---
_id: '8657'
abstract:
- lang: eng
text: "Synthesis of proteins – translation – is a fundamental process of life. Quantitative
studies anchor translation into the context of bacterial physiology and reveal
several mathematical relationships, called “growth laws,” which capture physiological
feedbacks between protein synthesis and cell growth. Growth laws describe the
dependency of the ribosome abundance as a function of growth rate, which can change
depending on the growth conditions. Perturbations of translation reveal that bacteria
employ a compensatory strategy in which the reduced translation capability results
in increased expression of the translation machinery.\r\nPerturbations of translation
are achieved in various ways; clinically interesting is the application of translation-targeting
antibiotics – translation inhibitors. The antibiotic effects on bacterial physiology
are often poorly understood. Bacterial responses to two or more simultaneously
applied antibiotics are even more puzzling. The combined antibiotic effect determines
the type of drug interaction, which ranges from synergy (the effect is stronger
than expected) to antagonism (the effect is weaker) and suppression (one of the
drugs loses its potency).\r\nIn the first part of this work, we systematically
measure the pairwise interaction network for translation inhibitors that interfere
with different steps in translation. We find that the interactions are surprisingly
diverse and tend to be more antagonistic. To explore the underlying mechanisms,
we begin with a minimal biophysical model of combined antibiotic action. We base
this model on the kinetics of antibiotic uptake and binding together with the
physiological response described by the growth laws. The biophysical model explains
some drug interactions, but not all; it specifically fails to predict suppression.\r\nIn
the second part of this work, we hypothesize that elusive suppressive drug interactions
result from the interplay between ribosomes halted in different stages of translation.
To elucidate this putative mechanism of drug interactions between translation
inhibitors, we generate translation bottlenecks genetically using in- ducible
control of translation factors that regulate well-defined translation cycle steps.
These perturbations accurately mimic antibiotic action and drug interactions,
supporting that the interplay of different translation bottlenecks partially causes
these interactions.\r\nWe extend this approach by varying two translation bottlenecks
simultaneously. This approach reveals the suppression of translocation inhibition
by inhibited translation. We rationalize this effect by modeling dense traffic
of ribosomes that move on transcripts in a translation factor-mediated manner.
This model predicts a dissolution of traffic jams caused by inhibited translocation
when the density of ribosome traffic is reduced by lowered initiation. We base
this model on the growth laws and quantitative relationships between different
translation and growth parameters.\r\nIn the final part of this work, we describe
a set of tools aimed at quantification of physiological and translation parameters.
We further develop a simple model that directly connects the abundance of a translation
factor with the growth rate, which allows us to extract physiological parameters
describing initiation. We demonstrate the development of tools for measuring translation
rate.\r\nThis thesis showcases how a combination of high-throughput growth rate
mea- surements, genetics, and modeling can reveal mechanisms of drug interactions.
Furthermore, by a gradual transition from combinations of antibiotics to precise
genetic interventions, we demonstrated the equivalency between genetic and chemi-
cal perturbations of translation. These findings tile the path for quantitative
studies of antibiotic combinations and illustrate future approaches towards the
quantitative description of translation."
acknowledged_ssus:
- _id: LifeSc
- _id: M-Shop
acknowledgement: I thank Life Science Facilities for their continuous support with
providing top-notch laboratory materials, keeping the devices humming, and coordinating
the repairs and building of custom-designed laboratory equipment with the MIBA Machine
shop.
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Bor
full_name: Kavcic, Bor
id: 350F91D2-F248-11E8-B48F-1D18A9856A87
last_name: Kavcic
orcid: 0000-0001-6041-254X
citation:
ama: 'Kavcic B. Perturbations of protein synthesis: from antibiotics to genetics
and physiology. 2020. doi:10.15479/AT:ISTA:8657'
apa: 'Kavcic, B. (2020). Perturbations of protein synthesis: from antibiotics
to genetics and physiology. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8657'
chicago: 'Kavcic, Bor. “Perturbations of Protein Synthesis: From Antibiotics to
Genetics and Physiology.” Institute of Science and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:8657.'
ieee: 'B. Kavcic, “Perturbations of protein synthesis: from antibiotics to genetics
and physiology,” Institute of Science and Technology Austria, 2020.'
ista: 'Kavcic B. 2020. Perturbations of protein synthesis: from antibiotics to genetics
and physiology. Institute of Science and Technology Austria.'
mla: 'Kavcic, Bor. Perturbations of Protein Synthesis: From Antibiotics to Genetics
and Physiology. Institute of Science and Technology Austria, 2020, doi:10.15479/AT:ISTA:8657.'
short: 'B. Kavcic, Perturbations of Protein Synthesis: From Antibiotics to Genetics
and Physiology, Institute of Science and Technology Austria, 2020.'
