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High spatial resolution is a key parameter in mass spectrometry imaging (MSI), enabling a greater understanding of system biology and cellular processes. Using a novel IR laser with good Gaussian beam quality ( M 2 = 4) coupled with spatial filtering and a reflective objective, 20 μm spatial resolution was obtained by IR-MALDESI. The optical train was optimized on burn paper before demonstrating feasibility for imaging of liver tissue. Finally, a mouse brain was analyzed using nested regions of interest at 20 and 140 μm spatial resolution, detecting neurotransmitters and lipids with high spatial resolution on the corpus callosum and surrounding brain tissue.

Quality control and system suitability testing are vital protocols implemented to ensure the repeatability and reproducibility of data in mass spectrometry investigations. However, mass spectrometry imaging (MSI) analyses present added complexity since both chemical and spatial information are measured. Herein, we employ various machine learning algorithms and a novel quality control mixture to classify the working conditions of an MSI platform. Each algorithm was evaluated in terms of its performance on unseen data, validated with negative control data sets to rule out confounding variables or chance agreement, and utilized to determine the necessary sample size to achieve a high level of accurate classifications. In this work, a robust machine learning workflow was established where models could accurately classify the instrument condition as clean or compromised based on data metrics extracted from the analyzed quality control sample. This work highlights the power of machine learning to recognize complex patterns in MSI data and use those relationships to perform a system suitability test for MSI platforms.

Native mass spectrometry (MS) is a powerful analytical technique to directly probe noncovalent protein-protein and protein-ligand interactions. However, not every MS platform can preserve proteins in their native conformation due to high energy deposition from the utilized ionization source. Most small molecules approved as drugs and in development interact with their targets through noncovalent interactions. Therefore, rapid methods to analyze noncovalent protein-ligand interactions are necessary for the early stages of the drug discovery pipeline. Herein, we describe a method for analyzing noncovalent protein-ligand complexes by IR-MALDESI-MS with analysis times of ∼13 s per sample. Carbonic anhydrase and the kinase domain of Bruton's tyrosine kinase are paired with known noncovalent binders to evaluate the effectiveness of native MS by IR-MALDESI.

Mass spectrometry imaging (MSI) is an analytical technique capable of measuring and visualizing the spatial distribution of thousands of ions across a sample. Measured ions can be putatively identified and annotated by comparing their mass-to-charge ratio ( m / z ) to a database of known compounds. For high-resolution, accurate mass (HRAM) imaging data sets, this is commonly performed by the annotation platform METASPACE. Annotations are reported with a metabolite-signal-match (MSM) score as a measure of the annotation's confidence level. However, the MSM scores reported by METASPACE often do not reflect a reasonable confidence level of an annotation and are not assigned consistently. The metabolite annotation confidence score (MACS) is an alternative scoring system based on fundamental mass spectrometry imaging metrics (mass measurement accuracy, spectral accuracy, and spatial distribution) to generate values that reflect the confidence of a specific annotation in HRAM-MSI data sets. Herein, the MACS system is characterized and compared to MSM scores from ions annotated by METASPACE.

Mass spectrometry imaging (MSI) data visualization relies on heatmaps to show the spatial distribution and measured abundances of molecules within a sample. Nonuniform color gradients such as jet are still commonly used to visualize MSI data, increasing the probability of data misinterpretation and false conclusions. Also, the use of nonuniform color gradients and the combination of hues used in common colormaps make it challenging for people with color vision deficiencies (CVDs) to visualize and accurately interpret data. Here we present best practices for choosing a colormap to accurately display MSI data, improve readability, and accommodate all CVDs. We also provide other resources on the misuse of color in the scientific field and resources on scientifically derived colormaps presented herein., (© 2022 The Authors. Journal of Mass Spectrometry published by John Wiley & Sons Ltd.)

Analyzing mass spectrometry imaging data can be laborious and time consuming, and as the size and complexity of datasets grow, so does the need for robust automated processing methods. We here present a method for comprehensive, semi-targeted discovery of molecular distributions of interest from mass spectrometry imaging data, using widely available image similarity scoring algorithms to rank images by spatial correlation. A fast and powerful batch search method using a MATLAB implementation of structural similarity (SSIM) index scoring with a pre-selected reference distribution is demonstrated for two sample imaging datasets, a plant metabolite study using Artemisia annua leaf, and a drug distribution study using maraviroc-dosed macaque tissue. Graphical Abstract ᅟ.

