"Mass defect" tags for biomolecular mass spectrometry

Investigation and Development of the BODIPY-Embedded Isotopic Signature for Chemoproteomics Labeling and Targeted Profiling

A common goal in mass spectrometry-based chemoproteomics is to directly measure the site of conjugation between the target protein and the small molecule ligand. However, these experiments are inherently challenging due to the low abundance of labeled proteins and the difficulty in identifying modification sites using standard proteomics software. Reporter tags that either generate signature fragment ions or isotopically encode target peptides can be used for the preemptive discovery of labeled peptides even in the absence of identification. We investigated the potential of BODIPY FL azide as a click chemistry enabled chemoproteomics reagent due to the presence of boron and the unique 1:4 natural abundance ratio of 10B:11B. The isotopes of boron encode BODIPY-labeled peptides with a predictable pattern between the monoisotopic (M) and M+1 peaks. BODIPY-labeled peptides were identified in MS1 spectra using an R script that filters for the signature 10B:11B intensity ratio and mass defect. Application of the boron detection script resulted in three times the labeled peptide coverage achieved for a BODIPY-conjugated BSA sample compared with untargeted data-dependent acquisition sequencing. Furthermore, we used the inherent HF neutral loss signature from BODIPY to assist with BODIPY-modified peptide identification. Finally, we demonstrate the application of this approach using the BODIPY-conjugated BSA sample spiked into a complex E. coli. digest. In summary, our results show that the commercially available BODIPY FL azide clicked to alkyne-labeled peptides provides a unique isotopic signature for pinpointing the site(s) of modification with the added potential for on- or off-line UV or fluorescence detection.

Iodine-Containing Mass-Defect-Tuned Dendrimers for Use as Internal Mass Spectrometry Calibrants

Calibrants based on synthetic dendrimers have been recently proposed as a versatile alternative to peptides and proteins for both MALDI and ESI mass spectrometry calibration. Because of their modular synthetic platform, dendrimer calibrants are particularly amenable to tailoring for specific applications. Utilizing this versatility, a set of dendrimers has been designed as an internal calibrant with a tailored mass defect to differentiate them from the majority of natural peptide analytes. This was achieved by incorporating a tris-iodinated aromatic core as an initiator for the dendrimer synthesis, thereby affording multiple calibration points (m/z range 600-2300) with an optimized mass-defect offset relative to all peptides composed of the 20 most common proteinogenic amino acids. Graphical abstract ᅟ.

Mass Defect from Nuclear Physics to Mass Spectral Analysis

Mass defect is associated with the binding energy of the nucleus. It is a fundamental property of the nucleus and the principle behind nuclear energy. Mass defect has also entered into the mass spectrometry terminology with the availability of high resolution mass spectrometry and has found application in mass spectral analysis. In this application, isobaric masses are differentiated and identified by their mass defect. What is the relationship between nuclear mass defect and mass defect used in mass spectral analysis, and are they the same? Graphical Abstract ᅟ.

An efficient data-filtering strategy for easy metabolite detection from the direct analysis of a biological fluid using Fourier transform mass spectrometry

RATIONALE

High-throughput analyses require an overall analytical workflow including not only a robust and high-speed technical platform, but also dedicated data-processing tools able to extract the relevant information. This work aimed at evaluating post-acquisition data-mining tools for selective extraction of metabolite species from direct introduction high-resolution mass spectrometry data.

METHODS

Investigations were performed on spectral data in which seven metabolites of vinclozolin, a dicarboximide fungicide containing two chloride atoms, were previously manually identified. The spectral data obtained from direct introduction (DI) and high-resolution mass spectrometry (HRMS) detection were post-processed by plotting the mass defect profiles and applying various data-filtering methods based on accurate mass values.

RESULTS

Exploration of mass defect profiles highlighted, in a specific plotting region, the presence of compounds containing common chemical elements and pairs of conjugated and non-conjugated metabolites resulting from classical metabolic pathways. Additionally, the judicious application of mass defect and/or isotope pattern filters removed many interfering ions from DI-HRMS data, greatly facilitating the detection of vinclozolin metabolites. Compared with previous results obtained by manual data treatment, three additional metabolites of vinclozolin were detected and putatively annotated.

