year: '2017' ... --- _id: '9849' abstract: - lang: eng text: This text provides additional information about the model, a derivation of the analytic results in Eq (4), and details about simulations of an additional parameter set. article_processing_charge: No 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 - 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. Modelling and simulation details. 2017. doi:10.1371/journal.pcbi.1005609.s001 apa: Lukacisinova, M., Novak, S., & Paixao, T. (2017). Modelling and simulation details. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005609.s001 chicago: Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Modelling and Simulation Details.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005609.s001. ieee: M. Lukacisinova, S. Novak, and T. Paixao, “Modelling and simulation details.” Public Library of Science, 2017. ista: Lukacisinova M, Novak S, Paixao T. 2017. Modelling and simulation details, Public Library of Science, 10.1371/journal.pcbi.1005609.s001. mla: Lukacisinova, Marta, et al. Modelling and Simulation Details. Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005609.s001. short: M. Lukacisinova, S. Novak, T. Paixao, (2017). date_created: 2021-08-09T14:02:34Z date_published: 2017-07-18T00:00:00Z date_updated: 2023-02-23T12:55:39Z day: '18' department: - _id: ToBo - _id: NiBa - _id: CaGu doi: 10.1371/journal.pcbi.1005609.s001 month: '07' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '696' relation: used_in_publication status: public status: public title: Modelling and simulation details type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2017' ... --- _id: '9850' abstract: - lang: eng text: In this text, we discuss how a cost of resistance and the possibility of lethal mutations impact our model. article_processing_charge: No 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 - 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. Extensions of the model. 2017. doi:10.1371/journal.pcbi.1005609.s002 apa: Lukacisinova, M., Novak, S., & Paixao, T. (2017). Extensions of the model. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005609.s002 chicago: Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Extensions of the Model.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005609.s002. ieee: M. Lukacisinova, S. Novak, and T. Paixao, “Extensions of the model.” Public Library of Science, 2017. ista: Lukacisinova M, Novak S, Paixao T. 2017. Extensions of the model, Public Library of Science, 10.1371/journal.pcbi.1005609.s002. mla: Lukacisinova, Marta, et al. Extensions of the Model. Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005609.s002. short: M. Lukacisinova, S. Novak, T. Paixao, (2017). date_created: 2021-08-09T14:05:24Z date_published: 2017-07-18T00:00:00Z date_updated: 2023-02-23T12:55:39Z day: '18' department: - _id: ToBo - _id: CaGu - _id: NiBa doi: 10.1371/journal.pcbi.1005609.s002 month: '07' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '696' relation: used_in_publication status: public status: public title: Extensions of the model type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2017' ... --- _id: '9851' abstract: - lang: eng text: Based on the intuitive derivation of the dynamics of SIM allele frequency pM in the main text, we present a heuristic prediction for the long-term SIM allele frequencies with χ > 1 stresses and compare it to numerical simulations. article_processing_charge: No 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 - 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. Heuristic prediction for multiple stresses. 2017. doi:10.1371/journal.pcbi.1005609.s003 apa: Lukacisinova, M., Novak, S., & Paixao, T. (2017). Heuristic prediction for multiple stresses. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005609.s003 chicago: Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Heuristic Prediction for Multiple Stresses.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005609.s003. ieee: M. Lukacisinova, S. Novak, and T. Paixao, “Heuristic prediction for multiple stresses.” Public Library of Science, 2017. ista: Lukacisinova M, Novak S, Paixao T. 2017. Heuristic prediction for multiple stresses, Public Library of Science, 10.1371/journal.pcbi.1005609.s003. mla: Lukacisinova, Marta, et al. Heuristic Prediction for Multiple Stresses. Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005609.s003. short: M. Lukacisinova, S. Novak, T. Paixao, (2017). date_created: 2021-08-09T14:08:14Z date_published: 2017-07-18T00:00:00Z date_updated: 2023-02-23T12:55:39Z day: '18' department: - _id: ToBo - _id: CaGu - _id: NiBa doi: 10.1371/journal.pcbi.1005609.s003 month: '07' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '696' relation: used_in_publication status: public status: public title: Heuristic prediction for multiple stresses type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2017' ... --- _id: '9852' abstract: - lang: eng text: We show how different combination strategies affect the fraction of individuals that are multi-resistant. article_processing_charge: No 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 - 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. Resistance frequencies for different combination strategies. 