News from LabRulezLCMS Library - Week 17, 2025

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This week we bring you application notes by Shimadzu and Waters Corporation, presentation by Agilent Technologies and technical notes by Knauer and Thermo Fisher Scientific!

1. Agilent Technologies: Size Exclusion Chromatography of Biomolecules: Column Selection and Method Optimization

• Presentation
• Full PDF for download

SEC Nomenclatures

• Column volume
• Exclusion limit/void volume
• Interstitial volume
• Pore volume
• Total permeation
• Nonspecific interaction

Size Exclusion Chromatography (SEC) 

• Separation of biomolecules based on size
• Separation by size under native (nondenaturing) mode
• Relies on absence of interactions between the  analyte and the stationary phase
• Ideal for separating and analyzing intact proteins from contaminants, such as:
  • Aggregates
  • Excipients
  • Cell debris
  • Degradation impurities
• High salt concentration puts excessive wear  on instrument parts

Column Selection Criteria for SEC

• Pore size
  • Sample MW range
  • Exclusion limit
  • Maximize pore volume
• Particle size
  • Smaller particles → higher resolution
• Number of columns and length
  • Resolution versus analysis time
  • Shorter column length → higher throughput
  • Longer column length → improved resolution
• Column id
  • smaller column id → reduced solvent consumption, smaller injection volume, or improved sensitivity

Column Selection Criteria for SEC

Common challenges

• Limited resolution – insufficient/incorrect pore sizes can reduce resolution 
• Nonspecific interactions contribute to loss of sample, lead to inconsistent results, rework 
• Long analysis times – SEC is typically slow 
• Poor pressure stability creates rework and increases cost 
• Consistent and reproducible results are desirable
• High salt conditions puts excessive wear on instrument, parts 

Agilent Size Exclusion Columns

• AdvanceBio SEC (1.9 µm)
• AdvanceBio SEC (2.7 µm)
• Agilent Bio SEC-3 (3 µm)
• Agilent Bio SEC-5 (5 µm)
• ProSEC 300S (5 µm)
• ZORBAX GF-250 and GF-450 (4 and 6 µm)

2. KNAUER: Column choice based on Tanaka characterization - not all C18 columns are the same

• Technical note
• Full PDF for download

The Tanaka test is an accepted standard method for the evaluation of performance and selectivity of a reversed phase HPLC column [1]. The Tanaka protocol is based on six variables (hydrophobic retention factor, hydrophobic selectivity, shape selectivity, hydrogen bonding capacity, total ion exchange capacity, acidic ion exchange capacity) reflecting different chromatographic properties. Here we focus on the hydrophobic retention, hydrophobic selectivity and shape selectivity of the following KNAUER C18 phases: Eurospher II C18 (ES II C18), Eurospher II C18 A (ES II C18 A), Eurospher II C18 H (ES II C18 H), Eurospher II C18 P (ES II C18 P), Eurospher I C18 (ES I C18), and Eurosil Bioselect C18 (EB C18). The hydrogen bonding capacity and ion exchange capacities are not considered here because they are nearly similar for the examined phases. The hydrophobic retention factor (HR) reflects the surface area and surface coverage (ligand density). Hydrophobic selectivity (HS) is a measure of the surface coverage of the phase as the selectivity between alkylbenzenes differentiated by one methylene group is dependent on the ligand density. Shape selectivity (SS) is a dimension which is influenced by the spacing of the ligands and probably also the shape/functionality of the silylating reagent [1].

RESULTS

A hexagonal net diagram was used to display the measured Tanaka parameters as it enables good visual comparison of phases. For this type of diagram measured values are multiplied by certain factors. The measured values without multipliers are shown in Tab. A1 in the additional results section. Fig. 1 to 3 show the Tanaka plots for the tested phases. The values for the ion exchange capacity and hydrogen bonding capacity are quite similar for all and were therefore not considered. The biggest difference between the tested phases could be seen when comparing the hydrophobic retention factor (HR) - the higher this value the less polar the modification. Sorting the phases with ascending hydrophobic retention leads to the following order: EB C18 > ES II C18 A > ES I C18 > ES II C18 > ES II C18 H > ES II C18 P. The value for shape selectivity of the Eurospher I phase is slightly deviating. This may be due to an incomplete endcapping.

