Distinguishing Oligosaccharide Isomers Using Far-Infrared Ion Spectroscopy: Identification of Biomarkers for Inborn Errors of Metabolism.

Distinguishing isomeric saccharides poses a major challenge for analytical workflows based on (liquid chromatography) mass spectrometry (LC-MS). In recent years, many studies have proposed infrared ion spectroscopy as a possible solution as the orthogonal, spectroscopic characterization of mass-selected ions can often distinguish isomeric species that remain unresolved using conventional MS. However, the high conformational flexibility and extensive hydrogen bonding in saccharides cause their room-temperature fingerprint infrared spectra to have broad features that often lack diagnostic value. Here, we show that room-temperature infrared spectra of ion-complexed saccharides recorded in the previously unexplored far-infrared wavelength range (300-1000 cm-1) provide well-resolved and highly diagnostic features. We show that this enables distinction of isomeric saccharides that differ either by their composition of monosaccharide units and/or the orientation of their glycosidic linkages. We demonstrate the utility of this approach from single monosaccharides up to isomeric tetrasaccharides differing only by the configuration of a single glycosidic linkage. Furthermore, through hyphenation with hydrophilic interaction liquid chromatography, we identify oligosaccharide biomarkers in patient body fluid samples, demonstrating a generalized and highly sensitive MS-based method for the identification of saccharides found in complex sample matrices.

Novel cerebrospinal fluid biomarkers of glucose transporter type 1 deficiency syndrome: Implications beyond the brain's energy deficit.

We used next-generation metabolic screening to identify new biomarkers for improved diagnosis and pathophysiological understanding of glucose transporter type 1 deficiency syndrome (GLUT1DS), comparing metabolic cerebrospinal fluid (CSF) profiles from 12 patients to those of 116 controls. This confirmed decreased CSF glucose and lactate levels in patients with GLUT1DS and increased glutamine at group level. We identified three novel biomarkers significantly decreased in patients, namely gluconic + galactonic acid, xylose-α1-3-glucose, and xylose-α1-3-xylose-α1-3-glucose, of which the latter two have not previously been identified in body fluids. CSF concentrations of gluconic + galactonic acid may be reduced as these metabolites could serve as alternative substrates for the pentose phosphate pathway. Xylose-α1-3-glucose and xylose-α1-3-xylose-α1-3-glucose may originate from glycosylated proteins; their decreased levels are hypothetically the consequence of insufficient glucose, one of two substrates for O-glucosylation. Since many proteins are O-glucosylated, this deficiency may affect cellular processes and thus contribute to GLUT1DS pathophysiology. The novel CSF biomarkers have the potential to improve the biochemical diagnosis of GLUT1DS. Our findings imply that brain glucose deficiency in GLUT1DS may cause disruptions at the cellular level that go beyond energy metabolism, underlining the importance of developing treatment strategies that directly target cerebral glucose uptake.

Increased throughput and ultra-high mass resolution in DESI FT-ICR MS imaging through new-generation external data acquisition system and advanced data processing approaches.

Desorption electrospray ionisation-mass spectrometry imaging (DESI-MSI) is a powerful imaging technique for the analysis of complex surfaces. However, the often highly complex nature of biological samples is particularly challenging for MSI approaches, as options to appropriately address molecular complexity are limited. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) offers superior mass accuracy and mass resolving power, but its moderate throughput inhibits broader application. Here we demonstrate the dramatic gains in mass resolution and/or throughput of DESI-MSI on an FT-ICR MS by developing and implementing a sophisticated data acquisition and data processing pipeline. The presented pipeline integrates, for the first time, parallel ion accumulation and detection, post-processing absorption mode Fourier transform and pixel-by-pixel internal re-calibration. To achieve that, first, we developed and coupled an external high-performance data acquisition system to an FT-ICR MS instrument to record the time-domain signals (transients) in parallel with the instrument's built-in electronics. The recorded transients were then processed by the in-house developed computationally-efficient data processing and data analysis software. Importantly, the described pipeline is shown to be applicable even to extremely large, up to 1 TB, imaging datasets. Overall, this approach provides improved analytical figures of merits such as: (i) enhanced mass resolution at no cost in experimental time; and (ii) up to 4-fold higher throughput while maintaining a constant mass resolution. Using this approach, we not only demonstrate the record 1 million mass resolution for lipid imaging from brain tissue, but explicitly show such mass resolution is required to resolve the complexity of the lipidome.

Independent assessment of matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) sample preparation quality: Effect of sample preparation on MALDI-MS of synthetic polymers.

