Interpreting the charge state assignment in electrospray mass spectra of bioparticles

In electrospray ionization mass spectra of heterogeneous protein complexes and other bioparticles, accurate mass determination is often hampered by the inaccuracy in determination of the charge states for individual signals. Here, we describe an algorithm that automatically minimizes the standard deviation in a series of related ion peaks with varying numbers of charges. The algorithm assumes that the mass is invariant and allows the determination of the correct charge state in a peak series. The analysis results in a periodic pattern, which can be interpreted as a harmonic oscillator, when the minimum standard deviation of a charge state series is found. We observed that a mass resolution of much less than 1000 in the acquired mass spectra is sufficient to achieve a correct charge state assignment. Moreover, the boundaries of mixed species can be identified by examining the loss of periodicity in the pattern of the analysis. We tested our algorithm successfully on novel spectra and on spectra reported in the literature with sample masses up to several million Dalton, e.g., viral particles, polyethylene glycol polymers, and polystyrene nanoparticles.     

Improved identification of noisy spectra using higher-ordered correlation spectral analysis

We used a higher-order correlation-based method of comparison for spectral identification. Higher-order correlations are an extension of the more familiar second-order cross-correlation function and have the significant advantage of being theoretically shown to eliminate noise of unknown spectral density under certain conditions. Specifically, we applied a third-order correlation technique to the identification of similar IR spectra in the presence of noise. We were able to reduce the effects of noise from a second-order correlation measurement by further processing the measurement with a third-order autocorrelation. Our results showed that the third-order correlation-based method increased the probability of detection of a spectrum in the presence of noise, when compared to using a second-order technique alone. The probability of detection increased enough at low signal-to-noise ratios that this technique may be useful when a second-order correlation technique is not acceptable. The third-order technique is applicable to a single experiment, but improved results were found by averaging the results of multiple experiments.     

Decomposition of ESR spectra using MALDI-TOF mass spectrometry

ESR (or EPR) spectroscopy on spin-labeled site-directed cysteine mutants is ideally suited for structural studies of membrane proteins due to its high sensitivity and its low demands with respect to sample purity and preparation. Many features can be inferred from the spectral line shape of an ESR spectrum, but the analysis of ESR spectra is complicated when multiple sites with different line shapes are present. Here, we present a method to decompose the spectrum of a doubly labeled peptide that is composed of a singly labeled, noninteracting component and a doubly labeled, dipolar-broadened component using a combination of optical and matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry. The effect on the interspin distance calculation based on the dipolar broadening is quantified and discussed.     

Automatic deconvolution of isotope-resolved mass spectra using variable selection and quantized peptide mass distribution

We present an algorithm for the deconvolution of isotope-resolved mass spectra of complex peptide mixtures where peaks and isotope series often overlap. The algorithm formulates the problem of mass spectrum deconvolution as a classical statistical problem of variable selection, which aims to interpret the spectrum with the least number of peptides. The LASSO method is used to perform automatic variable selection. The algorithm also makes use of the quantized distribution of peptide masses in the NCBInr database after in silico trypsin digestion as filters to aid the deconvolution process. Errors in the expected isotope pattern are accounted for to avoid spurious isotope series. The effectiveness of the algorithm is demonstrated with annotated ESI spectrum of known peptides for which the peaks and isotope series are highly overlapping. The algorithm successfully finds all correct masses in the experimental spectrum, except for one spectrum where an additional refinement procedure is required to obtain the correct results. Our results compare favorably to those from a widely used commercial program.     

Simplification of mass spectral analysis of acidic glycopeptides using GlycoPep ID

Mass spectral analysis is an increasingly common method used to characterize glycoproteins. When more than one glycosylation site is present on a protein, obtaining MS data of glycopeptides is a highly effective way of obtaining glycosylation information because this approach can be used to identify not only what the carbohydrates are but also at which glycosylation site they are attached. Unfortunately, this is not yet a routine analytical approach, in part because data analysis can be quite challenging. We are developing strategies to simplify this analysis. Presented herein is a novel mass spectrometry technique that identifies the peptide moiety of either sulfated, sialylated, or both sialylated and sulfated glycopeptides. This technique correlates product ions in collision-induced dissociation (CID) experiments of suspected glycopeptides to a peptide composition using a newly developed web-based tool, GlycoPep ID. After identifying the peptide portion of glycopeptides with GlycoPep ID, the process of assigning the rest of the glycopeptide composition to the MS data is greatly facilitated because the "unknown" portion of the mass assignment that remains can be directly attributed to the carbohydrate component. Several examples of the utility and reliability of this method are presented herein.     

