Oligonucleotide separations often fail for reasons that are easy to overlook. Peaks compress, impurities coelute, and resolution shifts unexpectedly during optimization—even when methods appear well designed. In a recent Separation Science webinar, Controlling Retention Factor When Investigating Oligonucleotide Chromatography, Daniel Meston discussed why retention factor is central to these problems—and how controlling it improves both predictability and performance.
Meston, Associate Research Professor at Gustavus Adolphus College, focuses on antisense oligonucleotides and related therapeutically relevant molecules. These compounds combine high charge density, structural heterogeneity, and extreme sensitivity to solvent strength. “Depending on the modification, truncations in particular can have very large differences in their retention factors,” he explains, creating chromatograms that span early void-volume eluters and strongly retained late species in a single run.
Why Retention Factor Dominates Oligonucleotide Separations
Unlike small molecules, oligonucleotides respond sharply to even minor changes in mobile-phase composition. As gradient strength increases, large sections of the chromatogram can collapse into coeluting bands. Conventional one-dimensional gradients often require analysts to choose between retaining early-eluting compounds and eluting late-eluting compounds.
Meston demonstrates that two-dimensional liquid chromatography (2D-LC) provides a practical workaround. By isolating congested regions in the first dimension and re-separating them under carefully controlled second-dimension conditions, laboratories regain selectivity without sacrificing coverage. Crucially, this only works when the retention factor is treated as a fixed, designable variable rather than an uncontrolled outcome.
Predicting Retention with Minimal Prior Knowledge
To achieve that control, Meston applies classical gradient elution theory in a deliberately pragmatic way. Two generic scouting gradients generate experimental retention factors, which are then used to extract key descriptors—S and Kₗ—that characterize an analyte’s sensitivity to solvent strength.
Once validated against experimental data, these parameters allow analysts to predict retention behavior under new gradient slopes and times. “It’s a guaranteed method,” Meston asserts. “You don’t need detailed molecular knowledge because everything is driven by experimental data.” Iterative refinement further reduces prediction error, enabling precise targeting of specific retention-factor windows.
Pressure and Flow Rate: Hidden Variables
One of the webinar’s most striking findings concerns pressure. For oligonucleotides, changes in pressure alone can dramatically alter retention. In ion-pair reversed-phase mode, increasing pressure from 100 to 500 bar increases log K by roughly a factor of three—a change large enough to invalidate many traditional optimization assumptions.
This has direct consequences for van Deemter-based optimization. Changing the flow rate alters the pressure, thereby affecting the retention factor. Meston shows that correcting for the retention factor at each flow rate reveals unexpectedly linear behavior and enables meaningful comparisons of resolution. In practical terms, lowering the flow rate from 0.75 to 0.1 mL/min roughly doubles the resolution between closely related phosphorothioate species.
Rethinking Orthogonality in 2D-LC
The work also challenges the idea that orthogonality is mandatory for effective two-dimensional separations. By running both dimensions in ion-pair reversed-phase mode, but at markedly different gradient slopes and retention factors, Meston achieves substantial gains in selectivity.
Shallow second-dimension gradients (as low as 2%) dramatically expand separation space, allowing shoulder peaks in the first dimension to resolve into multiple impurities that can be confidently identified by mass spectrometry. “The enormous sensitivity of these molecules to solvent strength becomes an advantage,” he notes, when retention is carefully controlled.
Pore Size: an Underused Lever
Perhaps the most consequential insight comes from pore-size studies. Using columns with identical chemistry but pore sizes ranging from 100 to 4,000 Å, Meston demonstrates that conventional 100 Å columns perform poorly for oligonucleotides—even relatively small (~7 kDa) antisense species.
At retention factors between 1 and 5—where many routine methods operate—100 Å materials show steep increases in plate height. As pore size increases, this sensitivity diminishes. At 4,000 Å, performance improves by nearly an order of magnitude, delivering roughly a 20-fold reduction in plate height compared with 100 Å columns under comparable conditions.
“These are molecules on the small end of therapeutic oligonucleotides,” notes Meston. “If pore size matters this much here, it’s going to matter even more for larger, structured species like guide RNAs.”
What this Means for Analytical Laboratories
The key message is not that oligonucleotide separations are inherently unpredictable, but that they require tighter control of variables often treated as secondary. Retention factor, pressure, and pore size interact in ways that can quietly undermine robustness if left unmanaged.
The on-demand webinar explores these relationships in depth, with detailed data, chromatographic examples, and method-development workflows. For laboratories working on oligonucleotide therapeutics or complex charged biomolecules, the full presentation offers a practical framework for turning retention factor from a liability into a powerful optimization tool.
Meet the Expert
Daniel Meston is an Associate Research Professor at Gustavus Adolphus College, USA. Daniel's research focuses on the development of bioanalytical separations, primarily of peptides and oligonucleotides, using online 2D-LC. Outside of research, Daniel is the ChromSoc Vice President and the editor of the publication ChromCom.