The LCGC Blog: Are We Scared to Properly Explore Selectivity Options in HPLC?

January 9, 2015
Tony Taylor
Tony Taylor

Tony Taylor is Group Technical Director of Crawford Scientific Group and CHROMacademy. His background is in pharmaceutical R&D and polymer chemistry, but he has spent the past 20 years in training and consulting, working with Crawford Scientific Group clients to ensure they attain the very best analytical science possible. He has trained and consulted with thousands of analytical chemists globally and is passionate about professional development in separation science, developing CHROMacademy as a means to provide high-quality online education to analytical chemists. His current research interests include HPLC column selectivity codification, advanced automated sample preparation, and LC–MS and GC–MS for materials characterization, especially in the field of extractables and leachables analysis.

The Column

The Column, The Column-01-08-2015, Volume 11, Issue 1

LCGC Blogger Tony Taylor asks if we are too scared to properly explore selectivity options in high performance liquid chromatography (HPLC).

Pages 2-5

LCGC blogger Tony Taylor asks if we are too scared to properly explore selectivity options in high performance liquid chromatography (HPLC).

Much has been written about options for increasing efficiency in high performance liquid chromatography (HPLC) - primarily through the use of core–shell and sub-2-μm particles, which have been used to increase efficiency, speed up separations, or increase peak capacity.



However, many separations can only be effectively improved by optimizing selectivity - resolution is a function of selectivity, efficiency, and retention, with selectivity being the most effective at achieving good resolution.

Optimizing separations through improved selectivity has become less fashionable, or perhaps more daunting and time-consuming. In evidence, I offer the proliferation of methods that use 0.1% trifluoroacetic acid (TFA) as a "buffer" (which it isn't) to keep well away from analyte pKa values, when using a highly hydrophobic phase such as C18 and acetonitrile as the organic modifier to control retention (and separation). This has almost become the "de facto" template for modern HPLC methods - especially when mass spectrometry (MS) detection is used.

At best, the most advanced laboratories will have a screening platform with a selection of "orthogonal" chemistries that are capable of various pH/organic modifier combinations. This will perhaps be utilized in combination with computer aided optimization software or as part of statistical experimental design. We hope that this approach follows Pareto's Law (which states that for many events, roughly 80% of the effects come from 20% of the causes) and for the 20% of cases where a method does not "drop out" of the screen, then we have to do some "real work".

There is absolutely nothing wrong with this approach - other than it does not encourage thought about the separation process and the nature of the interaction between the analytes, stationary phase chemistry, and mobile phase. Such considerations are often required to achieve suitable separations for complex samples, analytes which are chemically very similar, or for bio-separations with small chemical differences to be investigated within a large protein molecule.

I often give lectures on column selectivity and the effect of various stationary phase characteristics, and these talks often feature a section on mixed mode and hydrophilic interaction chromatography (HILIC), techniques which have emerged as useful alternatives to the standard reversed-phase mode. However, one ever present question after these lectures is on the complexity of these separations and the number of interactions which need to be understood to properly understand the retention mechanisms and build a robust, optimized separation. Well, robust and high throughput is fine - but difficult separations often need to be solved with specialist approaches and sometimes "shock horror" we even need to think about the nature of the separations at hand.

I'll quote two very simple examples that I hope will prove how useful the more complex of these approaches, mixed mode, can be.

Glycans are sugar moieties that, when bound to proteins such as monoclonal antibodies, can be used in recognition and regulatory processes - a little like the zip code to our proteins "envelope". Adjusting the glycan moiety can be used to fine tune the protein function, efficacy, and safety, and regulators require a detailed characterization of this moiety during development and manufacture. Glycans are highly polar, take many different forms, and can be differentiated by hydrophobicity, size (volume) in solution, position, and type of substituent sugars and charge.

Traditional techniques such as reversed-phase ion pair chromatography and anion-exchange chromatography were used for the analysis of glycans - but both of these techniques are unfashionable and difficult to interface with MS. HILIC can be used to distinguish differences in size and composition (hydrophobicity), but cannot be used to differentiate based on charge state.

Figure 1: Various methods of producing mixed mode HPLC stationary phases.

Mixed mode chromatography, using ligands which have hydrophobic and electrostatic moieties (anionic, cationic, or zwitterioninc [Figure 1]), can separate glycans on the basis of size, composition and charge (Figure 2).

Figure 2: Separation of underivatized glycans from bovine fetuin using an anion-exchange mixed mode HPLC column: GlycanPac AXH-1 column (2.1 × 150 mm, 1.9-μm) A: Acetonitrile:water (80:20), B: Ammonium formate (80 mM pH 4.4) 2.5% to 37.5% B in 40 min; linear gradient: 0.4 mL/min; 30 °C; 200 pmoles on column; MS detection: negative ion mode. Reproduced with permission of Thermo Fisher Scientific.

Even though these separations are complex, there are "screening" methods that explore the selectivity differences obtained by altering the eluotropic strength, eluent pH, and the nature or concentration of the buffer, which are the three common factors used to optimize the selectivity of mixed mode separations. Even though more thought needs to go into these separations, there are generic approaches to exploring the range of separation possibilities.

These generic approaches can involve TFA-based separations; therefore, our generic screening can result in methods which are suitable for MS detection. Figure 3 shows the range of selectivity that can be explored for a sample containing acidic, basic, and neutral analytes by adjusting pH and elutropic strength using a zwitterionic stationary phase.

Figure 3: Separation of acidic, basic, and neutral analytes using a simple screening approach with a zwitterionic mixed mode stationary phase. (a) BzAc: Benzoic acid; BzCN: Benzonitrile; TYR: Tyrosine; PHE: Phenylalanine; BzAm: Benzylamine. Column: Obelisc R (Zwitterionic), 150 × 4.6 mm, 1.0 mL/min, UV 250 nm, mobile phases as shown. (b) Ac: Benzoic acid; BzCN: Benzonitrile; TYR: Tyrosine; PHE: Phenylalanine; BzAm: Benzylamine. Column: Obelisc R (Zwitterionic), 150 × 4.6 mm, 1.0 mL/min, UV 250 nm, mobile phases as shown. Reproduced with permission from SIELC Technologies.

It is true that in order to understand and properly optimize a separation, one often needs to understand the chemistry of the analytes and the stationary phase, for example to know if the electrostatic groups on the stationary phase are ionized or non-ionized at various eluent pH values. It is also true that these columns often need more time to equilibrate initially. However, just because the columns can't be abused and because we need to think about the underlying chemistry of the separation, this doesn't make them unsuitable for us to use.

The separation of highly polar analytes, analytes with very similar hydrophobicity, mixtures of acids, bases, and neutrals ,and even the separation of analytes and their counter ions can be successfully achieved using this type of stationary phase. So why don't I see them used in every laboratory? Well, I think it is at least in part because selectivity optimization is less fashionable, a little bit more difficult, and often too much like hard work!

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This article is from The Column. The full issue can be found here>>