Immobilized RNA switches for the analysis of complex chemical and biological mixtures

A prototype biosensor array has been assembled from engineered RNA molecular switches that undergo ribozyme-mediated self-cleavage when triggered by specific effectors. Each type of switch is prepared with a 5'-thiotriphosphate moiety that permits immobilization on gold to form individually addressable pixels. The ribozymes comprising each pixel become active only when presented with their corresponding effector, such that each type of switch serves as a specific analyte sensor. An addressed array created with seven different RNA switches was used to report the status of targets in complex mixtures containing metal ion, enzyme cofactor, metabolite, and drug analytes. The RNA switch array also was used to determine the phenotypes of Escherichia coli strains for adenylate cyclase function by detecting naturally produced 3',5'- cyclic adenosine monophosphate (cAMP) in bacterial culture media.     

Linkage analysis for complex diseases: a new life for an old method

In this paper, I present the main approaches used in gene mapping of complex human diseases by linkage analysis based on molecular markers. The first section describes the traditional LOD-score analysis and gives a review of different improvements and refinements of this approach, which has been proposed in order to take into account complicating factors such as incomplete penetrance, genetic heterogeneity and unknown mode of inheritance. The second section describes the three main approaches of non-parametric linkage analysis, for which there is no need to specify a genetic model (mode of inheritance, allele frequencies, ..). A comparison between these three methods, which may seem to be more appropriate for complex diseases, is given based on the most recent published studies. In the third section and discussion, I compare the LOD-score and non-parametric methods by stressing the advantages and drawbacks of each approach as found in recent publications. I deduce that, in spite of its apparent and assumed inappropriateness to the analysis of complex diseases, the LOD-score method is still very useful and could provide, in some circumstances, more power and precision than model-free methods.     

Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra

To take advantage of the potential quantitative benefits offered by tandem mass spectrometry, we have modified the method in which tandem mass spectrum data are acquired in 'shotgun' proteomic analyses. The proposed method is not data dependent and is based on the sequential isolation and fragmentation of precursor windows (of 10 m/z) within the ion trap until a desired mass range has been covered. We compared the quantitative figures of merit for this method to those for existing strategies by performing an analysis of the soluble fraction of whole-cell lysates from yeast metabolically labeled in vivo with (15)N. To automate this analysis, we modified software (RelEx) previously written in the Yates lab to generate chromatograms directly from tandem mass spectra. These chromatograms showed improvements in signal-to-noise ratio of approximately three- to fivefold over corresponding chromatograms generated from mass spectrometry scans. In addition, to demonstrate the utility of the data-independent acquisition strategy coupled with chromatogram reconstruction from tandem mass spectra, we measured protein expression levels in two developmental stages of Caenorhabditis elegans.     

Novel application of reversed-phase UPLC-oaTOF-MS for lipid analysis in complex biological mixtures: a new tool for lipidomics

Ultra-Performance LC (UPLC) utilizing sub-2-mum porous stationary phase particles operating with high linear velocities at pressures >9000 psi was coupled with orthogonal acceleration time-of-flight (oaTOF) mass spectrometry and successfully employed for the rapid separation of lipids from complex matrices. The UPLC system produced information-rich chromatograms with typical measured peak widths of 3 s at peak base, generating peak capacities in excess of 200 in 10 min. Further UPLC coupled with MSE technology provided parent and fragment mass information of lipids in one chromatographic run, thus, providing an attractive alternative to current LC methods for targeted lipid analysis as well as lipidomic studies.     

Definition and characterization of a "trypsinosome" from specific peptide characteristics by nano-HPLC-MS/MS and in silico analysis of complex protein mixtures

Although HPLC-ESI-MS/MS is rapidly becoming an indispensable tool for the analysis of peptides in complex mixtures, the sequence coverage it affords is often quite poor. Low protein expression resulting in peptide signal intensities that fall below the limit of detection of the MS system in combination with differences in peptide ionization efficiency plays a significant role in this. A second important factor stems from differences in physicochemical properties of each peptide and how these properties relate to chromatographic retention and ultimate detection. To identify and understand those properties, we compared data from experimentally identified peptides with data from peptides predicted by in silico digest of all corresponding proteins in the experimental set. Three different complex protein mixtures extracted were used to define a training set to evaluate the amino acid retention coefficients based on linear regression analysis. The retention coefficients were also compared with other previous hydrophobic and retention scale. From this, we have constructed an empirical model that can be readily used to predict peptides that are likely to be observed on our HPLC-ESI-MS/MS system based on their physicochemical properties. Finally, we demonstrated that in silico prediction of peptides and their retention coefficients can be used to generate an inclusion list for a targeted mass spectrometric identification of low abundance proteins in complex protein samples. This approach is based on experimentally derived data to calibrate the method and therefore may theoretically be applied to any HPLC-MS/MS system on which data are being generated.     

