--- _id: '1586' abstract: - lang: eng text: Through metabolic engineering cyanobacteria can be employed in biotechnology. Combining the capacity for oxygenic photosynthesis and carbon fixation with an engineered metabolic pathway allows carbon-based product formation from CO2, light, and water directly. Such cyanobacterial 'cell factories' are constructed to produce biofuels, bioplastics, and commodity chemicals. Efforts of metabolic engineers and synthetic biologists allow the modification of the intermediary metabolism at various branching points, expanding the product range. The new biosynthesis routes 'tap' the metabolism ever more efficiently, particularly through the engineering of driving forces and utilization of cofactors generated during the light reactions of photosynthesis, resulting in higher product titers. High rates of carbon rechanneling ultimately allow an almost-complete allocation of fixed carbon to product above biomass. author: - first_name: Andreas full_name: Angermayr, Andreas id: 4677C796-F248-11E8-B48F-1D18A9856A87 last_name: Angermayr orcid: 0000-0001-8619-2223 - first_name: Aleix full_name: Gorchs, Aleix last_name: Gorchs - first_name: Klaas full_name: Hellingwerf, Klaas last_name: Hellingwerf citation: ama: Angermayr A, Gorchs A, Hellingwerf K. Metabolic engineering of cyanobacteria for the synthesis of commodity products. Trends in Biotechnology. 2015;33(6):352-361. doi:10.1016/j.tibtech.2015.03.009 apa: Angermayr, A., Gorchs, A., & Hellingwerf, K. (2015). Metabolic engineering of cyanobacteria for the synthesis of commodity products. Trends in Biotechnology. Elsevier. https://doi.org/10.1016/j.tibtech.2015.03.009 chicago: Angermayr, Andreas, Aleix Gorchs, and Klaas Hellingwerf. “Metabolic Engineering of Cyanobacteria for the Synthesis of Commodity Products.” Trends in Biotechnology. Elsevier, 2015. https://doi.org/10.1016/j.tibtech.2015.03.009. ieee: A. Angermayr, A. Gorchs, and K. Hellingwerf, “Metabolic engineering of cyanobacteria for the synthesis of commodity products,” Trends in Biotechnology, vol. 33, no. 6. Elsevier, pp. 352–361, 2015. ista: Angermayr A, Gorchs A, Hellingwerf K. 2015. Metabolic engineering of cyanobacteria for the synthesis of commodity products. Trends in Biotechnology. 33(6), 352–361. mla: Angermayr, Andreas, et al. “Metabolic Engineering of Cyanobacteria for the Synthesis of Commodity Products.” Trends in Biotechnology, vol. 33, no. 6, Elsevier, 2015, pp. 352–61, doi:10.1016/j.tibtech.2015.03.009. short: A. Angermayr, A. Gorchs, K. Hellingwerf, Trends in Biotechnology 33 (2015) 352–361. date_created: 2018-12-11T11:52:52Z date_published: 2015-06-01T00:00:00Z date_updated: 2021-01-12T06:51:46Z day: '01' department: - _id: ToBo doi: 10.1016/j.tibtech.2015.03.009 intvolume: ' 33' issue: '6' language: - iso: eng month: '06' oa_version: None page: 352 - 361 publication: Trends in Biotechnology publication_status: published publisher: Elsevier publist_id: '5585' quality_controlled: '1' scopus_import: 1 status: public title: Metabolic engineering of cyanobacteria for the synthesis of commodity products type: journal_article user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87 volume: 33 year: '2015' ... --- _id: '1623' abstract: - lang: eng text: "Background\r\nPhotosynthetic cyanobacteria are attractive for a range of biotechnological applications including biofuel production. However, due to slow growth, screening of mutant libraries using microtiter plates is not feasible.