Developments in FTICR-MS and Its Potential for Body Fluid Signatures

Mass spectrometry-based metabolomics for discovering active ingredients and exploring action mechanism of herbal medicine

Natural products derived from herbal medicine are a fruitful source of lead compounds because of their structural diversity and potent bioactivities. However, despite the success of active compounds derived from herbal medicine in drug discovery, some approaches cannot effectively elucidate the overall effect and action mechanism due to their multi-component complexity. Fortunately, mass spectrometry-based metabolomics has been recognized as an effective strategy for revealing the effect and discovering active components, detailed molecular mechanisms, and multiple targets of natural products. Rapid identification of lead compounds and isolation of active components from natural products would facilitate new drug development. In this context, mass spectrometry-based metabolomics has established an integrated pharmacology framework for the discovery of bioactivity-correlated constituents, target identification, and the action mechanism of herbal medicine and natural products. High-throughput functional metabolomics techniques could be used to identify natural product structure, biological activity, efficacy mechanisms, and their mode of action on biological processes, assisting bioactive lead discovery, quality control, and accelerating discovery of novel drugs. These techniques are increasingly being developed in the era of big data and use scientific language to clarify the detailed action mechanism of herbal medicine. In this paper, the analytical characteristics and application fields of several commonly used mass spectrometers are introduced, and the application of mass spectrometry in the metabolomics of traditional Chinese medicines in recent years and its active components as well as mechanism of action are also discussed.

Streamlined Multimodal DESI and MALDI Mass Spectrometry Imaging on a Singular Dual-Source FT-ICR Mass Spectrometer

The study of biological specimens by mass spectrometry imaging (MSI) has had a profound influence in the various forms of spatial-omics over the past two decades including applications for the identification of clinical biomarker analysis; the metabolic fingerprinting of disease states; treatment with therapeutics; and the profiling of lipids, peptides and proteins. No singular approach is able to globally map all biomolecular classes simultaneously. This led to the development of many complementary multimodal imaging approaches to solve analytical problems: fusing multiple ionization techniques, imaging microscopy or spectroscopy, or local extractions into robust multimodal imaging methods. However, each fusion typically requires the melding of analytical information from multiple commercial platforms, and the tandem utilization of multiple commercial or third-party software platforms—even in some cases requiring computer coding. Herein, we report the use of matrix-assisted laser desorption/ionization (MALDI) in tandem with desorption electrospray ionization (DESI) imaging in the positive ion mode on a singular commercial orthogonal dual-source Fourier transform ion cyclotron resonance (FT-ICR) instrument for the complementary detection of multiple analyte classes by MSI from tissue. The DESI source was 3D printed and the commercial Bruker Daltonics software suite was used to generate mass spectrometry images in tandem with the commercial MALDI source. This approach allows for the generation of multiple modes of mass spectrometry images without the need for third-party software and a customizable platform for ambient ionization imaging. Highlighted is the streamlined workflow needed to obtain phospholipid profiles, as well as increased depth of coverage of both annotated phospholipid, cardiolipin, and ganglioside species from rat brain with both high spatial and mass resolution.

High-throughput glycopeptide profiling of prostate-specific antigen from seminal plasma by MALDI-MS

An altered total seminal plasma glycosylation has been associated with male infertility, and the highly abundant seminal plasma glycoprotein prostate-specific antigen (PSA) plays an important role in fertilization. However, the exact role of PSA glycosylation in male fertility is not clear. To understand the involvement of PSA glycosylation in the fertilization process, analytical methods are required to study the glycosylation of PSA from seminal plasma with a high glycoform resolution and in a protein-specific manner. In this study, we developed a novel, high-throughput PSA glycopeptide workflow, based on matrix-assisted laser desorption/ionization-mass spectrometry, allowing the discrimination of sialic acid linkage isomers via the derivatization of glycopeptides. The method was successfully applied on a cohort consisting of seminal plasma from infertile and fertile men (N = 102). Forty-four glycopeptides were quantified in all samples, showing mainly complex-type glycans with high levels of fucosylation and sialylation. In addition, N,N-diacetyllactosamine (LacdiNAc) motives were found as well as hybrid-type and high mannose-type structures. Our method showed a high intra- and interday repeatability and revealed no difference in PSA glycosylation between fertile and infertile men. Next to seminal plasma, the method is also expected to be of use for studying PSA glycopeptides derived from other biofluids and/or in other disease contexts.