2017. doi:10.1371/journal.pcbi.1005609.s004 apa: Lukacisinova, M., Novak, S., & Paixao, T. (2017). Resistance frequencies for different combination strategies. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005609.s004 chicago: Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Resistance Frequencies for Different Combination Strategies.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005609.s004. ieee: M. Lukacisinova, S. Novak, and T. Paixao, “Resistance frequencies for different combination strategies.” Public Library of Science, 2017. ista: Lukacisinova M, Novak S, Paixao T. 2017. Resistance frequencies for different combination strategies, Public Library of Science, 10.1371/journal.pcbi.1005609.s004. mla: Lukacisinova, Marta, et al. Resistance Frequencies for Different Combination Strategies. Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005609.s004. short: M. Lukacisinova, S. Novak, T. Paixao, (2017). date_created: 2021-08-09T14:11:40Z date_published: 2017-07-18T00:00:00Z date_updated: 2023-02-23T12:55:39Z day: '18' department: - _id: ToBo - _id: CaGu - _id: NiBa doi: 10.1371/journal.pcbi.1005609.s004 month: '07' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '696' relation: used_in_publication status: public status: public title: Resistance frequencies for different combination strategies type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2017' ... --- _id: '818' abstract: - lang: eng text: 'Antibiotics have diverse effects on bacteria, including massive changes in bacterial gene expression. Whereas the gene expression changes under many antibiotics have been measured, the temporal organization of these responses and their dependence on the bacterial growth rate are unclear. As described in Chapter 1, we quantified the temporal gene expression changes in the bacterium Escherichia coli in response to the sudden exposure to antibiotics using a fluorescent reporter library and a robotic system. Our data show temporally structured gene expression responses, with response times for individual genes ranging from tens of minutes to several hours. We observed that many stress response genes were activated in response to antibiotics. As certain stress responses cross-protect bacteria from other stressors, we then asked whether cellular responses to antibiotics have a similar protective role in Chapter 2. Indeed, we found that the trimethoprim-induced acid stress response protects bacteria from subsequent acid stress. We combined microfluidics with time-lapse imaging to monitor survival, intracellular pH, and acid stress response in single cells. This approach revealed that the variable expression of the acid resistance operon gadBC strongly correlates with single-cell survival time. Cells with higher gadBC expression following trimethoprim maintain higher intracellular pH and survive the acid stress longer. Overall, we provide a way to identify single-cell cross-protection between antibiotics and environmental stressors from temporal gene expression data, and show how antibiotics can increase bacterial fitness in changing environments. While gene expression changes to antibiotics show a clear temporal structure at the population-level, it is unclear whether this clear temporal order is followed by every single cell. Using dual-reporter strains described in Chapter 3, we measured gene expression dynamics of promoter pairs in the same cells using microfluidics and microscopy. Chapter 4 shows that the oxidative stress response and the DNA stress response showed little timing variability and a clear temporal order under the antibiotic nitrofurantoin. In contrast, the acid stress response under trimethoprim ran independently from all other activated response programs including the DNA stress response, which showed particularly high timing variability in this stress condition. In summary, this approach provides insight into the temporal organization of gene expression programs at the single-cell level and suggests dependencies between response programs and the underlying variability-introducing mechanisms. Altogether, this work advances our understanding of the diverse effects that antibiotics have on bacteria. These results were obtained by taking into account gene expression dynamics, which allowed us to identify general principles, molecular mechanisms, and dependencies between genes. Our findings may have implications for infectious disease treatments, and microbial communities in the human body and in nature. ' acknowledgement: 'First of all, I would like to express great gratitude to my PhD supervisor Tobias Bollenbach. Through his open and trusting attitude I had the freedom to explore different scientific directions during this project, and follow the research lines of my interest. I am thankful for constructive and often extensive discussions and his support and commitment during the different stages of my PhD. I want to thank my committee members, Călin Guet, Terry Hwa and Nassos Typas for their interest and their valuable