date_created: 2020-10-13T16:46:14Z
date_published: 2020-10-14T00:00:00Z
date_updated: 2023-09-07T13:20:48Z
day: '14'
ddc:
- '571'
- '530'
- '570'
degree_awarded: PhD
department:
- _id: GaTk
doi: 10.15479/AT:ISTA:8657
file:
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checksum: d708ecd62b6fcc3bc1feb483b8dbe9eb
content_type: application/pdf
creator: bkavcic
date_created: 2020-10-15T06:41:20Z
date_updated: 2021-10-07T22:30:03Z
embargo: 2021-10-06
file_id: '8663'
file_name: kavcicB_thesis202009.pdf
file_size: 52636162
relation: main_file
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checksum: bb35f2352a04db19164da609f00501f3
content_type: application/zip
creator: bkavcic
date_created: 2020-10-15T06:41:53Z
date_updated: 2021-10-07T22:30:03Z
embargo_to: open_access
file_id: '8664'
file_name: 2020b.zip
file_size: 321681247
relation: source_file
file_date_updated: 2021-10-07T22:30:03Z
has_accepted_license: '1'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: '271'
publication_identifier:
isbn:
- 978-3-99078-011-4
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '7673'
relation: part_of_dissertation
status: public
- id: '8250'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
title: 'Perturbations of protein synthesis: from antibiotics to genetics and physiology'
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2020'
...
---
_id: '8250'
abstract:
- lang: eng
text: 'Antibiotics that interfere with translation, when combined, interact in diverse
and difficult-to-predict ways. Here, we explain these interactions by “translation
bottlenecks”: points in the translation cycle where antibiotics block ribosomal
progression. To elucidate the underlying mechanisms of drug interactions between
translation inhibitors, we generate translation bottlenecks genetically using
inducible control of translation factors that regulate well-defined translation
cycle steps. These perturbations accurately mimic antibiotic action and drug interactions,
supporting that the interplay of different translation bottlenecks causes these
interactions. We further show that growth laws, combined with drug uptake and
binding kinetics, enable the direct prediction of a large fraction of observed
interactions, yet fail to predict suppression. However, varying two translation
bottlenecks simultaneously supports that dense traffic of ribosomes and competition
for translation factors account for the previously unexplained suppression. These
results highlight the importance of “continuous epistasis” in bacterial physiology.'
acknowledgement: "We thank M. Hennessey-Wesen, I. Tomanek, K. Jain, A. Staron, K.
Tomasek, M. Scott,\r\nK.C. Huang, and Z. Gitai for reading the manuscript and constructive
comments. B.K. is\r\nindebted to C. Guet for additional guidance and generous support,
which rendered this\r\nwork possible. B.K. thanks all members of Guet group for
many helpful discussions and\r\nsharing of resources. B.K. additionally acknowledges
the tremendous support from A.\r\nAngermayr and K. Mitosch with experimental work.
We further thank E. Brown for\r\nhelpful comments regarding lamotrigine, and A.
Buskirk for valuable suggestions\r\nregarding the ribosome footprint size. This
work was supported in part by Austrian\r\nScience Fund (FWF) standalone grants P
27201-B22 (to T.B.) and P 28844 (to G.T.),\r\nHFSP program Grant RGP0042/2013 (to
T.B.), German Research Foundation (DFG)\r\nstandalone grant BO 3502/2-1 (to T.B.),
and German Research Foundation (DFG)\r\nCollaborative Research Centre (SFB) 1310
(to T.B.). Open access funding provided by\r\nProjekt DEAL."
article_number: '4013'
article_processing_charge: No
article_type: original
author:
- first_name: Bor
full_name: Kavcic, Bor
id: 350F91D2-F248-11E8-B48F-1D18A9856A87
last_name: Kavcic
orcid: 0000-0001-6041-254X
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Tobias
full_name: Bollenbach, Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Kavcic B, Tkačik G, Bollenbach MT. Mechanisms of drug interactions between
translation-inhibiting antibiotics. Nature Communications. 2020;11. doi:10.1038/s41467-020-17734-z
apa: Kavcic, B., Tkačik, G., & Bollenbach, M. T. (2020). Mechanisms of drug
interactions between translation-inhibiting antibiotics. Nature Communications.
Springer Nature. https://doi.org/10.1038/s41467-020-17734-z
chicago: Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “Mechanisms of
Drug Interactions between Translation-Inhibiting Antibiotics.” Nature Communications.
Springer Nature, 2020. https://doi.org/10.1038/s41467-020-17734-z.
ieee: B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Mechanisms of drug interactions
between translation-inhibiting antibiotics,” Nature Communications, vol.
