---
_id: '666'
abstract:
- lang: eng
text: Antibiotics elicit drastic changes in microbial gene expression, including
the induction of stress response genes. While certain stress responses are known
to “cross-protect” bacteria from other stressors, it is unclear whether cellular
responses to antibiotics have a similar protective role. By measuring the genome-wide
transcriptional response dynamics of Escherichia coli to four antibiotics, we
found that trimethoprim induces a rapid acid stress response that protects bacteria
from subsequent exposure to acid. Combining microfluidics with time-lapse imaging
to monitor survival and acid stress response in single cells revealed that the
noisy expression of the acid resistance operon gadBC correlates with single-cell
survival. Cells with higher gadBC expression following trimethoprim maintain higher
intracellular pH and survive the acid stress longer. The seemingly random single-cell
survival under acid stress can therefore be predicted from gadBC expression and
rationalized in terms of GadB/C molecular function. Overall, we provide a roadmap
for identifying the molecular mechanisms of single-cell cross-protection between
antibiotics and other stressors.
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Karin
full_name: Mitosch, Karin
id: 39B66846-F248-11E8-B48F-1D18A9856A87
last_name: Mitosch
- first_name: Georg
full_name: Rieckh, Georg
id: 34DA8BD6-F248-11E8-B48F-1D18A9856A87
last_name: Rieckh
- first_name: Tobias
full_name: Bollenbach, Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Mitosch K, Rieckh G, Bollenbach MT. Noisy response to antibiotic stress predicts
subsequent single cell survival in an acidic environment. Cell Systems.
2017;4(4):393-403. doi:10.1016/j.cels.2017.03.001
apa: Mitosch, K., Rieckh, G., & Bollenbach, M. T. (2017). Noisy response to
antibiotic stress predicts subsequent single cell survival in an acidic environment.
Cell Systems. Cell Press. https://doi.org/10.1016/j.cels.2017.03.001
chicago: Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Noisy Response
to Antibiotic Stress Predicts Subsequent Single Cell Survival in an Acidic Environment.”
Cell Systems. Cell Press, 2017. https://doi.org/10.1016/j.cels.2017.03.001.
ieee: K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Noisy response to antibiotic
stress predicts subsequent single cell survival in an acidic environment,” Cell
Systems, vol. 4, no. 4. Cell Press, pp. 393–403, 2017.
ista: Mitosch K, Rieckh G, Bollenbach MT. 2017. Noisy response to antibiotic stress
predicts subsequent single cell survival in an acidic environment. Cell Systems.
4(4), 393–403.
mla: Mitosch, Karin, et al. “Noisy Response to Antibiotic Stress Predicts Subsequent
Single Cell Survival in an Acidic Environment.” Cell Systems, vol. 4, no.
4, Cell Press, 2017, pp. 393–403, doi:10.1016/j.cels.2017.03.001.
short: K. Mitosch, G. Rieckh, M.T. Bollenbach, Cell Systems 4 (2017) 393–403.
date_created: 2018-12-11T11:47:48Z
date_published: 2017-04-26T00:00:00Z
date_updated: 2023-09-07T12:00:25Z
day: '26'
ddc:
- '576'
- '610'
department:
- _id: ToBo
- _id: GaTk
doi: 10.1016/j.cels.2017.03.001
ec_funded: 1
file:
- access_level: open_access
checksum: 04ff20011c3d9a601c514aa999a5fe1a
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:13:54Z
date_updated: 2020-07-14T12:47:35Z
file_id: '5041'
file_name: IST-2017-901-v1+1_1-s2.0-S2405471217300868-main.pdf
file_size: 2438660
relation: main_file
file_date_updated: 2020-07-14T12:47:35Z
has_accepted_license: '1'
intvolume: ' 4'
issue: '4'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '04'
oa: 1
oa_version: Published Version
page: 393 - 403
project:
- _id: 25E83C2C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '303507'
name: Optimality principles in responses to antibiotics
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
- _id: 25EB3A80-B435-11E9-9278-68D0E5697425
grant_number: RGP0042/2013
name: Revealing the fundamental limits of cell growth
publication: Cell Systems
publication_identifier:
issn:
- '24054712'
publication_status: published
publisher: Cell Press
publist_id: '7061'
pubrep_id: '901'
quality_controlled: '1'
related_material:
record:
- id: '818'
relation: dissertation_contains
status: public
scopus_import: 1
status: public
title: Noisy response to antibiotic stress predicts subsequent single cell survival
in an acidic environment
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 4
year: '2017'
...
---
_id: '822'
abstract:
- lang: eng
text: 'Polymicrobial infections constitute small ecosystems that accommodate several
bacterial species. Commonly, these bacteria are investigated in isolation. However,
it is unknown to what extent the isolates interact and whether their interactions
alter bacterial growth and ecosystem resilience in the presence and absence of
antibiotics. We quantified the complete ecological interaction network for 72
bacterial isolates collected from 23 individuals diagnosed with polymicrobial
urinary tract infections and found that most interactions cluster based on evolutionary
relatedness. Statistical network analysis revealed that competitive and cooperative
reciprocal interactions are enriched in the global network, while cooperative
interactions are depleted in the individual host community networks. A population
dynamics model parameterized by our measurements suggests that interactions restrict
community stability, explaining the observed species diversity of these communities.
We further show that the clinical isolates frequently protect each other from
clinically relevant antibiotics. Together, these results highlight that ecological
interactions are crucial for the growth and survival of bacteria in polymicrobial
infection communities and affect their assembly and resilience. '
article_processing_charge: No
author:
- first_name: Marjon
full_name: De Vos, Marjon
id: 3111FFAC-F248-11E8-B48F-1D18A9856A87
last_name: De Vos
- first_name: Marcin P
full_name: Zagórski, Marcin P
id: 343DA0DC-F248-11E8-B48F-1D18A9856A87
last_name: Zagórski
orcid: 0000-0001-7896-7762
- first_name: Alan
full_name: Mcnally, Alan
last_name: Mcnally
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: de Vos M, Zagórski MP, Mcnally A, Bollenbach MT. Interaction networks, ecological
stability, and collective antibiotic tolerance in polymicrobial infections. PNAS.
2017;114(40):10666-10671. doi:10.1073/pnas.1713372114
apa: de Vos, M., Zagórski, M. P., Mcnally, A., & Bollenbach, M. T. (2017). Interaction
networks, ecological stability, and collective antibiotic tolerance in polymicrobial
infections. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1713372114
chicago: Vos, Marjon de, Marcin P Zagórski, Alan Mcnally, and Mark Tobias Bollenbach.
“Interaction Networks, Ecological Stability, and Collective Antibiotic Tolerance
in Polymicrobial Infections.” PNAS. National Academy of Sciences, 2017.
https://doi.org/10.1073/pnas.1713372114.
ieee: M. de Vos, M. P. Zagórski, A. Mcnally, and M. T. Bollenbach, “Interaction
networks, ecological stability, and collective antibiotic tolerance in polymicrobial
infections,” PNAS, vol. 114, no. 40. National Academy of Sciences, pp.
10666–10671, 2017.
ista: de Vos M, Zagórski MP, Mcnally A, Bollenbach MT. 2017. Interaction networks,
ecological stability, and collective antibiotic tolerance in polymicrobial infections.
PNAS. 114(40), 10666–10671.
mla: de Vos, Marjon, et al. “Interaction Networks, Ecological Stability, and Collective
Antibiotic Tolerance in Polymicrobial Infections.” PNAS, vol. 114, no.
40, National Academy of Sciences, 2017, pp. 10666–71, doi:10.1073/pnas.1713372114.
short: M. de Vos, M.P. Zagórski, A. Mcnally, M.T. Bollenbach, PNAS 114 (2017) 10666–10671.
date_created: 2018-12-11T11:48:41Z
date_published: 2017-10-03T00:00:00Z
date_updated: 2023-09-26T16:18:48Z
day: '03'
department:
- _id: ToBo
doi: 10.1073/pnas.1713372114
ec_funded: 1
external_id:
isi:
- '000412130500061'
pmid:
- '28923953'
intvolume: ' 114'
isi: 1
issue: '40'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635929/
month: '10'
oa: 1
oa_version: Submitted Version
page: 10666 - 10671
pmid: 1
project:
- _id: 25E83C2C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '303507'
name: Optimality principles in responses to antibiotics
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
publication: PNAS
publication_identifier:
issn:
- '00278424'
publication_status: published
publisher: National Academy of Sciences
publist_id: '6827'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Interaction networks, ecological stability, and collective antibiotic tolerance
in polymicrobial infections
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 114
year: '2017'
...
---
_id: '5563'
abstract:
- lang: eng
text: "MATLAB code and processed datasets available for reproducing the results
in: \r\nLukačišin, M.*, Landon, M.*, Jajoo, R*. (2016) Sequence-Specific Thermodynamic
Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking
in Yeast.\r\n*equal contributions"
article_processing_charge: No
author:
- first_name: Martin
full_name: Lukacisin, Martin
id: 298FFE8C-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisin
orcid: 0000-0001-6549-4177
citation:
ama: Lukacisin M. MATLAB analysis code for “Sequence-Specific Thermodynamic Properties
of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.”
2017. doi:10.15479/AT:ISTA:64
apa: Lukacisin, M. (2017). MATLAB analysis code for “Sequence-Specific Thermodynamic
Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking
in Yeast.” Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:64
chicago: Lukacisin, Martin. “MATLAB Analysis Code for ‘Sequence-Specific Thermodynamic
Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking
in Yeast.’” Institute of Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:64.
ieee: M. Lukacisin, “MATLAB analysis code for ‘Sequence-Specific Thermodynamic Properties
of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.’”
Institute of Science and Technology Austria, 2017.
ista: Lukacisin M. 2017. MATLAB analysis code for ‘Sequence-Specific Thermodynamic
Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking
in Yeast’, Institute of Science and Technology Austria, 10.15479/AT:ISTA:64.
mla: Lukacisin, Martin. MATLAB Analysis Code for “Sequence-Specific Thermodynamic
Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking
in Yeast.” Institute of Science and Technology Austria, 2017, doi:10.15479/AT:ISTA:64.
short: M. Lukacisin, (2017).
datarep_id: '64'
date_created: 2018-12-12T12:31:33Z
date_published: 2017-03-20T00:00:00Z
date_updated: 2024-02-21T13:46:47Z
day: '20'
ddc:
- '571'
department:
- _id: ToBo
doi: 10.15479/AT:ISTA:64
file:
- access_level: open_access
checksum: ee697f2b1ade4dc14d6ac0334dd832ab
content_type: application/zip
creator: system
date_created: 2018-12-12T13:02:37Z
date_updated: 2020-07-14T12:47:03Z
file_id: '5602'
file_name: IST-2016-45-v1+1_PaperCode.zip
file_size: 296722548
relation: main_file
file_date_updated: 2020-07-14T12:47:03Z
has_accepted_license: '1'
license: https://creativecommons.org/licenses/by-sa/4.0/
month: '03'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
status: public
title: MATLAB analysis code for 'Sequence-Specific Thermodynamic Properties of Nucleic
Acids Influence Both Transcriptional Pausing and Backtracking in Yeast'
tmp:
image: /images/cc_by_sa.png
legal_code_url: https://creativecommons.org/licenses/by-sa/4.0/legalcode
name: Creative Commons Attribution-ShareAlike 4.0 International Public License (CC
BY-SA 4.0)
short: CC BY-SA (4.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2017'
...
