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Online separation and identification of isomers using IRMPD ion spectroscopy coupled to liquid chromatography: application to the analysis of disaccharides regio-isomers and monosaccharide anomers Baptiste Schindler, Gabrielle Laloy-Borgna, Loic Barnes, Abdul-Rahman Allouche, Elodie Bouju, Vincent Dugas, Claire Demesmay, and Isabelle Compagnon Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b02801 • Publication Date (Web): 28 Aug 2018 Downloaded from http://pubs.acs.org on August 30, 2018

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Analytical Chemistry

Online separation and identification of isomers using IRMPD ion spectroscopy coupled to liquid chromatography: application to the analysis of disaccharides regio-isomers and monosaccharide anomers Baptiste Schindler,† Gabrielle Laloy-Borgna,† Loïc Barnes,† Abdul-Rahman Allouche,† Elodie Bouju,‡ Vincent Dugas,‡ Claire Demesmay‡ and Isabelle Compagnon†,§* †

Univ Lyon, Université Claude Bernard Lyon 1, CNRS, Institut Lumière Matière, F-69622 Villeurbanne, France Univ Lyon, CNRS, Université Claude Bernard Lyon 1, Ens de Lyon, Institut des Sciences Analytiques, UMR 5280, 5 rue de la Doua, F-69100 Villeurbanne, France § Institut Universitaire de France IUF, 103 Boulevard St Michel, Paris F-75005, France ‡

ABSTRACT: The vast array of molecular isomerisms which form the complex molecular structure of carbohydrates is the foundation of their biological versatility, but defies the analytical chemist. Hyphenations of Mass spectrometry with orthogonal structural characterization, such as ion mobility or ion spectroscopy, have recently shown great promise for distinction between closely related molecular structures. Yet, the lack of analytical strategies for identification of isomers present in mixtures remains a major obstacle to routine carbohydrate sequencing. In this context, an ideal workflow for glycomics would combine isomer separation and individual characterization of the molecular structure with atomistic resolution. Here we report the implementation of such a multidimensional analytical strategy, which consists of the first online coupling of HPLC-MS (High Performance Liquid Chromatography) and IRMPD spectroscopy (InfraRed Multiple Photon Dissociation). The performance of this novel workflow is exemplified in the case of monosaccharides (anomers) and disaccharides (regioisomers) standards. We report that the LC-MS-IRMPD approach offers a robust advanced MS diagnostic of mixtures of isomers, including carbohydrate anomers - which is critical for carbohydrate sequencing. Our results also explain the bimodal character generally observed in LC chromatograms of carbohydrates. More generally, this multidimensional analytical strategy opens the gateway to rapid identification of molecular isoforms with potential application in «omics» fields.

Molecular isomerism expresses nature’s ability to fine-tune biological activity and function; it is also a formidable challenge for analytical chemists. Glycomics is a typical illustration of this situation: on one hand, glycans show a remarkable range of biological functions modulated by various isomerisms (connectivity and configuration of the glycosidic linkage, monosaccharide content, functional modifications),1 and yet, analytical tools allowing robust and routine characterization of such subtle structural variations are still to be developed. Novel glycomics approaches include in particular the hyphenation of MS (Mass Spectrometry) based methods with a variety of ionization[Zhang Z, Linhardt R: Sequence analysis of native oligosaccharides using negative ESI tandem MS. Curr Anal Chem 2009, 5:225-237. ; HARVEY] and fragmentation techniques (collisions, photons, electrons)2–5 and a measure of additional structural information. GC has been widely used to distinguish between permethylated carbohydrate isomers REF. Ion mobility spectrometry (IMS) in particular, gives access to the collision cross section, which characterizes the “outer shape” of the molecule.6,7 [POHL/Bowers] Ion spectroscopy is also rapidly emerging as a key technique in the glycomics toolkit. Vibrational spectroscopy in particular is remarkably sensitive to the most subtle variations of the molecular structure, and can be in principle integrated to any MS-based workflow to complement MS analysis with highly diagnostic spec-

