---
_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: '9283'
abstract:
- lang: eng
text: Gene expression levels are influenced by multiple coexisting molecular mechanisms.
Some of these interactions such as those of transcription factors and promoters
have been studied extensively. However, predicting phenotypes of gene regulatory
networks (GRNs) remains a major challenge. Here, we use a well-defined synthetic
GRN to study in Escherichia coli how network phenotypes depend on local genetic
context, i.e. the genetic neighborhood of a transcription factor and its relative
position. We show that one GRN with fixed topology can display not only quantitatively
but also qualitatively different phenotypes, depending solely on the local genetic
context of its components. Transcriptional read-through is the main molecular
mechanism that places one transcriptional unit (TU) within two separate regulons
without the need for complex regulatory sequences. We propose that relative order
of individual TUs, with its potential for combinatorial complexity, plays an important
role in shaping phenotypes of GRNs.
acknowledgement: "We thank J Bollback, L Hurst, M Lagator, C Nizak, O Rivoire, M Savageau,
G Tkacik, and B Vicozo\r\nfor helpful discussions; A Dolinar and A Greshnova for
technical assistance; T Bollenbach for supplying the strain JW0336; C Rusnac, and
members of the Guet lab for comments. 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 n˚\r\n628377
(ANS) and an Austrian Science Fund (FWF) grant n˚ I 3901-B32 (CCG)."
article_number: e65993
article_processing_charge: Yes
article_type: original
author:
- first_name: Anna A
full_name: Nagy-Staron, Anna A
id: 3ABC5BA6-F248-11E8-B48F-1D18A9856A87
last_name: Nagy-Staron
orcid: 0000-0002-1391-8377
- first_name: Kathrin
full_name: Tomasek, Kathrin
id: 3AEC8556-F248-11E8-B48F-1D18A9856A87
last_name: Tomasek
orcid: 0000-0003-3768-877X
- first_name: Caroline
full_name: Caruso Carter, Caroline
last_name: Caruso Carter
- first_name: Elisabeth
full_name: Sonnleitner, Elisabeth
last_name: Sonnleitner
- first_name: Bor
full_name: Kavcic, Bor
id: 350F91D2-F248-11E8-B48F-1D18A9856A87
last_name: Kavcic
orcid: 0000-0001-6041-254X
- first_name: Tiago
full_name: Paixão, Tiago
last_name: Paixão
- 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: Nagy-Staron AA, Tomasek K, Caruso Carter C, et al. Local genetic context shapes
the function of a gene regulatory network. eLife. 2021;10. doi:10.7554/elife.65993
apa: Nagy-Staron, A. A., Tomasek, K., Caruso Carter, C., Sonnleitner, E., Kavcic,
B., Paixão, T., & Guet, C. C. (2021). Local genetic context shapes the function
of a gene regulatory network. ELife. eLife Sciences Publications. https://doi.org/10.7554/elife.65993
chicago: Nagy-Staron, Anna A, Kathrin Tomasek, Caroline Caruso Carter, Elisabeth
Sonnleitner, Bor Kavcic, Tiago Paixão, and Calin C Guet. “Local Genetic Context
Shapes the Function of a Gene Regulatory Network.” ELife. eLife Sciences
Publications, 2021. https://doi.org/10.7554/elife.65993.
ieee: A. A. Nagy-Staron et al., “Local genetic context shapes the function
of a gene regulatory network,” eLife, vol. 10. eLife Sciences Publications,
2021.
ista: Nagy-Staron AA, Tomasek K, Caruso Carter C, Sonnleitner E, Kavcic B, Paixão
T, Guet CC. 2021. Local genetic context shapes the function of a gene regulatory
network. eLife. 10, e65993.
mla: Nagy-Staron, Anna A., et al. “Local Genetic Context Shapes the Function of
a Gene Regulatory Network.” ELife, vol. 10, e65993, eLife Sciences Publications,
2021, doi:10.7554/elife.65993.
short: A.A. Nagy-Staron, K. Tomasek, C. Caruso Carter, E. Sonnleitner, B. Kavcic,
T. Paixão, C.C. Guet, ELife 10 (2021).
date_created: 2021-03-23T10:11:46Z
date_published: 2021-03-08T00:00:00Z
date_updated: 2024-02-21T12:41:57Z
day: '08'
ddc:
- '570'
department:
- _id: GaTk
- _id: CaGu
doi: 10.7554/elife.65993
ec_funded: 1
external_id:
isi:
- '000631050900001'
file:
- access_level: open_access
checksum: 3c2f44058c2dd45a5a1027f09d263f8e
content_type: application/pdf
creator: bkavcic
date_created: 2021-03-23T10:12:58Z
date_updated: 2021-03-23T10:12:58Z
file_id: '9284'
file_name: elife-65993-v2.pdf
file_size: 1390469
relation: main_file
success: 1
file_date_updated: 2021-03-23T10:12:58Z
has_accepted_license: '1'
intvolume: ' 10'
isi: 1
keyword:
- Genetics and Molecular Biology
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
project:
- _id: 2517526A-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '628377'
name: 'The Systems Biology of Transcriptional Read-Through in Bacteria: from Synthetic
Networks to Genomic Studies'
- _id: 268BFA92-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: I03901
name: 'CyberCircuits: Cybergenetic circuits to test composability of gene networks'
publication: eLife
publication_identifier:
issn:
- 2050-084X
publication_status: published
publisher: eLife Sciences Publications
quality_controlled: '1'
related_material:
record:
- id: '8951'
relation: research_data
status: public
status: public
title: Local genetic context shapes the function of a gene regulatory network
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: 10
year: '2021'
...
---
_id: '9362'
abstract:
- lang: eng
text: A central goal in systems neuroscience is to understand the functions performed
by neural circuits. Previous top-down models addressed this question by comparing
the behaviour of an ideal model circuit, optimised to perform a given function,
with neural recordings. However, this requires guessing in advance what function
is being performed, which may not be possible for many neural systems. To address
this, we propose an inverse reinforcement learning (RL) framework for inferring
the function performed by a neural network from data. We assume that the responses
of each neuron in a network are optimised so as to drive the network towards ‘rewarded’
states, that are desirable for performing a given function. We then show how one
can use inverse RL to infer the reward function optimised by the network from
observing its responses. This inferred reward function can be used to predict
how the neural network should adapt its dynamics to perform the same function
when the external environment or network structure changes. This could lead to
theoretical predictions about how neural network dynamics adapt to deal with cell
death and/or varying sensory stimulus statistics.
acknowledgement: The authors would like to thank Ulisse Ferrari for useful discussions
and feedback.
article_number: e0248940
article_processing_charge: No
article_type: original
author:
- first_name: Matthew J
full_name: Chalk, Matthew J
id: 2BAAC544-F248-11E8-B48F-1D18A9856A87
last_name: Chalk
orcid: 0000-0001-7782-4436
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Olivier
full_name: Marre, Olivier
last_name: Marre
citation:
ama: Chalk MJ, Tkačik G, Marre O. Inferring the function performed by a recurrent
neural network. PLoS ONE. 2021;16(4). doi:10.1371/journal.pone.0248940
apa: Chalk, M. J., Tkačik, G., & Marre, O. (2021). Inferring the function performed
by a recurrent neural network. PLoS ONE. Public Library of Science. https://doi.org/10.1371/journal.pone.0248940
chicago: Chalk, Matthew J, Gašper Tkačik, and Olivier Marre. “Inferring the Function
Performed by a Recurrent Neural Network.” PLoS ONE. Public Library of Science,
2021. https://doi.org/10.1371/journal.pone.0248940.
ieee: M. J. Chalk, G. Tkačik, and O. Marre, “Inferring the function performed by
a recurrent neural network,” PLoS ONE, vol. 16, no. 4. Public Library of
Science, 2021.
ista: Chalk MJ, Tkačik G, Marre O. 2021. Inferring the function performed by a recurrent
neural network. PLoS ONE. 16(4), e0248940.
mla: Chalk, Matthew J., et al. “Inferring the Function Performed by a Recurrent
Neural Network.” PLoS ONE, vol. 16, no. 4, e0248940, Public Library of
Science, 2021, doi:10.1371/journal.pone.0248940.
short: M.J. Chalk, G. Tkačik, O. Marre, PLoS ONE 16 (2021).
date_created: 2021-05-02T22:01:28Z
date_published: 2021-04-15T00:00:00Z
date_updated: 2023-10-18T08:17:42Z
day: '15'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pone.0248940
external_id:
isi:
- '000641474900072'
pmid:
- '33857170'
file:
- access_level: open_access
checksum: c52da133850307d2031f552d998f00e8
content_type: application/pdf
creator: kschuh
date_created: 2021-05-04T13:22:19Z
date_updated: 2021-05-04T13:22:19Z
file_id: '9371'
file_name: 2021_pone_Chalk.pdf
file_size: 2768282
relation: main_file
success: 1
file_date_updated: 2021-05-04T13:22:19Z
has_accepted_license: '1'
intvolume: ' 16'
isi: 1
issue: '4'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
pmid: 1
publication: PLoS ONE
publication_identifier:
eissn:
- '19326203'
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Inferring the function performed by a recurrent neural network
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: 16
year: '2021'
...
