---
_id: '12156'
abstract:
- lang: eng
text: Models of transcriptional regulation that assume equilibrium binding of transcription
factors have been less successful at predicting gene expression from sequence
in eukaryotes than in bacteria. This could be due to the non-equilibrium nature
of eukaryotic regulation. Unfortunately, the space of possible non-equilibrium
mechanisms is vast and predominantly uninteresting. The key question is therefore
how this space can be navigated efficiently, to focus on mechanisms and models
that are biologically relevant. In this review, we advocate for the normative
role of theory—theory that prescribes rather than just describes—in providing
such a focus. Theory should expand its remit beyond inferring mechanistic models
from data, towards identifying non-equilibrium gene regulatory schemes that may
have been evolutionarily selected, despite their energy consumption, because they
are precise, reliable, fast, or otherwise outperform regulation at equilibrium.
We illustrate our reasoning by toy examples for which we provide simulation code.
acknowledgement: 'This work was supported through the Center for the Physics of Biological
Function (PHYe1734030) and by National Institutes of Health Grants R01GM097275 and
U01DK127429 (TG). GT acknowledges the support of the Austrian Science Fund grant
FWF P28844 and the Human Frontiers Science Program. '
article_number: '100435'
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Benjamin
full_name: Zoller, Benjamin
last_name: Zoller
- 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: '1'
citation:
ama: Zoller B, Gregor T, Tkačik G. Eukaryotic gene regulation at equilibrium, or
non? Current Opinion in Systems Biology. 2022;31(9). doi:10.1016/j.coisb.2022.100435
apa: Zoller, B., Gregor, T., & Tkačik, G. (2022). Eukaryotic gene regulation
at equilibrium, or non? Current Opinion in Systems Biology. Elsevier. https://doi.org/10.1016/j.coisb.2022.100435
chicago: Zoller, Benjamin, Thomas Gregor, and Gašper Tkačik. “Eukaryotic Gene Regulation
at Equilibrium, or Non?” Current Opinion in Systems Biology. Elsevier,
2022. https://doi.org/10.1016/j.coisb.2022.100435.
ieee: B. Zoller, T. Gregor, and G. Tkačik, “Eukaryotic gene regulation at equilibrium,
or non?,” Current Opinion in Systems Biology, vol. 31, no. 9. Elsevier,
2022.
ista: Zoller B, Gregor T, Tkačik G. 2022. Eukaryotic gene regulation at equilibrium,
or non? Current Opinion in Systems Biology. 31(9), 100435.
mla: Zoller, Benjamin, et al. “Eukaryotic Gene Regulation at Equilibrium, or Non?”
Current Opinion in Systems Biology, vol. 31, no. 9, 100435, Elsevier, 2022,
doi:10.1016/j.coisb.2022.100435.
short: B. Zoller, T. Gregor, G. Tkačik, Current Opinion in Systems Biology 31 (2022).
date_created: 2023-01-12T12:08:51Z
date_published: 2022-09-01T00:00:00Z
date_updated: 2023-02-13T09:20:34Z
day: '01'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1016/j.coisb.2022.100435
file:
- access_level: open_access
checksum: 97ef01e0cc60cdc84f45640a0f248fb0
content_type: application/pdf
creator: dernst
date_created: 2023-01-24T12:14:10Z
date_updated: 2023-01-24T12:14:10Z
file_id: '12362'
file_name: 2022_CurrentBiology_Zoller.pdf
file_size: 2214944
relation: main_file
success: 1
file_date_updated: 2023-01-24T12:14:10Z
has_accepted_license: '1'
intvolume: ' 31'
issue: '9'
keyword:
- Applied Mathematics
- Computer Science Applications
- Drug Discovery
- General Biochemistry
- Genetics and Molecular Biology
- Modeling and Simulation
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Current Opinion in Systems Biology
publication_identifier:
issn:
- 2452-3100
publication_status: published
publisher: Elsevier
quality_controlled: '1'
scopus_import: '1'
status: public
title: Eukaryotic gene regulation at equilibrium, or non?
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: 31
year: '2022'
...
---
_id: '8997'
abstract:
- lang: eng
text: Phenomenological relations such as Ohm’s or Fourier’s law have a venerable
history in physics but are still scarce in biology. This situation restrains predictive
theory. Here, we build on bacterial “growth laws,” which capture physiological
feedback between translation and cell growth, to construct a minimal biophysical
model for the combined action of ribosome-targeting antibiotics. Our model predicts
drug interactions like antagonism or synergy solely from responses to individual
drugs. We provide analytical results for limiting cases, which agree well with
numerical results. We systematically refine the model by including direct physical
interactions of different antibiotics on the ribosome. In a limiting case, our
model provides a mechanistic underpinning for recent predictions of higher-order
interactions that were derived using entropy maximization. We further refine the
model to include the effects of antibiotics that mimic starvation and the presence
of resistance genes. We describe the impact of a starvation-mimicking antibiotic
on drug interactions analytically and verify it experimentally. Our extended model
suggests a change in the type of drug interaction that depends on the strength
of resistance, which challenges established rescaling paradigms. We experimentally
show that the presence of unregulated resistance genes can lead to altered drug
interaction, which agrees with the prediction of the model. While minimal, the
model is readily adaptable and opens the door to predicting interactions of second
and higher-order in a broad range of biological systems.
acknowledgement: 'This work was supported in part by Tum stipend of Knafelj foundation
(to B.K.), Austrian Science Fund (FWF) standalone grants P 27201-B22 (to T.B.) and
P 28844(to G.T.), HFSP program Grant RGP0042/2013 (to T.B.), German Research Foundation
(DFG) individual grant BO 3502/2-1 (to T.B.), and German Research Foundation (DFG)
Collaborative Research Centre (SFB) 1310 (to T.B.). '
article_number: e1008529
article_processing_charge: Yes
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. Minimal biophysical model of combined antibiotic
action. PLOS Computational Biology. 2021;17. doi:10.1371/journal.pcbi.1008529
apa: Kavcic, B., Tkačik, G., & Bollenbach, M. T. (2021). Minimal biophysical
model of combined antibiotic action. PLOS Computational Biology. Public
Library of Science. https://doi.org/10.1371/journal.pcbi.1008529
chicago: Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “Minimal Biophysical
Model of Combined Antibiotic Action.” PLOS Computational Biology. Public
Library of Science, 2021. https://doi.org/10.1371/journal.pcbi.1008529.
ieee: B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Minimal biophysical model of
combined antibiotic action,” PLOS Computational Biology, vol. 17. Public
Library of Science, 2021.
ista: Kavcic B, Tkačik G, Bollenbach MT. 2021. Minimal biophysical model of combined
antibiotic action. PLOS Computational Biology. 17, e1008529.
mla: Kavcic, Bor, et al. “Minimal Biophysical Model of Combined Antibiotic Action.”
PLOS Computational Biology, vol. 17, e1008529, Public Library of Science,
2021, doi:10.1371/journal.pcbi.1008529.
short: B. Kavcic, G. Tkačik, M.T. Bollenbach, PLOS Computational Biology 17 (2021).
date_created: 2021-01-08T07:16:18Z
date_published: 2021-01-07T00:00:00Z
date_updated: 2024-02-21T12:41:41Z
day: '07'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1008529
external_id:
isi:
- '000608045000010'
file:
- access_level: open_access
checksum: e29f2b42651bef8e034781de8781ffac
content_type: application/pdf
creator: dernst
date_created: 2021-02-04T12:30:48Z
date_updated: 2021-02-04T12:30:48Z
file_id: '9092'
file_name: 2021_PlosComBio_Kavcic.pdf
file_size: 3690053
relation: main_file
success: 1
file_date_updated: 2021-02-04T12:30:48Z
has_accepted_license: '1'
intvolume: ' 17'
isi: 1
keyword:
- Modelling and Simulation
- Genetics
- Molecular Biology
- Antibiotics
- Drug interactions
language:
- iso: eng
month: '01'
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: PLOS Computational Biology
publication_identifier:
issn:
- 1553-7358
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
record:
- id: '7673'
relation: earlier_version
status: public
- id: '8930'
relation: research_data
status: public
status: public
title: Minimal biophysical model of combined antibiotic action
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: 17
year: '2021'
...