Mass spectrometry (MS) has emerged as a tool that can analyze nearly all classes of molecules, with its scope rapidly expanding in the areas of post-translational modifications, MS instrumentation, and many others. Yet integration of novel analyte preparatory and purification methods with existing or novel mass spectrometers can introduce new challenges for MS sensitivity. The mechanisms that govern detection by MS are particularly complex and interdependent, including ionization efficiency, ion suppression, and transmission. Performance of both off-line and MS methods can be optimized separately or, when appropriate, simultaneously through statistical designs, broadly referred to as "design of experiments" (DOE). The following review provides a tutorial-like guide into the selection of DOE for MS experiments, the practices for modeling and optimization of response variables, and the available software tools that support DOE implementation in any laboratory. This review comes 3 years after the latest DOE review (Hibbert DB, 2012), which provided a comprehensive overview on the types of designs available and their statistical construction. Since that time, new classes of DOE, such as the definitive screening design, have emerged and new calls have been made for mass spectrometrists to adopt the practice. Rather than exhaustively cover all possible designs, we have highlighted the three most practical DOE classes available to mass spectrometrists. This review further differentiates itself by providing expert recommendations for experimental setup and defining DOE entirely in the context of three case-studies that highlight the utility of different designs to achieve different goals. A step-by-step tutorial is also provided.

Quantitative methods for detection of biological molecules are needed more than ever before in the emerging age of "omics" and "big data." Here, we provide an integrated approach for systematic analysis of the "lipidome" in tissue. To test our approach in a biological context, we utilized brain tissue selectively deficient for the transcription factor Specificity Protein 2 (Sp2). Conditional deletion of Sp2 in the mouse cerebral cortex results in developmental deficiencies including disruption of lipid metabolism. Silver (Ag) cationization was implemented for infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) to enhance the ion abundances for olefinic lipids, as these have been linked to regulation by Sp2. Combining Ag-doped and conventional IR-MALDESI imaging, this approach was extended to IR-MALDESI imaging of embryonic mouse brains. Further, our imaging technique was combined with bottom-up shotgun proteomic LC-MS/MS analysis and western blot for comparing Sp2 conditional knockout (Sp2-cKO) and wild-type (WT) cortices of tissue sections. This provided an integrated omics dataset which revealed many specific changes to fundamental cellular processes and biosynthetic pathways. In particular, step-specific altered abundances of nucleotides, lipids, and associated proteins were observed in the cerebral cortices of Sp2-cKO embryos.

Ovarian cancer (OVC) remains the most lethal gynecological malignancy in the world due to the combined lack of early-stage diagnostics and effective therapeutic strategies. The development and application of advanced proteomics technology and new experimental models has created unique opportunities for translational studies. In this study, we investigated the ovarian cancer proteome of the chicken, an emerging experimental model of OVC that develops ovarian tumors spontaneously. Matched plasma, ovary, and oviduct tissue biospecimens derived from healthy, early-stage OVC, and late-stage OVC birds were quantitatively characterized by label-free proteomics. Over 2600 proteins were identified in this study, 348 of which were differentially expressed by more than twofold (p ≤ 0.05) in early- and late-stage ovarian tumor tissue specimens relative to healthy ovarian tissues. Several of the 348 proteins are known to be differentially regulated in human cancers including B2M, CLDN3, EPCAM, PIGR, S100A6, S100A9, S100A11, and TPD52. Of particular interest was ovostatin 2 (OVOS2), a novel 165-kDa protease inhibitor found to be strongly upregulated in chicken ovarian tumors (p = 0.0005) and matched plasma (p = 0.003). Indeed, RT-quantitative PCR and Western blot analysis demonstrated that OVOS2 mRNA and protein were also upregulated in multiple human OVC cell lines compared to normal ovarian epithelia (NOE) cells and immunohistochemical staining confirmed overexpression of OVOS2 in primary human ovarian cancers relative to non-cancerous tissues. Collectively, these data provide the first evidence for involvement of OVOS2 in the pathogenesis of both chicken and human ovarian cancer.