CONCLUSION 

The results obtained from the Tanaka test comparison can be used to assist in the choice of the most appropriate column for a given separation task. It is also important to know as much as possible about the chemical properties of the analyte. An analyte that is soluble only in a solvent with a high organic amount will have slightly or no retention on a C18 A phase. However, the C18 A phase can be operated with 100 % aqueous eluent without destroying the stationary phase. Inversely, a very polar analyte might have less retention on the C18 P or C18 H modification. However, due to their high carbon content they provide a high pH stability in an extended pH range. Furthermore, if the molecular weight of the analyte is above 2000 Da, a pore size of with 100 Å may be insufficient, making the so Eurosil Bioselect with a pore size of 300 Å the better choice. The KNAUER column portfolio offers classical and special C18 phases, making it easy to find the most appropriate column for a given application task.

3. Shimadzu: Simple Labor-Saving Calibration Curve Creation Using Autosampler Automatic Dilution Function Part 2

• Application note
• Full PDF for download

User Benefits

• The autosampler’s automatic dilution function reduces manual dilution preparation and organic solvent consumption.
• Simply specify the desired dilution ratio in the batch table, and use the same method file to automatically dilute solutions and create a calibration curve.
• Setting and management are easy when changing HPLC conditionssince a single method file is used regardless of the dilution ratio.

The dilution of standard and sample solutions for HPLC analysis is generally performed manually, using pipettes. However, such work is labor-intensive and time-consuming. In recent years, automation for the purpose of labor-saving is desired to improve work efficiency and productivity. When the organic solvent is a diluent, a large amount of solvent is consumed to prepare standard solutions for calibration curves in volumetric flasks, but the volume of sample solution required for HPLC analysis is only a few tens of μL or less. Using the automatic dilution function equipped with Nexera Autosamplers, it is possible to prepare a sample diluted at a userdefined factor and introduce it directly into the analytical column. The Application News 01-00717 describes a simple method for creating calibration curves using ultrapure water as a diluent. This article introducesthe analysis using organic solvent as a diluent.

Pretreatment Program and Operation Overview 

A method file contains information such as LC parameters, analytical parameters, and the pretreatment program. The pretreatment program can set various dilution ratios, such as a 100-fold dilution. In addition, when the program is used with the batch add-in (Fig. 2 on the next page), a single method file can be used regardless of the dilution ratio, thereby preventing human errorssuch as setup mistakes. 

The dilution factor and conditions related to the mixing process are configured using the LabSolutions workstation. The setup window for the autosampler pretreatment is shown in Fig. 1. Pretreatment program commands are shown in Table 1. In this article, the rinse solution was used as a diluent. 

A volume corresponding to the dilution ratio is aspirated from the stock solution vial and dispensed with the diluent into an empty vial (mixing vial) previously set in the autosampler (final volume is 100 μL in this example). The solution in the vial is mixed using the aspiration/dispensing function (pipetting). Finally, a specific amount of the solution is aspirated and injected into the column.

Analysis of Cinnamon 

A Sample of commercial Cinnamomum cassia was used. The pretreatment protocol is the same as the process up to filtration in Fig.3 from Application News No. 01-00233. Note that samples were manually diluted with acetonitrile at the final step of pretreatment in No. 01-00233-EN, but the sample was automatically diluted with an autosampler in this article. The pretreatment protocol is shown in Fig. 5. Acetonitrile was used as the extraction solvent. Lipids were removed using a dispersive solid phase extraction (dSPE) cartridge (Merck Supel QuE Z-Sep+). The cartridge eliminates the need to carry out conditioning before loading samples, which simplifies operations. 

Fig. 6 shows chromatograms obtained by diluting Cinnamomum cassia extracts 100-fold with acetonitrile using an automatic dilution function. The two target compounds were well separated from the contaminants. The analytical results (concentration after automatic dilution) are shown in Table 4. Table 4 also shows the analytical results obtained when standard solutions for calibration curves were prepared manually, and the 100-fold dilution with acetonitrile of the pretreated cinnamon extract was performed manually.

Conclusion 

By automatically preparing standard solutions for calibration curves at any dilution ratio and analyzing them directly, it was possible to create a calibration curve easily and accurately. In addition, when performing the determination of an actual sample, dilution could be performed automatically. It was confirmed that automatic determination was possible with only simple pretreatment. The calibration curve creation method described in this article is expected to lead to labor-saving for analysts and solvent-saving from a sustainability viewpoint.