CONCLUSIONS

Tracking simultaneously several specific species could be efficiently performed using data-mining tools based on accurate mass values. The selectivity of the data extraction was improved when the isotope filter was used for halogenated compounds, facilitating metabolite ion detection even for low-abundance species. Copyright © 2016 John Wiley & Sons, Ltd.

Deciphering lymphoma pathogenesis via state-of-the-art mass spectrometry-based quantitative proteomics

Mass spectrometry-based quantitative proteomics specifically applied to comprehend the pathogenesis of lymphoma has incremental value in deciphering the heterogeneity in complex deregulated molecular mechanisms/pathways of the lymphoma entities, implementing the current diagnostic and therapeutic strategies. Essential global, targeted and functional differential proteomics analyses although still evolving, have been successfully implemented to shed light on lymphoma pathogenesis to discover and explore the role of potential lymphoma biomarkers and drug targets. This review aims to outline and appraise the present status of MS-based quantitative proteomic approaches in lymphoma research, introducing the current state-of-the-art MS-based proteomic technologies, the opportunities they offer in biological discovery in human lymphomas and the related limitation issues arising from sample preparation to data evaluation. It is a synopsis containing information obtained from recent research articles, reviews and public proteomics repositories (PRIDE). We hope that this review article will aid, assimilate and assess all the information aiming to accelerate the development and validation of diagnostic, prognostic or therapeutic targets for an improved and empowered clinical proteomics application in lymphomas in the nearby future.

Stable isotope labelling methods in mass spectrometry-based quantitative proteomics

Mass-spectrometry based proteomics has evolved as a promising technology over the last decade and is undergoing a dramatic development in a number of different areas, such as; mass spectrometric instrumentation, peptide identification algorithms and bioinformatic computational data analysis. The improved methodology allows quantitative measurement of relative or absolute protein amounts, which is essential for gaining insights into their functions and dynamics in biological systems. Several different strategies involving stable isotopes label (ICAT, ICPL, IDBEST, iTRAQ, TMT, IPTL, SILAC), label-free statistical assessment approaches (MRM, SWATH) and absolute quantification methods (AQUA) are possible, each having specific strengths and weaknesses. Inductively coupled plasma mass spectrometry (ICP-MS), which is still widely recognised as elemental detector, has recently emerged as a complementary technique to the previous methods. The new application area for ICP-MS is targeting the fast growing field of proteomics related research, allowing absolute protein quantification using suitable elemental based tags. This document describes the different stable isotope labelling methods which incorporate metabolic labelling in live cells, ICP-MS based detection and post-harvest chemical label tagging for protein quantification, in addition to summarising their pros and cons.

A small azide-modified thiazole-based reporter molecule for fluorescence and mass spectrometric detection

Molecular probes are widely used tools in chemical biology that allow tracing of bioactive metabolites and selective labeling of proteins and other biomacromolecules. A common structural motif for such probes consists of a reporter that can be attached by copper(I)-catalyzed 1,2,3-triazole formation between terminal alkynes and azides to a reactive headgroup. Here we introduce the synthesis and application of the new thiazole-based, azide-tagged reporter 4-(3-azidopropoxy)-5-(4-bromophenyl)-2-(pyridin-2-yl)thiazole for fluorescence, UV and mass spectrometry (MS) detection. This small fluorescent reporter bears a bromine functionalization facilitating the automated data mining of electrospray ionization MS runs by monitoring for its characteristic isotope signature. We demonstrate the universal utility of the reporter for the detection of an alkyne-modified small molecule by LC–MS and for the visualization of a model protein by in-gel fluorescence. The novel probe advantageously compares with commercially available azide-modified fluorophores and a brominated one. The ease of synthesis, small size, stability, and the universal detection possibilities make it an ideal reporter for activity-based protein profiling and functional metabolic profiling.

