PS Poly: A chain tracing algorithm to determine persistence length and categorize complex polymers by shape

Area of Science:

• Biophysics
• Polymer Science
• Biochemistry

Background:

• Polymers like nucleic acids and proteins are fundamental to life, possessing diverse mechanical properties and shapes.
• Persistence length quantifies polymer bending rigidity, while shape (linear, cyclic, branched) is crucial for function and stability.
• Understanding polymer physical attributes is vital for biological applications.

Purpose of the Study:

• To introduce Persistence length Shape Polymer (PS Poly), a novel, automated algorithm for analyzing polymer physical attributes.
• To enable rapid and precise analysis of single polymer molecules from atomic force microscopy (AFM) images.
• To provide a general tool for extracting key information on polymer stiffness, shape, and polymerization.

Main Methods:

• Developed PS Poly, an algorithm utilizing image skeletonization and endpoint/branch point detection.
• Applied PS Poly to single-molecule AFM images acquired under physiologically relevant fluid conditions.
• Validated the algorithm's accuracy using well-characterized deoxyribonucleic acid (DNA) and complex candidalysin polymers.

Main Results:

• PS Poly achieves near-full automation and subpixel precision in analyzing polymer physical attributes.
• The algorithm successfully quantified persistence length and shape for thousands of polymer molecules.
• Demonstrated robustness and generalizability by analyzing both DNA and the fungal toxin candidalysin.

Conclusions:

• PS Poly is a robust and generalizable algorithm for extracting fundamental polymer information.
• The tool facilitates rapid analysis of polymer backbone stiffness, architecture, and polymerization mechanisms.
• PS Poly offers significant potential for advancing research in biophysics and polymer science.