\r\nResults\r\nWe present a method for high-throughput, single-cell analysis and sorting of genetically engineered l-lactate-producing strains of Synechocystis sp. PCC6803. A microfluidic device is used to encapsulate single cells in picoliter droplets, assay the droplets for l-lactate production, and sort strains with high productivity. We demonstrate the separation of low- and high-producing reference strains, as well as enrichment of a more productive l-lactate-synthesizing population after UV-induced mutagenesis. The droplet platform also revealed population heterogeneity in photosynthetic growth and lactate production, as well as the presence of metabolically stalled cells.\r\nConclusions\r\nThe workflow will facilitate metabolic engineering and directed evolution studies and will be useful in studies of cyanobacteria biochemistry and physiology.\r\n" article_number: '193' author: - first_name: Petter full_name: Hammar, Petter last_name: Hammar - first_name: Andreas full_name: Angermayr, Andreas id: 4677C796-F248-11E8-B48F-1D18A9856A87 last_name: Angermayr orcid: 0000-0001-8619-2223 - first_name: Staffan full_name: Sjostrom, Staffan last_name: Sjostrom - first_name: Josefin full_name: Van Der Meer, Josefin last_name: Van Der Meer - first_name: Klaas full_name: Hellingwerf, Klaas last_name: Hellingwerf - first_name: Elton full_name: Hudson, Elton last_name: Hudson - first_name: Hakaan full_name: Joensson, Hakaan last_name: Joensson citation: ama: Hammar P, Angermayr A, Sjostrom S, et al. Single-cell screening of photosynthetic growth and lactate production by cyanobacteria. Biotechnology for Biofuels. 2015;8(1). doi:10.1186/s13068-015-0380-2 apa: Hammar, P., Angermayr, A., Sjostrom, S., Van Der Meer, J., Hellingwerf, K., Hudson, E., & Joensson, H. (2015). Single-cell screening of photosynthetic growth and lactate production by cyanobacteria. Biotechnology for Biofuels. BioMed Central. https://doi.org/10.1186/s13068-015-0380-2 chicago: Hammar, Petter, Andreas Angermayr, Staffan Sjostrom, Josefin Van Der Meer, Klaas Hellingwerf, Elton Hudson, and Hakaan Joensson. “Single-Cell Screening of Photosynthetic Growth and Lactate Production by Cyanobacteria.” Biotechnology for Biofuels. BioMed Central, 2015. https://doi.org/10.1186/s13068-015-0380-2. ieee: P. Hammar et al., “Single-cell screening of photosynthetic growth and lactate production by cyanobacteria,” Biotechnology for Biofuels, vol. 8, no. 1. BioMed Central, 2015. ista: Hammar P, Angermayr A, Sjostrom S, Van Der Meer J, Hellingwerf K, Hudson E, Joensson H. 2015. Single-cell screening of photosynthetic growth and lactate production by cyanobacteria. Biotechnology for Biofuels. 8(1), 193. mla: Hammar, Petter, et al. “Single-Cell Screening of Photosynthetic Growth and Lactate Production by Cyanobacteria.” Biotechnology for Biofuels, vol. 8, no. 1, 193, BioMed Central, 2015, doi:10.1186/s13068-015-0380-2. short: P. Hammar, A. Angermayr, S. Sjostrom, J. Van Der Meer, K. Hellingwerf, E. Hudson, H. Joensson, Biotechnology for Biofuels 8 (2015). date_created: 2018-12-11T11:53:05Z date_published: 2015-11-25T00:00:00Z date_updated: 2021-01-12T06:52:04Z day: '25' ddc: - '570' department: - _id: ToBo doi: 10.1186/s13068-015-0380-2 file: - access_level: open_access checksum: 172b0b6f4eb2e5c22b7cec1d57dc0107 content_type: application/pdf creator: system date_created: 2018-12-12T10:10:11Z date_updated: 2020-07-14T12:45:07Z file_id: '4796' file_name: IST-2016-467-v1+1_s13068-015-0380-2.pdf file_size: 2914089 relation: main_file file_date_updated: 2020-07-14T12:45:07Z has_accepted_license: '1' intvolume: ' 8' issue: '1' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '11' oa: 1 oa_version: Published Version publication: Biotechnology for Biofuels publication_status: published publisher: BioMed Central publist_id: '5537' pubrep_id: '467' quality_controlled: '1' scopus_import: 1 status: public title: Single-cell screening of photosynthetic growth and lactate production by cyanobacteria tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 