Computational Systems Biology Lab

by Aditi Jain

Dr Karthik Raman, an Associate Professor at IIT Madras and a core member of RBCDSAI, is a scientist whose interest lies in discerning the dynamics of microbial interactions to utilize them for biotechnological application. Recently, Dr Raman and a post-doctoral fellow in his group, Dr Maziya Ibrahim proposed a computational approach named CAMP(Co-culture/Community Analyses for Metabolite Production) which suggests how to bundle two or more bacteria together, forming a community that produces the desired products in maximum quantity. Given the significance of the work, it has been published in a prestigious international Computational and Structural Biotechnology Journal.

“ To understand compatibility and interactions based on growth between the members of a microbial community, we have introduced a computational analysis framework that evaluates all possible two-species communities generated from a given set of microbial species on single or multiple substrates to achieve optimal production of a target metabolite,” says Dr Raman.

Read the full blog article at https://rbcdsai.iitm.ac.in/blogs/camp-the-perfect-bacterial-matchmaker/

Original Paper: 

• M. Ibrahim and K. Raman, “Two-Species Community Design of Lactic Acid Bacteria for Optimal Production of Lactate,” Computational and Structural Biotechnology Journal, vol. 19, pp. 6039-6049, 2021.
  [bibtex]

  @article{Ibrahim2021Twospecies,
    title = {Two-Species Community Design of Lactic Acid Bacteria for Optimal Production of Lactate},
    author = {Ibrahim, Maziya and Raman, Karthik},
    year = {2021},
    month = jan,
    journal = {Computational and Structural Biotechnology Journal},
    volume = {19},
    pages = {6039--6049},
    issn = {2001-0370},
    doi = {10.1016/j.csbj.2021.11.009},
    pmid = {34849207},
    abstract = {Microbial communities that metabolise pentose and hexose sugars are useful in producing high-value chemicals, resulting in the effective conversion of raw materials to the product, a reduction in the production cost, and increased yield. Here, we present a computational analysis approach called CAMP (Co-culture/Community Analyses for Metabolite Production) that simulates and identifies appropriate communities to produce a metabolite of interest. To demonstrate this approach, we focus on the optimal production of lactate from various Lactic Acid Bacteria. We used genome-scale metabolic models (GSMMs) belonging to Lactobacillus, Leuconostoc, and Pediococcus species from the Virtual Metabolic Human (VMH; https://vmh.life/) resource and well-curated GSMMs of L. plantarum WCSF1 and L. reuteri JCM 1112. We analysed 1176 two-species communities using a constraint-based modelling method for steady-state flux-balance analysis of communities. Flux variability analysis was used to detect the maximum lactate flux in the communities. Using glucose or xylose as substrates separately or in combination resulted in either parasitism, amensalism, or mutualism being the dominant interaction behaviour in the communities. Interaction behaviour between members of the community was deduced based on variations in the predicted growth rates of monocultures and co-cultures. Acetaldehyde, ethanol, acetate, among other metabolites, were found to be cross-fed between community members. L. plantarum WCSF1 was found to be a member of communities with high lactate yields. In silico community optimisation strategies to predict reaction knock-outs for improving lactate flux were implemented. Reaction knock-outs of acetate kinase, phosphate acetyltransferase, and fumarate reductase in the communities were found to enhance lactate production.},
    langid = {english},
    keywords = {Constraint-based modelling,Cross-feeding,Genome-scale metabolic models,Metabolic engineering,Microbial consortia}
  }