Isotope-differentiated binding energy shift tags (IDBEST™) for improved targeted biomarker discovery and validation

Mass spectrometry has proved to be an important tool for protein biomarker discovery, identification and characterization. However, global proteomic profiling strategies often fail to identify known low-abundance biomarkers as a result of the limited dynamic range of mass spectrometry (two to three orders of magnitude) compared with the large dynamic range of protein concentrations in biologic fluids (11 to 12 orders of magnitude for serum). In addition, the number of peptides generated in such methods vastly overwhelms the resolution capacity of mass spectrometers, requiring extensive sample clean-up (e.g., affinity tag, retentate chromatography and/or high-performance liquid chromatography) before mass spectrometry analysis. Baiting and affinity pre-enrichment strategies, which overcome the dynamic range and sample complexity issues of global proteomic strategies, are very difficult to couple to mass spectrometry. This is due to the fact that it is nearly impossible to sort target peptides from those of the bait since there will be many cases of isobaric peptides. IDBEST (Target Discovery, Inc.) is a new tagging strategy that enables such pre-enrichment of specific proteins or protein classes as the resulting tagged peptides are distinguishable from those of the bait by a mass defect shift of approximately 0.1 atomic mass units. The special characteristics of these tags allow: resolution of tagged peptides from untagged peptides through incorporation of a mass defect element; high-precision quantitation of up- and downregulation by using stable isotope versions of the same tag; and potential analysis of protein isoforms through more complete peptide coverage from the proteins of interest.

Method for recovery and immunoaffinity enrichment of membrane proteins illustrated with metastatic ovarian cancer tissues

Integral membrane proteins play key biological roles in cell signaling, transport, and pathogen invasion. However, quantitative clinical assays for this critical class of proteins remain elusive and are generally limited to serum-soluble extracellular fragments. Furthermore, classic proteomic approaches to membrane protein analysis typically involve proteolytic digestion of the soluble pieces, resulting in separation of intra- and extracellular segments and significant informational loss. In this paper, we describe the development of a new method for the quantitative extraction of intact integral membrane proteins (including GPCRs) from solid metastatic ovarian tumors using pressure cycling technology in combination with a new (ProteoSolve-TD) buffer system. This new extraction buffer is compatible with immunoaffinity methods (e.g., ELISA and immunoaffinity chromatography), as well as conventional proteomic techniques (e.g., 2D gels, western blots). We demonstrate near quantitative recovery of membrane proteins EDG2, EDG4, FASLG, KDR, and LAMP-3 by western blots. We have also adapted commercial ELISAs for serum-soluble membrane protein fragments (e.g., sVEGFR2) to measure the tissue titers of their transmembrane progenitors. Finally, we demonstrate the compatibility of the new buffers with immunoaffinity enrichment/mass spectrometric characterization of tissue proteins.

Improved mass defect model for theoretical tryptic peptides

Improvements in the mass accuracy and resolution of mass spectrometers have greatly aided mass spectrometry-based proteomics in profiling complex biological mixtures. With the use of innovative bioinformatics approaches, high mass accuracy and resolution information can be used for filtering chemical noise in mass spectral data. Using our recent algorithmic developments, we have generated the mass distributions of all theoretical tryptic peptides composed of 20 natural amino acids and with masses limited to 3.5 kDa. Peptide masses are distributed discretely, with well-defined peak clusters separated by empty or sparsely populated trough regions. Accurate models for peak centers and widths can be used to filter peptide signals from chemical noise. We modeled mass defects, the difference between monoisotopic and nominal masses, and peak centers and widths in the peptide mass distributions. We found that peak widths encompassing 95% of all peptide sequences are substantially smaller than previously thought. The result has implications for filtering out larger stretches of the mass axis. Mass defects of peptides exhibit an oscillatory behavior which is damped at high mass values. The periodicity of the oscillations is about 14 Da which is the most common difference between the masses of the 20 natural amino acids. To determine the effects of amino acid modifications on our findings, we examined the mass distributions of peptides composed of the 20 natural amino acids, oxidized Met, and phosphorylated Ser, Thr, and Tyr. We found that extension of the amino acid set by modifications increases the 95% peak width. Mass defects decrease, reflecting the fact that the average mass defect of natural amino acids is larger than that of oxidized Met. We propose that a new model for mass defects and peak widths of peptides may improve peptide identifications by filtering chemical noise in mass spectral data.

