---
_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:
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relation: used_in_publication
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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'
...