Global and site-specific detection of human integrin alpha 5 beta 1 glycosylation using tandem mass spectrometry and the StrOligo algorithm

Glycans are oligosaccharides associated with proteins, and are known to confer specific functions and conformations on glycoproteins. As protein tridimensional structures are related to function, the study of glycans and their impact on protein folding can provide important information to the field of proteomics. The subdiscipline of glycomics (or glycoproteomics) is rapidly growing in importance as glycans in proteins have shown to be involved in protein-protein or protein-(drug, virus, antibody) interactions. Glycomics studies most often aim at identifying glycosylation sites, and thus are performed on deglycosylated proteins resulting in loss of site-specific details concerning the glycosylation. In order to obtain such details by mass spectrometry (MS), either whole glycoproteins must be digested and analyzed as mixtures of peptides and glycopeptides, or glycans must be isolated from glycopeptide fractions and analyzed as pools. This article describes parallel experiments involving both approaches, designed to take advantage of the StrOligo algorithm functionalities with the aim of characterizing glycosylation microheterogeneity on a specific site. A hybrid quadrupole-quadrupole-time-of-flight (QqTOF) instrument equipped with a matrix-assisted laser desorption/ionization (MALDI) source was used. Glycosylation of alpha 5 beta 1 subunits of human integrin was studied to test the methodology. The sample was divided in two aliquots, and glycans from the first aliquot were released enzymatically, labelled with 2-aminobenzamide, and identified using tandem mass spectrometry (MS/MS) and the StrOligo program. The other aliquot was digested with trypsin and the resulting peptides separated by reversed-phase high-performance liquid chromatography (HPLC). A specific collected fraction was then analyzed by MS before and after glycan release. These spectra allowed, by comparison, detection of a glycopeptide (several glycoforms) and elucidation of peptide sequence. Compositions of glycans present were proposed, and identification of possible glycan structures was conducted using MS/MS and StrOligo.     

Automated structural assignment of derivatized complex N-linked oligosaccharides from tandem mass spectra

Glycoprotein function is controlled by several biological factors, one of them being the structure of carbohydrate chains (glycans) attached to specific amino acids of the protein backbone. Changes in glycan structures have been shown to modify the secondary and tertiary conformation of glycoproteins, thus their function. Powerful analytical tools are available for the characterization of sugar structures, and recently mass spectrometry (MS) has been increasingly useful for this purpose. Manual interpretation of tandem mass spectrum is possible but tedious. Automated interpretation should speed the analysis and enhance the results obtained. A new computer program for automated interpretation of tandem MS spectra of complex N-linked glycans oligosaccharides from mammals will be described. N-Linked oligosaccharides standards were derivatized with 1-phenyl-3-methyl-5-pyrazolone (PMP) and analyzed by matrix-assisted laser desorption/ionization (MALDI)-tandem MS. Simulated tandem mass spectra of other common glycans were also generated to test the algorithm. The MALDI-MS/MS spectra featured resolved isotopic distributions for the [M + H](+) and fragment ions of oligosaccharides. These isotopic distributions complicated the automated analysis of the spectra and were removed to leave only monoisotopic peaks. An algorithm was written for this purpose, yielding simplified tandem mass spectra. Another algorithm is then used to determine the structure of the oligosaccharide. A score is then given to each structure, depending on agreement with experimental results. The program successfully assigned the true structure in 24 out of the 28 cases (86%) and the true structure was among the three top scoring structures in all cases.     

