A Virtual Symposium presented by LCGC and CHROMacademy

ChromTalks 2022: Getting Under the Hood of Chromatography

Cracking the Code of Complex Drug Modalities via MDLC–MS

Accelerating the Understanding of Metabolomics in Disease Through Improved Sensitivity

Effectiveness of High-Resolution Ion Mobility for Complex Analyses

Dealing with Wandering First-Dimension Peaks in 2D-LC Separations

Quantifying Smoke Taint in California Wines by Immersive Sorbent Sheet Extraction Prior to DART-MS

The Al Yergey Mass Spectrometry Scientist Awards will be presented to three recipients this year at the American Society for Mass Spectrometry (ASMS) conference, which is being held in Minneapolis, Minnesota. Gordon A. Anderson, Michael A. Grayson, and Martha M. Vestling will receive their awards right before the plenary lecture, on Monday, June 6, at 4:45 pm. The award recognizes dedication and significant contributions to mass spectrometry–based science by “unsung heroes.” It is named in memory of Al Yergey, a well-respected scientist who served for 45 years at the National Institutes of Health, where he was known as a dedicated mentor.

Anderson is being recognized for his significant, impactful, and sustained contributions to mass spectrometry (MS), along with his technical contributions, strength of character, and mentoring of junior scientists, all of which exemplify the spirit of the Al Yergey Award. Anderson is the chief engineer of the family-run enterprise, GAA Custom Electronics, broadly serving the MS community with a range of innovative and highly functional MS-specific electronic solutions.

Grayson is committed to preserving the history of ASMS as archivist, historian, and oral history interviewer, and as a representative to the Heritage Council of the Science History Institute. This commitment has resulted in the rich resources now available through the 

. Grayson, now retired, continues to actively contribute to the many projects of the ASMS History Committee.

Vestling has provided extensive service to the MS community with contributions to MS-based research. She has educated and trained students and users from diverse scientific backgrounds for five decades. Serving as the director of the mass spectrometry laboratory at the University of Wisconsin-Madison, she has developed a “go-to” facility for researchers on campus and many other biomedical science departments and units.

Articles

The Al Yergey Mass Spectrometry Scientist Awards will be presented to three recipients this year at the American Society for Mass Spectrometry (ASMS) conference, which is being held in Minneapolis, Minnesota.

Three Win ASMS Al Yergey Mass Spectrometry Scientist Awards

This blog is a collaboration between LCGC and the American Chemical Society Analytical Division Subdivision on Chromatography and Separations Chemistry.

Separations science within microfluidics has already begun to make significant impact across any number of fields. But many times they are embedded within a larger system—their importance hidden or minimized.

The tiny length scale of microfluidics enables things to happen that have no equivalent on the benchtop. For instance, extremely large electric fields and gradients may be induced that are impossible on the macroscale. When resolution is coupled to the value of these elements, it can skyrocket. If the details of the techniques naturally lend themselves to multi-step separations or enhance detector function, the impact from the advanced resolution is multiplied.

I began to wonder “by how much?” Can I estimate how much better the separations can be and how much better the attached mass spec, cryoEM, spectrophotometry or NMR might work? What is the true “impact?” If I want to answer such a question, what are my metrics? What do I put on the 

-axes when I go to plot it? “Impact” didn’t seem to work well as an analytic unit of measure.

I can do a quick estimate of peak capacity (the number of separate pieces of information which can be gathered), coupled to the resolution and the maximum and minimum elution time or spatial elements. Microfluidics can provide ten to a thousand times better peak capacity on a single axis. Seems pretty good, right? So, what. What does that actually 

? How can you understand the impact of such a thing?

Cue my ignorance of entire fields of science.

Like most things in my career, someone else has been thinking about this type of stuff for a long, long time, and I just didn’t know about it. And of course, they did not use any words I would search for, or understand, initially. Some lucky wandering through some old gas chromatography and mass spectrometry literature from the sixties and seventies*, along with a friendship with a mathematician, were the key.

A new world for me: Information Theory. They have been at this a long time. The original driver was (to my understanding) to estimate the amount of information that could be pushed through the trans-Atlantic cable. To understand impact of an analytical technique I needed to be looking to boats, cables, oceans, and electronics? Obvious, right?

Buried within their analysis was a formula for the smallest “size” (bit) of information compared to the total width of that information, which in our world is peak capacity. Further, the amplitude range can be similarly quantified for “information content” or bits (these parts are pretty easy to understand, of course in hindsight only). The core of this is reflected in Shannon’s equation:

Adapted to separations science, this can give the number of available “bits” of information from that system.

Turns out spectroscopists, when challenged with similar problems, attacked them with concepts consistent with Shannon’s equation. Kaiser wrote two “A-page” articles in 1970 (

 42 (2970) 24A) that explains these concepts applied to identifying and quantifying all of the elements in lunar rock samples. A truly fascinating read. In that article, he defines the “Informing Power” of an overall technique (in available bits) and “Informing Volume” of that technique as applied to a particular problem. Importantly, also defined is the 

 needed from the sample or problem posed.

Now I have the tools, a way to estimate and compare the informing power of a separations science technique in terms of the available information in bits. I also have a construct to estimate the volume of the information needed to attack a particular problem.

On this second point is an interesting question we are playing with: how much information is contained in blood? It sounds ludicrous to ask such an open-ended question. But with these strategies enumerated by Information Theory, this can be considered. Think of cells, small bioparticles (exosomes for example), proteins, peptides, small molecules, and organic and inorganic ions; set maximum/minimum concentrations and smallest clinically relevant or biologically importance difference in concentration and ta-da, you have it. It’s a huge number that we are still refining, but for arguments sake let’s set it at 1022 bits. There are similarly large numbers for any number of other systems (environmental samples; search for life in the solar system, and so on).

Is it feasible to create analytical techniques to match this information volume? Well, when you start running through the numbers and the math, the simple answer is yes—but the keys are microfluidics and the multiplicative factors of having multiple axes and the amplification of the information rich detection schemes. When we are multiplying exponents, they grow real fast. Coupled with this outrageous (yes, outrageous—I just said you can get 1022 bits of information from blood—didn’t notice, did you?). The various axes of separation and detection must be compatible in time, space, configuration, and concentration.

We are in the process of writing an academic paper in this space. I am sure we are off a bit in detail here and there, but the numbers are so large that it won’t change the conclusion. When separations science is fully exploited and coupled with information rich detectors, the amount of information available will challenge data storage and computational systems: the bottle neck won’t be the analytics anymore.

Mark A. Hayes, Professor Arizona State University

On to my next ignorance and thanks for reading

 : channel capacity (bits/s) or information rate; 

 : bandwidth (Hz) or passband bandwidth; 

 : power of the noise (watts or V2)and interference over the bandwidth, measured in watts (or volts squared).

 and the American Chemical Society Analytical Division Subdivision on Chromatography and Separations Chemistry (ACS AD SCSC). The goals of the subdivision include

promoting chromatography and separations chemistry

organizing and sponsoring symposia on topics of interest to separations chemists

developing activities to promote the growth of separations science

increasing the professional status and the contacts between separations scientists.

For more information about the subdivision, or to get involved, please visit 

https://acsanalytical.org/subdivisions/separations/

Separations science within microfluidics has already begun to make significant impact across any number of fields. But many times they are embedded within a larger system—their importance hidden or minimized. 