Extending the information content of the MALDI analysis of biological fluids via multi-million shot analysis

INTRODUCTION

Reliable measurements of the protein content of biological fluids like serum or plasma can provide valuable input for the development of personalized medicine tests. Standard MALDI analysis typically only shows high abundance proteins, which limits its utility for test development. It also exhibits reproducibility issues with respect to quantitative measurements. In this paper we show how the sensitivity of MALDI profiling of intact proteins in unfractionated human serum can be substantially increased by exposing a sample to many more laser shots than are commonly used. Analytical reproducibility is also improved.

METHODS

To assess what is theoretically achievable we utilized spectra from the same samples obtained over many years and combined them to generate MALDI spectral averages of up to 100,000,000 shots for a single sample, and up to 8,000,000 shots for a set of 40 different serum samples. Spectral attributes, such as number of peaks and spectral noise of such averaged spectra were investigated together with analytical reproducibility as a function of the number of shots. We confirmed that results were similar on MALDI instruments from different manufacturers.

RESULTS

We observed an expected decrease of noise, roughly proportional to the square root of the number of shots, over the whole investigated range of the number of shots (5 orders of magnitude), resulting in an increase in the number of reliably detected peaks. The reproducibility of the amplitude of these peaks, measured by CV and concordance analysis also improves with very similar dependence on shot number, reaching median CVs below 2% for shot numbers > 4 million. Measures of analytical information content and association with biological processes increase with increasing number of shots.

CONCLUSIONS

We demonstrate that substantially increasing the number of laser shots in a MALDI-TOF analysis leads to more informative and reliable data on the protein content of unfractionated serum. This approach has already been used in the development of clinical tests in oncology.

Assessment of the Utility of the Oral Fluid and Plasma Proteomes for Hydrocodone Exposure

INTRODUCTION

Non-medical use and abuse of prescription opioids is a growing problem in both the civilian and military communities, with minimal technologies for detecting hydrocodone use. This study explored the proteomic changes that occur in the oral fluid and blood plasma following controlled hydrocodone administration in 20 subjects.

METHODS

The global proteomic profile was determined for samples taken at four time points per subject: pre-exposure and 4, 6, or 168 hours post-exposure. The oral fluid samples analyzed herein provided greater differentiation between baseline and response time points than was observed with blood plasma, at least partially due to significant person-to-person relative variability in the plasma proteome.

RESULTS

A total of 399 proteins were identified from oral fluid samples, and the abundance of 118 of those proteins was determined to be significantly different upon metabolism of hydrocodone (4 and 6 hour time points) as compared to baseline levels in the oral fluid (pre-dose and 168 hours).

CONCLUSIONS

We present an assessment of the oral fluid and plasma proteome following hydrocodone administration, which demonstrates the potential of oral fluid as a noninvasive sample that may reveal features of hydrocodone in opioid use, and with additional study, may be useful for other opioids and in settings of misuse.

