Cyclodextrins (CDs) are cyclic oligosaccharides composed of D-glucose units that are linked by α(1,4)-glucosidic bonds. The practically important, industrially produced CDs are α-CD, β-CD and γ-CD which differ in the number of glucose units involved [i.e., α-CD contains 6 glucose units, β-CD has 7 glucose units (Figure 1) and γ-CD has 8 glucose units]. CDs are generally produced through enzymatic conversion of starch. CDs have the shape of a torus with a hydrophobic interior cavity and a hydrophilic outside. The narrow rim is occupied by the primary hydroxyl groups at C6 while the wider rim contains the secondary hydroxyl groups at C2 and C3. The hydroxyl groups can be chemically modified resulting in a number of derivatives. With regard to their use as chiral selectors in CE the most important difference is the cavity size which is the smallest for α-CD and the largest for γ-CD.  

Figure 1: Schematic structure of  Î²-cyclodextrin.			

One of the premier applications of capillary electrophoresis (CE) is the resolution of stereoisomers (enantiomers). Enantioseparations by CE are achieved by the addition of a stereochemically pure substance, a so called chiral selector, into the background electrolyte. In order to achieve a chiral separation the enantiomers must have differing chromatographic interactions with the added chiral selector. The most frequently additives used are cyclodextrins because they are commercially available, UV-transparent and relatively low cost. 

There is a large variety of CD derivatives that allow optimization during method development as well as the separation of charged and neutral analytes. Many validated enantioseparation methods have been reported. Chiral CE methods for assessing chiral purity and stability are routinely used in many pharmaceutical companies and have also been included in numerous regulatory submissions. Chiral CE methods have also been included in Pharmacopoeias. For example, there is a chiral test method for epinephrine bitartrate in the 

Cyclodextrins are also useful in non-chiral separations. For example, they can be used to separate closely related compounds such as 

-isomers, which have virtually identical electrophoretic mobilities. These compounds will, however, have differing interactions with the CD's because of their differing shape. For example, a range of closely related impurities of the drug salbutamol were resolved from each other and from the salbutamol enantiomers

  using a low pH buffer containing 100 mM dimethyl-β-cyclodextrin. A more elaborate buffer of phosphate pH 3.0 containing 12 mM tetrapropyl and 8 mM tetrabutyl ammonium bromide and 20 mM methyl-β-CD was required for the separation of very closely-related Remoxipride achiral impurities from each other,

   a separation will be observed in most cases. 

How Does Adding CDs Help Achieve Chiral Separation? 

As mentioned before CDs can form complexes with molecules based on their inclusion into the hydrophobic cavity. Secondary interactions may include hydrogen bonding or dipole–dipole interactions with the hydroxyl groups on the CDs, or with other polar substituents of the CDs. In the case of charged CDs ionic interactions will also contribute, or may even dominate, the complexation mechanism. Effectively the CDs are contained in the buffer and their interaction with the analyte either slows or increases movement of the enantiomers. If the interaction is stronger for one enantiomer than the other then a separation will occur. 

CDs are naturally chiral molecules, therefore, binding of host enantiomer molecules results in diastereomeric complexes. These complexes differ in properties such as the enantiospecific binding constants, charge or size resulting in an enantioseparation. The thermodynamic complexation equilibria between the enantiomers R and S and the CD are characterized by the complexation constants K

, respectively, assuming the formation of a 1:1 complex between the enantiomers and the chiral selector. 				

Considering that the effective mobility μ

 of an analyte is the sum of its fraction migrating in the free form, μ

, and that the effective mobilities of the enantiomers must be different to observe a separation, the fundamental equation as developed by Wren and Rowe can be obtained.

 are the effective mobilities of the R- and S-enantiomers, μ

 are the mobilities of the complexed R- and S-enantiomers and [C] is the concentration of the CD. As can be derived from Equation 3 enantioseparations can be achieved if the analyte enantiomers differ in their complexation constants or in the complex mobilities, the former is certainly the more often the more dominant factor. Another important conclusion is the fact that the CD concentration plays an important role in enantioseparations. 

Cyclodextrins are also used in HPLC to achieve chiral separations where they are bonded onto stationary phase (e.g., Cyclobond columns). 

Commercially available CDs are based on the three CDs differing in cavity size (i.e., α-CD, β-CD and γ-CD). The derivatives are obtained by chemical modification of the primary and secondary hydroxyl groups on the CD rims. Most derivatives are based on β-CD but more and more derivatives of α- and γ-CD became available recently. Some commercially available neutral as well as charged CDs are summarized in Table 1. From a practical point of view it is important to keep in mind that many of the CD derivatives are randomly substituted CDs that are essentially a mixture of isomers as this may affect method robustness. Chemically pure single isomer CDs are also available such as the single isomer sulphated CDs developed by Vigh and coworkers in the late 1990s.

Table 1: Examples of commercially available cyclodextrins.			

The native CDs and several of their derivatives can be obtained from suppliers for organic chemicals such as Sigma, Aldrich or Fluka. A large variety of derivatives can be obtained from CTD Inc. (High Springs, Florida, USA), probably the most complete selection including variations in the degree of substitution and isomeric purity is supplied by Cyclolab (Budapest, Hungaria). Specific CDs are sold by specialized companies such as PAC L.P. (Houston, Texas, USA) providing single isomer sulphated β-CDs or CyDex Inc. (Lenexa, Kansas, USA) commercializing sulphobutylether-β-CD. 

Figure 2: Separation mechanism in chiral CE.			

In CE enantioseparations CDs act as pseudostationary chromatographic phase. Thus, depending on the charge of the analytes and the CDs different separation schemes can be applied. The most frequently used approaches are summarized in Figure 2 and in Table 2. In the case of neutral CDs only charged selectors can be separated.

Table 2: Commonly used modes of operation for chiral CE.			

When analysing basic compounds acidic background electrolytes are selected [Figure 2(a)]. Under these conditions the analyte is protonated and migrates to the detector at the cathodic end of the capillary while the selector does not possess an electrophoretic mobility but is transported by the EOF. At low acidic pH values the EOF is largely suppressed. Subsequently, the analyte enantiomer, which is complexed stronger by the selector, migrates second as it is complexed for a longer period of time compared with the weaker bound enantiomer. As the hydrodynamic radius of the enantiomer-CD complex is larger than the radius of the free analyte the complex migrates slower. The CD effectively acts as a "net" trapping one enantiomer more than the other and slowing its migration down causing separation to occur. 