The LCGC Blog: Curing My Personal Ignorance, One Day at a Time

 is proud to announce that Szabolcs Fekete is the winner of the 2022 HTC Innovation Award. Fekete was honoured at the Hyphenated Techniques and Separations Technology (HTC-17) conference in Ghent, Belgium on Friday 20 May 2022 for his outstanding contributions to the field of separation science.

Symposium Chair of HTC-17, Deirdre Cabooter, said,“Szabolcs Fekete has developed a complete package of novel approaches to push intact protein and protein subunit chromatography to the next level–including the so-called ‘ultra-short column’, ‘multi-isocratic’, ‘negative gradient segment’, and ‘on-column fractioning’ approaches. With these methods, separation scientists can improve selectivity between closely eluting species for more accurate peak integration/identification or routinely separate critical sample components in less than 30 seconds.

“Szabolcs’ research has challenged the status quo of analytical labs in the biopharmaceutical industry, that for a long time have standardized many of their product characterization and quality control techniques on 50 to 150 mm long columns. Szabolcs has challenged conventional thinking by asking fundamental questions, pushing modern column fabrication techniques, and offering new method ideas that have broken the paradigm of these standardized techniques. He has achieved separations of protein species that had long been elusive, and has collected drug product information in 10x less time versus traditional approaches.”

Szabolcs worked in the pharmaceutical industry in analytical R&D for 10 years, and then moved to the University of Geneva in Switzerland, to work in the group of Jean-Luc Veuthey and Davy Guillarme as postdoc and as scientific collaborator for a decade. In April 2021, he joined Waters Corporation and now works as a consulting scientist. He has contributed to 160+ peer-reviewed journal articles and has co-authored 10+ book chapters and edited two handbooks. His main interests include pharmaceuticals, therapeutic proteins and other biomolecules separations, fundamentals of chromatography, column technology, method development, experimental designs, and modelling. He is well known for his various collaborations with both academic and industrial partners.

“It is a huge honour for me to receive the HTC Innovation Award. I feel myself very lucky because I had many possibilities and opportunities to work or collaborate with several outstanding scientists worldwide. I was involved in many industrial and academic collaborations that were very motivating and inspiring. What we have achieved is due to our teamwork. I would like to especially thank Davy Guillarme, Jean-Luc Veuthey, and Matthew Lauber for their continuous support and encouragement,” said Fekete.

The HTC Innovation Award was launched by 

 and the HTC Scientific Committeeto celebrate a separation scientist who has made pioneering contribution to the field of separation sciences by introducing new methodologies, new instrumentation, or new techniques in the field, with a strong focus on applications that benefit society.

 added, “We are very pleased that the HTC Organizing Committee has awarded the prize to Szabolcs, who clearly demonstrates scientific creativity with innovative and practical solutions for biopharmaceutical analysts.”

LCGC is proud to announce that Szabolcs Fekete is the winner of the 2022 HTC Innovation Award. Fekete was honoured at the Hyphenated Techniques and Separations Technology (HTC-17) conference in Ghent, Belgium on Friday 20 May 2022 for his outstanding contributions to the field of separation science.

Szabolcs Fekete Wins 2022 HTC Innovation Award

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 LCâMS and GCâMS for materials characterization, especially in the field of extractables and leachables analysis.

In this next installment of our “Critical Evaluation” series, we will examine gas chromatography methods which use mass spectrometric detection (GC–MS).

We will consider the method variables that are “typical” for single quadrupole MS detectors and what can be learned about the method in question before setting foot in the laboratory. In my experience with GC–MS method specifications, it’s often more about which details are excluded from the specification rather than those that have been cited. Often, the more esoteric mass spectrometric (MS) detection parameters are assumed to be “fixed” and are therefore not included as variables within the specification. These “assumptions” can often lead to problems when implementing new methods. Further, because MS detectors are often “tuned” using automated algorithms to ensure they are operating within the manufacturers specifications, subtle differences in detector settings resulting from the automated tuning, can lead to variability in instrument output. While there needs to be some flexibility in these settings, one needs to carefully consider the impact on the analytical output of the detector.

As always, let’s start by citing a real-world GC-MS method as a “typical” method specification for us to dissect. In this case, the method is for the determination of cannabinoids in hemp, however, the actual analytical determination is almost irrelevant because it is the method variables that we are more interested in, initially.

Oven Program: 50 °C (1 min); ramp 20 °C/min to 300 °C (hold for 1.5 min)

Column Flow: 1.2 mL/min (constant flow mode)

Column: (35%-phenyl)-methylpolysiloxane (inert and MS compatible), 30 m × 0.25 mm, 0.25 µm

Purge Flow to Split Vent: 15 mL/min after 0.75 min

To the experienced eye, this method looks “OK” in terms of the amount of detail included, but on first reading I can already feel myself filling in some of the “gaps” in the required information and also highlighting areas that will need further consideration.

So how to dissect this method and intercept any problems that we might face once in the laboratory? I usually tackle GC–MS method evaluation in the order in which the analyte passes through the system to be systematic about the evaluation, so we will follow this process here, starting with the inlet.

The first issue here is that we are not told the injection volume used within the experiment, and any experiment in splitless injection mode needs to be carefully evaluated for the possibility of ‘backflashing’ the sample in the inlet leading to poor quantitative reproducibility and carry over between injections. Elsewhere in the method, I’m told that the sample solvent is Ethyl Acetate. So we will need to evaluate the solvent expansion under the method conditions shown as well as estimating the liner volume. Again, fortunately, I know that straight, fritted liners from my manufacturer have an internal volume of around 870 mL, which we also need to know in order to use of the solvent expansion tools provided by GC and consumables manufacturers to estimate the risk of backflash.

I also need to know the pressure within the inlet to estimate backflash, and for this I can also use a calculator to estimate both the inlet head pressure and column linear velocity and flow from the given method parameters. Figure 1 shows the results of these computations.

Calculation of required inlet pressure under the method conditions shown (Top) and the resulting vapor volume from a 1ml injection of ethyl acetate

When using MS detectors, it’s important to check the required inlet pressure with “vacuum” selected as the outlet pressure. In this case, the combination of the desired carrier gas flow rate and column dimensions with vacuum at the column outlet gives a head pressure of 9.785 psi and a carrier gas linear velocity of 39.9 cm/sec, both of which are reasonable. Here I’m considering any values above 5psi for the inlet pressure and between 20 and 50 cm/sec for the carrier gas linear velocity to be reasonable. When using lower flow rates and larger internal diameter GC columns (typically 0.32mm i.d. or greater), the inlet pressure required to generate the selected flow rate is very low, as the vacuum is creating a flow within the column without applying any forward pressure to the carrier gas, and the electronic pneumatic control units may struggle to attain or maintain the very inlet low pressures required to generate the required column flow rate or linear velocity.

Figure 1 also shows us that under the experimental conditions, the volume of vapor that will be created in the liner by a 1 mL sample injection is around 278 mL or 32% of its total usable volume. To be absolutely sure of avoiding backflash, I like to keep the vapor volume below half of the liner capacity, although we could easily increase the injection volume to 2 mL without risking backflash, depending upon the required sensitivity of the method. Of course, this parameter will need to be empirically optimized as it was not stated within the method.