FluClass: A novel algorithm and approach to score and visualize the phylogeny of the influenza virus using mass spectrometry

A novel computer algorithm FluClass has been developed to facilitate the phylogenetic classification of influenza virus using mass spectral data. FluClass accepts a DNA or protein-based phylogenetic tree as input and generates theoretical peptide mass lists for each node. An experimental mass spectrum from an influenza virus protein digest is then placed onto the phylogenetic tree using a novel random resampling function (Z-score) that allows the scoring of spectrum against both internal and leaf nodes. Testing of the algorithm using hemagglutinin protein sequences from human-host influenza viruses showed that the Z-score performs comparably to the Profound scoring method for the scoring of leaf nodes and is substantially better at scoring internal nodes. Scoring of internal nodes allows colorizations of nodes of the phylogenetic tree enabling the classification of the query spectrum to be rapidly visualized. Finally we demonstrate the utility of FluClass on experimental spectra from six strains. Given that mass spectrometry data can be generated rapidly for influenza virus proteins, FluClass provides a fast and direct method for phylogenetic analysis of influenza proteins.     

基于稀疏模型的气相色谱-质谱数据解析及其在严重重叠峰解析中的应用

提出一种气相色谱-质谱（GC-MS）数据解析算法。以色谱峰顶点处的质谱作为待测谱,在谱库中检索一定量相关参考谱,求解关于各纯组分色谱响应值的方程。质谱检索采取分步策略,先利用质谱碎片规律建立高速索引进行粗选,然后使用强峰高概率出峰准则和耐挤压性准则排除无关质谱。为求解色谱响应值方程,提出基于稀疏模型的回归算法,相比传统算法,稀疏算法利于提取待测谱的主要结构,避免"过拟合"。实验结果表明,该质谱检索算法具有较高的精度和规模较小的剩余参考谱集,而所提稀疏模型算法可有效解析严重重叠峰。该算法可作为GC-MS重叠峰解析,特别是严重重叠峰解析的一种有效解决方案。     

Resolving the problem of chromatographic overlap by 3D cross correlation (3DCC) processing of LC, MS and NMR data for characterization of complex glycan mixtures

Chromatographic overlap is a common problem in the analysis of complex mixtures. As a result, it is not possible to identify the components because each resulting NMR or MS spectrum contains multiple components. We introduce three-dimensional cross correlation (3DCC) that dissects NMR spectra of a mixture into spectra of the individual components without actually separating them. Correlation of peaks from MS and NMR profiles along a common LC time domain yields 3DCC NMR spectra of pure components correlated with a mass and a retention time. The method requires an LC run followed by fractionation and recording of MS and NMR spectra. The method is applicable to mixtures of any classes of molecules. Here, we demonstrate its application to a mixture of complex glycans obtained from a glycoprotein. Fourteen glycans eluting within only 3 min showed heavy overlap in the chromatographic run. 3DCC allowed their direct characterization without separation. Some of these structures from the glycoprotein bovine fibrinogen had not previously been described. The 3DCC procedure has been implemented in standard software. Actually, 3DCC can be used for any combination of separation techniques, like LC or GC, combined with two characterization methods like UV, IR, Raman, NMR or MS.     

GlycoDeNovo – an Efficient Algorithm for Accurate de novo Glycan Topology Reconstruction from Tandem Mass Spectra

A major challenge in glycomics is the characterization of complex glycan structures that are essential for understanding their diverse roles in many biological processes. We present a novel efficient computational approach, named GlycoDeNovo, for accurate elucidation of the glycan topologies from their tandem mass spectra. Given a spectrum, GlycoDeNovo first builds an interpretation-graph specifying how to interpret each peak using preceding interpreted peaks. It then reconstructs the topologies of peaks that contribute to interpreting the precursor ion. We theoretically prove that GlycoDeNovo is highly efficient. A major innovative feature added to GlycoDeNovo is a data-driven IonClassifier which can be used to effectively rank candidate topologies. IonClassifier is automatically learned from experimental spectra of known glycans to distinguish B- and C-type ions from all other ion types. Our results showed that GlycoDeNovo is robust and accurate for topology reconstruction of glycans from their tandem mass spectra.

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Graphical Abstract ?