LC-MS-based method for the qualitative and quantitative analysis of complex lipid mixtures

A simple and robust LC-MS-based methodology for the investigation of lipid mixtures is described, and its application to the analysis of human lipoprotein-associated lipids is demonstrated. After an optional initial fractionation on Silica 60, normal-phase HPLC-MS on a YMC PVA-Sil column is used first for class separation, followed by reversed-phase LC-MS or LC-tandem mass spectrometry using an Atlantis dC18 capillary column, and/or nanospray MS, to fully characterize the individual lipids. The methodology is applied here for the analysis of human apolipoprotein B-associated lipids. This approach allows for the determination of even low percentages of lipids of each molecular species and showed clear differences between lipids associated with apolipoprotein B-100-LDL isolated from a normal individual and those associated with a truncated version, apolipoprotein B-67-containing lipoproteins, isolated from a homozygote patient with familial hypobetalipoproteinemia. The methods described should be easily adaptable to most modern MS instrumentation.     

Development and validation of a spectral library searching method for peptide identification from MS/MS

A notable inefficiency of shotgun proteomics experiments is the repeated rediscovery of the same identifiable peptides by sequence database searching methods, which often are time-consuming and error-prone. A more precise and efficient method, in which previously observed and identified peptide MS/MS spectra are catalogued and condensed into searchable spectral libraries to allow new identifications by spectral matching, is seen as a promising alternative. To that end, an open-source, functionally complete, high-throughput and readily extensible MS/MS spectral searching tool, SpectraST, was developed. A high-quality spectral library was constructed by combining the high-confidence identifications of millions of spectra taken from various data repositories and searched using four sequence search engines. The resulting library consists of over 30,000 spectra for Saccharomyces cerevisiae. Using this library, SpectraST vastly outperforms the sequence search engine SEQUEST in terms of speed and the ability to discriminate good and bad hits. A unique advantage of SpectraST is its full integration into the popular Trans Proteomic Pipeline suite of software, which facilitates user adoption and provides important functionalities such as peptide and protein probability assignment, quantification, and data visualization. This method of spectral library searching is especially suited for targeted proteomics applications, offering superior performance to traditional sequence searching.     

Fast atom bombardment: A new mass spectrometric method for peptide sequence analysis

We have studied a selection of peptides using a new mass spectrometric ionisation technique - fast atom bombardment (FAB). We define the fragmentation pathways observed and comment on the utility in sequence analysis. A simple acetylation experiment is shown to aid rapid sequence assignment.     

Maximal clique method for the automated analysis of NMR TOCSY spectra of complex mixtures

Characterization of the chemical components of complex mixtures in solution is important in many areas of biochemistry and chemical biology, including metabolomics. The use of 2D NMR total correlation spectroscopy (TOCSY) experiments has proven very useful for the identification of known metabolites as well as for the characterization of metabolites that are unknown by taking advantage of the good resolution and high sensitivity of this homonuclear experiment. Due to the complexity of the resulting spectra, automation is critical to facilitate and speed-up their analysis and enable high-throughput applications. To better meet these emerging needs, an automated spin-system identification algorithm of TOCSY spectra is introduced that represents the cross-peaks and their connectivities as a mathematical graph, for which all subgraphs are determined that are maximal cliques. Each maximal clique can be assigned to an individual spin system thereby providing a robust deconvolution of the original spectrum for the easy extraction of critical spin system information. The approach is demonstrated for a complex metabolite mixture consisting of 20 compounds and for E. coli cell lysate.     

Development of high-throughput liquid chromatography injected ion mobility quadrupole time-of-flight techniques for analysis of complex peptide mixtures

The development of a multidimensional approach involving high-performance liquid chromatography (LC), ion mobility spectrometry (IMS) and tandem mass spectrometry is described for the analysis of complex peptide mixtures. In this approach, peptides are separated based on differences in their LC retention times and mobilities (as ions drift through He) prior to being introduced into a quadrupole/octopole/time-of-flight mass spectrometer. The initial LC separation and IMS dispersion of ions is used to label ions for subsequent fragmentation studies that are carried out for mixtures of ions. The approach is demonstrated by examining a mixture of peptides generated from tryptic digestion of 18 commercially available proteins. Current limitations of this initial study and potential advantages of the experimental approach are discussed.     

