---
_id: '12261'
abstract:
- lang: eng
text: 'Dose–response relationships are a general concept for quantitatively describing
biological systems across multiple scales, from the molecular to the whole-cell
level. A clinically relevant example is the bacterial growth response to antibiotics,
which is routinely characterized by dose–response curves. The shape of the dose–response
curve varies drastically between antibiotics and plays a key role in treatment,
drug interactions, and resistance evolution. However, the mechanisms shaping the
dose–response curve remain largely unclear. Here, we show in Escherichia coli
that the distinctively shallow dose–response curve of the antibiotic trimethoprim
is caused by a negative growth-mediated feedback loop: Trimethoprim slows growth,
which in turn weakens the effect of this antibiotic. At the molecular level, this
feedback is caused by the upregulation of the drug target dihydrofolate reductase
(FolA/DHFR). We show that this upregulation is not a specific response to trimethoprim
but follows a universal trend line that depends primarily on the growth rate,
irrespective of its cause. Rewiring the feedback loop alters the dose–response
curve in a predictable manner, which we corroborate using a mathematical model
of cellular resource allocation and growth. Our results indicate that growth-mediated
feedback loops may shape drug responses more generally and could be exploited
to design evolutionary traps that enable selection against drug resistance.'
acknowledged_ssus:
- _id: M-Shop
acknowledgement: This work was in part supported by Human Frontier Science Program
GrantRGP0042/2013, Marie Curie Career Integration Grant303507, AustrianScience Fund
(FWF) Grant P27201-B22, and German Research Foundation(DFG) Collaborative Research
Center (SFB)1310to TB. SAA was supportedby the European Union’s Horizon2020Research
and Innovation Programunder the Marie Skłodowska-Curie Grant agreement No707352.
We wouldlike to thank the Bollenbach group for regular fruitful discussions. We
areparticularly thankful for the technical assistance of Booshini Fernando andfor
discussions of the theoretical aspects with Gerrit Ansmann. We areindebted to Bor
Kavˇciˇc for invaluable advice, help with setting up theluciferase-based growth
monitoring system, and for sharing plasmids. Weacknowledge the IST Austria Miba
Machine Shop for their support inbuilding a housing for the stacker of the plate
reader, which enabled thehigh-throughput luciferase-based experiments. We are grateful
to RosalindAllen, Bor Kavˇciˇc and Dor Russ for feedback on the manuscript. Open
Accessfunding enabled and organized by Projekt DEAL.
article_number: e10490
article_processing_charge: No
article_type: original
author:
- first_name: Andreas
full_name: Angermayr, Andreas
id: 4677C796-F248-11E8-B48F-1D18A9856A87
last_name: Angermayr
orcid: 0000-0001-8619-2223
- first_name: Tin Yau
full_name: Pang, Tin Yau
last_name: Pang
- first_name: Guillaume
full_name: Chevereau, Guillaume
last_name: Chevereau
- first_name: Karin
full_name: Mitosch, Karin
id: 39B66846-F248-11E8-B48F-1D18A9856A87
last_name: Mitosch
- first_name: Martin J
full_name: Lercher, Martin J
last_name: Lercher
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Angermayr A, Pang TY, Chevereau G, Mitosch K, Lercher MJ, Bollenbach MT. Growth‐mediated
negative feedback shapes quantitative antibiotic response. Molecular Systems
Biology. 2022;18(9). doi:10.15252/msb.202110490
apa: Angermayr, A., Pang, T. Y., Chevereau, G., Mitosch, K., Lercher, M. J., &
Bollenbach, M. T. (2022). Growth‐mediated negative feedback shapes quantitative
antibiotic response. Molecular Systems Biology. Embo Press. https://doi.org/10.15252/msb.202110490
chicago: Angermayr, Andreas, Tin Yau Pang, Guillaume Chevereau, Karin Mitosch, Martin
J Lercher, and Mark Tobias Bollenbach. “Growth‐mediated Negative Feedback Shapes
Quantitative Antibiotic Response.” Molecular Systems Biology. Embo Press,
2022. https://doi.org/10.15252/msb.202110490.
ieee: A. Angermayr, T. Y. Pang, G. Chevereau, K. Mitosch, M. J. Lercher, and M.
T. Bollenbach, “Growth‐mediated negative feedback shapes quantitative antibiotic
response,” Molecular Systems Biology, vol. 18, no. 9. Embo Press, 2022.
ista: Angermayr A, Pang TY, Chevereau G, Mitosch K, Lercher MJ, Bollenbach MT. 2022.
Growth‐mediated negative feedback shapes quantitative antibiotic response. Molecular
Systems Biology. 18(9), e10490.
mla: Angermayr, Andreas, et al. “Growth‐mediated Negative Feedback Shapes Quantitative
Antibiotic Response.” Molecular Systems Biology, vol. 18, no. 9, e10490,
Embo Press, 2022, doi:10.15252/msb.202110490.
short: A. Angermayr, T.Y. Pang, G. Chevereau, K. Mitosch, M.J. Lercher, M.T. Bollenbach,
Molecular Systems Biology 18 (2022).
date_created: 2023-01-16T09:58:34Z
date_published: 2022-09-01T00:00:00Z
date_updated: 2023-08-04T09:51:49Z
day: '01'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.15252/msb.202110490
external_id:
isi:
- '000856482800001'
file:
- access_level: open_access
checksum: 8b1d8f5ea20c8408acf466435fb6ae01
content_type: application/pdf
creator: dernst
date_created: 2023-01-30T09:49:55Z
date_updated: 2023-01-30T09:49:55Z
file_id: '12446'
file_name: 2022_MolecularSystemsBio_Angermayr.pdf
file_size: 1098812
relation: main_file
success: 1
file_date_updated: 2023-01-30T09:49:55Z
has_accepted_license: '1'
intvolume: ' 18'
isi: 1
issue: '9'
keyword:
- Applied Mathematics
- Computational Theory and Mathematics
- General Agricultural and Biological Sciences
- General Immunology and Microbiology
- General Biochemistry
- Genetics and Molecular Biology
- Information Systems
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
publication: Molecular Systems Biology
publication_identifier:
eissn:
- 1744-4292
publication_status: published
publisher: Embo Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Growth‐mediated negative feedback shapes quantitative antibiotic response
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 18
year: '2022'
...