---
_id: '1029'
abstract:
- lang: eng
text: RNA Polymerase II pauses and backtracks during transcription, with many consequences
for gene expression and cellular physiology. Here, we show that the energy required
to melt double-stranded nucleic acids in the transcription bubble predicts pausing
in Saccharomyces cerevisiae far more accurately than nucleosome roadblocks do.
In addition, the same energy difference also determines when the RNA polymerase
backtracks instead of continuing to move forward. This data-driven model corroborates—in
a genome wide and quantitative manner—previous evidence that sequence-dependent
thermodynamic features of nucleic acids influence both transcriptional pausing
and backtracking.
article_number: e0174066
article_processing_charge: Yes
author:
- first_name: Martin
full_name: Lukacisin, Martin
id: 298FFE8C-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisin
orcid: 0000-0001-6549-4177
- first_name: Matthieu
full_name: Landon, Matthieu
last_name: Landon
- first_name: Rishi
full_name: Jajoo, Rishi
last_name: Jajoo
citation:
ama: Lukacisin M, Landon M, Jajoo R. Sequence-specific thermodynamic properties
of nucleic acids influence both transcriptional pausing and backtracking in yeast.
PLoS One. 2017;12(3). doi:10.1371/journal.pone.0174066
apa: Lukacisin, M., Landon, M., & Jajoo, R. (2017). Sequence-specific thermodynamic
properties of nucleic acids influence both transcriptional pausing and backtracking
in yeast. PLoS One. Public Library of Science. https://doi.org/10.1371/journal.pone.0174066
chicago: Lukacisin, Martin, Matthieu Landon, and Rishi Jajoo. “Sequence-Specific
Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing
and Backtracking in Yeast.” PLoS One. Public Library of Science, 2017.
https://doi.org/10.1371/journal.pone.0174066.
ieee: M. Lukacisin, M. Landon, and R. Jajoo, “Sequence-specific thermodynamic properties
of nucleic acids influence both transcriptional pausing and backtracking in yeast,”
PLoS One, vol. 12, no. 3. Public Library of Science, 2017.
ista: Lukacisin M, Landon M, Jajoo R. 2017. Sequence-specific thermodynamic properties
of nucleic acids influence both transcriptional pausing and backtracking in yeast.
PLoS One. 12(3), e0174066.
mla: Lukacisin, Martin, et al. “Sequence-Specific Thermodynamic Properties of Nucleic
Acids Influence Both Transcriptional Pausing and Backtracking in Yeast.” PLoS
One, vol. 12, no. 3, e0174066, Public Library of Science, 2017, doi:10.1371/journal.pone.0174066.
short: M. Lukacisin, M. Landon, R. Jajoo, PLoS One 12 (2017).
date_created: 2018-12-11T11:49:46Z
date_published: 2017-03-16T00:00:00Z
date_updated: 2024-03-27T23:30:05Z
day: '16'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.1371/journal.pone.0174066
external_id:
isi:
- '000396318300121'
file:
- access_level: open_access
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:09:47Z
date_updated: 2018-12-12T10:09:47Z
file_id: '4772'
file_name: IST-2017-800-v1+1_journal.pone.0174066.pdf
file_size: 3429381
relation: main_file
file_date_updated: 2018-12-12T10:09:47Z
has_accepted_license: '1'
intvolume: ' 12'
isi: 1
issue: '3'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
publication: PLoS One
publication_identifier:
issn:
- '19326203'
publication_status: published
publisher: Public Library of Science
publist_id: '6361'
pubrep_id: '800'
quality_controlled: '1'
related_material:
record:
- id: '5556'
relation: popular_science
status: public
- id: '6392'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Sequence-specific thermodynamic properties of nucleic acids influence both
transcriptional pausing and backtracking in yeast
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 12
year: '2017'
...
---
_id: '696'
abstract:
- lang: eng
text: Mutator strains are expected to evolve when the availability and effect of
beneficial mutations are high enough to counteract the disadvantage from deleterious
mutations that will inevitably accumulate. As the population becomes more adapted
to its environment, both availability and effect of beneficial mutations necessarily
decrease and mutation rates are predicted to decrease. It has been shown that
certain molecular mechanisms can lead to increased mutation rates when the organism
finds itself in a stressful environment. While this may be a correlated response
to other functions, it could also be an adaptive mechanism, raising mutation rates
only when it is most advantageous. Here, we use a mathematical model to investigate
the plausibility of the adaptive hypothesis. We show that such a mechanism can
be mantained if the population is subjected to diverse stresses. By simulating
various antibiotic treatment schemes, we find that combination treatments can
reduce the effectiveness of second-order selection on stress-induced mutagenesis.
We discuss the implications of our results to strategies of antibiotic therapy.
article_number: e1005609
article_type: original
author:
- first_name: Marta
full_name: Lukacisinova, Marta
id: 4342E402-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisinova
orcid: 0000-0002-2519-8004
- first_name: Sebastian
full_name: Novak, Sebastian
id: 461468AE-F248-11E8-B48F-1D18A9856A87
last_name: Novak
orcid: 0000-0002-2519-824X
- first_name: Tiago
full_name: Paixao, Tiago
id: 2C5658E6-F248-11E8-B48F-1D18A9856A87
last_name: Paixao
orcid: 0000-0003-2361-3953
citation:
ama: 'Lukacisinova M, Novak S, Paixao T. Stress induced mutagenesis: Stress diversity
facilitates the persistence of mutator genes. PLoS Computational Biology.
2017;13(7). doi:10.1371/journal.pcbi.1005609'
apa: 'Lukacisinova, M., Novak, S., & Paixao, T. (2017). Stress induced mutagenesis:
Stress diversity facilitates the persistence of mutator genes. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005609'
chicago: 'Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Stress Induced
Mutagenesis: Stress Diversity Facilitates the Persistence of Mutator Genes.” PLoS
Computational Biology. Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005609.'
ieee: 'M. Lukacisinova, S. Novak, and T. Paixao, “Stress induced mutagenesis: Stress
diversity facilitates the persistence of mutator genes,” PLoS Computational
Biology, vol. 13, no. 7. Public Library of Science, 2017.'
ista: 'Lukacisinova M, Novak S, Paixao T. 2017. Stress induced mutagenesis: Stress
diversity facilitates the persistence of mutator genes. PLoS Computational Biology.
13(7), e1005609.'
mla: 'Lukacisinova, Marta, et al. “Stress Induced Mutagenesis: Stress Diversity
Facilitates the Persistence of Mutator Genes.” PLoS Computational Biology,
vol. 13, no. 7, e1005609, Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005609.'
short: M. Lukacisinova, S. Novak, T. Paixao, PLoS Computational Biology 13 (2017).
date_created: 2018-12-11T11:47:58Z
date_published: 2017-07-18T00:00:00Z
date_updated: 2024-03-27T23:30:28Z
day: '18'
ddc:
- '576'
department:
- _id: ToBo
- _id: NiBa
- _id: CaGu
doi: 10.1371/journal.pcbi.1005609
ec_funded: 1
file:
- access_level: open_access
checksum: 9143c290fa6458ed2563bff4b295554a
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:15:01Z
date_updated: 2020-07-14T12:47:46Z
file_id: '5117'
file_name: IST-2017-894-v1+1_journal.pcbi.1005609.pdf
file_size: 3775716
relation: main_file
file_date_updated: 2020-07-14T12:47:46Z
has_accepted_license: '1'
intvolume: ' 13'
issue: '7'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
project:
- _id: 25B1EC9E-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '618091'
name: Speed of Adaptation in Population Genetics and Evolutionary Computation
publication: PLoS Computational Biology
publication_identifier:
issn:
- 1553734X
publication_status: published
publisher: Public Library of Science
publist_id: '7004'
pubrep_id: '894'
quality_controlled: '1'
related_material:
record:
- id: '9849'
relation: research_data
status: public
- id: '9850'
relation: research_data
status: public
- id: '9851'
relation: research_data
status: public
- id: '9852'
relation: research_data
status: public
- id: '6263'
relation: dissertation_contains
status: public
scopus_import: 1
status: public
title: 'Stress induced mutagenesis: Stress diversity facilitates the persistence of
mutator genes'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2017'
...
---
_id: '1027'
abstract:
- lang: eng
text: The rising prevalence of antibiotic resistant bacteria is an increasingly
serious public health challenge. To address this problem, recent work ranging
from clinical studies to theoretical modeling has provided valuable insights into
the mechanisms of resistance, its emergence and spread, and ways to counteract
it. A deeper understanding of the underlying dynamics of resistance evolution
will require a combination of experimental and theoretical expertise from different
disciplines and new technology for studying evolution in the laboratory. Here,
we review recent advances in the quantitative understanding of the mechanisms
and evolution of antibiotic resistance. We focus on key theoretical concepts and
new technology that enables well-controlled experiments. We further highlight
key challenges that can be met in the near future to ultimately develop effective
strategies for combating resistance.
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Marta
full_name: Lukacisinova, Marta
id: 4342E402-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisinova
orcid: 0000-0002-2519-8004
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Lukacisinova M, Bollenbach MT. Toward a quantitative understanding of antibiotic
resistance evolution. Current Opinion in Biotechnology. 2017;46:90-97.
doi:10.1016/j.copbio.2017.02.013
apa: Lukacisinova, M., & Bollenbach, M. T. (2017). Toward a quantitative understanding
of antibiotic resistance evolution. Current Opinion in Biotechnology. Elsevier.
https://doi.org/10.1016/j.copbio.2017.02.013
chicago: Lukacisinova, Marta, and Mark Tobias Bollenbach. “Toward a Quantitative
Understanding of Antibiotic Resistance Evolution.” Current Opinion in Biotechnology.