---
_id: '9226'
abstract:
- lang: eng
text: 'Half a century after Lewis Wolpert''s seminal conceptual advance on how cellular
fates distribute in space, we provide a brief historical perspective on how the
concept of positional information emerged and influenced the field of developmental
biology and beyond. We focus on a modern interpretation of this concept in terms
of information theory, largely centered on its application to cell specification
in the early Drosophila embryo. We argue that a true physical variable (position)
is encoded in local concentrations of patterning molecules, that this mapping
is stochastic, and that the processes by which positions and corresponding cell
fates are determined based on these concentrations need to take such stochasticity
into account. With this approach, we shift the focus from biological mechanisms,
molecules, genes and pathways to quantitative systems-level questions: where does
positional information reside, how it is transformed and accessed during development,
and what fundamental limits it is subject to?'
acknowledgement: This work was supported in part by the National Science Foundation,
through the Center for the Physics of Biological Function (PHY-1734030), by the
National Institutes of Health (R01GM097275) and by the Fonds zur Förderung der wissenschaftlichen
Forschung (FWF P28844). Deposited in PMC for release after 12 months.
article_number: dev176065
article_processing_charge: No
article_type: original
author:
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Thomas
full_name: Gregor, Thomas
last_name: Gregor
citation:
ama: Tkačik G, Gregor T. The many bits of positional information. Development.
2021;148(2). doi:10.1242/dev.176065
apa: Tkačik, G., & Gregor, T. (2021). The many bits of positional information.
Development. The Company of Biologists. https://doi.org/10.1242/dev.176065
chicago: Tkačik, Gašper, and Thomas Gregor. “The Many Bits of Positional Information.”
Development. The Company of Biologists, 2021. https://doi.org/10.1242/dev.176065.
ieee: G. Tkačik and T. Gregor, “The many bits of positional information,” Development,
vol. 148, no. 2. The Company of Biologists, 2021.
ista: Tkačik G, Gregor T. 2021. The many bits of positional information. Development.
148(2), dev176065.
mla: Tkačik, Gašper, and Thomas Gregor. “The Many Bits of Positional Information.”
Development, vol. 148, no. 2, dev176065, The Company of Biologists, 2021,
doi:10.1242/dev.176065.
short: G. Tkačik, T. Gregor, Development 148 (2021).
date_created: 2021-03-07T23:01:25Z
date_published: 2021-02-01T00:00:00Z
date_updated: 2023-08-07T13:57:30Z
day: '01'
department:
- _id: GaTk
doi: 10.1242/dev.176065
external_id:
isi:
- '000613906000007'
pmid:
- '33526425'
intvolume: ' 148'
isi: 1
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1242/dev.176065
month: '02'
oa: 1
oa_version: Published Version
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: Development
publication_identifier:
eissn:
- 1477-9129
publication_status: published
publisher: The Company of Biologists
quality_controlled: '1'
scopus_import: '1'
status: public
title: The many bits of positional information
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 148
year: '2021'
...
---
_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: 2024-03-25T23:30:05Z
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: 2024-03-25T23:30:05Z
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: '6900'
abstract:
- lang: eng
text: Across diverse biological systems—ranging from neural networks to intracellular
signaling and genetic regulatory networks—the information about changes in the
environment is frequently encoded in the full temporal dynamics of the network
nodes. A pressing data-analysis challenge has thus been to efficiently estimate
the amount of information that these dynamics convey from experimental data. Here
we develop and evaluate decoding-based estimation methods to lower bound the mutual
information about a finite set of inputs, encoded in single-cell high-dimensional
time series data. For biological reaction networks governed by the chemical Master
equation, we derive model-based information approximations and analytical upper
bounds, against which we benchmark our proposed model-free decoding estimators.
In contrast to the frequently-used k-nearest-neighbor estimator, decoding-based
estimators robustly extract a large fraction of the available information from
high-dimensional trajectories with a realistic number of data samples. We apply
these estimators to previously published data on Erk and Ca2+ signaling in mammalian
cells and to yeast stress-response, and find that substantial amount of information
about environmental state can be encoded by non-trivial response statistics even
in stationary signals. We argue that these single-cell, decoding-based information
estimates, rather than the commonly-used tests for significant differences between
selected population response statistics, provide a proper and unbiased measure
for the performance of biological signaling networks.
article_processing_charge: No
author:
- first_name: Sarah A
full_name: Cepeda Humerez, Sarah A
id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87
last_name: Cepeda Humerez
- first_name: Jakob
full_name: Ruess, Jakob
last_name: Ruess
orcid: 0000-0003-1615-3282
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Cepeda Humerez SA, Ruess J, Tkačik G. Estimating information in time-varying
signals. PLoS computational biology. 2019;15(9):e1007290. doi:10.1371/journal.pcbi.1007290
apa: Cepeda Humerez, S. A., Ruess, J., & Tkačik, G. (2019). Estimating information
in time-varying signals. PLoS Computational Biology. Public Library of
Science. https://doi.org/10.1371/journal.pcbi.1007290
chicago: Cepeda Humerez, Sarah A, Jakob Ruess, and Gašper Tkačik. “Estimating Information
in Time-Varying Signals.” PLoS Computational Biology. Public Library of
Science, 2019. https://doi.org/10.1371/journal.pcbi.1007290.
ieee: S. A. Cepeda Humerez, J. Ruess, and G. Tkačik, “Estimating information in
time-varying signals,” PLoS computational biology, vol. 15, no. 9. Public
Library of Science, p. e1007290, 2019.
ista: Cepeda Humerez SA, Ruess J, Tkačik G. 2019. Estimating information in time-varying
signals. PLoS computational biology. 15(9), e1007290.
mla: Cepeda Humerez, Sarah A., et al. “Estimating Information in Time-Varying Signals.”
PLoS Computational Biology, vol. 15, no. 9, Public Library of Science,
2019, p. e1007290, doi:10.1371/journal.pcbi.1007290.
short: S.A. Cepeda Humerez, J. Ruess, G. Tkačik, PLoS Computational Biology 15 (2019)
e1007290.
date_created: 2019-09-22T22:00:37Z
date_published: 2019-09-03T00:00:00Z
date_updated: 2023-09-07T12:55:21Z
day: '03'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1007290
external_id:
isi:
- '000489741800021'
pmid:
- '31479447'
file:
- access_level: open_access
checksum: 81bdce1361c9aa8395d6fa635fb6ab47
content_type: application/pdf
creator: kschuh
date_created: 2019-10-01T10:53:45Z
date_updated: 2020-07-14T12:47:44Z
file_id: '6925'
file_name: 2019_PLoS_Cepeda-Humerez.pdf
file_size: 3081855
relation: main_file
file_date_updated: 2020-07-14T12:47:44Z
has_accepted_license: '1'
intvolume: ' 15'
isi: 1
issue: '9'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: e1007290
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: PLoS computational biology
publication_identifier:
eissn:
- '15537358'
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
record:
- id: '6473'
relation: part_of_dissertation
status: public
scopus_import: '1'
status: public
title: Estimating information in time-varying signals
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: '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
arxiv: 1
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: '6071'
abstract:
- lang: eng
text: 'Transcription factors, by binding to specific sequences on the DNA, control
the precise spatio-temporal expression of genes inside a cell. However, this specificity
is limited, leading to frequent incorrect binding of transcription factors that
might have deleterious consequences on the cell. By constructing a biophysical
model of TF-DNA binding in the context of gene regulation, I will first explore
how regulatory constraints can strongly shape the distribution of a population
in sequence space. Then, by directly linking this to a picture of multiple types
of transcription factors performing their functions simultaneously inside the
cell, I will explore the extent of regulatory crosstalk -- incorrect binding interactions
between transcription factors and binding sites that lead to erroneous regulatory
states -- and understand the constraints this places on the design of regulatory
systems. I will then develop a generic theoretical framework to investigate the
coevolution of multiple transcription factors and multiple binding sites, in the
context of a gene regulatory network that performs a certain function. As a particular
tractable version of this problem, I will consider the evolution of two transcription
factors when they transmit upstream signals to downstream target genes. Specifically,
I will describe the evolutionary steady states and the evolutionary pathways involved,
along with their timescales, of a system that initially undergoes a transcription
factor duplication event. To connect this important theoretical model to the prominent
biological event of transcription factor duplication giving rise to paralogous
families, I will then describe a bioinformatics analysis of C2H2 Zn-finger transcription
factors, a major family in humans, and focus on the patterns of evolution that
paralogs have undergone in their various protein domains in the recent past. '
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Roshan
full_name: Prizak, Roshan
id: 4456104E-F248-11E8-B48F-1D18A9856A87
last_name: Prizak
citation:
ama: Prizak R. Coevolution of transcription factors and their binding sites in sequence
space. 2019. doi:10.15479/at:ista:th6071
apa: Prizak, R. (2019). Coevolution of transcription factors and their binding
sites in sequence space. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:th6071
chicago: Prizak, Roshan. “Coevolution of Transcription Factors and Their Binding
Sites in Sequence Space.” Institute of Science and Technology Austria, 2019. https://doi.org/10.15479/at:ista:th6071.