---
_id: '7026'
abstract:
- lang: eng
text: Effective design of combination therapies requires understanding the changes
in cell physiology that result from drug interactions. Here, we show that the
genome-wide transcriptional response to combinations of two drugs, measured at
a rigorously controlled growth rate, can predict higher-order antagonism with
a third drug in Saccharomyces cerevisiae. Using isogrowth profiling, over 90%
of the variation in cellular response can be decomposed into three principal components
(PCs) that have clear biological interpretations. We demonstrate that the third
PC captures emergent transcriptional programs that are dependent on both drugs
and can predict antagonism with a third drug targeting the emergent pathway. We
further show that emergent gene expression patterns are most pronounced at a drug
ratio where the drug interaction is strongest, providing a guideline for future
measurements. Our results provide a readily applicable recipe for uncovering emergent
responses in other systems and for higher-order drug combinations. A record of
this paper’s transparent peer review process is included in the Supplemental Information.
acknowledged_ssus:
- _id: LifeSc
article_processing_charge: No
article_type: original
author:
- first_name: Martin
full_name: Lukacisin, Martin
id: 298FFE8C-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisin
orcid: 0000-0001-6549-4177
- first_name: Tobias
full_name: Bollenbach, Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Lukacisin M, Bollenbach MT. Emergent gene expression responses to drug combinations
predict higher-order drug interactions. Cell Systems. 2019;9(5):423-433.e1-e3.
doi:10.1016/j.cels.2019.10.004
apa: Lukacisin, M., & Bollenbach, M. T. (2019). Emergent gene expression responses
to drug combinations predict higher-order drug interactions. Cell Systems.
Cell Press. https://doi.org/10.1016/j.cels.2019.10.004
chicago: Lukacisin, Martin, and Mark Tobias Bollenbach. “Emergent Gene Expression
Responses to Drug Combinations Predict Higher-Order Drug Interactions.” Cell
Systems. Cell Press, 2019. https://doi.org/10.1016/j.cels.2019.10.004.
ieee: M. Lukacisin and M. T. Bollenbach, “Emergent gene expression responses to
drug combinations predict higher-order drug interactions,” Cell Systems,
vol. 9, no. 5. Cell Press, pp. 423-433.e1-e3, 2019.
ista: Lukacisin M, Bollenbach MT. 2019. Emergent gene expression responses to drug
combinations predict higher-order drug interactions. Cell Systems. 9(5), 423-433.e1-e3.
mla: Lukacisin, Martin, and Mark Tobias Bollenbach. “Emergent Gene Expression Responses
to Drug Combinations Predict Higher-Order Drug Interactions.” Cell Systems,
vol. 9, no. 5, Cell Press, 2019, pp. 423-433.e1-e3, doi:10.1016/j.cels.2019.10.004.
short: M. Lukacisin, M.T. Bollenbach, Cell Systems 9 (2019) 423-433.e1-e3.
date_created: 2019-11-15T10:51:42Z
date_published: 2019-11-27T00:00:00Z
date_updated: 2023-08-30T07:24:58Z
day: '27'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.1016/j.cels.2019.10.004
external_id:
isi:
- '000499495400003'
file:
- access_level: open_access
checksum: 7a11d6c2f9523d65b049512d61733178
content_type: application/pdf
creator: dernst
date_created: 2019-11-15T10:57:42Z
date_updated: 2020-07-14T12:47:48Z
file_id: '7027'
file_name: 2019_CellSystems_Lukacisin.pdf
file_size: 4238460
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file_date_updated: 2020-07-14T12:47:48Z
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intvolume: ' 9'
isi: 1
issue: '5'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
page: 423-433.e1-e3
project:
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
- _id: 25EB3A80-B435-11E9-9278-68D0E5697425
grant_number: RGP0042/2013
name: Revealing the fundamental limits of cell growth
publication: Cell Systems
publication_identifier:
issn:
- 2405-4712
publication_status: published
publisher: Cell Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Emergent gene expression responses to drug combinations predict higher-order
drug interactions
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 9
year: '2019'
...
---
_id: '6392'
abstract:
- lang: eng
text: "The regulation of gene expression is one of the most fundamental processes
in living systems. In recent years, thanks to advances in sequencing technology
and automation, it has become possible to study gene expression quantitatively,
genome-wide and in high-throughput. This leads to the possibility of exploring
changes in gene expression in the context of many external perturbations and their
combinations, and thus of characterising the basic principles governing gene regulation.
