Computational Systems Biology Lab

by Aditi Jain

Dr Karthik Raman, an Associate Professor at IIT Madras and a core member of RBCDSAI, realized this issue as a major bottleneck hampering the commercialization of bioprocesses. He, together with Lavanya Raajaraam, his PhD student, decided to find a solution to this problem. As a microbe produces many metabolites so they thought one should work to optimize the production of metabolites so as to get a minimum quantity of at least two industrially important metabolites to make the bioprocess economically feasible. The research team has developed a new algorithm co-FSEOF (co-production using Flux Scanning based on Enforced Objective Flux) to solve this problem. This research study has been published in the international journal, Frontiers in Bioengineering and Biotechnology.

“Bioprocesses are often limited by feasibility and yield. Even after various strain improvements, a process might not be economically feasible. To overcome this issue, we can co-produce multiple metabolites in a single process. However, there is a lack of algorithms available for rational strain engineering for co-production,” says Dr Raman.

Read the full blog article at: https://rbcdsai.iitm.ac.in/blogs/it-takes-two-to-tango-making-bio-production-more-economical/

Original Paper: 

• L. Raajaraam and K. Raman, “A Computational Framework to Identify Metabolic Engineering Strategies for the Co-Production of Metabolites,” Frontiers in Bioengineering and Biotechnology, vol. 9, p. 1330, 2022.
  [bibtex]

  @article{Raajaraam2022Computational,
    title = {A {{Computational Framework}} to {{Identify Metabolic Engineering Strategies}} for the {{Co-Production}} of {{Metabolites}}},
    author = {Raajaraam, Lavanya and Raman, Karthik},
    year = {2022},
    journal = {Frontiers in Bioengineering and Biotechnology},
    volume = {9},
    pages = {1330},
    issn = {2296-4185},
    doi = {10.3389/fbioe.2021.779405},
    pmid = {35071202},
    abstract = {Microbial production of chemicals is a more sustainable alternative to traditional chemical processes. However, the shift to bioprocess is usually accompanied by a drop in economic feasibility. Co-production of more than one chemical can improve the economy of bioprocesses, enhance carbon utilization and also ensure better exploitation of resources. While a number of tools exist for in silico metabolic engineering, there is a dearth of computational tools that can co-optimize the production of multiple metabolites. In this work, we propose co-FSEOF (co-production using Flux Scanning based on Enforced Objective Flux), an algorithm designed to identify intervention strategies to co-optimize the production of a set of metabolites. Co-FSEOF can be used to identify all pairs of products that can be co-optimized with ease using a single intervention. Beyond this, it can also identify higher-order intervention strategies for a given set of metabolites. We have employed this tool on the genome-scale metabolic models of Escherichia coli and Saccharomyces cerevisiae, and identified intervention targets that can co-optimize the production of pairs of metabolites under both aerobic and anaerobic conditions. Anaerobic conditions were found to support the co-production of a higher number of metabolites when compared to aerobic conditions in both organisms. The proposed computational framework will enhance the ease of study of metabolite co-production and thereby aid the design of better bioprocesses.},
  }