---
_id: '9439'
abstract:
- lang: eng
text: The ability to adapt to changes in stimulus statistics is a hallmark of sensory
systems. Here, we developed a theoretical framework that can account for the dynamics
of adaptation from an information processing perspective. We use this framework
to optimize and analyze adaptive sensory codes, and we show that codes optimized
for stationary environments can suffer from prolonged periods of poor performance
when the environment changes. To mitigate the adversarial effects of these environmental
changes, sensory systems must navigate tradeoffs between the ability to accurately
encode incoming stimuli and the ability to rapidly detect and adapt to changes
in the distribution of these stimuli. We derive families of codes that balance
these objectives, and we demonstrate their close match to experimentally observed
neural dynamics during mean and variance adaptation. Our results provide a unifying
perspective on adaptation across a range of sensory systems, environments, and
sensory tasks.
acknowledgement: We thank D. Kastner and T. Münch for generously providing figures
from their work. We also thank V. Jayaraman, M. Noorman, T. Ma, and K. Krishnamurthy
for useful discussions and feedback on the manuscript. W.F.M. was funded by the
European Union’s Horizon 2020 Research and Innovation Programme under Marie Skłodowska-Curie
Grant Agreement No. 754411. A.M.H. was supported by the Howard Hughes Medical Institute.
article_processing_charge: No
article_type: original
author:
- first_name: Wiktor F
full_name: Mlynarski, Wiktor F
id: 358A453A-F248-11E8-B48F-1D18A9856A87
last_name: Mlynarski
- first_name: Ann M.
full_name: Hermundstad, Ann M.
last_name: Hermundstad
citation:
ama: Mlynarski WF, Hermundstad AM. Efficient and adaptive sensory codes. Nature
Neuroscience. 2021;24:998-1009. doi:10.1038/s41593-021-00846-0
apa: Mlynarski, W. F., & Hermundstad, A. M. (2021). Efficient and adaptive sensory
codes. Nature Neuroscience. Springer Nature. https://doi.org/10.1038/s41593-021-00846-0
chicago: Mlynarski, Wiktor F, and Ann M. Hermundstad. “Efficient and Adaptive Sensory
Codes.” Nature Neuroscience. Springer Nature, 2021. https://doi.org/10.1038/s41593-021-00846-0.
ieee: W. F. Mlynarski and A. M. Hermundstad, “Efficient and adaptive sensory codes,”
Nature Neuroscience, vol. 24. Springer Nature, pp. 998–1009, 2021.
ista: Mlynarski WF, Hermundstad AM. 2021. Efficient and adaptive sensory codes.
Nature Neuroscience. 24, 998–1009.
mla: Mlynarski, Wiktor F., and Ann M. Hermundstad. “Efficient and Adaptive Sensory
Codes.” Nature Neuroscience, vol. 24, Springer Nature, 2021, pp. 998–1009,
doi:10.1038/s41593-021-00846-0.
short: W.F. Mlynarski, A.M. Hermundstad, Nature Neuroscience 24 (2021) 998–1009.
date_created: 2021-05-30T22:01:24Z
date_published: 2021-05-20T00:00:00Z
date_updated: 2023-08-08T13:51:14Z
day: '20'
department:
- _id: GaTk
doi: 10.1038/s41593-021-00846-0
ec_funded: 1
external_id:
isi:
- '000652577300003'
intvolume: ' 24'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: 'https://doi.org/10.1101/669200 '
month: '05'
oa: 1
oa_version: Preprint
page: 998-1009
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Nature Neuroscience
publication_identifier:
eissn:
- 1546-1726
issn:
- 1097-6256
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Efficient and adaptive sensory codes
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 24
year: '2021'
...
---
_id: '10077'
abstract:
- lang: eng
text: Although much is known about how single neurons in the hippocampus represent
an animal’s position, how cell-cell interactions contribute to spatial coding
remains poorly understood. Using a novel statistical estimator and theoretical
modeling, both developed in the framework of maximum entropy models, we reveal
highly structured cell-to-cell interactions whose statistics depend on familiar
vs. novel environment. In both conditions the circuit interactions optimize the
encoding of spatial information, but for regimes that differ in the signal-to-noise
ratio of their spatial inputs. Moreover, the topology of the interactions facilitates
linear decodability, making the information easy to read out by downstream circuits.
These findings suggest that the efficient coding hypothesis is not applicable
only to individual neuron properties in the sensory periphery, but also to neural
interactions in the central brain.
acknowledgement: We thank Peter Baracskay, Karola Kaefer and Hugo Malagon-Vina for
the acquisition of the data. We thank Federico Stella for comments on an earlier
version of the manuscript. MN was supported by European Union Horizon 2020 grant
665385, JC was supported by European Research Council consolidator grant 281511,
GT was supported by the Austrian Science Fund (FWF) grant P34015, CS was supported
by an IST fellow grant, National Institute of Mental Health Award 1R01MH125571-01,
by the National Science Foundation under NSF Award No. 1922658 and a Google faculty
award.
article_processing_charge: No
author:
- first_name: Michele
full_name: Nardin, Michele
id: 30BD0376-F248-11E8-B48F-1D18A9856A87
last_name: Nardin
orcid: 0000-0001-8849-6570
- first_name: Jozsef L
full_name: Csicsvari, Jozsef L
id: 3FA14672-F248-11E8-B48F-1D18A9856A87
last_name: Csicsvari
orcid: 0000-0002-5193-4036
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Cristina
full_name: Savin, Cristina
id: 3933349E-F248-11E8-B48F-1D18A9856A87
last_name: Savin
citation:
ama: Nardin M, Csicsvari JL, Tkačik G, Savin C. The structure of hippocampal CA1
interactions optimizes spatial coding across experience. bioRxiv. doi:10.1101/2021.09.28.460602
apa: Nardin, M., Csicsvari, J. L., Tkačik, G., & Savin, C. (n.d.). The structure
of hippocampal CA1 interactions optimizes spatial coding across experience. bioRxiv.
Cold Spring Harbor Laboratory. https://doi.org/10.1101/2021.09.28.460602
chicago: Nardin, Michele, Jozsef L Csicsvari, Gašper Tkačik, and Cristina Savin.
“The Structure of Hippocampal CA1 Interactions Optimizes Spatial Coding across
Experience.” BioRxiv. Cold Spring Harbor Laboratory, n.d. https://doi.org/10.1101/2021.09.28.460602.
ieee: M. Nardin, J. L. Csicsvari, G. Tkačik, and C. Savin, “The structure of hippocampal
CA1 interactions optimizes spatial coding across experience,” bioRxiv.
Cold Spring Harbor Laboratory.
ista: Nardin M, Csicsvari JL, Tkačik G, Savin C. The structure of hippocampal CA1
interactions optimizes spatial coding across experience. bioRxiv, 10.1101/2021.09.28.460602.
mla: Nardin, Michele, et al. “The Structure of Hippocampal CA1 Interactions Optimizes
Spatial Coding across Experience.” BioRxiv, Cold Spring Harbor Laboratory,
doi:10.1101/2021.09.28.460602.
short: M. Nardin, J.L. Csicsvari, G. Tkačik, C. Savin, BioRxiv (n.d.).
date_created: 2021-10-04T06:23:34Z
date_published: 2021-09-29T00:00:00Z
date_updated: 2024-03-25T23:30:09Z
day: '29'
department:
- _id: GradSch
- _id: JoCs
- _id: GaTk
doi: 10.1101/2021.09.28.460602
ec_funded: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.biorxiv.org/content/10.1101/2021.09.28.460602
month: '09'
oa: 1
oa_version: Preprint
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 257A4776-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '281511'
name: Memory-related information processing in neuronal circuits of the hippocampus
and entorhinal cortex
- _id: 626c45b5-2b32-11ec-9570-e509828c1ba6
grant_number: P34015
name: Efficient coding with biophysical realism
publication: bioRxiv
publication_status: submitted
publisher: Cold Spring Harbor Laboratory
related_material:
record:
- id: '11932'
relation: dissertation_contains
status: public
status: public
title: The structure of hippocampal CA1 interactions optimizes spatial coding across
experience
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: preprint
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2021'
...
---
_id: '10535'
abstract:
- lang: eng
text: Realistic models of biological processes typically involve interacting components
on multiple scales, driven by changing environment and inherent stochasticity.