Acidic analytes can be analysed at alkaline pH values [Figure 2(b)]. Because of their negative charge acids migrate to the anode but are transported to the cathode by the strong EOF at alkaline pH values. In this case the stronger complexed enantiomer migrates first as its mobility in the opposite direction of the detector is slowed down. 

Charged chiral selectors are more versatile and offer additional possibilities as they possess an electrophoretic mobility themselves and, as a consequence, neutral molecules can be analysed as well. The possible scenarios are outlined for negatively charged selectors but analogous schemes can be drawn for positively charged selectors. At acidic pH values the negatively charged selector migrates to the anode while positively charged basic analytes migrate towards the cathode where they are detected [Figure 2(c)]. In this instance the stronger complexed enantiomer migrates second as described above for the use of neutral selectors. A general advantage of selectors with the opposite charge compared with the analytes is their counter mobility, which enables the use of low concentrations of the respective chiral selector. If high CD concentrations are selected the analyte may be carried to the anode. In this case the polarity of the applied voltage is reversed and detection is performed at the anode. This will lead to a reversal of the enantiomer migration order.   

At alkaline pH values negatively charged CDs may also be applied to the enantioresolution of neutral and basic analytes in the normal polarity mode [Figure 2(d)]. At alkaline pH values basic compounds are uncharged and are transported to the detector at the cathode as are neutral compounds. The anionic CD migrates to the anode and decelerates the stronger complexed enantiomer compared to the weaker complexed enantiomer. Thus, the weaker bound enantiomer is detected first.  

Are There Screening Approaches I Can Use in Method Development?

In practice it is common to use a variety of potential operating conditions to assess which operating conditions may prove useful. Standard sets of buffers and CD's may be assessed in an overnight sequence to discover which conditions provide some enantioseparation. These conditions are then optimized in terms of CD concentration and other factors such as buffer concentration/composition. Deeb et al.

 recently used a screen of 22 different CDs to optimize the separation of 14 different chiral compounds. They also systematically evaluated a series of operating parameters such as CD concentration, buffer type/concentration and the addition of organic solvents. 

A strategic approach to the development of capillary electrophoresis chiral methods for pharmaceutical basic compounds using sulphated cyclodextrins has also been published.

 More general method development strategies for the enantioseparation of drugs by capillary electrophoresis using cyclodextrins as chiral additives have also been published.

  Generic capillary electrophoresis conditions for chiral assays are often used in early pharmaceutical development and conditions have been published.

Especially pure CDs are not necessarily required for successful enantioseparations. In fact, many reported methods have been achieved using randomly substituted derivatives. However, randomly substituted CDs are a mixture of isomers differing in their degree of substitution (i.e., the number and the position of the substituents). Therefore, randomly substituted CDs from various suppliers may differ in this respect and differences may even be observed from batch-to-batch. Literature examples clearly demonstrate that the source of the CD and the degree of substitution affects the resolution in CE enantioseparations of several compounds while this may have no effect for other analytes. Even reversal of the enantiomer migration order has been observed when switching from a CD with low isomeric purity to a quality with high isomeric purity.

An illustrative example of the effect of CDs from different sources on the enantioseparation of ropivacaine is shown in Figure 4. While the separation of the minor (R)-enantiomer could be achieved with 2,6-dimethyl-β-CD from 2 suppliers, the product from Supplier 3 failed to resolve the enantiomers under the experimental conditions applied. This is because the CDs differ in their degree of substitution, as not all 2 and 6 positions of β-CD may be derivatives or methylation of the 3-hydroxy groups may have occurred as well. The example clearly demonstrates that variations in the degree of substitution of randomly substituted CDs can affect the robustness of the method and has to be considered during method validation. CDs of various suppliers and different batches should be evaluated during the process. Generally, it cannot be predicted if a higher or lower degree of substitution of a given CD results in a better enantioseparation, examples for both scenarios have been reported. With regard to method robustness single isomer CDs have a clear advantage when equally good enantioseparations are observed for both types of CDs. 

Figure 4: Dependence of the enantioseparation of (R)- and (S)-ropivacaine on the source of the cyclodextrin. Experimental conditions: 72 cm, 50 Î¼m i.d. fused-silica  capillary, mM sodium phosphate buffer, pH 3.0, containing 13.3 mg/mL 2,6-dimethyl-Î²-CD, 30 Â°C, applied voltage 27 kV. (Reprinted with permission from C. SÃ¤nger-van de Griend, Enantiomeric Separations by Capillary Electrophoresis in Pharmaceutical Analysis, PhD thesis, Acta Universitatis Upsaliensis, Uppsala 1999, ISBN 91-554-4561-6)			

How Much CD Do I Need to Add to Achieve My Separation? 

There is no general rule how much of a certain CD is necessary to achieve an enantioseparation as this will vary with the type of the CD, the analyte and the separation problem. The separation depends on the formation of the CD-analyte complexes as well as their electrophoretic mobilities (see Equation 3). Thus, if large differences of the complexation constants between the CD and the analyte enantiomers exist, relatively low concentrations of the CD will suffice to achieve an enantioseparation while higher concentrations may be necessary in the case of small differences between the complexation constants. The strong electrostatic interactions between oppositely charged analytes and CDs often allow the use of very low selector concentrations. For example, in the case of enantioseparations of protonated amines by negatively charged CDs efficient separations at CD concentrations in the range of 0.5–1 mg/mL have been reported. 

Sulphated cyclodextrins have multiple negative charges and, therefore, genearate high operating currents if used in high concentrations. Therefore, their use is limited to low concentrations or using narrow bore capillaries and/or cooling devices to limit the current. 

If only a chiral separation is desired (i.e., resolution R

 = 1.5) lower concentration may be sufficient compared with the determination of the enantiomeric excess when a low concentration of an enantiomeric impurity has to be determined in the presence of a large excess of the eutomer (desired enantiomer). Then higher concentration of CD may be necessary. However, one should keep in mind that optimum CD concentrations may exist resulting in lower resolution after the maximum. The choice of the CD and the optimization of the CD concentrations are among the most important variables in chiral CE.

What Other Additives Can I Use if CDs Don't Work?

