Methods and Challenges for Computational Data Analysis for DNA Adductomics

Area of Science:

• Environmental Health
• Genomics
• Analytical Chemistry

Background:

• Chemicals in the environment, diet, and endogenous processes cause DNA adducts, which can lead to mutations and diseases like cancer.
• Previous methods allowed targeted analysis of specific DNA adducts, but lacked the ability to screen for a comprehensive range of adducts in a single assay.
• The human genome harbors diverse DNA damages, necessitating advanced analytical techniques for thorough characterization.

Purpose of the Study:

• To introduce DNA adductomics as a novel, nontargeted approach for simultaneously screening multiple DNA adducts.
• To discuss the limitations of current computational tools in processing mass spectrometry data for DNA adduct discovery.
• To highlight the need for improved software and algorithms to advance DNA adductomics as a mature technology.

Main Methods:

• Utilizing high-resolution mass spectrometry (MS) instrumentation and advanced scanning technologies.
• Employing nontargeted "omics" approaches, including data-dependent and data-independent acquisition methods.
• Evaluating contemporary computational tools for feature finding in MS data, commonly used in proteomics and metabolomics.

Main Results:

• DNA adductomics enables the simultaneous screening of multiple DNA adducts, offering a broader view of genomic damage.
• Existing software and common MS data acquisition methods show limitations in reliably detecting low-abundance DNA adducts in human samples.
• Current computational tools, while effective in other omics fields, are not fully optimized for nontargeted DNA adduct biomarker discovery.

Conclusions:

• DNA adductomics holds promise for identifying a wide spectrum of DNA damages and potential cancer-causing agents.
• Significant challenges in data processing, particularly adduct detection at low abundance, must be addressed for DNA adductomics to reach its full potential.
• Improvements in MS data processing software and the development of novel algorithms are crucial for establishing DNA adductomics as a powerful tool in environmental health and disease research.