Elsevier, 2017. https://doi.org/10.1016/j.copbio.2017.02.013.
ieee: M. Lukacisinova and M. T. Bollenbach, “Toward a quantitative understanding
of antibiotic resistance evolution,” Current Opinion in Biotechnology,
vol. 46. Elsevier, pp. 90–97, 2017.
ista: Lukacisinova M, Bollenbach MT. 2017. Toward a quantitative understanding of
antibiotic resistance evolution. Current Opinion in Biotechnology. 46, 90–97.
mla: Lukacisinova, Marta, and Mark Tobias Bollenbach. “Toward a Quantitative Understanding
of Antibiotic Resistance Evolution.” Current Opinion in Biotechnology,
vol. 46, Elsevier, 2017, pp. 90–97, doi:10.1016/j.copbio.2017.02.013.
short: M. Lukacisinova, M.T. Bollenbach, Current Opinion in Biotechnology 46 (2017)
90–97.
date_created: 2018-12-11T11:49:45Z
date_published: 2017-08-01T00:00:00Z
date_updated: 2024-03-27T23:30:28Z
day: '01'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.1016/j.copbio.2017.02.013
ec_funded: 1
external_id:
isi:
- '000408077400015'
file:
- access_level: open_access
content_type: application/pdf
creator: dernst
date_created: 2019-01-18T09:57:57Z
date_updated: 2019-01-18T09:57:57Z
file_id: '5846'
file_name: 2017_CurrentOpinion_Lukaciinova.pdf
file_size: 858338
relation: main_file
success: 1
file_date_updated: 2019-01-18T09:57:57Z
has_accepted_license: '1'
intvolume: ' 46'
isi: 1
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 90 - 97
project:
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
- _id: 25E83C2C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '303507'
name: Optimality principles in responses to antibiotics
- _id: 25EB3A80-B435-11E9-9278-68D0E5697425
grant_number: RGP0042/2013
name: Revealing the fundamental limits of cell growth
publication: Current Opinion in Biotechnology
publication_status: published
publisher: Elsevier
publist_id: '6364'
pubrep_id: '801'
quality_controlled: '1'
related_material:
record:
- id: '6263'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Toward a quantitative understanding of antibiotic resistance evolution
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 46
year: '2017'
...
---
_id: '1154'
abstract:
- lang: eng
text: "Cellular locomotion is a central hallmark of eukaryotic life. It is governed
by cell-extrinsic molecular factors, which can either emerge in the soluble phase
or as immobilized, often adhesive ligands. To encode for direction, every cue
must be present as a spatial or temporal gradient. Here, we developed a microfluidic
chamber that allows measurement of cell migration in combined response to surface
immobilized and soluble molecular gradients. As a proof of principle we study
the response of dendritic cells to their major guidance cues, chemokines. The
majority of data on chemokine gradient sensing is based on in vitro studies employing
soluble gradients. Despite evidence suggesting that in vivo chemokines are often
immobilized to sugar residues, limited information is available how cells respond
to immobilized chemokines. We tracked migration of dendritic cells towards immobilized
gradients of the chemokine CCL21 and varying superimposed soluble gradients of
CCL19. Differential migratory patterns illustrate the potential of our setup to
quantitatively study the competitive response to both types of gradients. Beyond
chemokines our approach is broadly applicable to alternative systems of chemo-
and haptotaxis such as cells migrating along gradients of adhesion receptor ligands
vs. any soluble cue. \r\n"
acknowledgement: 'This work was supported by the Swiss National Science Foundation
(Ambizione fellowship; PZ00P3-154733 to M.M.), the Swiss Multiple Sclerosis Society
(research support to M.M.), a fellowship from the Boehringer Ingelheim Fonds (BIF)
to J.S., the European Research Council (grant ERC GA 281556) and a START award from
the Austrian Science Foundation (FWF) to M.S. #BioimagingFacility'
article_number: '36440'
author:
- first_name: Jan
full_name: Schwarz, Jan
id: 346C1EC6-F248-11E8-B48F-1D18A9856A87
last_name: Schwarz
- first_name: Veronika
full_name: Bierbaum, Veronika
id: 3FD04378-F248-11E8-B48F-1D18A9856A87
last_name: Bierbaum
- first_name: Jack
full_name: Merrin, Jack
id: 4515C308-F248-11E8-B48F-1D18A9856A87
last_name: Merrin
orcid: 0000-0001-5145-4609
- first_name: Tino
full_name: Frank, Tino
last_name: Frank
- first_name: Robert
full_name: Hauschild, Robert
id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87
last_name: Hauschild
orcid: 0000-0001-9843-3522
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
- first_name: Savaş
full_name: Tay, Savaş
last_name: Tay
- first_name: Michael K
full_name: Sixt, Michael K
id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87
last_name: Sixt
orcid: 0000-0002-6620-9179
- first_name: Matthias
full_name: Mehling, Matthias
id: 3C23B994-F248-11E8-B48F-1D18A9856A87
last_name: Mehling
orcid: 0000-0001-8599-1226
citation:
ama: Schwarz J, Bierbaum V, Merrin J, et al. A microfluidic device for measuring
cell migration towards substrate bound and soluble chemokine gradients. Scientific
Reports. 2016;6. doi:10.1038/srep36440
apa: Schwarz, J., Bierbaum, V., Merrin, J., Frank, T., Hauschild, R., Bollenbach,
M. T., … Mehling, M. (2016). A microfluidic device for measuring cell migration
towards substrate bound and soluble chemokine gradients. Scientific Reports.
Nature Publishing Group. https://doi.org/10.1038/srep36440
chicago: Schwarz, Jan, Veronika Bierbaum, Jack Merrin, Tino Frank, Robert Hauschild,
Mark Tobias Bollenbach, Savaş Tay, Michael K Sixt, and Matthias Mehling. “A Microfluidic
Device for Measuring Cell Migration towards Substrate Bound and Soluble Chemokine
Gradients.” Scientific Reports. Nature Publishing Group, 2016. https://doi.org/10.1038/srep36440.
ieee: J. Schwarz et al., “A microfluidic device for measuring cell migration
towards substrate bound and soluble chemokine gradients,” Scientific Reports,
vol. 6. Nature Publishing Group, 2016.
ista: Schwarz J, Bierbaum V, Merrin J, Frank T, Hauschild R, Bollenbach MT, Tay
S, Sixt MK, Mehling M. 2016. A microfluidic device for measuring cell migration
towards substrate bound and soluble chemokine gradients. Scientific Reports. 6,
36440.
mla: Schwarz, Jan, et al. “A Microfluidic Device for Measuring Cell Migration towards
Substrate Bound and Soluble Chemokine Gradients.” Scientific Reports, vol.
6, 36440, Nature Publishing Group, 2016, doi:10.1038/srep36440.
short: J. Schwarz, V. Bierbaum, J. Merrin, T. Frank, R. Hauschild, M.T. Bollenbach,
S. Tay, M.K. Sixt, M. Mehling, Scientific Reports 6 (2016).
date_created: 2018-12-11T11:50:27Z
date_published: 2016-11-07T00:00:00Z
date_updated: 2021-01-12T06:48:41Z
day: '07'
ddc:
- '579'
department:
- _id: MiSi
- _id: NanoFab
- _id: Bio
- _id: ToBo
doi: 10.1038/srep36440
ec_funded: 1
file:
- access_level: open_access
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:09:32Z
date_updated: 2018-12-12T10:09:32Z
file_id: '4756'
file_name: IST-2017-744-v1+1_srep36440.pdf
file_size: 2353456
relation: main_file
file_date_updated: 2018-12-12T10:09:32Z
has_accepted_license: '1'
intvolume: ' 6'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
project:
- _id: 25A603A2-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '281556'
name: Cytoskeletal force generation and force transduction of migrating leukocytes
(EU)
- _id: 25A8E5EA-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Y 564-B12
name: Cytoskeletal force generation and transduction of leukocytes (FWF)
publication: Scientific Reports
publication_status: published
publisher: Nature Publishing Group
publist_id: '6204'
pubrep_id: '744'
quality_controlled: '1'
scopus_import: 1
status: public
title: A microfluidic device for measuring cell migration towards substrate bound
and soluble chemokine gradients
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 6
year: '2016'
...
---
_id: '1218'
abstract:
- lang: eng
text: Investigating the physiology of cyanobacteria cultured under a diel light
regime is relevant for a better understanding of the resulting growth characteristics
and for specific biotechnological applications that are foreseen for these photosynthetic
organisms. Here, we present the results of a multiomics study of the model cyanobacterium
Synechocystis sp. strain PCC 6803, cultured in a lab-scale photobioreactor in
physiological conditions relevant for large-scale culturing. The culture was sparged
withN2 andCO2, leading to an anoxic environment during the dark period. Growth
followed the availability of light. Metabolite analysis performed with 1Hnuclear
magnetic resonance analysis showed that amino acids involved in nitrogen and sulfur
assimilation showed elevated levels in the light. Most protein levels, analyzed
through mass spectrometry, remained rather stable. However, several high-light-response
proteins and stress-response proteins showed distinct changes at the onset of
the light period. Microarray-based transcript analysis found common patterns of~56%
of the transcriptome following the diel regime. These oscillating transcripts
could be grouped coarsely into genes that were upregulated and downregulated in
the dark period. The accumulated glycogen was degraded in the anaerobic environment
in the dark. A small part was degraded gradually, reflecting basic maintenance
requirements of the cells in darkness. Surprisingly, the largest part was degraded
rapidly in a short time span at the end of the dark period. This degradation could
allow rapid formation of metabolic intermediates at the end of the dark period,
preparing the cells for the resumption of growth at the start of the light period.
acknowledgement: "Dutch Ministry of Economic Affairs, Agriculture, and Innovation
through the program BioSolar CellsS. Andreas Angermayr,Pascal van Alphen, Klaas
J. Hellingwerf\r\nWe thank Naira Quintana (presently at Rousselot, Belgium) for
the ini-\r\ntiative at the 10th Cyanobacterial Molecular Biology Workshop\r\n(CMBW),
June 2010, Lake Arrowhead, Los Angeles, CA, USA, to start the\r\ncollaborative endeavor
reported here. We thank Timo Maarleveld from\r\nCWI/VU (Amsterdam) for a custom-made
Python script handling the output from the NMR analysis and for evaluating and visualizing
the\r\nseparate metabolites for their evaluation. We thank Rob Verpoorte from\r\nLeiden
University (metabolome analysis) and Hans Aerts from the AMC\r\n(proteome analysis)
for lab space and equipment. We thank Robert Leh-\r\nmann (Humboldt University Berlin)
and Ilka Axmann (University of\r\nDüsseldorf) for sharing the R-code for the LOS
transformation of the\r\ntranscript data. We thank Hans C. P. Matthijs from IBED
for inspiring\r\ndialogues and insightful thoughts on continuous culturing of cyanobac-\r\nteria.
We thank Sandra Waaijenborg for performing the transcript nor-\r\nmalization and
Johan Westerhuis from BDA, Jeroen van der Steen and\r\nFilipe Branco dos Santos
from MMP, and Lucas Stal from IBED/NIOZ for\r\nhelpful discussions. We thank Milou
Schuurmans from MMP for help\r\nwith sampling and glycogen determination. We thank
the members of the\r\nRNA Biology & Applied Bioinformatics group at SILS, in particular
Selina\r\nvan Leeuwen, Elisa Hoekstra, and Martijs Jonker, for the microarray anal-\r\nysis.