It is worth noting here the GC column chemistry cited in the method, (35%-phenyl)-methylpolysiloxane (inert and MS compatible). There are many “MS compatible” phases available these days, and essentially these are phases which show lower a lower degree of bleed. These can either be selected during manufacturers QC process as those which show the lowest bleed level within a batch of columns, or the phase chemistry itself may have been altered, or the phase deactivation process improved, in order to inherently produce a lower bleed column, and hence reduce the amount of ion source fouling which occurs as a result of this bleed. Needless to say, where the phase chemistry has been altered, there may be subtle differences in selectivity between the MS compatible and non-MS compatible versions of the same nominal phase chemistry, Wherever possible, one should try to match the column chemistry to that cited in the method and very often GC–MS methods will be written so that one may recognize the manufacturer of the column from the code letters used to describe the phase (in this case DB-35MS, Rtx35-MS, ZB-35, SPB-35 and so forth). MS compatibility of the GC column will generally lead to longer intervals between MS detector ion source cleaning.

As the analyte passes through the instrument, it will elute into the ion source of the mass spectrometer. We have been supplied temperature values for the ion source and quadrupole, which is helpful, and these values are very often omitted from method specification. Remember that we wish to keep any analytes entering the mass spectrometer in the gas phase, and that most detectors will have optimal temperatures for the various regions within the instrument, and therefore these temperatures are vital information. We have not, however, been provided a temperature value for the heated transfer line that carries the analytes from the end of the GC column into the detector ion source. Typically there should be a temperature differential that will step down from the transfer line, through the ion source, and into the quadrupole. It is vital that less volatile analytes do not condense within the transfer line, and therefore this value is typically set a little higher than the ion source temperature. and a little lower than the upper temperature of the oven temperature program. In this case, a value of 270 or 280 oC would be suitable.

We have also been provided an acquisition mode for the detector (in this case full scanning rather than selection ion monitoring mode) and range of masses over which the scan will be performed during each cycle of the analyzer (65 to 600 

). While the details of the analyzer operation is a little beyond the scope of our present discussion (See reference 1 for further information on the working principle of the quadrupole mass analyzer), we need to carefully consider for each method, the operating mode and range of the mass analyzer. In full scanning mode, the detector progressively cycles from high to low mass values, and will record all ions which pass through the analyzer at sequentially lower 

 values. Having a wide scan range will decrease the number of cycles per second that the detector can achieve and therefore will reduce the analyzer sensitivity. Further, as our analytes will not generate ions at every 

 value, some of the acquisition will be “dead time,” where no signal is produced for the analytes of interest. For this reason, the scan range should be kept as narrow as possible and to within the range of molecular weights covered by the analytes of interest, if this is known. The positive benefit of full scanning is that no information is lost and all analytes within this stipulated mass range will be recorded, which is advantageous when one does not know the nature of the sample.

The alternative acquisition mode is to select target ions that are known to be present in the spectra of the analytes of interest and to “fix” the analyzer at these values according to the time at which the analytes elute from the column. In this way, detector cycle times are reduced and only ions known to be present are recorded, hence improving the sensitivity of the detector. When selected ion monitoring modes are used, it is important that the specification includes the 

 values of the ions being monitored, the time window over which these ions are monitored prior to switching to a new group of ions and, crucially, the dwell time for each ion, that corresponds to the amount of time within each measurement cycle that the instrument is “tuned” to each of the ions within each group. A typical example of this might be:

Typical method specification for quadrupole analyzer settings in a selected ion monitoring type experiment

In the method under consideration here, it is presumed that the range of 65 of 600 

 has been optimized to include the analytes of interest, although this should be fully confirmed prior to transferring the method into your laboratory. If low molecular weight analytes are present within the sample or analytes are known to produce significant fragments at low molecular weight, then one might consider lowering the lower bound of the range. Similarly, if high molecular weight analytes are being analyzed, then the upper limit of the range should be increased. Typically, not much useful information will be gained below around 30 

 and some modern quadrupole analyzing devices will have a maximum upper mass range of 2000 

The solvent delay value (7 mins) corresponds to the time when the filaments used to generate fragmenting electrons within the ion source are switched off, and therefore no spectral information (and therefore no chromatogram) is being generated. The solvent delay time is used to protect the filaments during the time when the sample solvent is eluting from the analytical column, which causes a reduction in vacuum within the ion source and may “burn out” the filaments within the instrument. This delay time can also be used to save filament burn time (filaments have a finite lifetime) prior to the time at which the first analytes begin to elute from the GC column. In this method then, we are assuming that no useful information is derived for the first seven minutes of the analysis, which will need to be verified. This value also suggests that some optimization of the temperature program could have been possible to save wasted time at the beginning of each analysis. One needs to take care when optimizing the solvent delay time, and if the mass spectrometer is fitted with a vacuum monitoring gauge, the increase in source pressure followed by the subsequent reduction can be used to gauge the passage of the sample solvent through the ion source, and can therefore be used to set an appropriate solvent delay.

This brings us to the final consideration, that of the instrument tune.” In this case, the name of the type of tune has been cited as “Autotune.” It is worthy of note that this is a particular tune file associated with a particular manufacturer and the tune itself will impart certain response characteristics to the instrument, depending on the tune targets written into the instrument tune algorithm. Some tune algorithms may be good for overall spectral fidelity, some may target higher sensitivity at higher or lower mass, some may be tunes for specific types of target analytes or application areas such as environmental analysis. When implementing a literature method or transferring methods between laboratories and instruments, one needs to carefully consider the instrument tuning and assess its appropriateness for the analysis at hand. While a full consideration of the various aspects of MS detector tuning is beyond our scope here, it is important that the analyst understands the tune parameters in order to make a judgement regarding the suitability of the instrument tuning. Some tunes are more suited to qualitative analysis and others for quantitative analysis, for example.

While all manufacturers will differ in the tune targets they apply to instrument variables for the various methods of tuning, they will all result in an assurance that the instrument is operating to within required tolerances. For this reason, I tend to prefer a more objective measurement to be included in method specifications, and some typical values that might be included are:

69 (perflurotributylamine) has a peak width of between 0.5 and 0.6 m/z

 502 (perflurotributylamine) has a signal count of least X with a signal to noise value of Y 

 analyte X injected at 0.1 mg/ML has a signal to noise ratio of at least 5:1

For more information on setting and interpreting MS tuning parameters see reference 2.

When evaluating GC–MS methods, it’s important to consider the suitability of the column dimensions and required carrier gas flow rate to establish the feasibility of easily meeting and maintaining the lower inlet pressures required when the GC column outlet is at vacuum.

The correct setting of more minor variables within the MS detector is also important to ensure that the detector performance requirements are met. Giving prior consideration to the method variables and thinking through any potential issues can save a lot of head scratching once we have crossed the laboratory threshold!

https://www.chromatographyonline.com/view/the-lcgc-blog-the-beauty-of-the-quadrupole-mass-analyzer

https://www.chromatographyonline.com/view/what-gc-ms-tune-report-can-tell-you-0

Tony Taylor is the Chief Scientific Officer of Arch Sciences Group and the Technical Director of 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 LCGC Blog: Critical Evaluation of Analytical Methods: Gas Chromatography and Mass Spectrometry 

Analytical methods for quality control (QC) of monoclonal antibodies (mAbs) rely on peptide mapping workflows with liquid chromatography–mass spectrometry (LC–MS) systems. Whilst LC–MS is effective, peptide mapping with LC–MS can involve long analysis times that reduce the throughput of QC testing. Modern tandem LC methods can increase analysis efficiency and are designed to reduce the downtime of MS sampling to increase the efficiency of QC pipelines. The approach presented here improves the efficiency of mAb analysis peptide mapping, whilst returning high-quality data.