Comparison of mass spectral techniques using organic peroxides related to artemisinin

The mass spectra of three peroxides related to artemisinin (1) are compared in nine different ionization modes. Ion trap mass spectrometry (MS/MS) spectra reveal numerous pathways for the electron impact (EI) decompositions. In the EI mode, the best spectra are obtained by using the ion trap mass spectrometer at low temperatures. Loss of oxygen is observed with the other EI spectrometers, suggesting catalytic decomposition in the ion source. Methane positive and negative chemical ionization (CI) spectra show considerable fragmentation, while isobutane CI spectra show only (M + H)+ for 1 and (M + H - H2O)+ for dihydroartemisinin (2) and (3). An unusually abundant (2M + H)+ is observed for 1 in both positive-ion plasma desorption and fast atom bombardment mass spectra.     

Metabolite identification using automated comparison of high-resolution multistage mass spectral trees

Multistage mass spectrometry (MS(n)) generating so-called spectral trees is a powerful tool in the annotation and structural elucidation of metabolites and is increasingly used in the area of accurate mass LC/MS-based metabolomics to identify unknown, but biologically relevant, compounds. As a consequence, there is a growing need for computational tools specifically designed for the processing and interpretation of MS(n) data. Here, we present a novel approach to represent and calculate the similarity between high-resolution mass spectral fragmentation trees. This approach can be used to query multiple-stage mass spectra in MS spectral libraries. Additionally the method can be used to calculate structure-spectrum correlations and potentially deduce substructures from spectra of unknown compounds. The approach was tested using two different spectral libraries composed of either human or plant metabolites which currently contain 872 MS(n) spectra acquired from 549 metabolites using Orbitrap FTMS(n). For validation purposes, for 282 of these 549 metabolites, 765 additional replicate MS(n) spectra acquired with the same instrument were used. Both the dereplication and de novo identification functionalities of the comparison approach are discussed. This novel MS(n) spectral processing and comparison approach increases the probability to assign the correct identity to an experimentally obtained fragmentation tree. Ultimately, this tool may pave the way for constructing and populating large MS(n) spectral libraries that can be used for searching and matching experimental MS(n) spectra for annotation and structural elucidation of unknown metabolites detected in untargeted metabolomics studies.     

Tandem mass tag protein labeling for top-down identification and quantification

Top-down mass spectrometry holds tremendous potential for characterization and quantification of intact proteins. So far, however, very few studies have combined top-down proteomics with protein quantification. In view of the success of isobaric mass tags in quantitative bottom-up proteomics, we applied the tandem mass tag (TMT) technology to label intact proteins and examined the feasibility to directly quantify TMT-labeled proteins. A top-down platform encompassing separation via ion-pair reversed-phase liquid chromatography using monolithic stationary phases coupled online to an LTQ-Orbitrap Velos electron-transfer dissociation (ETD) mass spectrometer (MS) was established to simultaneously identify and quantify TMT-labeled proteins. The TMT-labeled proteins were found to be readily dissociated under high-energy collision dissociation (HCD) activation. The liberated reporter ions delivered expected ratios over a wide dynamic range independent of the protein charge state. Furthermore, protein sequence tags generated either by low-energy HCD or ETD activation along with the intact protein mass information allow for confident identification of small proteins below 35 kDa. We conclude that the approach presented in this pilot study paves the way for further developments and numerous applications for straightforward, accurate, and multiplexed quantitative analysis in protein chemistry and proteomics.     

