Research

Growth and viability testing identified malate, succinate, pyruvate and oxoadipate as resensitising agents for antibiotic therapy. Resistant genes were catalogued through whole genome sequencing. Intracellular metabolomic profiling identified violacein as a potential biomarker for resistance. The temporal variance of metabolites captured the linearized dynamics around the steady state and correlated to growth rate. A constraints-based flux balance model was used to predict the metabolic basis of antibiotic susceptibility and resistance. The resistant pathogen rewired its metabolic networks to compensate for disruption of redox homeostasis. We foresee the utility of such scalable workflows in identifying metabolites for clinical isolates as inevitable solutions to mitigate antibiotic resistance.

D Banerjee, D Parmar, N Bhattacharya, AD Ghanate, V Panchagnula, A Raghunathan. A scalable metabolite supplementation strategy against antibiotic resistant pathogen Chromobacterium violaceum induced by NAD+/NADH+ imbalance. BMC systems biology 11 (1), 51 3, 2017.

D Banerjee, A Raghunathan. Knowledge, attitude and practice of antibiotic use and antimicrobial resistance: a study post the'Red Line'initiative. Current Science (00113891) 114 (9), 2018.

Even educated were unaware about proper use of antibiotics: survey, The Hindu BusinessLine, June 4th, 2018

To our knowledge this is the first study addressing the functional characterization in terms of integrating knowledge related to drug efflux, growth/proliferation, nutrient preference and metabolite profiling to drug dose response establishing an integrated resistance paradigm.

Although the existence of small minority populations with differential histology and dye efflux properties within cancer cell lines has been known for decades [8], the underlying biochemical physiology of how this shapes functional drug response, susceptibility and resistance is still incompletely understood. The integrative analysis of the heterogenous data types including exome data, transcriptomic data, metabolomic and respiromic data can help delineate mechanisms of resistance.

There is a critical need for detailed functional characterization and integrative analysis of minor populations in cell lines and tumor models to unravel the role of physiological contributors to drug resistance. Such integrative paradigms across molecular hierarchies in the cell would potentially help design combinatorial treatments using metabolite supplements to overcome drug resistance.

SRC Immanuel, AD Ghanate, DS Parmar, F Marriage, V Panchagnula, PJ Day, A Raghunathan. Integrative analysis of rewired central metabolism in temozolomide resistant cells. Biochemical and biophysical research communications 495 (2), 2010-2016, 2018.

When complex pathways are introduced inside the cell, limitations including intermediate toxicity, low enzyme activity, metabolic burden (cofactor imbalance etc.) need to be overcome for high performance. Such bottlenecks can be addressed using pathway engineering that exploits the synergies of synthetic biology, metabolic engineering and systems biology. Successful metabolic engineering for platform cell factories to produce a wide range of fuels and chemicals necessitates identifying the sensitivity of product/process to nutrient precursors and cofactors a priori. Constraints based flux balance analysis (FBA) of metabolic models has been used to design strains in silico that simultaneously maximize fitness and the desired product . These models predict intracellular reaction fluxes and identify strategies for substrate uptake, energy and cofactor balance. Such integrated computational and experimental strategies are invaluable for creating suites of strains for value added products and are critical to transcending from fundamental synthetic biology to metabolic engineering applications for industry.

SRC Immanuel*, D Banerjee*, MP Rajankar* and A Raghunathan. Integrated Constraints Based Analysis Of An Engineered Violacein Pathway In Escherichia coli. Biosystems. 171, 10–19, 2018

(*Equal contributors)

4. CONSTRAINTS BASED FLUX BALANCE MODELING

Our lab engages efforts in building metabolic network reconstructions and updating existing ones to understand biological complexity through computing cell phenotypes.

Chromobacterium violaceum

A genome-scale metabolic model (GSMM) was reconstructed for Chromobacterium violaceum, an opportunistic human pathogen. The model was used to represent antibiotic resistant and susceptible strains and predicted the NAD/NADH imbalance in the presence of antibiotics.

Glioblastoma and other Cancer cell models

The field of cancer research is caught in a data deluge by the advent of inexpensive genome-scale high throughput technologies. The complexity of a living system justifies the need for data acquisition at all levels of cell hierarchy from DNA to tissue and organ level delineation. However, just listing candidate genes (From genomic/exome data) or gene expression signatures (from transcriptomic data) are not enough to understand a complex, multi-hit, multifactorial emergent disease like cancer.

Our lab works on

1. Developing Context specific models to represent for cancer cell phenotypes in silico.

2. Algorithm development for incorporating trancriptomic data in metabolic flux balance models.