11. Springer Nature, 2020.
ista: Kavcic B, Tkačik G, Bollenbach MT. 2020. Mechanisms of drug interactions between
translation-inhibiting antibiotics. Nature Communications. 11, 4013.
mla: Kavcic, Bor, et al. “Mechanisms of Drug Interactions between Translation-Inhibiting
Antibiotics.” Nature Communications, vol. 11, 4013, Springer Nature, 2020,
doi:10.1038/s41467-020-17734-z.
short: B. Kavcic, G. Tkačik, M.T. Bollenbach, Nature Communications 11 (2020).
date_created: 2020-08-12T09:13:50Z
date_published: 2020-08-11T00:00:00Z
date_updated: 2024-03-27T23:30:08Z
day: '11'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1038/s41467-020-17734-z
external_id:
isi:
- '000562769300008'
file:
- access_level: open_access
checksum: 986bebb308850a55850028d3d2b5b664
content_type: application/pdf
creator: dernst
date_created: 2020-08-17T07:36:57Z
date_updated: 2020-08-17T07:36:57Z
file_id: '8275'
file_name: 2020_NatureComm_Kavcic.pdf
file_size: 1965672
relation: main_file
success: 1
file_date_updated: 2020-08-17T07:36:57Z
has_accepted_license: '1'
intvolume: ' 11'
isi: 1
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
project:
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Nature Communications
publication_identifier:
issn:
- 2041-1723
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '8657'
relation: dissertation_contains
status: public
status: public
title: Mechanisms of drug interactions between translation-inhibiting 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: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 11
year: '2020'
...
---
_id: '7673'
abstract:
- lang: eng
text: Combining drugs can improve the efficacy of treatments. However, predicting
the effect of drug combinations is still challenging. The combined potency of
drugs determines the drug interaction, which is classified as synergistic, additive,
antagonistic, or suppressive. While probabilistic, non-mechanistic models exist,
there is currently no biophysical model that can predict antibiotic interactions.
Here, we present a physiologically relevant model of the combined action of antibiotics
that inhibit protein synthesis by targeting the ribosome. This model captures
the kinetics of antibiotic binding and transport, and uses bacterial growth laws
to predict growth in the presence of antibiotic combinations. We find that this
biophysical model can produce all drug interaction types except suppression. We
show analytically that antibiotics which cannot bind to the ribosome simultaneously
generally act as substitutes for one another, leading to additive drug interactions.
Previously proposed null expectations for higher-order drug interactions follow
as a limiting case of our model. We further extend the model to include the effects
of direct physical or allosteric interactions between individual drugs on the
ribosome. Notably, such direct interactions profoundly change the combined drug
effect, depending on the kinetic parameters of the drugs used. The model makes
additional predictions for the effects of resistance genes on drug interactions
and for interactions between ribosome-targeting antibiotics and antibiotics with
other targets. These findings enhance our understanding of the interplay between
drug action and cell physiology and are a key step toward a general framework
for predicting drug interactions.
article_processing_charge: No
author:
- first_name: Bor
full_name: Kavcic, Bor
id: 350F91D2-F248-11E8-B48F-1D18A9856A87
last_name: Kavcic
orcid: 0000-0001-6041-254X
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Tobias
full_name: Bollenbach, Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Kavcic B, Tkačik G, Bollenbach MT. A minimal biophysical model of combined
antibiotic action. bioRxiv. 2020. doi:10.1101/2020.04.18.047886
apa: Kavcic, B., Tkačik, G., & Bollenbach, M. T. (2020). A minimal biophysical
model of combined antibiotic action. bioRxiv. Cold Spring Harbor Laboratory.
https://doi.org/10.1101/2020.04.18.047886
chicago: Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “A Minimal Biophysical
Model of Combined Antibiotic Action.” BioRxiv. Cold Spring Harbor Laboratory,
2020. https://doi.org/10.1101/2020.04.18.047886.
ieee: B. Kavcic, G. Tkačik, and M. T. Bollenbach, “A minimal biophysical model of
combined antibiotic action,” bioRxiv. Cold Spring Harbor Laboratory, 2020.
ista: Kavcic B, Tkačik G, Bollenbach MT. 2020. A minimal biophysical model of combined
antibiotic action. bioRxiv, 10.1101/2020.04.18.047886.
mla: Kavcic, Bor, et al. “A Minimal Biophysical Model of Combined Antibiotic Action.”
BioRxiv, Cold Spring Harbor Laboratory, 2020, doi:10.1101/2020.04.18.047886.
short: B. Kavcic, G. Tkačik, M.T. Bollenbach, BioRxiv (2020).
date_created: 2020-04-22T08:27:56Z
date_published: 2020-04-18T00:00:00Z
date_updated: 2024-03-27T23:30:08Z
day: '18'
department:
- _id: GaTk
doi: 10.1101/2020.04.18.047886
language:
- iso: eng
main_file_link:
- open_access: '1'
url: 'https://doi.org/10.1101/2020.04.18.047886 '
month: '04'
oa: 1
oa_version: Preprint
project:
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: bioRxiv
publication_status: published
publisher: Cold Spring Harbor Laboratory
related_material:
record:
- id: '8997'
relation: later_version
status: public
- id: '8657'
relation: dissertation_contains
status: public
status: public
title: A minimal biophysical model of combined antibiotic action
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2020'
...
---
_id: '7652'
abstract:
- lang: eng
text: Organisms cope with change by taking advantage of transcriptional regulators.
