In an international collaboration with the University of Stellenbosch, Gustavus Adolphus College and Envalior, a peak-tracking algorithm was developed by CAST scientist Stef Molenaar to compare multiple datasets in one-dimensional (1D) and two-dimensional (2D) chromatography [1]. In his study, Molenaar investigated two application strategies: i) data processing where all chromatograms are produced in one sequence and processed simultaneously, and ii) method optimization where chromatograms are produced and processed cumulatively. The latter strategy is analogue to practice in within the AutoLC framework that is developed by the Pirok group.
One of the difficult operations in using comprehensive 2D chromatography concerns the data processing. With the first dimension not having its own detector, the first-dimension chromatogram must be reconstructed using the information obtained from the second-dimension detector (Figure 1A). This process is also referred to as “folding of the chromatogram”. The result is what is shown in Figure 1B.
As a result, the number of datapoints in the first dimension is equal to the number of modulations. There thus exists a scarcity of data to reconstruct the first dimension (Figure 1D), relative to the abundance of datapoints to describe the second dimension (Figure 1E).
In his article, Molenaar tested the first strategy on data from comprehensive 2D liquid chromatography (LC×LC) and comprehensive 2D gas chromatography (GC×GC) separations of academic and industrial samples of varying compound classes (monoclonal-antibody digest, wine volatiles, polymer granulate headspace, and mayonnaise). To accomplish this, he collaborated with scientists Dr. John Mommers (Envalior), Prof. Dwight Stoll (Gustavus Adolphus College), Sithandile Ngxangxa (University of Stellenbosch) and Prof. André de Villiers (University of Stellenbosch).
The work is envisaged to be instrumental for successful translation of the AutoLC algorithm [3] to 2D separations. The study was part of the UPSTAIRS project of Pirok and funded by the Dutch Research Council (NWO).
The study was recently published in Journal of Chromatography A and can be accessed freely here.
References
- Algorithm for tracking peaks amongst numerous datasets in comprehensive two-dimensional chromatography to enhance data analysis and interpretation, S.R.A. Molenaar, J.H.M. Mommers, D.R. Stoll, S. Ngxangxa, A.J. de Villiers, P.J. Schoenmakers, B.W.J. Pirok, Chromatogr. A, 1705, 2023, 464223: DOI: 10.1016/j.chroma.2023.464223.
- Challenges in Obtaining Relevant Information from One- and Two-Dimensional LC Experiments, B.W.J. Pirok & J.A. Westerhuis, LC-GC North America, 6(38), 2020, 8-14, DOI: 10.56530/lcgc.na.jk4782s5.
- Chemometric Strategies for Fully Automated Interpretive Method Development in Liquid Chromatography S. Bos, J. Boelrijk, S.R.A. Molenaar, B. van ‘t Veer, L.E. Niezen, D. van Herwerden, S. Samanipour, D.R. Stoll, P. Forré, B. Ensing, G.W. Somsen, B.W.J. Pirok, Anal. Chem. 2022, 94(46), 16060–16068, DOI: 10.1021/acs.analchem.2c03160.
