PeakClimber: A software tool for the accurate quantification of complex HPLC chromatograms

Area of Science:

• Analytical Chemistry
• Biochemistry
• Computational Biology

Background:

• High-performance liquid chromatography (HPLC) is crucial for quantifying components in biological extracts.
• Accurate quantification of multianalyte samples in HPLC is challenging due to overlapping peaks.
• Existing software lacks the precision comparable to mass spectrometry approaches.

Purpose of the Study:

• To develop a computational tool, PeakClimber, for precise deconvolution of overlapping peaks in HPLC data.
• To enhance the accuracy of analyte quantification in complex biological mixtures analyzed by HPLC.

Main Methods:

• Developed PeakClimber, utilizing a sum of bidirectional exponentially modified Gaussian (BEMG) functions.
• Applied PeakClimber to deconvolve overlapping peaks in HPLC traces.
• Validated PeakClimber's performance against standard industry and open-source HPLC software.

Main Results:

• Demonstrated that HPLC peaks are accurately modeled by BEMG functions.
• Showcased PeakClimber's superior accuracy in quantifying known peak areas compared to existing software.
• Confirmed PeakClimber's ability to accurately quantify differences in triglyceride abundance in fruit fly samples.

Conclusions:

• PeakClimber offers a significant advancement in HPLC data analysis for complex biological samples.
• The tool provides enhanced precision for quantifying analytes, addressing a critical limitation in current HPLC methodologies.
• PeakClimber enables more accurate biological insights from HPLC data, as exemplified by fruit fly studies.