---
_id: '12837'
abstract:
- lang: eng
text: As developing tissues grow in size and undergo morphogenetic changes, their
material properties may be altered. Such changes result from tension dynamics
at cell contacts or cellular jamming. Yet, in many cases, the cellular mechanisms
controlling the physical state of growing tissues are unclear. We found that at
early developmental stages, the epithelium in the developing mouse spinal cord
maintains both high junctional tension and high fluidity. This is achieved via
a mechanism in which interkinetic nuclear movements generate cell area dynamics
that drive extensive cell rearrangements. Over time, the cell proliferation rate
declines, effectively solidifying the tissue. Thus, unlike well-studied jamming
transitions, the solidification uncovered here resembles a glass transition that
depends on the dynamical stresses generated by proliferation and differentiation.
Our finding that the fluidity of developing epithelia is linked to interkinetic
nuclear movements and the dynamics of growth is likely to be relevant to multiple
developing tissues.
acknowledgement: 'We thank S. Hippenmeyer for the reagents and C. P. Heisenberg, J.
Briscoe and K. Page for comments on the manuscript. This work was supported by IST
Austria; the European Research Council under Horizon 2020 research and innovation
programme grant no. 680037 and Horizon Europe grant 101044579 (A.K.); Austrian Science
Fund (FWF): F78 (Stem Cell Modulation) (A.K.); ISTFELLOW postdoctoral program (A.S.);
Narodowe Centrum Nauki, Poland SONATA, 2017/26/D/NZ2/00454 (M.Z.); and the Polish
National Agency for Academic Exchange (M.Z.).'
article_processing_charge: No
article_type: original
author:
- first_name: Laura
full_name: Bocanegra, Laura
id: 4896F754-F248-11E8-B48F-1D18A9856A87
last_name: Bocanegra
- first_name: Amrita
full_name: Singh, Amrita
id: 76250f9f-3a21-11eb-9a80-a6180a0d7958
last_name: Singh
- first_name: Edouard B
full_name: Hannezo, Edouard B
id: 3A9DB764-F248-11E8-B48F-1D18A9856A87
last_name: Hannezo
orcid: 0000-0001-6005-1561
- first_name: Marcin P
full_name: Zagórski, Marcin P
id: 343DA0DC-F248-11E8-B48F-1D18A9856A87
last_name: Zagórski
orcid: 0000-0001-7896-7762
- first_name: Anna
full_name: Kicheva, Anna
id: 3959A2A0-F248-11E8-B48F-1D18A9856A87
last_name: Kicheva
orcid: 0000-0003-4509-4998
citation:
ama: Bocanegra L, Singh A, Hannezo EB, Zagórski MP, Kicheva A. Cell cycle dynamics
control fluidity of the developing mouse neuroepithelium. Nature Physics.
2023;19:1050-1058. doi:10.1038/s41567-023-01977-w
apa: Bocanegra, L., Singh, A., Hannezo, E. B., Zagórski, M. P., & Kicheva, A.
(2023). Cell cycle dynamics control fluidity of the developing mouse neuroepithelium.
Nature Physics. Springer Nature. https://doi.org/10.1038/s41567-023-01977-w
chicago: Bocanegra, Laura, Amrita Singh, Edouard B Hannezo, Marcin P Zagórski, and
Anna Kicheva. “Cell Cycle Dynamics Control Fluidity of the Developing Mouse Neuroepithelium.”
Nature Physics. Springer Nature, 2023. https://doi.org/10.1038/s41567-023-01977-w.
ieee: L. Bocanegra, A. Singh, E. B. Hannezo, M. P. Zagórski, and A. Kicheva, “Cell
cycle dynamics control fluidity of the developing mouse neuroepithelium,” Nature
Physics, vol. 19. Springer Nature, pp. 1050–1058, 2023.
ista: Bocanegra L, Singh A, Hannezo EB, Zagórski MP, Kicheva A. 2023. Cell cycle
dynamics control fluidity of the developing mouse neuroepithelium. Nature Physics.
19, 1050–1058.
mla: Bocanegra, Laura, et al. “Cell Cycle Dynamics Control Fluidity of the Developing
Mouse Neuroepithelium.” Nature Physics, vol. 19, Springer Nature, 2023,
pp. 1050–58, doi:10.1038/s41567-023-01977-w.
short: L. Bocanegra, A. Singh, E.B. Hannezo, M.P. Zagórski, A. Kicheva, Nature Physics
19 (2023) 1050–1058.