Sara Carillo is the applications development team leader in the Characterization and Comparability Laboratory in NIBRT, Ireland. Sara completed her PhD in Chemical Science at the University of Naples in 2013 working on bacterial glyco‑conjugates structural characterization. In 2015, Sara joined Jonathan Bones’ research group in NIBRT, working on CHO cell glycome and biotherapeutics characterization.

Jonathan Bones, PhD, is principal investigator at NIBRT.

The development and production of therapeutics, such as monoclonal antibodies (mAbs), require high-throughput sample analysis and high‑quality data. For example, post-translational modifications (PTMs) can have a major impact on the quality and efficacy of the final product and, therefore, need to be monitored. Orthogonal analyses of protein PTMs are required to ensure certain critical quality attributes (CQAs) are within the established ranges to maintain lot-to-lot consistency in line with regulatory requirements and International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) guidelines (1).

Peptide mapping is considered a gold standard for mAb analysis because it delivers information on many attributes at the peptide level within a single analysis, providing a strong method for an analytical control strategy. One type of peptide mapping approach using liquid chromatography–mass spectrometry (LC–MS) analysis is the multi-attribute method (MAM), which allows high-quality, confident PTM identification in research and at later stages in quality control (QC) laboratories (2–4). However, peptide mapping with LC–MS methods can involve long analysis times due to the lengthy LC gradient needed to resolve peptides in the complex sample resulting from tryptic digestion. This creates challenges for high-throughput laboratories where efficiency is key. Moreover, long downtimes are also created between analyses to allow for column washing and re-equilibration steps, and when eluents are diverted to waste. During these periods, no separation is taking place. This reduces the time available to perform MS testing and reduces efficiency in research and QC pipelines.

Innovations in ultrahigh-performance liquid chromatography (UHPLC) instrumentation have led to the development of a tandem LC system that can be leveraged for high-throughput “tandem-mode” LC–MS analysis.

This article demonstrates the applicability of a tandem LC–MS workflow for peptide mapping analysis of trastuzumab in a high-throughput manner. With a tandem LC–MS approach, a greater number of sample injections were performed in the same timeframe, increasing analytical throughput and significantly reducing MS downtime. Chromatographic results were found to be equivalent across the two chromatographic channels. Additionally, the reproducibility of the obtained PTM values during a continuous 16-h period of operation were tested, demonstrating the stability of MS performance under continuous acquisition.

Samples were prepared following a published method (5) to obtain peptides from tryptic digestion of trastuzumab. Trastuzumab samples were diluted to 2 mg/mL in water. For each sample digest, sample, digestion buffer (buffer 1, pH 6.5 or buffer 2, pH 7.2), and 5 mM TCEP (final concentration) were added to each lane of a Thermo Scientific KingFisher deep well 96-well plate. Trypsin bead “wash buffer” was prepared by diluting digestion buffer 1:4 (v/v) in water. Bead buffer was neat digestion buffer. Digestion was performed using a Thermo Scientific KingFisher Duo Prime Purification System with Thermo Scientific BindIt software (version 4.0). Samples were incubated for 5 to 40 min at 70 °C on medium mixing speed to prevent sedimentation of beads for the digestion time course study, and beads were removed at each time point. Following digestion, 100-μL samples were transferred to 300‑μL Thermo Scientific PP Screw vials and cap and 1 μL of 10% trifluoroacetic acid (TFA) was added (final concentration 0.1% TFA) and immediately analyzed by high-resolution accurate mass LC–MS.

 The resulted peptides were separated on a 2.1 × 250 mm, 2.2‑μm Acclaim Vanquish C18 column (Thermo Scientific) using the Thermo Scientific Vanquish Horizon Duo UHPLC System for tandem LC–MS workflows. Analysis was performed using a binary gradient of 0.1% (v/v) formic acid in water (A) and 0.1% (v/v) formic acid in acetonitrile (B) with a flow rate of 0.3 mL/min. The gradient started at 2% B and increased to 40% B over 45 min on the analytical pump, while the reconditioning pump performed two cycles from 2% to 80% B in 20 min and equilibrated back to 2% B for 25 min.

Mass spectrometry data acquisition was performed with the Thermo Scientific Orbitrap Exploris 240 MS system with biopharma option at resolution 120,000 FWHM. Application‑specific MS tune and acquisition settings are templated and provided within the Thermo Scientific Chromeleon Chromatography Data System (CDS) software, which makes this approach directly and easily transferable from instrument to instrument.

Spray voltage: 3.8 kV; sheath gas: 25; auxiliary gas: 10; ion transfer tube temperature: 320 °C; vaporizer temperature: 150 °C; pressure mode: peptide.

; RF lens (%): 60; AGC target: 3 × 106; max injection time: 100 ms.

 Resolution: 15,000; normalized collision energy: 30; injection time: 200 ms; AGC target: 1 × 106; TopN: 5; microscan: 1; isolation window: 2 

Data were processed using the Thermo Scientific BioPharma Finder Software 4.0.

Peptide mapping is a routine analysis in biopharmaceutical assessment and is gaining more interest as part of the MAM workflow. It is driving the wider adoption of MS methods for later stages of biopharmaceutical product development and, ultimately, allowing its use in the QC laboratory. Method transfer onto the QC stage requires improved robustness and high‑throughput due to the high number of samples that must be processed and the required reliability of the methods assuring product quality.

In this study, trastuzumab monoclonal antibody was digested using a trypsin protein digestion kit and the generation of tryptic peptides was performed automatically on the purification system. The digested monoclonal antibody was then analyzed via tandem
LC–MS/MS analysis. CDS software automatically split the gradient across the two columns and pumps, managing when the analytical gradient was complete and the wash step started. Twenty‑one sample injections were performed in this study, alternating between the two columns to obtain a perfect overlap of runs coming from the two channels (Figure 1). This qualitative evaluation demonstrates the reproducibility of LC performance not only across the two channels but also when using two different columns.

Chromatographic reproducibility was evaluated across the gradient by plotting the retention times for five different peptides along with the 21 injections. No difference was observed between the two data sets, returning overall relative standard deviation (RSD) values lower than 1.5% (Figure 2). Excellent retention time reproducibility is important for correct identification of components to evaluate and quantify drug product CQAs using MS. However, it would be possible to allow higher values of %RSD for the retention times when using high-resolution MS, as this level of resolution gives a confident identification of components even when using a wider retention time window.

Peptide mapping analysis is mainly performed to evaluate PTMs in therapeutic proteins that need to be monitored during bioprocessing and batch release to guarantee drug product quality. For this reason, we evaluated product quality attributes for trastuzumab across the 21 injections performed in tandem mode (Table 1). Each modification was calculated considering up to one missed cleavage, and without considering Na+ and K+ adducts or non-specific cleavages, using a confidence score ≥ 95% and within ± 5 ppm. Detection of most PTMs resulted in very low RSD values, which exceeded 15% only for some low abundant modifications (N328 + deamidation = 0.20%). This proved excellent chromatographic equivalence of the two channels for PTM evaluation, as well as the suitability of the tandem LC–MS workflow for PTMs assessment and quantitation.