Other chiral selectors are available but have been less frequently used as a result of limited availability, applicability with regard to analytes, or experimental problems including adsorption to the capillary wall. Consequently, only a few validated and robust methods have been reported using these selectors. Macrocyclic glycopeptide antibiotics such as vancomycin or teicoplanin have been successfully applied to the enantioresolution of acidic compounds.

  The chiral crown ether, (+)-(18-crown-6)-2,3,11,12-tetracarboxylic acid, is suitable for enantioseparations of primary amines and amino acids.

  The enantioresolution of amino acids and their derivatives has been achieved by ligand exchange employing copper(II)-complexes of amino acids or amino acid derivatives.

  Chiral ion-pairing reagents such as cinchona alkaloid derivatives or camphorsulphonic acid proved to be effective selectors in non-aqueous capillary electrophoresis.

  Further selectors include linear polysaccharides and proteins. In micellar electrokinetic chromatography (MEKC) and microemulsion electrokinetic chromatography (MEEKC) enantioseparations using chiral detergents such as bile acids or amino acid derivatives have been described.

Enantioselective CE methods have been applied to analytical processes in the chemical, pharmaceutical, food and cosmetics industry as well as in forensic and environmental sciences. A specifically challenging area in pharmaceutical analysis is the determination of the stereochemical purity of a compound when the stereochemical impurity has to be quantified in the presence of a large excess of the other stereoisomer. Overloading the CE system creates problems ranging from peak distortion to loss of resolutions. Nevertheless, chiral CE methods have been successfully developed and validated. 

Table 3: Examples of validated CE methods for the determination of the chiral purity of drugs.12			

Some recent examples are summarized in Table 3. It can be clearly seen that most assays are able to detect 0.1% of the impurity, the identification threshold defined by the ICH guidelines. In some cases the separation of all stereoisomers of compounds with multiple stereogenic centres has been achieved as illustrated for galantamine featuring three stereogenic carbon atoms (Figure 3). All seven distomers (undesired isomers) could be separated from the eutomer (desired isomer).

  Several methods also allow the simultaneous determination of other (achiral) related substances.

Figure 3: Electropherogram of the separation of galantamine (R113675) and its stereoisomers. Experimental conditions: 50/57 cm, 75 Î¼m i.d. fused-silica capillary 50 mM sodium phosphate buffer, pH 3.0, containing 4.9 mg/mL Î±-CD, 20 Â°C, applied voltage 15 kV. (Adapted from reference 20 with permission from LCGC Europe)			

Articles

CE Currents

Describing the theoretical background on how the separations occur, the operating approaches that can be taken and method development.

Using Cyclodextrins to Achieve Chiral and Non-chiral Separations in Capillary Electrophoresis

Gelatin nanoparticles are used as a novel, biodegradable and well-tolerated drug carrier in tumour therapy and numerous other diseases. For a valid formulation approach in clinical studies an in-depth understanding of the molecular weight characteristics of this biopolymer is essential. Asymmetrical Flow Field Flow Fractionation (AF4) analysis was shown to be a fast and reliable analysis method for the pre-formulation screening of standard hydrophilic and hydrophobic prototype gelatins and also for mucoadhesive thiomers.

Polymer and protein-based drugs are becoming more common in the pharmaceutical industry and asymmetrical flow field-flow fractionation (AF4) offers a number of advantages over existing techniques, particularly for formulations containing polymers and nanoparticles. The interest in AF4 has grown since Giddings' break-through work in the nineties

  and the subsequent research by Fraunhofer

  has helped the technique gain wider acceptance and use. By combining this technique with multiangle light-scattering detectors (MALS), polymeric active ingredients can now be separated from polymeric excipients and particulate structures such as nanoparticles or virus-like particles (VLPs).

Expert knowledge and practical expertise in this technique is, however, somewhat limited, but the advantages of AF4 are becoming more widely accepted. This article describes novel work in polymer and nanoparticle research and highlights the importance and potential of AF4 in this emerging field.

In practice established methods for protein and polymer analysis, such as reversed-phase high performance liquid chromatography (RP HPLC), size exclusion chromatography (SEC) and fluorimetry are often limited (e.g., shear force destruction of protein aggregates in stability studies due to the presence of the stationary phase or the need for fluorometric moieties in the sample). A typical packed column for these techniques requires high pressure — but this is not the case for AF4. 

The separation principle of AF4, however, is based on a differential flow of a solvent in a channel and a respective perpendicular cross-flow to separate the analytes only by hydrodynamic properties in a fast, non-destructive, one-phase separation mechanism. One phase, non-destructive separation ensures very gentle separation conditions for large biomolecule analysis and aggregate detection, a rapid cost-effective analysis time and less unwanted interactions because of the small surface area of the channel compared with packed columns. Additionally, the smallest molecules can be analysed simultaneously with large proteins, aggregates or nanoparticles, which means AF4 offers a wider dynamic range than other chromatographic methods. 

Figure 1 shows a schematic diagram of this separation channel. In theory macromolecules between 1  kDa and several GDa or particles between 2  nm and 100  μm can be separated by AF4.

Figure 1: Schematic drawing of an AF4 channel. 

Nanoparticles have the potential to offer numerous advantages for targeted, safe and effective drug delivery,

  especially when made of biocompatible and biodegradable polymers. Such nanoparticles could be useful for the targeted delivery of drugs to improve bioavailability, sustain drug effects at the target site, solubilize drugs for intravascular delivery and improve the stability of therapeutic agents against enzymatic degradation.

  Additionally, by modulating the polymer characteristics, the release of a therapeutic agent from nanoparticles can be controlled to achieve the desired therapeutic efficacy.

Gelatin nanoparticles, for example, are a promising drug carrier system for future applications in various new approaches in gene therapy.

  Innovative gelatin prototypes with modifications of the backbone offer a further improvement regarding enhanced drug loading and modified targeting properties 

The aim of this investigation was to characterize the molar mass profile of two newly modified gelatin prototypes by AF4 and compare them with standard gelatin and fractionated gelatin, where low molecular weight (lmw) gelatin was removed from high molecular weight (hmw) gelatin. A thorough knowledge of the molar mass profiles in these highly lmw-reduced samples and in the prototype samples is mandatory for all nanoparticle formulation steps from gelatin as well as from other polymers such as chitosan. Hence, we also examined the molecular weight fractions of highly different chitosan–thiomer batches modified in two ways with sulphydryl groups and prompting different viscosities and chain lengths. In the course of method development we determined the optimum settings in terms of optical detector parameters as well as the correct type of membrane and elution profile for the separation of hydrophobic large proteins.  