     

De novo glycan structural identification from mass spectra using tree merging strategy

MotivationGlycans are large molecules with specific tree structures. Glycans play important roles in a great variety of biological processes. These roles are primarily determined by the fine details of their structures, making glycan structural identification highly desirable. Mass spectrometry (MS) has become the major technology for elucidation of glycan structures. Most de novo approaches to glycan structural identification from mass spectra fall into three categories: enumerating followed by filtering approaches, heuristic and dynamic programming-based approaches. The former suffers from its low efficiency while the latter two suffer from the possibility of missing the actual glycan structures. Thus, how to reliably and efficiently identify glycan structures from mass spectra still remains challenging.ResultsIn this study we propose an efficient and reliable approach to glycan structure identification using tree merging strategy. Briefly, for each MS peak, our approach first calculated monosaccharide composition of its corresponding fragment ion, and then built a constraint that forces these monosaccharides to be directly connected in the underlying glycan tree structure. According to these connecting constraints, we next merged constituting monosaccharides of the glycan into a complete structure step by step. During this process, the intermediate structures were represented as subtrees, which were merged iteratively until a complete tree structure was generated. Finally the generated complete structures were ranked according to their compatibility to the input mass spectra. Unlike the traditional enumerating followed by filtering strategy, our approach performed deisomorphism to remove isomorphic subtrees, and ruled out invalid structures that violates the connection constraints at each tree merging step, thus significantly increasing efficiency. In addition, all complete structures satisfying the connection constraints were enumerated without any missing structure. Over a test set of 10 N-glycan standards, our approach accomplished structural identification in minutes and gave the manually-validated structure first three highest score. We further successfully applied our approach to profiling and subsequent structure assignment of glycans released from glycoprotein mAb, which was in perfect agreement with previous studies and CE analysis.     

ESIprot: a universal tool for charge state determination and molecular weight calculation of proteins from electrospray ionization mass spectrometry data

Electrospray ionization (ESI) ion trap mass spectrometers with relatively low resolution are frequently used for the analysis of natural products and peptides. Although ESI spectra of multiply charged protein molecules also can be measured on this type of devices, only average spectra are produced for the majority of naturally occurring proteins. Evaluating such ESI protein spectra would provide valuable information about the native state of investigated proteins. However, no suitable and freely available software could be found which allows the charge state determination and molecular weight calculation of single proteins from average ESI‐MS data. Therefore, an algorithm based on standard deviation optimization (scatter minimization) was implemented for the analysis of protein ESI‐MS data. The resulting software ESIprot was tested with ESI‐MS data of six intact reference proteins between 12.4 and 66.7 kDa. In all cases, the correct charge states could be determined. The obtained absolute mass errors were in a range between ?0.2 and 1.2 Da, the relative errors below 30 ppm. The possible mass accuracy allows for valid conclusions about the actual condition of proteins. Moreover, the ESIprot algorithm demonstrates an extraordinary robustness and allows spectral interpretation from as little as two peaks, given sufficient quality of the provided m/z data, without the necessity for peak intensity data. ESIprot is independent from the raw data format and the computer platform, making it a versatile tool for mass spectrometrists. The program code was released under the open‐source GPLv3 license to support future developments of mass spectrometry software. Copyright © 2010 John Wiley & Sons, Ltd.     

GARANT-a general algorithm for resonance assignment of multidimensional nuclear magnetic resonance spectra

A new program for automatic resonance assignment of nuclear magnetic resonance (NMR) spectra of proteins, GARANT (General Algorithm for Resonance AssignmeNT), is introduced. Three principal elements used in this approach are: (a) representation of resonance assignments as an optimal match of two graphs describing, respectively, peaks expected from combined knowledge of the primary structure and the magnetization transfer pathways in the spectra used, and experimentally observed peaks; (b) a scoring scheme able to distinguish between correct and incorrect resonance assignments; and (c) combination of an evolutionary algorithm with a local optimization routine. The score that evaluates the match of expected peaks to observed peaks relies on the agreement of the information available about these peaks, most prominently, but not exclusively, the chemical shifts. Tests show that the combination of an evolutionary algorithm and a local optimization routine yields results that are clearly superior to those obtained when using either of the two techniques separately in the search for the correct assignments. GARANT is laid out for assignment problems involving peaks observed in two- and three-dimensional homonuclear and heteronuclear NMR spectra of proteins. © 1997 by John Wiley & Sons, Inc.     