ieee: R. Prizak, “Coevolution of transcription factors and their binding sites in
sequence space,” Institute of Science and Technology Austria, 2019.
ista: Prizak R. 2019. Coevolution of transcription factors and their binding sites
in sequence space. Institute of Science and Technology Austria.
mla: Prizak, Roshan. Coevolution of Transcription Factors and Their Binding Sites
in Sequence Space. Institute of Science and Technology Austria, 2019, doi:10.15479/at:ista:th6071.
short: R. Prizak, Coevolution of Transcription Factors and Their Binding Sites in
Sequence Space, Institute of Science and Technology Austria, 2019.
date_created: 2019-03-06T16:16:10Z
date_published: 2019-03-11T00:00:00Z
date_updated: 2025-05-28T11:57:05Z
day: '11'
ddc:
- '576'
degree_awarded: PhD
department:
- _id: GaTk
- _id: NiBa
doi: 10.15479/at:ista:th6071
file:
- access_level: open_access
checksum: e60a72de35d270b31f1a23d50f224ec0
content_type: application/pdf
creator: rprizak
date_created: 2019-03-06T16:05:07Z
date_updated: 2020-07-14T12:47:18Z
file_id: '6072'
file_name: Thesis_final_PDFA_RoshanPrizak.pdf
file_size: 20995465
relation: main_file
- access_level: closed
checksum: 67c2630333d05ebafef5f018863a8465
content_type: application/zip
creator: rprizak
date_created: 2019-03-06T16:09:39Z
date_updated: 2020-07-14T12:47:18Z
file_id: '6073'
file_name: thesis_v2_merge.zip
file_size: 85705272
relation: source_file
title: Latex files
file_date_updated: 2020-07-14T12:47:18Z
has_accepted_license: '1'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
page: '189'
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '1358'
relation: part_of_dissertation
status: public
- id: '955'
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
title: Coevolution of transcription factors and their binding sites in sequence space
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2019'
...
---
_id: '281'
abstract:
- lang: eng
text: 'Although cells respond specifically to environments, how environmental identity
is encoded intracellularly is not understood. Here, we study this organization
of information in budding yeast by estimating the mutual information between environmental
transitions and the dynamics of nuclear translocation for 10 transcription factors.
Our method of estimation is general, scalable, and based on decoding from single
cells. The dynamics of the transcription factors are necessary to encode the highest
amounts of extracellular information, and we show that information is transduced
through two channels: Generalists (Msn2/4, Tod6 and Dot6, Maf1, and Sfp1) can
encode the nature of multiple stresses, but only if stress is high; specialists
(Hog1, Yap1, and Mig1/2) encode one particular stress, but do so more quickly
and for a wider range of magnitudes. In particular, Dot6 encodes almost as much
information as Msn2, the master regulator of the environmental stress response.
Each transcription factor reports differently, and it is only their collective
behavior that distinguishes between multiple environmental states. Changes in
the dynamics of the localization of transcription factors thus constitute a precise,
distributed internal representation of extracellular change. We predict that such
multidimensional representations are common in cellular decision-making.'
acknowledgement: This work was supported by the Biotechnology and Biological Sciences
Research Council (J.M.J.P., I.F., and P.S.S.), the Engineering and Physical Sciences
Research Council (EPSRC) (A.A.G.), and Austrian Science Fund Grant FWF P28844 (to
G.T.).
article_processing_charge: No
article_type: original
author:
- first_name: Alejandro
full_name: Granados, Alejandro
last_name: Granados
- first_name: Julian
full_name: Pietsch, Julian
last_name: Pietsch
- first_name: Sarah A
full_name: Cepeda Humerez, Sarah A
id: 3DEE19A4-F248-11E8-B48F-1D18A9856A87
last_name: Cepeda Humerez
- first_name: Isebail
full_name: Farquhar, Isebail
last_name: Farquhar
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Peter
full_name: Swain, Peter
last_name: Swain
citation:
ama: Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkačik G, Swain P. Distributed
and dynamic intracellular organization of extracellular information. PNAS.
2018;115(23):6088-6093. doi:10.1073/pnas.1716659115
apa: Granados, A., Pietsch, J., Cepeda Humerez, S. A., Farquhar, I., Tkačik, G.,
& Swain, P. (2018). Distributed and dynamic intracellular organization of
extracellular information. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1716659115
chicago: Granados, Alejandro, Julian Pietsch, Sarah A Cepeda Humerez, Isebail Farquhar,
Gašper Tkačik, and Peter Swain. “Distributed and Dynamic Intracellular Organization
of Extracellular Information.” PNAS. National Academy of Sciences, 2018.
https://doi.org/10.1073/pnas.1716659115.
ieee: A. Granados, J. Pietsch, S. A. Cepeda Humerez, I. Farquhar, G. Tkačik, and
P. Swain, “Distributed and dynamic intracellular organization of extracellular
information,” PNAS, vol. 115, no. 23. National Academy of Sciences, pp.
6088–6093, 2018.
ista: Granados A, Pietsch J, Cepeda Humerez SA, Farquhar I, Tkačik G, Swain P. 2018.
Distributed and dynamic intracellular organization of extracellular information.
PNAS. 115(23), 6088–6093.
mla: Granados, Alejandro, et al. “Distributed and Dynamic Intracellular Organization
of Extracellular Information.” PNAS, vol. 115, no. 23, National Academy
of Sciences, 2018, pp. 6088–93, doi:10.1073/pnas.1716659115.
short: A. Granados, J. Pietsch, S.A. Cepeda Humerez, I. Farquhar, G. Tkačik, P.
Swain, PNAS 115 (2018) 6088–6093.
date_created: 2018-12-11T11:45:35Z
date_published: 2018-06-05T00:00:00Z
date_updated: 2023-09-11T12:58:24Z
day: '05'
department:
- _id: GaTk
doi: 10.1073/pnas.1716659115
external_id:
isi:
- '000434114900071'
pmid:
- '29784812'
intvolume: ' 115'
isi: 1
issue: '23'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.biorxiv.org/content/early/2017/09/21/192039
month: '06'
oa: 1
oa_version: Preprint
page: 6088 - 6093
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: PNAS
publication_status: published
publisher: National Academy of Sciences
publist_id: '7618'
quality_controlled: '1'
related_material:
record:
- id: '6473'
relation: part_of_dissertation
status: public
scopus_import: '1'
status: public
title: Distributed and dynamic intracellular organization of extracellular information
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 115
year: '2018'
...