Persistent HIV replication within active viral reservoirs may be caused by inadequate antiretroviral penetration. Here, we used mass spectrometry imaging with infrared matrix-assisted laser desorption-electrospray ionization to quantify the distribution of efavirenz within tissues from a macaque dosed orally to a steady state. Intratissue efavirenz distribution was heterogeneous, with the drug concentrating in the lamina propria of the colon, the primary follicles of lymph nodes, and the brain gray matter. These are the first imaging data of an antiretroviral drug in active viral reservoirs., (Copyright © 2015, American Society for Microbiology. All Rights Reserved.)

Rationale: Site occupancy measurements using liquid chromatography/mass spectrometry (LC/MS) are reported throughout the literature. However, site occupancy quantification suffers from ionization bias between modified and unmodified peptides containing the active site. In this study, we explore the MS signal as a function of nonpolar surface area (NPSA) in order to better understand this bias in electrospray response. The correlation between hydrophobicity and LC/MS response was evaluated and applied to study enzyme intermediates in polyketide synthases., Methods: Site occupancy methods were developed to study acyltransferase activity. To further evaluate these methods, several standard peptides containing one cysteine residue were modified with alkylation reagents of increasing hydrophobicity to study the MS signal as a function of NPSA., Results: A consistent trend in MS response was observed which is dependent on the NPSA of the analyte. An optimal NPSA zone was observed for the peptides studied., Conclusions: Nonpolar surface area can be used as metric to determine relative LC/MS response for peptides and evaluate site occupancy measurements., (Copyright © 2014 John Wiley & Sons, Ltd.)

The Individuality Normalization when Labeling with Isotopic Glycan Hydrazide Tags (INLIGHT) strategy for the sample preparation, data analysis, and relative quantification of N-linked glycans is presented. Glycans are derivatized with either natural (L) or stable-isotope labeled (H) hydrazide reagents and analyzed using reversed phase liquid chromatography coupled online to a Q Exactive mass spectrometer. A simple glycan ladder, maltodextrin, is first used to demonstrate the relative quantification strategy in samples with negligible analytical and biological variability. It is shown that after a molecular weight correction attributable to isotopic overlap and a post-acquisition normalization of the data to account for any systematic bias, a plot of the experimental H:L ratio versus the calculated H:L ratio exhibits a correlation of unity for maltodextrin samples mixed in different ratios. We also demonstrate that the INLIGHT approach can quantify species over four orders of magnitude in ion abundance. The INLIGHT strategy is further demonstrated in pooled human plasma, where it is shown that the post-acquisition normalization is more effective than using a single spiked-in internal standard. Finally, changes in glycosylation are able to be detected in complex biological matrices, when spiked with a glycoprotein. The ability to spike in a glycoprotein and detect change at the glycan level validates both the sample preparation and data analysis strategy, making INLIGHT an invaluable relative quantification strategy for the field of glycomics.

Achieving and maintaining high mass measurement accuracy (MMA) throughout a mass spectrometry imaging (MSI) experiment is vital to the identification of the observed ions. However, when using FTMS instruments, fluctuations in the total ion abundance at each pixel due to inherent biological variation in the tissue section can introduce space charge effects that systematically shift the observed mass. Herein we apply a recalibration based on the observed cyclotron frequency shift of ions found in the ambient laboratory environment, polydimethylcyclosiloxanes (PDMS). This calibration method is capable of achieving part per billion (ppb) mass accuracy with relatively high precision for an infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) MSI dataset. Comparisons with previously published mass calibration approaches are also presented.

Rationale: Traditionally, free oligosaccharide internal standards are used to account for variability in glycan relative quantification experiments by mass spectrometry. However, a more suitable internal standard would be a glycoprotein, which could also control for enzymatic cleavage efficiency, allowing for more accurate quantitative experiments., Methods: Hydrophobic, hydrazide N-linked glycan reagents (both native and stable-isotope labeled) are used to derivatize and differentially label N-linked glycan samples for relative quantification, and the samples are analyzed by a reversed-phase liquid chromatography chip system coupled online to a Q-Exactive mass spectrometer. The inclusion of two internal standards, maltoheptaose (previously used) and horseradish peroxidase (HRP) (novel), is studied to demonstrate the effectiveness of using a glycoprotein as an internal standard in glycan relative quantification experiments., Results: HRP is a glycoprotein containing a xylosylated N-linked glycan, which is unique from mammalian N-linked glycans. Thus, the internal standard xylosylated glycan could be detected without interference to the sample. Additionally, it was shown that differences in cleavage efficiency can be detected by monitoring the HRP glycan. In a sample where cleavage efficiency variation is minimal, the HRP glycan performs as well as maltoheptaose., Conclusions: Because the HRP glycan performs as well as maltoheptaose but is also capable of correcting and accounting for cleavage variability, it is a more versatile internal standard and will be used in all subsequent biological studies. Because of the possible lot-to-lot variation of an enzyme, differences in biological matrix, and variable enzyme activity over time, it is a necessity to account for glycan cleavage variability in glycan relative quantification experiments., (Copyright © 2013 John Wiley & Sons, Ltd.)