Complete mass spectral characterization of a synthetic ultralow-molecular-weight heparin using collision-induced dissociation

Glycosaminoglycans (GAGs) are a class of biologically important molecules, and their structural analysis is the target of considerable research effort. Advances in tandem mass spectrometry (MS/MS) have recently enabled the structural characterization of several classes of GAGs; however, the highly sulfated GAGs, such as heparins, have remained a relatively intractable class due their tendency to lose SO(3) during MS/MS, producing few sequence-informative fragment ions. The present work demonstrates for the first time the complete structural characterization of the highly sulfated heparin-based drug Arixtra. This was achieved by Na(+)/H(+) exchange to create a more ionized species that was stable against SO(3) loss, and that produced complete sets of both glycosidic and cross-ring fragment ions. MS/MS enables the complete structural determination of Arixtra, including the stereochemistry of its uronic acid residues, and suggests an approach for solving the structure of more complex, highly sulfated heparin-based drugs.     

Si-based flexible memristive systems constructed using top-down methods

Si-based memristive systems consisting of Ag, amorphous Si, and heavily doped p-type Si nanowires were successfully constructed on plastic substrates through top-down methods, including the crystallographic wet etching of Si wafers, transfer onto plastic substrates, and thin film patterning. The memristive systems showed excellent memory characteristics and flexibility, such as intrinsic hysteric and rectifying behaviors, on/off resistance ratios of >1 × 10(5), and durability for up to 1000 bending cycles. The correlations between the Ag-filament-related nanostructures formed in amorphous Si and the resistance-switching behaviors were carefully examined with the tunneling current model, transmission electron microscopy, and secondary ion mass spectroscopy to explore the switching mechanism. Our study suggests the promising potential of the Si-based memristive systems for the development of next-generation flexible nonvolatile memory.     

Characterization of variable regions of monoclonal antibodies by top-down mass spectrometry

A technique for rapid characterization of variable regions of monoclonal antibodies (mAb) is described. Several intact mAbs were analyzed on a Thermo-Fisher LTQ-Orbitrap high-resolution mass spectrometer (MS) by in-source fragmentation. In-source fragmentation has the unique advantage of fragmenting all charge states of a protein at the same time and, thus, greatly improves the sensitivity of the fragment ions over a true MS/MS experiment, where a single charge state is isolated and fragmented. In addition, immediate fragmentation of the protein before tertiary structure formation may also facilitate protein fragmentation. This technique has been proved very useful for top-down analysis of large proteins. In-source fragmentation of mAbs generated a series of fragment ions. In addition to some small b and y ions from the light chain and heavy chain in the low m/z region, a series of b ions corresponding to N-terminal 106-120 residues of both heavy chain and light chain were observed. The cleavage sites for these b ions happen to be near the linker regions between the variable domains and the constant domains of these antibodies. These b ions, therefore, correspond to the entire variable region of each chain. Similar results were obtained for all mAbs analyzed, including both immunoglobulin G1 and G2 molecules. To further characterize the variable regions, these b ions were isolated and fragmented by collision-induced dissociation in the linear trap, followed by mass analysis in the orbitrap. Large number of product ions was observed from these b ions. Many of these product ions are internal fragments between the two disulfide-linked cysteine residues. To demonstrate the capability of the technique, several mAbs were force-oxidized by treating with tert-butyl hydroperoxide, followed by mass spectrometric analysis. In-source fragmentation and MS/MS of the variable region b ions clearly identified the locations of the oxidized methionine.     

A strategy for identification of oligosaccharide structures using observational multistage mass spectral library

Glycosylation is the most widespread posttranslational modification in eukaryotes; however, the role of oligosaccharides attached to proteins has been little studied because of the lack of a sensitive and easy analytical method for oligosaccharide structures. Recently, tandem mass spectrometric techniques have been revealing that oligosaccharides might have characteristic signal intensity profiles. We describe here a strategy for the rapid and accurate identification of the oligosaccharide structures on glycoproteins using only mass spectrometry. It is based on a comparison of the signal intensity profiles of multistage tandem mass (MSn) spectra between the analyte and a library of observational mass spectra acquired from structurally defined oligosaccharides prepared using glycosyltransferases. To smartly identify the oligosaccharides released from biological materials, a computer suggests which ion among the fragment ions in the MS/MS spectrum should yield the most informative MS3 spectrum to distinguish similar oligosaccharides. Using this strategy, we were able to identify the structure of N-linked oligosaccharides in immunoglobulin G as an example.     