date_created: 2023-04-16T22:01:09Z
date_published: 2023-07-01T00:00:00Z
date_updated: 2023-10-04T11:14:05Z
day: '01'
ddc:
- '570'
department:
- _id: EdHa
- _id: AnKi
doi: 10.1038/s41567-023-01977-w
ec_funded: 1
external_id:
isi:
- '000964029300003'
file:
- access_level: open_access
checksum: 858225a4205b74406e5045006cdd853f
content_type: application/pdf
creator: dernst
date_created: 2023-10-04T11:13:28Z
date_updated: 2023-10-04T11:13:28Z
file_id: '14392'
file_name: 2023_NaturePhysics_Boncanegra.pdf
file_size: 5532285
relation: main_file
success: 1
file_date_updated: 2023-10-04T11:13:28Z
has_accepted_license: '1'
intvolume: ' 19'
isi: 1
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '07'
oa: 1
oa_version: Published Version
page: 1050-1058
project:
- _id: B6FC0238-B512-11E9-945C-1524E6697425
call_identifier: H2020
grant_number: '680037'
name: Coordination of Patterning And Growth In the Spinal Cord
- _id: bd7e737f-d553-11ed-ba76-d69ffb5ee3aa
grant_number: '101044579'
name: Mechanisms of tissue size regulation in spinal cord development
- _id: 059DF620-7A3F-11EA-A408-12923DDC885E
grant_number: F07802
name: Morphogen control of growth and pattern in the spinal cord
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Nature Physics
publication_identifier:
eissn:
- 1745-2481
issn:
- 1745-2473
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '13081'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Cell cycle dynamics control fluidity of the developing mouse neuroepithelium
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: 19
year: '2023'
...
---
_id: '7165'
abstract:
- lang: eng
text: Cell division, movement and differentiation contribute to pattern formation
in developing tissues. This is the case in the vertebrate neural tube, in which
neurons differentiate in a characteristic pattern from a highly dynamic proliferating
pseudostratified epithelium. To investigate how progenitor proliferation and differentiation
affect cell arrangement and growth of the neural tube, we used experimental measurements
to develop a mechanical model of the apical surface of the neuroepithelium that
incorporates the effect of interkinetic nuclear movement and spatially varying
rates of neuronal differentiation. Simulations predict that tissue growth and
the shape of lineage-related clones of cells differ with the rate of differentiation.
Growth is isotropic in regions of high differentiation, but dorsoventrally biased
in regions of low differentiation. This is consistent with experimental observations.
The absence of directional signalling in the simulations indicates that global
mechanical constraints are sufficient to explain the observed differences in anisotropy.
This provides insight into how the tissue growth rate affects cell dynamics and
growth anisotropy and opens up possibilities to study the coupling between mechanics,
pattern formation and growth in the neural tube.
article_number: dev176297
article_processing_charge: No
article_type: original
author:
- first_name: Pilar
full_name: Guerrero, Pilar
last_name: Guerrero
- first_name: Ruben
full_name: Perez-Carrasco, Ruben
last_name: Perez-Carrasco
- first_name: Marcin P
full_name: Zagórski, Marcin P
id: 343DA0DC-F248-11E8-B48F-1D18A9856A87
last_name: Zagórski
orcid: 0000-0001-7896-7762
- first_name: David
full_name: Page, David
last_name: Page
- first_name: Anna
full_name: Kicheva, Anna
id: 3959A2A0-F248-11E8-B48F-1D18A9856A87
last_name: Kicheva
orcid: 0000-0003-4509-4998
- first_name: James
full_name: Briscoe, James
last_name: Briscoe
- first_name: Karen M.
full_name: Page, Karen M.
last_name: Page
citation:
ama: Guerrero P, Perez-Carrasco R, Zagórski MP, et al. Neuronal differentiation
influences progenitor arrangement in the vertebrate neuroepithelium. Development.
2019;146(23). doi:10.1242/dev.176297
apa: Guerrero, P., Perez-Carrasco, R., Zagórski, M. P., Page, D., Kicheva, A., Briscoe,
J., & Page, K. M. (2019). Neuronal differentiation influences progenitor arrangement
in the vertebrate neuroepithelium. Development. The Company of Biologists.
https://doi.org/10.1242/dev.176297
chicago: Guerrero, Pilar, Ruben Perez-Carrasco, Marcin P Zagórski, David Page, Anna
Kicheva, James Briscoe, and Karen M. Page. “Neuronal Differentiation Influences
Progenitor Arrangement in the Vertebrate Neuroepithelium.” Development.
The Company of Biologists, 2019. https://doi.org/10.1242/dev.176297.
ieee: P. Guerrero et al., “Neuronal differentiation influences progenitor
arrangement in the vertebrate neuroepithelium,” Development, vol. 146,
no. 23. The Company of Biologists, 2019.
ista: Guerrero P, Perez-Carrasco R, Zagórski MP, Page D, Kicheva A, Briscoe J, Page
KM. 2019. Neuronal differentiation influences progenitor arrangement in the vertebrate
neuroepithelium. Development. 146(23), dev176297.
mla: Guerrero, Pilar, et al. “Neuronal Differentiation Influences Progenitor Arrangement
in the Vertebrate Neuroepithelium.” Development, vol. 146, no. 23, dev176297,
The Company of Biologists, 2019, doi:10.1242/dev.176297.
short: P. Guerrero, R. Perez-Carrasco, M.P. Zagórski, D. Page, A. Kicheva, J. Briscoe,
K.M. Page, Development 146 (2019).