We thank the reviewers of this work for their insightful comments\r\nwhich improved
the quality of the manuscript. This work, including the efforts of S. Andreas Angermayr,
Pascal van\r\nAlphen, and Klaas J. Hellingwerf, was funded by Dutch Ministry of
Eco-\r\nnomic Affairs, Agriculture, and Innovation through the program BioSolar\r\nCells."
author:
- first_name: Andreas
full_name: Angermayr, Andreas
id: 4677C796-F248-11E8-B48F-1D18A9856A87
last_name: Angermayr
orcid: 0000-0001-8619-2223
- first_name: Pascal
full_name: Van Alphen, Pascal
last_name: Van Alphen
- first_name: Dicle
full_name: Hasdemir, Dicle
last_name: Hasdemir
- first_name: Gertjan
full_name: Kramer, Gertjan
last_name: Kramer
- first_name: Muzamal
full_name: Iqbal, Muzamal
last_name: Iqbal
- first_name: Wilmar
full_name: Van Grondelle, Wilmar
last_name: Van Grondelle
- first_name: Huub
full_name: Hoefsloot, Huub
last_name: Hoefsloot
- first_name: Younghae
full_name: Choi, Younghae
last_name: Choi
- first_name: Klaas
full_name: Hellingwerf, Klaas
last_name: Hellingwerf
citation:
ama: Angermayr A, Van Alphen P, Hasdemir D, et al. Culturing synechocystis sp. Strain
pcc 6803 with N2 and CO2 in a diel regime reveals multiphase glycogen dynamics
with low maintenance costs. Applied and Environmental Microbiology. 2016;82(14):4180-4189.
doi:10.1128/AEM.00256-16
apa: Angermayr, A., Van Alphen, P., Hasdemir, D., Kramer, G., Iqbal, M., Van Grondelle,
W., … Hellingwerf, K. (2016). Culturing synechocystis sp. Strain pcc 6803 with
N2 and CO2 in a diel regime reveals multiphase glycogen dynamics with low maintenance
costs. Applied and Environmental Microbiology. American Society for Microbiology.
https://doi.org/10.1128/AEM.00256-16
chicago: Angermayr, Andreas, Pascal Van Alphen, Dicle Hasdemir, Gertjan Kramer,
Muzamal Iqbal, Wilmar Van Grondelle, Huub Hoefsloot, Younghae Choi, and Klaas
Hellingwerf. “Culturing Synechocystis Sp. Strain Pcc 6803 with N2 and CO2 in a
Diel Regime Reveals Multiphase Glycogen Dynamics with Low Maintenance Costs.”
Applied and Environmental Microbiology. American Society for Microbiology,
2016. https://doi.org/10.1128/AEM.00256-16.
ieee: A. Angermayr et al., “Culturing synechocystis sp. Strain pcc 6803 with
N2 and CO2 in a diel regime reveals multiphase glycogen dynamics with low maintenance
costs,” Applied and Environmental Microbiology, vol. 82, no. 14. American
Society for Microbiology, pp. 4180–4189, 2016.
ista: Angermayr A, Van Alphen P, Hasdemir D, Kramer G, Iqbal M, Van Grondelle W,
Hoefsloot H, Choi Y, Hellingwerf K. 2016. Culturing synechocystis sp. Strain pcc
6803 with N2 and CO2 in a diel regime reveals multiphase glycogen dynamics with
low maintenance costs. Applied and Environmental Microbiology. 82(14), 4180–4189.
mla: Angermayr, Andreas, et al. “Culturing Synechocystis Sp. Strain Pcc 6803 with
N2 and CO2 in a Diel Regime Reveals Multiphase Glycogen Dynamics with Low Maintenance
Costs.” Applied and Environmental Microbiology, vol. 82, no. 14, American
Society for Microbiology, 2016, pp. 4180–89, doi:10.1128/AEM.00256-16.
short: A. Angermayr, P. Van Alphen, D. Hasdemir, G. Kramer, M. Iqbal, W. Van Grondelle,
H. Hoefsloot, Y. Choi, K. Hellingwerf, Applied and Environmental Microbiology
82 (2016) 4180–4189.
date_created: 2018-12-11T11:50:46Z
date_published: 2016-07-01T00:00:00Z
date_updated: 2021-01-12T06:49:10Z
day: '01'
department:
- _id: ToBo
doi: 10.1128/AEM.00256-16
intvolume: ' 82'
issue: '14'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4959195/
month: '07'
oa: 1
oa_version: Submitted Version
page: 4180 - 4189
publication: Applied and Environmental Microbiology
publication_status: published
publisher: American Society for Microbiology
publist_id: '6117'
quality_controlled: '1'
scopus_import: 1
status: public
title: Culturing synechocystis sp. Strain pcc 6803 with N2 and CO2 in a diel regime
reveals multiphase glycogen dynamics with low maintenance costs
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 82
year: '2016'
...
---
_id: '1552'
abstract:
- lang: eng
text: Antibiotic resistance carries a fitness cost that must be overcome in order
for resistance to persist over the long term. Compensatory mutations that recover
the functional defects associated with resistance mutations have been argued to
play a key role in overcoming the cost of resistance, but compensatory mutations
are expected to be rare relative to generally beneficial mutations that increase
fitness, irrespective of antibiotic resistance. Given this asymmetry, population
genetics theory predicts that populations should adapt by compensatory mutations
when the cost of resistance is large, whereas generally beneficial mutations should
drive adaptation when the cost of resistance is small. We tested this prediction
by determining the genomic mechanisms underpinning adaptation to antibiotic-free
conditions in populations of the pathogenic bacterium Pseudomonas aeruginosa that
carry costly antibiotic resistance mutations. Whole-genome sequencing revealed
that populations founded by high-cost rifampicin-resistant mutants adapted via
compensatory mutations in three genes of the RNA polymerase core enzyme, whereas
populations founded by low-cost mutants adapted by generally beneficial mutations,
predominantly in the quorum-sensing transcriptional regulator gene lasR. Even
though the importance of compensatory evolution in maintaining resistance has
been widely recognized, our study shows that the roles of general adaptation in
maintaining resistance should not be underestimated and highlights the need to
understand how selection at other sites in the genome influences the dynamics
of resistance alleles in clinical settings.
acknowledgement: "We thank the High-Throughput Genomics Group at the Wellcome Trust
Centre for Human Genetics funded by Wellcome\r\nTrust grant reference 090532/Z/09/Z
and Medical Research Council Hub grant no. G0900747 91070 for generation of the
high-throughput sequencing data. We thank Wook Kim and two anonymous reviewers for
their constructive feedback on previous versions of our manuscript."
article_number: '20152452'
author:
- first_name: Qin
full_name: Qi, Qin
id: 3B22D412-F248-11E8-B48F-1D18A9856A87
last_name: Qi
orcid: 0000-0002-6148-2416
- first_name: Macarena
full_name: Toll Riera, Macarena
last_name: Toll Riera
- first_name: Karl
full_name: Heilbron, Karl
last_name: Heilbron
- first_name: Gail
full_name: Preston, Gail
last_name: Preston
- first_name: R Craig
full_name: Maclean, R Craig
last_name: Maclean
citation:
ama: Qi Q, Toll Riera M, Heilbron K, Preston G, Maclean RC. The genomic basis of
adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa.
Proceedings of the Royal Society of London Series B Biological Sciences.
2016;283(1822). doi:10.1098/rspb.2015.2452
apa: Qi, Q., Toll Riera, M., Heilbron, K., Preston, G., & Maclean, R. C. (2016).
The genomic basis of adaptation to the fitness cost of rifampicin resistance in
Pseudomonas aeruginosa. Proceedings of the Royal Society of London Series B
Biological Sciences. Royal Society, The. https://doi.org/10.1098/rspb.2015.2452
chicago: Qi, Qin, Macarena Toll Riera, Karl Heilbron, Gail Preston, and R Craig
Maclean. “The Genomic Basis of Adaptation to the Fitness Cost of Rifampicin Resistance
in Pseudomonas Aeruginosa.” Proceedings of the Royal Society of London Series
B Biological Sciences. Royal Society, The, 2016. https://doi.org/10.1098/rspb.2015.2452.
ieee: Q. Qi, M. Toll Riera, K. Heilbron, G. Preston, and R. C. Maclean, “The genomic
basis of adaptation to the fitness cost of rifampicin resistance in Pseudomonas
aeruginosa,” Proceedings of the Royal Society of London Series B Biological
Sciences, vol. 283, no. 1822. Royal Society, The, 2016.
ista: Qi Q, Toll Riera M, Heilbron K, Preston G, Maclean RC. 2016. The genomic basis
of adaptation to the fitness cost of rifampicin resistance in Pseudomonas aeruginosa.
Proceedings of the Royal Society of London Series B Biological Sciences. 283(1822),
20152452.
mla: Qi, Qin, et al. “The Genomic Basis of Adaptation to the Fitness Cost of Rifampicin
Resistance in Pseudomonas Aeruginosa.” Proceedings of the Royal Society of
London Series B Biological Sciences, vol. 283, no. 1822, 20152452, Royal Society,
The, 2016, doi:10.1098/rspb.2015.2452.
short: Q. Qi, M. Toll Riera, K. Heilbron, G. Preston, R.C. Maclean, Proceedings
of the Royal Society of London Series B Biological Sciences 283 (2016).
date_created: 2018-12-11T11:52:40Z
date_published: 2016-01-13T00:00:00Z
date_updated: 2021-01-12T06:51:33Z
day: '13'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.1098/rspb.2015.2452
file:
- access_level: open_access
checksum: 78ffe70c1c88af3856d31ca6b7195a27
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:11:43Z
date_updated: 2020-07-14T12:45:02Z
file_id: '4899'
file_name: IST-2016-488-v1+1_20152452.full.pdf
file_size: 626804
relation: main_file
file_date_updated: 2020-07-14T12:45:02Z
has_accepted_license: '1'
intvolume: ' 283'
issue: '1822'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
publication: Proceedings of the Royal Society of London Series B Biological Sciences
publication_status: published
publisher: Royal Society, The
publist_id: '5619'
pubrep_id: '488'
quality_controlled: '1'
scopus_import: 1
status: public
title: The genomic basis of adaptation to the fitness cost of rifampicin resistance
in Pseudomonas aeruginosa
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 283
year: '2016'
...