---
_id: '5587'
abstract:
- lang: eng
text: "Supporting material to the article \r\nSTATISTICAL MECHANICS FOR METABOLIC
NETWORKS IN STEADY-STATE GROWTH\r\n\r\nboundscoli.dat\r\nFlux Bounds of the E.
coli catabolic core model iAF1260 in a glucose limited minimal medium. \r\n\r\npolcoli.dat\r\nMatrix
enconding the polytope of the E. coli catabolic core model iAF1260 in a glucose
limited minimal medium, \r\nobtained from the soichiometric matrix by standard
linear algebra (reduced row echelon form).\r\n\r\nellis.dat\r\nApproximate Lowner-John
ellipsoid rounding the polytope of the E. coli catabolic core model iAF1260 in
a glucose limited minimal medium\r\nobtained with the Lovasz method.\r\n\r\npoint0.dat\r\nCenter
of the approximate Lowner-John ellipsoid rounding the polytope of the E. coli
catabolic core model iAF1260 in a glucose limited minimal medium\r\nobtained with
the Lovasz method.\r\n\r\nlovasz.cpp \r\nThis c++ code file receives in input
the polytope of the feasible steady states of a metabolic network, \r\n(matrix
and bounds), and it gives in output an approximate Lowner-John ellipsoid rounding
the polytope\r\nwith the Lovasz method \r\nNB inputs are referred by defaults
to the catabolic core of the E.Coli network iAF1260. \r\nFor further details we
refer to PLoS ONE 10.4 e0122670 (2015).\r\n\r\nsampleHRnew.cpp \r\nThis c++
code file receives in input the polytope of the feasible steady states of a metabolic
network, \r\n(matrix and bounds), the ellipsoid rounding the polytope, a point
inside and \r\nit gives in output a max entropy sampling at fixed average growth
rate \r\nof the steady states by performing an Hit-and-Run Monte Carlo Markov
chain.\r\nNB inputs are referred by defaults to the catabolic core of the E.Coli
network iAF1260. \r\nFor further details we refer to PLoS ONE 10.4 e0122670 (2015)."
article_processing_charge: No
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: De Martino D, Tkačik G. Supporting materials “STATISTICAL MECHANICS FOR METABOLIC
NETWORKS IN STEADY-STATE GROWTH.” 2018. doi:10.15479/AT:ISTA:62
apa: De Martino, D., & Tkačik, G. (2018). Supporting materials “STATISTICAL
MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science
and Technology Austria. https://doi.org/10.15479/AT:ISTA:62
chicago: De Martino, Daniele, and Gašper Tkačik. “Supporting Materials ‘STATISTICAL
MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science
and Technology Austria, 2018. https://doi.org/10.15479/AT:ISTA:62.
ieee: D. De Martino and G. Tkačik, “Supporting materials ‘STATISTICAL MECHANICS
FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.’” Institute of Science and Technology
Austria, 2018.
ista: De Martino D, Tkačik G. 2018. Supporting materials ‘STATISTICAL MECHANICS
FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH’, Institute of Science and Technology
Austria, 10.15479/AT:ISTA:62.
mla: De Martino, Daniele, and Gašper Tkačik. Supporting Materials “STATISTICAL
MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH.” Institute of Science
and Technology Austria, 2018, doi:10.15479/AT:ISTA:62.
short: D. De Martino, G. Tkačik, (2018).
datarep_id: '111'
date_created: 2018-12-12T12:31:41Z
date_published: 2018-09-21T00:00:00Z
date_updated: 2024-02-21T13:45:39Z
day: '21'
ddc:
- '530'
department:
- _id: GaTk
doi: 10.15479/AT:ISTA:62
ec_funded: 1
file:
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checksum: 97992e3e8cf8544ec985a48971708726
content_type: application/zip
creator: system
date_created: 2018-12-12T13:05:13Z
date_updated: 2020-07-14T12:47:08Z
file_id: '5641'
file_name: IST-2018-111-v1+1_CODES.zip
file_size: 14376
relation: main_file
file_date_updated: 2020-07-14T12:47:08Z
has_accepted_license: '1'
keyword:
- metabolic networks
- e.coli core
- maximum entropy
- monte carlo markov chain sampling
- ellipsoidal rounding
license: https://creativecommons.org/publicdomain/zero/1.0/
month: '09'
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
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '161'
relation: research_paper
status: public
status: public
title: Supporting materials "STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE
GROWTH"
tmp:
image: /images/cc_0.png
legal_code_url: https://creativecommons.org/publicdomain/zero/1.0/legalcode
name: Creative Commons Public Domain Dedication (CC0 1.0)
short: CC0 (1.0)
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2018'
...
---
_id: '161'
abstract:
- lang: eng
text: 'Which properties of metabolic networks can be derived solely from stoichiometry?
Predictive results have been obtained by flux balance analysis (FBA), by postulating
that cells set metabolic fluxes to maximize growth rate. Here we consider a generalization
of FBA to single-cell level using maximum entropy modeling, which we extend and
test experimentally. Specifically, we define for Escherichia coli metabolism a
flux distribution that yields the experimental growth rate: the model, containing
FBA as a limit, provides a better match to measured fluxes and it makes a wide
range of predictions: on flux variability, regulation, and correlations; on the
relative importance of stoichiometry vs. optimization; on scaling relations for
growth rate distributions. We validate the latter here with single-cell data at
different sub-inhibitory antibiotic concentrations. The model quantifies growth
optimization as emerging from the interplay of competitive dynamics in the population
and regulation of metabolism at the level of single cells.'
article_number: '2988'
article_processing_charge: No
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
- first_name: Andersson Anna
full_name: Mc, Andersson Anna
last_name: Mc
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- 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: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. Statistical mechanics
for metabolic networks during steady state growth. Nature Communications.
2018;9(1). doi:10.1038/s41467-018-05417-9
apa: De Martino, D., Mc, A. A., Bergmiller, T., Guet, C. C., & Tkačik, G. (2018).
Statistical mechanics for metabolic networks during steady state growth. Nature
Communications. Springer Nature. https://doi.org/10.1038/s41467-018-05417-9
chicago: De Martino, Daniele, Andersson Anna Mc, Tobias Bergmiller, Calin C Guet,
and Gašper Tkačik. “Statistical Mechanics for Metabolic Networks during Steady
State Growth.” Nature Communications. Springer Nature, 2018. https://doi.org/10.1038/s41467-018-05417-9.
ieee: D. De Martino, A. A. Mc, T. Bergmiller, C. C. Guet, and G. Tkačik, “Statistical
mechanics for metabolic networks during steady state growth,” Nature Communications,
vol. 9, no. 1. Springer Nature, 2018.
ista: De Martino D, Mc AA, Bergmiller T, Guet CC, Tkačik G. 2018. Statistical mechanics
for metabolic networks during steady state growth. Nature Communications. 9(1),
2988.
mla: De Martino, Daniele, et al. “Statistical Mechanics for Metabolic Networks during
Steady State Growth.” Nature Communications, vol. 9, no. 1, 2988, Springer
Nature, 2018, doi:10.1038/s41467-018-05417-9.
short: D. De Martino, A.A. Mc, T. Bergmiller, C.C. Guet, G. Tkačik, Nature Communications
9 (2018).
date_created: 2018-12-11T11:44:57Z
date_published: 2018-07-30T00:00:00Z
date_updated: 2024-02-21T13:45:39Z
day: '30'
ddc:
- '570'
department:
- _id: GaTk
- _id: CaGu
doi: 10.1038/s41467-018-05417-9
ec_funded: 1
external_id:
isi:
- '000440149300021'
file:
- access_level: open_access
checksum: 3ba7ab27b27723c7dcf633e8fc1f8f18
content_type: application/pdf
creator: dernst
date_created: 2018-12-17T16:44:28Z
date_updated: 2020-07-14T12:45:06Z
file_id: '5728'
file_name: 2018_NatureComm_DeMartino.pdf
file_size: 1043205
relation: main_file
file_date_updated: 2020-07-14T12:45:06Z
has_accepted_license: '1'
intvolume: ' 9'
isi: 1
issue: '1'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Nature Communications
publication_status: published
publisher: Springer Nature
publist_id: '7760'
quality_controlled: '1'
related_material:
record:
- id: '5587'
relation: popular_science
status: public
scopus_import: '1'
status: public
title: Statistical mechanics for metabolic networks during steady state growth
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: 9
year: '2018'
...