date_created: 2019-12-10T14:39:50Z
date_published: 2019-12-04T00:00:00Z
date_updated: 2023-09-06T11:26:36Z
day: '04'
ddc:
- '570'
department:
- _id: AnKi
doi: 10.1242/dev.176297
ec_funded: 1
external_id:
isi:
- '000507575700004'
pmid:
- '31784457'
file:
- access_level: open_access
checksum: b6533c37dc8fbd803ffeca216e0a8b8a
content_type: application/pdf
creator: dernst
date_created: 2019-12-13T07:34:06Z
date_updated: 2020-07-14T12:47:50Z
file_id: '7177'
file_name: 2019_Development_Guerrero.pdf
file_size: 7797881
relation: main_file
file_date_updated: 2020-07-14T12:47:50Z
has_accepted_license: '1'
intvolume: ' 146'
isi: 1
issue: '23'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: B6FC0238-B512-11E9-945C-1524E6697425
call_identifier: H2020
grant_number: '680037'
name: Coordination of Patterning And Growth In the Spinal Cord
publication: Development
publication_identifier:
eissn:
- 1477-9129
issn:
- 0950-1991
publication_status: published
publisher: The Company of Biologists
quality_controlled: '1'
scopus_import: '1'
status: public
title: Neuronal differentiation influences progenitor arrangement in the vertebrate
neuroepithelium
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 146
year: '2019'
...
---
_id: '37'
abstract:
- lang: eng
text: Developmental processes are inherently dynamic and understanding them requires
quantitative measurements of gene and protein expression levels in space and time.
While live imaging is a powerful approach for obtaining such data, it is still
a challenge to apply it over long periods of time to large tissues, such as the
embryonic spinal cord in mouse and chick. Nevertheless, dynamics of gene expression
and signaling activity patterns in this organ can be studied by collecting tissue
sections at different developmental stages. In combination with immunohistochemistry,
this allows for measuring the levels of multiple developmental regulators in a
quantitative manner with high spatiotemporal resolution. The mean protein expression
levels over time, as well as embryo-to-embryo variability can be analyzed. A key
aspect of the approach is the ability to compare protein levels across different
samples. This requires a number of considerations in sample preparation, imaging
and data analysis. Here we present a protocol for obtaining time course data of
dorsoventral expression patterns from mouse and chick neural tube in the first
3 days of neural tube development. The described workflow starts from embryo dissection
and ends with a processed dataset. Software scripts for data analysis are included.
The protocol is adaptable and instructions that allow the user to modify different
steps are provided. Thus, the procedure can be altered for analysis of time-lapse
images and applied to systems other than the neural tube.
alternative_title:
- Methods in Molecular Biology
article_processing_charge: No
author:
- first_name: Marcin P
full_name: Zagórski, Marcin P
id: 343DA0DC-F248-11E8-B48F-1D18A9856A87
last_name: Zagórski
orcid: 0000-0001-7896-7762
- first_name: Anna
full_name: Kicheva, Anna
id: 3959A2A0-F248-11E8-B48F-1D18A9856A87
last_name: Kicheva
orcid: 0000-0003-4509-4998
citation:
ama: 'Zagórski MP, Kicheva A. Measuring dorsoventral pattern and morphogen signaling
profiles in the growing neural tube. In: Morphogen Gradients . Vol 1863.
MIMB. Springer Nature; 2018:47-63. doi:10.1007/978-1-4939-8772-6_4'
apa: Zagórski, M. P., & Kicheva, A. (2018). Measuring dorsoventral pattern and
morphogen signaling profiles in the growing neural tube. In Morphogen Gradients
(Vol. 1863, pp. 47–63). Springer Nature. https://doi.org/10.1007/978-1-4939-8772-6_4
chicago: Zagórski, Marcin P, and Anna Kicheva. “Measuring Dorsoventral Pattern and
Morphogen Signaling Profiles in the Growing Neural Tube.” In Morphogen Gradients
, 1863:47–63. MIMB. Springer Nature, 2018. https://doi.org/10.1007/978-1-4939-8772-6_4.
ieee: M. P. Zagórski and A. Kicheva, “Measuring dorsoventral pattern and morphogen
signaling profiles in the growing neural tube,” in Morphogen Gradients ,
vol. 1863, Springer Nature, 2018, pp. 47–63.
ista: 'Zagórski MP, Kicheva A. 2018.Measuring dorsoventral pattern and morphogen
signaling profiles in the growing neural tube. In: Morphogen Gradients . Methods
in Molecular Biology, vol. 1863, 47–63.'
mla: Zagórski, Marcin P., and Anna Kicheva. “Measuring Dorsoventral Pattern and
Morphogen Signaling Profiles in the Growing Neural Tube.” Morphogen Gradients
, vol. 1863, Springer Nature, 2018, pp. 47–63, doi:10.1007/978-1-4939-8772-6_4.
short: M.P. Zagórski, A. Kicheva, in:, Morphogen Gradients , Springer Nature, 2018,
pp. 47–63.