Such models are often analytically and numerically intractable. We revisit a dynamic
maximum entropy method that combines a static maximum entropy with a quasi-stationary
approximation. This allows us to reduce stochastic non-equilibrium dynamics expressed
by the Fokker-Planck equation to a simpler low-dimensional deterministic dynamics,
without the need to track microscopic details. Although the method has been previously
applied to a few (rather complicated) applications in population genetics, our
main goal here is to explain and to better understand how the method works. We
demonstrate the usefulness of the method for two widely studied stochastic problems,
highlighting its accuracy in capturing important macroscopic quantities even in
rapidly changing non-stationary conditions. For the Ornstein-Uhlenbeck process,
the method recovers the exact dynamics whilst for a stochastic island model with
migration from other habitats, the approximation retains high macroscopic accuracy
under a wide range of scenarios in a dynamic environment.
acknowledged_ssus:
- _id: ScienComp
acknowledgement: "Computational resources for the study were provided by the Institute
of Science and Technology, Austria.\r\nKB received funding from the Scientific Grant
Agency of the Slovak Republic under the Grants Nos. 1/0755/19 and 1/0521/20."
article_number: e1009661
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Katarína
full_name: Bod'ová, Katarína
id: 2BA24EA0-F248-11E8-B48F-1D18A9856A87
last_name: Bod'ová
orcid: 0000-0002-7214-0171
- first_name: Eniko
full_name: Szep, Eniko
id: 485BB5A4-F248-11E8-B48F-1D18A9856A87
last_name: Szep
- first_name: Nicholas H
full_name: Barton, Nicholas H
id: 4880FE40-F248-11E8-B48F-1D18A9856A87
last_name: Barton
orcid: 0000-0002-8548-5240
citation:
ama: Bodova K, Szep E, Barton NH. Dynamic maximum entropy provides accurate approximation
of structured population dynamics. PLoS Computational Biology. 2021;17(12).
doi:10.1371/journal.pcbi.1009661
apa: Bodova, K., Szep, E., & Barton, N. H. (2021). Dynamic maximum entropy provides
accurate approximation of structured population dynamics. PLoS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1009661
chicago: Bodova, Katarina, Eniko Szep, and Nicholas H Barton. “Dynamic Maximum Entropy
Provides Accurate Approximation of Structured Population Dynamics.” PLoS Computational
Biology. Public Library of Science, 2021. https://doi.org/10.1371/journal.pcbi.1009661.
ieee: K. Bodova, E. Szep, and N. H. Barton, “Dynamic maximum entropy provides accurate
approximation of structured population dynamics,” PLoS Computational Biology,
vol. 17, no. 12. Public Library of Science, 2021.
ista: Bodova K, Szep E, Barton NH. 2021. Dynamic maximum entropy provides accurate
approximation of structured population dynamics. PLoS Computational Biology. 17(12),
e1009661.
mla: Bodova, Katarina, et al. “Dynamic Maximum Entropy Provides Accurate Approximation
of Structured Population Dynamics.” PLoS Computational Biology, vol. 17,
no. 12, e1009661, Public Library of Science, 2021, doi:10.1371/journal.pcbi.1009661.
short: K. Bodova, E. Szep, N.H. Barton, PLoS Computational Biology 17 (2021).
date_created: 2021-12-12T23:01:27Z
date_published: 2021-12-01T00:00:00Z
date_updated: 2022-08-01T10:48:04Z
day: '01'
ddc:
- '570'
department:
- _id: NiBa
- _id: GaTk
doi: 10.1371/journal.pcbi.1009661
external_id:
arxiv:
- '2102.03669'
pmid:
- '34851948'
file:
- access_level: open_access
checksum: dcd185d4f7e0acee25edf1d6537f447e
content_type: application/pdf
creator: dernst
date_created: 2022-05-16T08:53:11Z
date_updated: 2022-05-16T08:53:11Z
file_id: '11383'
file_name: 2021_PLOsComBio_Bodova.pdf
file_size: 2299486
relation: main_file
success: 1
file_date_updated: 2022-05-16T08:53:11Z
has_accepted_license: '1'
intvolume: ' 17'
issue: '12'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
pmid: 1
publication: PLoS Computational Biology
publication_identifier:
eissn:
- 1553-7358
issn:
- 1553-734X
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Dynamic maximum entropy provides accurate approximation of structured population
dynamics
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: 17
year: '2021'
...
---
_id: '10579'
abstract:
- lang: eng
text: 'We consider a totally asymmetric simple exclusion process (TASEP) consisting
of particles on a lattice that require binding by a "token" to move. Using a combination
of theory and simulations, we address the following questions: (i) How token binding
kinetics affects the current-density relation; (ii) How the current-density relation
depends on the scarcity of tokens; (iii) How tokens propagate the effects of the
locally-imposed disorder (such a slow site) over the entire lattice; (iv) How
a shared pool of tokens couples concurrent TASEPs running on multiple lattices;
(v) How our results translate to TASEPs with open boundaries that exchange particles
with the reservoir. Since real particle motion (including in systems that inspired
the standard TASEP model, e.g., protein synthesis or movement of molecular motors)
is often catalyzed, regulated, actuated, or otherwise mediated, the token-driven
TASEP dynamics analyzed in this paper should allow for a better understanding
of real systems and enable a closer match between TASEP theory and experimental
observations.'
acknowledgement: B.K. thanks Stefano Elefante, Simon Rella, and Michal Hledík for
their help with the usage of the cluster. B.K. additionally thanks Călin Guet and
his group for help and advice. We thank M. Hennessey-Wesen for constructive comments
on the manuscript. We thank Ankita Gupta (Indian Institute of Technology) for spotting
a typographical error in Eq. (49) in the preprint version of this paper.
article_number: '2112.13558'
article_processing_charge: No
arxiv: 1
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
citation:
ama: Kavcic B, Tkačik G. Token-driven totally asymmetric simple exclusion process.
arXiv. doi:10.48550/arXiv.2112.13558
apa: Kavcic, B., & Tkačik, G. (n.d.). Token-driven totally asymmetric simple
exclusion process. arXiv. https://doi.org/10.48550/arXiv.2112.13558
chicago: Kavcic, Bor, and Gašper Tkačik. “Token-Driven Totally Asymmetric Simple
Exclusion Process.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2112.13558.
ieee: B. Kavcic and G. Tkačik, “Token-driven totally asymmetric simple exclusion
process,” arXiv. .
ista: Kavcic B, Tkačik G. Token-driven totally asymmetric simple exclusion process.
arXiv, 2112.13558.
mla: Kavcic, Bor, and Gašper Tkačik. “Token-Driven Totally Asymmetric Simple Exclusion
Process.” ArXiv, 2112.13558, doi:10.48550/arXiv.2112.13558.
short: B. Kavcic, G. Tkačik, ArXiv (n.d.).
date_created: 2021-12-28T06:52:09Z
date_published: 2021-12-27T00:00:00Z
date_updated: 2023-05-03T10:54:05Z
day: '27'
ddc:
- '530'
department:
- _id: GaTk
doi: 10.48550/arXiv.2112.13558
external_id:
arxiv:
- '2112.13558'
has_accepted_license: '1'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2112.13558
month: '12'
oa: 1
oa_version: Preprint
publication: arXiv
publication_status: submitted
status: public
title: Token-driven totally asymmetric simple exclusion process
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2021'
...
---
_id: '9822'
abstract:
- lang: eng
text: Attachment of adhesive molecules on cell culture surfaces to restrict cell
adhesion to defined areas and shapes has been vital for the progress of in vitro
research. In currently existing patterning methods, a combination of pattern properties
such as stability, precision, specificity, high-throughput outcome, and spatiotemporal
control is highly desirable but challenging to achieve. Here, we introduce a versatile
and high-throughput covalent photoimmobilization technique, comprising a light-dose-dependent
patterning step and a subsequent functionalization of the pattern via click chemistry.
This two-step process is feasible on arbitrary surfaces and allows for generation
of sustainable patterns and gradients. The method is validated in different biological
systems by patterning adhesive ligands on cell-repellent surfaces, thereby constraining
the growth and migration of cells to the designated areas. We then implement a
sequential photopatterning approach by adding a second switchable patterning step,
allowing for spatiotemporal control over two distinct surface patterns. As a proof
of concept, we reconstruct the dynamics of the tip/stalk cell switch during angiogenesis.
Our results show that the spatiotemporal control provided by our “sequential photopatterning”
system is essential for mimicking dynamic biological processes and that our innovative
approach has great potential for further applications in cell science.
acknowledgement: We would like to thank Charlott Leu for the production of our chromium
wafers, Louise Ritter for her contribution of the IF stainings in Figure 4, Shokoufeh
Teymouri for her help with the Bioinert coated slides, and finally Prof. Dr. Joachim
Rädler for his valuable scientific guidance.
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Themistoklis
full_name: Zisis, Themistoklis
last_name: Zisis
- first_name: Jan
full_name: Schwarz, Jan
id: 346C1EC6-F248-11E8-B48F-1D18A9856A87
last_name: Schwarz
- first_name: Miriam
full_name: Balles, Miriam
last_name: Balles
- first_name: Maibritt
full_name: Kretschmer, Maibritt
last_name: Kretschmer
- first_name: Maria
full_name: Nemethova, Maria
id: 34E27F1C-F248-11E8-B48F-1D18A9856A87
last_name: Nemethova
- 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: Robert
full_name: Hauschild, Robert
id: 4E01D6B4-F248-11E8-B48F-1D18A9856A87
last_name: Hauschild
orcid: 0000-0001-9843-3522
- first_name: Janina
full_name: Lange, Janina
last_name: Lange
- 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: Michael K
full_name: Sixt, Michael K
id: 41E9FBEA-F248-11E8-B48F-1D18A9856A87
last_name: Sixt
orcid: 0000-0002-4561-241X
- first_name: Stefan
full_name: Zahler, Stefan
last_name: Zahler
citation:
ama: Zisis T, Schwarz J, Balles M, et al. Sequential and switchable patterning for
studying cellular processes under spatiotemporal control. ACS Applied Materials
and Interfaces. 2021;13(30):35545–35560. doi:10.1021/acsami.1c09850
apa: Zisis, T., Schwarz, J., Balles, M., Kretschmer, M., Nemethova, M., Chait, R.
P., … Zahler, S. (2021). Sequential and switchable patterning for studying cellular
processes under spatiotemporal control. ACS Applied Materials and Interfaces.