In this study, we have demonstrated the suitability of a tandem LC system for tandem LC–MS analysis for peptide mapping and the MAM workflow. This tandem LC approach significantly increased analytical throughput by reducing the time when MS was not fully utilized for valuable data generation; this was achieved by minimizing the time window where LC was diverted to waste and the MS not utilized. This workflow proved to be a more time-efficient alternative to traditional methods, while also maintaining or improving the performance and reproducibility required for a method to be considered for adoption in a QC laboratory.

Twenty-one samples of trastuzumab tryptic digest were analyzed using LC–MS/MS analysis in tandem mode. System performance was evaluated by monitoring retention time reproducibility and identifying PTMs, with both evaluations yielding excellent data and low %RSD values. Tandem analysis of peptide mapping replicates did not affect the accuracy of the results and the correct identification, but it had the benefit of saving at least 6 h of instrument time when compared to single mode during 24 h. The use of automated digest kits versus in-solution digestion has been shown to save between 2–20 h preparation time for each sample (6), providing significant sample preparation time savings, which, when combined with the efficiency benefits of the tandem analysis, can dramatically increase throughput.

In conclusion, tandem LC–MS represents a powerful way to increase laboratory productivity without compromising data quality, especially when combined with automated sample preparation of the tryptic digest. The operational simplicity of tandem LC–MS methods means that little training is required for high-throughput peptide mapping of biopharmaceuticals, enabling straightforward compliance-ready enterprise acquisition of LC–MS data for current good manufacturing practice (cGMP) environments.

Guidance for Industry: Quality Considerations in Demonstrating Biosimilarity of a Therapeutic Protein Product to a Reference Product

S. Rogstad, A. Faustino, A. Ruth, D. Keire, M. Boyne, and J. Park,

R.S. Rogers, N.S. Nightlinger, B. Livingston, P. Campbell, R. Bailey, and A. Balland, 

R.S. Rogers, M. Abernathy, D.D. Richardson, J.C. Rouse, J.B. Sperry, P. Swann, et al., 

S. Millán-Martín, C. Jakes, S. Carillo, 

Thermo Scientific Application Note 72141, 

SMART Digest compared to classic in-solution digestion of rituximab for in-depth peptide mapping characterization

, http://tools.thermofisher.com/content/sfs/brochures/AN-1159-SP-SMART-Digest-Peptides-AN72141-EN.pdf

obtained his B.Sc. in analytical science (chemistry) and Ph.D. in analytical chemistry from Dublin City University (DCU). He joined Pauline M. Rudd’s group at NIBRT in 2007. In 2010, Jonathan was appointed as the “John Hatsopoulos Research Scholarship” at the Barnett Institute of Chemical and Biological Analysis at Northeastern University in Boston, Massachusetts, USA, working under the mentorship of Barry L. Karger and investigating new approaches for glycomics and the application of proteomics for a better understanding of mammalian cell bioprocessing. In 2012, he returned to NIBRT.

completed her Ph.D. in chemical sciences in 2013 at the University of Naples “Federico II”. Under the guidance of Professor Corsaro, she focused on the structural characterization of polysaccharides and glyco-conjugates from Gram-negative bacteria via nuclear magnetic resonance (NMR) and mass spectrometry techniques, focusing on the immunological properties and potentials of extremophiles endotoxins. After a period at the University College of Dublin, she joined Jonathan Bones’s research group in NIBRT in 2015, working on the understanding of the effects of extractables and leachables from single‑use bioreactors on CHO cells N-glycome and produced monoclonal antibodies. She is now working at NIBRT as Applications Development Team Leader for the development of new analytical approaches in biopharma.

 is Applications Scientist in the Characterization and Comparability Laboratory in NIBRT, Ireland. She obtained her degree in pharmacy and Ph.D. in analytical chemistry from the University of the Basque country in North Spain, where her work focused on the development of LC–MS/MS- and GC–MS-based analytical techniques for the identification and quantitation of environmental, pharmaceutical, and nutritional significant compounds. She also worked for four years in a small contract research organization in the analytical services unit, and focused on the determination of bioactive compounds in natural sources and the application of metabolomics/proteomics approaches with the aim of evaluating their health benefits to potentially be used as functional ingredients in the food industry. In September 2012, she joined NIBRT, becoming part of the GlycoScience Group as a postdoctoral researcher in the mass spec lab and working on academic and contract research projects with biopharma companies. Her work focused on full detailed glycan analysis by MS and MS/MS and other orthogonal techniques, and on the development of advanced LC–MS‑based platforms for quantitative glycomics, with applications in bioprocessing and clinical biomarker discovery. In September 2016, she joined the Characterization and Comparability Laboratory, which is led by Jonathan Bones and collaborates with Thermo Fisher Scientific, to focus on the development of new applications for the characterization of biopharmaceuticals, and the associated processes used for their production.

 jonathan.bones@nibrt.ie / sara.carillo@nibrt.ie / silvia.millanmartin@nibrt.ie


The benefits of tandem LC–MS are revealed.

High-Throughput Peptide Mapping of Monoclonal Antibodies Using Tandem Liquid Chromatography– Mass Spectrometry

Accelerating the understanding of metabolomics in disease is increasingly high on the agenda for many researchers looking to develop their drug discovery efforts into clinical trials. With personalized medicine the goal that many are striving to achieve, metabolomic technologies must continue to develop improved sensitivity if they are to make a real difference to the drug research of the future.

Lucy Woods is Business Unit Manager Phenomics and Metabolomics at Bruker Daltonics.

Metabolites are the chemical entities that are transformed during metabolism in the body, and they provide a functional readout of cellular biochemistry. Metabolites are the products of metabolic pathways and include small molecules such as lipids, sugars, nucleotides, and amino acids. With mass spectrometry (MS)-based metabolomics techniques, thousands of metabolites can be quantitatively measured from minimal amounts of biological material, which has subsequently enabled systems-level analyses. Global or untargeted metabolite profiling is revealing new discoveries linking cellular pathways to biological mechanisms, shaping the understanding of cell biology, physiology, and medicine.

Metabolomics plays a major role in clinical practice, as it represents more than 95% of the workload in clinical laboratories worldwide (1). Although relatively new compared with its genomic and proteomic predecessors, research into metabolomics has already led to the discovery of biomarkers for disease diagnosis, fundamental insights into cellular biochemistry, and observations related to disease pathogenesis.

One of the biggest challenges facing untargeted metabolomics research is reliable compound identification to ensure accurate interpretation of data. Due to the chemical similarity of metabolites (isobars and isomers), identification by MS or chromatography alone can often be difficult for researchers looking into the behaviour of metabolites. The challenge is that isomers can have the same mass, charge, and physical properties, but can vary widely in their bioactivity, making both separation and identification a time- and resource-intensive process.

Another challenge is that the metabolome is extremely sensitive, meaning a person’s metabolic phenotype is influenced by environmental factors. Data can also be more ambiguous because metabolites are the products of upstream biological transformations of molecules in a similar mass range, which in turn presents the need for higher sensitivity to obtain broad metabolite coverage and relative concentrations. The field of metabolomics is much newer than proteomics and researchers also experience significant challenges in the interpretation of data, for example, in the interpretation of fragmentation data.

Ion mobility spectrometry–mass spectrometry (IMS-MS) has emerged as a powerful technology to address such issues, and the use of IMS-MS in untargeted metabolomics has improved the separation of metabolite isomers and supports metabolite identification through generation of orthogonal data, such as collision cross section values.

New technology is continually being developed to realize the biological relevance of these metabolites, to delve deeper into their behaviours, and to look further into new metabolomic possibilities.