8 year: '2015' ... --- _id: '1810' abstract: - lang: eng text: Combining antibiotics is a promising strategy for increasing treatment efficacy and for controlling resistance evolution. When drugs are combined, their effects on cells may be amplified or weakened, that is the drugs may show synergistic or antagonistic interactions. Recent work revealed the underlying mechanisms of such drug interactions by elucidating the drugs'; joint effects on cell physiology. Moreover, new treatment strategies that use drug combinations to exploit evolutionary tradeoffs were shown to affect the rate of resistance evolution in predictable ways. High throughput studies have further identified drug candidates based on their interactions with established antibiotics and general principles that enable the prediction of drug interactions were suggested. Overall, the conceptual and technical foundation for the rational design of potent drug combinations is rapidly developing. author: - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: 'Bollenbach MT. Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution. Current Opinion in Microbiology. 2015;27:1-9. doi:10.1016/j.mib.2015.05.008' apa: 'Bollenbach, M. T. (2015). Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution. Current Opinion in Microbiology. Elsevier. https://doi.org/10.1016/j.mib.2015.05.008' chicago: 'Bollenbach, Mark Tobias. “Antimicrobial Interactions: Mechanisms and Implications for Drug Discovery and Resistance Evolution.” Current Opinion in Microbiology. Elsevier, 2015. https://doi.org/10.1016/j.mib.2015.05.008.' ieee: 'M. T. Bollenbach, “Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution,” Current Opinion in Microbiology, vol. 27. Elsevier, pp. 1–9, 2015.' ista: 'Bollenbach MT. 2015. Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution. Current Opinion in Microbiology. 27, 1–9.' mla: 'Bollenbach, Mark Tobias. “Antimicrobial Interactions: Mechanisms and Implications for Drug Discovery and Resistance Evolution.” Current Opinion in Microbiology, vol. 27, Elsevier, 2015, pp. 1–9, doi:10.1016/j.mib.2015.05.008.' short: M.T. Bollenbach, Current Opinion in Microbiology 27 (2015) 1–9. date_created: 2018-12-11T11:54:08Z date_published: 2015-06-01T00:00:00Z date_updated: 2021-01-12T06:53:21Z day: '01' ddc: - '570' department: - _id: ToBo doi: 10.1016/j.mib.2015.05.008 ec_funded: 1 file: - access_level: open_access checksum: 1683bb0f42ef892a5b3b71a050d65d25 content_type: application/pdf creator: system date_created: 2018-12-12T10:17:23Z date_updated: 2020-07-14T12:45:17Z file_id: '5277' file_name: IST-2016-493-v1+1_1-s2.0-S1369527415000594-main.pdf file_size: 1047255 relation: main_file file_date_updated: 2020-07-14T12:45:17Z has_accepted_license: '1' intvolume: ' 27' language: - iso: eng month: '06' oa: 1 oa_version: Published Version page: 1 - 9 project: - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 25E83C2C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '303507' name: Optimality principles in responses to antibiotics - _id: 25EB3A80-B435-11E9-9278-68D0E5697425 grant_number: RGP0042/2013 name: Revealing the fundamental limits of cell growth publication: Current Opinion in Microbiology publication_status: published publisher: Elsevier publist_id: '5298' pubrep_id: '493' quality_controlled: '1' scopus_import: 1 status: public title: 'Antimicrobial interactions: Mechanisms and implications for drug discovery and resistance evolution' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 27 year: '2015' ... --- _id: '1823' abstract: - lang: eng text: Abstract Drug combinations are increasingly important in disease treatments, for combating drug resistance, and for elucidating fundamental relationships in cell