In this thesis, I present quantitative experimental approaches to studying transcriptional
and protein level changes in response to combinatorial drug treatment, as well
as a theoretical data-driven approach to analysing thermodynamic principles guiding
transcription of protein coding genes. \r\nIn the first part of this work, I
present a novel methodological framework for quantifying gene expression changes
in drug combinations, termed isogrowth profiling. External perturbations through
small molecule drugs influence the growth rate of the cell, leading to wide-ranging
changes in cellular physiology and gene expression. This confounds the gene expression
changes specifically elicited by the particular drug. Combinatorial perturbations,
owing to the increased stress they exert, influence the growth rate even more
strongly and hence suffer the convolution problem to a greater extent when measuring
gene expression changes. Isogrowth profiling is a way to experimentally abstract
non-specific, growth rate related changes, by performing the measurement using
varying ratios of two drugs at such concentrations that the overall inhibition
rate is constant. Using a robotic setup for automated high-throughput re-dilution
culture of Saccharomyces cerevisiae, the budding yeast, I investigate all pairwise
interactions of four small molecule drugs through sequencing RNA along a growth
isobole. Through principal component analysis, I demonstrate here that isogrowth
profiling can uncover drug-specific as well as drug-interaction-specific gene
expression changes. I show that drug-interaction-specific gene expression changes
can be used for prediction of higher-order drug interactions. I propose a simplified
generalised framework of isogrowth profiling, with few measurements needed for
each drug pair, enabling the broad application of isogrowth profiling to high-throughput
screening of inhibitors of cellular growth and beyond. Such high-throughput screenings
of gene expression changes specific to pairwise drug interactions will be instrumental
for predicting the higher-order interactions of the drugs.\r\n\r\nIn the second
part of this work, I extend isogrowth profiling to single-cell measurements of
gene expression, characterising population heterogeneity in the budding yeast
in response to combinatorial drug perturbation while controlling for non-specific
growth rate effects. Through flow cytometry of strains with protein products fused
to green fluorescent protein, I discover multiple proteins with bi-modally distributed
expression levels in the population in response to drug treatment. I characterize
more closely the effect of an ionic stressor, lithium chloride, and find that
it inhibits the splicing of mRNA, most strongly affecting ribosomal protein transcripts
and leading to a bi-stable behaviour of a small ribosomal subunit protein Rps22B.
Time-lapse microscopy of a microfluidic culture system revealed that the induced
Rps22B heterogeneity leads to preferential survival of Rps22B-low cells after
long starvation, but to preferential proliferation of Rps22B-high cells after
short starvation. Overall, this suggests that yeast cells might use splicing of
ribosomal genes for bet-hedging in fluctuating environments. I give specific examples
of how further exploration of cellular heterogeneity in yeast in response to external
perturbation has the potential to reveal yet-undiscovered gene regulation circuitry.\r\n\r\nIn
the last part of this thesis, a re-analysis of a published sequencing dataset
of nascent elongating transcripts is used to characterise the thermodynamic constraints
for RNA polymerase II (RNAP) elongation. Population-level data on RNAP position
throughout the transcribed genome with single nucleotide resolution are used to
infer the sequence specific thermodynamic determinants of RNAP pausing and backtracking.
This analysis reveals that the basepairing strength of the eight nucleotide-long
RNA:DNA duplex relative to the basepairing strength of the same sequence when
in DNA:DNA duplex, and the change in this quantity during RNA polymerase movement,
is the key determinant of RNAP pausing. This is true for RNAP pausing while elongating,
but also of RNAP pausing while backtracking and of the backtracking length. The
quantitative dependence of RNAP pausing on basepairing energetics is used to infer
the increase in pausing due to transcriptional mismatches, leading to a hypothesis
that pervasive RNA polymerase II pausing is due to basepairing energetics, as
an evolutionary cost for increased RNA polymerase II fidelity.\r\n\r\nThis work
advances our understanding of the general principles governing gene expression,
with the goal of making computational predictions of single-cell gene expression
responses to combinatorial perturbations based on the individual perturbations
possible. This ability would substantially facilitate the design of drug combination
treatments and, in the long term, lead to our increased ability to more generally
design targeted manipulations to any biological system. "
acknowledged_ssus:
- _id: LifeSc
- _id: M-Shop
- _id: Bio
alternative_title:
- IST Austria Thesis
author:
- first_name: Martin
full_name: Lukacisin, Martin
id: 298FFE8C-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisin
orcid: 0000-0001-6549-4177
citation:
ama: Lukacisin M. Quantitative investigation of gene expression principles through
combinatorial drug perturbation and theory. 2019. doi:10.15479/AT:ISTA:6392
apa: Lukacisin, M. (2019). Quantitative investigation of gene expression principles
through combinatorial drug perturbation and theory. IST Austria. https://doi.org/10.15479/AT:ISTA:6392
chicago: Lukacisin, Martin. “Quantitative Investigation of Gene Expression Principles
through Combinatorial Drug Perturbation and Theory.” IST Austria, 2019. https://doi.org/10.15479/AT:ISTA:6392.
ieee: M. Lukacisin, “Quantitative investigation of gene expression principles through
combinatorial drug perturbation and theory,” IST Austria, 2019.
ista: Lukacisin M. 2019. Quantitative investigation of gene expression principles
through combinatorial drug perturbation and theory. IST Austria.
mla: Lukacisin, Martin. Quantitative Investigation of Gene Expression Principles
through Combinatorial Drug Perturbation and Theory. IST Austria, 2019, doi:10.15479/AT:ISTA:6392.
short: M. Lukacisin, Quantitative Investigation of Gene Expression Principles through
Combinatorial Drug Perturbation and Theory, IST Austria, 2019.