Data filtration for more robust alignment of chromatograms of complex peptide mixtures

In carrying out proteomic researches using mass-spectrometry there often arises a need to compare experimental data with each other (e.g. control of pathology, the labeled to unlabelled samples). If for peptide identification in different experiments one uses only their exact mass measurements and the retention time in the chromatographic column, difficulties with the identification of chromatographic peaks belonging to the same substances in different chromatograms come up (retention time normalization). Due to inevitable discrepancies in chromatographic conditions of experiments (replacement of chromatographic columns, small changes in mobile phase flow rate or solvent concentration) retention times of the same peptides will diverge from experiment to experiment. In this paper we offer a reliable method for selecting peaks from mass-chromatograms corresponding to the same peptides, which can later be used for retention time normalization (either linear or any other monotone function).     

MS/IR,a new MS-based hyphenated method for analysis of hexuronic acid epimers in glycosaminoglycans

We report an original MS-based hyphenated method for the elucidation of the epimerization in GAG fragments. It consists of measuring simultaneously the MS/MS spectrum and the gas phase IR spectrum to gain direct structural information. This is possible using a customized MS instrument, modified to allow injection of a tunable IR laser inside of the instrument for in situ spectroscopy of trapped ions. The proof of principle of this approach is performed in the case of a hyaluronic acid tetrasaccharide standard. In addition, we provide the reference IR fingerprint of glucuronic and Iduronic monosaccharide standards. Remarkably, we show that the gas phase IR fingerprint of reference hexuronic acid monosaccharides proves to be transposable to oligosaccharides. Therefore, the method presented here is predictive and allows structural elucidation of unknown GAG fragments, even in the absence of referenced standards.     

Characterizing complex peptide mixtures using a multi-dimensional liquid chromatography-mass spectrometry system: Saccharomyces cerevisiae as a model system

A rugged, reproducible, multi-dimensional LC-MS system was developed to identify and characterize proteins involved in protein-protein interactions and/or protein complexes. Our objective was to optimize chromatographic parameters for complex protein mixture analyses using automated peptide sequence recognition as an analytical end-point. The chromatographic system uses orthogonal separation mechanisms by employing strong cation exchange (SCX) in the first dimension and reversed phase (RP) in the second dimension. The system is fully automated and sufficiently robust to handle direct injections of protein digests. This system incorporates a streamlined post analysis results comparison, called DBParser, which permitted comprehensive evaluation of sample loading and chromatographic conditions to optimize the performance and reproducibility. Peptides obtained from trypsin digestion of a yeast soluble extract provided an open-ended model system containing a wide variety and dynamic range of components. Conditions are described that resulted in an average (n = 4) of 1489 unique peptide identifications, corresponding to 459 non-redundant protein sequence database records (SDRs) in the 20 microg soluble fraction digest.     

Preparative peptide isoelectric focusing as a tool for improving the identification of lysine-acetylated peptides from complex mixtures

Protein sequence database searching of tandem mass spectrometry data is commonly employed to identify post-translational modifications (PTMs) to peptides in global proteomic studies. In these studies, the accurate identification of these modified peptides relies on strategies to ensure high-confidence results from sequence database searching in which differential mass shift parameters are employed to identify PTMs to specific amino acids. Using lysine acetylation as an example PTM, we have observed that the inclusion of differential modification information in sequence database searching dramatically increases the potential for false-positive sequence matches to modified peptides, making the confident identification of true sequence matches difficult. In a proof-of-principle study of whole cell yeast lysates, we demonstrate the combination of preparative isoelectric focusing using free-flow electrophoresis, and an adjusted peptide isoelectric point prediction algorithm, as an effective means to increase the confidence of lysine-acetylated peptide identification. These results demonstrate the potential utility of this general strategy for improving the identification of PTMs which cause a shift to the intrinsic isoelectric point of peptides.     

A new algorithm for the evaluation of shotgun peptide sequencing in proteomics: support vector machine classification of peptide MS/MS spectra and SEQUEST scores

Shotgun tandem mass spectrometry-based peptide sequencing using programs such as SEQUEST allows high-throughput identification of peptides, which in turn allows the identification of corresponding proteins. We have applied a machine learning algorithm, called the support vector machine, to discriminate between correctly and incorrectly identified peptides using SEQUEST output. Each peptide was characterized by SEQUEST-calculated features such as delta Cn and Xcorr, measurements such as precursor ion current and mass, and additional calculated parameters such as the fraction of matched MS/MS peaks. The trained SVM classifier performed significantly better than previous cutoff-based methods at separating positive from negative peptides. Positive and negative peptides were more readily distinguished in training set data acquired on a QTOF, compared to an ion trap mass spectrometer. The use of 13 features, including four new parameters, significantly improved the separation between positive and negative peptides. Use of the support vector machine and these additional parameters resulted in a more accurate interpretation of peptide MS/MS spectra and is an important step toward automated interpretation of peptide tandem mass spectrometry data in proteomics.     

