Easy and accurate high-performance liquid chromatography retention prediction with different gradients, flow rates, and instruments by back-calculation of gradient and flow rate profiles.

Isocratic retention data should make a suitable foundation for an accurate, cross-instrument LC retention prediction system. Our previous work suggested that in order to accurately calculate (or "project") gradient retention times on a wide range of HPLC systems using a single set of isocratic retention data, the precise shape of both the gradient and flow rate profiles produced by each instrument must be properly taken into account. However, accurate measurement of these system properties is difficult and time-consuming. In this work, we describe an approach that uses the measured gradient retention times of a set of standard solutes spiked into the sample along with their known isocratic retention vs. eluent composition relationships to determine the effective gradient and flow rate profiles by back-calculation. Retention "projections" of 20 other solutes using these back-calculated profiles, under various chromatographic conditions typical of metabolomics experiments, were remarkably accurate (as good as 0.23% of the gradient time, R2 up to 0.99996), being very near the level of retention reproducibility. Our calculations suggest that this level of accuracy will allow a quadrupole MS to identify 38-fold more compounds out of a simulated mixture of 7307; it would allow an FTICR-MS to improve its identification rate nearly two-fold with the same mixture. Moreover, very little effort is required of the user. This approach provides a simple way to correct for all instrument-related factors affecting retention, allowing dramatically streamlined and improved retention projection across gradients, flow rates, and HPLC instruments.

[1]  Roger M. Smith Alkylarylketones as a retention index scale in liquid chromatography , 1982 .

[2]  O. Fiehn Metabolomics – the link between genotypes and phenotypes , 2004, Plant Molecular Biology.

[3]  V. Spicer,et al.  Peptide retention standards and hydrophobicity indexes in reversed-phase high-performance liquid chromatography of peptides. , 2009, Analytical chemistry.

[4]  Roger M. Smith,et al.  The application of retention indices using the alkylarylketone scale to the separation of the barbiturates by HPLC. I. The effect of the eluent , 1984 .

[5]  P. Jandera Gradient elution in normal-phase high-performance liquid chromatographic systems. , 2002, Journal of chromatography. A.

[6]  H. Vandendool,et al.  A GENERALIZATION OF THE RETENTION INDEX SYSTEM INCLUDING LINEAR TEMPERATURE PROGRAMMED GAS-LIQUID PARTITION CHROMATOGRAPHY. , 1963, Journal of chromatography.

[7]  P. Nikitas,et al.  Expressions of the fundamental equation of gradient elution and a numerical solution of these equations under any gradient profile. , 2005, Analytical chemistry.

[8]  Roger M. Smith,et al.  Comparison of retetion index scales based on alkyl aryl ketones, alkan-2-ones and 1-nitroalkanes for polar drugs on reversed-phase high-performance liquid chromatography , 1991 .

[9]  U. Neue,et al.  Improved reversed-phase gradient retention modeling. , 2010, Journal of chromatography. A.

[10]  Raoul J. Bino,et al.  A Liquid Chromatography-Mass Spectrometry-Based Metabolome Database for Tomato1 , 2006, Plant Physiology.

[11]  Hung-jye Lin,et al.  Viscous dissipation in packed beds , 1981 .

[12]  D. Stoll,et al.  High speed gradient elution reversed phase liquid chromatography of bases in buffered eluents. Part II. Full equilibrium. , 2008, Journal of chromatography. A.

[13]  Susumu Goto,et al.  KEGG for representation and analysis of molecular networks involving diseases and drugs , 2009, Nucleic Acids Res..

[14]  M. Bogusz,et al.  Improved standardization in reversed-phase high-performance liquid chromatography using 1-nitroalkanes as a retention index scale. , 1988, Journal of chromatography.

[15]  L. Snyder,et al.  Slow equilibration of reversed-phase columns for the separation of ionized solutes. , 2003, Journal of chromatography. A.

[16]  Roman Kaliszan,et al.  Predictions of peptides' retention times in reversed‐phase liquid chromatography as a new supportive tool to improve protein identification in proteomics , 2009, Proteomics.

[17]  L. Snyder,et al.  Column selectivity in reversed-phase liquid chromatography I. A general quantitative relationship. , 2002, Journal of chromatography. A.

[18]  J. Griffin The Cinderella story of metabolic profiling: does metabolomics get to go to the functional genomics ball? , 2006, Philosophical Transactions of the Royal Society B: Biological Sciences.

[19]  L. Snyder,et al.  Characterization and applications of reversed-phase column selectivity based on the hydrophobic-subtraction model. , 2008, Journal of chromatography. A.

[20]  Roger M. Smith Retention and selectivity in liquid chromatography : prediction, standardisation and phase comparisons , 1995 .

[21]  U. Neue,et al.  Investigation of the effect of pressure on retention of small molecules using reversed-phase ultra-high-pressure liquid chromatography. , 2008, Journal of chromatography. A.

[22]  P. Jandera,et al.  Prediction of retention in gradient-elution normal-phase high-performance liquid chromatography with binary solvent gradients , 1997 .

[23]  Susumu Goto,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 2000, Nucleic Acids Res..

[24]  Mei Wang,et al.  Mass spectrometric tracer pulse chromatographic investigations of eluent sorption with bonded RPLC packings. , 2008, Analytical chemistry.

[25]  L. Snyder,et al.  The hydrophobic-subtraction model of reversed-phase column selectivity. , 2004, Journal of chromatography. A.

[26]  G. Guiochon,et al.  Influence of pressure on the retention and separation of insulin variants under linear conditions. , 2003, Analytical chemistry.

[27]  J. Carstensen,et al.  Aligning of single and multiple wavelength chromatographic profiles for chemometric data analysis using correlation optimised warping , 1998 .

[28]  Kiyoko F. Aoki-Kinoshita,et al.  From genomics to chemical genomics: new developments in KEGG , 2005, Nucleic Acids Res..

[29]  L. Snyder,et al.  Measurement and use of retention data from high-performance gradient elution : Correction for “non-ideal” processes originating within the column , 1984 .

[30]  W. Qingqing,et al.  Programmed-temperature gas chromatographic retention index , 1993 .

[31]  J. Knox,et al.  Theory of solvent disturbance peaks and experimentaldetermination of thermodynamic dead-volume in column liquid chromatography , 1985 .

[32]  G. Guiochon,et al.  Influence of viscous friction heating on the efficiency of columns operated under very high pressures. , 2009, Analytical chemistry.

[33]  Xinmiao Liang,et al.  A new method for chemical identification based on orthogonal parallel liquid chromatography separation and accurate molecular weight confirmation. , 2011, Journal of chromatography. A.

[34]  R. E. Skelton,et al.  Estimation of high pressure liquid chromatographic retention indices of narcotic analgetics and related drugs. , 1979, Journal of chromatographic science.

[35]  Ying Xu,et al.  Improved peptide elution time prediction for reversed-phase liquid chromatography-MS by incorporating peptide sequence information. , 2006, Analytical chemistry.

[36]  L. Snyder,et al.  Measurement and use of retention data from high-performance gradient elution : Contributions from “non-ideal” gradient equipment , 1984 .

[37]  Steffen Neumann,et al.  Critical assessment of alignment procedures for LC-MS proteomics and metabolomics measurements , 2008, BMC Bioinformatics.