date_created: 2019-05-09T19:53:00Z
date_published: 2019-05-09T00:00:00Z
date_updated: 2023-09-22T09:19:41Z
day: '09'
ddc:
- '570'
department:
- _id: ToBo
doi: 10.15479/AT:ISTA:6392
extern: '1'
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content_type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
creator: mlukacisin
date_created: 2019-05-10T13:51:49Z
date_updated: 2020-07-14T12:47:29Z
embargo_to: open_access
file_id: '6409'
file_name: Thesis_Draft_v3.4Final.docx
file_size: 43740796
relation: hidden
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page: '103'
publication_identifier:
isbn:
- 978-3-99078-001-5
issn:
- 2663-337X
publication_status: published
publisher: IST Austria
related_material:
record:
- id: '1029'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
title: Quantitative investigation of gene expression principles through combinatorial
drug perturbation and theory
type: dissertation
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2019'
...
---
_id: '6263'
abstract:
- lang: eng
text: 'Antibiotic resistance can emerge spontaneously through genomic mutation and render
treatment ineffective. To counteract this process, in addition to the discovery and
description of resistance mechanisms,a deeper understanding of resistanceevolvabilityand
its determinantsis needed. To address this challenge, this thesisuncoversnew genetic
determinants of resistance evolvability using a customized robotic setup,
exploressystematic ways in which resistance evolution is perturbed due to
dose-responsecharacteristics of drugs and mutation rate differences,and mathematically investigates
the evolutionary fate of one specific type of evolvability modifier -a stress-induced
mutagenesis allele.We find severalgenes which strongly inhibit or potentiate resistance evolution. In order
to identify them, we first developedan automated high-throughput feedback-controlled
protocol whichkeeps the population size and selection pressure approximately constant
for hundreds of cultures by dynamically re-diluting the cultures and adjusting the antibiotic
concentration. We implementedthis protocol on a customized liquid handling robot and
propagated 100 different gene deletion strains of Escherichia coliin triplicate for over 100
generations in tetracycline and in chloramphenicol, and comparedtheir adaptation rates.We find a diminishing returns pattern, where initially sensitive strains adapted more
compared to less sensitive ones. Our data uncover that deletions of certain genes
which do not affect mutation rate,including efflux pump components, a chaperone and
severalstructural and regulatory genes can strongly and reproducibly alterresistance evolution.
Sequencing analysis of evolved populations indicates that epistasis with resistance
mutations is the most likelyexplanation. This work could inspire treatment strategies in
which targeted inhibitors of evolvability mechanisms will be given alongside antibiotics to
slow down resistance evolution and extend theefficacy of antibiotics.We implemented astochasticpopulation genetics model,
toverifyways in which general properties, namely, dose-response characteristics of drugs and mutation rates, influence
evolutionary dynamics. In particular, under the exposure to antibiotics with shallow dose-response curves,bacteria have narrower distributions of fitness effects of new mutations.
We show that in silicothis also leads to slower resistance evolution. We
see and confirm with experiments that increased mutation rates, apart from speeding
up evolution, also leadto high reproducibility of phenotypic adaptation in a context
of continually strong selection pressure.Knowledge of these patterns can aid in predicting the dynamics of antibiotic
resistance evolutionand adapting treatment schemes accordingly.Focusing on a previously described type of evolvability modifier
–a stress-induced mutagenesis allele –we find conditions under which it can persist in a population under
periodic selectionakin to clinical treatment. We set up a deterministic
infinite populationcontinuous time model tracking the frequencies of a mutator and resistance allele and
evaluate various treatment schemes in how well they maintain a stress-induced
mutator allele. In particular,a high diversity of stresses is crucial for the persistence
of the mutator allele. This leads to a general trade-off where exactly those
diversifying treatment schemes which are likely to decrease levels of resistance could lead to stronger selection of highly
evolvable genotypes.In the long run, this work will lead to a deeper understanding of the genetic and cellular
mechanisms involved in antibiotic resistance evolution and could inspire new strategies
for slowing down its rate. '
acknowledged_ssus:
- _id: M-Shop
- _id: LifeSc
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Marta
full_name: Lukacisinova, Marta
id: 4342E402-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisinova
orcid: 0000-0002-2519-8004
citation:
ama: Lukacisinova M. Genetic determinants of antibiotic resistance evolution. 2018.
doi:10.15479/AT:ISTA:th1072
apa: Lukacisinova, M. (2018). Genetic determinants of antibiotic resistance evolution.
Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th1072
chicago: Lukacisinova, Marta. “Genetic Determinants of Antibiotic Resistance Evolution.”
Institute of Science and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:th1072.
ieee: M. Lukacisinova, “Genetic determinants of antibiotic resistance evolution,”
Institute of Science and Technology Austria, 2018.
ista: Lukacisinova M. 2018. Genetic determinants of antibiotic resistance evolution.
Institute of Science and Technology Austria.
mla: Lukacisinova, Marta. Genetic Determinants of Antibiotic Resistance Evolution.
Institute of Science and Technology Austria, 2018, doi:10.15479/AT:ISTA:th1072.
short: M. Lukacisinova, Genetic Determinants of Antibiotic Resistance Evolution,
Institute of Science and Technology Austria, 2018.
date_created: 2019-04-09T13:57:15Z
date_published: 2018-12-28T00:00:00Z
date_updated: 2023-09-22T09:20:37Z
day: '28'
ddc:
- '570'
- '576'
- '579'
degree_awarded: PhD
department:
- _id: ToBo
doi: 10.15479/AT:ISTA:th1072
file:
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checksum: fc60585c9eaad868ac007004ef130908
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creator: dernst
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related_material:
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status: public
- id: '696'
relation: part_of_dissertation
status: public
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relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Tobias
full_name: Bollenbach, Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
title: Genetic determinants of antibiotic resistance evolution
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2018'
...