date_created: 2018-12-11T11:44:17Z
date_published: 2018-10-16T00:00:00Z
date_updated: 2021-01-12T07:49:03Z
day: '16'
ddc:
- '570'
department:
- _id: AnKi
doi: 10.1007/978-1-4939-8772-6_4
ec_funded: 1
file:
- access_level: open_access
checksum: 2a97d0649fdcfcf1bdca7c8ad1dce71b
content_type: application/pdf
creator: dernst
date_created: 2020-10-13T14:20:37Z
date_updated: 2020-10-13T14:20:37Z
file_id: '8656'
file_name: 2018_MIMB_Zagorski.pdf
file_size: 4906815
relation: main_file
success: 1
file_date_updated: 2020-10-13T14:20:37Z
has_accepted_license: '1'
intvolume: ' 1863'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Submitted Version
page: 47 - 63
project:
- _id: B6FC0238-B512-11E9-945C-1524E6697425
call_identifier: H2020
grant_number: '680037'
name: Coordination of Patterning And Growth In the Spinal Cord
publication: 'Morphogen Gradients '
publication_identifier:
isbn:
- 978-1-4939-8771-9
issn:
- 1064-3745
publication_status: published
publisher: Springer Nature
publist_id: '8018'
quality_controlled: '1'
scopus_import: '1'
series_title: MIMB
status: public
title: Measuring dorsoventral pattern and morphogen signaling profiles in the growing
neural tube
type: book_chapter
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 1863
year: '2018'
...
---
_id: '822'
abstract:
- lang: eng
text: 'Polymicrobial infections constitute small ecosystems that accommodate several
bacterial species. Commonly, these bacteria are investigated in isolation. However,
it is unknown to what extent the isolates interact and whether their interactions
alter bacterial growth and ecosystem resilience in the presence and absence of
antibiotics. We quantified the complete ecological interaction network for 72
bacterial isolates collected from 23 individuals diagnosed with polymicrobial
urinary tract infections and found that most interactions cluster based on evolutionary
relatedness. Statistical network analysis revealed that competitive and cooperative
reciprocal interactions are enriched in the global network, while cooperative
interactions are depleted in the individual host community networks. A population
dynamics model parameterized by our measurements suggests that interactions restrict
community stability, explaining the observed species diversity of these communities.
We further show that the clinical isolates frequently protect each other from
clinically relevant antibiotics. Together, these results highlight that ecological
interactions are crucial for the growth and survival of bacteria in polymicrobial
infection communities and affect their assembly and resilience. '
article_processing_charge: No
author:
- first_name: Marjon
full_name: De Vos, Marjon
id: 3111FFAC-F248-11E8-B48F-1D18A9856A87
last_name: De Vos
- first_name: Marcin P
full_name: Zagórski, Marcin P
id: 343DA0DC-F248-11E8-B48F-1D18A9856A87
last_name: Zagórski
orcid: 0000-0001-7896-7762
- first_name: Alan
full_name: Mcnally, Alan
last_name: Mcnally
- first_name: Mark Tobias
full_name: Bollenbach, Mark Tobias
id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
last_name: Bollenbach
orcid: 0000-0003-4398-476X
citation:
ama: de Vos M, Zagórski MP, Mcnally A, Bollenbach MT. Interaction networks, ecological
stability, and collective antibiotic tolerance in polymicrobial infections. PNAS.
2017;114(40):10666-10671. doi:10.1073/pnas.1713372114
apa: de Vos, M., Zagórski, M. P., Mcnally, A., & Bollenbach, M. T. (2017). Interaction
networks, ecological stability, and collective antibiotic tolerance in polymicrobial
infections. PNAS. National Academy of Sciences. https://doi.org/10.1073/pnas.1713372114
chicago: Vos, Marjon de, Marcin P Zagórski, Alan Mcnally, and Mark Tobias Bollenbach.
“Interaction Networks, Ecological Stability, and Collective Antibiotic Tolerance
in Polymicrobial Infections.” PNAS. National Academy of Sciences, 2017.
https://doi.org/10.1073/pnas.1713372114.
ieee: M. de Vos, M. P. Zagórski, A. Mcnally, and M. T. Bollenbach, “Interaction
networks, ecological stability, and collective antibiotic tolerance in polymicrobial
infections,” PNAS, vol. 114, no. 40. National Academy of Sciences, pp.
10666–10671, 2017.
ista: de Vos M, Zagórski MP, Mcnally A, Bollenbach MT. 2017. Interaction networks,
ecological stability, and collective antibiotic tolerance in polymicrobial infections.
PNAS. 114(40), 10666–10671.
mla: de Vos, Marjon, et al. “Interaction Networks, Ecological Stability, and Collective
Antibiotic Tolerance in Polymicrobial Infections.” PNAS, vol. 114, no.