RATIONALE: Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) provides detailed and in-depth information about the molecular characteristics of synthetic polymers. To obtain the most accurate results the sample preparation parameters should be chosen to suit the sample and the aim of the experiment. Because the underlying principles of MALDI are still not fully known, a priori determination of optimal sample preparation protocols is often not possible. METHODS: Employing an automated sample preparation quality assessment method recently presented by us we quantified the sample preparation quality obtained using various sample preparation protocols. Six conventional matrices with and without added potassium as a cationization agent and six ionic liquid matrices (ILMs) were assessed using poly(ethylene glycol) (PEG), polytetrahydrofuran (PTHF) and poly(methyl methacrylate) (PMMA) as samples. All sample preparation protocols were scored and ranked based on predefined quality parameters and spot-to-spot repeatability. RESULTS: Clearly distinctive preferences were observed in matrix identity and cationization agent for PEG, PTHF and PMMA, as the addition of an excess of potassium cationization agent results in an increased score for PMMA and a contrasting matrix-dependent effect for PTHF and PEG. The addition of excess cationization agent to sample mixtures dissipates any overrepresentation of high molecular weight polymer species. Our results show reduced ionization efficiency and similar sample deposit homogeneity for all tested ILMs, compared with well-performing conventional MALDI matrices. CONCLUSIONS: The results published here represent a start in the unsupervised quantification of sample preparation quality for MALDI samples. This method can select the best sample preparation parameters for any synthetic polymer sample and the results can be used to formulate hypotheses on MALDI principles. Copyright © 2016 John Wiley & Sons, Ltd.

Visualizing molecular distributions for biomaterials applications with mass spectrometry imaging: a review.

Mass spectrometry imaging (MSI) is a rapidly emerging field that is continually finding applications in new and exciting areas. The ability of MSI to measure the spatial distribution of molecules at or near the surface of complex substrates makes it an ideal candidate for many applications, including those in the sphere of materials chemistry. Continual development and optimization of both ionization sources and analyzer technologies have resulted in a wide array of MSI tools available, both commercially available and custom-built, with each configuration possessing inherent strengths and limitations. Despite the unique potential of MSI over other chemical imaging methods, their potential and application to (bio)materials science remains in our view a largely underexplored avenue. This review will discuss these techniques enabling high parallel molecular detection, focusing on those with reported uses in (bio)materials chemistry applications and highlighted with select applications. Different technologies are presented in three main sections; secondary ion mass spectrometry (SIMS) imaging, matrix-assisted laser desorption ionization (MALDI) MSI, and emerging MSI technologies with potential for biomaterial analysis. The first two sections (SIMS and MALDI) discuss well-established methods that are continually evolving both in technological advancements and in experimental versatility. In the third section, relatively new and versatile technologies capable of performing measurements under ambient conditions will be introduced, with reported applications in materials chemistry or potential applications discussed. The aim of this review is to provide a concise resource for those interested in utilizing MSI for applications such as biomimetic materials, biological/synthetic material interfaces, polymer formulation and bulk property characterization, as well as the spatial and chemical distributions of nanoparticles, or any other molecular imaging application requiring broad chemical speciation.

Independent assessment of matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) sample preparation quality: A novel statistical approach for quality scoring.

Preparation of samples according to an optimized method is crucial for accurate determination of polymer sample characteristics by Matrix-Assisted Laser Desorption Ionization (MALDI) analysis. Sample preparation conditions such as matrix choice, cationization agent, deposition technique or even the deposition volume should be chosen to suit the sample of interest. Many sample preparation protocols have been developed and employed, yet finding the optimal sample preparation protocol remains a challenge. Because an objective comparison between the results of diverse protocols is not possible, "gut-feeling" or "good enough" is often decisive in the search for an optimum. This implies that sub-optimal protocols are used, leading to a loss of mass spectral information quality. To address this problem a novel analytical strategy based on MALDI imaging and statistical data processing was developed in which eight parameters were formulated to objectively quantify the quality of sample deposition and optimal MALDI matrix composition and finally sum up to an overall quality score of the sample deposition. These parameters can be established in a fully automated way using commercially available mass spectrometry imaging instruments without any hardware adjustments. With the newly developed analytical strategy the highest quality MALDI spots were selected, resulting in more reproducible and more valuable spectra for PEG in a variety of matrices. Moreover, our method enables an objective comparison of sample preparation protocols for any analyte and opens up new fields of investigation by presenting MALDI performance data in a clear and concise way.

Fluorescence behavior of (selected) flavonols: a combined experimental and computational study.

In this article, results of (time-dependent) density functional theory (DFT and TDDFT) calculations are combined with experimental absorption and fluorescence measurements to explain fluorescence properties of a series of flavonols. The well-understood fluorescence properties of 3- and 5-hydroxyflavone are revisited and validate our combined experimental and theoretical approach. The accuracy of the computational data (energy differences for selected points at the PES, excitation energies and oscillator strengths) allows us to understand quite different experimentally observed fluorescence spectra in the presence of only subtle structural differences. We show that for flavonols with additional hydroxyl groups not the neutral molecule but rather anions lead to fluorescence and that solvation molecules need to be included explicitly in the theoretical calculations to obtain a sufficient accuracy-enabling the understanding and prediction of experimental data for flavonols belonging to different sub-classes.