However, when faced with rare environments, the evolution of transcriptional regulators
and their promoters may be too slow. Here, we investigate whether the intrinsic
instability of gene duplication and amplification provides a generic alternative
to canonical gene regulation. Using real-time monitoring of gene-copy-number mutations
in Escherichia coli, we show that gene duplications and amplifications enable
adaptation to fluctuating environments by rapidly generating copy-number and,
therefore, expression-level polymorphisms. This amplification-mediated gene expression
tuning (AMGET) occurs on timescales that are similar to canonical gene regulation
and can respond to rapid environmental changes. Mathematical modelling shows that
amplifications also tune gene expression in stochastic environments in which transcription-factor-based
schemes are hard to evolve or maintain. The fleeting nature of gene amplifications
gives rise to a generic population-level mechanism that relies on genetic heterogeneity
to rapidly tune the expression of any gene, without leaving any genomic signature.
acknowledgement: We thank L. Hurst, N. Barton, M. Pleska, M. Steinrück, B. Kavcic
and A. Staron for input on the manuscript, and To. Bergmiller and R. Chait for help
with microfluidics experiments. I.T. is a recipient the OMV fellowship. R.G. is
a recipient of a DOC (Doctoral Fellowship Programme of the Austrian Academy of Sciences)
Fellowship of the Austrian Academy of Sciences.
article_processing_charge: No
article_type: original
author:
- first_name: Isabella
full_name: Tomanek, Isabella
id: 3981F020-F248-11E8-B48F-1D18A9856A87
last_name: Tomanek
orcid: 0000-0001-6197-363X
- first_name: Rok
full_name: Grah, Rok
id: 483E70DE-F248-11E8-B48F-1D18A9856A87
last_name: Grah
orcid: 0000-0003-2539-3560
- first_name: M.
full_name: Lagator, M.
last_name: Lagator
- first_name: A. M. C.
full_name: Andersson, A. M. C.
last_name: Andersson
- first_name: Jonathan P
full_name: Bollback, Jonathan P
id: 2C6FA9CC-F248-11E8-B48F-1D18A9856A87
last_name: Bollback
orcid: 0000-0002-4624-4612
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
citation:
ama: Tomanek I, Grah R, Lagator M, et al. Gene amplification as a form of population-level
gene expression regulation. Nature Ecology & Evolution. 2020;4(4):612-625.
doi:10.1038/s41559-020-1132-7
apa: Tomanek, I., Grah, R., Lagator, M., Andersson, A. M. C., Bollback, J. P., Tkačik,
G., & Guet, C. C. (2020). Gene amplification as a form of population-level
gene expression regulation. Nature Ecology & Evolution. Springer Nature.
https://doi.org/10.1038/s41559-020-1132-7
chicago: Tomanek, Isabella, Rok Grah, M. Lagator, A. M. C. Andersson, Jonathan P
Bollback, Gašper Tkačik, and Calin C Guet. “Gene Amplification as a Form of Population-Level
Gene Expression Regulation.” Nature Ecology & Evolution. Springer Nature,
2020. https://doi.org/10.1038/s41559-020-1132-7.
ieee: I. Tomanek et al., “Gene amplification as a form of population-level
gene expression regulation,” Nature Ecology & Evolution, vol. 4, no.
4. Springer Nature, pp. 612–625, 2020.
ista: Tomanek I, Grah R, Lagator M, Andersson AMC, Bollback JP, Tkačik G, Guet CC.
2020. Gene amplification as a form of population-level gene expression regulation.
Nature Ecology & Evolution. 4(4), 612–625.
mla: Tomanek, Isabella, et al. “Gene Amplification as a Form of Population-Level
Gene Expression Regulation.” Nature Ecology & Evolution, vol. 4, no.
4, Springer Nature, 2020, pp. 612–25, doi:10.1038/s41559-020-1132-7.
short: I. Tomanek, R. Grah, M. Lagator, A.M.C. Andersson, J.P. Bollback, G. Tkačik,
C.C. Guet, Nature Ecology & Evolution 4 (2020) 612–625.
date_created: 2020-04-08T15:20:53Z
date_published: 2020-04-01T00:00:00Z
date_updated: 2024-03-27T23:30:36Z
day: '01'
ddc:
- '570'
department:
- _id: GaTk
- _id: CaGu
doi: 10.1038/s41559-020-1132-7
external_id:
isi:
- '000519008300005'
file:
- access_level: open_access
checksum: ef3bbf42023e30b2c24a6278025d2040
content_type: application/pdf
creator: dernst
date_created: 2020-10-09T09:56:01Z
date_updated: 2020-10-09T09:56:01Z
file_id: '8640'
file_name: 2020_NatureEcolEvo_Tomanek.pdf
file_size: 745242
relation: main_file
success: 1
file_date_updated: 2020-10-09T09:56:01Z
has_accepted_license: '1'
intvolume: ' 4'
isi: 1
issue: '4'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Submitted Version
page: 612-625
project:
- _id: 267C84F4-B435-11E9-9278-68D0E5697425
name: Biophysically realistic genotype-phenotype maps for regulatory networks
publication: Nature Ecology & Evolution
publication_identifier:
issn:
- 2397-334X
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
link:
- description: News on IST Homepage
relation: press_release
url: https://ist.ac.at/en/news/how-to-thrive-without-gene-regulation/
record:
- id: '8155'
relation: dissertation_contains
status: public
- id: '7383'
relation: research_data
status: public
- id: '7016'
relation: research_data
status: public
- id: '8653'
relation: used_in_publication
status: public
scopus_import: '1'
status: public
title: Gene amplification as a form of population-level gene expression regulation
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 4
year: '2020'
...