input to this project. Special thanks to Nassos for career guidance, and for accepting me in his lab. A big thank you goes to the past, present and affiliated members of the Bollenbach group: Guillaume Chevereau, Marjon de Vos, Marta Lukačišinová, Veronika Bierbaum, Qi Qin, Marcin Zagórski, Martin Lukačišin, Andreas Angermayr, Bor Kavčič, Julia Tischler, Dilay Ayhan, Jaroslav Ferenc, and Georg Rieckh. I enjoyed working and discussing with you very much and I will miss our lengthy group meetings, our inspiring journal clubs, and our common lunches. Special thanks to Bor for great mental and professional support during the hard months of thesis writing, and to Marta for very creative times during the beginning of our PhDs. May the ‘Bacterial Survival Guide’ decorate the walls of IST forever! A great thanks to my friend and collaborator Georg Rieckh for his enthusiasm and for getting so involved in these projects, for his endurance and for his company throughout the years. Thanks to the FriSBi crowd at IST Austria for interesting meetings and discussions. In particular I want to thank Magdalena Steinrück, and Anna Andersson for inspiring exchange, and enjoyable time together. Thanks to everybody who contributed to the cover for Cell Systems: The constructive input from Tobias Bollenbach, Bor Kavčič, Georg Rieckh, Marta Lukačišinová, and Sebastian Nozzi, and the professional implementation by the graphic designer Martina Markus from the University of Cologne. Thanks to all my office mates in the first floor Bertalanffy building throughout the years: for ensuring a pleasant working atmosphere, and for your company! In general, I want to thank all the people that make IST such a great environment, with the many possibilities to shape our own social and research environment. I want to thank my family for all kind of practical support during the years, and my second family in Argentina for their enthusiasm. Thanks to my brother Bernhard and my sister Martina for being great siblings, and to Helena and Valentin for the joy you brought to my life. My deep gratitude goes to Sebastian Nozzi, for constant support, patience, love and for believing in me. ' alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Karin full_name: Mitosch, Karin id: 39B66846-F248-11E8-B48F-1D18A9856A87 last_name: Mitosch citation: ama: Mitosch K. Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics. 2017. doi:10.15479/AT:ISTA:th_862 apa: Mitosch, K. (2017). Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th_862 chicago: Mitosch, Karin. “Timing, Variability and Cross-Protection in Bacteria – Insights from Dynamic Gene Expression Responses to Antibiotics.” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:th_862. ieee: K. Mitosch, “Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics,” Institute of Science and Technology Austria, 2017. ista: Mitosch K. 2017. Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses to antibiotics. Institute of Science and Technology Austria. mla: Mitosch, Karin. Timing, Variability and Cross-Protection in Bacteria – Insights from Dynamic Gene Expression Responses to Antibiotics. Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:th_862. short: K. Mitosch, Timing, Variability and Cross-Protection in Bacteria – Insights from Dynamic Gene Expression Responses to Antibiotics, Institute of Science and Technology Austria, 2017. date_created: 2018-12-11T11:48:40Z date_published: 2017-09-27T00:00:00Z date_updated: 2023-09-07T12:00:26Z day: '27' ddc: - '571' - '579' degree_awarded: PhD department: - _id: ToBo doi: 10.15479/AT:ISTA:th_862 file: - access_level: closed checksum: da3993c5f90f59a8e8623cc31ad501dd content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document creator: dernst date_created: 2019-04-05T08:48:51Z date_updated: 2020-07-14T12:48:09Z file_id: '6210' file_name: Thesis_KarinMitosch.docx file_size: 6331071 relation: source_file - access_level: open_access checksum: 24c3d9e51992f1b721f3df55aa13fcb8 content_type: application/pdf creator: dernst date_created: 2019-04-05T08:48:51Z date_updated: 2020-07-14T12:48:09Z file_id: '6211' file_name: Thesis_KarinMitosch.pdf file_size: 9289852 relation: main_file file_date_updated: 2020-07-14T12:48:09Z has_accepted_license: '1' language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: '113' publication_identifier: issn: - 2663-337X publication_status: published publisher: Institute of Science and Technology Austria publist_id: '6831' pubrep_id: '862' related_material: record: - id: '2001' relation: part_of_dissertation status: public - id: '666' relation: part_of_dissertation status: public status: public supervisor: - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X title: Timing, variability and cross-protection in bacteria – insights from dynamic gene expression responses 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: dissertation user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 year: '2017' ... --- _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 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' 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' ...