---
_id: '5556'
abstract:
- lang: eng
text: "MATLAB code and processed datasets available for reproducing the results
in: \r\nLukačišin, M.*, Landon, M.*, Jajoo, R*. (2016) Sequence-Specific Thermodynamic
Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking
in Yeast.\r\n*equal contributions"
article_processing_charge: No
author:
- first_name: Martin
full_name: Lukacisin, Martin
id: 298FFE8C-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisin
orcid: 0000-0001-6549-4177
- first_name: Matthieu
full_name: Landon, Matthieu
last_name: Landon
- first_name: Rishi
full_name: Jajoo, Rishi
last_name: Jajoo
citation:
ama: Lukacisin M, Landon M, Jajoo R. MATLAB analysis code for “Sequence-Specific
Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing
and Backtracking in Yeast.” 2016. doi:10.15479/AT:ISTA:45
apa: Lukacisin, M., Landon, M., & Jajoo, R. (2016). MATLAB analysis code for
“Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional
Pausing and Backtracking in Yeast.” Institute of Science and Technology Austria.
https://doi.org/10.15479/AT:ISTA:45
chicago: Lukacisin, Martin, Matthieu Landon, and Rishi Jajoo. “MATLAB Analysis Code
for ‘Sequence-Specific Thermodynamic Properties of Nucleic Acids Influence Both
Transcriptional Pausing and Backtracking in Yeast.’” Institute of Science and
Technology Austria, 2016. https://doi.org/10.15479/AT:ISTA:45.
ieee: M. Lukacisin, M. Landon, and R. Jajoo, “MATLAB analysis code for ‘Sequence-Specific
Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing
and Backtracking in Yeast.’” Institute of Science and Technology Austria, 2016.
ista: Lukacisin M, Landon M, Jajoo R. 2016. MATLAB analysis code for ‘Sequence-Specific
Thermodynamic Properties of Nucleic Acids Influence Both Transcriptional Pausing
and Backtracking in Yeast’, Institute of Science and Technology Austria, 10.15479/AT:ISTA:45.
mla: Lukacisin, Martin, et al. MATLAB Analysis Code for “Sequence-Specific Thermodynamic
Properties of Nucleic Acids Influence Both Transcriptional Pausing and Backtracking
in Yeast.” Institute of Science and Technology Austria, 2016, doi:10.15479/AT:ISTA:45.
short: M. Lukacisin, M. Landon, R. Jajoo, (2016).
datarep_id: '45'
date_created: 2018-12-12T12:31:31Z
date_published: 2016-08-25T00:00:00Z
date_updated: 2024-02-21T13:51:53Z
day: '25'
ddc:
- '571'
department:
- _id: ToBo
doi: 10.15479/AT:ISTA:45
file:
- access_level: open_access
checksum: ee697f2b1ade4dc14d6ac0334dd832ab
content_type: application/zip
creator: system
date_created: 2018-12-12T13:02:58Z
date_updated: 2020-07-14T12:47:02Z
file_id: '5616'
file_name: IST-2016-45-v1+1_PaperCode.zip
file_size: 296722548
relation: main_file
file_date_updated: 2020-07-14T12:47:02Z
has_accepted_license: '1'
keyword:
- transcription
- pausing
- backtracking
- polymerase
- RNA
- NET-seq
- nucleosome
- basepairing
month: '08'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '8431'
relation: used_in_publication
status: deleted
- id: '1029'
relation: research_paper
status: public
status: public
title: MATLAB analysis code for 'Sequence-Specific Thermodynamic Properties of Nucleic
Acids Influence Both Transcriptional Pausing and Backtracking in Yeast'
tmp:
image: /images/cc_by_sa.png
legal_code_url: https://creativecommons.org/licenses/by-sa/4.0/legalcode
name: Creative Commons Attribution-ShareAlike 4.0 International Public License (CC
BY-SA 4.0)
short: CC BY-SA (4.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2016'
...
---
_id: '1571'
abstract:
- lang: eng
text: Epistatic interactions can frustrate and shape evolutionary change. Indeed,
phenotypes may fail to evolve when essential mutations are only accessible through
positive selection if they are fixed simultaneously. How environmental variability
affects such constraints is poorly understood. Here, we studied genetic constraints
in fixed and fluctuating environments using the Escherichia coli lac operon as
a model system for genotype-environment interactions. We found that, in different
fixed environments, all trajectories that were reconstructed by applying point
mutations within the transcription factor-operator interface became trapped at
suboptima, where no additional improvements were possible. Paradoxically, repeated
switching between these same environments allows unconstrained adaptation by continuous
improvements. This evolutionary mode is explained by pervasive cross-environmental
tradeoffs that reposition the peaks in such a way that trapped genotypes can repeatedly
climb ascending slopes and hence, escape adaptive stasis. Using a Markov approach,
we developed a mathematical framework to quantify the landscape-crossing rates
and show that this ratchet-like adaptive mechanism is robust in a wide spectrum
of fluctuating environments. Overall, this study shows that genetic constraints
can be overcome by environmental change and that crossenvironmental tradeoffs
do not necessarily impede but also, can facilitate adaptive evolution. Because
tradeoffs and environmental variability are ubiquitous in nature, we speculate
this evolutionary mode to be of general relevance.
acknowledgement: This work is part of the research program of the Foundation for Fundamental
Research on Matter, which is part of the Netherlands Organization for Scientific
Research (NWO). M.G.J.d.V. was (partially) funded by NWO Earth and Life Sciences
(ALW), project 863.14.015. We thank D. M. Weinreich, J. A. G. M. de Visser, T. Paixão,
J. Polechová, T. Friedlander, and A. E. Mayo for reading and commenting on earlier
versions of the manuscript and B. Houchmandzadeh, O. Rivoire, and M. Hemery for
discussions and suggestions on the Markov computation. Furthermore, we thank F.
J. Poelwijk for sharing plasmid pCascade5 and pRD007 and Y. Yokobayashi for sharing
plasmid pINV-110. We also thank the anonymous reviewers for remarks on the initial
version of the manuscript.
author:
- first_name: Marjon
full_name: De Vos, Marjon
id: 3111FFAC-F248-11E8-B48F-1D18A9856A87
last_name: De Vos
- first_name: Alexandre
full_name: Dawid, Alexandre
last_name: Dawid
- first_name: Vanda
full_name: Šunderlíková, Vanda
last_name: Šunderlíková
- first_name: Sander
full_name: Tans, Sander
last_name: Tans
citation:
ama: de Vos M, Dawid A, Šunderlíková V, Tans S. Breaking evolutionary constraint
with a tradeoff ratchet. PNAS. 2015;112(48):14906-14911. doi:10.1073/pnas.1510282112
apa: de Vos, M., Dawid, A., Šunderlíková, V., & Tans, S. (2015). Breaking evolutionary
constraint with a tradeoff ratchet. PNAS. National Academy of Sciences.
https://doi.org/10.1073/pnas.1510282112
chicago: Vos, Marjon de, Alexandre Dawid, Vanda Šunderlíková, and Sander Tans. “Breaking
Evolutionary Constraint with a Tradeoff Ratchet.” PNAS. National Academy
of Sciences, 2015. https://doi.org/10.1073/pnas.1510282112.
ieee: M. de Vos, A. Dawid, V. Šunderlíková, and S. Tans, “Breaking evolutionary
constraint with a tradeoff ratchet,” PNAS, vol. 112, no. 48. National Academy
of Sciences, pp. 14906–14911, 2015.
ista: de Vos M, Dawid A, Šunderlíková V, Tans S. 2015. Breaking evolutionary constraint
with a tradeoff ratchet. PNAS. 112(48), 14906–14911.
mla: de Vos, Marjon, et al. “Breaking Evolutionary Constraint with a Tradeoff Ratchet.”
PNAS, vol. 112, no. 48, National Academy of Sciences, 2015, pp. 14906–11,
doi:10.1073/pnas.1510282112.
short: M. de Vos, A. Dawid, V. Šunderlíková, S. Tans, PNAS 112 (2015) 14906–14911.
date_created: 2018-12-11T11:52:47Z
date_published: 2015-12-01T00:00:00Z
date_updated: 2021-01-12T06:51:40Z
day: '01'
department:
- _id: ToBo
doi: 10.1073/pnas.1510282112
intvolume: ' 112'
issue: '48'
language:
- iso: eng
month: '12'
oa_version: None
page: 14906 - 14911
publication: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '5600'
quality_controlled: '1'
scopus_import: 1
status: public
title: Breaking evolutionary constraint with a tradeoff ratchet
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 112
year: '2015'
...
---
_id: '1581'
abstract:
- lang: eng
text: In animal embryos, morphogen gradients determine tissue patterning and morphogenesis.
Shyer et al. provide evidence that, during vertebrate gut formation, tissue folding
generates graded activity of signals required for subsequent steps of gut growth
and differentiation, thereby revealing an intriguing link between tissue morphogenesis
and morphogen gradient formation.
article_processing_charge: No
author:
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
- first_name: Carl-Philipp J
full_name: Heisenberg, Carl-Philipp J
id: 39427864-F248-11E8-B48F-1D18A9856A87
last_name: Heisenberg
orcid: 0000-0002-0912-4566
citation:
ama: Bollenbach MT, Heisenberg C-PJ. Gradients are shaping up. Cell. 2015;161(3):431-432.
doi:10.1016/j.cell.2015.04.009
apa: Bollenbach, M. T., & Heisenberg, C.-P. J. (2015). Gradients are shaping
up. Cell. Cell Press. https://doi.org/10.1016/j.cell.2015.04.009
chicago: Bollenbach, Mark Tobias, and Carl-Philipp J Heisenberg. “Gradients Are
Shaping Up.” Cell. Cell Press, 2015. https://doi.org/10.1016/j.cell.2015.04.009.
ieee: M. T. Bollenbach and C.-P. J. Heisenberg, “Gradients are shaping up,” Cell,
vol. 161, no. 3. Cell Press, pp. 431–432, 2015.
ista: Bollenbach MT, Heisenberg C-PJ. 2015. Gradients are shaping up. Cell. 161(3),
431–432.
mla: Bollenbach, Mark Tobias, and Carl-Philipp J. Heisenberg. “Gradients Are Shaping
Up.” Cell, vol. 161, no. 3, Cell Press, 2015, pp. 431–32, doi:10.1016/j.cell.2015.04.009.
short: M.T. Bollenbach, C.-P.J. Heisenberg, Cell 161 (2015) 431–432.
date_created: 2018-12-11T11:52:50Z
date_published: 2015-04-23T00:00:00Z
date_updated: 2022-08-25T13:56:10Z
day: '23'
department:
- _id: ToBo
- _id: CaHe
doi: 10.1016/j.cell.2015.04.009
intvolume: ' 161'
issue: '3'
language:
- iso: eng
month: '04'
oa_version: None
page: 431 - 432
publication: Cell
publication_status: published
publisher: Cell Press
publist_id: '5590'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Gradients are shaping up
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 161
year: '2015'
...
---
_id: '1586'
abstract:
- lang: eng
text: Through metabolic engineering cyanobacteria can be employed in biotechnology.