---
_id: '818'
abstract:
- lang: eng
text: 'Antibiotics have diverse effects on bacteria, including massive changes in
bacterial gene expression. Whereas the gene expression changes under many antibiotics
have been measured, the temporal organization of these responses and their dependence
on the bacterial growth rate are unclear. As described in Chapter 1, we quantified
the temporal gene expression changes in the bacterium Escherichia coli in response
to the sudden exposure to antibiotics using a fluorescent reporter library and
a robotic system. Our data show temporally structured gene expression responses,
with response times for individual genes ranging from tens of minutes to several
hours. We observed that many stress response genes were activated in response
to antibiotics. As certain stress responses cross-protect bacteria from other
stressors, we then asked whether cellular responses to antibiotics have a similar
protective role in Chapter 2. Indeed, we found that the trimethoprim-induced acid
stress response protects bacteria from subsequent acid stress. We combined microfluidics
with time-lapse imaging to monitor survival, intracellular pH, and acid stress
response in single cells. This approach revealed that the variable expression
of the acid resistance operon gadBC strongly correlates with single-cell survival
time. Cells with higher gadBC expression following trimethoprim maintain higher
intracellular pH and survive the acid stress longer. Overall, we provide a way
to identify single-cell cross-protection between antibiotics and environmental
stressors from temporal gene expression data, and show how antibiotics can increase
bacterial fitness in changing environments. While gene expression changes to antibiotics
show a clear temporal structure at the population-level, it is unclear whether
this clear temporal order is followed by every single cell. Using dual-reporter
strains described in Chapter 3, we measured gene expression dynamics of promoter
pairs in the same cells using microfluidics and microscopy. Chapter 4 shows that
the oxidative stress response and the DNA stress response showed little timing
variability and a clear temporal order under the antibiotic nitrofurantoin. In
contrast, the acid stress response under trimethoprim ran independently from all
other activated response programs including the DNA stress response, which showed
particularly high timing variability in this stress condition. In summary, this
approach provides insight into the temporal organization of gene expression programs
at the single-cell level and suggests dependencies between response programs and
the underlying variability-introducing mechanisms. Altogether, this work advances
our understanding of the diverse effects that antibiotics have on bacteria. These
results were obtained by taking into account gene expression dynamics, which allowed
us to identify general principles, molecular mechanisms, and dependencies between
genes. Our findings may have implications for infectious disease treatments, and
microbial communities in the human body and in nature. '
acknowledgement: 'First of all, I would like to express great gratitude to my PhD
supervisor Tobias Bollenbach. Through his open and trusting attitude I had the freedom
to explore different scientific directions during this project, and follow the research
lines of my interest. I am thankful for constructive and often extensive discussions
and his support and commitment during the different stages of my PhD. I want to
thank my committee members, Călin Guet, Terry Hwa and Nassos Typas for their interest
and their valuable input to this project. Special thanks to Nassos for career guidance,
and for accepting me in his lab. A big thank you goes to the past, present and affiliated
members of the Bollenbach group: Guillaume Chevereau, Marjon de Vos, Marta Lukačišinová,
Veronika Bierbaum, Qi Qin, Marcin Zagórski, Martin Lukačišin, Andreas Angermayr,
Bor Kavčič, Julia Tischler, Dilay Ayhan, Jaroslav Ferenc, and Georg Rieckh. I enjoyed
working and discussing with you very much and I will miss our lengthy group meetings,
our inspiring journal clubs, and our common lunches. Special thanks to Bor for great
mental and professional support during the hard months of thesis writing, and to
Marta for very creative times during the beginning of our PhDs. May the ‘Bacterial
Survival Guide’ decorate the walls of IST forever! A great thanks to my friend and
collaborator Georg Rieckh for his enthusiasm and for getting so involved in these
projects, for his endurance and for his company throughout the years. Thanks to
the FriSBi crowd at IST Austria for interesting meetings and discussions. In particular
I want to thank Magdalena Steinrück, and Anna Andersson for inspiring exchange,
and enjoyable time together. Thanks to everybody who contributed to the cover for
Cell Systems: The constructive input from Tobias Bollenbach, Bor Kavčič, Georg Rieckh,
Marta Lukačišinová, and Sebastian Nozzi, and the professional implementation by
the graphic designer Martina Markus from the University of Cologne. Thanks to all
my office mates in the first floor Bertalanffy building throughout the years: for
ensuring a pleasant working atmosphere, and for your company! In general, I want
to thank all the people that make IST such a great environment, with the many possibilities
to shape our own social and research environment. I want to thank my family for
all kind of practical support during the years, and my second family in Argentina
for their enthusiasm. Thanks to my brother Bernhard and my sister Martina for being
great siblings, and to Helena and Valentin for the joy you brought to my life. My
deep gratitude goes to Sebastian Nozzi, for constant support, patience, love and
for believing in me. '
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Karin
full_name: Mitosch, Karin
id: 39B66846-F248-11E8-B48F-1D18A9856A87
last_name: Mitosch
citation:
ama: Mitosch K. Timing, variability and cross-protection in bacteria – insights
from dynamic gene expression responses to antibiotics. 2017. doi:10.15479/AT:ISTA:th_862
apa: Mitosch, K. (2017). Timing, variability and cross-protection in bacteria
– insights from dynamic gene expression responses to antibiotics. Institute
of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:th_862
chicago: Mitosch, Karin. “Timing, Variability and Cross-Protection in Bacteria –
Insights from Dynamic Gene Expression Responses to Antibiotics.” Institute of
Science and Technology Austria, 2017. https://doi.org/10.15479/AT:ISTA:th_862.
