High-Resolution Analysis of DNA Electrophoretic Separations via Digital Image Processing

Compared with capillary electrophoresis (CE), gel electrophoresis (GE) is a traditional method for the analysis of nucleic acids because of its low cost, although the operation process is complicated. The electropherogram from CE can offer more information (e.g., DNA size and its concentration) for researchers. Based on the self-built integrated biochip GE system, we proposed a computational method that converts conventional agarose GE images into CE-like fluorescence profiles for enhanced DNA analysis. The gel images were processed using an image-based algorithm involving median filtering to remove background noise and pixel-wise intensity summation along the migration axis to generate one-dimensional records of electrophoretic separations. Each DNA band in the gel was thereby transformed into a distinct fluorescence peak, reflecting its migration distance and relative intensity. To further enhance resolution and peak separation, Gaussian modeling was applied to fit the fluorescence intensity distribution, providing smoother and more distinguishable spectral peaks. To validate the method, three periodontal pathogens—Porphyromonas gingivalis (P.g), Treponema denticola (T.d), and Tannerella forsythia (T.f)—were amplified using PCR and analyzed by gel electrophoresis. The method successfully identified distinct electrophoretic patterns for the three pathogens by using a 50 bp DNA ladder as an internal calibration reference. The results demonstrate that image-based reconstruction of electrophoretic data provides a reliable, quantitative, and visually interpretable representation of DNA migration, comparable to CE output. This approach bridges a gap between traditional GE and modern capillary systems, allowing for the semi-quantitative analysis of DNA fragments without specialized CE instrument. The proposed method offers a valuable analysis method for the separation of DNA, RNA, protein and polypeptides.