---
_id: '1320'
abstract:
- lang: eng
text: 'In recent years, several biomolecular systems have been shown to be scale-invariant
(SI), i.e. to show the same output dynamics when exposed to geometrically scaled
input signals (u → pu, p > 0) after pre-adaptation to accordingly scaled constant
inputs. In this article, we show that SI systems-as well as systems invariant
with respect to other input transformations-can realize nonlinear differential
operators: when excited by inputs obeying functional forms characteristic for
a given class of invariant systems, the systems'' outputs converge to constant
values directly quantifying the speed of the input.'
acknowledgement: 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° [291734]. Work supported
in part by grants AFOSR FA9550-14-1-0060 and NIH 1R01GM100473.
article_number: '7526722'
author:
- first_name: Moritz
full_name: Lang, Moritz
id: 29E0800A-F248-11E8-B48F-1D18A9856A87
last_name: Lang
- first_name: Eduardo
full_name: Sontag, Eduardo
last_name: Sontag
citation:
ama: 'Lang M, Sontag E. Scale-invariant systems realize nonlinear differential operators.
In: Vol 2016-July. IEEE; 2016. doi:10.1109/ACC.2016.7526722'
apa: 'Lang, M., & Sontag, E. (2016). Scale-invariant systems realize nonlinear
differential operators (Vol. 2016–July). Presented at the ACC: American Control
Conference, Boston, MA, USA: IEEE. https://doi.org/10.1109/ACC.2016.7526722'
chicago: Lang, Moritz, and Eduardo Sontag. “Scale-Invariant Systems Realize Nonlinear
Differential Operators,” Vol. 2016–July. IEEE, 2016. https://doi.org/10.1109/ACC.2016.7526722.
ieee: 'M. Lang and E. Sontag, “Scale-invariant systems realize nonlinear differential
operators,” presented at the ACC: American Control Conference, Boston, MA, USA,
2016, vol. 2016–July.'
ista: 'Lang M, Sontag E. 2016. Scale-invariant systems realize nonlinear differential
operators. ACC: American Control Conference vol. 2016–July, 7526722.'
mla: Lang, Moritz, and Eduardo Sontag. Scale-Invariant Systems Realize Nonlinear
Differential Operators. Vol. 2016–July, 7526722, IEEE, 2016, doi:10.1109/ACC.2016.7526722.
short: M. Lang, E. Sontag, in:, IEEE, 2016.
conference:
end_date: 2016-07-08
location: Boston, MA, USA
name: 'ACC: American Control Conference'
start_date: 2016-07-06
date_created: 2018-12-11T11:51:21Z
date_published: 2016-07-28T00:00:00Z
date_updated: 2021-01-12T06:49:51Z
day: '28'
ddc:
- '003'
- '621'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1109/ACC.2016.7526722
ec_funded: 1
file:
- access_level: local
checksum: 7219432b43defc62a0d45f48d4ce6a19
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:16:17Z
date_updated: 2020-07-14T12:44:43Z
file_id: '5203'
file_name: IST-2017-810-v1+1_root.pdf
file_size: 539166
relation: main_file
file_date_updated: 2020-07-14T12:44:43Z
has_accepted_license: '1'
language:
- iso: eng
month: '07'
oa_version: Preprint
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication_status: published
publisher: IEEE
publist_id: '5950'
pubrep_id: '810'
quality_controlled: '1'
scopus_import: 1
status: public
title: Scale-invariant systems realize nonlinear differential operators
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 2016-July
year: '2016'
...
---
_id: '1332'
abstract:
- lang: eng
text: Antibiotic-sensitive and -resistant bacteria coexist in natural environments
with low, if detectable, antibiotic concentrations. Except possibly around localized
antibiotic sources, where resistance can provide a strong advantage, bacterial
fitness is dominated by stresses unaffected by resistance to the antibiotic. How
do such mixed and heterogeneous conditions influence the selective advantage or
disadvantage of antibiotic resistance? Here we find that sub-inhibitory levels
of tetracyclines potentiate selection for or against tetracycline resistance around
localized sources of almost any toxin or stress. Furthermore, certain stresses
generate alternating rings of selection for and against resistance around a localized
source of the antibiotic. In these conditions, localized antibiotic sources, even
at high strengths, can actually produce a net selection against resistance to
the antibiotic. Our results show that interactions between the effects of an antibiotic
and other stresses in inhomogeneous environments can generate pervasive, complex
patterns of selection both for and against antibiotic resistance.
acknowledgement: This work was partially supported by US National Institutes of Health
grant R01-GM081617, Israeli Centers of Research Excellence I-CORE Program ISF Grant
No. 152/11, and the European Research Council FP7 ERC Grant 281891.
article_number: '10333'
author:
- first_name: Remy P
full_name: Chait, Remy P
id: 3464AE84-F248-11E8-B48F-1D18A9856A87
last_name: Chait
orcid: 0000-0003-0876-3187
- first_name: Adam
full_name: Palmer, Adam
last_name: Palmer
- first_name: Idan
full_name: Yelin, Idan
last_name: Yelin
- first_name: Roy
full_name: Kishony, Roy
last_name: Kishony
citation:
ama: Chait RP, Palmer A, Yelin I, Kishony R. Pervasive selection for and against
antibiotic resistance in inhomogeneous multistress environments. Nature Communications.