ieee: K. Mitosch, “Timing, variability and cross-protection in bacteria – insights
from dynamic gene expression responses to antibiotics,” Institute of Science and
Technology Austria, 2017.
ista: Mitosch K. 2017. Timing, variability and cross-protection in bacteria – insights
from dynamic gene expression responses to antibiotics. Institute of Science and
Technology Austria.
mla: Mitosch, Karin. Timing, Variability and Cross-Protection in Bacteria – Insights
from Dynamic Gene Expression Responses to Antibiotics. Institute of Science
and Technology Austria, 2017, doi:10.15479/AT:ISTA:th_862.
short: K. Mitosch, Timing, Variability and Cross-Protection in Bacteria – Insights
from Dynamic Gene Expression Responses to Antibiotics, Institute of Science and
Technology Austria, 2017.
date_created: 2018-12-11T11:48:40Z
date_published: 2017-09-27T00:00:00Z
date_updated: 2023-09-07T12:00:26Z
day: '27'
ddc:
- '571'
- '579'
degree_awarded: PhD
department:
- _id: ToBo
doi: 10.15479/AT:ISTA:th_862
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page: '113'
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
publist_id: '6831'
pubrep_id: '862'
related_material:
record:
- id: '2001'
relation: part_of_dissertation
status: public
- id: '666'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
title: Timing, variability and cross-protection in bacteria – insights from dynamic
gene expression responses to antibiotics
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2017'
...
---
_id: '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: '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:
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content_type: application/pdf
creator: system
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date_updated: 2020-07-14T12:47:35Z
file_id: '5041'
file_name: IST-2017-901-v1+1_1-s2.0-S2405471217300868-main.pdf
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relation: main_file
file_date_updated: 2020-07-14T12:47:35Z
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intvolume: ' 4'
issue: '4'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
page: 393 - 403
project:
- _id: 25E83C2C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '303507'
name: Optimality principles in responses to antibiotics
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
- _id: 25EB3A80-B435-11E9-9278-68D0E5697425
grant_number: RGP0042/2013
name: Revealing the fundamental limits of cell growth
publication: Cell Systems
publication_identifier:
issn:
- '24054712'
publication_status: published
publisher: Cell Press
publist_id: '7061'
pubrep_id: '901'
quality_controlled: '1'
related_material:
record:
- id: '818'
relation: dissertation_contains
status: public
scopus_import: 1
status: public
title: Noisy response to antibiotic stress predicts subsequent single cell survival
in an acidic environment
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 4
year: '2017'
...
---
_id: '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: 2024-03-25T23:30:14Z
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: '520'
abstract:
- lang: eng
text: Cyanobacteria are mostly engineered to be sustainable cell-factories by genetic
manipulations alone. Here, by modulating the concentration of allosteric effectors,
we focus on increasing product formation without further burdening the cells with
increased expression of enzymes. Resorting to a novel 96-well microplate cultivation
system for cyanobacteria, and using lactate-producing strains of Synechocystis
PCC6803 expressing different l-lactate dehydrogenases (LDH), we titrated the effect
of 2,5-anhydro-mannitol supplementation. The latter acts in cells as a nonmetabolizable
analogue of fructose 1,6-bisphosphate, a known allosteric regulator of one of
the tested LDHs. In this strain (SAA023), we achieved over 2-fold increase of
lactate productivity. Furthermore, we observed that as carbon is increasingly
deviated during growth toward product formation, there is an increased fixation
rate in the population of spontaneous mutants harboring an impaired production
pathway. This is a challenge in the development of green cell factories, which
may be countered by the incorporation in biotechnological processes of strategies
such as the one pioneered here.
article_type: letter_note
author:
- first_name: Wei
full_name: Du, Wei
last_name: Du
- first_name: Andreas
full_name: Angermayr, Andreas
id: 4677C796-F248-11E8-B48F-1D18A9856A87
last_name: Angermayr
orcid: 0000-0001-8619-2223
- first_name: Joeri
full_name: Jongbloets, Joeri
last_name: Jongbloets
- first_name: Douwe
full_name: Molenaar, Douwe
last_name: Molenaar
- first_name: Herwig
full_name: Bachmann, Herwig
last_name: Bachmann
- first_name: Klaas
full_name: Hellingwerf, Klaas
last_name: Hellingwerf
- first_name: Filipe
full_name: Branco Dos Santos, Filipe
last_name: Branco Dos Santos
citation:
ama: Du W, Angermayr A, Jongbloets J, et al. Nonhierarchical flux regulation exposes
the fitness burden associated with lactate production in Synechocystis sp. PCC6803.
ACS Synthetic Biology. 2017;6(3):395-401. doi:10.1021/acssynbio.6b00235
apa: Du, W., Angermayr, A., Jongbloets, J., Molenaar, D., Bachmann, H., Hellingwerf,
K., & Branco Dos Santos, F. (2017). Nonhierarchical flux regulation exposes
the fitness burden associated with lactate production in Synechocystis sp. PCC6803.