American Chemical Society. https://doi.org/10.1021/acsami.1c09850
chicago: Zisis, Themistoklis, Jan Schwarz, Miriam Balles, Maibritt Kretschmer, Maria
Nemethova, Remy P Chait, Robert Hauschild, et al. “Sequential and Switchable Patterning
for Studying Cellular Processes under Spatiotemporal Control.” ACS Applied
Materials and Interfaces. American Chemical Society, 2021. https://doi.org/10.1021/acsami.1c09850.
ieee: T. Zisis et al., “Sequential and switchable patterning for studying
cellular processes under spatiotemporal control,” ACS Applied Materials and
Interfaces, vol. 13, no. 30. American Chemical Society, pp. 35545–35560, 2021.
ista: Zisis T, Schwarz J, Balles M, Kretschmer M, Nemethova M, Chait RP, Hauschild
R, Lange J, Guet CC, Sixt MK, Zahler S. 2021. Sequential and switchable patterning
for studying cellular processes under spatiotemporal control. ACS Applied Materials
and Interfaces. 13(30), 35545–35560.
mla: Zisis, Themistoklis, et al. “Sequential and Switchable Patterning for Studying
Cellular Processes under Spatiotemporal Control.” ACS Applied Materials and
Interfaces, vol. 13, no. 30, American Chemical Society, 2021, pp. 35545–35560,
doi:10.1021/acsami.1c09850.
short: T. Zisis, J. Schwarz, M. Balles, M. Kretschmer, M. Nemethova, R.P. Chait,
R. Hauschild, J. Lange, C.C. Guet, M.K. Sixt, S. Zahler, ACS Applied Materials
and Interfaces 13 (2021) 35545–35560.
date_created: 2021-08-08T22:01:28Z
date_published: 2021-08-04T00:00:00Z
date_updated: 2023-08-10T14:22:48Z
day: '04'
ddc:
- '620'
- '570'
department:
- _id: MiSi
- _id: GaTk
- _id: Bio
- _id: CaGu
doi: 10.1021/acsami.1c09850
ec_funded: 1
external_id:
isi:
- '000683741400026'
pmid:
- '34283577'
file:
- access_level: open_access
checksum: b043a91d9f9200e467b970b692687ed3
content_type: application/pdf
creator: asandaue
date_created: 2021-08-09T09:44:03Z
date_updated: 2021-08-09T09:44:03Z
file_id: '9833'
file_name: 2021_ACSAppliedMaterialsAndInterfaces_Zisis.pdf
file_size: 7123293
relation: main_file
success: 1
file_date_updated: 2021-08-09T09:44:03Z
has_accepted_license: '1'
intvolume: ' 13'
isi: 1
issue: '30'
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 35545–35560
pmid: 1
project:
- _id: 25FE9508-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '724373'
name: Cellular navigation along spatial gradients
publication: ACS Applied Materials and Interfaces
publication_identifier:
eissn:
- '19448252'
issn:
- '19448244'
publication_status: published
publisher: American Chemical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Sequential and switchable patterning for studying cellular processes under
spatiotemporal control
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 13
year: '2021'
...
---
_id: '9828'
abstract:
- lang: eng
text: Amplitude demodulation is a classical operation used in signal processing.
For a long time, its effective applications in practice have been limited to narrowband
signals. In this work, we generalize amplitude demodulation to wideband signals.
We pose demodulation as a recovery problem of an oversampled corrupted signal
and introduce special iterative schemes belonging to the family of alternating
projection algorithms to solve it. Sensibly chosen structural assumptions on the
demodulation outputs allow us to reveal the high inferential accuracy of the method
over a rich set of relevant signals. This new approach surpasses current state-of-the-art
demodulation techniques apt to wideband signals in computational efficiency by
up to many orders of magnitude with no sacrifice in quality. Such performance
opens the door for applications of the amplitude demodulation procedure in new
contexts. In particular, the new method makes online and large-scale offline data
processing feasible, including the calculation of modulator-carrier pairs in higher
dimensions and poor sampling conditions, independent of the signal bandwidth.
We illustrate the utility and specifics of applications of the new method in practice
by using natural speech and synthetic signals.
acknowledgement: The author thanks his colleagues K. Huszár and G. Tkačik for valuable
discussions and comments on the manuscript.
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Mantas
full_name: Gabrielaitis, Mantas
id: 4D5B0CBC-F248-11E8-B48F-1D18A9856A87
last_name: Gabrielaitis
orcid: 0000-0002-7758-2016
citation:
ama: Gabrielaitis M. Fast and accurate amplitude demodulation of wideband signals.
IEEE Transactions on Signal Processing. 2021;69:4039-4054. doi:10.1109/TSP.2021.3087899
apa: Gabrielaitis, M. (2021). Fast and accurate amplitude demodulation of wideband
signals. IEEE Transactions on Signal Processing. Institute of Electrical
and Electronics Engineers. https://doi.org/10.1109/TSP.2021.3087899
chicago: Gabrielaitis, Mantas. “Fast and Accurate Amplitude Demodulation of Wideband
Signals.” IEEE Transactions on Signal Processing. Institute of Electrical
and Electronics Engineers, 2021. https://doi.org/10.1109/TSP.2021.3087899.
ieee: M. Gabrielaitis, “Fast and accurate amplitude demodulation of wideband signals,”
IEEE Transactions on Signal Processing, vol. 69. Institute of Electrical
and Electronics Engineers, pp. 4039–4054, 2021.
ista: Gabrielaitis M. 2021. Fast and accurate amplitude demodulation of wideband
signals. IEEE Transactions on Signal Processing. 69, 4039–4054.
mla: Gabrielaitis, Mantas. “Fast and Accurate Amplitude Demodulation of Wideband
Signals.” IEEE Transactions on Signal Processing, vol. 69, Institute of
Electrical and Electronics Engineers, 2021, pp. 4039–54, doi:10.1109/TSP.2021.3087899.
short: M. Gabrielaitis, IEEE Transactions on Signal Processing 69 (2021) 4039–4054.
date_created: 2021-08-08T22:01:31Z
date_published: 2021-06-09T00:00:00Z
date_updated: 2023-08-10T14:19:33Z
day: '09'
department:
- _id: GaTk
doi: 10.1109/TSP.2021.3087899
external_id:
arxiv:
- '2102.04832'
isi:
- '000682123900002'
intvolume: ' 69'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2102.04832
month: '06'
oa: 1
oa_version: Preprint
page: 4039 - 4054
publication: IEEE Transactions on Signal Processing
publication_identifier:
eissn:
- 1941-0476
issn:
- 1053-587X
publication_status: published
publisher: Institute of Electrical and Electronics Engineers
quality_controlled: '1'
scopus_import: '1'
status: public
title: Fast and accurate amplitude demodulation of wideband signals
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 69
year: '2021'
...
---
_id: '8084'
abstract:
- lang: eng
text: Origin and functions of intermittent transitions among sleep stages, including
brief awakenings and arousals, constitute a challenge to the current homeostatic
framework for sleep regulation, focusing on factors modulating sleep over large
time scales. Here we propose that the complex micro-architecture characterizing
sleep on scales of seconds and minutes results from intrinsic non-equilibrium
critical dynamics. We investigate θ- and δ-wave dynamics in control rats and in
rats where the sleep-promoting ventrolateral preoptic nucleus (VLPO) is lesioned
(male Sprague-Dawley rats). We demonstrate that bursts in θ and δ cortical rhythms
exhibit complex temporal organization, with long-range correlations and robust
duality of power-law (θ-bursts, active phase) and exponential-like (δ-bursts,
quiescent phase) duration distributions, features typical of non-equilibrium systems
self-organizing at criticality. We show that such non-equilibrium behavior relates
to anti-correlated coupling between θ- and δ-bursts, persists across a range of
time scales, and is independent of the dominant physiologic state; indications
of a basic principle in sleep regulation. Further, we find that VLPO lesions lead
to a modulation of cortical dynamics resulting in altered dynamical parameters
of θ- and δ-bursts and significant reduction in θ–δ coupling. Our empirical findings
and model simulations demonstrate that θ–δ coupling is essential for the emerging
non-equilibrium critical dynamics observed across the sleep–wake cycle, and indicate
that VLPO neurons may have dual role for both sleep and arousal/brief wake activation.
The uncovered critical behavior in sleep- and wake-related cortical rhythms indicates
a mechanism essential for the micro-architecture of spontaneous sleep-stage and
arousal transitions within a novel, non-homeostatic paradigm of sleep regulation.
article_processing_charge: No
article_type: original
author:
- first_name: Fabrizio
full_name: Lombardi, Fabrizio
id: A057D288-3E88-11E9-986D-0CF4E5697425
last_name: Lombardi
orcid: 0000-0003-2623-5249
- first_name: Manuel
full_name: Gómez-Extremera, Manuel
last_name: Gómez-Extremera
- first_name: Pedro
full_name: Bernaola-Galván, Pedro
last_name: Bernaola-Galván
- first_name: Ramalingam
full_name: Vetrivelan, Ramalingam
last_name: Vetrivelan
- first_name: Clifford B.
full_name: Saper, Clifford B.
last_name: Saper
- first_name: Thomas E.
full_name: Scammell, Thomas E.
last_name: Scammell
- first_name: Plamen Ch.
full_name: Ivanov, Plamen Ch.
last_name: Ivanov
citation:
ama: Lombardi F, Gómez-Extremera M, Bernaola-Galván P, et al. Critical dynamics
and coupling in bursts of cortical rhythms indicate non-homeostatic mechanism
for sleep-stage transitions and dual role of VLPO neurons in both sleep and wake.