During the past decade, the field of mass spectrometry imaging (MSI) has greatly evolved, to a point where it has now been fully integrated by most vendors as an optional or dedicated platform that can be purchased with their instruments. However, the technology is not mature and multiple research groups in both academia and industry are still very actively studying the fundamentals of imaging techniques, adapting the technology to new ionization sources, and developing new applications. As a result, there important varieties of data file formats used to store mass spectrometry imaging data and, concurrent to the development of MSi, collaborative efforts have been undertaken to introduce common imaging data file formats. However, few free software packages to read and analyze files of these different formats are readily available. We introduce here MSiReader, a free open source application to read and analyze high resolution MSI data from the most common MSi data formats. The application is built on the Matlab platform (Mathworks, Natick, MA, USA) and includes a large selection of data analysis tools and features. People who are unfamiliar with the Matlab language will have little difficult navigating the user-friendly interface, and users with Matlab programming experience can adapt and customize MSiReader for their own needs.

Color Index Disperse Yellow 42 (DY42), a high-volume disperse dye for polyester, was used to compare the capabilities of the LTQ-Orbitrap XL and the LTQ-FT-ICR with respect to mass measurement accuracy (MMA), spectral accuracy, and sulfur counting. The results of this research will be used in the construction of a dye database for forensic purposes; the additional spectral information will increase the confidence in the identification of unknown dyes found in fibers at crime scenes. Initial LTQ-Orbitrap XL data showed MMAs greater than 3 ppm and poor spectral accuracy. Modification of several Orbitrap installation parameters (e.g., deflector voltage) resulted in a significant improvement of the data. The LTQ-FT-ICR and LTQ-Orbitrap XL (after installation parameters were modified) exhibited MMA ≤ 3 ppm, good spectral accuracy (χ(2) values for the isotopic distribution ≤ 2), and were correctly able to ascertain the number of sulfur atoms in the compound at all resolving powers investigated for AGC targets of 5.00 × 10(5) and 1.00 × 10(6)., (© American Society for Mass Spectrometry, 2011)

Fractionation prior to mass spectrometry is an indispensable step in proteomics. In this paper we report the success of performing offline reversed phase high pressure liquid chromatography (HPLC) fractionation on a C18 2.0 mm×150 mm column at the peptide level with microliter per minute flow rates prior to online nano-flow reversed phase liquid chromatography mass spectrometry (nanoLC-MS) using the well-studied fungus Saccharomyces cerevisiae. A C18 75 μm×150 mm column was used online and the online elution gradients for each fraction were adjusted in order to obtain well resolved separation. Comparing this method directly to only performing nanoLC-MS we observed a 61.6% increase in the number of identified proteins. At a 1% false discovery rate 1028 proteins were identified using two dimensions of RPLC versus 636 proteins identified in a single nano-flow separation. The majority of proteins identified by one dimension of nano-LC were present in the proteins identified in our two dimensional strategy. Although increasing analysis time, this non-orthogonal and facile pre-fractionation method affords a more comprehensive examination of the proteome., (Copyright © 2011 Elsevier B.V. All rights reserved.)

A method is detailed for the global profiling of underivatized N-linked glycans that are derived from complex protein mixtures. The method consists of five main steps that include the following: (1) protein denaturation; (2) enzymatic digestion; (3) solid phase extraction; (4) nanoLC MS analysis; and (5) data interpretation. Materials, methods, and algorithms for the identification of both glycan composition and structure are summarized. In addition, potential problems and their resolutions are addressed.