Combining the capacity for oxygenic photosynthesis and carbon fixation with an
engineered metabolic pathway allows carbon-based product formation from CO2, light,
and water directly. Such cyanobacterial 'cell factories' are constructed to produce
biofuels, bioplastics, and commodity chemicals. Efforts of metabolic engineers
and synthetic biologists allow the modification of the intermediary metabolism
at various branching points, expanding the product range. The new biosynthesis
routes 'tap' the metabolism ever more efficiently, particularly through the engineering
of driving forces and utilization of cofactors generated during the light reactions
of photosynthesis, resulting in higher product titers. High rates of carbon rechanneling
ultimately allow an almost-complete allocation of fixed carbon to product above
biomass.
author:
- first_name: Andreas
full_name: Angermayr, Andreas
id: 4677C796-F248-11E8-B48F-1D18A9856A87
last_name: Angermayr
orcid: 0000-0001-8619-2223
- first_name: Aleix
full_name: Gorchs, Aleix
last_name: Gorchs
- first_name: Klaas
full_name: Hellingwerf, Klaas
last_name: Hellingwerf
citation:
ama: Angermayr A, Gorchs A, Hellingwerf K. Metabolic engineering of cyanobacteria
for the synthesis of commodity products. Trends in Biotechnology. 2015;33(6):352-361.
doi:10.1016/j.tibtech.2015.03.009
apa: Angermayr, A., Gorchs, A., & Hellingwerf, K. (2015). Metabolic engineering
of cyanobacteria for the synthesis of commodity products. Trends in Biotechnology.
Elsevier. https://doi.org/10.1016/j.tibtech.2015.03.009
chicago: Angermayr, Andreas, Aleix Gorchs, and Klaas Hellingwerf. “Metabolic Engineering
of Cyanobacteria for the Synthesis of Commodity Products.” Trends in Biotechnology.
Elsevier, 2015. https://doi.org/10.1016/j.tibtech.2015.03.009.
ieee: A. Angermayr, A. Gorchs, and K. Hellingwerf, “Metabolic engineering of cyanobacteria
for the synthesis of commodity products,” Trends in Biotechnology, vol.
33, no. 6. Elsevier, pp. 352–361, 2015.
ista: Angermayr A, Gorchs A, Hellingwerf K. 2015. Metabolic engineering of cyanobacteria
for the synthesis of commodity products. Trends in Biotechnology. 33(6), 352–361.
mla: Angermayr, Andreas, et al. “Metabolic Engineering of Cyanobacteria for the
Synthesis of Commodity Products.” Trends in Biotechnology, vol. 33, no.
6, Elsevier, 2015, pp. 352–61, doi:10.1016/j.tibtech.2015.03.009.
short: A. Angermayr, A. Gorchs, K. Hellingwerf, Trends in Biotechnology 33 (2015)
352–361.
date_created: 2018-12-11T11:52:52Z
date_published: 2015-06-01T00:00:00Z
date_updated: 2021-01-12T06:51:46Z
day: '01'
department:
- _id: ToBo
doi: 10.1016/j.tibtech.2015.03.009
intvolume: ' 33'
issue: '6'
language:
- iso: eng
month: '06'
oa_version: None
page: 352 - 361
publication: Trends in Biotechnology
publication_status: published
publisher: Elsevier
publist_id: '5585'
quality_controlled: '1'
scopus_import: 1
status: public
title: Metabolic engineering of cyanobacteria for the synthesis of commodity products
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 33
year: '2015'
...
---
_id: '1623'
abstract:
- lang: eng
text: "Background\r\nPhotosynthetic cyanobacteria are attractive for a range of
biotechnological applications including biofuel production. However, due to slow
growth, screening of mutant libraries using microtiter plates is not feasible.\r\nResults\r\nWe
present a method for high-throughput, single-cell analysis and sorting of genetically
engineered l-lactate-producing strains of Synechocystis sp. PCC6803. A microfluidic
device is used to encapsulate single cells in picoliter droplets, assay the droplets
for l-lactate production, and sort strains with high productivity. We demonstrate
the separation of low- and high-producing reference strains, as well as enrichment
of a more productive l-lactate-synthesizing population after UV-induced mutagenesis.
The droplet platform also revealed population heterogeneity in photosynthetic
growth and lactate production, as well as the presence of metabolically stalled
cells.\r\nConclusions\r\nThe workflow will facilitate metabolic engineering and
directed evolution studies and will be useful in studies of cyanobacteria biochemistry
and physiology.\r\n"
article_number: '193'
author:
- first_name: Petter
full_name: Hammar, Petter
last_name: Hammar
- first_name: Andreas
full_name: Angermayr, Andreas
id: 4677C796-F248-11E8-B48F-1D18A9856A87
last_name: Angermayr
orcid: 0000-0001-8619-2223
- first_name: Staffan
full_name: Sjostrom, Staffan
last_name: Sjostrom
- first_name: Josefin
full_name: Van Der Meer, Josefin
last_name: Van Der Meer
- first_name: Klaas
full_name: Hellingwerf, Klaas
last_name: Hellingwerf
- first_name: Elton
full_name: Hudson, Elton
last_name: Hudson
- first_name: Hakaan
full_name: Joensson, Hakaan
last_name: Joensson
citation:
ama: Hammar P, Angermayr A, Sjostrom S, et al. Single-cell screening of photosynthetic
growth and lactate production by cyanobacteria. Biotechnology for Biofuels.
2015;8(1). doi:10.1186/s13068-015-0380-2
apa: Hammar, P., Angermayr, A., Sjostrom, S., Van Der Meer, J., Hellingwerf, K.,
Hudson, E., & Joensson, H. (2015). Single-cell screening of photosynthetic
growth and lactate production by cyanobacteria. Biotechnology for Biofuels.
BioMed Central. https://doi.org/10.1186/s13068-015-0380-2
chicago: Hammar, Petter, Andreas Angermayr, Staffan Sjostrom, Josefin Van Der Meer,
Klaas Hellingwerf, Elton Hudson, and Hakaan Joensson. “Single-Cell Screening of
Photosynthetic Growth and Lactate Production by Cyanobacteria.” Biotechnology
for Biofuels. BioMed Central, 2015. https://doi.org/10.1186/s13068-015-0380-2.
ieee: P. Hammar et al., “Single-cell screening of photosynthetic growth and
lactate production by cyanobacteria,” Biotechnology for Biofuels, vol.
8, no. 1. BioMed Central, 2015.
ista: Hammar P, Angermayr A, Sjostrom S, Van Der Meer J, Hellingwerf K, Hudson E,
Joensson H. 2015. Single-cell screening of photosynthetic growth and lactate production
by cyanobacteria. Biotechnology for Biofuels. 8(1), 193.
mla: Hammar, Petter, et al. “Single-Cell Screening of Photosynthetic Growth and
Lactate Production by Cyanobacteria.” Biotechnology for Biofuels, vol.
8, no. 1, 193, BioMed Central, 2015, doi:10.1186/s13068-015-0380-2.
short: P. Hammar, A. Angermayr, S. Sjostrom, J. Van Der Meer, K. Hellingwerf, E.
Hudson, H. Joensson, Biotechnology for Biofuels 8 (2015).
date_created: 2018-12-11T11:53:05Z
date_published: 2015-11-25T00:00:00Z
date_updated: 2021-01-12T06:52:04Z
day: '25'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.1186/s13068-015-0380-2
file:
- access_level: open_access
checksum: 172b0b6f4eb2e5c22b7cec1d57dc0107
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:10:11Z
date_updated: 2020-07-14T12:45:07Z
file_id: '4796'
file_name: IST-2016-467-v1+1_s13068-015-0380-2.pdf
file_size: 2914089
relation: main_file
file_date_updated: 2020-07-14T12:45:07Z
has_accepted_license: '1'
intvolume: ' 8'
issue: '1'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
publication: Biotechnology for Biofuels
publication_status: published
publisher: BioMed Central
publist_id: '5537'
pubrep_id: '467'
quality_controlled: '1'
scopus_import: 1
status: public
title: Single-cell screening of photosynthetic growth and lactate production by cyanobacteria
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 8
year: '2015'
...
---
_id: '1810'
abstract:
- lang: eng
text: Combining antibiotics is a promising strategy for increasing treatment efficacy
and for controlling resistance evolution. When drugs are combined, their effects
on cells may be amplified or weakened, that is the drugs may show synergistic
or antagonistic interactions. Recent work revealed the underlying mechanisms of
such drug interactions by elucidating the drugs'; joint effects on cell physiology.
Moreover, new treatment strategies that use drug combinations to exploit evolutionary
tradeoffs were shown to affect the rate of resistance evolution in predictable
ways. High throughput studies have further identified drug candidates based on
their interactions with established antibiotics and general principles that enable
the prediction of drug interactions were suggested. Overall, the conceptual and
technical foundation for the rational design of potent drug combinations is rapidly
developing.
author:
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: 'Bollenbach MT. Antimicrobial interactions: Mechanisms and implications for
drug discovery and resistance evolution. Current Opinion in Microbiology.
2015;27:1-9. doi:10.1016/j.mib.2015.05.008'
apa: 'Bollenbach, M. T. (2015). Antimicrobial interactions: Mechanisms and implications
for drug discovery and resistance evolution. Current Opinion in Microbiology.
Elsevier. https://doi.org/10.1016/j.mib.2015.05.008'
chicago: 'Bollenbach, Mark Tobias. “Antimicrobial Interactions: Mechanisms and Implications
for Drug Discovery and Resistance Evolution.” Current Opinion in Microbiology.
Elsevier, 2015. https://doi.org/10.1016/j.mib.2015.05.008.'
ieee: 'M. T. Bollenbach, “Antimicrobial interactions: Mechanisms and implications
for drug discovery and resistance evolution,” Current Opinion in Microbiology,
vol. 27. Elsevier, pp. 1–9, 2015.'
ista: 'Bollenbach MT. 2015. Antimicrobial interactions: Mechanisms and implications
for drug discovery and resistance evolution. Current Opinion in Microbiology.
27, 1–9.'
mla: 'Bollenbach, Mark Tobias. “Antimicrobial Interactions: Mechanisms and Implications
for Drug Discovery and Resistance Evolution.” Current Opinion in Microbiology,
vol. 27, Elsevier, 2015, pp. 1–9, doi:10.1016/j.mib.2015.05.008.'
short: M.T. Bollenbach, Current Opinion in Microbiology 27 (2015) 1–9.
date_created: 2018-12-11T11:54:08Z
date_published: 2015-06-01T00:00:00Z
date_updated: 2021-01-12T06:53:21Z
day: '01'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.1016/j.mib.2015.05.008
ec_funded: 1
file:
- access_level: open_access
checksum: 1683bb0f42ef892a5b3b71a050d65d25
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:17:23Z
date_updated: 2020-07-14T12:45:17Z
file_id: '5277'
file_name: IST-2016-493-v1+1_1-s2.0-S1369527415000594-main.pdf
file_size: 1047255
relation: main_file
file_date_updated: 2020-07-14T12:45:17Z
has_accepted_license: '1'
intvolume: ' 27'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
page: 1 - 9
project:
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
- _id: 25E83C2C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '303507'
name: Optimality principles in responses to antibiotics
- _id: 25EB3A80-B435-11E9-9278-68D0E5697425
grant_number: RGP0042/2013
name: Revealing the fundamental limits of cell growth
publication: Current Opinion in Microbiology
publication_status: published
publisher: Elsevier
publist_id: '5298'
pubrep_id: '493'
quality_controlled: '1'
scopus_import: 1
status: public
title: 'Antimicrobial interactions: Mechanisms and implications for drug discovery
and resistance evolution'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 27
year: '2015'
...