Alterations at the metabolome level reflect disturbances in preceding biological cascades, bridging the gap between the genome and phenotype. Changes at this level can lead to the onset of disease symptoms, making metabolomics an essential diagnostic and prognostic tool in investigating the mode of action of chemical compounds and obtaining an in-depth understanding of the impact of infection, for example (2). Current metabolomics research focuses on a range of challenging diseases, including Alzheimer’s disease and cancer.

Scientists are looking further into metabolomic research to examine how the cells in our body behave and what this could mean as we look towards a future of personalized medicine. The acceleration of this research has driven new developments in lipid biochemistry. Lipids are fatty small molecules that share common physical and chemical properties, and the abundance of lipids and different lipid classes is key to metabolic regulation. Lipids studied using metabolomic approaches—lipidomics—are an ideal subject for metabolomic measurements. Lipids also allow scientists to gain further insight into genomes and genetic polymorphisms (3).

As metabolomic possibilities progress, the study of lipidomics has become a prominent source for collecting and measuring data within the metabolome. Because the abundance of lipids in typical samples, such as plasma extracts, can vary considerably, analytical methods with high sensitivity and dynamic range are required. One novel method focuses on coupling a vacuum insulated probe heated ion source (VIP-HESI) with a mass spectrometer. This technology looks at enhancing the limit of detection (LOD) and the dynamic range, as well as examining the lipid identification annotation capability. It enables sensitivity gains of up to 16-fold by efficient desolvation, enabling new applications across all small molecules (4).

Looking further into lipids is crucial to further understanding challenging diseases. Lipids are involved in biological processes such as blood clotting, mediating inflammation, or as signalling molecules, which makes them an interesting target for the discovery of new biomarkers. Insights such as this are essential for developing new treatments and for personalized medicine (5). The discovery of new biomarkers increases the likelihood of finding real-life outcomes for patients as this data progresses into the clinic.

It is key that research progresses in the field of metabolomics, and, within that, lipidomics, to transform insights and cellular findings into new drugs. In turn, personalized medicine becomes a brighter prospect to combat a range
of diseases.

Data from an experiment using VIP-HESI is highlighted in Figure 1, showing the difference that it makes to the analysis and sensitivity of lipids across different sample concentrations (4). This technology allows data from lipids to be acquired through a deeper and broader analysis than in previous lipidomic workflows, with the figure showing a higher number of lipid identification annotations for untargeted workflows (4).

Looking Towards the Future of Personalized Medicine

As new technologies evolve and researchers look to optimize equipment to accelerate their studies, it is important that software and analytics keep pace to support the abundance of new data. Looking to a future in which personalized medicine is perceived to be within reach, advances in metabolomics research are significant in discovering new biomarkers to guide insight into our genetic make‑up. With the advancement of MS, as well as technologies such as nuclear magnetic resonance (NMR),
further strides can be made in clinical practice.

M. Jacob, A.L. Lopata, M. Dasouki, and A.M. Abdel Rahman, 

V. Tounta, Y. Liu, A. Cheyne, and G. Larrouy‑Maumus, 

J.B. German, L.A. Gillies, J.T. Smilowitz, A.M. Zivkovic, and S.M. Watkins, 

M. Szesny, L. Woods, S. Meyer, A. Korf, N. Kessler, and A. Barsch, 

Improved sensitivity and higher lipid annotation ID capabilities using a new vacuum insulated heated ESI source

 (online). Available at: https://www.uni-due.de/aac/lipidomics.php (Accessed 8 November 2021).

By using MS-based techniques, thousands of metabolites can be measured.

This month we interview Valentina D’Atri, a Research and Teaching Fellow in the Analytical Sciences Department of the School of Pharmaceutical Sciences at the University of Geneva in Switzerland, about her work to couple cation-exchange chromatography (CEC) to mass spectrometry (MS), and the challenges of analyzing increasingly complex biopharmaceuticals, such as therapeutic Fc-fusion proteins and bispecific antibodies.

Q. When did you first encounter chromatography and what attracted you to the subject?

 It was in February 2016, when I was recruited by Jean-Luc Veuthey and Davy Guillarme as a postdoctoral researcher at the University of Geneva. The goal of the project was the characterization of biopharmaceutical proteins by coupling several chromatographic methods to mass spectrometry (MS). Although I had no previous experience with chromatography, I was motivated to challenge myself in the field, and it seems that I was motivated enough for them to accept me into the group. Szabolcs Fekete gave me my first “practical lessons” in front of a high performance liquid chromatography (HPLC) system and introduced me to the elegance and the beauty of chromatographic separations. It was only after a while that I realized that there would be no better place to debut with this technique! What attracted me most about the subject was its versatility; it is simply marvellous how the results achieved with different chromatographic modes can be combined to understand the specific features of the molecules being analyzed. Although everything may seem predictable it is not just about a mobile phase passing through a column, it is about interactions, partitioning, adsorption, and the deep understanding of all these mechanisms.

Q. Can you tell us more about your Ph.D. thesis?

 My Ph.D. thesis was focused on G-quadruplexes, some particular DNA secondary structures that have a natural propensity to self-associate in three‑dimensional scaffolds. These higher-ordered DNA structures exhibit a dramatic thermal stability and represent a suitable nucleic acid scaffold for DNA‑based nanostructures and therapeutic oligonucleotides (aptamers). During my Ph.D. research studies, I focused on both applications. I identified and characterized some DNA-based nanostructures with a fixed and tailored length, in addition to potentially therapeutic aptamers endowed with anti-HIV activity. In the latter case, the aim was to identify the structural features required for the aptamer biological activity and succeed in improving them. It was therefore necessary to exploit the synthesis and the structural characterization of quadruplex‑forming oligonucleotides, the analysis of the sequence-specific thermodynamic stability, the physical‑chemical properties and the structural features of resulting G-quadruplexes, and evaluate the binding properties to the selected proteins. I really enjoyed my Ph.D. thesis; I had the opportunity to learn different techniques and be supported by highly competent mentors.

Q. What chromatographic techniques have you worked with?

 I started with hydrophilic interaction liquid chromatography (HILIC) and the comparison of its performance with reversed-phase LC for the analysis of biopharmaceutical proteins performed at the subunit level. Then, I moved to non‑denaturing techniques, such as size-exclusion chromatography (SEC) and ion-exchange chromatography (IEC), for performing the analysis at the intact protein level. In all cases, my goal was the direct coupling to MS for the comprehensive characterization of post-translational modifications (PTMs) and critical quality attributes (CQAs) associated with biopharmaceutical proteins.

Q. The success of therapeutic monoclonal antibodies (mAbs) has led to the development of many new antibody-based drug formats. What are some of the challenges involved in ensuring that the final product produced is the intended drug?

 The field of antibody-based drug formats has practically exploded in recent years, with biosimilars, antibody-drug conjugates, multi‑specific antibodies, and Fc-fusion proteins filling the pipelines of the pharmaceutical industries to get into the market. To ensure that the final product is the intended drug, the challenges are virtually the same: a complete characterization of the structural features associated with the micro-heterogeneity of these formats. Unfortunately, there is no single LC mode that allows for this characterization. The use of different chromatographic methods is necessary and the complementarity between the modes is the key to overcoming these challenges.