Journal of Neuroscience. 2020;40(1):171-190. doi:10.1523/jneurosci.1278-19.2019
apa: Lombardi, F., Gómez-Extremera, M., Bernaola-Galván, P., Vetrivelan, R., Saper,
C. B., Scammell, T. E., & Ivanov, P. C. (2020). Critical dynamics and coupling
in bursts of cortical rhythms indicate non-homeostatic mechanism for sleep-stage
transitions and dual role of VLPO neurons in both sleep and wake. Journal of
Neuroscience. Society for Neuroscience. https://doi.org/10.1523/jneurosci.1278-19.2019
chicago: Lombardi, Fabrizio, Manuel Gómez-Extremera, Pedro Bernaola-Galván, Ramalingam
Vetrivelan, Clifford B. Saper, Thomas E. Scammell, and Plamen Ch. Ivanov. “Critical
Dynamics and Coupling in Bursts of Cortical Rhythms Indicate Non-Homeostatic Mechanism
for Sleep-Stage Transitions and Dual Role of VLPO Neurons in Both Sleep and Wake.”
Journal of Neuroscience. Society for Neuroscience, 2020. https://doi.org/10.1523/jneurosci.1278-19.2019.
ieee: F. Lombardi et al., “Critical dynamics and coupling in bursts of cortical
rhythms indicate non-homeostatic mechanism for sleep-stage transitions and dual
role of VLPO neurons in both sleep and wake,” Journal of Neuroscience,
vol. 40, no. 1. Society for Neuroscience, pp. 171–190, 2020.
ista: Lombardi F, Gómez-Extremera M, Bernaola-Galván P, Vetrivelan R, Saper CB,
Scammell TE, Ivanov PC. 2020. Critical dynamics and coupling in bursts of cortical
rhythms indicate non-homeostatic mechanism for sleep-stage transitions and dual
role of VLPO neurons in both sleep and wake. Journal of Neuroscience. 40(1), 171–190.
mla: Lombardi, Fabrizio, et al. “Critical Dynamics and Coupling in Bursts of Cortical
Rhythms Indicate Non-Homeostatic Mechanism for Sleep-Stage Transitions and Dual
Role of VLPO Neurons in Both Sleep and Wake.” Journal of Neuroscience,
vol. 40, no. 1, Society for Neuroscience, 2020, pp. 171–90, doi:10.1523/jneurosci.1278-19.2019.
short: F. Lombardi, M. Gómez-Extremera, P. Bernaola-Galván, R. Vetrivelan, C.B.
Saper, T.E. Scammell, P.C. Ivanov, Journal of Neuroscience 40 (2020) 171–190.
date_created: 2020-07-05T15:24:51Z
date_published: 2020-01-02T00:00:00Z
date_updated: 2023-09-05T14:02:55Z
day: '02'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1523/jneurosci.1278-19.2019
ec_funded: 1
external_id:
isi:
- '000505167600016'
pmid:
- '31694962'
file:
- access_level: open_access
content_type: application/pdf
creator: dernst
date_created: 2020-07-22T11:44:48Z
date_updated: 2020-07-22T11:44:48Z
file_id: '8150'
file_name: 2020_JournNeuroscience_Lombardi.pdf
file_size: 6646046
relation: main_file
success: 1
file_date_updated: 2020-07-22T11:44:48Z
has_accepted_license: '1'
intvolume: ' 40'
isi: 1
issue: '1'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
page: 171-190
pmid: 1
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Journal of Neuroscience
publication_identifier:
eissn:
- 1529-2401
issn:
- 0270-6474
publication_status: published
publisher: Society for Neuroscience
quality_controlled: '1'
scopus_import: '1'
status: public
title: Critical dynamics and coupling in bursts of cortical rhythms indicate non-homeostatic
mechanism for sleep-stage transitions and dual role of VLPO neurons in both sleep
and wake
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 40
year: '2020'
...
---
_id: '8097'
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.'
acknowledged_ssus:
- _id: LifeSc
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. Analysis scripts and research data for the paper “Mechanisms of drug
interactions between translation-inhibiting antibiotics.” 2020. doi:10.15479/AT:ISTA:8097
apa: Kavcic, B. (2020). Analysis scripts and research data for the paper “Mechanisms
of drug interactions between translation-inhibiting antibiotics.” Institute of
Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8097
chicago: Kavcic, Bor. “Analysis Scripts and Research Data for the Paper ‘Mechanisms
of Drug Interactions between Translation-Inhibiting Antibiotics.’” Institute of
Science and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:8097.
ieee: B. Kavcic, “Analysis scripts and research data for the paper ‘Mechanisms of
drug interactions between translation-inhibiting antibiotics.’” Institute of Science
and Technology Austria, 2020.
ista: Kavcic B. 2020. Analysis scripts and research data for the paper ‘Mechanisms
of drug interactions between translation-inhibiting antibiotics’, Institute of
Science and Technology Austria, 10.15479/AT:ISTA:8097.
mla: Kavcic, Bor. Analysis Scripts and Research Data for the Paper “Mechanisms
of Drug Interactions between Translation-Inhibiting Antibiotics.” Institute
of Science and Technology Austria, 2020, doi:10.15479/AT:ISTA:8097.
short: B. Kavcic, (2020).
contributor:
- contributor_type: research_group
first_name: Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- contributor_type: research_group
first_name: Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
date_created: 2020-07-06T20:40:19Z
date_published: 2020-07-15T00:00:00Z
date_updated: 2024-02-21T12:40:51Z
day: '15'
department:
- _id: GaTk
doi: 10.15479/AT:ISTA:8097
file:
- access_level: open_access
checksum: 5c321dbbb6d4b3c85da786fd3ebbdc98
content_type: application/zip
creator: bkavcic
date_created: 2020-07-06T20:38:27Z
date_updated: 2020-07-14T12:48:09Z
file_id: '8098'
file_name: natComm_2020_scripts.zip
file_size: 255770756
relation: main_file
file_date_updated: 2020-07-14T12:48:09Z
has_accepted_license: '1'
keyword:
- Escherichia coli
- antibiotic combinations
- translation
- growth laws
- drug interactions
- bacterial physiology
- translation inhibitors
month: '07'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
status: public
title: Analysis scripts and research data for the paper "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: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2020'
...
---
_id: '8105'
abstract:
- lang: eng
text: Physical and biological systems often exhibit intermittent dynamics with bursts
or avalanches (active states) characterized by power-law size and duration distributions.
These emergent features are typical of systems at the critical point of continuous
phase transitions, and have led to the hypothesis that such systems may self-organize
at criticality, i.e. without any fine tuning of parameters. Since the introduction
of the Bak-Tang-Wiesenfeld (BTW) model, the paradigm of self-organized criticality
(SOC) has been very fruitful for the analysis of emergent collective behaviors
in a number of systems, including the brain. Although considerable effort has
been devoted in identifying and modeling scaling features of burst and avalanche
statistics, dynamical aspects related to the temporal organization of bursts remain
often poorly understood or controversial. Of crucial importance to understand
the mechanisms responsible for emergent behaviors is the relationship between
active and quiet periods, and the nature of the correlations. Here we investigate
the dynamics of active (θ-bursts) and quiet states (δ-bursts) in brain activity
during the sleep-wake cycle. We show the duality of power-law (θ, active phase)
and exponential-like (δ, quiescent phase) duration distributions, typical of SOC,
jointly emerge with power-law temporal correlations and anti-correlated coupling
between active and quiet states. Importantly, we demonstrate that such temporal
organization shares important similarities with earthquake dynamics, and propose
that specific power-law correlations and coupling between active and quiet states
are distinctive characteristics of a class of systems with self-organization at
criticality.
article_number: '00005'
article_processing_charge: No
article_type: original
author:
- first_name: Fabrizio
full_name: Lombardi, Fabrizio
id: A057D288-3E88-11E9-986D-0CF4E5697425
last_name: Lombardi
orcid: 0000-0003-2623-5249
- first_name: Jilin W.J.L.
full_name: Wang, Jilin W.J.L.
last_name: Wang
- first_name: Xiyun
full_name: Zhang, Xiyun
last_name: Zhang
- first_name: Plamen Ch
full_name: Ivanov, Plamen Ch
last_name: Ivanov
citation:
ama: Lombardi F, Wang JWJL, Zhang X, Ivanov PC. Power-law correlations and coupling
of active and quiet states underlie a class of complex systems with self-organization
at criticality. EPJ Web of Conferences. 2020;230. doi:10.1051/epjconf/202023000005
apa: Lombardi, F., Wang, J. W. J. L., Zhang, X., & Ivanov, P. C. (2020). Power-law
correlations and coupling of active and quiet states underlie a class of complex
systems with self-organization at criticality. EPJ Web of Conferences.
EDP Sciences. https://doi.org/10.1051/epjconf/202023000005
chicago: Lombardi, Fabrizio, Jilin W.J.L. Wang, Xiyun Zhang, and Plamen Ch Ivanov.
“Power-Law Correlations and Coupling of Active and Quiet States Underlie a Class
of Complex Systems with Self-Organization at Criticality.” EPJ Web of Conferences.