Automatic analysis of hydrogen/deuterium exchange mass spectra of peptides and proteins using calculations of isotopic distributions

High mass-resolving power has been shown to be useful for studying the conformational dynamics of proteins by hydrogen/deuterium (H/D) exchange. A computer algorithm was developed that automatically identifies peptides and their extent of deuterium incorporation from H/D exchange mass spectra of enzymatic digests or fragment ions produced by collisionally induced dissociation (CID) or electron capture dissociation (ECD). The computer algorithm compares measured and calculated isotopic distributions and uses a fast calculation of isotopic distributions using the fast Fourier transform (FFT). The algorithm facilitates rapid and automated analysis of H/D exchange mass spectra suitable for high-throughput approaches to the study of peptide and protein structures. The algorithm also makes the identification independent on comparisons with undeuterated control samples. The applicability of the algorithm was demonstrated on simulated isotopic distributions as well as on experimental data, such as Fourier transform ion cyclotron resonance (FTICR) mass spectra of myoglobin peptic digests, and CID and ECD spectra of substance P.     

Pattern-based algorithm for peptide sequencing from tandem high energy collision-induced dissociation mass spectra

A new strategy is reported for extracting complete and partial sequence information from collision-induced dissociation (CID) spectra of peptides, CID spectra are obtained from high energy CID of peptide molecular ions on a four-sector tandem mass spectrometer with an electro-optically coupled microchannel array detector, A peak detection routine reduces the spectrum to a list of peak masses and peak heights, which is then used for sequencing, The sequencing algorithm was designed to use spectral data to generate sequence fits directly rather than to use data to test the fit of series of sequence guesses. The peptide sequencing algorithm uses a pattern based on the polymeric nature of peptides to classify spectral peaks into sets that are related in a sequence-independent manner, It then establishes sequence relationships among these sets, Peak detection from raw data takes 10–20 s, with sequence generation requiring an additional 10–60 s on a Sun 3/60 workstation, The program is written in the C language to run on a Unix platform. The principal advantages of our method are in the speed of analysis and the potential for identifying modified or rare amino acids. The algorithm was designed to permit real-time sequencing but awaits hardware modifications to allow real-time access to CID spectra.     

Stereospecific assignments of protein NMR resonances based on the tertiary structure and 2D/3D NOE data

In many cases of protein structure determination by NMR a high-quality structure is required. An important contribution to structural precision is stereospecific assignment of magnetically nonequivalent prochiral methylene and methyl groups, eliminating the need for introducing pseudoatoms and pseudoatom corrections in distance restraint lists. Here, we introduce the stereospecific assignment program that uses the resonance assignment, a preliminary 3D structure and 2D and/or 3D nuclear Overhauser effect spectroscopy peak lists for stereospecific assignment. For each prochiral group the algorithm automatically calculates a score for the two different stereospecific assignment possibilities, taking into account the presence and intensity of the nuclear Overhauser effect (NOE) peaks that are expected from the local environment of each prochiral group (i.e., the close neighbors). The performance of the algorithm has been tested and used on NMR data of alpha-helical and beta-sheet proteins using homology models and/or X-ray structures. The program produced no erroneous stereospecific assignments provided the NOEs were carefully picked and the 3D model was sufficiently accurate. The set of NOE distance restraints produced by nmr2st using the results of the SSA module was superior in generating good-quality ensembles of NMR structures (low deviations from upper limits in conjunction with low root-mean-square-deviation values) in the first round of structure calculations. The program uses a novel approach that employs the entire 3D structure of the protein to obtain stereospecific assignment; it can be used to speed up the NMR structure refinement and to increase the quality of the final NMR ensemble even when no scalar or residual dipolar coupling information is available.     

