New HPLC System Created with Emphasis on Quantifying Complex Chromatograms

Researchers from Johns Hopkins University in Baltimore, Maryland recently created a new software package aimed at properly quantifying complex high performance liquid chromatography (HPLC) chromatograms. Their research and testing processes were published in the Journal of Chromatography A (1).

Originally, liquid chromatography (LC) techniques relied on gravity for solvent flux; this meant that individual chromatographs would take hours or days to run. In the 1960s, HPLCwas introduced, speeding up flow rates by forcing solvents through extremely narrow columns at high pressures. While this has led to improvements in column performance, trade-offs between mass transfer resistance and diffusive behaviors fundamentally limit peak resolution. Typically, this is sufficient, since these analyses are often concerned with the presence or absence of specific peaks or with quantification of relatively pure analytes with little peak overlap. However, for quantifying more complicated and biological samples with overlapping peaks, integration on its own can be inaccurate.

Solutions have been proposed for this problem in the past, including industry software that use the valley-to-valley method, where a line is dropped from the lowest point between two peaks to the chromatograph’s baseline, which is determined by the rolling-ball method. The peaks are then integrated on either side of the line. This method is neutral to underlying peak shapes, independent of surrounding peaks, and has a fast runtime. However, most peaks map to a variation of Gaussian distribution, and are not independent of neighboring peaks with which they overlap. Two more recent open-source software packages, HappyTools and hplc.io, improved on the valley-to-valley method by fitting chromatographs to a sum of Gaussian or skewed Gaussian curves, respectively. However, the theoretical peak shapes created by this software were not necessarily suited to the underlying data, with peak shapes not being universally agreed upon.

In this research, the scientists created a tool known as PeakClimber, which uses a sum of bidirectional exponentially modified Gaussian (BEMG) functions (which are the reciprocals of the delay time component of exponentially modified Gaussian [EMG] functions) to accurately deconvolve overlapping, multianalyte peaks in HPLC traces (3). This tool is said to fit chromatographs to a sum of BEMG curves, showing that the curves are mathematically and empirically good fits for single analyte peaks, and are consistent with extensive literature suggesting that this approach empirically aligns with chromatography data. When compared to other open-source software tools, PeakClimber makes iterative improvements in denoising data, detrending data, and reducing the runtime of the analysis.

To highlight the utility of PeakClimber, the scientists compared its performance to other algorithms by analyzing co-injections of three fatty-acids. Further, it was used to quantify differences in lipid composition between Drosophila melanogaster (fruit flies) reared with and without bacteria (2). 20 μL of the sample was injected onto the HPLC system. Component peaks were resolved over an 80 min time range in a multistep mobile phase gradient as follows: 0–5 min = 0.8 mL/min in 98 % mobile phase A (methanol-water-acetic acid, 750:250:4) and 2 % mobile phase B (acetonitrile-acetic acid, 1000:4); 5–35 min = 0.8–1.0 mL/min, 98–30 % A, 2–65 % B, and 0–5 % mobile phase C (2-propanol); 35–45 min = 1.0 mL/min, 30–0 % A, 65–95 % B, and 5 % C; 45–73 min = 1.0 mL/min, 95–60 % B and 5–40 % C; and 73–80 min = 1.0 mL/min, 60 % B, and 40 % C.

For downstream LC–MS analysis, peaks were collected in the following intervals via fraction collector 60–60.4 min (1), 60.4–60.9 min (2), 60.9–61.5 min (3), 61.5–63 min (4) 63.2–64 min (5),64–66 min (6),66–67 min (7), 67–69 min (8). Peaks were then evaporated to dryness and resuspended in 100 μL methanol and DCM (50/50 v/v) with a concentration of 5 mM ammonium acetate in the final solution.

With their findings, the scientists concluded that PeakClimber could more accurately quantify known peak areas than standard industry software and other open-source software packages for HPLC. Further, the technology accurately quantified differences in triglyceride abundances between colonized and germ-free fruit flies.

References

Derrick, J. T.; Deme, P.; Haughey, N. J.; Farber, S. A.; Ludington, W. B. PeakClimber: A Software Tool for the Accurate Quantification of Complex HPLC Chromatograms. J. Chromatogr. B 2025, 1264, 124721. DOI: 10.1016/j.jchromb.2025.124721

Drosophila Melanogaster. ScienceDirect 2007. https://www.sciencedirect.com/topics/neuroscience/drosophila-melanogaster (accessed 2025-07-30)

Yanagisawa, T. New Data Processing Method for Photodiode Array Detectors: Principle and Overview of Intelligent Peak Deconvolution Analysis (i-PDeA II). Shimadzu Corporation 2017. https://www.shimadzu.com/an/sites/shimadzu.com.an/files/pim/pim_document_file/technical/technical_reports/13438/jpl217011.pdf (accessed 2025-07-30)