40, National Academy of Sciences, 2017, pp. 10666–71, doi:10.1073/pnas.1713372114.
short: M. de Vos, M.P. Zagórski, A. Mcnally, M.T. Bollenbach, PNAS 114 (2017) 10666–10671.
date_created: 2018-12-11T11:48:41Z
date_published: 2017-10-03T00:00:00Z
date_updated: 2023-09-26T16:18:48Z
day: '03'
department:
- _id: ToBo
doi: 10.1073/pnas.1713372114
ec_funded: 1
external_id:
isi:
- '000412130500061'
pmid:
- '28923953'
intvolume: ' 114'
isi: 1
issue: '40'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635929/
month: '10'
oa: 1
oa_version: Submitted Version
page: 10666 - 10671
pmid: 1
project:
- _id: 25E83C2C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '303507'
name: Optimality principles in responses to antibiotics
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P27201-B22
name: Revealing the mechanisms underlying drug interactions
publication: PNAS
publication_identifier:
issn:
- '00278424'
publication_status: published
publisher: National Academy of Sciences
publist_id: '6827'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Interaction networks, ecological stability, and collective antibiotic tolerance
in polymicrobial infections
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 114
year: '2017'
...
---
_id: '943'
abstract:
- lang: eng
text: Like many developing tissues, the vertebrate neural tube is patterned by antiparallel
morphogen gradients. To understand how these inputs are interpreted, we measured
morphogen signaling and target gene expression in mouse embryos and chick ex vivo
assays. From these data, we derived and validated a characteristic decoding map
that relates morphogen input to the positional identity of neural progenitors.
Analysis of the observed responses indicates that the underlying interpretation
strategy minimizes patterning errors in response to the joint input of noisy opposing
gradients. We reverse-engineered a transcriptional network that provides a mechanistic
basis for the observed cell fate decisions and accounts for the precision and
dynamics of pattern formation. Together, our data link opposing gradient dynamics
in a growing tissue to precise pattern formation.
article_processing_charge: No
author:
- first_name: Marcin P
full_name: Zagórski, Marcin P
id: 343DA0DC-F248-11E8-B48F-1D18A9856A87
last_name: Zagórski
orcid: 0000-0001-7896-7762
- first_name: Yoji
full_name: Tabata, Yoji
last_name: Tabata
- first_name: Nathalie
full_name: Brandenberg, Nathalie
last_name: Brandenberg
- first_name: Matthias
full_name: Lutolf, Matthias
last_name: Lutolf
- first_name: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- first_name: Tobias
full_name: Bollenbach, Tobias
last_name: Bollenbach
- first_name: James
full_name: Briscoe, James
last_name: Briscoe
- first_name: Anna
full_name: Kicheva, Anna
id: 3959A2A0-F248-11E8-B48F-1D18A9856A87
last_name: Kicheva
orcid: 0000-0003-4509-4998
citation:
ama: Zagórski MP, Tabata Y, Brandenberg N, et al. Decoding of position in the developing
neural tube from antiparallel morphogen gradients. Science. 2017;356(6345):1379-1383.
doi:10.1126/science.aam5887
apa: Zagórski, M. P., Tabata, Y., Brandenberg, N., Lutolf, M., Tkačik, G., Bollenbach,
T., … Kicheva, A. (2017). Decoding of position in the developing neural tube from
antiparallel morphogen gradients. Science. American Association for the
Advancement of Science. https://doi.org/10.1126/science.aam5887
chicago: Zagórski, Marcin P, Yoji Tabata, Nathalie Brandenberg, Matthias Lutolf,
Gašper Tkačik, Tobias Bollenbach, James Briscoe, and Anna Kicheva. “Decoding of
Position in the Developing Neural Tube from Antiparallel Morphogen Gradients.”
Science. American Association for the Advancement of Science, 2017. https://doi.org/10.1126/science.aam5887.
ieee: M. P. Zagórski et al., “Decoding of position in the developing neural
tube from antiparallel morphogen gradients,” Science, vol. 356, no. 6345.
American Association for the Advancement of Science, pp. 1379–1383, 2017.
ista: Zagórski MP, Tabata Y, Brandenberg N, Lutolf M, Tkačik G, Bollenbach T, Briscoe
J, Kicheva A. 2017. Decoding of position in the developing neural tube from antiparallel
morphogen gradients. Science. 356(6345), 1379–1383.
mla: Zagórski, Marcin P., et al. “Decoding of Position in the Developing Neural
Tube from Antiparallel Morphogen Gradients.” Science, vol. 356, no. 6345,
American Association for the Advancement of Science, 2017, pp. 1379–83, doi:10.1126/science.aam5887.