A universal algorithm for fast and automated charge state deconvolution of electrospray mass-to-charge ratio spectra

This article describes a new algorithm for charge state determination and deconvolution of electrospray ionization (ESI) mass-to-charge ratio spectra. The algorithm (Zscore) is based on a charge scoring scheme that incorporates all above-threshold members of a family of charge states or isotopic components, and deconvolves both low- and high-resolution mass-to-charge ratio spectra, with or without a peak list (stick plot). A scoring weight factor, log (I/I ₀), in which I is the signal magnitude at a calculated mass-to-charge ratio, and I ₀ is the signal threshold near that mass-to-charge ratio, was used in most cases. For high-resolution mass-to-charge ratio spectra in which all isotopic peaks are resolved, the algorithm can deconvolve overlapped isotopic multiplets of the same or different charge state. Compared to other deconvolution techniques, the algorithm is robust, rapid, and fully automated (i. e., no user input during the deconvolution process). It eliminates artifact peaks without introducing peak distortions. Its performance is demonstrated for experimental ESI Fourier transform ion cyclotron resonance mass-to-charge ratio spectra (both low and high resolution). Charge state deconvolution to yield a “zero-charge” mass spectrum should prove particularly useful for interpreting spectra of complex mixtures, identifying contaminants, noncovalent adducts, fragments (N-terminal, C-terminal, internal), and chemical modifications of electrosprayed biomacromolecules.     

A theoretical study of pure and mixed caesium clusters and cluster ions, Cs(l)H(m)O(n)(0/+), l ≤ 5: geometry, energetics and photofragmentation

Motivated by recent progress in the mass spectroscopy of the elementary reaction of alkali metals and water dispersed in ultracold helium nanodroplets (S. Müller et al., Phys. Rev. Lett., 2009, 102, 183401.), we investigate the properties of pure and mixed Cs clusters and cluster ions, Cs(l)H(m)O(n)(0/+), from a quantum chemical perspective. The presence of Cs atoms requires a careful choice of the methodology, which we have tested for small molecules for which experimental results were available. With the thus selected density functional, pseudopotential and basis set, we compute the geometry, the ionization potentials and the atomization energy, enabling a proper estimate of the energetics of cluster fragmentation upon photoionization. Based upon these calculations, we are able to construct a fragmentation tree that rationalizes the origin of all peaks observed in the experimental mass spectrum. Infrared spectra are computed, and we introduce a simple mixed quantum-classical model that essentially reproduces the cluster geometries.     

Precursor ion scanning for detection and structural characterization of heterogeneous glycopeptide mixtures

The structure of N-linked glycans is determined by a complex, anabolic, intracellular pathway but the exact role of individual glycans is not always clear. Characterization of carbohydrates attached to glycoproteins is essential to aid understanding of this complex area of biology. Specific mass spectral detection of glycopeptides from protein digests may be achieved by on-line HPLC-MS, with selected ion monitoring (SIM) for diagnostic product ions generated by cone voltage fragmentation, or by precursor ion scanning for terminal saccharide product ions, which can yield the same information more rapidly. When glycosylation is heterogeneous, however, these approaches can result in spectra that are complex and poorly resolved. We have developed methodology, based around precursor ion scanning for ions of high m/z, that allows site specific detection and structural characterization of glycans at high sensitivity and resolution. These methods have been developed using the standard glycoprotein, fetuin, and subsequently applied to the analysis of the N-linked glycans attached to the scrapie-associated prion protein, PrP(Sc). These glycans are highly heterogeneous and over 30 structures have been identified and characterized site specifically. Product ion spectra have been obtained on many glycopeptides confirming structure assignments. The glycans are highly fucosylated and carry Lewis X or sialyl Lewis X epitopes and the structures are in-line with previous results.     

