ProSec - Bacterial protein secretion: from modeling and data analysis to application
Contacts: Prof. Dr. Michael Bott; Prof. Dr. Holger Gohlke
Background: Microbial production of proteins is a cornerstone of biotechnology, especially when chemical synthesis is not feasible. Efficient secretion of proteins into the culture medium is key to simplifying purification and reducing production costs. Corynebacterium glutamicum, a gram-positive bacterium widely used in industrial amino acid production, has also emerged as a promising host for protein secretion.
Aim: Building on over a decade of research and a high-throughput secretion platform developed at IBG-1, this project focuses on elucidating the role of the export initiation domain, a short amino acid sequence directly downstream of the signal peptide, for secretion efficiency.
Approach: The project combines automated library construction and high-throughput screening, structural bioinformatics, and machine learning to unravel the mechanistic role of the export initiation domain and to develop predictive tools for designing secretion-optimized proteins. Beyond C. glutamicum, the approach can be extended to other microbial workhorses such as Bacillus subtilis, providing broad impact for industrial biotechnology.
Candidates for this project should have:
- a strong background in molecular or structural biology, bioinformatics, or biotechnology
- if possible, experience with protein expression, bacterial secretion systems, and synthetic biology tools
- familiarity with sequence/structure-based modeling, machine learning, or simulation tools
- motivation to work across scales from atomistic modeling to cellular biotechnology
- interest in developing predictive tools for industrial protein production
This position offers the opportunity to work at the interface of microbial biotechnology, structural bioinformatics, and AI, contributing to mechanistic understanding and predictive design tools for protein secretion in industrially relevant microbes.