James Gomes’ Lab


About the Lab and Research

Amyotrophic Lateral Sclerosis

The broad area of our research in the investigation of mechanisms of neurodegeneration leading to diseases such as Alzheimer’s disease and Amyotrophic Lateral Sclerosis (ALS). We use computational and experimental methods to carry out our work. The computational methods of interest to us include Network Theory, Nonlinear Systems Analysis and Feedback Control. We use these methods to analyse experimental data, to create new algorithms to address large-scale gene regulatory networks and develop hypothesis that can be tested by directed experiments. The recent focus of our research has been Amyotrophic Lateral Sclerosis in Indian patients. We analysed the genetic basis of ALS in Indian population and determined the frequency of the hexanucleotide repeat expansion in C9orf72 and the trinucleotide (CAG) repeat expansion in ATXN2 in Indian ALS patients. Using targeted NGS analysis, we identified variants associated with ALS (known variants), rare variants (present at extremely low frequency in ExAC database) and novel variants (absent in our healthy controls and ExAC).

We are working on the mutations discovered in Indian ALS patients, for example, mutations in D-amino acid oxidase (DAO) gene. This D-amino acid degrading enzyme plays an important role in motor neuron degeneration through D-serine regulation. This mutation, which has been predicted as deleterious by Poly Phen-2, SIFT, Mutation taster, is being studied to elucidate destabilizing and activity altering mechanisms through molecular dynamic simulations, biochemical and cell culture methods to understand neurodegeneration.

The aim of the computational work on this topic is to understand what causes the onset of ALS and how different genes associated with ALS participate in disease progression. Using methods of network and systems theory, we use publicly available micro-array datasets of ALS to identify the cluster of genes whose functional interaction results in a disease outcome. The goal of this computational work is to support the clinical and wet lab research, through different testable hypotheses that can describe observed disease progression; in addition, we are examining new options for therapeutic intervention

NF-kappa-B

Epithelial cells function as the first line of defence against pathogens. Whenever these cells sense an extraneous invasion, they mount an immediate response, medically known as inflammation. Usually, inflammatory processes benefit the host organism by eventually clearing the infection. A successful pathogen clearance requires enforcement of the army of immune cells, such as macrophages, and neutrophils at the site of infection. On the other hand, uncontrolled inflammation is detrimental to the host tissues and may be fatal in certain circumstances. Evolutionarily, the conserved transcription factor NF-kB plays a pivotal role in eliciting this meticulously controlled dynamic response against pathogens in different cell types. This intracellular signal transduction pathway has two interconnected arms, namely the classical and the alternative. The classical NF-kB pathway is stimulated when the dedicated receptors at the cell surface sense pathogen-associated molecules in the environment. The alternative pathway primarily participates in development of immune organs, such as lymph nodes. Since these pathways are interconnected, they engage in crosstalk with each other. We explore the implications of this pathway crosstalk, which orchestrates this fine-tuned cellular combat mechanism, at the systems level, with mathematical and computational tools, for varied pathogenic stimuli and host cell-types.

Advanced Bioprocess Control

Bioprocesses are intrinsically nonlinear and required special attention when strategies are developed to control bioreactors. We have developed and implemented a range of advanced and novel controllers such as the Decoupled Input-Output Linearizing Controller (DIOLC), Decoupled Adaptive Controller, Sequential Adaptive Network (SAN) Controllers, Self-Organizing Network Controllers and the Permissible Metabolic Regime Controllers.

Lab Students

Ph.D. Scholars
M.S. (Research) Students
Postdoctoral Researchers

Lab Alumni