Human embryonic stem cells (hESCs) are self-renewing pluripotent cells with relevance to treatment of numerous medical conditions. However, a global understanding of the role of the hESC proteome in maintaining pluripotency or triggering differentiation is still largely lacking. The emergence of top-down proteomics has facilitated the identification and characterization of intact protein forms that are not readily apparent in bottom-up studies. Combined with metabolic labeling techniques such as stable isotope labeling by amino acids in cell culture (SILAC), quantitative comparison of intact protein expression under differing experimental conditions is possible. Herein, quantitative top-down proteomics of hESCs is demonstrated using the SILAC method and nano-flow reverse phase chromatography directly coupled to a linear-ion-trap Fourier transform ion cyclotron resonance mass spectrometer (nLC-LTQ-FT-ICR-MS). In this study, which to the best of our knowledge represents the first top-down analysis of hESCs, we have confidently identified 11 proteins by accurate intact mass, MS/MS, and amino acid counting facilitated by SILAC labeling. Although quantification is challenging due to the incorporation of multiple labeled amino acids (i.e., lysine and arginine) and arginine to proline conversion, we are able to quantitatively account for these phenomena using a mathematical model., (Copyright 2010. Published by Elsevier Inc.)

PC-IDMS experiments for two peptides, laminin nonapeptide and the N-terminal tryptic peptide of prostate specific antigen, were performed utilizing a variety of alkylating reagents. These experiments were conducted to investigate how hydrophobicity influences the limits-of-detection (LOD) by altering their electrospray ionization response. Nonpolar surface areas were calculated for both peptides and all alkylating reagents to provide an estimate of the hydrophobicity of the differently alkylated peptides. Decreases in LOD by 2-fold were observed for both peptides between the best and worst performing combination of alkylating reagent. However, while an increase in hydrophobicity was found to aid in decreasing LOD to an extent, beyond a certain hydrophobicity, we observed a decrease.

Fourier transform ion cyclotron resonance mass spectrometry has the ability to realize exceptional mass measurement accuracy (MMA); MMA is one of the most significant attributes of mass spectrometric measurements as it affords extraordinary molecular specificity. However, due to space-charge effects, the achievable MMA significantly depends on the total number of ions trapped in the ICR cell for a particular measurement, as well as relative ion abundance of a given species. Artificial neural network calibration in conjunction with automatic gain control (AGC) is utilized in these experiments to formally account for the differences in total ion population in the ICR cell between the external calibration spectra and experimental spectra. In addition, artificial neural network calibration is used to account for both differences in total ion population in the ICR cell as well as relative ion abundance of a given species, which also affords mean MMA values at the parts-per-billion level.

Recent investigations continue to emphasize the importance of glycosylation in various diseases including cancer. In this work, we present a step-by-step protocol describing a method for N-linked glycan profiling of plasma glycoproteins by nanoflow liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). A large experimental space was initially explored and is described herein. Three internal standards were spiked into the sample and provided normalization of plasma glycan abundance across different experimental conditions. Incubation methods and times and the effect of NP40 detergent on glycan abundance were explored. It was found that an 18-h incubation with no detergent led to the greatest ion abundance; however, data could be obtained in less than one day from raw plasma samples utilizing microwave irradiation or shorter incubation periods. The intersample precision of three different glycans was less than 5.5% (RSD) when the internal standards were added prior to the initial processing step. The high mass measurement accuracy (<3 ppm) afforded by the FTICR mass spectrometer provided confident identifications of several glycan species.

The design and implementation of a radio frequency acoustic desorption ionization (RADIO) source has been demonstrated for the analysis of multiply charged peptides and proteins. One muL aliquots of melittin, BNP-32, and ubiquitin ( approximately 1 mug of analyte) were deposited onto a quartz crystal microbalance (QCM) electrode before radio frequency actuation for desorption. Continuous electrospray parallel to/above the sampling surface enabled the ionization of desorbed species. Detection by a hybrid linear ion trap Fourier transform ion cyclotron resonance mass spectrometer confirmed the intact and dissociated species observed during MS and MS/MS experiments, respectively.

A method employing protein cleavage isotope dilution mass spectrometry (PC-IDMS) was developed for quantification of C-reactive protein (CRP) in human plasma. This method was completed without the use of immunoaffinity chromatography or size exclusion chromatography, as previous mass spectrometric methods for the quantification of CRP have employed. A total of 110 human plasma samples were analyzed with PC-IDMS via 1-D nanoLC-MS/MS using a 30 min gradient with a triple quadrupole mass spectrometer operated in selective reaction monitoring (SRM) mode. The results from this newly developed method were compared to results generated from an enzyme-linked immunosorbent assay (ELISA) performed by an independent CLIA certified laboratory. The comparison of these results generated an R(2) = 0.9708 which indicates successful quantification of CRP from human plasma utilizing the methodology described herein. Interestingly, the PC-IDMS method provided concentration values that were approximately 10x the concentration reported by the ELISA method, which demonstrated that the method of detection is an important consideration when determining reference ranges of a particular analyte. In addition, data is shown that illustrates that, as epithelial ovarian cancer (EOC) progresses from stage I to stage IV, mean levels of CRP increase.