4. Thermo Fisher Scientific: Setting the start position for flexible fraction collection by using custom variables in Chromeleon CDS

• Technical note
• Full PDF for download

Driven recently by the vigorous growth of biopharmaceutical, pharmaceutical, and chemical industries, an urgent need for the extraction of active or rare components in complex matrixes has emerged.¹ The Thermo Scientific™ Vanquish™ Fraction Collector, which is fully integrated into the Thermo Scientific™ Vanquish™ Analytical Purification LC system, can achieve fully automated fraction collection from analytical to semipreparative flow rates (up to 10 mL/min). The achievable fraction volume is extremely small with drop volume down to just 6 μL due to the fraction needle design. In addition, the fraction collection valve is designed so that residual fraction volume in the collection needle capillary and needle is pushed out into the fraction vessel by a “flush”, resulting in very low cross contamination rates of less than 0.15%.² 

The highlights of the purification hardware performance can only be achieved through a robust and simple yet flexible and multi-faceted chromatography data system. From the instrument method wizard to the sequence control and the data processing, the Chromeleon CDS provides rich versatility for specific fraction collection needs to address seamless integration into the purification workflow. Where and how a compound is isolated in fractions can simplify further downstream processes or analytics.

Generally, the default path for automatic fraction collection is one of the four modes "HorizontalSaw, Horizontal, VerticalSaw, or Vertical," as shown in Figure 1A, which address most of the collection needs. However, some specific applications might require more customized collection paths/areas beyond the above-mentioned default modes, as shown in Figure 1B. As shown in this technical note, the system is extremely flexible. For example, the simple insertion of a custom variable into the injection list through the user-friendly interface can be used to customize the starting position of fraction collection. Monoclonal antibody (mAb) samples were used to validate multiple collection modes, including single-component, multi-component, and peak-based fraction collection. An operation protocol for setting custom-defined fraction start positions is provided, facilitating flexibility, ease of use, and efficiency in the purification process.

Experimental

Instrument configuration 

The configuration of the Vanquish Analytical Purification LC system is described in Table 1 and includes a binary pump, autosampler, column compartment, UV detector, and fraction collector, and is controlled by the Chromeleon Chromatography Data System 7.3.1 and newer.

Results and discussion 

UHPLC method development for separation 

The optimized method showed that the crude mAb sample contains a main component presenting as a broad peak at 9.7 min (Figure 7A) as well as acidic (10.0 min) impurities. Although the sample concentration was increased 10-fold, with a maximum signal as high as 2,000 mAU, excellent resolution was still obtained as shown in Figure 7B. Thus, the Vanquish UHPLC system with ProPac WCX-10 column offers a reliable separation for protein samples even when high sample concentrations are analyzed.

Repeatability of UHPLC and single-component collection 

The repeatability of the chromatographic system and separation chemistry ensure the purity, precision, and reproducibility for fraction collection. Hence, the crude mAb sample was fractionated six times, successively (Figure 8). The peak at 9.667 min is mAb with average peak area of 38.9%, and its retention time RSD of mAb was 0.06%, as listed in Table 5. The obtained fractions were then reanalyzed using the same condition used for validating the fractionating repeatability.

Conclusions 

The Vanquish Fraction Collector controlled by Chromeleon CDS enables excellent purification combined with the flexibility of singlecomponent, multi-component, and biocompatible collection. The use of the collection start position custom variable, combined with rapid and accurate flow control, lets scientists reliably obtain purer samples for further research.

5. Waters Corporation: Oligo Mapping of mRNA Digests Using a Novel Informatics Workflow

• Application note
• Full PDF for download

Benefits

• A new informatics workflow featuring the waters_connect™ MAP Sequence App streamlines oligonucleotide mapping of mRNA digest data acquired using UPLC QTof MS
• RNase T2 enzymes (MC1 and Cusativin) offer unique cleavage specificity and opportunity to generate overlapping digestion products, achieving higher sequence coverage, compared to conventional RNase T1 digestion

The recent development and approval of two COVID mRNA-based vaccines has brought RNA-based therapeutics to the forefront of the biopharma industry.^1–3 The resulting need for rapid product development has necessitated development of analytics for the precise characterization of mRNA critical quality attributes (CQAs), including sequence and modification integrity. Two workflows were previously developed by Waters™ for directly assessing mRNA CQAs, namely 5’ capping efficiency measurement and Poly(A) Tail heterogeneity analysis, utilizing the waters_connect INTACT Mass App, while a different workflow utilizing the MAP Sequence App, was recently demonstrated for oligo mapping of 100-mer single guide RNAs.^4,5,6 

Conventional oligonucleotide sequencing techniques, like Sanger sequencing and next-generation sequencing (NGS) have been applied for sequence analysis of mRNAs, due to their cost effectiveness and throughput, but lack the ability for assessment of the many modifications that can arise during production and degradation of mRNA molecules. Alternatively, LC-MS based approaches known for their exceptional specificity, sensitivity, and quantification performance are becoming more popular, and readily address base and backbone modifications. ^7–10 Overall, for characterization of complex biologics, orthogonal techniques are desired to obtain a holistic view of product quality. 