With this data, an improved formulation process for nanoparticles was developed based on the traditional desolvation method developed by Coester.

  The physicochemical characterization of all nanoparticles was done by static light scattering (SLS) and compared with established gelatin nanoparticle formulations in terms of size, zeta potential and polydispersity index (PI).  

 As well as two hydrophobically modified gelatin prototypes (Gelita, Eberbach, Germany) called MS and MA, with succinate and dodecenylsuccinate residues, standard gelatin type A (Bloom ~175) from porcine skin (Sigma Aldrich, Munich, Germany) was analysed in this study. As control experiments in turn, measurements with two customized Gelita batches (VP306/VP413-2) that possessed less than 20% (w/w) peptides < 65  kDa were conducted. The AF4 analysis of these gelatins was performed on an AF1000-FOCUS system (Postnova, Landsberg am Lech, Germany) coupled with a UV detector (UV100 Thermo Scientific, Egelsbach, Germany), an RI detector (n-1000 WGE Dr. Bures, Germany) for concentration detection and a static light-scattering detector (miniDAWN Wyatt Technology Corporation, Dernbach, Germany) for molecular weight determination. The laser wavelength accounted for 690  nm, while slice collection was set to 1200. For molar mass determination the refractive index (RI) increment was set to 0.174  mL/g and the second virial coefficient was set to 0. The separation was achieved using a PBS buffer pH 6.0 as the mobile phase, a channel with 350  μm height and an ultrafiltration membrane consisting of regenerated cellulose with 5  kDa cut-off (Postnova). All proteins were dissolved in analysis buffer at a concentration of 2.5%. The channel flow-rate accounted for 1  mL/min, while the cross flow was adjusted to 0.05  mL/min over 10  min and then reduced to 0  mL/min, which resulted in a total measurement period of 20  min. 

 The modification of the chitosan materials (Sigma) was conducted according to protocols described elsewhere.

-acetylcysteine (Sigma) (lyophilized); chitosan low viscosity modified with thiobutylamidine (Sigma) (lyophilized); chitosan low molecular weight modified with 

-acetylcysteine (lyophilized) and chitosan low molecular-weight modified with thiobutylamidine (lyophilized) were investigated with the same AF4 hardware set-up as for gelatin. The solvent and the running buffer for the chitosan samples were made of 0.3  M acetic acid, 0.2  M sodium acetate and sodium hydroxide/hydrochloric acid q.s. The pH was adjusted to 4 at a chitosan concentration of 0.1%. A membrane consisting of regenerated cellulose with a cut-off of 10  kDa was used in a 350  μm separation channel. The detector's dn/dc was set to 0.163  mL/g and the second virial coefficient to 0. For chitosan the cross flow was set to 1.0  mL/min at a channel flow of 1.0  mL/min while the focus time amounted to 350  s. The complete measurement period was 25  min. 

 Microviscosimetry experiments were performed using an AMVn microviscosimeter (Anton-Paar, Ostfildern, Germany). The viscosity of all investigated polymer solutions was determined by examining the rolling time of a steel sphere under the influence of gravity in an inclined cylindrical tube filled with the sample liquid. To ensure a constant temperature of 40  °C ± 0.01  °C, a built-in peltier was used. The viscosity was then calculated using the laws of Stoke:  

 being the frictional force, η the fluid viscosity and 

 the diameter of the spherical object. The molecular weight was approximated with the Mark-Houwink equation.

 Nanoparticles from Sigma gelatin were prepared using the established two-step desolvation technique.

 In brief, a first desolvation step was performed with acetone (Sigma) as an antisolvent to remove the low molecular weight fractions of Sigma gelatin. After resolvation of the sediment with 40  °C warm highly purified water, nanoparticles were formed in a second desolvation step under constant stirring by addition of acetone at pH 2.5. The 

 nanoparticles were then stabilized by crosslinking with glutaraldehyde (Sigma). Before further analysis the nanoparticles were centrifuged and washed twice with highly purified water.  

The MA and MS prototype gelatin nanoparticles were prepared from a 1% solution of gelatin by a novel desolvation method including several modifications to the previously mentioned two-step desolvation method: for succinylated gelatin the pH was set to 10, while for dodecenylsuccinylated gelatin the pH could be varied in a range from 2.4–10 to reach particles in the lower nanometer range. For a higher precision in the desolvation and to ensure a good size control, a peristaltic pump (Miniplus 3, Abimed Gilson, Langenfeld, Germany) was combined with an immersed needle for the first time where acetone is added via a 26  G steel needle (Sterican, Braun, Emmenbruecke, Germany) into the stirred solution. Crosslinking was achieved by the addition of glutaraldehyde, however, at a different concentration and pH.

The chitosan nanoparticles were prepared by ionic gelation in 0.05% acetic acid solution at a polymer concentration of 2.5% (w/v) and a pH of 5.5. After complete dissolution of the polymer at 40  °C, a 0.2% (w/v) solution of sodium triphosphate pentabasic (Sigma) as the counter polyanion was added dropwisely (5  mL/min) under constant stirring until nanoparticles were formed. The final crosslinking was done by adding 10  μL of a 1  mM iodine (Sigma) solution. The anions and iodine were removed by dialysis against 0.1  M HCl over 12  h. 

The size distribution of all nanoparticles was analysed in aqueous dispersion by SLS (LA-950 laser difractometer, Retsch Technologies, Haan, Germany). Each size value and corresponding polydispersity index was the mean of 10 subruns. Static light scattering was used to screen larger agglomerates. All experiments were conducted with a refractive index of 1.59 (i

 = 0.01) and highly purified water as the dispersion medium. The zeta potential of the nanoparticles was measured with the Zetasizer Nano (Malvern) and flow through cells in highly purified water under controlled ionic strength conditions. All measurements were conducted in triplicate. 