Biomarker discovery and proteomics have become synonymous with mass spectrometry in recent years. Although this conflation is an injustice to the many essential biomolecular techniques widely used in biomarker-discovery platforms, it underscores the power and potential of contemporary mass spectrometry. Numerous novel and powerful technologies have been developed around mass spectrometry, proteomics, and biomarker discovery over the past 20 years to globally study complex proteomes (e.g., plasma). However, very few large-scale longitudinal studies have been carried out using these platforms to establish the analytical variability relative to true biological variability. The purpose of this review is not to cover exhaustively the applications of mass spectrometry to biomarker discovery, but rather to discuss the analytical methods and strategies that have been developed for mass spectrometry-based biomarker-discovery platforms and to place them in the context of the many challenges and opportunities yet to be addressed.

Operation of any mass spectrometer requires implementation of mass calibration laws to translate experimentally measured physical quantities into a m/z range. While internal calibration in Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) offers several attractive features, including exposure of calibrant and analyte ions to identical experimental conditions (e.g. space charge), external calibration affords simpler pulse sequences and higher throughput. The automatic gain control method used in hybrid linear trap quadrupole (LTQ) FT-ICR-MS to consistently obtain the same ion population is not readily amenable to matrix-assisted laser desorption/ionization (MALDI) FT-ICR-MS, due to the heterogeneous nature and poor spot-to-spot reproducibility of MALDI. This can be compensated for by taking external calibration laws into account that consider magnetic and electric fields, as well as relative and total ion abundances. Herein, an evaluation of external mass calibration laws applied to MALDI-FT-ICR-MS is performed to achieve higher mass measurement accuracy (MMA)., (Copyright (c) 2008 John Wiley & Sons, Ltd.)

Fourier transform ion cyclotron resonance mass spectrometry has the ability to achieve unprecedented mass measurement accuracy (MMA); MMA is one of the most significant attributes of mass spectrometric measurements as it affords extraordinary molecular specificity. However, due to space-charge effects, the achievable MMA significantly depends on the total number of ions trapped in the ion cyclotron resonance (ICR) cell for a particular measurement. Even through the use of automatic gain control (AGC), the total ion population is not constant between spectra. Multiple linear regression calibration in conjunction with AGC is utilized in these experiments to formally account for the differences in total ion population in the ICR cell between the external calibration spectra and experimental spectra. This ability allows for the extension of dynamic range of the instrument and for the mean MMA values to remain less than 1 part-per-million (ppm). In addition, multiple linear regression calibration is used to account for both differences in total ion population in the ICR cell as well as relative ion abundance of a given species, which also affords mean MMA values at the parts-per-billion (ppb) level.

16O/18O labeling is one differential proteomics technology among many that promises diagnostic and prognostic biomarkers of disease. Although the incorporation of 18O in the C-terminal carboxyl group during endoproteinase digestion in the presence of H2 18O makes the process of labeling facile, the ease and effectiveness of label incorporation have in some regards been outweighed by the difficulties in interpreting the resulting spectra. Complex isotope patterns result from the composition of unlabeled (18O(0)), singly labeled (18O(1)), and doubly labeled species (18O(2)) as well as contributions from the naturally occurring isotopes (e.g. 13C and 15N). Moreover because labeling is enzymatic, the number of 18O atoms incorporated can vary from peptide to peptide. Finally it is difficult to distinguish highly up-regulated from highly down-regulated or C-terminal peptides. We have developed an algorithm entitled regression analysis applied to mass spectrometry (RAAMS) that automatically, rapidly, and confidently interprets spectra of 18O-labeled peptides without requiring chemical composition information derived from product ion spectra. The algorithm is able to measure the effective 18O incorporation rate due to variable enzyme substrate specificity of the pseudosubstrate during the isotope exchange reaction and corrects for the 18O(0) abundance that remains in the labeled sample when using a two-step digestion/labeling procedure. We have also incorporated a method for distinguishing pure 18O(0) from pure 18O(2) peptides utilizing impure H2 18O. The algorithm operates on centroided peak lists and is therefore very fast: nine chromatograms of, on average, 1,168 spectra and containing, on average, 6,761 isotopic clusters were interpreted in, on average, 45 s per chromatogram. RAAMS is fast enough (average, 38 ms/spectrum) to allow the possibility of performing information-dependent MS/MS on a chromatographic time scale on species exceeding predetermined ratio thresholds. We describe in detail the operation of the algorithm and demonstrate its use on datasets with known and unknown ratios.