Automated Plasma Glycomics with Linkage-Specific Sialic Acid Esterification and Ultrahigh Resolution MS

High-throughput mass spectrometry (MS) glycomics is an emerging field driven by technological advancements including sample preparation and data processing. Previously, we reported an automated protocol for the analysis of N-glycans released from plasma proteins that included sialic acid derivatization with linkage-specificity, namely, ethylation of α2,6-linked sialic acid residues and lactone formation of α2,3-linked sialic acids. In the current study, each step in this protocol was further optimized. Method improvements included minimizing the extent of side-reaction during derivatization, an adjusted glycan purification strategy and mass analysis of the released N-glycans by ultrahigh resolution matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance MS. The latter resolved peak overlap and simplified spectral alignment due to high mass measurement precision. Moreover, this resulted in more confident glycan assignments and improved signal-to-noise for low-abundant species. The performance of the protocol renders high-throughput applications feasible in the exciting field of clinical glycomics.

Foodomics and Food Safety: Where We Are

The power of foodomics as a discipline that is now broadly used for quality assurance of food products and adulteration identification, as well as for determining the safety of food, is presented. Concerning sample preparation and application, maintenance of highly sophisticated instruments for both high-performance and high-throughput techniques, and analysis and data interpretation, special attention has to be paid to the development of skilled analysts. The obtained data shall be integrated under a strong bioinformatics environment. Modern mass spectrometry is an extremely powerful analytical tool since it can provide direct qualitative and quantitative information about a molecule of interest from only a minute amount of sample. Quality of this information is influenced by the sample preparation procedure, the type of mass spectrometer used and the analyst's skills. Technical advances are bringing new instruments of increased sensitivity, resolution and speed to the market. Other methods presented here give additional information and can be used as complementary tools to mass spectrometry or for validation of obtained results. Genomics and transcriptomics, as well as affinity-based methods, still have a broad use in food analysis. Serious drawbacks of some of them, especially the affinity-based methods, are the cross-reactivity between similar molecules and the influence of complex food matrices. However, these techniques can be used for pre-screening in order to reduce the large number of samples. Great progress has been made in the application of bioinformatics in foodomics. These developments enabled processing of large amounts of generated data for both identification and quantification, and for corresponding modeling.

Structural Characterization of Biofunctionalized Gold Nanoparticles by Ultrahigh-Resolution Mass Spectrometry

Biofunctionalized gold nanoparticles (AuNPs) enable innovative translational research and development in biomedicine. Biomolecules such as peptides, proteins, lipids, and carbohydrates can be assembled onto AuNPs to yield nanomaterials with unique properties for applications in imaging, photothermal therapy, vaccination strategies, and drug delivery. The characterization of functionalized AuNPs still remains an analytical challenge that normally requires the combination of multiple techniques. Laser desorption/ionization (LDI) and matrix-assisted LDI (MALDI) have been applied successfully in combination with time-of-flight (TOF) mass spectrometry (MS) for the analysis of the surface chemistry of AuNPs functionalized with synthetic ligands, however only for ligands with a molecular mass limited to 1000 Da. TOF-MS-based approaches in addition exhibit limited performance in terms of mass resolution and MS/MS possibilities. To overcome these limitations, we designed an approach for the analysis of AuNPs based on ultrahigh resolution Fourier transform ion cyclotron resonance (FTICR) MS and a combination of LDI and MALDI. To illustrate the performance of the method, we present a comprehensive characterization of the surface chemistry of AuNPs conjugated via a thiol-ending linker to either the ovalbumin peptide (OVA 323-339), the Lewis X antigen (Galβ1-4[Fucα1-3]GlcNAcβ1) trisaccharide, the tetramannoside Manα1-2Manα1-2Manα1-3Manα1, or a mixture of both carbohydrates. Collision-induced dissociation (CID) was used to characterize the structure of pseudomolecular ions generated by LDI/MALDI in-depth. These included [M + H]⁺ and [M + Na]⁺, and importantly also [M + Au]⁺ and [M + 2Au-H]⁺ ions. This first observation of gold-containing pseudomolecular ions provides direct evidence for the Au-conjugation of ligands. In addition, we show the applicability of the method to monitor proteolytic cleavage of peptides that are conjugated to the AuNP surface. The presented LDI/MALDI-FTICR-MS and MS/MS approach will be applicable to the characterization of a wide range of functionalized AuNPs.