troscopic fingerprints. Following the pioneering work of John Simons,8 several spectroscopic schemes have been used to collect fingerprints of carbohydrate ions and to establish the sensitivity of the spectroscopic approach for the identification of all kinds of carbohydrate isomerisms.9–11 This type of advanced MS diagnostic has shown a remarkable analytical potential and a valuable complementarity with the resolving power of commercial Ion Mobility techniques. Among the variety of gas phase spectroscopy schemes,12 IRMPD (Infrared Multiple Photon dissociation) is certainly the most frugal and simplest to implement on any existing mass spectrometer equipped with an ion trap, and provides a refined signature of the molecular structure at the atomistic scale. We have recently reported that IRMPD spectroscopy provides an excellent diagnostic for all kind of isomerisms present in mono- and disaccharides. [REF N. Comms, Sufates] The groups of Oomens, Polfer and Compagnon have actively promoted the potential of IRMPD spectroscopy for analytical applications in the context of metabolomics13–15 and glycomics.11,16,17 However, in contrast with more elaborate spectroscopic schemes, IRMPD does not allow pre-selection of overlapping m/z ions, which considerably reduces its specificity when isoforms are present in mixtures in a sample. To overcome this limitation, IRMPD spectroscopy has been coupled with upstream separation techniques such as FAIMS (High-Field Asymmetric

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Waveform Ion Mobility Spectrometry)18 and IMS,19 or combined with semi-preparative HPLC where the sample is fractionated prior to IRMPD analysis.20,21 These hyphenations of separative methods and ion spectroscopy are paving the way towards isomer-specific structural mass spectrometry, and show great promise in the omics fields. In this context, online spectroscopic analysis of LC-MS selected ions is extremely appealing but faces a major obstacle: the timescale of analysis by LC (10 min) are not compatible. Here we report the first implementation of such online coupling for the analysis of mixture of isomers. This novel LC-MS-IRMPD workflow is validated on disaccharide standards (mixture of regio-isomers) and applied to the separation, identification and structural characterization of the anomer populations of glucosamine.

RESULTS AND DISCUSSION Spectroscopic analysis of LC-separated isomers. Tandem Mass Spectrometry (MS/MS) is widely used to identify molecular species, but may fail to provide diagnostic fingerprints of closely related isomers, such as stereo- or regio-isomers of carbohydrates. This situation is illustrated in Fig. 1b in the case of GlcNAcβ1,4GlcNAc (green MS/MS trace) and GlcNAcβ1,6GlcNAc (orange MS/MS trace) where both ions have the same mass (m/z 425) and show the same pattern of fragmentation upon standard collisional activation: a main B1 fragment at m/z 204 and two minor fragments at m/z 222 (C1 fragment) and m/z 407 (B2 fragment). In absence of diagnostic fragments, additional structural information is needed. As illustrated in Fig. 1c, GlcNAcβ1,4GlcNAc and GlcNAcβ1,6GlcNAc standards show distinctive IRMPD fingerprints (green and orange spectra, respectively) in the 2700-3700 cm-1 spectral range, which covers the CH stretching, NH stretching, and OH stretching vibrations. In contrast to traditional spectroscopy in the condensed phase, IRMPD applies to m/z-selected ions and can advantageously be used to collect the individual spectroscopic fingerprint of each species present in a mixture. When overlapping m/z ions are present, however, the resulting spectroscopic signature is a convolution of the ensemble and the identification of the individual species is hindered, as shown in Figure S1. To extend the range of analytical applications of ion spectroscopy, it is thus essential to separate isomeric species prior to spectroscopic analysis. Several hyphenations of IMS and ion spectroscopy have been proposed in this context, but the integration of spectroscopy in a LC-MS workflow has remained a major technical challenge. Indeed, recording an IRMPD spectrum over the 2700-3700 cm-1 spectral range requires about 30 minutes of ion signal, while the typical peakwidth in LC is less than 1 minute. As a consequence, IRMPD analysis of LC fractions has been possible20,21 but online LCMS-IRMPD has never been reported.