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.

Two-dimensional liquid chromatography (2D-LC), combined with gas phase fractionation tandem mass spectrometry, was used to identify 13 naturally processed peptides originating from measles virus that were presented by HLA-DRB1*03 class II molecules. The peptides are from three of the six measles structural proteins: phosphoprotein, nucleocapsid, and hemagglutinin. These peptides provide an important first step toward understanding the mechanism of immune response to measles virus and development of a new generation of peptide-based vaccines.

In this study we use replicate 2D-LC-MS/MS analyses of crude membranes from B cells derived from a patient with chronic lymphocytic leukemia (CLL) to examine the protein expression profile of CLL B cells. Protein identifications made by replicate 2D-LC-MS/MS analysis of tryptic peptides from detergent solubilized B cell membrane proteins, as well as replicate LC-MS/MS analysis of single off-line strong cation exchange chromatography (SCX) fractions, were analyzed. We show that despite the variance in SCX, capillary LC, and the data-dependent selection of precursor ions, an overlap of 64% between proteins identified in replicate runs was achieved for this system.

A voltage-assisted venturi device modeled after an industrial air amplifier was used to improve the ion transmission efficiency of a 16.2 kDa oligonucleotide and a 53-mer PCR product in the high-pressure region between an electrospray ionization (ESI) emitter and the sampling orifices of two Fourier transform ion cyclotron resonance mass spectrometers (FT-ICR-MS). The venturi device increased the total ion abundance of the oligonucleotide and the PCR product by more than 6-fold relative to the best achievable signal without the device. Furthermore, the average charge states of the oligonucleotide and PCR product shifted from 12.5- to 14.5- and 10.9- to 12.6-, respectively, with the addition of the venturi device. Specific to FT-ICR mass spectrometry, this increase in the charge state directly translates to an increase in theoretical mass resolving power (>10000 full width half-maximum for the results presented here at 7 T). Adduction was still observed while using the device, suggesting that it is "soft" relative to other high-pressure ion focusing methods.

Protein cleavage coupled with isotope dilution mass spectrometry (PC-IDMS) has the potential to provide the absolute concentration of a specific protein, or multiple proteins, in complex mixtures. However, PC-IDMS differs from standard IDMS since the internal standard is a different molecule than the analyte at the start of the experiment, more specifically, the internal standard is a peptide and the analyte is a protein prior to cleavage. It is not until after the cleavage process that the stable isotope labeled synthetic peptide has the same physicochemical behavior as the peptide cleaved from the protein. The work presented here evaluates the use of tryptic cleavage sites incorporated into the internal standard synthetic peptide in an attempt to create an internal standard that has cleavage characteristics more similar to the protein being quantified. Results presented here suggest that an internal standard synthetic peptide incorporating internal cleavage sites does not improve the accuracy and precision of the values obtained when performing PC-IDMS.

PCR amplification of a segment of the 16/23S rDNA interspace region (ISR) from Bacillus cereus 6464 produced a mixture of products. An 89-bp product was predicted on the basis of the reported sequence. The ESI-FTICR analysis revealed three double-stranded products, differing in size by a single nucleotide corresponding to two homoduplexes of 89 and 88 base pairs and a heteroduplex of 89 and 88 nucleotide strands. These were produced from a single preparation of genomic DNA and a single primer pair. ESI-FTICR analysis of the single strands identified a deletion of a T in the coding strand and a corresponding loss of an A in the noncoding strand of this product. The ESI-FTICR analysis indicated the presence of an unreported sequence variation between rRNA operons in this organism. This report illustrates that PCR products amplified from templates differing by a single nucleotide can be resolved and identified using ESI-FTICR at the 89-bp level. Furthermore, the ESI-FTICR mass measurements provided the identity of the deletion, which is indicative of interoperon variability.