EDP Sciences, 2020. https://doi.org/10.1051/epjconf/202023000005.
ieee: F. Lombardi, J. W. J. L. Wang, X. Zhang, and P. C. Ivanov, “Power-law correlations
and coupling of active and quiet states underlie a class of complex systems with
self-organization at criticality,” EPJ Web of Conferences, vol. 230. EDP
Sciences, 2020.
ista: Lombardi F, Wang JWJL, Zhang X, Ivanov PC. 2020. Power-law correlations and
coupling of active and quiet states underlie a class of complex systems with self-organization
at criticality. EPJ Web of Conferences. 230, 00005.
mla: Lombardi, Fabrizio, et al. “Power-Law Correlations and Coupling of Active and
Quiet States Underlie a Class of Complex Systems with Self-Organization at Criticality.”
EPJ Web of Conferences, vol. 230, 00005, EDP Sciences, 2020, doi:10.1051/epjconf/202023000005.
short: F. Lombardi, J.W.J.L. Wang, X. Zhang, P.C. Ivanov, EPJ Web of Conferences
230 (2020).
date_created: 2020-07-12T16:20:33Z
date_published: 2020-03-11T00:00:00Z
date_updated: 2021-01-12T08:16:55Z
day: '11'
ddc:
- '530'
department:
- _id: GaTk
doi: 10.1051/epjconf/202023000005
file:
- access_level: open_access
content_type: application/pdf
creator: dernst
date_created: 2020-07-22T06:17:11Z
date_updated: 2020-07-22T06:17:11Z
file_id: '8144'
file_name: 2020_EPJWebConf_Lombardi.pdf
file_size: 2197543
relation: main_file
success: 1
file_date_updated: 2020-07-22T06:17:11Z
has_accepted_license: '1'
intvolume: ' 230'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
publication: EPJ Web of Conferences
publication_identifier:
issn:
- 2100-014X
publication_status: published
publisher: EDP Sciences
quality_controlled: '1'
status: public
title: Power-law correlations and coupling of active and quiet states underlie a class
of complex systems with self-organization at criticality
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: 230
year: '2020'
...
---
_id: '8155'
abstract:
- lang: eng
text: "In the thesis we focus on the interplay of the biophysics and evolution of
gene regulation. We start by addressing how the type of prokaryotic gene regulation
– activation and repression – affects spurious binding to DNA, also known as\r\ntranscriptional
crosstalk. We propose that regulatory interference caused by excess regulatory
proteins in the dense cellular medium – global crosstalk – could be a factor in
determining which type of gene regulatory network is evolutionarily preferred.
Next,we use a normative approach in eukaryotic gene regulation to describe minimal\r\nnon-equilibrium
enhancer models that optimize so-called regulatory phenotypes. We find a class
of models that differ from standard thermodynamic equilibrium models by a single
parameter that notably increases the regulatory performance. Next chapter addresses
the question of genotype-phenotype-fitness maps of higher dimensional phenotypes.
We show that our biophysically realistic approach allows us to understand how
the mechanisms of promoter function constrain genotypephenotype maps, and how
they affect the evolutionary trajectories of promoters.\r\nIn the last chapter
we ask whether the intrinsic instability of gene duplication and amplification
provides a generic alternative to canonical gene regulation. Using mathematical
modeling, we show that amplifications can tune gene expression in many environments,
including those where transcription factor-based schemes are\r\nhard to evolve
or maintain. "
acknowledgement: For the duration of his PhD, Rok was a recipient of a DOC fellowship
of the Austrian Academy of Sciences.
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Rok
full_name: Grah, Rok
id: 483E70DE-F248-11E8-B48F-1D18A9856A87
last_name: Grah
orcid: 0000-0003-2539-3560
citation:
ama: Grah R. Gene regulation across scales – how biophysical constraints shape evolution.
2020. doi:10.15479/AT:ISTA:8155
apa: Grah, R. (2020). Gene regulation across scales – how biophysical constraints
shape evolution. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8155
chicago: Grah, Rok. “Gene Regulation across Scales – How Biophysical Constraints
Shape Evolution.” Institute of Science and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:8155.
ieee: R. Grah, “Gene regulation across scales – how biophysical constraints shape
evolution,” Institute of Science and Technology Austria, 2020.
ista: Grah R. 2020. Gene regulation across scales – how biophysical constraints
shape evolution. Institute of Science and Technology Austria.
mla: Grah, Rok. Gene Regulation across Scales – How Biophysical Constraints Shape
Evolution. Institute of Science and Technology Austria, 2020, doi:10.15479/AT:ISTA:8155.
short: R. Grah, Gene Regulation across Scales – How Biophysical Constraints Shape
Evolution, Institute of Science and Technology Austria, 2020.
date_created: 2020-07-23T09:51:28Z
date_published: 2020-07-24T00:00:00Z
date_updated: 2023-09-07T13:13:27Z
day: '24'
ddc:
- '530'
- '570'
degree_awarded: PhD
department:
- _id: CaGu
- _id: GaTk
doi: 10.15479/AT:ISTA:8155
file:
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content_type: application/pdf
creator: rgrah
date_created: 2020-07-27T12:00:07Z
date_updated: 2020-07-27T12:00:07Z
file_id: '8176'
file_name: Thesis_RokGrah_200727_convertedNew.pdf
file_size: 16638998
relation: main_file
success: 1
- access_level: closed
content_type: application/zip
creator: rgrah
date_created: 2020-07-27T12:02:23Z
date_updated: 2020-07-30T13:04:55Z
file_id: '8177'
file_name: Thesis_new.zip
file_size: 347459978
relation: main_file
file_date_updated: 2020-07-30T13:04:55Z
has_accepted_license: '1'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: '310'
project:
- _id: 267C84F4-B435-11E9-9278-68D0E5697425
name: Biophysically realistic genotype-phenotype maps for regulatory networks
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '7675'
relation: part_of_dissertation
status: public
- id: '7569'
relation: part_of_dissertation
status: public
- id: '7652'
relation: part_of_dissertation
status: public
status: public
supervisor:
- 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
title: Gene regulation across scales – how biophysical constraints shape evolution
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: 2024-03-25T23:30:05Z
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: '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:
- access_level: open_access
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: '8698'
abstract:
- lang: eng
text: The brain represents and reasons probabilistically about complex stimuli and
motor actions using a noisy, spike-based neural code. A key building block for
such neural computations, as well as the basis for supervised and unsupervised
learning, is the ability to estimate the surprise or likelihood of incoming high-dimensional
neural activity patterns. Despite progress in statistical modeling of neural responses
and deep learning, current approaches either do not scale to large neural populations
or cannot be implemented using biologically realistic mechanisms. Inspired by
the sparse and random connectivity of real neuronal circuits, we present a model
for neural codes that accurately estimates the likelihood of individual spiking
patterns and has a straightforward, scalable, efficient, learnable, and realistic
neural implementation. This model’s performance on simultaneously recorded spiking
activity of >100 neurons in the monkey visual and prefrontal cortices is comparable
with or better than that of state-of-the-art models. Importantly, the model can
be learned using a small number of samples and using a local learning rule that
utilizes noise intrinsic to neural circuits. Slower, structural changes in random
connectivity, consistent with rewiring and pruning processes, further improve
the efficiency and sparseness of the resulting neural representations. Our results
merge insights from neuroanatomy, machine learning, and theoretical neuroscience
to suggest random sparse connectivity as a key design principle for neuronal computation.
acknowledgement: We thank Udi Karpas, Roy Harpaz, Tal Tamir, Adam Haber, and Amir
Bar for discussions and suggestions; and especially Oren Forkosh and Walter Senn
for invaluable discussions of the learning rule. This work was supported by European
Research Council Grant 311238 (to E.S.) and Israel Science Foundation Grant 1629/12
(to E.S.); as well as research support from Martin Kushner Schnur and Mr. and Mrs.
Lawrence Feis (E.S.); National Institute of Mental Health Grant R01MH109180 (to
R.K.); a Pew Scholarship in Biomedical Sciences (to R.K.); Simons Collaboration
on the Global Brain Grant 542997 (to R.K. and E.S.); and a CRCNS (Collaborative
Research in Computational Neuroscience) grant (to R.K. and E.S.).
article_processing_charge: No
article_type: original
author:
- first_name: Ori
full_name: Maoz, Ori
last_name: Maoz
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- first_name: Mohamad Saleh
full_name: Esteki, Mohamad Saleh
last_name: Esteki
- first_name: Roozbeh
full_name: Kiani, Roozbeh
last_name: Kiani
- first_name: Elad
full_name: Schneidman, Elad
last_name: Schneidman
citation:
ama: Maoz O, Tkačik G, Esteki MS, Kiani R, Schneidman E. Learning probabilistic
neural representations with randomly connected circuits. Proceedings of the
National Academy of Sciences of the United States of America. 2020;117(40):25066-25073.
doi:10.1073/pnas.1912804117
apa: Maoz, O., Tkačik, G., Esteki, M. S., Kiani, R., & Schneidman, E. (2020).
Learning probabilistic neural representations with randomly connected circuits.
Proceedings of the National Academy of Sciences of the United States of America.
National Academy of Sciences. https://doi.org/10.1073/pnas.1912804117
chicago: Maoz, Ori, Gašper Tkačik, Mohamad Saleh Esteki, Roozbeh Kiani, and Elad
Schneidman. “Learning Probabilistic Neural Representations with Randomly Connected
Circuits.” Proceedings of the National Academy of Sciences of the United States
of America. National Academy of Sciences, 2020. https://doi.org/10.1073/pnas.1912804117.
ieee: O. Maoz, G. Tkačik, M. S. Esteki, R. Kiani, and E. Schneidman, “Learning probabilistic
neural representations with randomly connected circuits,” Proceedings of the
National Academy of Sciences of the United States of America, vol. 117, no.