The use of mass defect in modern mass spectrometry

Mass defect is defined as the difference between a compound's exact mass and its nominal mass. This concept has been increasingly used in mass spectrometry over the years, mainly due to the growing use of high resolution mass spectrometers capable of exact mass measurements in many application areas in analytical and bioanalytical chemistry. This article is meant as an introduction to the different uses of mass defect in applications using modern MS instrumentation. Visualizing complex mass spectra may be simplified with the concept of Kendrick mass by plotting nominal mass as a function of Kendrick mass defect, based on hydrocarbons subunits, as well as slight variations on this theme. Mass defect filtering of complex MS data has been used for selectively detecting compounds of interest, including drugs and their metabolites or endogenous compounds such as peptides and small molecule metabolites. Several strategies have been applied for labeling analytes with reagents containing unique mass defect features, thus shifting molecules into a less noisy area in the mass spectrum, thus increasing their detectability, especially in the area of proteomics. All these concepts will be covered to introduce the interested reader to the plethora of possibilities of mass defect analysis of high resolution mass spectra.

A parallel method for enumerating amino acid compositions and masses of all theoretical peptides

Background

Enumeration of all theoretically possible amino acid compositions is an important problem in several proteomics workflows, including peptide mass fingerprinting, mass defect labeling, mass defect filtering, and de novo peptide sequencing. Because of the high computational complexity of this task, reported methods for peptide enumeration were restricted to cover limited mass ranges (below 2 kDa). In addition, implementation details of these methods as well as their computational performance have not been provided. The increasing availability of parallel (multi-core) computers in all fields of research makes the development of parallel methods for peptide enumeration a timely topic.

Results

We describe a parallel method for enumerating all amino acid compositions up to a given length. We present recursive procedures which are at the core of the method, and show that a single task of enumeration of all peptide compositions can be divided into smaller subtasks that can be executed in parallel. The computational complexity of the subtasks is compared with the computational complexity of the whole task. Pseudocodes of processes (a master and workers) that are used to execute the enumerating procedure in parallel are given. We present computational times for our method executed on a computer cluster with 12 Intel Xeon X5650 CPUs (72 cores) running Windows HPC Server. Our method has been implemented as a 32- and 64-bit Windows application using Microsoft Visual C++ and the Message Passing Interface. It is available for download at https://ispace.utmb.edu/users/rgsadygo/Proteomics/ParallelMethod.

Conclusion

We describe implementation of a parallel method for generating mass distributions of all theoretically possible amino acid compositions.

Examining troughs in the mass distribution of all theoretically possible tryptic peptides

This work describes the mass distribution of all theoretically possibly tryptic peptides made of 20 amino acids, up to the mass of 3 kDa, with resolution of 0.001 Da. We characterize regions between the peaks of the distribution, including gaps (forbidden zones) and low-populated areas (quiet zones). We show how the gaps shrink over the mass range and when they completely disappear. We demonstrate that peptide compositions in quiet zones are less diverse than those in the peaks of the distribution and that by eliminating certain types of unrealistic compositions the gaps in the distribution may be increased. The mass distribution is generated using a parallel implementation of a recursive procedure that enumerates all amino acid compositions. It allows us to enumerate all compositions of tryptic peptides below 3 kDa in 48 min using a computer cluster with 12 Intel Xeon X5650 CPUs (72 cores). The results of this work can be used to facilitate protein identification and mass defect labeling in mass spectrometry-based proteomics experiments.

Non-linear classification for on-the-fly fractional mass filtering and targeted precursor fragmentation in mass spectrometry experiments

MOTIVATION

Mass spectrometry (MS) has become the method of choice for protein/peptide sequence and modification analysis. The technology employs a two-step approach: ionized peptide precursor masses are detected, selected for fragmentation, and the fragment mass spectra are collected for computational analysis. Current precursor selection schemes are based on data- or information-dependent acquisition (DDA/IDA), where fragmentation mass candidates are selected by intensity and are subsequently included in a dynamic exclusion list to avoid constant refragmentation of highly abundant species. DDA/IDA methods do not exploit valuable information that is contained in the fractional mass of high-accuracy precursor mass measurements delivered by current instrumentation.