2016;7. doi:10.1038/ncomms10333
apa: Chait, R. P., Palmer, A., Yelin, I., & Kishony, R. (2016). Pervasive selection
for and against antibiotic resistance in inhomogeneous multistress environments.
Nature Communications. Nature Publishing Group. https://doi.org/10.1038/ncomms10333
chicago: Chait, Remy P, Adam Palmer, Idan Yelin, and Roy Kishony. “Pervasive Selection
for and against Antibiotic Resistance in Inhomogeneous Multistress Environments.”
Nature Communications. Nature Publishing Group, 2016. https://doi.org/10.1038/ncomms10333.
ieee: R. P. Chait, A. Palmer, I. Yelin, and R. Kishony, “Pervasive selection for
and against antibiotic resistance in inhomogeneous multistress environments,”
Nature Communications, vol. 7. Nature Publishing Group, 2016.
ista: Chait RP, Palmer A, Yelin I, Kishony R. 2016. Pervasive selection for and
against antibiotic resistance in inhomogeneous multistress environments. Nature
Communications. 7, 10333.
mla: Chait, Remy P., et al. “Pervasive Selection for and against Antibiotic Resistance
in Inhomogeneous Multistress Environments.” Nature Communications, vol.
7, 10333, Nature Publishing Group, 2016, doi:10.1038/ncomms10333.
short: R.P. Chait, A. Palmer, I. Yelin, R. Kishony, Nature Communications 7 (2016).
date_created: 2018-12-11T11:51:25Z
date_published: 2016-01-20T00:00:00Z
date_updated: 2021-01-12T06:49:57Z
day: '20'
ddc:
- '570'
- '579'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1038/ncomms10333
file:
- access_level: open_access
checksum: ef147bcbb8bd37e9079cf3ce06f5815d
content_type: application/pdf
creator: system
date_created: 2018-12-12T10:13:52Z
date_updated: 2020-07-14T12:44:44Z
file_id: '5039'
file_name: IST-2016-662-v1+1_ncomms10333.pdf
file_size: 1844107
relation: main_file
file_date_updated: 2020-07-14T12:44:44Z
has_accepted_license: '1'
intvolume: ' 7'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
publication: Nature Communications
publication_status: published
publisher: Nature Publishing Group
publist_id: '5936'
pubrep_id: '662'
quality_controlled: '1'
scopus_import: 1
status: public
title: Pervasive selection for and against antibiotic resistance in inhomogeneous
multistress environments
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 7
year: '2016'
...
---
_id: '1342'
abstract:
- lang: eng
text: A key aspect of bacterial survival is the ability to evolve while migrating
across spatially varying environmental challenges. Laboratory experiments, however,
often study evolution in well-mixed systems. Here, we introduce an experimental
device, the microbial evolution and growth arena (MEGA)-plate, in which bacteria
spread and evolved on a large antibiotic landscape (120 × 60 centimeters) that
allowed visual observation of mutation and selection in a migrating bacterial
front.While resistance increased consistently, multiple coexisting lineages diversified
both phenotypically and genotypically. Analyzing mutants at and behind the propagating
front,we found that evolution is not always led by the most resistant mutants;
highly resistant mutants may be trapped behindmore sensitive lineages.TheMEGA-plate
provides a versatile platformfor studying microbial adaption and directly visualizing
evolutionary dynamics.
author:
- first_name: Michael
full_name: Baym, Michael
last_name: Baym
- first_name: Tami
full_name: Lieberman, Tami
last_name: Lieberman
- first_name: Eric
full_name: Kelsic, Eric
last_name: Kelsic
- 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: Rotem
full_name: Gross, Rotem
last_name: Gross
- first_name: Idan
full_name: Yelin, Idan
last_name: Yelin
- first_name: Roy
full_name: Kishony, Roy
last_name: Kishony
citation:
ama: Baym M, Lieberman T, Kelsic E, et al. Spatiotemporal microbial evolution on
antibiotic landscapes. Science. 2016;353(6304):1147-1151. doi:10.1126/science.aag0822
apa: Baym, M., Lieberman, T., Kelsic, E., Chait, R. P., Gross, R., Yelin, I., &
Kishony, R. (2016). Spatiotemporal microbial evolution on antibiotic landscapes.