short: M.P. Zagórski, Y. Tabata, N. Brandenberg, M. Lutolf, G. Tkačik, T. Bollenbach,
J. Briscoe, A. Kicheva, Science 356 (2017) 1379–1383.
date_created: 2018-12-11T11:49:20Z
date_published: 2017-06-30T00:00:00Z
date_updated: 2023-09-26T15:38:05Z
day: '30'
department:
- _id: AnKi
- _id: GaTk
doi: 10.1126/science.aam5887
ec_funded: 1
external_id:
isi:
- '000404351500036'
pmid:
- '28663499'
intvolume: ' 356'
isi: 1
issue: '6345'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5568706/
month: '06'
oa: 1
oa_version: Submitted Version
page: 1379 - 1383
pmid: 1
project:
- _id: 254E9036-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P28844-B27
name: Biophysics of information processing in gene regulation
- _id: B6FC0238-B512-11E9-945C-1524E6697425
call_identifier: H2020
grant_number: '680037'
name: Coordination of Patterning And Growth In the Spinal Cord
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
- _id: 2524F500-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '201439'
name: Developing High-Throughput Bioassays for Human Cancers in Zebrafish
publication: Science
publication_identifier:
issn:
- '00368075'
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '6474'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Decoding of position in the developing neural tube from antiparallel morphogen
gradients
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 356
year: '2017'
...
---
_id: '1167'
abstract:
- lang: eng
text: Evolutionary pathways describe trajectories of biological evolution in the
space of different variants of organisms (genotypes). The probability of existence
and the number of evolutionary pathways that lead from a given genotype to a better-adapted
genotype are important measures of accessibility of local fitness optima and the
reproducibility of evolution. Both quantities have been studied in simple mathematical
models where genotypes are represented as binary sequences of two types of basic
units, and the network of permitted mutations between the genotypes is a hypercube
graph. However, it is unclear how these results translate to the biologically
relevant case in which genotypes are represented by sequences of more than two
units, for example four nucleotides (DNA) or 20 amino acids (proteins), and the
mutational graph is not the hypercube. Here we investigate accessibility of the
best-adapted genotype in the general case of K > 2 units. Using computer generated
and experimental fitness landscapes we show that accessibility of the global fitness
maximum increases with K and can be much higher than for binary sequences. The
increase in accessibility comes from the increase in the number of indirect trajectories
exploited by evolution for higher K. As one of the consequences, the fraction
of genotypes that are accessible increases by three orders of magnitude when the
number of units K increases from 2 to 16 for landscapes of size N ∼ 106genotypes.
This suggests that evolution can follow many different trajectories on such landscapes
and the reconstruction of evolutionary pathways from experimental data might be
an extremely difficult task.
acknowledgement: MZ acknowledges the Polish National Science Centre grant no. DEC-2012/07/N/NZ2/00107.
BW was supported by the Scottish Government/Royal Society of Edinburgh Personal
Research Fellowship. We thank Marjon de Vos and Oliver Martin for critically reading
the manuscript.
article_number: e1005218
article_processing_charge: No
author:
- first_name: Marcin P
full_name: Zagórski, Marcin P
id: 343DA0DC-F248-11E8-B48F-1D18A9856A87
last_name: Zagórski
orcid: 0000-0001-7896-7762
- first_name: Zdzisław
full_name: Burda, Zdzisław
last_name: Burda
- first_name: Bartłomiej
full_name: Wacław, Bartłomiej
last_name: Wacław
citation:
ama: Zagórski MP, Burda Z, Wacław B. Beyond the hypercube evolutionary accessibility
of fitness landscapes with realistic mutational networks. PLoS Computational
Biology. 2016;12(12). doi:10.1371/journal.pcbi.1005218
apa: Zagórski, M. P., Burda, Z., & Wacław, B. (2016). Beyond the hypercube evolutionary
accessibility of fitness landscapes with realistic mutational networks. PLoS
Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005218
chicago: Zagórski, Marcin P, Zdzisław Burda, and Bartłomiej Wacław. “Beyond the
Hypercube Evolutionary Accessibility of Fitness Landscapes with Realistic Mutational
Networks.” PLoS Computational Biology. Public Library of Science, 2016.
https://doi.org/10.1371/journal.pcbi.1005218.
ieee: M. P. Zagórski, Z. Burda, and B. Wacław, “Beyond the hypercube evolutionary
accessibility of fitness landscapes with realistic mutational networks,” PLoS
Computational Biology, vol. 12, no. 12. Public Library of Science, 2016.
ista: Zagórski MP, Burda Z, Wacław B. 2016. Beyond the hypercube evolutionary accessibility
of fitness landscapes with realistic mutational networks. PLoS Computational Biology.