---
_id: '1823'
abstract:
- lang: eng
text: Abstract Drug combinations are increasingly important in disease treatments,
for combating drug resistance, and for elucidating fundamental relationships in
cell physiology. When drugs are combined, their individual effects on cells may
be amplified or weakened. Such drug interactions are crucial for treatment efficacy,
but their underlying mechanisms remain largely unknown. To uncover the causes
of drug interactions, we developed a systematic approach based on precise quantification
of the individual and joint effects of antibiotics on growth of genome-wide Escherichia
coli gene deletion strains. We found that drug interactions between antibiotics
representing the main modes of action are highly robust to genetic perturbation.
This robustness is encapsulated in a general principle of bacterial growth, which
enables the quantitative prediction of mutant growth rates under drug combinations.
Rare violations of this principle exposed recurring cellular functions controlling
drug interactions. In particular, we found that polysaccharide and ATP synthesis
control multiple drug interactions with previously unexplained mechanisms, and
small molecule adjuvants targeting these functions synthetically reshape drug
interactions in predictable ways. These results provide a new conceptual framework
for the design of multidrug combinations and suggest that there are universal
mechanisms at the heart of most drug interactions. Synopsis A general principle
of bacterial growth enables the prediction of mutant growth rates under drug combinations.
Rare violations of this principle expose cellular functions that control drug
interactions and can be targeted by small molecules to alter drug interactions
in predictable ways. Drug interactions between antibiotics are highly robust to
genetic perturbations. A general principle of bacterial growth enables the prediction
of mutant growth rates under drug combinations. Rare violations of this principle
expose cellular functions that control drug interactions. Diverse drug interactions
are controlled by recurring cellular functions, including LPS synthesis and ATP
synthesis. A general principle of bacterial growth enables the prediction of mutant
growth rates under drug combinations. Rare violations of this principle expose
cellular functions that control drug interactions and can be targeted by small
molecules to alter drug interactions in predictable ways.
article_number: '807'
author:
- first_name: Guillaume
full_name: Chevereau, Guillaume
id: 424D78A0-F248-11E8-B48F-1D18A9856A87
last_name: Chevereau
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Chevereau G, Bollenbach MT. Systematic discovery of drug interaction mechanisms.
Molecular Systems Biology. 2015;11(4). doi:10.15252/msb.20156098
apa: Chevereau, G., & Bollenbach, M. T. (2015). Systematic discovery of drug
interaction mechanisms. Molecular Systems Biology. Nature Publishing Group.
https://doi.org/10.15252/msb.20156098
chicago: Chevereau, Guillaume, and Mark Tobias Bollenbach. “Systematic Discovery
of Drug Interaction Mechanisms.” Molecular Systems Biology. Nature Publishing
Group, 2015. https://doi.org/10.15252/msb.20156098.
ieee: G. Chevereau and M. T. Bollenbach, “Systematic discovery of drug interaction
mechanisms,” Molecular Systems Biology, vol. 11, no. 4. Nature Publishing
Group, 2015.
ista: Chevereau G, Bollenbach MT. 2015. Systematic discovery of drug interaction
mechanisms. Molecular Systems Biology. 11(4), 807.
mla: Chevereau, Guillaume, and Mark Tobias Bollenbach. “Systematic Discovery of
Drug Interaction Mechanisms.” Molecular Systems Biology, vol. 11, no. 4,
807, Nature Publishing Group, 2015, doi:10.15252/msb.20156098.
short: G. Chevereau, M.T. Bollenbach, Molecular Systems Biology 11 (2015).
date_created: 2018-12-11T11:54:12Z
date_published: 2015-04-01T00:00:00Z
date_updated: 2021-01-12T06:53:26Z
day: '01'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.15252/msb.20156098
ec_funded: 1
file:
- access_level: open_access
checksum: 4289b518fbe2166682fb1a1ef9b405f3
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:14:34Z
date_updated: 2020-07-14T12:45:17Z
file_id: '5087'
file_name: IST-2015-395-v1+1_807.full.pdf
file_size: 1273573
relation: main_file
file_date_updated: 2020-07-14T12:45:17Z
has_accepted_license: '1'
intvolume: ' 11'
issue: '4'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
project:
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
- _id: 25EB3A80-B435-11E9-9278-68D0E5697425
grant_number: RGP0042/2013
name: Revealing the fundamental limits of cell growth
- _id: 25E83C2C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '303507'
name: Optimality principles in responses to antibiotics
publication: Molecular Systems Biology
publication_status: published
publisher: Nature Publishing Group
publist_id: '5283'
pubrep_id: '395'
quality_controlled: '1'
scopus_import: 1
status: public
title: Systematic discovery of drug interaction mechanisms
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 11
year: '2015'
...
---
_id: '9711'
article_processing_charge: No
author:
- first_name: Guillaume
full_name: Chevereau, Guillaume
id: 424D78A0-F248-11E8-B48F-1D18A9856A87
last_name: Chevereau
- first_name: Marta
full_name: Lukacisinova, Marta
id: 4342E402-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisinova
orcid: 0000-0002-2519-8004
- first_name: Tugce
full_name: Batur, Tugce
last_name: Batur
- first_name: Aysegul
full_name: Guvenek, Aysegul
last_name: Guvenek
- first_name: Dilay Hazal
full_name: Ayhan, Dilay Hazal
last_name: Ayhan
- first_name: Erdal
full_name: Toprak, Erdal
last_name: Toprak
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Chevereau G, Lukacisinova M, Batur T, et al. Excel file containing the raw
data for all figures. 2015. doi:10.1371/journal.pbio.1002299.s001
apa: Chevereau, G., Lukacisinova, M., Batur, T., Guvenek, A., Ayhan, D. H., Toprak,
E., & Bollenbach, M. T. (2015). Excel file containing the raw data for all
figures. Public Library of Science. https://doi.org/10.1371/journal.pbio.1002299.s001
chicago: Chevereau, Guillaume, Marta Lukacisinova, Tugce Batur, Aysegul Guvenek,
Dilay Hazal Ayhan, Erdal Toprak, and Mark Tobias Bollenbach. “Excel File Containing
the Raw Data for All Figures.” Public Library of Science, 2015. https://doi.org/10.1371/journal.pbio.1002299.s001.
ieee: G. Chevereau et al., “Excel file containing the raw data for all figures.”
Public Library of Science, 2015.
ista: Chevereau G, Lukacisinova M, Batur T, Guvenek A, Ayhan DH, Toprak E, Bollenbach
MT. 2015. Excel file containing the raw data for all figures, Public Library of
Science, 10.1371/journal.pbio.1002299.s001.
mla: Chevereau, Guillaume, et al. Excel File Containing the Raw Data for All
Figures. Public Library of Science, 2015, doi:10.1371/journal.pbio.1002299.s001.
short: G. Chevereau, M. Lukacisinova, T. Batur, A. Guvenek, D.H. Ayhan, E. Toprak,
M.T. Bollenbach, (2015).
date_created: 2021-07-23T11:53:50Z
date_published: 2015-11-18T00:00:00Z
date_updated: 2023-02-23T10:07:02Z
day: '18'
department:
- _id: ToBo
doi: 10.1371/journal.pbio.1002299.s001
month: '11'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '1619'
relation: used_in_publication
status: public
status: public
title: Excel file containing the raw data for all figures
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2015'
...
---
_id: '9765'
article_processing_charge: No
author:
- first_name: Guillaume
full_name: Chevereau, Guillaume
id: 424D78A0-F248-11E8-B48F-1D18A9856A87
last_name: Chevereau
- first_name: Marta
full_name: Lukacisinova, Marta
id: 4342E402-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisinova
orcid: 0000-0002-2519-8004
- first_name: Tugce
full_name: Batur, Tugce
last_name: Batur
- first_name: Aysegul
full_name: Guvenek, Aysegul
last_name: Guvenek
- first_name: Dilay Hazal
full_name: Ayhan, Dilay Hazal
last_name: Ayhan
- first_name: Erdal
full_name: Toprak, Erdal
last_name: Toprak
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Chevereau G, Lukacisinova M, Batur T, et al. Gene ontology enrichment analysis
for the most sensitive gene deletion strains for all drugs. 2015. doi:10.1371/journal.pbio.1002299.s008
apa: Chevereau, G., Lukacisinova, M., Batur, T., Guvenek, A., Ayhan, D. H., Toprak,
E., & Bollenbach, M. T. (2015). Gene ontology enrichment analysis for the
most sensitive gene deletion strains for all drugs. Public Library of Science.
https://doi.org/10.1371/journal.pbio.1002299.s008
chicago: Chevereau, Guillaume, Marta Lukacisinova, Tugce Batur, Aysegul Guvenek,
Dilay Hazal Ayhan, Erdal Toprak, and Mark Tobias Bollenbach. “Gene Ontology Enrichment
Analysis for the Most Sensitive Gene Deletion Strains for All Drugs.” Public Library
of Science, 2015. https://doi.org/10.1371/journal.pbio.1002299.s008.
ieee: G. Chevereau et al., “Gene ontology enrichment analysis for the most
sensitive gene deletion strains for all drugs.” Public Library of Science, 2015.
ista: Chevereau G, Lukacisinova M, Batur T, Guvenek A, Ayhan DH, Toprak E, Bollenbach
MT. 2015. Gene ontology enrichment analysis for the most sensitive gene deletion
strains for all drugs, Public Library of Science, 10.1371/journal.pbio.1002299.s008.
mla: Chevereau, Guillaume, et al. Gene Ontology Enrichment Analysis for the Most
Sensitive Gene Deletion Strains for All Drugs. Public Library of Science,
2015, doi:10.1371/journal.pbio.1002299.s008.
short: G. Chevereau, M. Lukacisinova, T. Batur, A. Guvenek, D.H. Ayhan, E. Toprak,
M.T. Bollenbach, (2015).
date_created: 2021-08-03T07:05:16Z
date_published: 2015-11-18T00:00:00Z
date_updated: 2023-02-23T10:07:02Z
day: '18'
department:
- _id: ToBo
doi: 10.1371/journal.pbio.1002299.s008
month: '11'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '1619'
relation: used_in_publication
status: public
status: public
title: Gene ontology enrichment analysis for the most sensitive gene deletion strains
for all drugs
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2015'
...