40. National Academy of Sciences, pp. 25066–25073, 2020.
ista: Maoz O, Tkačik G, Esteki MS, Kiani R, Schneidman E. 2020. Learning probabilistic
neural representations with randomly connected circuits. Proceedings of the National
Academy of Sciences of the United States of America. 117(40), 25066–25073.
mla: Maoz, Ori, et al. “Learning Probabilistic Neural Representations with Randomly
Connected Circuits.” Proceedings of the National Academy of Sciences of the
United States of America, vol. 117, no. 40, National Academy of Sciences,
2020, pp. 25066–73, doi:10.1073/pnas.1912804117.
short: O. Maoz, G. Tkačik, M.S. Esteki, R. Kiani, E. Schneidman, Proceedings of
the National Academy of Sciences of the United States of America 117 (2020) 25066–25073.
date_created: 2020-10-25T23:01:16Z
date_published: 2020-10-06T00:00:00Z
date_updated: 2023-08-22T12:11:23Z
day: '06'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1073/pnas.1912804117
external_id:
isi:
- '000579045200012'
pmid:
- '32948691'
file:
- access_level: open_access
checksum: c6a24fdecf3f28faf447078e7a274a88
content_type: application/pdf
creator: cziletti
date_created: 2020-10-27T14:57:50Z
date_updated: 2020-10-27T14:57:50Z
file_id: '8713'
file_name: 2020_PNAS_Maoz.pdf
file_size: 1755359
relation: main_file
success: 1
file_date_updated: 2020-10-27T14:57:50Z
has_accepted_license: '1'
intvolume: ' 117'
isi: 1
issue: '40'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: 25066-25073
pmid: 1
publication: Proceedings of the National Academy of Sciences of the United States
of America
publication_identifier:
eissn:
- '10916490'
issn:
- '00278424'
publication_status: published
publisher: National Academy of Sciences
quality_controlled: '1'
scopus_import: '1'
status: public
title: Learning probabilistic neural representations with randomly connected circuits
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 117
year: '2020'
...
---
_id: '8930'
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.
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. Analysis scripts and research data for the paper “Minimal biophysical
model of combined antibiotic action.” 2020. doi:10.15479/AT:ISTA:8930
apa: Kavcic, B. (2020). Analysis scripts and research data for the paper “Minimal
biophysical model of combined antibiotic action.” Institute of Science and Technology
Austria. https://doi.org/10.15479/AT:ISTA:8930
chicago: Kavcic, Bor. “Analysis Scripts and Research Data for the Paper ‘Minimal
Biophysical Model of Combined Antibiotic Action.’” Institute of Science and Technology
Austria, 2020. https://doi.org/10.15479/AT:ISTA:8930.
ieee: B. Kavcic, “Analysis scripts and research data for the paper ‘Minimal biophysical
model of combined antibiotic action.’” Institute of Science and Technology Austria,
2020.
ista: Kavcic B. 2020. Analysis scripts and research data for the paper ‘Minimal
biophysical model of combined antibiotic action’, Institute of Science and Technology
Austria, 10.15479/AT:ISTA:8930.
mla: Kavcic, Bor. Analysis Scripts and Research Data for the Paper “Minimal Biophysical
Model of Combined Antibiotic Action.” Institute of Science and Technology
Austria, 2020, doi:10.15479/AT:ISTA:8930.
short: B. Kavcic, (2020).
contributor:
- contributor_type: supervisor
first_name: Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
- contributor_type: supervisor
first_name: Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
date_created: 2020-12-09T15:04:02Z
date_published: 2020-12-10T00:00:00Z
date_updated: 2024-02-21T12:41:42Z
day: '10'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.15479/AT:ISTA:8930
file:
- access_level: open_access
checksum: 60a818edeffaa7da1ebf5f8fbea9ba18
content_type: application/zip
creator: bkavcic
date_created: 2020-12-09T15:00:19Z
date_updated: 2020-12-09T15:00:19Z
file_id: '8932'
file_name: PLoSCompBiol2020_datarep.zip
file_size: 315494370
relation: main_file
success: 1
file_date_updated: 2020-12-09T15:00:19Z
has_accepted_license: '1'
keyword:
- Escherichia coli
- antibiotic combinations
- translation
- growth laws
- drug interactions
- bacterial physiology
- translation inhibitors
month: '12'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '8997'
relation: used_in_publication
status: public
status: public
title: Analysis scripts and research data for the paper "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: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2020'
...
---
_id: '8955'
abstract:
- lang: eng
text: Skeletal muscle activity is continuously modulated across physiologic states
to provide coordination, flexibility and responsiveness to body tasks and external
inputs. Despite the central role the muscular system plays in facilitating vital
body functions, the network of brain-muscle interactions required to control hundreds
of muscles and synchronize their activation in relation to distinct physiologic
states has not been investigated. Recent approaches have focused on general associations
between individual brain rhythms and muscle activation during movement tasks.
However, the specific forms of coupling, the functional network of cortico-muscular
coordination, and how network structure and dynamics are modulated by autonomic
regulation across physiologic states remains unknown. To identify and quantify
the cortico-muscular interaction network and uncover basic features of neuro-autonomic
control of muscle function, we investigate the coupling between synchronous bursts
in cortical rhythms and peripheral muscle activation during sleep and wake. Utilizing
the concept of time delay stability and a novel network physiology approach, we
find that the brain-muscle network exhibits complex dynamic patterns of communication
involving multiple brain rhythms across cortical locations and different electromyographic
frequency bands. Moreover, our results show that during each physiologic state
the cortico-muscular network is characterized by a specific profile of network
links strength, where particular brain rhythms play role of main mediators of
interaction and control. Further, we discover a hierarchical reorganization in
network structure across physiologic states, with high connectivity and network
link strength during wake, intermediate during REM and light sleep, and low during
deep sleep, a sleep-stage stratification that demonstrates a unique association
between physiologic states and cortico-muscular network structure. The reported
empirical observations are consistent across individual subjects, indicating universal
behavior in network structure and dynamics, and high sensitivity of cortico-muscular
control to changes in autonomic regulation, even at low levels of physical activity
and muscle tone during sleep. Our findings demonstrate previously unrecognized
basic principles of brain-muscle network communication and control, and provide
new perspectives on the regulatory mechanisms of brain dynamics and locomotor
activation, with potential clinical implications for neurodegenerative, movement
and sleep disorders, and for developing efficient treatment strategies.
acknowledgement: We acknowledge support from the W. M. Keck Foundation, National Institutes
of Health (NIH Grant 1R01-HL098437), the US-Israel Binational Science Foundation
(BSF Grant 2012219), and the Office of Naval Research (ONR Grant 000141010078).
FL acknowledges support also from the European Union's Horizon 2020 research and
innovation program under the Marie Sklodowska-Curie Grant Agreement No. 754411.
article_number: '558070'
article_processing_charge: No
article_type: original
author:
- first_name: Rossella
full_name: Rizzo, Rossella
last_name: Rizzo
- first_name: Xiyun
full_name: Zhang, Xiyun
last_name: Zhang
- first_name: Jilin W.J.L.
full_name: Wang, Jilin W.J.L.
last_name: Wang
- first_name: Fabrizio
full_name: Lombardi, Fabrizio
id: A057D288-3E88-11E9-986D-0CF4E5697425
last_name: Lombardi
orcid: 0000-0003-2623-5249
- first_name: Plamen Ch
full_name: Ivanov, Plamen Ch
last_name: Ivanov
citation:
ama: Rizzo R, Zhang X, Wang JWJL, Lombardi F, Ivanov PC. Network physiology of cortico–muscular
interactions. Frontiers in Physiology. 2020;11. doi:10.3389/fphys.2020.558070
apa: Rizzo, R., Zhang, X., Wang, J. W. J. L., Lombardi, F., & Ivanov, P. C.
(2020). Network physiology of cortico–muscular interactions. Frontiers in Physiology.
Frontiers. https://doi.org/10.3389/fphys.2020.558070
chicago: Rizzo, Rossella, Xiyun Zhang, Jilin W.J.L. Wang, Fabrizio Lombardi, and
Plamen Ch Ivanov. “Network Physiology of Cortico–Muscular Interactions.” Frontiers
in Physiology. Frontiers, 2020. https://doi.org/10.3389/fphys.2020.558070.
ieee: R. Rizzo, X. Zhang, J. W. J. L. Wang, F. Lombardi, and P. C. Ivanov, “Network
physiology of cortico–muscular interactions,” Frontiers in Physiology,
vol. 11. Frontiers, 2020.
ista: Rizzo R, Zhang X, Wang JWJL, Lombardi F, Ivanov PC. 2020. Network physiology
of cortico–muscular interactions. Frontiers in Physiology. 11, 558070.
mla: Rizzo, Rossella, et al. “Network Physiology of Cortico–Muscular Interactions.”