Here we establish that IRMPD measurements can be optimized in order to be achieved in about 6 minutes to become compatible with the online analysis of LC-separated isomers in stop flow mode. Details of the experimental methods are available in the supplementary information. Fig. 1a shows the LC chromatogram of a mixture of the two disaccharide standards GlcNAcβ1,4GlcNAc and GlcNAcβ1,6GlcNAc. Comparison with the reference LC traces of each standard (green trace: GlcNAcβ1,4GlcNAc; orange trace: GlcNAcβ1,6GlcNAc) shows that the first group of features (5 to 7 minutes) corresponds to the GlcNAcβ1,4GlcNAc signal, and the second group of features (8 to 10 minutes) corresponds to the GlcNAcβ1,6GlcNAc signal. The IRMPD spectra recorded in stopflow mode for each signal are displayed in black in Fig. 1c and are compared with the reference IRMPD spectrum of the corresponding standard. The two LC-MS-IRMPD fingerprints are distinct from each other and from the IRMPD spectrum of the mixture (Figure S1), which indicates that the individual contributions of the isomers present in the sample have been properly extracted. Upon visual inspection, it is clear that the fingerprints of the LC-separated isomers are very similar to the reference spectra: the position and shape of the bands match, and the local pattern of intensity (relative intensities of adjacent bands) is well reproduced. In this case, it is noteworthy that the IRMPD fingerprints do not show any baselineresolved isomer diagnostic band. Therefore the whole pattern of intensity must be considered for the comparison with reference spectra. This example highlights the importance of isomers separation prior to spectroscopic analysis and comparison with reference spectra when isomer-diagnostic bands are absent. Note that databases of reference IR signatures are central to interpret the data produced by this new workflow. Concerning mammalian glycans, which consist of a few dozen common monosaccharides, it is reasonable to consider populating a IR database of synthetic standards. For plants and bacterial saccharides however, hundreds of monosaccharides will have to be referenced, including rare ones for which standards are not available. In the future, it will thus become essential to couple our approach with databases of theoretical IR spectra. One can also question the universality of the spectroscopic diagnostic for the disambiguation of carbohydrate isomers. Indeed, as the size of the analyte increases, its fingerprint becomes congested in the OH diagnostic region and closely related isomers are difficult to identify [REF chitosans]. A number of strategies have been proposed to overcome this limitation, such as cold-ion spectroscopy [REF 9 et 10] which provides increased spectral resolution; and the fragment-based IRMPD approach, which re-focus the analysis on monosaccharide subunits. [NCOMMS, GAG 1, GAG2] We expect that the latter will be readily compatible with a LC-MS workflow.


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Figure 1. Comparison of the performance of the LC-MS/MS and LC-MS-IRMPD workflows. (a) LC chromatograms of GlcNAcβ1,4GlcNAc (green trace), GlcNAcβ1,6GlcNAc (orange trace) and the mixture of both isomers (black trace). (b) MS/MS spectra of the LC populations (black) and reference MS/MS spectra of the disaccharide standards GlcNAcβ1,4GlcNAc (green) and GlcNAcβ1,6GlcNAc (orange). (c) IRMPD fingerprints of the LC populations (black) and reference IRMPD spectra of the disaccharide standards GlcNAcβ1,4GlcNAc (green) and GlcNAcβ1,6GlcNAc (orange)

LC Separation and spectroscopic identification of anomers. While pure standards can be synthesized for MS databases, this is not true for α and β anomers. Only one of the forms is generally available in crystalline form, and interconverts in minutes to form equilibrium mixtures, which is not compatible with ESI-MS analysis. Besides, tandem MS does not provide diagnostic fingerprints of the two populations present in mixtures since there are no anomer-specific cleavages. Finally, IMS-MS analysis of monosaccharides does not show bimodal arrival time distributions (ATD), indicating that anomers cannot be separated based on their collision cross section at the currently achievable IMS resolution. In contrast, LC chromatograms of glycans often show bimodal distributions.22–24 Fig. 2a illustrates the case of the monosacharide standard glucosamine. This is generally interpreted as a signature of the two populations of anomers, but this hypothesis remains empirical: in absence of MS/MS diagnostic fragments, the nature of these two populations is not verified. Besides, the dynamics of mutarotation precludes the production of pure anomeric references by semi-preparative LC. As a consequence, reference MS signatures of individual anomers are not yet available although carbohydrate sequencing hingeson this diagnostic. Indeed, the stereochemistry of the glycosidic bond is retained upon MS/MS fragmentation, and can be identified by comparison with standards in pure anomeric configuration.11 In this context, it is timely to provide reference MS data for individual anomers. Early studies by John Simons suggested that IR spectroscopy in the gas phase offers sufficient structural resolution to

