The COVID-19 pandemic has been characterized by a diversity of symptoms with the majority being asymptomatic. Within symptomatic also, there has been mild, moderate, and severe category with a fraction resulting in mortality. There has been a significant role of Genomics in taking forward the Genomic Surveillance for SARS-CoV-2 with more than 1.25 million genomes being submitted to GISAID. It has highlighted the strength of Genomics in knowing the pathogen, underlying mutations, mutations linked to disease outcome, and genomics surveillance (GS).  

There has been renewed effort toward the role of genome sequencing and genomic surveillance in catching the early trends of a microbe evolving into a potential pathogen.

Different regions of Telangana have been challenged by infectious diseases which have an impact on patients both in terms of mortality and quality of life. This includes the challenge posed by SARS-CoV-2 as well as the persistent challenge from the pathogens like Mycobacterium tuberculosis (Mtb), Dengue, Chikungunya, Human Papilloma Virus (HPV), and other vector-borne diseases. IDSP (Integrated Disease Surveillance Program) currently gives only the prevalence of a Communicable Disease from a network of centers. No information is available on the genomic architecture, underlying mutations, variants, mutations linked to disease outcome, etc. of the pathogens. An advance warning based on the GS, in continuous consultation with the health department, would help to evolve strategies toward containment and ramping up of the hospital infrastructure in the districts of concern.  

MicroLabs [based on the pillars of Scale, Speed, Sensitivity, & Sample cost], set up at IIIT Hyderabad in collaboration with IGIB, brings genomic surveillance for communicable diseases to Point of Care (POC). 

Main Objectives:

  • To understand the Genome architecture of the pathogen and potential pathogens. 
  • Identify genomic hotspots based on whole genome sequencing (WGS). 
  • To correlate genomic mutations with the clinical severity and outcome. 
  • To develop AI-enabled models for pre-emptive surveillance for susceptible sub-groups. 
  • To develop a genetic assay based on clinical outcome-associated mutations.

Targeted Outcomes:

Datasets – We have a pre-existing bio-digital repository of the clinical samples and associated digital records of clinical data. In combination, existing retrospective data, as well as prospective data, would be an ideal study to make learning and implement/test in future patients. The multi-omics dataset collected during the project would be a wealth for future pandemic preparedness for informed decisions towards preventive and informed decisions for the future. 

Diversity – The pan-state footprint of the proposed hospitals, diversity of infectious diseases, and associated pathogens would help towards generic and specific understanding. Given the functional role of co-infections, the diversity of the microbes would be very helpful for a holistic understanding of the clinical outcome.  

Cheaper diagnostics – As final outcome, we aim to develop genetic assays based on high-throughput sequencing and significantly cheaper per sample cost. Given India’s bigger population base in general and Telangana, it would be pertinent to make progress in this regard. 

Trained manpower – The trained manpower (both experimental and computational) during the tenure of the project would add to the pool of skilled people required for genetic diagnostics. It is important for future pandemic preparedness wherein we may need an unexpectedly big number of hands and minds. 

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