---
_id: '665'
abstract:
- lang: eng
text: The molecular mechanisms underlying phenotypic variation in isogenic bacterial
populations remain poorly understood.We report that AcrAB-TolC, the main multidrug
efflux pump of Escherichia coli, exhibits a strong partitioning bias for old cell
poles by a segregation mechanism that is mediated by ternary AcrAB-TolC complex
formation. Mother cells inheriting old poles are phenotypically distinct and display
increased drug efflux activity relative to daughters. Consequently, we find systematic
and long-lived growth differences between mother and daughter cells in the presence
of subinhibitory drug concentrations. A simple model for biased partitioning predicts
a population structure of long-lived and highly heterogeneous phenotypes. This
straightforward mechanism of generating sustained growth rate differences at subinhibitory
antibiotic concentrations has implications for understanding the emergence of
multidrug resistance in bacteria.
article_processing_charge: No
article_type: original
author:
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Anna M
full_name: Andersson, Anna M
id: 2B8A40DA-F248-11E8-B48F-1D18A9856A87
last_name: Andersson
orcid: 0000-0003-2912-6769
- first_name: Kathrin
full_name: Tomasek, Kathrin
id: 3AEC8556-F248-11E8-B48F-1D18A9856A87
last_name: Tomasek
orcid: 0000-0003-3768-877X
- first_name: Enrique
full_name: Balleza, Enrique
last_name: Balleza
- first_name: Daniel
full_name: Kiviet, Daniel
last_name: Kiviet
- first_name: Robert
full_name: Hauschild, Robert
id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87
last_name: Hauschild
orcid: 0000-0001-9843-3522
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
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: Bergmiller T, Andersson AM, Tomasek K, et al. Biased partitioning of the multidrug
efflux pump AcrAB TolC underlies long lived phenotypic heterogeneity. Science.
2017;356(6335):311-315. doi:10.1126/science.aaf4762
apa: Bergmiller, T., Andersson, A. M., Tomasek, K., Balleza, E., Kiviet, D., Hauschild,
R., … Guet, C. C. (2017). Biased partitioning of the multidrug efflux pump AcrAB
TolC underlies long lived phenotypic heterogeneity. Science. American Association
for the Advancement of Science. https://doi.org/10.1126/science.aaf4762
chicago: Bergmiller, Tobias, Anna M Andersson, Kathrin Tomasek, Enrique Balleza,
Daniel Kiviet, Robert Hauschild, Gašper Tkačik, and Calin C Guet. “Biased Partitioning
of the Multidrug Efflux Pump AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.”
Science. American Association for the Advancement of Science, 2017. https://doi.org/10.1126/science.aaf4762.
ieee: T. Bergmiller et al., “Biased partitioning of the multidrug efflux
pump AcrAB TolC underlies long lived phenotypic heterogeneity,” Science,
vol. 356, no. 6335. American Association for the Advancement of Science, pp. 311–315,
2017.
ista: Bergmiller T, Andersson AM, Tomasek K, Balleza E, Kiviet D, Hauschild R, Tkačik
G, Guet CC. 2017. Biased partitioning of the multidrug efflux pump AcrAB TolC
underlies long lived phenotypic heterogeneity. Science. 356(6335), 311–315.
mla: Bergmiller, Tobias, et al. “Biased Partitioning of the Multidrug Efflux Pump
AcrAB TolC Underlies Long Lived Phenotypic Heterogeneity.” Science, vol.
356, no. 6335, American Association for the Advancement of Science, 2017, pp.
311–15, doi:10.1126/science.aaf4762.
short: T. Bergmiller, A.M. Andersson, K. Tomasek, E. Balleza, D. Kiviet, R. Hauschild,
G. Tkačik, C.C. Guet, Science 356 (2017) 311–315.
date_created: 2018-12-11T11:47:48Z
date_published: 2017-04-21T00:00:00Z
date_updated: 2024-02-21T13:49:00Z
day: '21'
department:
- _id: CaGu
- _id: GaTk
- _id: Bio
doi: 10.1126/science.aaf4762
intvolume: ' 356'
issue: '6335'
language:
- iso: eng
month: '04'
oa_version: None
page: 311 - 315
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Science
publication_identifier:
issn:
- '00368075'
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '7064'
quality_controlled: '1'
related_material:
record:
- id: '5560'
relation: popular_science
status: public
scopus_import: 1
status: public
title: Biased partitioning of the multidrug efflux pump AcrAB TolC underlies long
lived phenotypic heterogeneity
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 356
year: '2017'
...
---
_id: '613'
abstract:
- lang: eng
text: 'Bacteria in groups vary individually, and interact with other bacteria and
the environment to produce population-level patterns of gene expression. Investigating
such behavior in detail requires measuring and controlling populations at the
single-cell level alongside precisely specified interactions and environmental
characteristics. Here we present an automated, programmable platform that combines
image-based gene expression and growth measurements with on-line optogenetic expression
control for hundreds of individual Escherichia coli cells over days, in a dynamically
adjustable environment. This integrated platform broadly enables experiments that
bridge individual and population behaviors. We demonstrate: (i) population structuring
by independent closed-loop control of gene expression in many individual cells,
(ii) cell-cell variation control during antibiotic perturbation, (iii) hybrid
bio-digital circuits in single cells, and freely specifiable digital communication
between individual bacteria. These examples showcase the potential for real-time
integration of theoretical models with measurement and control of many individual
cells to investigate and engineer microbial population behavior.'
acknowledgement: We are grateful to M. Lang, H. Janovjak, M. Khammash, A. Milias-Argeitis,
M. Rullan, G. Batt, A. Bosma-Moody, Aryan, S. Leibler, and members of the Guet and
Tkačik groups for helpful discussion, comments, and suggestions. We thank A. Moglich,
T. Mathes, J. Tabor, and S. Schmidl for kind gifts of strains, and R. Hauschild,
B. Knep, M. Lang, T. Asenov, E. Papusheva, T. Menner, T. Adletzberger, and J. Merrin
for technical assistance. The research leading to these results has received funding
from the People Programme (Marie Curie Actions) of the European Union’s Seventh
Framework Programme (FP7/2007–2013) under REA grant agreement no. [291734]. (to
R.C. and J.R.), Austrian Science Fund grant FWF P28844 (to G.T.), and internal IST
Austria Interdisciplinary Project Support. J.R. acknowledges support from the Agence
Nationale de la Recherche (ANR) under Grant Nos. ANR-16-CE33-0018 (MEMIP), ANR-16-CE12-0025
(COGEX) and ANR-10-BINF-06-01 (ICEBERG).
article_number: '1535'
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Remy P
full_name: Chait, Remy P
id: 3464AE84-F248-11E8-B48F-1D18A9856A87
last_name: Chait
orcid: 0000-0003-0876-3187
- first_name: Jakob
full_name: Ruess, Jakob
id: 4A245D00-F248-11E8-B48F-1D18A9856A87
last_name: Ruess
orcid: 0000-0003-1615-3282
- first_name: Tobias
full_name: Bergmiller, Tobias
id: 2C471CFA-F248-11E8-B48F-1D18A9856A87
last_name: Bergmiller
orcid: 0000-0001-5396-4346
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
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: Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. Shaping bacterial population
behavior through computer interfaced control of individual cells. Nature Communications.
2017;8(1). doi:10.1038/s41467-017-01683-1
apa: Chait, R. P., Ruess, J., Bergmiller, T., Tkačik, G., & Guet, C. C. (2017).