physiology. When drugs are combined, their individual effects on cells may be amplified or weakened. Such drug interactions are crucial for treatment efficacy, but their underlying mechanisms remain largely unknown. To uncover the causes of drug interactions, we developed a systematic approach based on precise quantification of the individual and joint effects of antibiotics on growth of genome-wide Escherichia coli gene deletion strains. We found that drug interactions between antibiotics representing the main modes of action are highly robust to genetic perturbation. This robustness is encapsulated in a general principle of bacterial growth, which enables the quantitative prediction of mutant growth rates under drug combinations. Rare violations of this principle exposed recurring cellular functions controlling drug interactions. In particular, we found that polysaccharide and ATP synthesis control multiple drug interactions with previously unexplained mechanisms, and small molecule adjuvants targeting these functions synthetically reshape drug interactions in predictable ways. These results provide a new conceptual framework for the design of multidrug combinations and suggest that there are universal mechanisms at the heart of most drug interactions. Synopsis A general principle of bacterial growth enables the prediction of mutant growth rates under drug combinations. Rare violations of this principle expose cellular functions that control drug interactions and can be targeted by small molecules to alter drug interactions in predictable ways. Drug interactions between antibiotics are highly robust to genetic perturbations. A general principle of bacterial growth enables the prediction of mutant growth rates under drug combinations. Rare violations of this principle expose cellular functions that control drug interactions. Diverse drug interactions are controlled by recurring cellular functions, including LPS synthesis and ATP synthesis. A general principle of bacterial growth enables the prediction of mutant growth rates under drug combinations. Rare violations of this principle expose cellular functions that control drug interactions and can be targeted by small molecules to alter drug interactions in predictable ways. article_number: '807' author: - first_name: Guillaume full_name: Chevereau, Guillaume id: 424D78A0-F248-11E8-B48F-1D18A9856A87 last_name: Chevereau - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: Chevereau G, Bollenbach MT. Systematic discovery of drug interaction mechanisms. Molecular Systems Biology. 2015;11(4). doi:10.15252/msb.20156098 apa: Chevereau, G., & Bollenbach, M. T. (2015). Systematic discovery of drug interaction mechanisms. Molecular Systems Biology. Nature Publishing Group. https://doi.org/10.15252/msb.20156098 chicago: Chevereau, Guillaume, and Mark Tobias Bollenbach. “Systematic Discovery of Drug Interaction Mechanisms.” Molecular Systems Biology. Nature Publishing Group, 2015. https://doi.org/10.15252/msb.20156098. ieee: G. Chevereau and M. T. Bollenbach, “Systematic discovery of drug interaction mechanisms,” Molecular Systems Biology, vol. 11, no. 4. Nature Publishing Group, 2015. ista: Chevereau G, Bollenbach MT. 2015. Systematic discovery of drug interaction mechanisms. Molecular Systems Biology. 