Q. Post-translational modifications of the drug product can result in changes to the molecular surface charge distribution, with IEC and cation‑exchange chromatography (CEC) being key techniques to monitor this. In your recent paper you mention “salt‑mediated pH gradients” as a powerful tool to achieve better separation efficiency (1). Could you explain in more detail what this entails?

 In CEC, the separation is performed with a negatively charged stationary phase that retains ionic compounds, allowing their elution through two different mechanisms: i) via salt-gradient mode, by increasing the salt concentration to weaken the ionic interactions between the protein and the stationary phase; or ii) via pH-gradient mode, by increasing the mobile phase pH while keeping a constant ionic strength to change the charge of the proteins (based on their isoelectric point [pI]). A “salt-mediated pH gradient” can be considered as a boosted pH-gradient mode that is basically obtained by using a mild salt gradient in combination with a pH-gradient mode. This approach allows the cover of a wider range of protein pI and therefore improves the separation of proteins that can be simultaneously analyzed.

Q. When attempting to discover the cause of the changes to molecular surface charge distribution your paper mentions that MS would be the
go‑to detection method, and in the past would be paired with reversed‑phase LC and HILIC, what has changed in this regard and why?

 The mobile phase composition of denaturing chromatographic techniques such as HILIC and reversed-phase LC allows their direct coupling to MS, although at the expense of losing the native conformation of proteins. On the other hand, CEC is a non-denaturing technique that allows the therapeutic proteins to keep in their native folded state while separating charge protein variants. Historically, CEC was performed with a high concentration of nonvolatile salts in the mobile phases and was therefore incompatible with MS. In these conditions, apart from being able to assign a given variant as acidic or basic by reference to its elution time in relation to the main peak, it was not possible to identify which variation was responsible for the change in charge. MS analysis is essential for such identification and was obtained after performing the desalting of the CEC‑collected peaks. Among the first attempts at obtaining the coupling of CEC to MS was multidimensional chromatography (mD-LC). This could have been a solution, but the approach was not straightforward to implement and not well adapted for routine applications. For these reasons, MS-compatible mobile phases for CEC applications have emerged with the aim of obtaining a direct coupling of CEC to MS for allowing unbiased and straightforward characterization of charge variants. Different solutions have been proposed by several research groups and it is now clear that CEC–MS is a real possibility.

Q. Your recent publication details a straightforward and rapid CEC–MS method that allows the separation and identification of several charge variants (1). What challenges did you face in creating this method and what benefits does it offer over alternatives?

Our goal was to develop a generic CEC–MS method by using a compact benchtop time-of-flight mass spectrometer (TOF-MS). The first challenge to overcome was to find a compromise between the LC performance and the MS sensitivity. Indeed, when using mobile phases consisting exclusively of volatile salts, it should be considered that they may have a lower buffering capacity compared to mobile phases containing nonvolatile salts. In addition, the LC setup should be compatible, with a proper MS ionization process to avoid the risk of obtaining low signal intensities. Therefore, we optimized the chromatographic conditions by testing various buffers and column dimensions to select the most suitable mobile phase in terms of pH response, buffer stability over time, MS compatibility, and in terms of efficiency versus MS compatibility for the column. Then, we took care of the second challenge: the CEC–MS coupling. Honestly, we expected that it would work on the first try and that a slight optimization of the MS source conditions would be enough to achieve a good ionization of the proteins, but we had to change our minds. The first attempts at direct CEC–MS coupling were not at all satisfactory; the MS signal had very low values of intensity and resolution, and it took a moment to realize that everything depended on the way we prepared the mobile phases. Indeed, metal contaminants from the water source and the glassware, including all the laboratory glassware, mobile phase bottles, and vials, were mainly responsible for the loss of MS resolution and sensitivity. It seemed to be a small detail, but it was not obvious. We then switched to trace metal certified thermoplastics, avoided glass-bottled water, and we managed to overcome the problem of the MS sensitivity. Having solved this problem, everything was smooth and easy to perform. The optimized CEC–MS setup allowed CEC analysis in less than 10 min, and in particular the simultaneous separation and identification of several charge variants by MS.

Regarding the benefits of this CEC–MS method over alternatives, I think that a strength is that it could be easily implemented in another laboratory. Above all, it does not need an MS technology offering an exaggerated resolving power; our method has been developed on a compact benchtop MS system consisting of a TOF-MS offering a resolving power of 10,000.

Q. Another paper you published recently focused on therapeutic Fc‑fusion proteins (2). What are these exactly and what therapeutic uses could they have?

 Fc-fusion proteins are a special mAb‑based format generated by the fusion of the fragment crystallizable (Fc) domain of an immunoglobulin G (IgG) with a biologically active domain that may be represented by a peptide, a cytokine trap, an extracellular domain (ECD) of natural receptors, or even a recombinant enzyme. The strategy behind this particular design relies on the fact that by coupling a biologically active domain to an Fc‑IgG, the size of the resulting construct can be increased above the threshold for kidney filtration (60 kDa) and therefore the circulation time of the active domain can be enhanced by avoiding the renal clearance. Therefore, the therapeutic potential of the pharmacologically active moiety would be increased, together with the general stability and solubility of the construct directly linked to the presence of the Fc‑domain. Ideally, any active domain suffering from low circulation time could be fused to an Fc-fragment to generate an Fc-fusion protein. For this reason, the therapeutic uses can be really different, from providing a replacement therapy for haemophilia A/B to the treatment of rheumatoid arthritis, plaque psoriasis, or colorectal cancer.

Q. What are the analytical challenges that therapeutic Fc-fusion proteins present?

Given the diverse nature of the biologically active domain constituting the Fc-fusion proteins, the analytical challenges can indeed be sample-dependent, even though the main goal is generally to obtain a complete characterization of the PTMs. Among the PTMs, I think that the most challenging one would be the characterization of the glycan profile. Indeed, some Fc-fusion proteins, such as etanercept, abatacept, and belatacep, contain up to six 

-glycosylation sites, aflibercept can have up to 10, and conbercept up to 14. In addition, 

-glycans may also be present, as in the case of etanercept, which can have up to 26 

-glycans. It is therefore easy to imagine the complexity of these glycosylation profiles and how they can be tricky to analyze compared to mAbs, which generally contain only two 

Q. You recently published a paper on bispecific antibodies (bsAbs) (3). What exactly are bsAbs and what do they offer that other biopharmaceuticals
do not?

Bispecific antibodies (bsAbs) combine the antigen recognition sites of two (or more) antibodies in a single protein construct, and therefore allow the targeting of two (or more) different epitopes either on the same or on different antigens. As an example, emicizumab is a bsAb with a mAb‑shaped structure consisting of two identical light chains (LCs) and two different heavy chains (HCs) able to recognize two different targets, namely the activated coagulation factor IX (FIXa) and the coagulation factor X (FX). By using this double recognition, emicizumab can mimic the function of the plasma clotting factor VIII (FVIII) that is generally missing in patients with haemophilia A. So, without having any homology to the native FVIII, emicizumab acts as cofactor mimetic and is used for the routine prophylaxis of patients missing FVIII.

Q. What unique analytical challenges do bsAbs present?

 The correct chain-association is the most critical challenge to monitor during bsAbs development and production. The higher the number of antigen recognition sites, the higher the probability of mismatched chains. Therefore, beyond the canonical analytical characterization that is applied to mAb-related formats, the correct chain‑association is the dedicated challenge related to bsAbs.