Shaping bacterial population behavior through computer interfaced control of individual
cells. Nature Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-01683-1
chicago: Chait, Remy P, Jakob Ruess, Tobias Bergmiller, Gašper Tkačik, and Calin
C Guet. “Shaping Bacterial Population Behavior through Computer Interfaced Control
of Individual Cells.” Nature Communications. Nature Publishing Group, 2017.
https://doi.org/10.1038/s41467-017-01683-1.
ieee: R. P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, and C. C. Guet, “Shaping
bacterial population behavior through computer interfaced control of individual
cells,” Nature Communications, vol. 8, no. 1. Nature Publishing Group,
2017.
ista: Chait RP, Ruess J, Bergmiller T, Tkačik G, Guet CC. 2017. Shaping bacterial
population behavior through computer interfaced control of individual cells. Nature
Communications. 8(1), 1535.
mla: Chait, Remy P., et al. “Shaping Bacterial Population Behavior through Computer
Interfaced Control of Individual Cells.” Nature Communications, vol. 8,
no. 1, 1535, Nature Publishing Group, 2017, doi:10.1038/s41467-017-01683-1.
short: R.P. Chait, J. Ruess, T. Bergmiller, G. Tkačik, C.C. Guet, Nature Communications
8 (2017).
date_created: 2018-12-11T11:47:30Z
date_published: 2017-12-01T00:00:00Z
date_updated: 2021-01-12T08:06:15Z
day: '01'
ddc:
- '576'
- '579'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1038/s41467-017-01683-1
ec_funded: 1
file:
- access_level: open_access
checksum: 44bb5d0229926c23a9955d9fe0f9723f
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:16:05Z
date_updated: 2020-07-14T12:47:20Z
file_id: '5190'
file_name: IST-2017-911-v1+1_s41467-017-01683-1.pdf
file_size: 1951699
relation: main_file
file_date_updated: 2020-07-14T12:47:20Z
has_accepted_license: '1'
intvolume: ' 8'
issue: '1'
language:
- iso: eng
month: '12'
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
- _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:
- '20411723'
publication_status: published
publisher: Nature Publishing Group
publist_id: '7191'
pubrep_id: '911'
quality_controlled: '1'
scopus_import: 1
status: public
title: Shaping bacterial population behavior through computer interfaced control of
individual cells
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: 8
year: '2017'
...
---
_id: '943'
abstract:
- lang: eng
text: Like many developing tissues, the vertebrate neural tube is patterned by antiparallel
morphogen gradients. To understand how these inputs are interpreted, we measured
morphogen signaling and target gene expression in mouse embryos and chick ex vivo
assays. From these data, we derived and validated a characteristic decoding map
that relates morphogen input to the positional identity of neural progenitors.
Analysis of the observed responses indicates that the underlying interpretation
strategy minimizes patterning errors in response to the joint input of noisy opposing
gradients. We reverse-engineered a transcriptional network that provides a mechanistic
basis for the observed cell fate decisions and accounts for the precision and
dynamics of pattern formation. Together, our data link opposing gradient dynamics
in a growing tissue to precise pattern formation.
article_processing_charge: No
author:
- 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: Yoji
full_name: Tabata, Yoji
last_name: Tabata
- first_name: Nathalie
full_name: Brandenberg, Nathalie
last_name: Brandenberg
- first_name: Matthias
full_name: Lutolf, Matthias
last_name: Lutolf
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Tobias
full_name: Bollenbach, Tobias
last_name: Bollenbach
- first_name: James
full_name: Briscoe, James
last_name: Briscoe
- first_name: Anna
full_name: Kicheva, Anna
id: 3959A2A0-F248-11E8-B48F-1D18A9856A87
last_name: Kicheva
orcid: 0000-0003-4509-4998
citation:
ama: Zagórski MP, Tabata Y, Brandenberg N, et al. Decoding of position in the developing
neural tube from antiparallel morphogen gradients. Science. 2017;356(6345):1379-1383.
doi:10.1126/science.aam5887
apa: Zagórski, M. P., Tabata, Y., Brandenberg, N., Lutolf, M., Tkačik, G., Bollenbach,
T., … Kicheva, A. (2017). Decoding of position in the developing neural tube from
antiparallel morphogen gradients. Science. American Association for the
Advancement of Science. https://doi.org/10.1126/science.aam5887
chicago: Zagórski, Marcin P, Yoji Tabata, Nathalie Brandenberg, Matthias Lutolf,
Gašper Tkačik, Tobias Bollenbach, James Briscoe, and Anna Kicheva. “Decoding of
Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.”
Science. American Association for the Advancement of Science, 2017. https://doi.org/10.1126/science.aam5887.
ieee: M. P. Zagórski et al., “Decoding of position in the developing neural
tube from antiparallel morphogen gradients,” Science, vol. 356, no. 6345.
American Association for the Advancement of Science, pp. 1379–1383, 2017.
ista: Zagórski MP, Tabata Y, Brandenberg N, Lutolf M, Tkačik G, Bollenbach T, Briscoe
J, Kicheva A. 2017. Decoding of position in the developing neural tube from antiparallel
morphogen gradients. Science. 356(6345), 1379–1383.
mla: Zagórski, Marcin P., et al. “Decoding of Position in the Developing Neural
Tube from Antiparallel Morphogen Gradients.” Science, vol. 356, no. 6345,
American Association for the Advancement of Science, 2017, pp. 1379–83, doi:10.1126/science.aam5887.
short: M.P. Zagórski, Y. Tabata, N. Brandenberg, M. Lutolf, G. Tkačik, T. Bollenbach,
J. Briscoe, A. Kicheva, Science 356 (2017) 1379–1383.
date_created: 2018-12-11T11:49:20Z
date_published: 2017-06-30T00:00:00Z
date_updated: 2023-09-26T15:38:05Z
day: '30'
department:
- _id: AnKi
- _id: GaTk
doi: 10.1126/science.aam5887
ec_funded: 1
external_id:
isi:
- '000404351500036'
pmid:
- '28663499'
intvolume: ' 356'
isi: 1
issue: '6345'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568706/
month: '06'
oa: 1
oa_version: Submitted Version
page: 1379 - 1383
pmid: 1
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
- _id: B6FC0238-B512-11E9-945C-1524E6697425
call_identifier: H2020
grant_number: '680037'
name: Coordination of Patterning And Growth In the Spinal Cord
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 2524F500-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '201439'
name: Developing High-Throughput Bioassays for Human Cancers in Zebrafish
publication: Science
publication_identifier:
issn:
- '00368075'
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '6474'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Decoding of position in the developing neural tube from antiparallel morphogen
gradients
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 356
year: '2017'
...
---
_id: '955'
abstract:
- lang: eng
text: 'Gene expression is controlled by networks of regulatory proteins that interact
specifically with external signals and DNA regulatory sequences. These interactions
force the network components to co-evolve so as to continually maintain function.
Yet, existing models of evolution mostly focus on isolated genetic elements. In
contrast, we study the essential process by which regulatory networks grow: the
duplication and subsequent specialization of network components. We synthesize
a biophysical model of molecular interactions with the evolutionary framework
to find the conditions and pathways by which new regulatory functions emerge.
We show that specialization of new network components is usually slow, but can
be drastically accelerated in the presence of regulatory crosstalk and mutations
that promote promiscuous interactions between network components.'
article_number: '216'
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Tamar
full_name: Friedlander, Tamar
id: 36A5845C-F248-11E8-B48F-1D18A9856A87
last_name: Friedlander
- first_name: Roshan
full_name: Prizak, Roshan
id: 4456104E-F248-11E8-B48F-1D18A9856A87
last_name: Prizak
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Friedlander T, Prizak R, Barton NH, Tkačik G. Evolution of new regulatory functions
on biophysically realistic fitness landscapes. Nature Communications. 2017;8(1).
doi:10.1038/s41467-017-00238-8
apa: Friedlander, T., Prizak, R., Barton, N. H., & Tkačik, G. (2017). Evolution
of new regulatory functions on biophysically realistic fitness landscapes. Nature
Communications. Nature Publishing Group. https://doi.org/10.1038/s41467-017-00238-8
chicago: Friedlander, Tamar, Roshan Prizak, Nicholas H Barton, and Gašper Tkačik.
“Evolution of New Regulatory Functions on Biophysically Realistic Fitness Landscapes.”
