M1/M2 internship: High-throughput Estimation of Protein Expression costs

il y a 5 jours

JouyenJosas, Île-de-France INRAE Temps plein
M1/M2 internship: High-throughput Estimation of Protein Expression costs

Réf ABG-134535

Stage master 2 / Ingénieur

Durée 6 mois

Salaire net mensuel 610

25/11/2025

INRAE

Lieu de travail

Jouy-en-Josas Ile-de-France France

Champs scientifiques

  • Biotechnologie
  • Biochimie

Mots clés

synthetic biology, protein expression, cellular burden

Établissement recruteur
Site web :

You will be welcomed into the Cellular Computing Team, located within the Systems Biology and Synthesis pole of the Micalis Institute, a joint research unit (UMR 1319) of INRAE (Jouy-en-Josas), AgroParisTech, and Université Paris-Saclay. The team specializes in theoretical and experimental methods aimed at expanding research in synthetic biology for various applications.

Description

A Master's research internship (M1/M2, 4 to 6 months) is available at the Micalis Institute (INRAE UMR1319), Jouy-en-Josas. The intern will participate in a project funded by the GS-LSH / LivingMachines Work interdisciplinary program at the University of Paris-Saclay.

Project Summary

When synthetic genetic circuits are installed inside living cells, they result in increased cellular growth burden. This causes many circuits to break due to negative selection pressure, especially when the engineered cells are grown for prolonged periods of time. Understanding the growth burden of protein expression is essential for optimizing synthetic circuits and metabolic pathways, as well as for predicting evolutionary dynamics of engineered biological systems. This project aims to build on a high-throughput method for measuring the expression burden of a library of protein-coding sequences. Our approach will combine a modular reporter system with pooled competitive assays and next-generation sequencing. The expression levels and fitness data will be used to estimate the expression cost of each barcoded sequence variant. Ultimately, this work will provide a useful framework for studying how protein sequence variation impacts cellular fitness and resource allocation, helping inform the design choices for low-burden sequences for synthetic biology and metabolic engineering.

We are looking for a highly motivated candidate, with experience in experimental microbiology and molecular biology. Although not required, background in computational modeling/bioinformatics will be an advantage. They should have strong communication skills and the willingness to work collaboratively with other members of the team.

The work will be carried out in the Cellular Computing team at Micalis Institute, in collaboration with the Synthetic Metabolism team at Genoscope (UMR 8030).

Profil

We are looking for a highly motivated candidate, with experience in experimental microbiology, molecular biology, and/or synthetic biology. Although not required, background in computational modeling/bioinformatics will be an advantage. They should have strong communication skills and the willingness to work collaboratively with other members of the team.

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