Identifying molecular dynamics in single-molecule FRET experiments with burst variance analysis

Area of Science:

• Biophysics
• Structural Biology
• Biochemistry

Background:

• Single-molecule Förster resonance energy transfer (smFRET) histograms reveal biomolecular structures and functions.
• Current methods like probability distribution analysis (PDA) detect structural heterogeneity but cannot differentiate between static and dynamic origins.

Purpose of the Study:

• Introduce Burst Variance Analysis (BVA) to differentiate dynamic from static sources of heterogeneity in smFRET data.
• Validate BVA's capability to distinguish heterogeneity sources using simulations and DNA hairpin experiments.
• Investigate dynamics in the Klenow fragment of DNA polymerase I during nucleotide incorporation.

Main Methods:

• Burst Variance Analysis (BVA) compares the standard deviation of single-molecule FRET efficiency over time against theoretical expectations.
• Simulations and experimental data from DNA hairpins were used for method validation.
• BVA was applied to analyze the fingers-closing transition in the Klenow fragment of E. coli DNA polymerase I.

Main Results:

• BVA successfully distinguishes between static and dynamic sources of structural heterogeneity in smFRET histograms.
• BVA can test dynamic models against observed standard deviation data.
• Substantial dynamics were identified in polymerase complexes before nucleotide incorporation, potentially impacting DNA synthesis fidelity.

Conclusions:

• BVA is a valuable new method for analyzing dynamics in single-molecule FRET studies.
• BVA complements existing techniques like PDA and fluorescence correlation spectroscopy (FCS) for molecular dynamics research.
• The identified dynamics in DNA polymerase complexes may be crucial for DNA synthesis accuracy.