Metabolomics for clinical use and research in chronic kidney disease

Chronic kidney disease (CKD) has a high prevalence in the general population and is associated with high mortality; a need therefore exists for better biomarkers for diagnosis, monitoring of disease progression and therapy stratification. Moreover, very sensitive biomarkers are needed in drug development and clinical research to increase understanding of the efficacy and safety of potential and existing therapies. Metabolomics analyses can identify and quantify all metabolites present in a given sample, covering hundreds to thousands of metabolites. Sample preparation for metabolomics requires a very fast arrest of biochemical processes. Present key technologies for metabolomics are mass spectrometry and proton nuclear magnetic resonance spectroscopy, which require sophisticated biostatistic and bioinformatic data analyses. The use of metabolomics has been instrumental in identifying new biomarkers of CKD such as acylcarnitines, glycerolipids, dimethylarginines and metabolites of tryptophan, the citric acid cycle and the urea cycle. Biomarkers such as c-mannosyl tryptophan and pseudouridine have better performance in CKD stratification than does creatinine. Future challenges in metabolomics analyses are prospective studies and deconvolution of CKD biomarkers from those of other diseases such as metabolic syndrome, diabetes mellitus, inflammatory conditions, stress and cancer.

Applications of Fourier Transform Ion Cyclotron Resonance (FT-ICR) and Orbitrap Based High Resolution Mass Spectrometry in Metabolomics and Lipidomics

Metabolomics, along with other "omics" approaches, is rapidly becoming one of the major approaches aimed at understanding the organization and dynamics of metabolic networks. Mass spectrometry is often a technique of choice for metabolomics studies due to its high sensitivity, reproducibility and wide dynamic range. High resolution mass spectrometry (HRMS) is a widely practiced technique in analytical and bioanalytical sciences. It offers exceptionally high resolution and the highest degree of structural confirmation. Many metabolomics studies have been conducted using HRMS over the past decade. In this review, we will explore the latest developments in Fourier transform mass spectrometry (FTMS) and Orbitrap based metabolomics technology, its advantages and drawbacks for using in metabolomics and lipidomics studies, and development of novel approaches for processing HRMS data.

Typing Pseudomonas aeruginosa Isolates with Ultrahigh Resolution MALDI-FTICR Mass Spectrometry

The introduction of standardized matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) platforms in the medical microbiological practice has revolutionized the way microbial species identification is performed on a daily basis. To a large extent, this is due to the ease of operation. Acquired spectra are compared to profiles obtained from cultured colonies present in a reference spectra database. It is fast and reliable, and costs are low compared to previous diagnostic approaches. However, the low resolution and dynamic range of the MALDI-TOF profiles have shown limited applicability for the discrimination of different bacterial strains, as achieved with typing based on genetic markers. This is pivotal in cases where certain strains are associated with, e.g., virulence or antibiotic resistance. Ultrahigh resolution MALDI-FTICR MS allows the measurement of small proteins at isotopic resolution and can be used to analyze complex mixtures with increased dynamic range and higher precision than MALDI-TOF MS, while still generating results in a similar time frame. Here, we propose to use ultrahigh resolution 15T MALDI-Fourier transform ion cyclotron resonance (FTICR) MS to discriminate clinically relevant bacterial strains after species identification performed by MALDI-TOF MS. We used a collection of well characterized Pseudomonas aeruginosa strains, featuring distinct antibiotic resistance profiles, and isolates obtained during hospital outbreaks. Following cluster analysis based on amplification fragment length polymorphism (AFLP), these strains were grouped into three different clusters. The same clusters were obtained using protein profiles generated by MALDI-FTICR MS. Subsequent intact protein analysis by electrospray ionization (ESI)-collision-induced dissociation (CID)-FTICR MS was applied to identify protein isoforms that contribute to the separation of the different clusters, illustrating the additional advantage of this analytical platform.