distinguish anomers.25 Later IRMPD studies confirmed that α and β populations have distinctive vibrational fingerprints, both of which can be observed in the heterogeneous IRMPD spectrum of monosaccharides,11,26–28 although their individual spectroscopic signatures have not been reported. This challenging case of structural heterogeneity is addressed using the LC-MS-IRMPD strategy established above. The LC chromatogram of glucosamine displayed in Fig. 2a shows a main feature with a maximum of ion intensity at 12 minutes, referred to as population I; and a secondary feature centered around 14 minutes, due to the presence of a second population (population II). Note that, given the higher intensity of peak I, its asymmetry and the lack of baseline separation, it is very likely that population II is contaminated by population I. Fig. 2b shows the IRMPD spectra (grey and black traces) of the two LC features, recorded in the 2800-3700 cm-1 spectral range in stop-flow mode. The two LC-IRMPD fingerprints are distinct. Population I (grey trace) has a broad, intense OH band at 3430 cm-1, which is weak in the spectrum of population II (black). In the NH range, the strongest feature for population I is a narrow peak at 3345 cm-1, while population II shows a broad, unresolved feature with two maxima at 3300 and 3324 cm-1. Such differences indicate that LC populations I and II correspond to two distinct molecular structures. Recent IRMPD studies suggest that 1-O-methylated species - which do not interconvert, and can be produced in pure α or β configurations - are good models to interpret the heterogeneous IRMPD spectrum of a natural monosaccharide.11,27 Here



we exploit this property to identify the two populations present in the LC chromatogram of glucosamine. Fig. 2c compare their IRMPD fingerprints to the reference spectra of α-1-Omethyl glucosamine (red trace) and β-1-O-methyl glucosamine (blue trace) from ref 11. It is clear that the LC-IRMPD fingerprint of population I closely resembles the reference IRMPD spectrum of the α-1-O-methyl glucosamine standard. One noteworthy exception is the strong intense peak observed at 3638 cm-1 in population I, which is missing in the spectrum of α-1-O-methyl glucosamine. This feature is therefore readily assigned to the vibration of the O1H group, which is absent in 1-O-methylated species. The rest of the spectra are virtually identical; population I is thus identified as α-glucosamine. Similarly, the LC-IRMPD fingerprint of population II resembles the reference spectrum of β-1-O-methyl glucosamine, again with the exception of the O1H band at 3638 cm-1. Some discrepancies can be observed however: β-1-O-methyl glucosamine does not absorb at 3345 cm-1 (main diagnostic α band in the NH range) or at 3430 cm-1 (broad diagnostic α band in the OH range), whereas the LC-IRMPD spectrum of population II shows some weak absorption at these positions. Besides that, the main diagnostic of the β configuration, i.e. a doublet of peaks around 3310 cm-1 in the NH range, is present in the LC-IRMPD fingerprint of population II. Population II is

therefore identified as β-glucosamine, with some contamination due to the slow decay of population I in the LC chromatogram. Closer examination of the IRMPD fingerprints of α- and βglucosamine reveals an additional level of structural heterogeneity. β-glucosamine shows 4 bands at 3670, 3638, 3611 and 3550 cm-1 in the OH range (the weak absorption at 3430 cm-1 arises from some α contamination and is disregarded). The band at 3638 cm-1 was previously identified as the O1H mode by comparison with β-1-O-methylglucosamine, and the three remaining bands correspond to the O3H, O4H and O6H vibrations. Quantum chemistry analysis allows us to interpret this pattern of OH vibrations in terms of molecular conformation. The band at 3550 cm-1 is found to be diagnostic of a 4C1 conformation (See Figure S2). In contrast, the LC-IRMPD fingerprint of α-glucosamine shows these four bands, plus a fifth band at 3430 cm-1. This additional band reveals the presence of a second stable conformation among the population of αglucosamine. Quantum chemistry validates the band at 3550 cm-1 as a diagnostic of a 4C1 conformation and the band at 3430 cm-1 as a diagnostic of a 1C4 conformation (Figure S2).