 At first, gelatin bulk material from Sigma-Aldrich was analysed to gain a benchmark for the following investigations of the modified samples. The molar mass was determined to comprise sizes ranging from 10  kDa to above 10000  kDa (Figure  2), which confirmed the data reported by Fraunhofer

  and exceeded the findings from size exclusion high performance liquid chromatography–MALS (SE-HPLC–MALS) analysis

  by more than one order of magnitude. The discrepancy between sizing data obtained from SE-HPLC and AF4 reflects the fundamental differences between these two separation techniques. While SE-HPLC separation takes place in a packed column, AF4 uses an open channel leading to lower hydrostatic pressure and therewith lower shear forces on the samples are encountered during analysis. High molecular weight specimens particularly suffer from degradation by increased shear forces and are, therefore, preserved and can be detected during AF4 analysis.

Figure 2: Molecular weight distribution of standard Sigma gelatin. UV (curve) and MALS (dotted line) signal. 

Figure  2 also shows how the high molecular weight fractions of gelatin almost elute over the whole experimental period. As a result of the broad variety of molecules possessing different molar masses in gelatin bulk material, a baseline separation of particular portions is excluded. Thus it was decided to only apply a weak separation force to expand the elution of the blend of molecules over a prolonged period to demonstrate the broad molecular variety within gelatin. A thorough understanding of the molecular weight distribution of natural polymers is essentially important for the formulation scientist. As will be discussed later, by delpeting certain fractions of gelatin, smaller and more homogenously distributed nanoparticles can be generated. 

While very fast analysis is, of course, always possible with AF4 we demonstrate that the broad molecular weight distribution of the analysed gelatins has important implications in nanopartcile formulation. In this particular experiment, however, our goal was to highlight the broad molecular weight distribution of these gelatins, rather than a superfast analysis (which is, of course, possible). 

As only the high molecular weight fraction of Sigma gelatin can be used for the preparation of homogenous nanoparticles it generally has to be processed by two-step desolvation. Manufacturing experiments in turn, conducted with two customized Gelita batches (VP306/VP413-2) that possessed less than 20% (w/w) peptides < 65  kDa resulted in successful one-step desolvation synthesis of gelatin nanoparticles exhibiting equivalent size and size distribution.

 These findings reveal the restriction that has to be especially made for the presence of low molecular weight portions in gelatin batches designated to one-step desolvation. The successful depletion of the low molecular weight fraction of gelatin is demonstrated in Figure  3.  

Figure 3: UV signal (continuous line) and molecular weight (dots) calculated from respective UV and MALS data resulting from AF4 analysis of gelatin bulk material VP413-2 developed and provided from Gelita; the circle marks the low molecular-weight fraction. 

In addition, gelatin sediment obtained from two-step desolvation after the first desolvation step — as the result from fractionation and used for the preparation of nanoparticles — also underwent AF4 analysis. Data from these experiments and from gelatin bulk material are displayed as function of their mean molecular weight in Figure  4.  

Figure 4: Mean molecular weight fractions calculated from respective UV and MALS data resulting from AF4 analysis of (1) gelatin bulk material purchased from Sigma-Aldrich, (2) gelatin bulk material VP306, (3) VP413-2 developed and provided from Gelita, and of (4) gelatin sediment obtained after the first desolvation step from the manufacturing process of the gelatin nanoparticles. 

Interestingly the clear shift of the mean molecular weight of the gelatin sediment (4) by more than one order of magnitude compared with the bulk material (1) is not a prerequisite for a successful one-step desolvation. A mean molecular weight between 400 and 500  kDa determined for the Gelita batches VP306 and VP413-2 was already sufficient to allow the new production process. Thus, derived from these findings and the specification of the applied gelatin batches a mean molecular weight of ~500  kDa and a threshold of a maximum of 20% (w/w) for the portion of low molecular weight fractions < 65  kDa could be defined as prerequisite for the successful manufacturing of gelatin nanoparticles by a one-step desolvation procedure. 

The mean molecular weight of gelatin sediment ranges clearly above the one of the Gelita batches, which may not only be attributed to even more reduced amounts of peptides <  65  kDa far below 20% in the sediment. Thus, the fractionation of gelatin bulk material during two-step desolvation supposedly led to a depletion of molecular weight fractions bigger than 65  kDa. 

In the process of method development for the analysis of MA and MS gelatins, several ultrafiltration membrane types were tested. After experiments with different materials and cut-off values regenerated cellulose with a cut-off of 10  kDa proved to be the most adequate. The results in terms of recovery rate, repeatability and signal quality are presented in Table  1. Regenerated cellulose is a very low protein binder and therefore ideally suited for analyses that require maximum sample recovery. In addition the membrane possesses a good solvent resistance with both aqueous and organic solvents, and is able to work over a wide pH range.  

Table 1: Influence of the different membrane types on recovery rate and repeatability (defined as the intra day repeatability of a 100% value in per cent of six replicates).  

The derivated hydrophobic prototype gelatins showed a molar mass distribution from 140–10000  kDa and 200–100000  kDa for MS and MA, respectively. While the average molecular weight of MS was 218  kDa, MA showed an average molecular weight of 395  kDa. The molar mass distribution of standard gelatin was found to be between 140–1000  kDa with an average molar mass of 158  kDa. (Figure  5). This is in accordance with the prior studies, where even fractions up to 10000  kDa were detected. The average recovery was about 97.4%.   

Figure 5: AF4 signals of the examined gelatin batches MALS (dots) and UV signals (curves). Key represents MALS signals.  

For the analysis of chitosan, the cumulative mass distribution was plotted for a better comparison with the gelatin samples. As seen in Figure  6 the distribution of molecular weight fractions in chitosan is much broader than for gelatin (Figure  7). Interestingly, chitosan lmw modified with thiobutylamidine as a potential nanoparticle crosslinker showed an increased amount of low molecular weight fractions compared with the unmodified chitosan lmw samples. A polymer crosslinking throughout the small molecular weight range could be the potential reason for this data. In contrast, the thiobutylamidine modification of low viscosity chitosan lead to higher molar mass profiles over the whole range, which might be based on the natural origin of chitosan and also on a partial depolymerization during the sulphhydryl modification process.  

Figure 6: Cumulative weight fractions of chitosan samples. 