Variable reference alignment: an improved peak alignment protocol for NMR spectral data with large intersample variation

In an effort to address the variable correspondence problem across large sample cohorts common in metabolomic/metabonomic studies, we have developed a prealignment protocol that aims to generate spectral segments sharing a common target spectrum. Under the assumption that a single reference spectrum will not correctly represent all spectra of a data set, the goal of this approach is to perform local alignment corrections on spectral regions which share a common "most similar" spectrum. A natural beneficial outcome of this procedure is the automatic definition of spectral segments, a feature that is not common to all alignment methods. This protocol is shown to specifically improve the quality of alignment in (1)H NMR data sets exhibiting large intersample compositional variation (e.g., pH, ionic strength). As a proof-of-principle demonstration, we have utilized two recently developed alignment algorithms specific to NMR data, recursive segment-wise peak alignment and interval correlated shifting, and applied them to two data sets composed of 15 aqueous cell line extract and 20 human urine (1)H NMR profiles. Application of this protocol represents a fundamental shift from current alignment methodologies that seek to correct misalignments utilizing a single representative spectrum, with the added benefit that it can be appended to any alignment algorithm.     

Automated proteomics of E. coli via top-down electron-transfer dissociation mass spectrometry

Electron-transfer dissociation (ETD) has recently been introduced as a fragmentation method for peptide and protein analysis. Unlike collisionally induced dissociation (CID), fragmentation by ETD occurs randomly along the peptide backbone. With the use of the sequences determined from the protein termini and the parent protein mass, intact proteins can be unambiguously identified. Because of the fast kinetics of these reactions, top-down proteomics can be performed using ETD in a linear ion trap mass spectrometer on a chromatographic time scale. Here we demonstrate the utility of ETD in high-throughput top-down proteomics using soluble extracts of E. coli. Development of a multidimensional fractionation platform, as well as a custom algorithm and scoring scheme specifically designed for this type of data, is described. The analysis resulted in the robust identification of 322 different protein forms representing 174 proteins, comprising one of the most comprehensive data sets assembled on intact proteins to date.     

Target spectra guided spectral unmixing for hyperspectral images

针对现在高光谱图像混合像元分解方法需要对所提取的端元的物理含义进行诠释的问题,提出了一种目标光谱指导下的混合像元分解方法,并给出了其具体算法实现.该方法首先针对若干给定的、具有明确物理含义的目标光谱,将光谱识别步骤引入混合像元分解过程,建立端元光谱与目标光谱间的对应关系,其次在最小距离限制的非负矩阵分解(MDC-NMF)方法基础上,引入光谱特征距离(SFD)作为正则项,以度量和保持存在对应关系的端元光谱与目标光谱间的相似性,并给出求解相应优化问题的优化算法.分别用模拟数据和真实数据对该方法的可行性和实际混合像元分解效果进行了验证,并将其与非监督情况下混合像元分解结果进行了比较分析.实验结果表明,该方法能够在目标光谱指导下较好诠释端元的物理含义,同时解决端元提取中的病态性问题.     

Statistical model for large-scale peptide identification in databases from tandem mass spectra using SEQUEST

Recent technological advances have made multidimensional peptide separation techniques coupled with tandem mass spectrometry the method of choice for high-throughput identification of proteins. Due to these advances, the development of software tools for large-scale, fully automated, unambiguous peptide identification is highly necessary. In this work, we have used as a model the nuclear proteome from Jurkat cells and present a processing algorithm that allows accurate predictions of random matching distributions, based on the two SEQUEST scores Xcorr and DeltaCn. Our method permits a very simple and precise calculation of the probabilities associated with individual peptide assignments, as well as of the false discovery rate among the peptides identified in any experiment. A further mathematical analysis demonstrates that the score distributions are highly dependent on database size and precursor mass window and suggests that the probability associated with SEQUEST scores depends on the number of candidate peptide sequences available for the search. Our results highlight the importance of adjusting the filtering criteria to discriminate between correct and incorrect peptide sequences according to the circumstances of each particular experiment.     

