Research

Chemical Sciences

Title :

single cell diagnostics using programmable array on DNA nanostructure and sERs-based detection

Area of research :

Chemical Sciences

Focus area :

Molecular Diagnostics

Principal Investigator :

Dr. Manzoor Ahmed, Jawaharlal Nehru Centre for Advanced scientific Research, Bangalore, Karnataka

Timeline Start Year :

2024

Timeline End Year :

2026

Contact info :

Details

Executive Summary :

Analyzing proteomic and genomic signatures from single cell provides valuable insight into cellular heterogeneity, which plays an important role in disease development and progression, stem cell differentiation, and cellular response to therapeutic agents. However, most of the currently available technologies are either limited by their requirement for large sample sizes or have limited multiplexing capability. Here, we propose to employ an innovative approach by synergistically combining the programmability of the DNA nanostructure with the single-molecule sensitivity of surface-Enhanced Raman spectroscopy (sERs) based detection method to generate a diagnostic platform for single-cell analysis. This innovative diagnostic platform is benefitted from the two unique features of DNA nanostructure: 1) the ability to organize nanoparticles on DNA nanostructure in any predefined pattern to generate well-defined plasmonic hot spot, and 2) the ability to precisely place the analyte molecules ‘only' at the hot spot region to get the maximum benefit from the field enhancement and to achieve highly sensitive analysis. In addition to high sensitivity, inherent to sERs based detection method is high multiplexing through the unique spectroscopic signature of Raman active dyes. Therefore, once developed, this proposed highly multiplexable single-cell analysis platform would facilitate proteome and genome-wide classification of disease states, devising therapeutic decisions, monitoring therapeutic responses, and highlighting heterogeneity in much finer detail.

Total Budget (INR):

Organizations involved