Bioanalytic applications of mass spectrometry

Mass spectrometry has suddenly expanded out of research and assay laboratories into biology, medicine and therapeutics. Electrospray ionization and matrix-assisted laser desorption/ionization yield increased mass-range and sensitivity, leading to novel applications and sparking new analyzer designs, software, and robotics.     

Orbitrap mass analyzer--overview and applications in proteomics

The orbitrap mass analyzer is proving itself as a useful addition to a proteomics tool box. The key attributes of this analyzer are accurate mass and high resolution similar to those achievable with FT ICR instrumentation. The basic principles underlying these capabilities, and how they translate into benefits in real-life proteomics experiments are discussed. The focus is on reviewing examples of protein identification with bottom-up and top-down approaches, and detection of post-translational modifications.     

New applications of mass spectrometry in lipid analysis

Mass spectrometry has emerged as a powerful tool for the analysis of all lipids. Lipidomic analysis of biological systems using various approaches is now possible with a quantitative measurement of hundreds of lipid molecular species. Although availability of reference and internal standards lags behind the field, approaches using stable isotope-labeled derivative tagging permit precise determination of specific phospholipids in an experimental series. The use of reactivity of ozone has enabled assessment of double bond positions in fatty acyl groups even when species remain in complex lipid mixtures. Rapid scanning tandem mass spectrometers are capable of quantitative analysis of hundreds of targeted lipids at high sensitivity in a single on-line chromatographic separation. Imaging mass spectrometry of lipids in tissues has opened new insights into the distribution of lipid molecular species with promising application to study pathophysiological events and diseases.     

Recent advances in biomedical applications of accelerator mass spectrometry

The use of radioisotopes has a long history in biomedical science, and the technique of accelerator mass spectrometry (AMS), an extremely sensitive nuclear physics technique for detection of very low-abundant, stable and long-lived isotopes, has now revolutionized high-sensitivity isotope detection in biomedical research, because it allows the direct determination of the amount of isotope in a sample rather than measuring its decay, and thus the quantitative analysis of the fate of the radiolabeled probes under the given conditions. Since AMS was first used in the early 90's for the analysis of biological samples containing enriched ¹⁴C for toxicology and cancer research, the biomedical applications of AMS to date range from in vitro to in vivo studies, including the studies of 1) toxicant and drug metabolism, 2) neuroscience, 3) pharmacokinetics, and 4) nutrition and metabolism of endogenous molecules such as vitamins. In addition, a new drug development concept that relies on the ultrasensitivity of AMS, known as human microdosing, is being used to obtain early human metabolism information of candidate drugs. These various aspects of AMS are reviewed and a perspective on future applications of AMS to biomedical research is provided.     

Missing values in mass spectrometry based metabolomics: an undervalued step in the data processing pipeline

Missing values in mass spectrometry metabolomic datasets occur widely and can originate from a number of sources, including for both technical and biological reasons. Currently, little is known about these data, i.e. about their distributions across datasets, the need (or not) to consider them in the data processing pipeline, and most importantly, the optimal way of assigning them values prior to univariate or multivariate data analysis. Here, we address all of these issues using direct infusion Fourier transform ion cyclotron resonance mass spectrometry data. We have shown that missing data are widespread, accounting for ca. 20% of data and affecting up to 80% of all variables, and that they do not occur randomly but rather as a function of signal intensity and mass-to-charge ratio. We have demonstrated that missing data estimation algorithms have a major effect on the outcome of data analysis when comparing the differences between biological sample groups, including by t test, ANOVA and principal component analysis. Furthermore, results varied significantly across the eight algorithms that we assessed for their ability to impute known, but labelled as missing, entries. Based on all of our findings we identified the k-nearest neighbour imputation method (KNN) as the optimal missing value estimation approach for our direct infusion mass spectrometry datasets. However, we believe the wider significance of this study is that it highlights the importance of missing metabolite levels in the data processing pipeline and offers an approach to identify optimal ways of treating missing data in metabolomics experiments.