---
_id: '7552'
abstract:
- lang: eng
text: 'There is increasing evidence that protein binding to specific sites along
DNA can activate the reading out of genetic information without coming into direct
physical contact with the gene. There also is evidence that these distant but
interacting sites are embedded in a liquid droplet of proteins which condenses
out of the surrounding solution. We argue that droplet-mediated interactions can
account for crucial features of gene regulation only if the droplet is poised
at a non-generic point in its phase diagram. We explore a minimal model that embodies
this idea, show that this model has a natural mechanism for self-tuning, and suggest
direct experimental tests. '
article_processing_charge: No
author:
- first_name: William
full_name: Bialek, William
last_name: Bialek
- first_name: Thomas
full_name: Gregor, Thomas
last_name: Gregor
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Bialek W, Gregor T, Tkačik G. Action at a distance in transcriptional regulation.
arXiv:191208579.
apa: Bialek, W., Gregor, T., & Tkačik, G. (n.d.). Action at a distance in transcriptional
regulation. arXiv:1912.08579. ArXiv.
chicago: Bialek, William, Thomas Gregor, and Gašper Tkačik. “Action at a Distance
in Transcriptional Regulation.” ArXiv:1912.08579. ArXiv, n.d.
ieee: W. Bialek, T. Gregor, and G. Tkačik, “Action at a distance in transcriptional
regulation,” arXiv:1912.08579. ArXiv.
ista: Bialek W, Gregor T, Tkačik G. Action at a distance in transcriptional regulation.
arXiv:1912.08579, .
mla: Bialek, William, et al. “Action at a Distance in Transcriptional Regulation.”
ArXiv:1912.08579, ArXiv.
short: W. Bialek, T. Gregor, G. Tkačik, ArXiv:1912.08579 (n.d.).
date_created: 2020-02-28T10:57:08Z
date_published: 2019-12-18T00:00:00Z
date_updated: 2021-01-12T08:14:09Z
day: '18'
department:
- _id: GaTk
external_id:
arxiv:
- '1912.08579'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1912.08579
month: '12'
oa: 1
oa_version: Preprint
page: '5'
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: arXiv:1912.08579
publication_status: submitted
publisher: ArXiv
status: public
title: Action at a distance in transcriptional regulation
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2019'
...
---
_id: '5945'
abstract:
- lang: eng
text: In developing organisms, spatially prescribed cell identities are thought
to be determined by the expression levels of multiple genes. Quantitative tests
of this idea, however, require a theoretical framework capable of exposing the
rules and precision of cell specification over developmental time. We use the
gap gene network in the early fly embryo as an example to show how expression
levels of the four gap genes can be jointly decoded into an optimal specification
of position with 1% accuracy. The decoder correctly predicts, with no free parameters,
the dynamics of pair-rule expression patterns at different developmental time
points and in various mutant backgrounds. Precise cellular identities are thus
available at the earliest stages of development, contrasting the prevailing view
of positional information being slowly refined across successive layers of the
patterning network. Our results suggest that developmental enhancers closely approximate
a mathematically optimal decoding strategy.
article_processing_charge: No
article_type: original
author:
- first_name: Mariela D.
full_name: Petkova, Mariela D.
last_name: Petkova
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: William
full_name: Bialek, William
last_name: Bialek
- first_name: Eric F.
full_name: Wieschaus, Eric F.
last_name: Wieschaus
- first_name: Thomas
full_name: Gregor, Thomas
last_name: Gregor
citation:
ama: Petkova MD, Tkačik G, Bialek W, Wieschaus EF, Gregor T. Optimal decoding of
cellular identities in a genetic network. Cell. 2019;176(4):844-855.e15.
doi:10.1016/j.cell.2019.01.007
apa: Petkova, M. D., Tkačik, G., Bialek, W., Wieschaus, E. F., & Gregor, T.
(2019). Optimal decoding of cellular identities in a genetic network. Cell.
Cell Press. https://doi.org/10.1016/j.cell.2019.01.007
chicago: Petkova, Mariela D., Gašper Tkačik, William Bialek, Eric F. Wieschaus,
and Thomas Gregor. “Optimal Decoding of Cellular Identities in a Genetic Network.”