Nature Communications. Nature Publishing Group, 2017. https://doi.org/10.1038/s41467-017-00238-8.
ieee: T. Friedlander, R. Prizak, N. H. Barton, and G. Tkačik, “Evolution of new
regulatory functions on biophysically realistic fitness landscapes,” Nature
Communications, vol. 8, no. 1. Nature Publishing Group, 2017.
ista: Friedlander T, Prizak R, Barton NH, Tkačik G. 2017. Evolution of new regulatory
functions on biophysically realistic fitness landscapes. Nature Communications.
8(1), 216.
mla: Friedlander, Tamar, et al. “Evolution of New Regulatory Functions on Biophysically
Realistic Fitness Landscapes.” Nature Communications, vol. 8, no. 1, 216,
Nature Publishing Group, 2017, doi:10.1038/s41467-017-00238-8.
short: T. Friedlander, R. Prizak, N.H. Barton, G. Tkačik, Nature Communications
8 (2017).
date_created: 2018-12-11T11:49:23Z
date_published: 2017-08-09T00:00:00Z
date_updated: 2025-05-28T11:42:50Z
day: '09'
ddc:
- '539'
- '576'
department:
- _id: GaTk
- _id: NiBa
doi: 10.1038/s41467-017-00238-8
ec_funded: 1
external_id:
isi:
- '000407198800005'
file:
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checksum: 29a1b5db458048d3bd5c67e0e2a56818
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creator: system
date_created: 2018-12-12T10:14:14Z
date_updated: 2020-07-14T12:48:16Z
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content_type: application/pdf
creator: system
date_created: 2018-12-12T10:14:15Z
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file_id: '5065'
file_name: IST-2017-864-v1+2_41467_2017_238_MOESM1_ESM.pdf
file_size: 9715993
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has_accepted_license: '1'
intvolume: ' 8'
isi: 1
issue: '1'
language:
- iso: eng
month: '08'
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
- _id: 25B07788-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '250152'
name: Limits to selection in biology and in evolutionary computation
- _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:
- '20411723'
publication_status: published
publisher: Nature Publishing Group
publist_id: '6459'
pubrep_id: '864'
quality_controlled: '1'
related_material:
record:
- id: '6071'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Evolution of new regulatory functions on biophysically realistic fitness landscapes
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: 8
year: '2017'
...
---
_id: '1358'
abstract:
- lang: eng
text: 'Gene regulation relies on the specificity of transcription factor (TF)–DNA
interactions. Limited specificity may lead to crosstalk: a regulatory state in
which a gene is either incorrectly activated due to noncognate TF–DNA interactions
or remains erroneously inactive. As each TF can have numerous interactions with
noncognate cis-regulatory elements, crosstalk is inherently a global problem,
yet has previously not been studied as such. We construct a theoretical framework
to analyse the effects of global crosstalk on gene regulation. We find that crosstalk
presents a significant challenge for organisms with low-specificity TFs, such
as metazoans. Crosstalk is not easily mitigated by known regulatory schemes acting
at equilibrium, including variants of cooperativity and combinatorial regulation.
Our results suggest that crosstalk imposes a previously unexplored global constraint
on the functioning and evolution of regulatory networks, which is qualitatively
distinct from the known constraints that act at the level of individual gene regulatory
elements.'
article_number: '12307'
author:
- first_name: Tamar
full_name: Friedlander, Tamar
id: 36A5845C-F248-11E8-B48F-1D18A9856A87
last_name: Friedlander
- first_name: Roshan
full_name: Prizak, Roshan
id: 4456104E-F248-11E8-B48F-1D18A9856A87
last_name: Prizak
- 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: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. Intrinsic limits to
gene regulation by global crosstalk. Nature Communications. 2016;7. doi:10.1038/ncomms12307
apa: Friedlander, T., Prizak, R., Guet, C. C., Barton, N. H., & Tkačik, G. (2016).
Intrinsic limits to gene regulation by global crosstalk. Nature Communications.
Nature Publishing Group. https://doi.org/10.1038/ncomms12307
chicago: Friedlander, Tamar, Roshan Prizak, Calin C Guet, Nicholas H Barton, and
Gašper Tkačik. “Intrinsic Limits to Gene Regulation by Global Crosstalk.” Nature
Communications. Nature Publishing Group, 2016. https://doi.org/10.1038/ncomms12307.
ieee: T. Friedlander, R. Prizak, C. C. Guet, N. H. Barton, and G. Tkačik, “Intrinsic
limits to gene regulation by global crosstalk,” Nature Communications,
vol. 7. Nature Publishing Group, 2016.
ista: Friedlander T, Prizak R, Guet CC, Barton NH, Tkačik G. 2016. Intrinsic limits
to gene regulation by global crosstalk. Nature Communications. 7, 12307.
mla: Friedlander, Tamar, et al. “Intrinsic Limits to Gene Regulation by Global Crosstalk.”
Nature Communications, vol. 7, 12307, Nature Publishing Group, 2016, doi:10.1038/ncomms12307.
short: T. Friedlander, R. Prizak, C.C. Guet, N.H. Barton, G. Tkačik, Nature Communications
7 (2016).
date_created: 2018-12-11T11:51:34Z
date_published: 2016-08-04T00:00:00Z
date_updated: 2023-09-07T12:53:49Z
day: '04'
ddc:
- '576'
department:
- _id: GaTk
- _id: NiBa
- _id: CaGu
doi: 10.1038/ncomms12307
ec_funded: 1
file:
- access_level: open_access
checksum: fe3f3a1526d180b29fe691ab11435b78
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:12:01Z
date_updated: 2020-07-14T12:44:46Z
file_id: '4919'
file_name: IST-2016-627-v1+1_ncomms12307.pdf
file_size: 861805
relation: main_file
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checksum: 164864a1a675f3ad80e9917c27aba07f
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:12:02Z
date_updated: 2020-07-14T12:44:46Z
file_id: '4920'
file_name: IST-2016-627-v1+2_ncomms12307-s1.pdf
file_size: 1084703
relation: main_file
file_date_updated: 2020-07-14T12:44:46Z
has_accepted_license: '1'
intvolume: ' 7'
language:
- iso: eng
month: '08'
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
- _id: 25B07788-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '250152'
name: Limits to selection in biology and in evolutionary computation
- _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_status: published
publisher: Nature Publishing Group
publist_id: '5887'
pubrep_id: '627'
quality_controlled: '1'
related_material:
record:
- id: '6071'
relation: dissertation_contains
status: public
scopus_import: 1
status: public
title: Intrinsic limits to gene regulation by global crosstalk
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: 7
year: '2016'
...
---
_id: '1242'
abstract:
- lang: eng
text: A crucial step in the regulation of gene expression is binding of transcription
factor (TF) proteins to regulatory sites along the DNA. But transcription factors
act at nanomolar concentrations, and noise due to random arrival of these molecules
at their binding sites can severely limit the precision of regulation. Recent
work on the optimization of information flow through regulatory networks indicates
that the lower end of the dynamic range of concentrations is simply inaccessible,
overwhelmed by the impact of this noise. Motivated by the behavior of homeodomain
proteins, such as the maternal morphogen Bicoid in the fruit fly embryo, we suggest
a scheme in which transcription factors also act as indirect translational regulators,
binding to the mRNA of other regulatory proteins. Intuitively, each mRNA molecule
acts as an independent sensor of the input concentration, and averaging over these
multiple sensors reduces the noise. We analyze information flow through this scheme
and identify conditions under which it outperforms direct transcriptional regulation.
Our results suggest that the dual role of homeodomain proteins is not just a historical
accident, but a solution to a crucial physics problem in the regulation of gene
expression.
acknowledgement: "We thank T. Gregor, A. Prochaintz, and others for\r\nhelpful discussions.
This work was supported in part by\r\nGrants No. PHY-1305525 and No. CCF-0939370
from the\r\nUS National Science Foundation and by the W.M. Keck\r\nFoundation. A.M.W.
acknowledges the support by European\r\nResearch Council (ERC) Grant No. MCCIG PCIG10–GA-\r\n2011–303561.