Frontiers in Physiology, vol. 11, 558070, Frontiers, 2020, doi:10.3389/fphys.2020.558070.
short: R. Rizzo, X. Zhang, J.W.J.L. Wang, F. Lombardi, P.C. Ivanov, Frontiers in
Physiology 11 (2020).
date_created: 2020-12-20T23:01:18Z
date_published: 2020-11-26T00:00:00Z
date_updated: 2023-08-24T11:00:45Z
day: '26'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.3389/fphys.2020.558070
ec_funded: 1
external_id:
isi:
- '000596849400001'
pmid:
- '33324233'
file:
- access_level: open_access
checksum: ef9515b28c5619b7126c0f347958bcb3
content_type: application/pdf
creator: dernst
date_created: 2020-12-21T10:37:50Z
date_updated: 2020-12-21T10:37:50Z
file_id: '8961'
file_name: 2020_Frontiers_Rizzo.pdf
file_size: 13380030
relation: main_file
success: 1
file_date_updated: 2020-12-21T10:37:50Z
has_accepted_license: '1'
intvolume: ' 11'
isi: 1
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Frontiers in Physiology
publication_identifier:
eissn:
- 1664042X
publication_status: published
publisher: Frontiers
quality_controlled: '1'
scopus_import: '1'
status: public
title: Network physiology of cortico–muscular interactions
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 11
year: '2020'
...
---
_id: '9000'
abstract:
- lang: eng
text: 'In prokaryotes, thermodynamic models of gene regulation provide a highly
quantitative mapping from promoter sequences to gene-expression levels that is
compatible with in vivo and in vitro biophysical measurements. Such concordance
has not been achieved for models of enhancer function in eukaryotes. In equilibrium
models, it is difficult to reconcile the reported short transcription factor (TF)
residence times on the DNA with the high specificity of regulation. In nonequilibrium
models, progress is difficult due to an explosion in the number of parameters.
Here, we navigate this complexity by looking for minimal nonequilibrium enhancer
models that yield desired regulatory phenotypes: low TF residence time, high specificity,
and tunable cooperativity. We find that a single extra parameter, interpretable
as the “linking rate,” by which bound TFs interact with Mediator components, enables
our models to escape equilibrium bounds and access optimal regulatory phenotypes,
while remaining consistent with the reported phenomenology and simple enough to
be inferred from upcoming experiments. We further find that high specificity in
nonequilibrium models is in a trade-off with gene-expression noise, predicting
bursty dynamics—an experimentally observed hallmark of eukaryotic transcription.
By drastically reducing the vast parameter space of nonequilibrium enhancer models
to a much smaller subspace that optimally realizes biological function, we deliver
a rich class of models that could be tractably inferred from data in the near
future.'
acknowledgement: G.T. was supported by Human Frontiers Science Program Grant RGP0034/2018.
R.G. was supported by the Austrian Academy of Sciences DOC Fellowship. R.G. thanks
S. Avvakumov for helpful discussions.
article_processing_charge: No
article_type: original
author:
- first_name: Rok
full_name: Grah, Rok
id: 483E70DE-F248-11E8-B48F-1D18A9856A87
last_name: Grah
orcid: 0000-0003-2539-3560
- first_name: Benjamin
full_name: Zoller, Benjamin
last_name: Zoller
- first_name: Gašper
full_name: Tkačik, Gašper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkačik
orcid: 0000-0002-6699-1455
citation:
ama: Grah R, Zoller B, Tkačik G. Nonequilibrium models of optimal enhancer function.
PNAS. 2020;117(50):31614-31622. doi:10.1073/pnas.2006731117
apa: Grah, R., Zoller, B., & Tkačik, G. (2020). Nonequilibrium models of optimal
enhancer function. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.2006731117
chicago: Grah, Rok, Benjamin Zoller, and Gašper Tkačik. “Nonequilibrium Models of
Optimal Enhancer Function.” PNAS. National Academy of Sciences, 2020. https://doi.org/10.1073/pnas.2006731117.
ieee: R. Grah, B. Zoller, and G. Tkačik, “Nonequilibrium models of optimal enhancer
function,” PNAS, vol. 117, no. 50. National Academy of Sciences, pp. 31614–31622,
2020.
ista: Grah R, Zoller B, Tkačik G. 2020. Nonequilibrium models of optimal enhancer
function. PNAS. 117(50), 31614–31622.
mla: Grah, Rok, et al. “Nonequilibrium Models of Optimal Enhancer Function.” PNAS,
vol. 117, no. 50, National Academy of Sciences, 2020, pp. 31614–22, doi:10.1073/pnas.2006731117.
short: R. Grah, B. Zoller, G. Tkačik, PNAS 117 (2020) 31614–31622.
date_created: 2021-01-10T23:01:17Z
date_published: 2020-12-15T00:00:00Z
date_updated: 2023-08-24T11:10:22Z
day: '15'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1073/pnas.2006731117
external_id:
isi:
- '000600608300015'
pmid:
- '33268497'
file:
- access_level: open_access
checksum: 69039cd402a571983aa6cb4815ffa863
content_type: application/pdf
creator: dernst
date_created: 2021-01-11T08:37:31Z
date_updated: 2021-01-11T08:37:31Z
file_id: '9004'
file_name: 2020_PNAS_Grah.pdf
file_size: 1199247
relation: main_file
success: 1
file_date_updated: 2021-01-11T08:37:31Z
has_accepted_license: '1'
intvolume: ' 117'
isi: 1
issue: '50'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
page: 31614-31622
pmid: 1
project:
- _id: 2665AAFE-B435-11E9-9278-68D0E5697425
grant_number: RGP0034/2018
name: Can evolution minimize spurious signaling crosstalk to reach optimal performance?
- _id: 267C84F4-B435-11E9-9278-68D0E5697425
name: Biophysically realistic genotype-phenotype maps for regulatory networks
publication: PNAS
publication_identifier:
eissn:
- '10916490'
issn:
- '00278424'
publication_status: published
publisher: National Academy of Sciences
quality_controlled: '1'
related_material:
link:
- description: News on IST Homepage
relation: press_release
url: https://ist.ac.at/en/news/new-compact-model-for-gene-regulation-in-higher-organisms/
scopus_import: '1'
status: public
title: Nonequilibrium models of optimal enhancer function
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 117
year: '2020'
...
---
_id: '7383'
abstract:
- lang: eng
text: Organisms cope with change by employing transcriptional regulators. However,
when faced with rare environments, the evolution of transcriptional regulators
and their promoters may be too slow. We ask whether the intrinsic instability
of gene duplication and amplification provides a generic alternative to canonical
gene regulation. By real-time monitoring of gene copy number mutations in E. coli,
we show that gene duplications and amplifications enable adaptation to fluctuating
environments by rapidly generating copy number, and hence expression level, polymorphism.
This ‘amplification-mediated gene expression tuning’ occurs on timescales similar
to canonical gene regulation and can deal with rapid environmental changes. Mathematical
modeling shows that amplifications also tune gene expression in stochastic environments
where 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 expression of any gene, without
leaving any genomic signature.
article_processing_charge: No
author:
- first_name: Rok
full_name: Grah, Rok
id: 483E70DE-F248-11E8-B48F-1D18A9856A87
last_name: Grah
orcid: 0000-0003-2539-3560
citation:
ama: 'Grah R. Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level
Gene Expression regulation. 2020. doi:10.15479/AT:ISTA:7383'
apa: 'Grah, R. (2020). Matlab scripts for the Paper: Gene Amplification as a Form
of Population-Level Gene Expression regulation. Institute of Science and Technology
Austria. https://doi.org/10.15479/AT:ISTA:7383'
chicago: 'Grah, Rok. “Matlab Scripts for the Paper: Gene Amplification as a Form
of Population-Level Gene Expression Regulation.” Institute of Science and Technology
Austria, 2020. https://doi.org/10.15479/AT:ISTA:7383.'
ieee: 'R. Grah, “Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level
Gene Expression regulation.” Institute of Science and Technology Austria, 2020.'
ista: 'Grah R. 2020. Matlab scripts for the Paper: Gene Amplification as a Form
of Population-Level Gene Expression regulation, Institute of Science and Technology
Austria, 10.15479/AT:ISTA:7383.'
mla: 'Grah, Rok. Matlab Scripts for the Paper: Gene Amplification as a Form of
Population-Level Gene Expression Regulation. Institute of Science and Technology
Austria, 2020, doi:10.15479/AT:ISTA:7383.'
short: R. Grah, (2020).
contributor:
- contributor_type: project_leader
first_name: Calin C
id: 47F8433E-F248-11E8-B48F-1D18A9856A87
last_name: Guet
orcid: 0000-0001-6220-2052
date_created: 2020-01-28T10:41:49Z
date_published: 2020-01-28T00:00:00Z
date_updated: 2024-02-21T12:42:31Z
day: '28'
department:
- _id: CaGu
- _id: GaTk
doi: 10.15479/AT:ISTA:7383
file:
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checksum: 9d292cf5207b3829225f44c044cdb3fd
content_type: application/zip
creator: rgrah
date_created: 2020-01-28T10:39:40Z
date_updated: 2020-07-14T12:47:57Z
file_id: '7384'
file_name: Scripts.zip
file_size: 73363365
relation: main_file
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checksum: 4076ceab32ef588cc233802bab24c1ab
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creator: rgrah
date_created: 2020-01-28T10:39:30Z
date_updated: 2020-07-14T12:47:57Z
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file_name: READ_ME_MAIN.txt
file_size: 962
relation: main_file
file_date_updated: 2020-07-14T12:47:57Z
has_accepted_license: '1'
keyword:
- Matlab scripts
- analysis of microfluidics
- mathematical model
month: '01'
oa: 1
oa_version: Published Version
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '7652'
relation: used_in_publication
status: public
status: public
title: 'Matlab scripts for the Paper: Gene Amplification as a Form of Population-Level
Gene Expression regulation'
type: research_data
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2020'
...