Because the chitosans were modified with the potentially crosslinking sulphhydryl groups we compared the total amount of free sulphydryl groups and the existing disulphide bonds to the calculated molar masses. In Figure  8 these three parameters were correlated and it was shown, that a constant amount of disulphide bonds throughout the samples does not automatically account for higher molar masses of the polymers. The influence of these modifications is given exemplarily for the case of TBA-modified chitosan in Figure  9. For the 

-acetylcysteine modification of chitosan lmw, the viscosity was so high, that a molar mass calculation could not be made. In all other cases the molar separation and molecular weight calculation was successful and reproducible. In conclusion, AF4 analysis was able to give a good idea of what the molecular weight distribution of the chitosan samples looks like and where modifications of the backbone lead to different retention behaviour.  

Figure 7: Cumulative molar mass distribution within the gelatin samples. 

 The molecular weight results from AF4 were in accordance with the calculated values from automatic microviscosimetry via the Mark-Houwink equation (Table  2). A correlation factor of 1.0 stands for an optimum compliance of the calculation with the measured values.  

Figure 8: Comparison of the calculated molecular weights with disulphide bonds and free sulphhydryl groups in the chitosan samples. The CS-NAC low-molecular-weight-sample was too viscous for analysis. 

Nanoparticle formulation and characterization:

 The prototype gelatin nanoparticles were prepared from a 1% solution of gelatin by a single desolvation method including several modifications to the above mentioned two-step desolvation method: the pH for negatively charged MS gelatin nanoparticles had to be adjusted to 10 for a homogeneous and small particle size, while MA gelatin with long hydrophobic side chains lead to nanoparticles in the whole pH range from 2.5–10. Paying tribute to the changed physicochemical properties of the protein, inert glass stirring beads had to be used for the preparation process to prevent aggregation during desolvation. Furthermore, the amount of acetone needed for desolvation and the amount of glutaraldehyde as a crosslinker had to be optimized because several changes in the functional groups of the protein had occurred during the prior modification.  

Figure 9: Molar mass signals of chitosan samples. 

Resulting MA nanoparticles were 193  nm ± 16  nm (mean ± SD; n = 3) in size with a polydispersity index (PDI) of 0.107, while MS nanoparticles were larger, with 362  nm ± 22  nm (mean ± SD; n = 3) and a PDI of 0.053. Statistical analysis of the data was performed by a one way analysis of variance (Table  3).  

Table 2: Molecular weight of Sigma gelatin and modified gelatin prototypes determined by automatic microviscosimetry compared with AF4 (mean value). 

Chitosan nanoparticles prepared from the modified samples resulted in small and stable nanoparticles (Table 3). However, their polydispersity index was much higher than for the gelatin nanoparticles.  

Table 3: Size and distribution of the nanoparticles as measured by SLS and zeta potential (n=3). 

Regular article

This article describes some of the latest developments for the analysis of polymers and nanoparticles.

Analysis of Polymers and Protein Nanoparticles using Asymmetrical Flow Field-Flow Fractionation (AF4)

In the past decade high performance liquid chromatography (HPLC) has emerged as a technique for the separation of complex proteomic samples because of its outstanding chromatographic resolving power,

  the possibilities to automate the analysis (ease-of-use and outstanding reproducibility)

  and its compatibility with mass-spectrometric (MS) detection using electrospray (ES) interfacing.

A good performance criterion for the gradient separation of peptides is peak capacity, which is defined as the maximum number of peaks that can be separated with a resolution of 1 and elute in the applied gradient window.

  The maximum peak capacity obtained in one-dimensional (1D) LC is mainly determined by the column technology (column length and particle size) and the duration of the gradient. The maximum allowable column length is determined by the permeability of the chromatographic bed and the maximum pressure drop of the HPLC instrumentation.

  Whereas fast separations are typically obtained on short columns packed with small (<2 μm) silica particles, high-efficiency 1D-LC separations are obtained on long columns packed with a slightly larger particle size applying long gradients.

Whereas 1D-LC allows the separation of hundreds of analytes, multidimensional separation approaches have the potential to separate thousands of components.

  Of all the 2D-LC techniques, off-line 2D-LC (or LC×LC) offers the most flexibility in terms of separation modes and LC conditions, because matching eluents, flow-rates and transfer volumes are less critical than in on-line 2D-LC.

  Moreover, off-line 2D-LC allows re-analysis of samples when partial injection of the fractions is applied. Because peptides can be pre-concentrated and desalted between the two dimensions, external band-broadening due to the second-dimension injection volume must be minimized.

  Consequently, for proteomics separations a large (1  mm) i.d. first-dimension column is typically applied, providing high sample capacity, and a small (75  μm) i.d. column is applied as second-dimension column, providing high mass sensitivity and easy coupling with MS. 

To use the full peak capacity offered by comprehensive LC×LC the separation mechanism used in the first dimension should be independent of the retention mechanism in the second-dimension separation and none of the separation achieved should be lost due to undersampling (i.e., transferring too few fractions to the second-dimension column). In this case, the maximum 2D-LC peak capacity (

 is the peak capacity obtained in the first dimension and 

 the peak capacity obtained in the second dimension. 

This article describes an optimization strategy to obtain the best possible performance in the shortest analysis time — called the peak production rate — for comprehensive off-line two-dimensional LC. 

Acetonitrile (ACN, HPLC supra-gradient quality) and trifluoroacetic acid (TFA, ULC–MS quality) were purchased from Biosolve (Valkenswaard, The Netherlands). Sodium dihydrogenphosphate (·2 H

O) and sodium chloride (analytical reagent grade) were purchased from Sigma-Aldrich (Steinheim, Germany). Ortho-phosphoric acid (85%) was obtained from Bio Lab (Jerusalem, Israel). 

For column testing (determination of peak capacity) a digest of cytochrome 

 and a six-protein-mixture digest containing tryptic peptides of transferrin, bovine serum albumin, β-galactosidase, alcohol dehydrogenase, lysozyme and cytochrome 

 (Dionex) were used as test samples. For 2D-LC experiments a nine-protein tryptic digest of the six proteins listed above plus β-casein, myoglobin and a monoclonal antibody (MAb) was used, as well as an 

Acclaim PepMap nanoLC columns (150 and 500  mm length; 75  μm i.d.) packed with 3 μm, 100  Å C18 particles (Dionex) were used for reversed-phase peptide separations. Peptide pre-concentration and desalting were performed prior to a second-dimension separation on a 5 × 300  μm i.d. mm trap column packed with Acclaim PepMap 5  μm, 100  Å C18 particles. A 1 × 150  mm i.d. column packed with polypeptide-coated strong-cation-exchange silica particles packed of either 3 or 5  μm average diameter with 300  Å pores was used for the IEX experiments. 