Index-ion triggered MS2 ion quantification: a novel proteomics approach for reproducible detection and quantification of targeted proteins in complex mixtures

Biomedical research requires protein detection technology that is not only sensitive and quantitative, but that can reproducibly measure any set of proteins in a biological system in a high throughput manner. Here we report the development and application of a targeted proteomics platform termed index-ion triggered MS2 ion quantification (iMSTIQ) that allows reproducible and accurate peptide quantification in complex mixtures. The key feature of iMSTIQ is an approach called index-ion triggered analysis (ITA) that permits the reproducible acquisition of full MS2 spectra of targeted peptides independent of their ion intensities. Accurate quantification is achieved by comparing the relative intensities of multiple pairs of fragment ions derived from isobaric targeted peptides during MS2 analysis. Importantly, the method takes advantage of the favorable performance characteristics of the LTQ-Orbitrap, which include high mass accuracy, resolution, and throughput. As such it provides an attractive targeted proteomics tool to meet the demands of systems biology research and biomarker studies.     

Network-based diffusion analysis: a new method for detecting social learning

Social learning has been documented in a wide diversity of animals. In free-living animals, however, it has been difficult to discern whether animals learn socially by observing other group members or asocially by acquiring a new behaviour independently. We addressed this challenge by developing network-based diffusion analysis (NBDA), which analyses the spread of traits through animal groups and takes into account that social network structure directs social learning opportunities. NBDA fits agent-based models of social and asocial learning to the observed data using maximum-likelihood estimation. The underlying learning mechanism can then be identified using model selection based on the Akaike information criterion. We tested our method with artificially created learning data that are based on a real-world co-feeding network of macaques. NBDA is better able to discriminate between social and asocial learning in comparison with diffusion curve analysis, the main method that was previously applied in this context. NBDA thus offers a new, more reliable statistical test of learning mechanisms. In addition, it can be used to address a wide range of questions related to social learning, such as identifying behavioural strategies used by animals when deciding whom to copy.     

H2BC: a new technique for NMR analysis of complex carbohydrates

It is demonstrated that the H2BC NMR pulse sequence (J. Am. Chem. Soc.2005, 127, 6154, Magn. Reson. Chem.2005, 43, 971-974) offers unambiguous assignments and significant simplification of NMR spectra of large and complex carbohydrates compared to other techniques for the establishment of correlations over more than one bond. H2BC almost exclusively correlates protons and proton-bearing carbon spins separated by two covalent bonds and is independent of occasionally vanishing (2)J(CH) coupling constants, which alleviates the problem of missing two-bond correlations in HMBC spectra. H2BC also solves the problem of distinguishing two- and three-bond correlations in HSQC-TOCSY or HMBC. It is a further asset of H2BC that the experiment is significantly shorter than HMBC and HSQC-TOCSY, and hence less sensitive to transverse relaxation. The H2BC experiment is demonstrated on an approximately 30-residue oligosaccharide from Francisella victoria.     

Absolute quantification of allergens from complex mixtures: a new sensitive tool for standardization of allergen extracts for specific immunotherapy

Products for specific diagnosis and immunotherapy of IgE-mediated allergies are currently based on natural extracts. Quantification of major allergen content is an important aspect of standardization as important allergens particularly impact vaccine potency. The aim of the study was to develop a mass spectrometry (MS) based assay for absolute quantification of Timothy (Phleum pratense) pollen allergens Phl p 1 and Phl p 5 in P. pratense extract. High-resolution and accurate mass (HRAM) MS was selected for its ability to detect peptides with high selectivity and mass accuracy (<3 ppm). Isotope labeled heavy peptides were used for absolute quantification of specific isoallergens of Phl p 1 and Phl p 5 at low femtomole level in P. pratense extract. Robustness and linearity of the method was demonstrated with intra day precision ≤ 5% (n = 3). Phl p 1b was shown to be 5 times less abundant than its variant Phl p 1a and Phl p 5b was shown to be 9 times more abundant than the Phl p 5a. The present study shows that allergen, and/or isoallergen specific, surrogate signature peptides analyzed with HRAM MS is a sensitive and accurate tool for identification and quantification of allergens from complex allergen sources.