Algorithm-Assisted Structure Identification of Individual Nucleobases in Single DNA Chains through Tip-Enhanced Raman...

Area of Science:

• Biophysics
• Spectroscopy
• Computational Chemistry

Background:

• DNA structure and function depend on sequence and stereochemistry.
• Current DNA sequencing methods often involve labeling and replication, risking structural information loss.
• Single-molecule tip-enhanced Raman spectroscopy (TERS) offers label-free analysis but is limited to short DNA molecules.

Purpose of the Study:

• To develop an algorithm-assisted strategy for determining the structures of long-chain DNA molecules using TERS imaging.
• To overcome the computational limitations of simulating TERS spectra for large DNA molecules.
• To enable precise structural determination of DNA at the single-nucleobase level.

Main Methods:

• Development of a matching algorithm to rapidly simulate TERS spectra and mapping images for long DNA chains.
• Validation of the algorithm's accuracy and efficiency across various DNA molecular systems.
• Integration of the matching algorithm with Bayesian algorithms for experimental structure determination from TERS measurements.

Main Results:

• Successful simulation of TERS spectra and mapping images for DNA molecules with tens of thousands of atoms.
• Demonstration of accurate and efficient structural determination of long single-stranded DNA (ssDNA) molecules on surfaces.
• Achieved single-nucleobase precision in determining experimental molecular structures, showing agreement between theoretical predictions and experimental data.

Conclusions:

• The proposed algorithm-assisted TERS strategy enables label-free, high-resolution structural analysis of long DNA molecules.
• This approach overcomes previous limitations in TERS application to complex biomolecular systems.
• Promotes TERS as a versatile tool for identifying the sequence and configuration of various complex biomolecules, including DNA, RNA, proteins, and glycopeptides.