BART: A transferable liquid chromatography retention time library for bile acids.

Identification of unknown bile acids, especially the distinguishment between isomers, requires retention times of a large number of reference standards, which are often not commercially available. Meanwhile, published retention information cannot be directly transferred across labs due to the differences between liquid chromatography (LC) systems, such as different extra column volume and dwell volume. To improve this situation, a transferrable retention time library for bile acids named BART was developed. BART was composed of isocratic retention models of 272 bile acids and a software tool to predict their gradient retention times on various LC systems. The isocratic retention times of bile acids were acquired on a Waters BEH C18 column with mobile phases of acidic ammonium acetate buffer and acetonitrile, and fit to the quadratic solvent strength model (QSSM). Segmented linear gradient retention times were calculated with holdup time (t0), dwell time (tD) and actual gradient profile corrected using 21 bile acid calibration standards. In addition to the reference system where the isocratic retention times were acquired, this approach has been validated on four other LC-MS systems in four labs with two gradient methods. Average root mean square errors (RMSE) between predicted and experimental retention times were 0.052 and 0.054 min for the two gradients tested, which were 9-fold more accurate than referring to a static retention time library. The library is freely available at https://bafinder.github.io/.

Retention projection enables accurate calculation of liquid chromatographic retention times across labs and methods.

Identification of small molecules by liquid chromatography-mass spectrometry (LC-MS) can be greatly improved if the chromatographic retention information is used along with mass spectral information to narrow down the lists of candidates. Linear retention indexing remains the standard for sharing retention data across labs, but it is unreliable because it cannot properly account for differences in the experimental conditions used by various labs, even when the differences are relatively small and unintentional. On the other hand, an approach called "retention projection" properly accounts for many intentional differences in experimental conditions, and when combined with a "back-calculation" methodology described recently, it also accounts for unintentional differences. In this study, the accuracy of this methodology is compared with linear retention indexing across eight different labs. When each lab ran a test mixture under a range of multi-segment gradients and flow rates they selected independently, retention projections averaged 22-fold more accurate for uncharged compounds because they properly accounted for these intentional differences, which were more pronounced in steep gradients. When each lab ran the test mixture under nominally the same conditions, which is the ideal situation to reproduce linear retention indices, retention projections still averaged 2-fold more accurate because they properly accounted for many unintentional differences between the LC systems. To the best of our knowledge, this is the most successful study to date aiming to calculate (or even just to reproduce) LC gradient retention across labs, and it is the only study in which retention was reliably calculated under various multi-segment gradients and flow rates chosen independently by labs.

A practical methodology to measure unbiased gas chromatographic retention factor vs. temperature relationships.

Compound identification continues to be a major challenge. Gas chromatography-mass spectrometry (GC-MS) is a primary tool used for this purpose, but the GC retention information it provides is underutilized because existing retention databases are experimentally restrictive and unreliable. A methodology called "retention projection" has the potential to overcome these limitations, but it requires the retention factor (k) vs. T relationship of a compound to calculate its retention time. Direct methods of measuring k vs. T relationships from a series of isothermal runs are tedious and time-consuming. Instead, a series of temperature programs can be used to quickly measure the k vs. T relationships, but they are generally not as accurate when measured this way because they are strongly biased by non-ideal behavior of the GC system in each of the runs. In this work, we overcome that problem by using the retention times of 25 n-alkanes to back-calculate the effective temperature profile and hold-up time vs. T profiles produced in each of the six temperature programs. When the profiles were measured this way and taken into account, the k vs. T relationships measured from each of two different GC-MS instruments were nearly as accurate as the ones measured isothermally, showing less than two-fold more error. Furthermore, temperature-programmed retention times calculated in five other laboratories from the new k vs. T relationships had the same distribution of error as when they were calculated from k vs. T relationships measured isothermally. Free software was developed to make the methodology easy to use. The new methodology potentially provides a relatively fast and easy way to measure unbiased k vs. T relationships.