ACS Synthetic Biology. American Chemical Society. https://doi.org/10.1021/acssynbio.6b00235
chicago: Du, Wei, Andreas Angermayr, Joeri Jongbloets, Douwe Molenaar, Herwig Bachmann,
Klaas Hellingwerf, and Filipe Branco Dos Santos. “Nonhierarchical Flux Regulation
Exposes the Fitness Burden Associated with Lactate Production in Synechocystis
Sp. PCC6803.” ACS Synthetic Biology. American Chemical Society, 2017. https://doi.org/10.1021/acssynbio.6b00235.
ieee: W. Du et al., “Nonhierarchical flux regulation exposes the fitness
burden associated with lactate production in Synechocystis sp. PCC6803,” ACS
Synthetic Biology, vol. 6, no. 3. American Chemical Society, pp. 395–401,
2017.
ista: Du W, Angermayr A, Jongbloets J, Molenaar D, Bachmann H, Hellingwerf K, Branco
Dos Santos F. 2017. Nonhierarchical flux regulation exposes the fitness burden
associated with lactate production in Synechocystis sp. PCC6803. ACS Synthetic
Biology. 6(3), 395–401.
mla: Du, Wei, et al. “Nonhierarchical Flux Regulation Exposes the Fitness Burden
Associated with Lactate Production in Synechocystis Sp. PCC6803.” ACS Synthetic
Biology, vol. 6, no. 3, American Chemical Society, 2017, pp. 395–401, doi:10.1021/acssynbio.6b00235.
short: W. Du, A. Angermayr, J. Jongbloets, D. Molenaar, H. Bachmann, K. Hellingwerf,
F. Branco Dos Santos, ACS Synthetic Biology 6 (2017) 395–401.
date_created: 2018-12-11T11:46:56Z
date_published: 2017-03-17T00:00:00Z
date_updated: 2021-01-12T08:01:21Z
day: '17'
department:
- _id: ToBo
doi: 10.1021/acssynbio.6b00235
external_id:
pmid:
- '27936615'
intvolume: ' 6'
issue: '3'
language:
- iso: eng
month: '03'
oa_version: None
page: 395 - 401
pmid: 1
publication: ACS Synthetic Biology
publication_identifier:
issn:
- '21615063'
publication_status: published
publisher: American Chemical Society
publist_id: '7298'
quality_controlled: '1'
scopus_import: 1
status: public
title: Nonhierarchical flux regulation exposes the fitness burden associated with
lactate production in Synechocystis sp. PCC6803
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 6
year: '2017'
...
---
_id: '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: '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: 2024-03-25T23:30:15Z
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: '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: 2024-03-25T23:30:03Z
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: '9849'
abstract:
- lang: eng
text: This text provides additional information about the model, a derivation of
the analytic results in Eq (4), and details about simulations of an additional
parameter set.
article_processing_charge: No
author:
- first_name: Marta
full_name: Lukacisinova, Marta
id: 4342E402-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisinova
orcid: 0000-0002-2519-8004
- first_name: Sebastian
full_name: Novak, Sebastian
id: 461468AE-F248-11E8-B48F-1D18A9856A87
last_name: Novak
- first_name: Tiago
full_name: Paixao, Tiago
id: 2C5658E6-F248-11E8-B48F-1D18A9856A87
last_name: Paixao
orcid: 0000-0003-2361-3953
citation:
ama: Lukacisinova M, Novak S, Paixao T. Modelling and simulation details. 2017.
doi:10.1371/journal.pcbi.1005609.s001
apa: Lukacisinova, M., Novak, S., & Paixao, T. (2017). Modelling and simulation
details. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005609.s001
chicago: Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Modelling and
Simulation Details.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005609.s001.
ieee: M. Lukacisinova, S. Novak, and T. Paixao, “Modelling and simulation details.”
Public Library of Science, 2017.
ista: Lukacisinova M, Novak S, Paixao T. 2017. Modelling and simulation details,
Public Library of Science, 10.1371/journal.pcbi.1005609.s001.
mla: Lukacisinova, Marta, et al. Modelling and Simulation Details. Public
Library of Science, 2017, doi:10.1371/journal.pcbi.1005609.s001.
short: M. Lukacisinova, S. Novak, T. Paixao, (2017).
date_created: 2021-08-09T14:02:34Z
date_published: 2017-07-18T00:00:00Z
date_updated: 2023-02-23T12:55:39Z
day: '18'
department:
- _id: ToBo
- _id: NiBa
- _id: CaGu
doi: 10.1371/journal.pcbi.1005609.s001
month: '07'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '696'
relation: used_in_publication
status: public
status: public
title: Modelling and simulation details
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2017'
...
---
_id: '9850'
abstract:
- lang: eng
text: In this text, we discuss how a cost of resistance and the possibility of lethal
mutations impact our model.
article_processing_charge: No
author:
- first_name: Marta
full_name: Lukacisinova, Marta
id: 4342E402-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisinova
orcid: 0000-0002-2519-8004
- first_name: Sebastian
full_name: Novak, Sebastian
id: 461468AE-F248-11E8-B48F-1D18A9856A87
last_name: Novak
- first_name: Tiago
full_name: Paixao, Tiago
id: 2C5658E6-F248-11E8-B48F-1D18A9856A87
last_name: Paixao
orcid: 0000-0003-2361-3953
citation:
ama: Lukacisinova M, Novak S, Paixao T. Extensions of the model. 2017. doi:10.1371/journal.pcbi.1005609.s002
apa: Lukacisinova, M., Novak, S., & Paixao, T. (2017). Extensions of the model.
Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005609.s002
chicago: Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Extensions of
the Model.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005609.s002.
ieee: M. Lukacisinova, S. Novak, and T. Paixao, “Extensions of the model.” Public
Library of Science, 2017.
ista: Lukacisinova M, Novak S, Paixao T. 2017. Extensions of the model, Public Library
of Science, 10.1371/journal.pcbi.1005609.s002.
mla: Lukacisinova, Marta, et al. Extensions of the Model. Public Library
of Science, 2017, doi:10.1371/journal.pcbi.1005609.s002.
short: M. Lukacisinova, S. Novak, T. Paixao, (2017).
date_created: 2021-08-09T14:05:24Z
date_published: 2017-07-18T00:00:00Z
date_updated: 2023-02-23T12:55:39Z
day: '18'
department:
- _id: ToBo
- _id: CaGu
- _id: NiBa
doi: 10.1371/journal.pcbi.1005609.s002
month: '07'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '696'
relation: used_in_publication
status: public
status: public
title: Extensions of the model
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2017'
...
---
_id: '9851'
abstract:
- lang: eng
text: Based on the intuitive derivation of the dynamics of SIM allele frequency
pM in the main text, we present a heuristic prediction for the long-term SIM allele
frequencies with χ > 1 stresses and compare it to numerical simulations.
article_processing_charge: No
author:
- first_name: Marta
full_name: Lukacisinova, Marta
id: 4342E402-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisinova
orcid: 0000-0002-2519-8004
- first_name: Sebastian
full_name: Novak, Sebastian
id: 461468AE-F248-11E8-B48F-1D18A9856A87
last_name: Novak
- first_name: Tiago
full_name: Paixao, Tiago
id: 2C5658E6-F248-11E8-B48F-1D18A9856A87
last_name: Paixao
orcid: 0000-0003-2361-3953
citation:
ama: Lukacisinova M, Novak S, Paixao T. Heuristic prediction for multiple stresses.
2017. doi:10.1371/journal.pcbi.1005609.s003
apa: Lukacisinova, M., Novak, S., & Paixao, T. (2017). Heuristic prediction
for multiple stresses. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005609.s003
chicago: Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Heuristic Prediction
for Multiple Stresses.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005609.s003.
ieee: M. Lukacisinova, S. Novak, and T. Paixao, “Heuristic prediction for multiple
stresses.” Public Library of Science, 2017.
ista: Lukacisinova M, Novak S, Paixao T. 2017. Heuristic prediction for multiple
stresses, Public Library of Science, 10.1371/journal.pcbi.1005609.s003.
mla: Lukacisinova, Marta, et al. Heuristic Prediction for Multiple Stresses.
Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005609.s003.
short: M. Lukacisinova, S. Novak, T. Paixao, (2017).
date_created: 2021-08-09T14:08:14Z
date_published: 2017-07-18T00:00:00Z
date_updated: 2023-02-23T12:55:39Z
day: '18'
department:
- _id: ToBo
- _id: CaGu
- _id: NiBa
doi: 10.1371/journal.pcbi.1005609.s003
month: '07'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '696'
relation: used_in_publication
status: public
status: public
title: Heuristic prediction for multiple stresses
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2017'
...
---
_id: '9852'
abstract:
- lang: eng
text: We show how different combination strategies affect the fraction of individuals
that are multi-resistant.
article_processing_charge: No
author:
- first_name: Marta
full_name: Lukacisinova, Marta
id: 4342E402-F248-11E8-B48F-1D18A9856A87
last_name: Lukacisinova
orcid: 0000-0002-2519-8004
- first_name: Sebastian
full_name: Novak, Sebastian
id: 461468AE-F248-11E8-B48F-1D18A9856A87
last_name: Novak
- first_name: Tiago
full_name: Paixao, Tiago
id: 2C5658E6-F248-11E8-B48F-1D18A9856A87
last_name: Paixao
orcid: 0000-0003-2361-3953
citation:
ama: Lukacisinova M, Novak S, Paixao T. Resistance frequencies for different combination
strategies. 2017. doi:10.1371/journal.pcbi.1005609.s004
apa: Lukacisinova, M., Novak, S., & Paixao, T. (2017). Resistance frequencies
for different combination strategies. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005609.s004
chicago: Lukacisinova, Marta, Sebastian Novak, and Tiago Paixao. “Resistance Frequencies
for Different Combination Strategies.” Public Library of Science, 2017. https://doi.org/10.1371/journal.pcbi.1005609.s004.
ieee: M. Lukacisinova, S. Novak, and T. Paixao, “Resistance frequencies for different
combination strategies.” Public Library of Science, 2017.
ista: Lukacisinova M, Novak S, Paixao T. 2017. Resistance frequencies for different
combination strategies, Public Library of Science, 10.1371/journal.pcbi.1005609.s004.
mla: Lukacisinova, Marta, et al. Resistance Frequencies for Different Combination
Strategies. Public Library of Science, 2017, doi:10.1371/journal.pcbi.1005609.s004.
short: M. Lukacisinova, S. Novak, T. Paixao, (2017).
date_created: 2021-08-09T14:11:40Z
date_published: 2017-07-18T00:00:00Z
date_updated: 2023-02-23T12:55:39Z
day: '18'
department:
- _id: ToBo
- _id: CaGu
- _id: NiBa
doi: 10.1371/journal.pcbi.1005609.s004
month: '07'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '696'
relation: used_in_publication
status: public
status: public
title: Resistance frequencies for different combination strategies
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2017'
...
---
_id: '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: '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: '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: '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'
...