     

Missing values in mass spectrometry based metabolomics: an undervalued step in the data processing pipeline

Missing values in mass spectrometry metabolomic datasets occur widely and can originate from a number of sources, including for both technical and biological reasons. Currently, little is known about these data, i.e. about their distributions across datasets, the need (or not) to consider them in the data processing pipeline, and most importantly, the optimal way of assigning them values prior to univariate or multivariate data analysis. Here, we address all of these issues using direct infusion Fourier transform ion cyclotron resonance mass spectrometry data. We have shown that missing data are widespread, accounting for ca. 20% of data and affecting up to 80% of all variables, and that they do not occur randomly but rather as a function of signal intensity and mass-to-charge ratio. We have demonstrated that missing data estimation algorithms have a major effect on the outcome of data analysis when comparing the differences between biological sample groups, including by t test, ANOVA and principal component analysis. Furthermore, results varied significantly across the eight algorithms that we assessed for their ability to impute known, but labelled as missing, entries. Based on all of our findings we identified the k-nearest neighbour imputation method (KNN) as the optimal missing value estimation approach for our direct infusion mass spectrometry datasets. However, we believe the wider significance of this study is that it highlights the importance of missing metabolite levels in the data processing pipeline and offers an approach to identify optimal ways of treating missing data in metabolomics experiments.     

Synthesis of releasable electrophore tags for applications in mass spectrometry

Releasable electrophore mass tags (electrophore tags) are compounds for use as labels in ligand assays such as hybridization assays and immunoassays. In such assays, the electrophore-tagged reagent (e.g., DNA probe or antibody) is quantified at the conclusion of the assay by cleaving a bond in the attached tag so that the electrophore part can be brought into the gas phase (usually thermally) for detection by electron capture mass spectrometry (EC-MS) or a related technique. Interest in these tags is promoted mainly by their potential to provide highly sensitive and multiplexed assays. The high multiplexing arises from the opportunity to measure many such tags simultaneously in the mass spectrometer, where each tag has an electrophore part with a unique mass. In this study five precursors of electrophore mass tags are presented. Each precursor can lead to a large library of electrophore tags in a practical way, since each precursor can be converted to many different electrophore tags by reaction with commonly available phenols that provide a variation in mass. The phenol-reactive part of the tag is either a polyfluorobiphenyl or a benzyl chloride moiety. Representative library compounds are prepared and detected in an inert ester form by gas chromatography electron capture mass spectrometry (GC-EC-MS). Further, one tag is conjugated to DNA, and the resulting product is detected by laser-induced electron capture time-of-flight mass spectrometry on a silver surface. A calculation by the semiempirical method AM1 for an ion formed by one of the electrophores suggests that ring rotation promotes dissociative electron capture. The features of practical synthesis, simple composition, physicochemical stability, high multiplicity, high sensitivity, and potential for high throughput detection make releasable electrophore mass tags attractive for highly multiplexed assays. This includes their use in SNP assays or dideoxy DNA sequencing for detection of mutations in individuals, where the combination of high accuracy and speed is essential.     

Prospective applications of ultrahigh resolution proteomics in clinical mass spectrometry

Introduction: Advances in mass spectrometry (MS)-based proteomic strategies have resulted in robust protein biomarker discovery studies often performed on high resolution accurate mass (HRAM) platforms. For successful translation of promising protein biomarkers into useful clinical tests, trans-sector networks and collaboration among stakeholders involved in the biomarker pipeline are urgently needed.

Areas covered: In this perspective, literature- and empirical evidence is combined with author’s opinions to discuss the progress of ultrahigh resolution MS and provide insight in its potential for validation and development of clinical tests.

Expert commentary: Thus far two ‘low resolution’ MS strategies have been implemented in the clinic: quantification of proteins using triple quadrupole instruments and identification of unknown microorganisms using comparative analysis with spectral libraries on MALDI-TOF instruments. The rise of HRAM technology further boosts the potential of MS-based tests for detection and quantitation of disease-specific biomarkers which meet the analytical performance specifications needed for clinical assays.     