RESULTS

We extend previous contributions that suggest that fractional mass information allows targeted fragmentation of analytes of interest. We introduce a non-linear Random Forest classification and a discrete mapping approach, which can be trained to discriminate among arbitrary fractional mass patterns for an arbitrary number of classes of analytes. These methods can be used to increase fragmentation efficiency for specific subsets of analytes or to select suitable fragmentation technologies on-the-fly. We show that theoretical generalization error estimates transfer into practical application, and that their quality depends on the accuracy of prior distribution estimate of the analyte classes. The methods are applied to two real-world proteomics datasets.

AVAILABILITY

All software used in this study is available from http://software.steenlab.org/fmf

CONTACT

hanno.steen@childrens.harvard.edu

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Shifting unoccupied spectral space in mass spectrum of peptide fragment ions

Ions near the high-end border of a mass defect distribution plot for native peptide fragment ions have potential as signature markers that are based on mass-to-charge ratio determination. The specificity of these marker ions, including phosphoryl ions, can be improved by removing interfering isobaric ions from the border region on the distribution plot. These interfering ions are rich in Asp and Glu content. The masses of amino acid residues and peptides are rescaled from the IUPAC scale (12C = 12 u as the mass reference) to the averagine scale (averagine mass = 111 u* as the mass reference with zero mass defect; u*: the mass unit on the averagine scale), using a scaling factor of 0.999493894. It is theoretically predicted that esterification of Asp and Glu side-chain carboxylates with n-butanol can achieve a sufficient retreat of the high-end border on a mass defect distribution plot based on the use of mass spectrometers with better-than-medium resolution. Theoretical calculations and laboratory experiments are performed to examine effects of various esterifications on the averagine-scale mass defect distribution of peptide fragment ions and on the specificity of two positive phosphoryl ions: the phosphotyrosine immonium ion and a cyclophosphoramidate ion.

Direct quantitation of peptide mixtures without standards using clusters formed by electrospray ionization mass spectrometry

In electrospray ionization mass spectrometry, ion abundances depend on a number of different factors, including analyte surface activity, competition between analytes for charge, analyte concentration, as well as instrumental factors, including mass-dependent ion transmission and detection. Here, a novel method for obtaining quantitative information about solution-phase concentrations of peptide mixtures is described and demonstrated for five different peptide mixtures with relative concentrations ranging from 0.05% to 50%. In this method, the abundances of large clusters containing anywhere from 0 to 13 impurity molecules are measured and directly related to the relative solution-phase concentration of the peptides. For clusters containing approximately 15 or more peptides, the composition of the clusters approaches the statistical value indicating that these clusters are formed nonspecifically and that any differences in ion detection or ionization efficiency are negligible at these large cluster sizes. This method is accurate to within approximately 20% or better, even when the relative ion intensities of the protonated monomers can differ by over an order of magnitude compared to their solution-phase concentrations. Although less accurate than other quantitation methods that employ internal standards, this method does have the key advantages of speed, simplicity, and the ability to quantitate components in solution even when the identities of the components are unknown.

Mass defect filter technique and its applications to drug metabolite identification by high-resolution mass spectrometry

Identification of drug metabolites by liquid chromatography/mass spectrometry (LC/MS) involves metabolite detection in biological matrixes and structural characterization based on product ion spectra. Traditionally, metabolite detection is accomplished primarily on the basis of predicted molecular masses or fragmentation patterns of metabolites using triple-quadrupole and ion trap mass spectrometers. Recently, a novel mass defect filter (MDF) technique has been developed, which enables high-resolution mass spectrometers to be utilized for detecting both predicted and unexpected drug metabolites based on narrow, well-defined mass defect ranges for these metabolites. This is a new approach that is completely different from, but complementary to, traditional molecular mass- or MS/MS fragmentation-based LC/MS approaches. This article reviews the mass defect patterns of various classes of drug metabolites and the basic principles of the MDF approach. Examples are given on the applications of the MDF technique to the detection of stable and chemically reactive metabolites in vitro and in vivo. Advantages, limitations, and future applications are also discussed on MDF and its combinations with other data mining techniques for the detection and identification of drug metabolites.