Science. American Association for the Advancement of Science. https://doi.org/10.1126/science.aag0822
chicago: Baym, Michael, Tami Lieberman, Eric Kelsic, Remy P Chait, Rotem Gross,
Idan Yelin, and Roy Kishony. “Spatiotemporal Microbial Evolution on Antibiotic
Landscapes.” Science. American Association for the Advancement of Science,
2016. https://doi.org/10.1126/science.aag0822.
ieee: M. Baym et al., “Spatiotemporal microbial evolution on antibiotic landscapes,”
Science, vol. 353, no. 6304. American Association for the Advancement of
Science, pp. 1147–1151, 2016.
ista: Baym M, Lieberman T, Kelsic E, Chait RP, Gross R, Yelin I, Kishony R. 2016.
Spatiotemporal microbial evolution on antibiotic landscapes. Science. 353(6304),
1147–1151.
mla: Baym, Michael, et al. “Spatiotemporal Microbial Evolution on Antibiotic Landscapes.”
Science, vol. 353, no. 6304, American Association for the Advancement of
Science, 2016, pp. 1147–51, doi:10.1126/science.aag0822.
short: M. Baym, T. Lieberman, E. Kelsic, R.P. Chait, R. Gross, I. Yelin, R. Kishony,
Science 353 (2016) 1147–1151.
date_created: 2018-12-11T11:51:29Z
date_published: 2016-09-09T00:00:00Z
date_updated: 2021-01-12T06:50:01Z
day: '09'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1126/science.aag0822
intvolume: ' 353'
issue: '6304'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5534434/
month: '09'
oa: 1
oa_version: Preprint
page: 1147 - 1151
publication: Science
publication_status: published
publisher: American Association for the Advancement of Science
publist_id: '5911'
quality_controlled: '1'
scopus_import: 1
status: public
title: Spatiotemporal microbial evolution on antibiotic landscapes
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 353
year: '2016'
...
---
_id: '1394'
abstract:
- lang: eng
text: "The solution space of genome-scale models of cellular metabolism provides
a map between physically\r\nviable flux configurations and cellular metabolic
phenotypes described, at the most basic level, by the\r\ncorresponding growth
rates. By sampling the solution space of E. coliʼs metabolic network, we show\r\nthat
empirical growth rate distributions recently obtained in experiments at single-cell
resolution can\r\nbe explained in terms of a trade-off between the higher fitness
of fast-growing phenotypes and the\r\nhigher entropy of slow-growing ones. Based
on this, we propose a minimal model for the evolution of\r\na large bacterial
population that captures this trade-off. The scaling relationships observed in\r\nexperiments
encode, in such frameworks, for the same distance from the maximum achievable
growth\r\nrate, the same degree of growth rate maximization, and/or the same rate
of phenotypic change. Being\r\ngrounded on genome-scale metabolic network reconstructions,
these results allow for multiple\r\nimplications and extensions in spite of the
underlying conceptual simplicity."
acknowledgement: "The research leading to these results has received funding from
the from the Marie\r\nCurie Action ITN NETADIS, grant agreement no. 290038."
article_number: '036005'
author:
- first_name: Daniele
full_name: De Martino, Daniele
id: 3FF5848A-F248-11E8-B48F-1D18A9856A87
last_name: De Martino
orcid: 0000-0002-5214-4706
- first_name: Fabrizio
full_name: Capuani, Fabrizio
last_name: Capuani
- first_name: Andrea
full_name: De Martino, Andrea
last_name: De Martino
citation:
ama: 'De Martino D, Capuani F, De Martino A. Growth against entropy in bacterial
metabolism: the phenotypic trade-off behind empirical growth rate distributions
in E. coli. Physical Biology. 2016;13(3). doi:10.1088/1478-3975/13/3/036005'
apa: 'De Martino, D., Capuani, F., & De Martino, A. (2016). Growth against entropy
in bacterial metabolism: the phenotypic trade-off behind empirical growth rate
distributions in E. coli. Physical Biology. IOP Publishing Ltd. https://doi.org/10.1088/1478-3975/13/3/036005'
chicago: 'De Martino, Daniele, Fabrizio Capuani, and Andrea De Martino. “Growth
against Entropy in Bacterial Metabolism: The Phenotypic Trade-off behind Empirical
Growth Rate Distributions in E. Coli.” Physical Biology. IOP Publishing
Ltd., 2016. https://doi.org/10.1088/1478-3975/13/3/036005.'
ieee: 'D. De Martino, F. Capuani, and A. De Martino, “Growth against entropy in
bacterial metabolism: the phenotypic trade-off behind empirical growth rate distributions
in E. coli,” Physical Biology, vol. 13, no. 3. IOP Publishing Ltd., 2016.'
ista: 'De Martino D, Capuani F, De Martino A. 2016. Growth against entropy in bacterial
metabolism: the phenotypic trade-off behind empirical growth rate distributions
in E. coli. Physical Biology. 13(3), 036005.'
mla: 'De Martino, Daniele, et al. “Growth against Entropy in Bacterial Metabolism:
The Phenotypic Trade-off behind Empirical Growth Rate Distributions in E. Coli.”
