---
_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'
...