11(4), 807. mla: Chevereau, Guillaume, and Mark Tobias Bollenbach. “Systematic Discovery of Drug Interaction Mechanisms.” Molecular Systems Biology, vol. 11, no. 4, 807, Nature Publishing Group, 2015, doi:10.15252/msb.20156098. short: G. Chevereau, M.T. Bollenbach, Molecular Systems Biology 11 (2015). date_created: 2018-12-11T11:54:12Z date_published: 2015-04-01T00:00:00Z date_updated: 2021-01-12T06:53:26Z day: '01' ddc: - '570' department: - _id: ToBo doi: 10.15252/msb.20156098 ec_funded: 1 file: - access_level: open_access checksum: 4289b518fbe2166682fb1a1ef9b405f3 content_type: application/pdf creator: system date_created: 2018-12-12T10:14:34Z date_updated: 2020-07-14T12:45:17Z file_id: '5087' file_name: IST-2015-395-v1+1_807.full.pdf file_size: 1273573 relation: main_file file_date_updated: 2020-07-14T12:45:17Z has_accepted_license: '1' intvolume: ' 11' issue: '4' language: - iso: eng month: '04' oa: 1 oa_version: Published Version project: - _id: 25E9AF9E-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P27201-B22 name: Revealing the mechanisms underlying drug interactions - _id: 25EB3A80-B435-11E9-9278-68D0E5697425 grant_number: RGP0042/2013 name: Revealing the fundamental limits of cell growth - _id: 25E83C2C-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '303507' name: Optimality principles in responses to antibiotics publication: Molecular Systems Biology publication_status: published publisher: Nature Publishing Group publist_id: '5283' pubrep_id: '395' quality_controlled: '1' scopus_import: 1 status: public title: Systematic discovery of drug interaction mechanisms tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 11 year: '2015' ... --- _id: '9711' article_processing_charge: No author: - first_name: Guillaume full_name: Chevereau, Guillaume id: 424D78A0-F248-11E8-B48F-1D18A9856A87 last_name: Chevereau - first_name: Marta full_name: Lukacisinova, Marta id: 4342E402-F248-11E8-B48F-1D18A9856A87 last_name: Lukacisinova orcid: 0000-0002-2519-8004 - first_name: Tugce full_name: Batur, Tugce last_name: Batur - first_name: Aysegul full_name: Guvenek, Aysegul last_name: Guvenek - first_name: Dilay Hazal full_name: Ayhan, Dilay Hazal last_name: Ayhan - first_name: Erdal full_name: Toprak, Erdal last_name: Toprak - first_name: Mark Tobias full_name: Bollenbach, Mark Tobias id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87 last_name: Bollenbach orcid: 0000-0003-4398-476X citation: ama: Chevereau G, Lukacisinova M, Batur T, et al. Excel file containing the raw data for all figures. 2015. doi:10.1371/journal.pbio.1002299.s001 apa: Chevereau, G., Lukacisinova, M., Batur, T., Guvenek, A., Ayhan, D. H., Toprak, E., & Bollenbach, M. T. (2015). Excel file containing the raw data for all figures. Public Library of Science. https://doi.org/10.1371/journal.pbio.1002299.s001 chicago: Chevereau, Guillaume, Marta Lukacisinova, Tugce Batur, Aysegul Guvenek, Dilay Hazal Ayhan, Erdal Toprak, and Mark Tobias Bollenbach. “Excel File Containing the Raw Data for All Figures.” Public Library of Science, 2015. https://doi.org/10.1371/journal.pbio.1002299.s001. ieee: G. Chevereau et al., “Excel file containing the raw data for all figures.” Public Library of Science, 2015. ista: Chevereau G, Lukacisinova M, Batur T, Guvenek A, Ayhan DH, Toprak E, Bollenbach MT. 2015. Excel file containing the raw data for all figures, Public Library of Science, 10.1371/journal.pbio.1002299.s001. mla: Chevereau, Guillaume, et al. Excel File Containing the Raw Data for All Figures. Public Library of Science, 2015, doi:10.1371/journal.pbio.1002299.s001. short: G. Chevereau, M. Lukacisinova, T. Batur, A. Guvenek, D.H. Ayhan, E. Toprak, M.T. Bollenbach, (2015). date_created: 2021-07-23T11:53:50Z date_published: 2015-11-18T00:00:00Z date_updated: 2023-02-23T10:07:02Z day: '18' department: - _id: ToBo doi: 10.1371/journal.pbio.1002299.s001 month: '11' oa_version: Published Version publisher: Public Library of Science related_material: record: - id: '1619' relation: used_in_publication status: public status: public title: Excel file containing the raw data for all figures type: research_data_reference user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf year: '2015' ...