Search anything and hit enter
  • Teams
  • Members
  • Projects
  • Events
  • Calls
  • Jobs
  • publications
  • Software
  • Tools
  • Network
  • Equipment

A little guide for advanced search:

  • Tip 1. You can use quotes "" to search for an exact expression.
    Example: "cell division"
  • Tip 2. You can use + symbol to restrict results containing all words.
    Example: +cell +stem
  • Tip 3. You can use + and - symbols to force inclusion or exclusion of specific words.
    Example: +cell -stem
e.g. searching for members in projects tagged cancer
Search for
Count
IN
OUT
Content 1
  • member
  • team
  • department
  • center
  • program_project
  • nrc
  • whocc
  • project
  • software
  • tool
  • patent
  • Administrative Staff
  • Assistant Professor
  • Associate Professor
  • Clinical Research Assistant
  • Clinician Researcher
  • Department Manager
  • Full Professor
  • Graduate Student
  • Honorary Professor
  • Lab assistant
  • Non-permanent Researcher
  • Permanent Researcher
  • Pharmacist
  • PhD Student
  • Physician
  • Post-doc
  • Project Manager
  • Research Associate
  • Research Engineer
  • Retired scientist
  • Technician
  • Undergraduate Student
  • Veterinary
  • Visiting Scientist
  • Deputy Director of Center
  • Deputy Director of Department
  • Deputy Director of National Reference Center
  • Deputy Head of Facility
  • Director of Center
  • Director of Department
  • Director of Institute
  • Director of National Reference Center
  • Group Leader
  • Head of Facility
  • Head of Operations
  • Head of Structure
  • Honorary President of the Departement
  • Labex Coordinator
Content 2
  • member
  • team
  • department
  • center
  • program_project
  • nrc
  • whocc
  • project
  • software
  • tool
  • patent
  • Administrative Staff
  • Assistant Professor
  • Associate Professor
  • Clinical Research Assistant
  • Clinician Researcher
  • Department Manager
  • Full Professor
  • Graduate Student
  • Honorary Professor
  • Lab assistant
  • Non-permanent Researcher
  • Permanent Researcher
  • Pharmacist
  • PhD Student
  • Physician
  • Post-doc
  • Project Manager
  • Research Associate
  • Research Engineer
  • Retired scientist
  • Technician
  • Undergraduate Student
  • Veterinary
  • Visiting Scientist
  • Deputy Director of Center
  • Deputy Director of Department
  • Deputy Director of National Reference Center
  • Deputy Head of Facility
  • Director of Center
  • Director of Department
  • Director of Institute
  • Director of National Reference Center
  • Group Leader
  • Head of Facility
  • Head of Operations
  • Head of Structure
  • Honorary President of the Departement
  • Labex Coordinator
Search
Go back
Scroll to top
Share
© Inria / Photo C. Morel
Quantitative biology: numbers and fluorescent cells. InBio team (Inria/Institut Pasteur)
Publication : BioRxiv

A model-based approach to characterize enzyme-mediated response to antibiotic treatments: going beyond the SIR classification

Scientific Fields
Diseases
Organisms
Applications
Technique

Published in BioRxiv - 17 Jul 2021

Andreani V, You L, Glaser P, Batt G

bioRxiv. 2021.07.16.452741

To design appropriate treatments, one must be able to characterize accurately the response of bacteria to antibiotics. When exposed to β-lactam treatments, bacteria can be resistant and/or tolerant, and populations can exhibit resilience. Disentangling these phenomena is challenging and no consolidated understanding has been proposed so far. Because these responses involve processes happening at several levels, including the molecular level (e.g. antibiotic degradation), the cell physiology level (filamentation) and the population level (release of β-lactamases into the environment), quantitative modelling approaches are needed. Here, we propose a model of bacterial response to β-lactam treatments that accounts for bacterial resistance, tolerance, and population resilience. Our model can be calibrated solely based on optical density readouts, can predict the inoculum effect, and leads to a mechanistically relevant classification of bacterial response to treatments that goes beyond the classical susceptible / intermediate / resistant classification. Filamentation-mediated tolerance and collective enzyme-mediated antibiotic degradation are essential model features to explain the complex observed response of cell populations to antibiotic treatments.