12(12), e1005218.
mla: Zagórski, Marcin P., et al. “Beyond the Hypercube Evolutionary Accessibility
of Fitness Landscapes with Realistic Mutational Networks.” PLoS Computational
Biology, vol. 12, no. 12, e1005218, Public Library of Science, 2016, doi:10.1371/journal.pcbi.1005218.
short: M.P. Zagórski, Z. Burda, B. Wacław, PLoS Computational Biology 12 (2016).
date_created: 2018-12-11T11:50:30Z
date_published: 2016-12-09T00:00:00Z
date_updated: 2023-02-23T14:11:22Z
day: '09'
ddc:
- '570'
department:
- _id: AnKi
doi: 10.1371/journal.pcbi.1005218
file:
- access_level: open_access
checksum: 84f44ae92866c52ff1ca8a574558dca7
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:12:08Z
date_updated: 2020-07-14T12:44:37Z
file_id: '4926'
file_name: IST-2017-740-v1+1_journal.pcbi.1005218.pdf
file_size: 3822299
relation: main_file
file_date_updated: 2020-07-14T12:44:37Z
has_accepted_license: '1'
intvolume: ' 12'
issue: '12'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
publication: PLoS Computational Biology
publication_status: published
publisher: Public Library of Science
publist_id: '6190'
pubrep_id: '740'
quality_controlled: '1'
related_material:
record:
- id: '9866'
relation: research_data
status: public
scopus_import: '1'
status: public
title: Beyond the hypercube evolutionary accessibility of fitness landscapes with
realistic mutational networks
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: 6785fbc1-c503-11eb-8a32-93094b40e1cf
volume: 12
year: '2016'
...
---
_id: '1371'
abstract:
- lang: eng
text: Living cells can maintain their internal states, react to changing environments,
grow, differentiate, divide, etc. All these processes are tightly controlled by
what can be called a regulatory program. The logic of the underlying control can
sometimes be guessed at by examining the network of influences amongst genetic
components. Some associated gene regulatory networks have been studied in prokaryotes
and eukaryotes, unveiling various structural features ranging from broad distributions
of out-degrees to recurrent "motifs", that is small subgraphs having
a specific pattern of interactions. To understand what factors may be driving
such structuring, a number of groups have introduced frameworks to model the dynamics
of gene regulatory networks. In that context, we review here such in silico approaches
and show how selection for phenotypes, i.e., network function, can shape network
structure.
acknowledgement: 'MZ has been supported by Polish National Science Centre Grant No.
DEC-2012/07/N/NZ2/00107 and by Foundation of Polish Science award START. '
author:
- first_name: Olivier
full_name: Martin, Olivier
last_name: Martin
- first_name: André
full_name: Krzywicki, André
last_name: Krzywicki
- first_name: Marcin P
full_name: Zagórski, Marcin P
id: 343DA0DC-F248-11E8-B48F-1D18A9856A87
last_name: Zagórski
orcid: 0000-0001-7896-7762
citation:
ama: 'Martin O, Krzywicki A, Zagórski MP. Drivers of structural features in gene
regulatory networks: From biophysical constraints to biological function. Physics
of Life Reviews. 2016;17:124-158. doi:10.1016/j.plrev.2016.06.002'
apa: 'Martin, O., Krzywicki, A., & Zagórski, M. P. (2016). Drivers of structural
features in gene regulatory networks: From biophysical constraints to biological
function. Physics of Life Reviews. Elsevier. https://doi.org/10.1016/j.plrev.2016.06.002'
chicago: 'Martin, Olivier, André Krzywicki, and Marcin P Zagórski. “Drivers of Structural
Features in Gene Regulatory Networks: From Biophysical Constraints to Biological
Function.” Physics of Life Reviews. Elsevier, 2016. https://doi.org/10.1016/j.plrev.2016.06.002.'
ieee: 'O. Martin, A. Krzywicki, and M. P. Zagórski, “Drivers of structural features
in gene regulatory networks: From biophysical constraints to biological function,”
Physics of Life Reviews, vol. 17. Elsevier, pp. 124–158, 2016.'
ista: 'Martin O, Krzywicki A, Zagórski MP. 2016. Drivers of structural features
in gene regulatory networks: From biophysical constraints to biological function.
Physics of Life Reviews. 17, 124–158.'
mla: 'Martin, Olivier, et al. “Drivers of Structural Features in Gene Regulatory
Networks: From Biophysical Constraints to Biological Function.” Physics of
Life Reviews, vol. 17, Elsevier, 2016, pp. 124–58, doi:10.1016/j.plrev.2016.06.002.'
short: O. Martin, A. Krzywicki, M.P. Zagórski, Physics of Life Reviews 17 (2016)
124–158.
date_created: 2018-12-11T11:51:38Z
date_published: 2016-07-01T00:00:00Z
date_updated: 2021-01-12T06:50:13Z
day: '01'
department:
- _id: AnKi
doi: 10.1016/j.plrev.2016.06.002
ec_funded: 1
intvolume: ' 17'
language:
- iso: eng
month: '07'
oa_version: None
page: 124 - 158
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Physics of Life Reviews
publication_status: published
publisher: Elsevier
publist_id: '5840'
quality_controlled: '1'
scopus_import: 1
status: public
title: 'Drivers of structural features in gene regulatory networks: From biophysical
constraints to biological function'
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 17
year: '2016'
...