---
_id: '1509'
abstract:
- lang: eng
text: The Auxin Binding Protein1 (ABP1) has been identified based on its ability
to bind auxin with high affinity and studied for a long time as a prime candidate
for the extracellular auxin receptor responsible for mediating in particular the
fast non-transcriptional auxin responses. However, the contradiction between the
embryo-lethal phenotypes of the originally described Arabidopsis T-DNA insertional
knock-out alleles (abp1-1 and abp1-1s) and the wild type-like phenotypes of other
recently described loss-of-function alleles (abp1-c1 and abp1-TD1) questions the
biological importance of ABP1 and relevance of the previous genetic studies. Here
we show that there is no hidden copy of the ABP1 gene in the Arabidopsis genome
but the embryo-lethal phenotypes of abp1-1 and abp1-1s alleles are very similar
to the knock-out phenotypes of the neighboring gene, BELAYA SMERT (BSM). Furthermore,
the allelic complementation test between bsm and abp1 alleles shows that the embryo-lethality
in the abp1-1 and abp1-1s alleles is caused by the off-target disruption of the
BSM locus by the T-DNA insertions. This clarifies the controversy of different
phenotypes among published abp1 knock-out alleles and asks for reflections on
the developmental role of ABP1.
acknowledgement: "This work was supported by ERC Independent Research grant (ERC-2011-StG-20101109-PSDP
to JF). JM internship was supported by the grant “Action Austria – Slovakia”.\r\nData
associated with the article are available under the terms of the Creative Commons
Zero \"No rights reserved\" data waiver (CC0 1.0 Public domain dedication). \r\n\r\nData
availability: \r\nF1000Research: Dataset 1. Dataset 1, 10.5256/f1000research.7143.d104552\r\n\r\nF1000Research:
Dataset 2. Dataset 2, 10.5256/f1000research.7143.d104553\r\n\r\nF1000Research: Dataset
3. Dataset 3, 10.5256/f1000research.7143.d104554"
article_processing_charge: No
author:
- first_name: Jaroslav
full_name: Michalko, Jaroslav
id: 483727CA-F248-11E8-B48F-1D18A9856A87
last_name: Michalko
- first_name: Marta
full_name: Dravecka, Marta
id: 4342E402-F248-11E8-B48F-1D18A9856A87
last_name: Dravecka
orcid: 0000-0002-2519-8004
- first_name: Tobias
full_name: Bollenbach, Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
- first_name: Jirí
full_name: Friml, Jirí
id: 4159519E-F248-11E8-B48F-1D18A9856A87
last_name: Friml
orcid: 0000-0002-8302-7596
citation:
ama: Michalko J, Lukacisinova M, Bollenbach MT, Friml J. Embryo-lethal phenotypes
in early abp1 mutants are due to disruption of the neighboring BSM gene. F1000
Research . 2015;4. doi:10.12688/f1000research.7143.1
apa: Michalko, J., Lukacisinova, M., Bollenbach, M. T., & Friml, J. (2015).
Embryo-lethal phenotypes in early abp1 mutants are due to disruption of the neighboring
BSM gene. F1000 Research . F1000 Research. https://doi.org/10.12688/f1000research.7143.1
chicago: Michalko, Jaroslav, Marta Lukacisinova, Mark Tobias Bollenbach, and Jiří
Friml. “Embryo-Lethal Phenotypes in Early Abp1 Mutants Are Due to Disruption of
the Neighboring BSM Gene.” F1000 Research . F1000 Research, 2015. https://doi.org/10.12688/f1000research.7143.1.
ieee: J. Michalko, M. Lukacisinova, M. T. Bollenbach, and J. Friml, “Embryo-lethal
phenotypes in early abp1 mutants are due to disruption of the neighboring BSM
gene,” F1000 Research , vol. 4. F1000 Research, 2015.
ista: Michalko J, Lukacisinova M, Bollenbach MT, Friml J. 2015. Embryo-lethal phenotypes
in early abp1 mutants are due to disruption of the neighboring BSM gene. F1000
Research . 4.
mla: Michalko, Jaroslav, et al. “Embryo-Lethal Phenotypes in Early Abp1 Mutants
Are Due to Disruption of the Neighboring BSM Gene.” F1000 Research , vol.
4, F1000 Research, 2015, doi:10.12688/f1000research.7143.1.
short: J. Michalko, M. Lukacisinova, M.T. Bollenbach, J. Friml, F1000 Research 4
(2015).
date_created: 2018-12-11T11:52:26Z
date_published: 2015-10-01T00:00:00Z
date_updated: 2023-10-10T14:10:24Z
day: '01'
ddc:
- '570'
department:
- _id: JiFr
- _id: ToBo
doi: 10.12688/f1000research.7143.1
ec_funded: 1
file:
- access_level: open_access
checksum: 8beae5cbe988e1060265ae7de2ee8306
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:16:12Z
date_updated: 2020-07-14T12:44:59Z
file_id: '5198'
file_name: IST-2016-497-v1+1_10.12688_f1000research.7143.1_20151102.pdf
file_size: 4414248
relation: main_file
file_date_updated: 2020-07-14T12:44:59Z
has_accepted_license: '1'
intvolume: ' 4'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
project:
- _id: 25716A02-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '282300'
name: Polarity and subcellular dynamics in plants
publication: 'F1000 Research '
publication_status: published
publisher: F1000 Research
publist_id: '5668'
pubrep_id: '497'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Embryo-lethal phenotypes in early abp1 mutants are due to disruption of the
neighboring BSM gene
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 4
year: '2015'
...
---
_id: '1619'
abstract:
- lang: eng
text: The emergence of drug resistant pathogens is a serious public health problem.
It is a long-standing goal to predict rates of resistance evolution and design
optimal treatment strategies accordingly. To this end, it is crucial to reveal
the underlying causes of drug-specific differences in the evolutionary dynamics
leading to resistance. However, it remains largely unknown why the rates of resistance
evolution via spontaneous mutations and the diversity of mutational paths vary
substantially between drugs. Here we comprehensively quantify the distribution
of fitness effects (DFE) of mutations, a key determinant of evolutionary dynamics,
in the presence of eight antibiotics representing the main modes of action. Using
precise high-throughput fitness measurements for genome-wide Escherichia coli
gene deletion strains, we find that the width of the DFE varies dramatically between
antibiotics and, contrary to conventional wisdom, for some drugs the DFE width
is lower than in the absence of stress. We show that this previously underappreciated
divergence in DFE width among antibiotics is largely caused by their distinct
drug-specific dose-response characteristics. Unlike the DFE, the magnitude of
the changes in tolerated drug concentration resulting from genome-wide mutations
is similar for most drugs but exceptionally small for the antibiotic nitrofurantoin,
i.e., mutations generally have considerably smaller resistance effects for nitrofurantoin
than for other drugs. A population genetics model predicts that resistance evolution
for drugs with this property is severely limited and confined to reproducible
mutational paths. We tested this prediction in laboratory evolution experiments
using the “morbidostat”, a device for evolving bacteria in well-controlled drug
environments. Nitrofurantoin resistance indeed evolved extremely slowly via reproducible
mutations—an almost paradoxical behavior since this drug causes DNA damage and
increases the mutation rate. Overall, we identified novel quantitative characteristics
of the evolutionary landscape that provide the conceptual foundation for predicting
the dynamics of drug resistance evolution.
article_number: e1002299
author:
- first_name: Guillaume
full_name: Chevereau, Guillaume
id: 424D78A0-F248-11E8-B48F-1D18A9856A87
last_name: Chevereau
- first_name: Marta
full_name: Dravecka, Marta
id: 4342E402-F248-11E8-B48F-1D18A9856A87
last_name: Dravecka
orcid: 0000-0002-2519-8004
- first_name: Tugce
full_name: Batur, Tugce
last_name: Batur
- first_name: Aysegul
full_name: Guvenek, Aysegul
last_name: Guvenek
- first_name: Dilay
full_name: Ayhan, Dilay
last_name: Ayhan
- first_name: Erdal
full_name: Toprak, Erdal
last_name: Toprak
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Chevereau G, Lukacisinova M, Batur T, et al. Quantifying the determinants of
evolutionary dynamics leading to drug resistance. PLoS Biology. 2015;13(11).
doi:10.1371/journal.pbio.1002299
apa: Chevereau, G., Lukacisinova, M., Batur, T., Guvenek, A., Ayhan, D., Toprak,
E., & Bollenbach, M. T. (2015). Quantifying the determinants of evolutionary
dynamics leading to drug resistance. PLoS Biology. Public Library of Science.
https://doi.org/10.1371/journal.pbio.1002299
chicago: Chevereau, Guillaume, Marta Lukacisinova, Tugce Batur, Aysegul Guvenek,
Dilay Ayhan, Erdal Toprak, and Mark Tobias Bollenbach. “Quantifying the Determinants
of Evolutionary Dynamics Leading to Drug Resistance.” PLoS Biology. Public
Library of Science, 2015. https://doi.org/10.1371/journal.pbio.1002299.
ieee: G. Chevereau et al., “Quantifying the determinants of evolutionary
dynamics leading to drug resistance,” PLoS Biology, vol. 13, no. 11. Public
Library of Science, 2015.
ista: Chevereau G, Lukacisinova M, Batur T, Guvenek A, Ayhan D, Toprak E, Bollenbach
MT. 2015. Quantifying the determinants of evolutionary dynamics leading to drug
resistance. PLoS Biology. 13(11), e1002299.
mla: Chevereau, Guillaume, et al. “Quantifying the Determinants of Evolutionary
Dynamics Leading to Drug Resistance.” PLoS Biology, vol. 13, no. 11, e1002299,
Public Library of Science, 2015, doi:10.1371/journal.pbio.1002299.
short: G. Chevereau, M. Lukacisinova, T. Batur, A. Guvenek, D. Ayhan, E. Toprak,
M.T. Bollenbach, PLoS Biology 13 (2015).
date_created: 2018-12-11T11:53:04Z
date_published: 2015-11-18T00:00:00Z
date_updated: 2024-03-27T23:30:28Z
day: '18'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.1371/journal.pbio.1002299
ec_funded: 1
file:
- access_level: open_access
checksum: 0e82e3279f50b15c6c170c042627802b
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:09:00Z
date_updated: 2020-07-14T12:45:07Z
file_id: '4723'
file_name: IST-2016-468-v1+1_journal.pbio.1002299.pdf
file_size: 1387760
relation: main_file
file_date_updated: 2020-07-14T12:45:07Z
has_accepted_license: '1'
intvolume: ' 13'
issue: '11'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
project:
- _id: 25EB3A80-B435-11E9-9278-68D0E5697425
grant_number: RGP0042/2013
name: Revealing the fundamental limits of cell growth
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
- _id: 25E83C2C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '303507'
name: Optimality principles in responses to antibiotics
publication: PLoS Biology
publication_status: published
publisher: Public Library of Science
publist_id: '5547'
pubrep_id: '468'
quality_controlled: '1'
related_material:
record:
- id: '9711'
relation: research_data
status: public
- id: '9765'
relation: research_data
status: public
- id: '6263'
relation: dissertation_contains
status: public
scopus_import: 1
status: public
title: Quantifying the determinants of evolutionary dynamics leading to drug resistance
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2015'
...