Instrumentation, configuration and LC conditions:

 All HPLC experiments were performed using an UltiMate 3000 Proteomics MDLC system (Dionex)) equipped with a membrane degasser, ×2 dual-gradient pump, a thermostatted flow manager, a well-plate sampler and two UV detectors. MS–MS data were generated with an ion-trap mass spectrometer (HCTultra, Bruker, Bremen, Germany) coupled on-line to the LC system via an ESI source. The mass spectrometer was operated in the positive ionization (PI) mode in the scan range from 

 = 300–1600, using a dry-gas stream of 4  L/min, nebulizer gas at 138  kPa, drying temperature of 300  °C and a target mass set to 

 = 800. Proteins were identified through a peptide search using the MASCOT software package (Matrix Science, London, UK). 

In the 1D-LC set-up, the nanoLC column was placed in the column compartment and connected with 20  μm i.d. tubing between the injector and the UV detector (containing a 3  nL Z-shaped detector flow cell). Injection volume = 1  μL, flow-rate = 300–1000  nL/min, mobile phase A = 0.05% aqueous TFA, mobile phase B = 80:20 ACN:H

O containing 0.04% TFA; gradient = 4–55% B, UV detection at 214  nm.  			

Figure  1 represents the schematic diagram of the 2D-LC system. The workflow for automated off-line 2D-LC includes: 					

A first-dimension ion-exchange separation using the well-plate sampler for both injection and automated fraction collection.

Repeated cycles of injection, preconcentration and desalting of the peptide on a trap column, and second-dimension reversed-phase separations of all the fractions. Tandem mass-spectrometric detection was performed to identify the peptides.

Figure 1: LC configuration for automated off-line 2D LC.						

 After injection of 2–10  μL (10  pmol) of a complex mixture of tryptic peptides, a linear salt gradient 0–600  mM NaCl in 5  mM phosphate buffer was applied at a flow-rate of 50  μL/min. Mobile phase A = 95:5 H

 buffer pH = 3, mobile phase B = mobile phase A + 1 M NaCl, gradient = 0–60% B, column temperature = 25  °C, UV detection with 45  nL flow cell at 214  nm. In three different series of experiments 50  μL fractions were collected every 1, 2 and 5  min. 

The second-dimension separation included 5  min on-line sample pre-concentration and desalting of the peptides using a trap column at a flow of 40  μL/min, followed by the reversed-phase separation of the peptides on a 15  cm long nanoLC column. Injection volume = 20  μL, flow-rate = 750  nL/min, mobile phase A = 0.05% aqueous TFA, mobile phase B = 80:20 ACN:H

O containing 0.04% TFA; gradient = 2–55% B, gradient time = 20  min, wash step at 90% B for 2.5  min; equilibration time = 12.5  min, column temperature = 60  °C. 

Peak capacity in ion-exchange (IEX) chromatography is mainly determined by the IEX conditions, such as gradient slope and time and the column technology applied. The strong-cation-exchange (SCX) separation of a six protein mix digest was performed on a 150  mm column packed with 5  μm peptide-coated SCX particles applying a gradient time of 20  min [Figure  2(a)]. Most of the tryptic peptides were doubly and triply and positively charged. Figure  2(b) and (c) show the SCX separation executed on a 250  mm long column packed with 3  μm particles and applying gradient times of 20 and 33 min, respectively. When applying the same gradient time, while increasing the column length and decreasing the particle size, a significant increase in peak capacity was obtained. When scaling the gradient time in proportion to 

 to 33 min the peak capacity was further increased.  

Figure 2: Strong cation-exchange separation of a six protein mix digest on a 15 cm column packed with 5 Î¼m particles applying a gradient of 20 min (a) and a separations on a 25 cm column packed with 3 Î¼m particles applying a gradient time of 20 (b) and 33 min (c), respectively.			

  showed that the sampling time applied for the second dimension (

D separation) should be adjusted to 2–4 times the standard deviation of a first-dimension (

D peak). This yields the best compromise between the time available for the 

D separations and maintaining separation obtained in the first dimension. Table  1 gives an overview of the effects of column length, particle size and gradient times on the optimal sampling time. The application of a 20  min gradient using a 150  mm column packed with 5  μm particles results already in a very high number of fractions (60) that need to be analysed in the second dimension. Even when applying short 10  min 

D gradients this results in a total analysis time of more than 10  h, not taking into account the gradient delay volume, column equilibration time, desalting time, etc.  

Table 1: Effect of column properties and gradient time on sampling time (2 cuts per peak) and the number of 1D fractions collected.			

When the first-dimension separation is 'undersampled', for example when the resolution obtained in the first-dimension is partially lost by the fraction collecting rate, the first-dimension peak capacity (

) cannot be higher than the number of fractions taken and is defined as:

 is the gradient duration in the first-dimension and 

 the sampling time. In case of undersampling, the easiest way to achieve a higher effective 

D peak capacity is by reducing the sampling time. Improving gradient time/slope or column technology is less effective than increasing the sampling time. 

A reversed-phase (RP) separation in the second-dimension ensures excellent solvent compatibility for interfacing to a mass spectrometer using electrospray ionization (ESI). To maximize the orthogonality between the two dimensions, 5% acetonitrile was added in the mobile phase of the 

D SCX separation. In this way hydrophobic interactions were suppressed. 

) in gradient-elution chromatography can be approximately defined as:

 is the duration of the second-dimension reversed-phase gradient, 

 the average peak width (which is approximately equal to four times the standard deviation, at σ), 

 the plate height. Equation  3 shows that peak capacity in gradient-elution chromatography depends on column technology (column length and plate-height value, 

. The latter parameter mainly reflects the particle size and the quality of the column) and LC conditions such as gradient time, and parameters that affect 

, such as flow-rate and column temperature. 

The effects of the column temperature, gradient time and flow-rate on the 

D peak capacity were systematically investigated using 150 and 500 mm long nanoLC columns packed with 3 μm silica C18 particles. When increasing the column temperature the mass-transfer in the mobile and stationary phases was enhanced, leading to narrower peaks and consequently higher peak capacities. The maximum peak capacity was obtained at a column temperature of 80  °C. With increasing column temperature a decrease in retention was observed, which can easily be counteracted by adjusting the initial and final compositions of the gradient. However, the trapping efficiency during desalting on a trap column was also decreased. This could potentially lead to break through of hydrophilic peptides. In addition, the column (chemically bonded phase and silica particles) may degrade more rapidly at high column temperature. Therefore, a column temperature of 60  °C was selected for further experiments — see Figure  3 for a typical separation example of a six protein mix digest.  