Cell. Cell Press, 2019. https://doi.org/10.1016/j.cell.2019.01.007.
ieee: M. D. Petkova, G. Tkačik, W. Bialek, E. F. Wieschaus, and T. Gregor, “Optimal
decoding of cellular identities in a genetic network,” Cell, vol. 176,
no. 4. Cell Press, p. 844–855.e15, 2019.
ista: Petkova MD, Tkačik G, Bialek W, Wieschaus EF, Gregor T. 2019. Optimal decoding
of cellular identities in a genetic network. Cell. 176(4), 844–855.e15.
mla: Petkova, Mariela D., et al. “Optimal Decoding of Cellular Identities in a Genetic
Network.” Cell, vol. 176, no. 4, Cell Press, 2019, p. 844–855.e15, doi:10.1016/j.cell.2019.01.007.
short: M.D. Petkova, G. Tkačik, W. Bialek, E.F. Wieschaus, T. Gregor, Cell 176 (2019)
844–855.e15.
date_created: 2019-02-10T22:59:16Z
date_published: 2019-02-07T00:00:00Z
date_updated: 2023-08-24T14:42:47Z
day: '07'
department:
- _id: GaTk
doi: 10.1016/j.cell.2019.01.007
external_id:
isi:
- '000457969200015'
pmid:
- '30712870'
intvolume: ' 176'
isi: 1
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1016/j.cell.2019.01.007
month: '02'
oa: 1
oa_version: Published Version
page: 844-855.e15
pmid: 1
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Cell
publication_status: published
publisher: Cell Press
quality_controlled: '1'
related_material:
link:
- description: News on IST Homepage
relation: press_release
url: https://ist.ac.at/en/news/cells-find-their-identity-using-a-mathematically-optimal-strategy/
scopus_import: '1'
status: public
title: Optimal decoding of cellular identities in a genetic network
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 176
year: '2019'
...
---
_id: '6049'
abstract:
- lang: eng
text: 'In this article it is shown that large systems with many interacting units
endowing multiple phases display self-oscillations in the presence of linear feedback
between the control and order parameters, where an Andronov–Hopf bifurcation takes
over the phase transition. This is simply illustrated through the mean field Landau
theory whose feedback dynamics turn out to be described by the Van der Pol equation
and it is then validated for the fully connected Ising model following heat bath
dynamics. Despite its simplicity, this theory accounts potentially for a rich
range of phenomena: here it is applied to describe in a stylized way (i) excess
demand-price cycles due to strong herding in a simple agent-based market model;
(ii) congestion waves in queuing networks triggered by user feedback to delays
in overloaded conditions; and (iii) metabolic network oscillations resulting from
cell growth control in a bistable phenotypic landscape.'
article_number: '045002'
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
citation:
ama: 'De Martino D. Feedback-induced self-oscillations in large interacting systems
subjected to phase transitions. Journal of Physics A: Mathematical and Theoretical.
2019;52(4). doi:10.1088/1751-8121/aaf2dd'
apa: 'De Martino, D. (2019). Feedback-induced self-oscillations in large interacting
systems subjected to phase transitions. Journal of Physics A: Mathematical
and Theoretical. IOP Publishing. https://doi.org/10.1088/1751-8121/aaf2dd'
chicago: 'De Martino, Daniele. “Feedback-Induced Self-Oscillations in Large Interacting
Systems Subjected to Phase Transitions.” Journal of Physics A: Mathematical
and Theoretical. IOP Publishing, 2019. https://doi.org/10.1088/1751-8121/aaf2dd.'
ieee: 'D. De Martino, “Feedback-induced self-oscillations in large interacting systems
subjected to phase transitions,” Journal of Physics A: Mathematical and Theoretical,
vol. 52, no. 4. IOP Publishing, 2019.'
ista: 'De Martino D. 2019. Feedback-induced self-oscillations in large interacting
systems subjected to phase transitions. Journal of Physics A: Mathematical and
Theoretical. 52(4), 045002.'
mla: 'De Martino, Daniele. “Feedback-Induced Self-Oscillations in Large Interacting
Systems Subjected to Phase Transitions.” Journal of Physics A: Mathematical
and Theoretical, vol. 52, no. 4, 045002, IOP Publishing, 2019, doi:10.1088/1751-8121/aaf2dd.'
short: 'D. De Martino, Journal of Physics A: Mathematical and Theoretical 52 (2019).'
date_created: 2019-02-24T22:59:19Z
date_published: 2019-01-07T00:00:00Z
date_updated: 2023-08-24T14:49:23Z
day: '07'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1088/1751-8121/aaf2dd
ec_funded: 1
external_id:
isi:
- '000455379500001'
file:
- access_level: open_access
checksum: 1112304ad363a6d8afaeccece36473cf
content_type: application/pdf
creator: kschuh
date_created: 2019-04-19T12:18:57Z
date_updated: 2020-07-14T12:47:17Z
file_id: '6344'
file_name: 2019_IOP_DeMartino.pdf
file_size: 1804557
relation: main_file
file_date_updated: 2020-07-14T12:47:17Z
has_accepted_license: '1'
intvolume: ' 52'
isi: 1
issue: '4'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: 'Journal of Physics A: Mathematical and Theoretical'
publication_status: published
publisher: IOP Publishing
quality_controlled: '1'
scopus_import: '1'
status: public
title: Feedback-induced self-oscillations in large interacting systems subjected to
phase transitions
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: 52
year: '2019'
...