---
_id: '1373'
article_processing_charge: No
author:
- first_name: Olivier
full_name: Martin, Olivier
last_name: Martin
- first_name: Marcin P
full_name: Zagórski, Marcin P
id: 343DA0DC-F248-11E8-B48F-1D18A9856A87
last_name: Zagórski
orcid: 0000-0001-7896-7762
citation:
ama: 'Martin O, Zagórski MP. Network architectures and operating principles. Reply
to comments on "Drivers of structural features in gene regulatory networks:
From biophysical constraints to biological function" Physics of Life
Reviews. 2016;17:168-171. doi:10.1016/j.plrev.2016.06.006'
apa: 'Martin, O., & Zagórski, M. P. (2016). Network architectures and operating
principles. Reply to comments on "Drivers of structural features in gene
regulatory networks: From biophysical constraints to biological function"
Physics of Life Reviews. Elsevier. https://doi.org/10.1016/j.plrev.2016.06.006'
chicago: 'Martin, Olivier, and Marcin P Zagórski. “Network Architectures and Operating
Principles. Reply to Comments on "Drivers of Structural Features in Gene
Regulatory Networks: From Biophysical Constraints to Biological Function"”
Physics of Life Reviews. Elsevier, 2016. https://doi.org/10.1016/j.plrev.2016.06.006.'
ieee: 'O. Martin and M. P. Zagórski, “Network architectures and operating principles.
Reply to comments on "Drivers of structural features in gene regulatory
networks: From biophysical constraints to biological function",” Physics
of Life Reviews, vol. 17. Elsevier, pp. 168–171, 2016.'
ista: 'Martin O, Zagórski MP. 2016. Network architectures and operating principles.
Reply to comments on "Drivers of structural features in gene regulatory
networks: From biophysical constraints to biological function" Physics
of Life Reviews. 17, 168–171.'
mla: 'Martin, Olivier, and Marcin P. Zagórski. “Network Architectures and Operating
Principles. Reply to Comments on "Drivers of Structural Features in Gene
Regulatory Networks: From Biophysical Constraints to Biological Function"”
Physics of Life Reviews, vol. 17, Elsevier, 2016, pp. 168–71, doi:10.1016/j.plrev.2016.06.006.'
short: O. Martin, M.P. Zagórski, Physics of Life Reviews 17 (2016) 168–171.
date_created: 2018-12-11T11:51:39Z
date_published: 2016-07-01T00:00:00Z
date_updated: 2022-08-26T09:39:27Z
day: '01'
department:
- _id: AnKi
doi: 10.1016/j.plrev.2016.06.006
intvolume: ' 17'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://hal.archives-ouvertes.fr/hal-01531698
month: '07'
oa: 1
oa_version: Preprint
page: 168 - 171
publication: Physics of Life Reviews
publication_status: published
publisher: Elsevier
publist_id: '5838'
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Network architectures and operating principles. Reply to comments on "Drivers
of structural features in gene regulatory networks: From biophysical constraints
to biological function"'
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 17
year: '2016'
...
---
_id: '9866'
article_processing_charge: No
author:
- first_name: Marcin P
full_name: Zagórski, Marcin P
id: 343DA0DC-F248-11E8-B48F-1D18A9856A87
last_name: Zagórski
orcid: 0000-0001-7896-7762
- first_name: Zdzisław
full_name: Burda, Zdzisław
last_name: Burda
- first_name: Bartłomiej
full_name: Wacław, Bartłomiej
last_name: Wacław
citation:
ama: Zagórski MP, Burda Z, Wacław B. ZIP-archived directory containing all data
and computer programs. 2016. doi:10.1371/journal.pcbi.1005218.s009
apa: Zagórski, M. P., Burda, Z., & Wacław, B. (2016). ZIP-archived directory
containing all data and computer programs. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1005218.s009
chicago: Zagórski, Marcin P, Zdzisław Burda, and Bartłomiej Wacław. “ZIP-Archived
Directory Containing All Data and Computer Programs.” Public Library of Science,
2016. https://doi.org/10.1371/journal.pcbi.1005218.s009.
ieee: M. P. Zagórski, Z. Burda, and B. Wacław, “ZIP-archived directory containing
all data and computer programs.” Public Library of Science, 2016.
ista: Zagórski MP, Burda Z, Wacław B. 2016. ZIP-archived directory containing all
data and computer programs, Public Library of Science, 10.1371/journal.pcbi.1005218.s009.
mla: Zagórski, Marcin P., et al. ZIP-Archived Directory Containing All Data and
Computer Programs. Public Library of Science, 2016, doi:10.1371/journal.pcbi.1005218.s009.
short: M.P. Zagórski, Z. Burda, B. Wacław, (2016).
date_created: 2021-08-10T08:37:20Z
date_published: 2016-12-09T00:00:00Z
date_updated: 2023-02-21T16:24:29Z
day: '09'
department:
- _id: AnKi
doi: 10.1371/journal.pcbi.1005218.s009
month: '12'
oa_version: Published Version
publisher: Public Library of Science
related_material:
record:
- id: '1167'
relation: used_in_publication
status: public
status: public
title: ZIP-archived directory containing all data and computer programs
type: research_data_reference
user_id: 6785fbc1-c503-11eb-8a32-93094b40e1cf
year: '2016'
...