Protease-dependent fractional mass and peptide properties

Mass spectrometric analyses of peptides mainly rely on cleavage of proteins with proteases that have a defined specificity. The specificities of the proteases imply that there is not a random distribution of amino acids in the peptides. The physico-chemical effects of this distribution have been partly analyzed for tryptic peptides, but to a lesser degree for other proteases. Using all human proteins in Swiss-Prot, the relationships between peptide fractional mass, pI and hydrophobicity were investigated. The distribution of the fractional masses and the average regression lines for the fractional masses were similar, but not identical, for the peptides generated by the proteases trypsin, chymotrypsin and gluC, with the steepest regression line for gluC. The fractional mass regression lines for individual proteins showed up to +/-100 ppm in mass difference from the average regression line and the peptides generated showed protease-dependent properties. We here show that the fractional mass and some other properties of the peptides are dependent on the protease used for generating the peptides. With the increasing accuracy of mass spectrometry instruments it is possible to exploit the information embedded in the fractional mass of unknown peaks in peptide mass fingerprint spectra.

High-precision frequency measurements: indispensable tools at the core of the molecular-level analysis of complex systems

This perspective article provides an assessment of the state-of-the-art in the molecular-resolution analysis of complex organic materials. These materials can be divided into biomolecules in complex mixtures (which are amenable to successful separation into unambiguously defined molecular fractions) and complex nonrepetitive materials (which cannot be purified in the conventional sense because they are even more intricate). Molecular-level analyses of these complex systems critically depend on the integrated use of high-performance separation, high-resolution organic structural spectroscopy and mathematical data treatment. At present, only high-precision frequency-derived data exhibit sufficient resolution to overcome the otherwise common and detrimental effects of intrinsic averaging, which deteriorate spectral resolution to the degree of bulk-level rather than molecular-resolution analysis. High-precision frequency measurements are integral to the two most influential organic structural spectroscopic methods for the investigation of complex materials-NMR spectroscopy (which provides unsurpassed detail on close-range molecular order) and FTICR mass spectrometry (which provides unrivalled resolution)-and they can be translated into isotope-specific molecular-resolution data of unprecedented significance and richness. The quality of this standalone de novo molecular-level resolution data is of unparalleled mechanistic relevance and is sufficient to fundamentally advance our understanding of the structures and functions of complex biomolecular mixtures and nonrepetitive complex materials, such as natural organic matter (NOM), aerosols, and soil, plant and microbial extracts, all of which are currently poorly amenable to meaningful target analysis. The discrete analytical volumetric pixel space that is presently available to describe complex systems (defined by NMR, FT mass spectrometry and separation technologies) is in the range of 10(8-14) voxels, and is therefore capable of providing the necessary detail for a meaningful molecular-level analysis of very complex mixtures. Nonrepetitive complex materials exhibit mass spectral signatures in which the signal intensity often follows the number of chemically feasible isomers. This suggests that even the most strongly resolved FTICR mass spectra of complex materials represent simplified (e.g. isomer-filtered) projections of structural space.

Probabilistic enrichment of phosphopeptides by their mass defect

The mass defect, that is, the difference between the nominal and actual monoisotopic masses, of a phosphorus in a phosphate group is greater than for most other atoms present in proteins. When the mass defects of tryptic peptides derived from the human proteome are plotted against their masses, phosphopeptides tend to fall off the regression line. By calculating the masses of all potential tryptic peptides from the human proteome, we show that regions of higher phosphorylation probability exist on such a plot. We developed a transformation function to estimate the mass defect of a peptide from its monoisotopic mass and empirically defined a simple formula for a user-selectable discriminant line that categorizes a peptide mass according to its probability of being phosphorylated. Our method performs similarly well on phosphopeptides derived from a database of experimentally validated phosphoproteins. The method is relatively insensitive to mass measurement error of up to 20 ppm. The approach can be used with a tandem mass spectrometer in real time to rapidly select and rank order the possible phosphopeptides from a mixture of unmodified peptides for subsequent phosphorylation site mapping and peptide sequence analysis.