A new matching algorithm for high resolution mass spectra

We present a new matching algorithm designed to compare high-resolution spectra. Whereas existing methods are bound to compare fixed intervals of ion masses, the accurate mass spectrum (AMS) distance method presented here is independent of any alignment. Based on the Jeffreys-Matusitas (JM) distance, a difference between observed peaks across pairs of spectra can be calculated, and used to find a unique correspondence between the peaks. The method takes into account that there may be differences in resolution of the spectra. The algorithm is used for indexing in a database containing 80 accurate mass spectra from an analysis of extracts of 80 isolates representing the nine closely related species in the Penicillium series Viridicata. Using this algorithm we can obtain a retrieval performance of approximately 97-98% that is comparable with the best of the existing methods (e.g., the dot-product distance). Furthermore, the presented method is independent of any variable alignment procedures or binning.     

Improving protein identification from peptide mass fingerprinting through a parameterized multi-level scoring algorithm and an optimized peak detection

We have developed a new algorithm to identify proteins by means of peptide mass fingerprinting. Starting from the matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) spectra and environmental data such as species, isoelectric point and molecular weight, as well as chemical modifications or number of missed cleavages of a protein, the program performs a fully automated identification of the protein. The first step is a peak detection algorithm, which allows precise and fast determination of peptide masses, even if the peaks are of low intensity or they overlap. In the second step the masses and environmental data are used by the identification algorithm to search in protein sequence databases (SWISS-PROT and/or TrEMBL) for protein entries that match the input data. Consequently, a list of candidate proteins is selected from the database, and a score calculation provides a ranking according to the quality of the match. To define the most discriminating scoring calculation we analyzed the respective role of each parameter in two directions. The first one is based on filtering and exploratory effects, while the second direction focuses on the levels where the parameters intervene in the identification process. Thus, according to our analysis, all input parameters contribute to the score, however with different weights. Since it is difficult to estimate the weights in advance, they have been computed with a generic algorithm, using a training set of 91 protein spectra with their environmental data. We tested the resulting scoring calculation on a test set of ten proteins and compared the identification results with those of other peptide mass fingerprinting programs.     

A method for reducing the time required to match protein sequences with tandem mass spectra

An algorithm for reducing the time necessary to match a large set of peptide tandem mass spectra with a list of protein sequences is described. This algorithm breaks the process into multiple steps. A rapid survey step identifies all protein sequences that are reasonable candidates for a match with a set of tandem mass spectra. These candidates are then used as models, which are refined by detailed analysis of the set of tandem mass spectra for evidence of incomplete enzymatic hydrolysis, non-specific hydrolysis and chemical modifications of amino acid residues resulting from either post-translational modifications or sample handling. Compared with current one-step methods for matching proteins to mass spectra, this multiple-step method can decrease the time required for the calculation by several orders of magnitude.     

Comparison of continuous and pulsed labeling amide hydrogen exchange/mass spectrometry for studies of protein dynamics

In contrast to the rigid structures portrayed by X-ray diffraction, proteins in solution display constant motion which leads to populations that are momentarily unfolded. To begin to understand protein dynamics, we must have experimental methods for determining rates of folding and unfolding, as well as for identifying structures of folding and unfolding intermediates. Amide hydrogen exchange has become an important tool for such measurements. When urea is used to stabilize unfolded forms of proteins, the refolding rates may become slower than the rates of isotope exchange. In such cases, the intermolecular distribution of deuterium among the entire population of molecules may become bimodal, giving rise to a bimodal distribution of isotope peaks in mass spectra of the protein or its peptic fragments. When the protein is exposed continuously to D2O, the relative intensities of the two envelopes of isotope peaks give an integrated account of populations participating in the folding/unfolding process. However, when the protein is exposed only briefly to D2O, the relative intensities of the two envelopes of isotope peaks give an instantaneous measure of the folded/unfolded populations. Application of these two labeling methods to a large protein, aldolase, is described along with a discussion of specific parameters required to optimize these experiments.