Figure 2. Application of the LC-MS-IRMPD workflow to the characterization of the structural heterogeneity of glucosamine. (a) LC chromatogram of glucosamine. (b) stable conformations of the α- and β-glucosamine ions obtained by DFT. (c) IRMPD fingerprints of LC populations I (grey trace) and II (black trace), reference IRMPD spectra of α-1-O-methyl glucosamine and β-1-O-methyl glucosamine standards (red and blue, respectively). Vibrational modes of interest for the conformational analysis are highlighted in orange and labelled.


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Corresponding Author

CONCLUSION

* [email protected]

We have demonstrated that an IRMPD spectrum can be acquired in only a few minutes, with enough structural resolution to identify closely related isomers. This increased speed of analysis enables online spectroscopic characterization of LC separated ions, and constitutes a breakthrough in terms of analytical applications of ion spectroscopy. Using this advanced LC-MS-IRMPD workflow, it has been possible to obtain direct MS signatures of individual carbohydrate anomers. The alpha and beta anomers of glucosamine were unambiguously identified by comparison with Density Functional Theory and with as 1-O-methylated models. Our results confirm that the bimodal distribution generally observed in the LC chromatograms of carbohydrates can be interpreted in terms of populations of anomers: in the case of glucosamine, the alpha population is observed at shorter retention time, and the beta population is observed at longer retention time. We expect that the IRMPD analysis of LC chromatograms will aid in the fundamental understanding of the intramolecular interaction responsible for the chromatographic separation of carbohydrates. These MS signatures of anomers are essential for carbohydrate sequencing because monosaccharide fragments obtained by collisional activation during MS/MS analysis of oligosaccharides hold the memory of the anomeric configuration of the glycosidic bond, which allows identification of its stereochemistry by comparison with monosaccharide standards in pure anomeric configuration. The LC-MS-IRMPD strategy presented here can furnish such reference data. While LC separation of anomers reduced the intrinsic heterogeneity of the IRMPD spectrum of glucosamine, it also unravelled a further level of structural heterogeneity of this ubiquitous monosaccharide. Density Functional theory was used to interpret the IRMPD signatures in terms of conformation of the ring, and revealed that β-glucosamine adopts a 4C1 conformation, as often observed for hexoses in both the gas phase and the condensed phase. More surprisingly, α-glucosamine co-exists in both 4C1 and 1C4 conformations. This contrasts with its counterparts glucose and N-acetylglucosamine, which were only observed in 4C1 conformation in similar conditions.6,27 This finding suggests that minor variations in the functionalization of glucose may critically affect the local conformation of a glycan chain, and thus its interaction with the environment. Finally, the LC-MS-IRMPD workflow reported here expands the MS toolkit with immediate applications in glycomics. More generally, we expect that this novel analytical strategy enabling identification of molecular isoforms in mixtures will have a broad impact in other «omics» fields.

ASSOCIATED CONTENT

ACKNOWLEDGMENT This work was supported by ANR Circé (grant ANR-16-CE300012), CNRS (programme de prématuration 2018), and was granted access to the HPC resources of the FLMSN, “Fédération Lyonnaise de Modélisation et Sciences Numériques”, partner of EQUIPEX EQUIP@MESO and to the “Centre de calcul CCIN2P3”. We thank Dr. A. Ross for proofreading.

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Supporting Information The Supporting Information is available free of charge on the ACS Publications website. Methods, IRMPD spectrum of a mixture of isomeric disaccharides and IRMPD spectrum of glucosamine compared to theoretical IR spectra (PDF)

AUTHOR INFORMATION

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