---
_id: '8997'
abstract:
- lang: eng
  text: Phenomenological relations such as Ohm’s or Fourier’s law have a venerable
    history in physics but are still scarce in biology. This situation restrains predictive
    theory. Here, we build on bacterial “growth laws,” which capture physiological
    feedback between translation and cell growth, to construct a minimal biophysical
    model for the combined action of ribosome-targeting antibiotics. Our model predicts
    drug interactions like antagonism or synergy solely from responses to individual
    drugs. We provide analytical results for limiting cases, which agree well with
    numerical results. We systematically refine the model by including direct physical
    interactions of different antibiotics on the ribosome. In a limiting case, our
    model provides a mechanistic underpinning for recent predictions of higher-order
    interactions that were derived using entropy maximization. We further refine the
    model to include the effects of antibiotics that mimic starvation and the presence
    of resistance genes. We describe the impact of a starvation-mimicking antibiotic
    on drug interactions analytically and verify it experimentally. Our extended model
    suggests a change in the type of drug interaction that depends on the strength
    of resistance, which challenges established rescaling paradigms. We experimentally
    show that the presence of unregulated resistance genes can lead to altered drug
    interaction, which agrees with the prediction of the model. While minimal, the
    model is readily adaptable and opens the door to predicting interactions of second
    and higher-order in a broad range of biological systems.
acknowledgement: 'This work was supported in part by Tum stipend of Knafelj foundation
  (to B.K.), Austrian Science Fund (FWF) standalone grants P 27201-B22 (to T.B.) and
  P 28844(to G.T.), HFSP program Grant RGP0042/2013 (to T.B.), German Research Foundation
  (DFG) individual grant BO 3502/2-1 (to T.B.), and German Research Foundation (DFG)
  Collaborative Research Centre (SFB) 1310 (to T.B.). '
article_number: e1008529
article_processing_charge: Yes
article_type: original
author:
- first_name: Bor
  full_name: Kavcic, Bor
  id: 350F91D2-F248-11E8-B48F-1D18A9856A87
  last_name: Kavcic
  orcid: 0000-0001-6041-254X
- first_name: Gašper
  full_name: Tkačik, Gašper
  id: 3D494DCA-F248-11E8-B48F-1D18A9856A87
  last_name: Tkačik
  orcid: 0000-0002-6699-1455
- first_name: Tobias
  full_name: Bollenbach, Tobias
  id: 3E6DB97A-F248-11E8-B48F-1D18A9856A87
  last_name: Bollenbach
  orcid: 0000-0003-4398-476X
citation:
  ama: Kavcic B, Tkačik G, Bollenbach MT. Minimal biophysical model of combined antibiotic
    action. <i>PLOS Computational Biology</i>. 2021;17. doi:<a href="https://doi.org/10.1371/journal.pcbi.1008529">10.1371/journal.pcbi.1008529</a>
  apa: Kavcic, B., Tkačik, G., &#38; Bollenbach, M. T. (2021). Minimal biophysical
    model of combined antibiotic action. <i>PLOS Computational Biology</i>. Public
    Library of Science. <a href="https://doi.org/10.1371/journal.pcbi.1008529">https://doi.org/10.1371/journal.pcbi.1008529</a>
  chicago: Kavcic, Bor, Gašper Tkačik, and Mark Tobias Bollenbach. “Minimal Biophysical
    Model of Combined Antibiotic Action.” <i>PLOS Computational Biology</i>. Public
    Library of Science, 2021. <a href="https://doi.org/10.1371/journal.pcbi.1008529">https://doi.org/10.1371/journal.pcbi.1008529</a>.
  ieee: B. Kavcic, G. Tkačik, and M. T. Bollenbach, “Minimal biophysical model of
    combined antibiotic action,” <i>PLOS Computational Biology</i>, vol. 17. Public
    Library of Science, 2021.
  ista: Kavcic B, Tkačik G, Bollenbach MT. 2021. Minimal biophysical model of combined
    antibiotic action. PLOS Computational Biology. 17, e1008529.
  mla: Kavcic, Bor, et al. “Minimal Biophysical Model of Combined Antibiotic Action.”
    <i>PLOS Computational Biology</i>, vol. 17, e1008529, Public Library of Science,
    2021, doi:<a href="https://doi.org/10.1371/journal.pcbi.1008529">10.1371/journal.pcbi.1008529</a>.
  short: B. Kavcic, G. Tkačik, M.T. Bollenbach, PLOS Computational Biology 17 (2021).
date_created: 2021-01-08T07:16:18Z
date_published: 2021-01-07T00:00:00Z
date_updated: 2024-02-21T12:41:41Z
day: '07'
ddc:
- '570'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1008529
external_id:
  isi:
  - '000608045000010'
file:
- access_level: open_access
  checksum: e29f2b42651bef8e034781de8781ffac
  content_type: application/pdf
  creator: dernst
  date_created: 2021-02-04T12:30:48Z
  date_updated: 2021-02-04T12:30:48Z
  file_id: '9092'
  file_name: 2021_PlosComBio_Kavcic.pdf
  file_size: 3690053
  relation: main_file
  success: 1
file_date_updated: 2021-02-04T12:30:48Z
has_accepted_license: '1'
intvolume: '        17'
isi: 1
keyword:
- Modelling and Simulation
- Genetics
- Molecular Biology
- Antibiotics
- Drug interactions
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
project:
- _id: 25E9AF9E-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: P27201-B22
  name: Revealing the mechanisms underlying drug interactions
- _id: 254E9036-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: P28844-B27
  name: Biophysics of information processing in gene regulation
publication: PLOS Computational Biology
publication_identifier:
  issn:
  - 1553-7358
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
  record:
  - id: '7673'
    relation: earlier_version
    status: public
  - id: '8930'
    relation: research_data
    status: public
status: public
title: Minimal biophysical model of combined antibiotic action
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 17
year: '2021'
...