---
_id: '6046'
abstract:
- lang: eng
text: Sudden stress often triggers diverse, temporally structured gene expression
responses in microbes, but it is largely unknown how variable in time such responses
are and if genes respond in the same temporal order in every single cell. Here,
we quantified timing variability of individual promoters responding to sublethal
antibiotic stress using fluorescent reporters, microfluidics, and time‐lapse microscopy.
We identified lower and upper bounds that put definite constraints on timing variability,
which varies strongly among promoters and conditions. Timing variability can be
interpreted using results from statistical kinetics, which enable us to estimate
the number of rate‐limiting molecular steps underlying different responses. We
found that just a few critical steps control some responses while others rely
on dozens of steps. To probe connections between different stress responses, we
then tracked the temporal order and response time correlations of promoter pairs
in individual cells. Our results support that, when bacteria are exposed to the
antibiotic nitrofurantoin, the ensuing oxidative stress and SOS responses are
part of the same causal chain of molecular events. In contrast, under trimethoprim,
the acid stress response and the SOS response are part of different chains of
events running in parallel. Our approach reveals fundamental constraints on gene
expression timing and provides new insights into the molecular events that underlie
the timing of stress responses.
acknowledged_ssus:
- _id: Bio
article_number: e8470
article_processing_charge: No
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: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: Mitosch K, Rieckh G, Bollenbach MT. Temporal order and precision of complex
stress responses in individual bacteria. Molecular systems biology. 2019;15(2).
doi:10.15252/msb.20188470
apa: Mitosch, K., Rieckh, G., & Bollenbach, M. T. (2019). Temporal order and
precision of complex stress responses in individual bacteria. Molecular Systems
Biology. Embo Press. https://doi.org/10.15252/msb.20188470
chicago: Mitosch, Karin, Georg Rieckh, and Mark Tobias Bollenbach. “Temporal Order
and Precision of Complex Stress Responses in Individual Bacteria.” Molecular
Systems Biology. Embo Press, 2019. https://doi.org/10.15252/msb.20188470.
ieee: K. Mitosch, G. Rieckh, and M. T. Bollenbach, “Temporal order and precision
of complex stress responses in individual bacteria,” Molecular systems biology,
vol. 15, no. 2. Embo Press, 2019.
ista: Mitosch K, Rieckh G, Bollenbach MT. 2019. Temporal order and precision of
complex stress responses in individual bacteria. Molecular systems biology. 15(2),
e8470.
mla: Mitosch, Karin, et al. “Temporal Order and Precision of Complex Stress Responses
in Individual Bacteria.” Molecular Systems Biology, vol. 15, no. 2, e8470,
Embo Press, 2019, doi:10.15252/msb.20188470.
short: K. Mitosch, G. Rieckh, M.T. Bollenbach, Molecular Systems Biology 15 (2019).
date_created: 2019-02-24T22:59:18Z
date_published: 2019-02-14T00:00:00Z
date_updated: 2023-08-24T14:49:53Z
day: '14'
department:
- _id: GaTk
doi: 10.15252/msb.20188470
external_id:
isi:
- '000459628300003'
pmid:
- '30765425'
intvolume: ' 15'
isi: 1
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pubmed/30765425
month: '02'
oa: 1
oa_version: Submitted Version
pmid: 1
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: Molecular systems biology
publication_status: published
publisher: Embo Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Temporal order and precision of complex stress responses in individual bacteria
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 15
year: '2019'
...
---
_id: '6784'
abstract:
- lang: eng
text: Mathematical models have been used successfully at diverse scales of biological
organization, ranging from ecology and population dynamics to stochastic reaction
events occurring between individual molecules in single cells. Generally, many
biological processes unfold across multiple scales, with mutations being the best
studied example of how stochasticity at the molecular scale can influence outcomes
at the population scale. In many other contexts, however, an analogous link between
micro- and macro-scale remains elusive, primarily due to the challenges involved
in setting up and analyzing multi-scale models. Here, we employ such a model to
investigate how stochasticity propagates from individual biochemical reaction
events in the bacterial innate immune system to the ecology of bacteria and bacterial
viruses. We show analytically how the dynamics of bacterial populations are shaped
by the activities of immunity-conferring enzymes in single cells and how the ecological
consequences imply optimal bacterial defense strategies against viruses. Our results
suggest that bacterial populations in the presence of viruses can either optimize
their initial growth rate or their population size, with the first strategy favoring
simple immunity featuring a single restriction modification system and the second
strategy favoring complex bacterial innate immunity featuring several simultaneously
active restriction modification systems.
article_number: e1007168
article_processing_charge: No
article_type: original
author:
- first_name: Jakob
full_name: Ruess, Jakob
id: 4A245D00-F248-11E8-B48F-1D18A9856A87
last_name: Ruess
orcid: 0000-0003-1615-3282
- first_name: Maros
full_name: Pleska, Maros
id: 4569785E-F248-11E8-B48F-1D18A9856A87
last_name: Pleska
orcid: 0000-0001-7460-7479
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Ruess J, Pleska M, Guet CC, Tkačik G. Molecular noise of innate immunity shapes
bacteria-phage ecologies. PLoS Computational Biology. 2019;15(7). doi:10.1371/journal.pcbi.1007168
apa: Ruess, J., Pleska, M., Guet, C. C., & Tkačik, G. (2019). Molecular noise
of innate immunity shapes bacteria-phage ecologies. PLoS Computational Biology.
Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007168
chicago: Ruess, Jakob, Maros Pleska, Calin C Guet, and Gašper Tkačik. “Molecular
Noise of Innate Immunity Shapes Bacteria-Phage Ecologies.” PLoS Computational
Biology. Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007168.
ieee: J. Ruess, M. Pleska, C. C. Guet, and G. Tkačik, “Molecular noise of innate
immunity shapes bacteria-phage ecologies,” PLoS Computational Biology,
vol. 15, no. 7. Public Library of Science, 2019.
ista: Ruess J, Pleska M, Guet CC, Tkačik G. 2019. Molecular noise of innate immunity
shapes bacteria-phage ecologies. PLoS Computational Biology. 15(7), e1007168.
mla: Ruess, Jakob, et al. “Molecular Noise of Innate Immunity Shapes Bacteria-Phage
Ecologies.” PLoS Computational Biology, vol. 15, no. 7, e1007168, Public
Library of Science, 2019, doi:10.1371/journal.pcbi.1007168.
short: J. Ruess, M. Pleska, C.C. Guet, G. Tkačik, PLoS Computational Biology 15
(2019).
date_created: 2019-08-11T21:59:19Z
date_published: 2019-07-02T00:00:00Z
date_updated: 2023-08-29T07:10:06Z
day: '02'
ddc:
- '570'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1371/journal.pcbi.1007168
external_id:
isi:
- '000481577700032'
file:
- access_level: open_access
checksum: 7ded4721b41c2a0fc66a1c634540416a
content_type: application/pdf
creator: dernst
date_created: 2019-08-12T12:27:26Z
date_updated: 2020-07-14T12:47:40Z
file_id: '6803'
file_name: 2019_PlosComputBiology_Ruess.pdf
file_size: 2200003
relation: main_file
file_date_updated: 2020-07-14T12:47:40Z
has_accepted_license: '1'
intvolume: ' 15'
isi: 1
issue: '7'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
project:
- _id: 251D65D8-B435-11E9-9278-68D0E5697425
grant_number: '24210'
name: Effects of Stochasticity on the Function of Restriction-Modi cation Systems
at the Single-Cell Level
- _id: 251BCBEC-B435-11E9-9278-68D0E5697425
grant_number: RGY0079/2011
name: Multi-Level Conflicts in Evolutionary Dynamics of Restriction-Modification
Systems
publication: PLoS Computational Biology
publication_identifier:
eissn:
- 1553-7358
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
record:
- id: '9786'
relation: research_data
status: public
scopus_import: '1'
status: public
title: Molecular noise of innate immunity shapes bacteria-phage ecologies
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: 15
year: '2019'
...
---
_id: '9786'
article_processing_charge: No
author:
- first_name: Jakob
full_name: Ruess, Jakob
id: 4A245D00-F248-11E8-B48F-1D18A9856A87
last_name: Ruess
orcid: 0000-0003-1615-3282
- first_name: Maros
full_name: Pleska, Maros
id: 4569785E-F248-11E8-B48F-1D18A9856A87
last_name: Pleska
orcid: 0000-0001-7460-7479
- first_name: Calin C
full_name: Guet, Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Ruess J, Pleska M, Guet CC, Tkačik G. Supporting text and results. 2019. doi:10.1371/journal.pcbi.1007168.s001
apa: Ruess, J., Pleska, M., Guet, C. C., & Tkačik, G. (2019). Supporting text
and results. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1007168.s001
chicago: Ruess, Jakob, Maros Pleska, Calin C Guet, and Gašper Tkačik. “Supporting
Text and Results.” Public Library of Science, 2019. https://doi.org/10.1371/journal.pcbi.1007168.s001.
ieee: J. Ruess, M. Pleska, C. C. Guet, and G. Tkačik, “Supporting text and results.”
Public Library of Science, 2019.
ista: Ruess J, Pleska M, Guet CC, Tkačik G. 2019. Supporting text and results, Public
Library of Science, 10.1371/journal.pcbi.1007168.s001.
mla: Ruess, Jakob, et al. Supporting Text and Results. Public Library of
Science, 2019, doi:10.1371/journal.pcbi.1007168.s001.
short: J. Ruess, M. Pleska, C.C. Guet, G. Tkačik, (2019).
date_created: 2021-08-06T08:23:43Z
date_published: 2019-07-02T00:00:00Z
date_updated: 2023-08-29T07:10:05Z
day: '02'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1371/journal.pcbi.1007168.s001
month: '07'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '6784'
relation: used_in_publication
status: public
status: public
title: Supporting text and results
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2019'
...