IIT Kharagpur model predicts effect of SARS-CoV-2 virus on lungs, post-infection

A model has been developed by Indian Institute of Technology Kharagpur researchers predicting alteration in metabolic reaction rates of lung cells post SARS-CoV-2 infection. The research would lead to a better understanding of metabolic reprogramming and aid the development of better therapeutics to deal with the viral pandemics, an institute spokesperson said on Wednesday. The spokesperson said researchers at IIT Kharagpur have, for the first time, reported such a method to find an alteration in metabolic reaction rates inside lung cells when they are affected by virus/pathogens.

As the method finds and reports critical aspects of physiology, which are affected by SARS-CoV-2 infection, it will definitely enable the discovery of therapeutic targets.

"We have used the gene expression of normal human bronchial cells infected with SARS-CoV-2 along with the macromolecular make-up of the virus to create this integrated genome-scale metabolic model. The growth rate predicted by the model showed a very high agreement with experimentally and clinically reported effects of SARS-CoV-2," said Dr Amit Ghosh, Assistant Professor, School of Energy Science and Engineering, IIT Kharagpur.

The findings are significant as scientists have been trying to extract information from the human genome sequences for the past two decades to gather a better understanding of genetic disorders.

Talking about this new development another researcher Piyush Nanda (currently a graduate student at Harvard University) said, "In this model, we have explored how metabolism works and how it is altered in diseases. Our work involved measuring how the tens of thousands or more complex chemical reactions change when biological cells are intruded on by an uninvited guest like SARS-CoV-2, which would help improve our understanding of diseases."

Using the power of genomics the researchers posed the operation of reactions as a set of mathematical equations and solved it to obtain which reactions are altered in the cells when SARS-CoV-2 infects a person.

"A better understanding of metabolic reprogramming would aid in the design of better therapeutics to deal with the COVID-19 pandemic," said Nanda.

Further, the researchers have identified pathways like fatty acid synthesis and lipid metabolism that can be targeted by novel drugs. This model is based on context-specific metabolic models.

"Using our method we have observed the alterations between diseased and normal metabolic states in the case of SARS-CoV-2 infection which have been proven using human patients data. The model will allow researchers to understand the wide spectrum of viruses that manipulate human metabolism and will help to design better therapeutics in COVID-19 treatment leveraging the power of systems biology," Ghosh added.

In the case of SARS-CoV-2 infection, the researchers predict that lipid metabolism particularly fatty acid oxidation, cholesterol biosynthesis to be most affected which was confirmed with clinical studies.

The research was published in the international journal PLOS Computational Biology.