LC-MS workflows for RNA digest oligo mapping have historically been laborious and time consuming, involving significant manual data analysis and curation. In a recent application note, we discussed a UPLC-MS and informatics workflow for automatically mapping sgRNAs sequences following individual digestion by an array of enzymes, including RNase T1 and RNase T2 enzymes (RapiZyme MC1 and Cusativin), and hRNase4.⁶ This application note extends the utility of the workflow (highlighted in Figure 1) to larger mRNA molecules digested by multiple RNA digestion enzymes, including two recently launched RNase T2 enzymes (RapiZyme MC1 and RapiZyme Cusativin), that have unique cleavage patterns that promote higher sequence coverage.^6,11 The rapid (<2 minutes) automated assignment of sgRNA digestion products and streamlined interface for data processing and review provided a significant advantage for sgRNAs and should provide even greater efficiencies for the more complex mRNA characterization exercise. In addition, digestion by RapiZyme MC1 and RapiZyme Cusativin was shown to provide superior results for the co-measurement of mRNA capping efficiency compared with the widely used RNase T1 digestion approach.

Experimental

LC Conditions

• LC-MS system: Xevo™ G3 QTof LC-MS with ACQUITY™ Premier, UPLC (Binary) System
• Column: ACQUITY Premier Oligonucleotide BEH™ C18 FIT Column 130 Å, 1.7 µm, 2.1 x 150 mm, (p/n: 186009487) 

MS Conditions

• MS system: Xevo™ G3 QTof Mass Spectrometer 

Results and Discussion

mRNA Oligo Mapping 

Three independent LC-MSE oligo map datasets were acquired for GFP mRNA sample digested with three different ribonucleases: RNase T1, RapiZyme MC1 and RapiZyme Cusativin. The three UPLC-MSE datasets were processed with the MAP Sequence App using the parameters highlighted in Figure 2 and the results were exported to the Coverage Viewer Micro App for quick visualization of sequence coverage. The three TIC chromatograms recorded for: RNase T1 (Figure 3A), Rapizyme MC1 (4A) and RapiZyme Cusativin (5A) are shown. MC1 and Cusativin are known to produce a significantly larger number of misses cleavages compared to RNase T1, and this enzymatic feature is clearly reflected in the complexity of chromatograms shown in Figures 4A and 5A^.6–9 

A comparison of the sequence mapping results (Figures 3B, 4B, and 5B) indicates that RNase T1 produced considerably lower unique coverage (~60%, 3B), compared to the MC1 (~97%, 4B) and Cusativin (~85%, 5B) analyses, because the number of ambiguously assigned digestion products was much higher. This is a direct result of the much broader specificity of RNase T1 (cleavage after every G residue), in contrast with MC1 and Cusativin cleavage specificity, which relies on very specific dinucleotide motifs.6–9 MC1 cleaves at the 5’-end of uridine residues, with three major cleavage sites (A_U / C_U / U_U) and two minor cleavage sites (C_A / C_G). Cusativin cleaves at the 3’-end of cytidine residues, with four major cleavage sites (C_A / C_G / C_U / U_A) and three minor cleavage sites (A_U / G_U / U_U). While RNase T1 adds a linear phosphate to the 3’-end of all its digestion products, both MC1 and Cusativin produce mainly digestion products with a 3’ cyclic phosphate. 

Compared to RNase T1, MC1, and Cusativin also have a higher capacity to generate controlled missed cleavages, therefore up to four missed cleavages were allowed for these two enzymes in the mRNA Cleaver prediction tool, while only two missed cleavages were applied for RNase T1. With more missed cleavages, both MC1 and Cusativin produced longer digestion products compared to RNase T1. These longer oligonucleotide products are more likely to have unique masses, reducing the chance for ambiguous assignments. As a result of these enzymatic features, the mapping results of MC1 and Cusativin exbibit better coverage values.

Conclusion 

• A new informatics workflow was demonstrated, featuring the waters_connect MAP Sequence waters App, which facilitated MS1 oligo mapping of mRNA digests using UPLC-MS acquired data 
• Two novel RNase T2 enzymes (RapiZyme MC1 and RapiZyme Cusativin) generated a greater population of fully digested oligonucleotides and missed cleavage oligos, with their unique digestion specificity compared to RNase T1, resulting in higher and more confident overlapping sequence coverage.
• Isomeric-digestion oligonucleotide products can be differentiated using the waters_connect CONFIRM Sequence App to match elevated energy fragment ions to sequences of isomeric oligos