G.T. and T.R.S. were supported by Austrian\r\nScience Fund (FWF) Grant No. P28844S."
article_number: '022404'
author:
- first_name: Thomas R
full_name: Sokolowski, Thomas R
id: 3E999752-F248-11E8-B48F-1D18A9856A87
last_name: Sokolowski
orcid: 0000-0002-1287-3779
- first_name: Aleksandra
full_name: Walczak, Aleksandra
last_name: Walczak
- first_name: William
full_name: Bialek, William
last_name: Bialek
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: Sokolowski TR, Walczak A, Bialek W, Tkačik G. Extending the dynamic range of
transcription factor action by translational regulation. Physical Review E
Statistical Nonlinear and Soft Matter Physics. 2016;93(2). doi:10.1103/PhysRevE.93.022404
apa: Sokolowski, T. R., Walczak, A., Bialek, W., & Tkačik, G. (2016). Extending
the dynamic range of transcription factor action by translational regulation.
Physical Review E Statistical Nonlinear and Soft Matter Physics. American
Institute of Physics. https://doi.org/10.1103/PhysRevE.93.022404
chicago: Sokolowski, Thomas R, Aleksandra Walczak, William Bialek, and Gašper Tkačik.
“Extending the Dynamic Range of Transcription Factor Action by Translational Regulation.”
Physical Review E Statistical Nonlinear and Soft Matter Physics. American
Institute of Physics, 2016. https://doi.org/10.1103/PhysRevE.93.022404.
ieee: T. R. Sokolowski, A. Walczak, W. Bialek, and G. Tkačik, “Extending the dynamic
range of transcription factor action by translational regulation,” Physical
Review E Statistical Nonlinear and Soft Matter Physics, vol. 93, no. 2. American
Institute of Physics, 2016.
ista: Sokolowski TR, Walczak A, Bialek W, Tkačik G. 2016. Extending the dynamic
range of transcription factor action by translational regulation. Physical Review
E Statistical Nonlinear and Soft Matter Physics. 93(2), 022404.
mla: Sokolowski, Thomas R., et al. “Extending the Dynamic Range of Transcription
Factor Action by Translational Regulation.” Physical Review E Statistical Nonlinear
and Soft Matter Physics, vol. 93, no. 2, 022404, American Institute of Physics,
2016, doi:10.1103/PhysRevE.93.022404.
short: T.R. Sokolowski, A. Walczak, W. Bialek, G. Tkačik, Physical Review E Statistical
Nonlinear and Soft Matter Physics 93 (2016).
date_created: 2018-12-11T11:50:54Z
date_published: 2016-02-04T00:00:00Z
date_updated: 2021-01-12T06:49:20Z
day: '04'
department:
- _id: GaTk
doi: 10.1103/PhysRevE.93.022404
intvolume: ' 93'
issue: '2'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1507.02562
month: '02'
oa: 1
oa_version: Preprint
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: Physical Review E Statistical Nonlinear and Soft Matter Physics
publication_status: published
publisher: American Institute of Physics
publist_id: '6088'
quality_controlled: '1'
scopus_import: 1
status: public
title: Extending the dynamic range of transcription factor action by translational
regulation
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 93
year: '2016'
...
---
_id: '1270'
abstract:
- lang: eng
text: A crucial step in the early development of multicellular organisms involves
the establishment of spatial patterns of gene expression which later direct proliferating
cells to take on different cell fates. These patterns enable the cells to infer
their global position within a tissue or an organism by reading out local gene
expression levels. The patterning system is thus said to encode positional information,
a concept that was formalized recently in the framework of information theory.
Here we introduce a toy model of patterning in one spatial dimension, which can
be seen as an extension of Wolpert's paradigmatic "French Flag" model,
to patterning by several interacting, spatially coupled genes subject to intrinsic
and extrinsic noise. Our model, a variant of an Ising spin system, allows us to
systematically explore expression patterns that optimally encode positional information.
We find that optimal patterning systems use positional cues, as in the French
Flag model, together with gene-gene interactions to generate combinatorial codes
for position which we call "Counter" patterns. Counter patterns can
also be stabilized against noise and variations in system size or morphogen dosage
by longer-range spatial interactions of the type invoked in the Turing model.
The simple setup proposed here qualitatively captures many of the experimentally
observed properties of biological patterning systems and allows them to be studied
in a single, theoretically consistent framework.
acknowledgement: The authors would like to thank Thomas Sokolowski and Filipe Tostevin
for helpful discussions. PH and UG were funded by the German Excellence Initiative
via the program "Nanosystems Initiative Munich" (https://www.nano-initiative-munich.de)
and the German Research Foundation via the SFB 1032 "Nanoagents for Spatiotemporal
Control of Molecular and Cellular Reactions" (http://www.sfb1032.physik.uni-muenchen.de).
GT was funded by the Austrian Science Fund (FWF P 28844) (http://www.fwf.ac.at).
article_number: e0163628
author:
- first_name: Patrick
full_name: Hillenbrand, Patrick
last_name: Hillenbrand
- first_name: Ulrich
full_name: Gerland, Ulrich
last_name: Gerland
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
citation:
ama: 'Hillenbrand P, Gerland U, Tkačik G. Beyond the French flag model: Exploiting
spatial and gene regulatory interactions for positional information. PLoS One.
2016;11(9). doi:10.1371/journal.pone.0163628'
apa: 'Hillenbrand, P., Gerland, U., & Tkačik, G. (2016). Beyond the French flag
model: Exploiting spatial and gene regulatory interactions for positional information.
PLoS One. Public Library of Science. https://doi.org/10.1371/journal.pone.0163628'
chicago: 'Hillenbrand, Patrick, Ulrich Gerland, and Gašper Tkačik. “Beyond the French
Flag Model: Exploiting Spatial and Gene Regulatory Interactions for Positional
Information.” PLoS One. Public Library of Science, 2016. https://doi.org/10.1371/journal.pone.0163628.'
ieee: 'P. Hillenbrand, U. Gerland, and G. Tkačik, “Beyond the French flag model:
Exploiting spatial and gene regulatory interactions for positional information,”
PLoS One, vol. 11, no. 9. Public Library of Science, 2016.'
ista: 'Hillenbrand P, Gerland U, Tkačik G. 2016. Beyond the French flag model: Exploiting
spatial and gene regulatory interactions for positional information. PLoS One.
11(9), e0163628.'
mla: 'Hillenbrand, Patrick, et al. “Beyond the French Flag Model: Exploiting Spatial
and Gene Regulatory Interactions for Positional Information.” PLoS One,
vol. 11, no. 9, e0163628, Public Library of Science, 2016, doi:10.1371/journal.pone.0163628.'
short: P. Hillenbrand, U. Gerland, G. Tkačik, PLoS One 11 (2016).
date_created: 2018-12-11T11:51:03Z
date_published: 2016-09-27T00:00:00Z
date_updated: 2023-02-23T14:11:37Z
day: '27'
ddc:
- '571'
department:
- _id: GaTk
doi: 10.1371/journal.pone.0163628
file:
- access_level: open_access
checksum: 3d0d55d373096a033bd9cf79288c8586
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:10:47Z
date_updated: 2020-07-14T12:44:42Z
file_id: '4837'
file_name: IST-2016-696-v1+1_journal.pone.0163628.PDF
file_size: 4950415
relation: main_file
file_date_updated: 2020-07-14T12:44:42Z
has_accepted_license: '1'
intvolume: ' 11'
issue: '9'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
publication: PLoS One
publication_status: published
publisher: Public Library of Science
publist_id: '6050'
pubrep_id: '696'
quality_controlled: '1'
related_material:
record:
- id: '9869'
relation: research_data
status: public
- id: '9870'
relation: research_data
status: public
- id: '9871'
relation: research_data
status: public
scopus_import: 1
status: public
title: 'Beyond the French flag model: Exploiting spatial and gene regulatory interactions
for positional information'
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: 11
year: '2016'
...