Multistationarity in mass action networks with applications to ERK activation

Ordinary Differential Equations (ODEs) are an important tool in many areas of Quantitative Biology. For many ODE systems multistationarity (i.e. the existence of at least two positive steady states) is a desired feature. In general establishing multistationarity is a difficult task as realistic biological models are large in terms of states and (unknown) parameters and in most cases poorly parameterized (because of noisy measurement data of few components, a very small number of data points and only a limited number of repetitions). For mass action networks establishing multistationarity hence is equivalent to establishing the existence of at least two positive solutions of a large polynomial system with unknown coefficients. For mass action networks with certain structural properties, expressed in terms of the stoichiometric matrix and the reaction rate-exponent matrix, we present necessary and sufficient conditions for multistationarity that take the form of linear inequality systems. Solutions of these inequality systems define pairs of steady states and parameter values. We also present a sufficient condition to identify networks where the aforementioned conditions hold. To show the applicability of our results we analyse an ODE system that is defined by the mass action network describing the extracellular signal-regulated kinase (ERK) cascade (i.e. ERK-activation).     

Vicinism and mass effect

Abstract. The term vicinism (neighbourship), first published in a phytosociological context by Nordhagen, refers to the occurrence of plant species in a less favourable environment -outside their sociological (ecological) amplitude — as a result of the continuous supply of propagules from neighbouring areas. In recent studies on this subject the term mass effect has been used for what seems to be the same phenomenon. This is unfortunate since this term was introduced much earlier to indicate the ability of plants which are able to grow in dense stands in order to change the local environment to the benefit of themselves — physically, chemically or mechanically- by developing a dense vegetation cover. Examples of this mass effect are mainly found in extreme environments such as salt marshes and lake shores. The occurrence of both vicinism and mass effect indicates that competition is not the only biological factor important in selection. Vicinism also contributes to connectivity, a major topic in landscape ecology. Both vicinism and connectivity as synecological concepts in their original meaning deserve more attention from ecologists.     

General tissue mass transfer model for cryopreservation applications

Successful cryopreservation of complex specimens, such as tissues and organs, would greatly benefit both the medical and scientific research fields. Vitrification is one of the most promising techniques for complex specimen cryopreservation, but toxicity remains a major challenge because of the high concentration of cryoprotectants (CPAs) needed to vitrify. Our group has approached this problem using mathematical optimization to design less toxic CPA equilibration methods for cells. To extend this approach to tissues, an appropriate mass transfer model is required. Fick’s law is commonly used, but this simple modeling framework does not account for the complexity of mass transfer in tissues, such as the effects of fixed charges, tissue size changes, and the interplay between cell membrane transport and transport through the extracellular fluid. Here, we propose a general model for mass transfer in tissues that accounts for all of these phenomena. To create this model, we augmented a previously published acellular model of mass transfer in articular cartilage to account for the effects of cells. We show that the model can accurately predict changes in CPA concentration and tissue size for both articular cartilage and pancreatic islets, tissue types with vastly different properties.     

Correction: Recent advances in biomedical applications of accelerator mass spectrometry

After publication of our article, it was noted that we inadvertently failed to include the complete list of authors. The full list, including co-authors, has now been added and the Authors' contributions and Competing interests sections modified accordingly.     

Proteomic applications of protein quantification by isotope-dilution mass spectrometry

Over the decades, isotope-dilution mass spectrometry (IDMS) has been implemented extensively for accurate quantification of drugs, metabolites and peptides in body fluids and tissues. More recently, it has been extended for quantifying specific proteins in complex mixtures. In this extended methodology, proteins are subjected to endoprotease action and specific resultant peptides are quantified by using synthetic stable isotope-labeled standard (SIS) peptides and IDMS. This article outlines the utilities and applications of quantifying proteins by IDMS, emphasizing its complementary value to global survey-based proteomic studies. The potential of SIS peptides to provide quantitative insights into cell signaling is also highlighted, with specific examples. Finally, we propose several novel mass spectrometric data acquisition strategies for large-scale applications of IDMS and SIS peptides in systems biology and protein biomarker validation studies.     

