Ivan Pogrebnyakov

Ivan Pogrebnyakov is a Researcher at the Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark (DTU), specializing in bacterial cell factories and metabolic engineering. His work contributes to several UN Sustainable Development Goals through sustainable bioproduction research.

Dr. Pogrebnyakov's research focuses on Metabolic Engineering, Genetic Engineering of Bacteria, and Bacterial Cell Factories. His expertise spans thermophilic bacteria, particularly Geobacillus species, and pathogenic bacteria like Pseudomonas aeruginosa. His fingerprint reveals significant contributions to Promoter Region studies (100%), Genetics (66%), Geobacillus research (50%), and Metabolic Engineering (41%).

His recent publications show a clear trajectory in bacterial engineering for sustainable production systems. The 2024 work on Pseudomonas aeruginosa demonstrates how metabolic specialization affects pathogenicity in cystic fibrosis patients, while his ribosomal mutation research reveals new antibiotic resistance mechanisms. His 2023 publications focus on developing genetic tools for thermophilic bacteria and chassis screening platforms that advance industrial biotechnology applications.

As a supervisor, Pogrebnyakov currently mentors PhD student (Escher), B. L. in the project "Metabolic engineering for production of volatile biochemicals" (2023-2026). Previously, he completed his own PhD research through two major projects: "Engineering of Thermophillic bacteria for the production of industrially relevant chemicals" (2013-2017) and "BacTory: Biorefinery Training Platform" (2012-2017), where he contributed to developing bacterial factories for sustainable chemical and drug production.

His laboratory work centers on the Bacterial Cell Factories research group at DTU Biosustain, where he develops genetic tools and engineering strategies for diverse bacterial hosts including Bacillus subtilis, Geobacillus species, and Pseudomonas strains. His research integrates adaptive laboratory evolution, genetic engineering, and metabolic modeling to create efficient microbial cell factories for industrial applications.