Optimized time alignment algorithm for LC-MS data: correlation optimized warping using component detection algorithm-selected mass chromatograms

Correlation optimized warping (COW) based on the total ion current (TIC) is a widely used time alignment algorithm (COW-TIC). This approach works successfully on chromatograms containing few compounds and having a well-defined TIC. In this paper, we have combined COW with a component detection algorithm (CODA) to align LC-MS chromatograms containing thousands of biological compounds with overlapping chromatographic peaks, a situation where COW-TIC often fails. CODA is a variable selection procedure that selects mass chromatograms with low noise and low background (so-called "high-quality" mass chromatograms). High-quality mass chromatograms selected in each COW segment ensure that the same compounds (based on their mass and their retention time) are used in the two-dimensional benefit function of COW to obtain correct and optimal alignments (COW-CODA). The performance of the COW-CODA algorithm was evaluated on three types of complex data sets obtained from the LC-MS analysis of samples commonly used for biomarker discovery and compared to COW-TIC using a new global comparison method based on overlapping peak area: trypsin-digested serum obtained from cervical cancer patients, trypsin-digested serum from a single patient that was treated with varying preanalytical parameters (factorial design study), and urine from pregnant and nonpregnant women. While COW-CODA did result in minor misalignments in rare cases, it was clearly superior to the COW-TIC algorithm, especially when applied to highly variable chromatograms (factorial design, urine). The presented algorithm thus enables automatic time alignment and accurate peak matching of multiple LC-MS data sets obtained from complex body fluids that are often used for biomarker discovery.     

Infrared multiphoton dissociation in quadrupole time-of-flight mass spectrometry: top-down characterization of proteins

The first implementation of infrared multiphoton dissociation (IRMPD) for a hybrid quadrupole time-of-flight (QqTOF) mass spectrometer is reported. Ions were trapped in the radio frequency-only quadrupole (q2), which normally serves as a collision cell, and irradiated by a continuous CO2 IR laser. The laser beam was introduced coaxially with the quadrupoles in order to maximize overlap with the ion path. The resolution of the TOF mass analyzer allowed direct charge state determination for fragments smaller than 7 kDa. For larger fragments, the charge state could be assigned using the multiple losses of water, characteristic for IRMPD of proteins. The analytical performance is demonstrated by top-down sequencing of several representative proteins (equine myoglobin, bovine casein, and human insulin and chaperonin 10). Various post-translational modifications such as phosphorylation, acetylation, formation of disulfide bridges, and removal of N-terminal methionine followed by acetylation are detected and characterized. The utility of IRMPD for the analysis of biological samples is demonstrated in a study of a recently identified potential marker for endometrial cancer, chaperonin 10.     

Measurement of the isotope enrichment of stable isotope-labeled proteins using high-resolution mass spectra of peptides

Stable isotope-enriched molecules are used as internal standards and as tracers of in vivo substrate metabolism. The accurate conversion of measured ratios in the mass spectrometer to mole ratios is complicated because a polyatomic molecule containing enriched atoms will result in a combinatorial distribution of isotopomers depending on the enrichment and number of "labeled" atoms. This effect could potentially cause a large error in the mole ratio measurement depending on which isotope peak or peaks were used to determine the ratio. We report a computational method that predicts isotope distributions over a range of enrichments and compares the predicted distributions to experimental peptide isotope distributions obtained by Fourier transform ion cyclotron resonance mass spectrometry. Our approach is accurate with measured enrichments within 1.5% of expected isotope distributions. The method is also precise with 4.9, 2.0, and 0.8% relative standard deviations for peptides containing 59, 79, and 99 atom % excess (15)N, respectively. The approach is automated making isotope enrichment calculations possible for thousands of peptides in a single muLC-FTICR-MS experiment.