Analytical model of peptide mass cluster centres with applications

Background  

The elemental composition of peptides results in formation of distinct, equidistantly spaced clusters across the mass range. The property of peptide mass clustering is used to calibrate peptide mass lists, to identify and remove non-peptide peaks and for data reduction.     

Investigation of protein-RNA interactions by mass spectrometry--Techniques and applications

Protein-RNA complexes play many important roles in diverse cellular functions. They are involved in a wide variety of different processes in growth and differentiation at the various stages of the cell cycle. As their function and catalytic activity are directly coupled to the structural arrangement of their components--proteins and ribonucleic acids--the investigation of protein-RNA interactions is of great functional and structural importance. Here we discuss the most prominent examples of protein-RNA complexes and describe some frequently used purification strategies. We present various techniques and applications of mass spectrometry to study protein-RNA complexes. We discuss the analysis of intact complexes as well as proteomics-based and crosslinking-based approaches in which proteins are cleaved into smaller peptides. This article is part of a Special Section entitled: Understanding genome regulation and genetic diversity by mass spectrometry.     

Thematic minireview series on biological applications of mass spectrometry

Mass spectrometry is a powerful technique with many applications in biology as well as chemistry and physics. The increases in sensitivity and resolution of the instruments, coupled with improvements in the analysis of data, have opened new dimensions in analyses of complex biological systems. Examples presented here include drug metabolism, lipid analysis, metabolomics, quantitative proteomics, direct analysis of intact proteins, and imaging of both small molecules and proteins in tissues.     

Construction of simultaneous SPR and QCM sensing platform

To construct a novel simultaneous SPR and QCM sensing system, an AT-cut quartz crystal is fabricated by sputtering 250 nm of ITO on one side of the quartz plate over a 5-nm thick underlay of titanium, while a 50-nm thick layer of gold is sputter-deposited on the other side to induce a total light reflection of an incident laser beam on the thin gold layer. The signals of the sensing system are detected using a Handy-SPR and QCA922 when dropping 200 μL of Milli-Q water into the sensing cell. A decrease in the SPR reflected light intensity is clearly identified. In the same experiment, the changes in the resonant frequency and resistance are about 2 kHz and 200 Ω, respectively. Furthermore, the oscillation stabilities of the resonant frequency and resistance are about 50 Hz and 2 Ω, respectively, which are sufficient to detect a large mass change on the QCM/SPR chip.     

Electrospray ionisation mass spectrometry: principles and clinical applications

This mini-review provides a general understanding of electrospray ionisation mass spectrometry (ESI-MS) which has become an increasingly important technique in the clinical laboratory for structural study or quantitative measurement of metabolites in a complex biological sample. The first part of the review explains the electrospray ionisation process, design of mass spectrometers with separation capability, characteristics of the mass spectrum, and practical considerations in quantitative analysis. The second part then focuses on some clinical applications. The capability of ESI-tandem-MS in measuring bio-molecules sharing similar molecular structures makes it particularly useful in screening for inborn errors of amino acid, fatty acid, purine, pyrimidine metabolism and diagnosis of galactosaemia and peroxisomal disorders. Electrospray ionisation is also efficient in generating cluster ions for structural elucidation of macromolecules. This has fostered a new and improved approach (vs electrophoresis) for identification and quantification of haemoglobin variants. With the understanding of glycohaemoglobin structure, an IFCC reference method for glycohaemoglobin assay has been established using ESI-MS. It represents a significant advancement for the standardisation of HbA1c in diabetic monitoring. With its other applications such as in therapeutic drug monitoring, ESI-MS will continue to exert an important influence in the future development and organisation of the clinical laboratory service.