 I am currently having fun with “exotic” mAb-related formats including multi‑specific antibodies and immunocytokines. In parallel, drug formats as therapeutic oligonucleotides and viral vectors for gene therapy have attracted our attention because they represent the pharmaceutical applications of a future that is already here. From an analytical point of view, these new research fields come with completely different and exciting challenges compared to the field of biopharmaceutical proteins. Therefore, beyond mAb-related formats, I am also currently working on the development of LC–MS analytical methods for the characterization of DNA/RNA oligonucleotides and viral vectors, and given the speed at which these fields are evolving, I imagine that I will not have time to get bored!

A. Murisier, B.L. Duivelshof, S. Fekete, J. Bourquin, A. Schmudlach, M.A. Lauber, J.M. Nguyen, A. Beck, D. Guillarme, and V. D’Atri. 

B.L. Duivelshof, A. Murisier, J. Camperi, S. Fekete, A. Beck, D. Guillarme, and V. D’Atri, 

B.L. Duivelshof, A. Beck, D. Guillarme, and V. D’Atri, 

 is a Research and Teaching Fellow in the Analytical Sciences Department of the School of Pharmaceutical Sciences at the University of Geneva in Switzerland. She studied pharmaceutical biotechnology sciences (M.Sc. and B.Sc.) and obtained her Ph.D. in industrial and molecular biotechnologies (2013) from the University of Naples Federico II, Italy. She had her first postdoctoral experience (2013–2015) in the group of Valérie Gabelica (INSERM, Bordeaux, France), where she was involved in projects related to the structural characterization of DNA structures by linking ion mobility–mass spectrometry to molecular modelling. In 2016, she joined the group of Jean-Luc Veuthey and Davy Guillarme at the University of Geneva, where she is now currently working. Her interests and research activities focus on the development of cutting-edge LC–MS analytical workflows for the detailed characterization of innovative therapeutic drugs, such as biopharmaceutical proteins (monoclonal antibodies, antibody-drug conjugates, bi/tri-specific antibodies, Fc-fusion proteins), therapeutic oligonucleotides (ASO, siRNA), and viral vectors (AAV). She has currently authored over 50 peer-reviewed contributions, including articles and book chapters.

The Column interviewed Valentina D’Atri about her work to couple CEC to MS, and the challenges of analyzing complex biopharmaceuticals.

Rising Stars of Separation Science: Valentina D’Atri

Ion mobility is a structurally selective separation strategy that is now routinely integrated with mass spectrometry (IM-MS) to improve peak capacity while simultaneously aiding in the separation of isobaric signals such as those encountered in complex chemical samples. Structures for lossless ion manipulation (SLIM) technology provides a modular architecture for developing tailored ion processing systems, including ion mobility spectrometers. This article evaluates the separation capabilities of a SLIM‑based high-resolution ion mobility spectrometer (HRIM) incorporating an extended (~13 m) separation path length design in order to determine benefits for scientists working with complex and challenging analyte classes such as glycans, peptides, and lipids.

Jody C. May is Research Assistant Professor at Vanderbilt University. He received his B.S. in chemistry from the University of Central Arkansas in 2001 and his Ph.D. in analytical chemistry from Texas A&M University in 2009. Jody held a postdoctoral position at Vanderbilt University before transitioning into a research faculty position in 2012. Jody’s research interests intersect multidimensional mass spectrometry techniques with advanced informatics to elucidate unseen and undiscovered chemical space.

Daniel DeBord is Vice President of R&D at MobilIion Systems. Daniel has extensive experience in the field of mass spectrometry. After receiving his Ph.D. in analytical chemistry from Texas A&M University, Daniel served as Associate Director of the Advanced Mass Spectrometry Facility at Florida International University. His industry experience includes positions at BASF and 1st Detect Corporation, where he worked to design and develop miniaturized MS-based detection systems for a variety of markets.

Katrina L. Leaptrot is Research Assistant Professor in the Vanderbilt University Chemistry Department. She received her B.S. in biology and chemistry from the University of Charleston (West Virginia) in 2011 and her Ph.D. in chemistry from Vanderbilt University in 2018. Following postdoctoral training at Vanderbilt University, she transitioned into a research faculty position in 2020 for the McLean Research Group, the Vanderbilt Center for Innovative Technology, and the SyBBURE Searle Undergraduate Research Programme. Katrina’s research focuses on analyses of lipids and related biomolecules via liquid chromatography–ion mobility‑mass spectrometry.


Bailey S. Rose is a recent graduate from the McLean Research Group at Vanderbilt University with a Ph.D. in chemistry. She received her B.S. in chemistry from Belmont University in 2017. Bailey’s research focuses on the application of ion mobility‑mass spectrometry and novel informatics approaches to untargeted metabolomics and lipidomics in support of high-confidence molecular annotation.

LiuLin Deng is Principal Scientist at Mobilion Systems Inc. and is currently responsible for designing, constructing, validating, and developing the next generation ion mobility spectrometry based upon SLIM technology.

Kelly Wormwood Moser is leading Mobilion’s application development, working with industry collaborators to develop methods to demonstrate HRIM separation capabilities with biological samples. Kelly is leveraging her Ph.D. research experience, where, under the direction of Dr. Costel Darie, she used mass spectrometry to identify potential protein biomarker signatures for autism spectrum disorders.

While conventional ion mobility (IM) does not perform at the same level of selectivity and resolution as liquid and gas chromatography (LC and GC), IM separations are significantly faster than LC and GC (100s of ms vs. minutes), and IM can be coupled online with chromatography techniques or mass spectrometry (MS) imaging to further increase peak capacity (1).

Concomitant with chemical separations, IM provides an additional molecular measurement in the form of gas-phase collision cross sections (CCSs), which can provide further structural insight and an additional molecular descriptor useful for compound identifications (2). Many of the technical hurdles associated with integrating IM with MS, such as poor sensitivity and limited throughput, have largely been addressed in the latest generation technologies. However, one contemporary challenge of IM has been the limited resolution imposed by the conventionally short, sub-metre path lengths used.

High-resolution ion mobility-mass spectrometry (HRIM-MS) based on structures for lossless ion manipulation (SLIM) technology has emerged as a promising separation strategy due to the ease at which this architecture can be scaled up to longer separation path lengths. HRIM-MS uses printed circuit boards (PCBs) held in a chamber maintained at a constant, reduced pressure (2–4 Torr). The PCBs have a series of radio frequency (RF), direct current (DC), and travelling wave electrodes printed on them that provide an ion conduit through which the analytes traverse along a separation path. The electric fields that propel the ions also prevent them from striking surfaces while moving, therefore preventing any losses along their way. Depending upon the speed of the travelling wave, ions either “surf” and are not separated (as in a total ion transmission mode), or they undergo enough collisions with the gas molecules present that they roll over the travelling wave peaks and IM separation occurs (3,4).

In HRIM, as with other IM technologies, an ion’s migration time is determined by its gas-phase size-to-charge ratio, which is representative of the analyte size and shape. As ions are driven along the separation path, collision with an inert buffer gas slows them down to a degree proportional to their size. The length of the ion separation path is crucial to achieving the high degree of separation required to gain adequate resolution of compounds with challenging structural diversity. In this HRIM arrangement, the ion path is 13 m (roughly half the length of a tennis court), allowing for high resolution separation power in a compact design (Figure 1).

HRIM has emerged as a robust separation strategy for complex chemical analyses due to its ability to improve peak capacity and aid in the separation of isobaric signals.