Figure 3: High-resolution chromatogram of the RP separation of a six protein mix digest on a 50 cm nanoLC Acclaim PepMap column (3 Î¼m silica C18 particles) applying a 120 min gradient.			

In general, longer gradient times yielded higher peak capacities. A strong increase in peak capacity was obtained when using relatively short gradients and operating the column at high flow-rates. The peak capacity was higher than that obtained when the column was operated at a flow-rate close to the optimum of the van Deemter curve, which may possibly be attributed to peak-compression effects. At longer gradient times the rate of increase in peak capacity was less steep. The maximum peak capacity of 390 on 15  cm columns was obtained at a flow-rate around the optimum of the van Deemter curve when applying a 120  min gradient. The peak production rate on a 50  cm column was significantly higher at all gradient times than that obtained on a 15  cm column. However, it should be noted that the required column-equilibration time also increases with column length. 

D gradient time on the 2D-LC peak production rate using 150 and 500  mm 

D columns. The peak capacity was estimated from experimental data by averaging the peak width at 4σ for at least five peptides and applying Equation  3. The total analysis time was calculated by summation of the 1D (ion-exchange) gradient time (10  min) and the product of number of fractions multiplied with the 

D time, taking into account the different pre-concentration/desalting times of 2 and 5  min, respectively, the gradient time, a wash step at high acetonitrile concentration for 2.5  min and the column equilibration times for the 150  mm (12.5  min) and 500  mm column (41.7  min), respectively.  

Figure 4: Effect of 2D gradient time on peak production rate for a 15 (triangles) and 50 cm (diamonds)) long nanoLC RP column applying a desalting step of 2 (open symbols) and 5 min (closed symbols), respectively			

The highest peak production rate is obtained for the 150  mm column when applying a 20  min 

D gradients the peak production rate is dominated by the time needed to desalt the peptide fractions. For longer 

D gradients the peak production rate decreases. The peak capacity increases slowly in this range, because of an increase in the average peak width of peptides at longer gradient times. The optimum peak production rate for the 500  mm column is significantly lower than that obtained with the 150  mm column and the optimum  is observed at a longer gradient time. The desalting time is less important because both the gradient duration and the equilibration time are longer for the 500  mm columns. 

Figure  5 shows the effect of sampling time on the 2D-LC performance for the SCX/×/RP separation (where the / indicates that this is an off-line approach) of a digest of a mixture of nine proteins, containing approximately 1000 peptides. A first-dimension gradient of 10  min was applied and fractions were collected applying sampling times of 5, 2 and 1  min, respectively. The fractions were pre-concentrated and desalted on a trap column and analysed on a 150  mm RP nanoLC column applying 20  min 

D gradients with UV and MS–MS detection. Figure  5 clearly shows the improved chromatographic performance (peak capacities around 400, 1000 and 2000) with decreasing sampling time, though obtained at the expense of analysis time.  

Figure 5: Effect of sampling time on the 2D-LC separation of a tryptic digest of a nine-protein mixture. Sampling times are (a), 5 min (b) 2 min and (c) 1 min respectively.			

Although a 25% decrease in total ion score was observed when decreasing the fraction collection time from 5  minutes to 1  minute, all proteins could positively be identified with a sequence coverage >29%. This is explained by the fast cycle time of the mass spectrometer; the cycle time is the time needed to isolate a precursor ion (MS) and measure the fragments after collision induced dissociation (MS–MS). When applying a cycle time of 2  s and analysing two precursor ions in MS–MS mode, the mass spectrometer can identify co-eluting peptides enhancing protein identification. 

Figure  6 illustrates the trade-off between the 1D-LC performance of proteomics separation on 150 and 500  mm long columns packed with 3  μm particles and the off-line 2D-LC performance under 'undersampling' conditions, applying optimized 

D gradients. It is evident that the use of longer columns in 1D-LC always yield higher peak capacity separations. However, it should be noted that in practice the column equilibration time also increases with column length. Under the applied conditions, 1D-LC is superior to 2D-LC for separations requiring a peak capacity of 400 (t

 = 80 min) or less. Higher peak capacities can be generated in 1D-LC using longer gradients. However, the gain in peak capacity per time unit is less than what can be obtained using 2D-LC.  

Figure 6: Trade-off between 1D-LC (black curves) and 2D-LC (red curves) using a 15 (triangles) and 50 cm (diamonds) RP (2D) column packed with 3 Î¼m particles and a comparison with 1D- and 2D-LC performance using 15 cm long columns packed with 1 Î¼m particles (dotted lines).			

Figure 6 also illustrates how the trade-off between the 1D-LC and 2D-LC performance may possibly be affected by future UHPLC column technology (assuming the use of 150  mm long columns packed with 1  μm particles). Theoretical peak capacities were calculated following an approach described by Neue et al.

  The effect of solvent composition on the retention factor was determined for 3  μm packed columns and its value was used to calculate the 1D-LC performance with 1  μm packed columns. The 1D-LC performance that theoretically can be obtained better than that currently offered by a factor of 2–3. In addition, the point where 1D-LC and 2D-LC show similar performance is shifted to shorter analysis times (40  min). When using shorter 

D columns this effect is further enhanced. 

An SCX/×/RP separation approach was developed using the micro-fractionation option of the autosampler, which allowed automatic fractionation of peptides after a first-dimension separation and re-injection, pre-concentration/desalting and separation of the fractions in the second-dimension. The LC conditions and column technology were optimized to maximize the peak production rate. When 'undersampling', changing 

An optimization strategy to obtain the best possible performance in the shortest analysis time for comprehensive off-line 2D-LC.

LCGC Europe-09-01-2009

Using Cyclodextrins to Achieve Chiral and Non-chiral Separations in Capillary Electrophoresis

Analysis of Polymers and Protein Nanoparticles using Asymmetrical Flow Field-Flow Fractionation (AF4)

Maximizing the Peak Production Rate in Off-line Comprehensive Two-Dimensional Liquid Chromatography with MS Detection

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