Lectin capture strategies combined with mass spectrometry for the discovery of serum glycoprotein biomarkers

The application of mass spectrometry to identify disease biomarkers in clinical fluids like serum using high throughput protein expression profiling continues to evolve as technology development, clinical study design, and bioinformatics improve. Previous protein expression profiling studies have offered needed insight into issues of technical reproducibility, instrument calibration, sample preparation, study design, and supervised bioinformatic data analysis. In this overview, new strategies to increase the utility of protein expression profiling for clinical biomarker assay development are discussed with an emphasis on utilizing differential lectin-based glycoprotein capture and targeted immunoassays. The carbohydrate binding specificities of different lectins offer a biological affinity approach that complements existing mass spectrometer capabilities and retains automated throughput options. Specific examples using serum samples from prostate cancer and hepatocellular carcinoma subjects are provided along with suggested experimental strategies for integration of lectin-based methods into clinical fluid expression profiling strategies. Our example workflow incorporates the necessity of early validation in biomarker discovery using an immunoaffinity-based targeted analytical approach that integrates well with upstream discovery technologies.

Mathematical tools in analytical mass spectrometry

Over the last few decades, mass spectrometry has become a powerful tool for exploring various aspects of molecular processes occurring in biological systems. Such exploration is leading to a greater understanding of various complex life processes; unraveling these processes poses the greatest challenge to contemporary bioscience. With due respect to sample preparation, data analysis is rapidly becoming a major obstacle to the conversion of experimental knowledge into valid conclusions. It is interesting to note that many problems related to mass spectrometry can be solved using techniques from computer science, graph theory and discrete mathematics. The aim of this manuscript is to recollect several essays that demonstrate the power and the need to apply such skills to mass spectrometry data interpretation. Special attention is paid to situations where traditional chemical analysis reaches its limits but mathematical reasoning can still allow us to reach valid conclusions.

Accessible proteomics space and its implications for peak capacity for zero-, one- and two-dimensional separations coupled with FT-ICR and TOF mass spectrometry

The number and wide dynamic range of components found in biological matrixes present several challenges for global proteomics. In this perspective, we will examine the potential of zero-dimensional (0D), one-dimensional (1D), and two-dimensional (2D) separations coupled with Fourier-transform ion cyclotron resonance (FT-ICR) and time-of-flight (TOF) mass spectrometry (MS) for the analysis of complex mixtures. We describe and further develop previous reports on the space occupied by peptides, to calculate the theoretical peak capacity available to each separations-mass spectrometry method examined. Briefly, the peak capacity attainable by each of the mass analyzers was determined from the mass resolving power (RP) and the m/z space occupied by peptides considered from the mass distribution of tryptic peptides from National Center for Biotechnology Information's (NCBI's) nonredundant database. Our results indicate that reverse-phase-nanoHPLC (RP-nHPLC) separation coupled with FT-ICR MS offers an order of magnitude improvement in peak capacity over RP-nHPLC separation coupled with TOF MS. The addition of an orthogonal separation method, strong cation exchange (SCX), for 2D LC-MS demonstrates an additional 10-fold improvement in peak capacity over 1D LC-MS methods. Peak capacity calculations for 0D LC, two different 1D RP-HPLC methods, and 2D LC (with various numbers of SCX fractions) for both RP-HPLC methods coupled to FT-ICR and TOF MS are examined in detail. Peak capacity production rates, which take into account the total analysis time, are also considered for each of the methods. Furthermore, the significance of the space occupied by peptides is discussed.

Stable isotope methods for high-precision proteomics

Stable isotope tagging methods provide a useful means of determining the relative expression level of individual proteins between samples in a mass spectrometer with high precision (coefficients of variation less than 10%). Because two or more samples tagged with different numbers of stable isotopes can be mixed before any processing steps, sample-to-sample recovery differences are eliminated. Mass spectrometry also allows post-translational modifications, splice variations and mutations (often unnoticed in immunoassays) to be detected and identified, increasing the clinical relevance of the assay and avoiding the issues of non-specific binding and cross-reactivity observed in immunoassays. Several stable isotope tagging methods are available for use in proteomics research. We discuss the advantages and disadvantages of each technique with respect to biomarker discovery, target validation, efficacy and toxicology screening and clinical diagnostic applications.