Physical Biology, vol. 13, no. 3, 036005, IOP Publishing Ltd., 2016, doi:10.1088/1478-3975/13/3/036005.'
short: D. De Martino, F. Capuani, A. De Martino, Physical Biology 13 (2016).
date_created: 2018-12-11T11:51:46Z
date_published: 2016-05-27T00:00:00Z
date_updated: 2021-01-12T06:50:23Z
day: '27'
department:
- _id: GaTk
doi: 10.1088/1478-3975/13/3/036005
ec_funded: 1
intvolume: ' 13'
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1601.03243
month: '05'
oa: 1
oa_version: Preprint
project:
- _id: 25681D80-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '291734'
name: International IST Postdoc Fellowship Programme
publication: Physical Biology
publication_status: published
publisher: IOP Publishing Ltd.
publist_id: '5815'
quality_controlled: '1'
scopus_import: 1
status: public
title: 'Growth against entropy in bacterial metabolism: the phenotypic trade-off behind
empirical growth rate distributions in E. coli'
type: journal_article
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 13
year: '2016'
...
---
_id: '1420'
abstract:
- lang: eng
text: 'Selection, mutation, and random drift affect the dynamics of allele frequencies
and consequently of quantitative traits. While the macroscopic dynamics of quantitative
traits can be measured, the underlying allele frequencies are typically unobserved.
Can we understand how the macroscopic observables evolve without following these
microscopic processes? This problem has been studied previously by analogy with
statistical mechanics: the allele frequency distribution at each time point is
approximated by the stationary form, which maximizes entropy. We explore the limitations
of this method when mutation is small (4Nμ < 1) so that populations are typically
close to fixation, and we extend the theory in this regime to account for changes
in mutation strength. We consider a single diallelic locus either under directional
selection or with overdominance and then generalize to multiple unlinked biallelic
loci with unequal effects. We find that the maximum-entropy approximation is remarkably
accurate, even when mutation and selection change rapidly. '
article_processing_charge: No
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: Gasper
full_name: Tkacik, Gasper
id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
last_name: Tkacik
orcid: 0000-0002-6699-1455
- 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, Tkačik G, Barton NH. A general approximation for the dynamics of
quantitative traits. Genetics. 2016;202(4):1523-1548. doi:10.1534/genetics.115.184127
apa: Bodova, K., Tkačik, G., & Barton, N. H. (2016). A general approximation
for the dynamics of quantitative traits. Genetics. Genetics Society of
America. https://doi.org/10.1534/genetics.115.184127
chicago: Bodova, Katarina, Gašper Tkačik, and Nicholas H Barton. “A General Approximation
for the Dynamics of Quantitative Traits.” Genetics. Genetics Society of
America, 2016. https://doi.org/10.1534/genetics.115.184127.
ieee: K. Bodova, G. Tkačik, and N. H. Barton, “A general approximation for the dynamics
of quantitative traits,” Genetics, vol. 202, no. 4. Genetics Society of
America, pp. 1523–1548, 2016.
ista: Bodova K, Tkačik G, Barton NH. 2016. A general approximation for the dynamics
of quantitative traits. Genetics. 202(4), 1523–1548.
mla: Bodova, Katarina, et al. “A General Approximation for the Dynamics of Quantitative
Traits.” Genetics, vol. 202, no. 4, Genetics Society of America, 2016,
pp. 1523–48, doi:10.1534/genetics.115.184127.
short: K. Bodova, G. Tkačik, N.H. Barton, Genetics 202 (2016) 1523–1548.
date_created: 2018-12-11T11:51:55Z
date_published: 2016-04-06T00:00:00Z
date_updated: 2022-08-01T10:49:55Z
day: '06'
department:
- _id: GaTk
- _id: NiBa
doi: 10.1534/genetics.115.184127
ec_funded: 1
external_id:
arxiv:
- '1510.08344'
intvolume: ' 202'
issue: '4'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: http://arxiv.org/abs/1510.08344
month: '04'
oa: 1
oa_version: Preprint
page: 1523 - 1548
project:
- _id: 25B07788-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '250152'
name: Limits to selection in biology and in evolutionary computation
- _id: 255008E4-B435-11E9-9278-68D0E5697425
grant_number: RGP0065/2012
name: Information processing and computation in fish groups
publication: Genetics
publication_status: published
publisher: Genetics Society of America
publist_id: '5787'
quality_controlled: '1'
scopus_import: '1'
status: public
title: A general approximation for the dynamics of quantitative traits
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 202
year: '2016'
...