Post alignment clustering procedure for comparative quantitative proteomics LC-MS data

Comparative LC-MS is a powerful method for detailed quantitative comparison of complex protein mixtures. Dedicated software is required for detection, matching, and alignment of peaks in multiple LC-MS datasets. However, retention time shifts, saturation effects, limitations of experimental accuracy, and possible occurrence of split peaks make it difficult for software to perfectly match all chromatograms. We describe a procedure to assess the above problems and show that dataset quality can be enhanced with the aid of cluster analysis.     

New method for global alignment of 2 DNA sequences by the tree data structure

We introduce a new approach to investigate problem of DNA sequence alignment. The method consists of three parts: (i) simple alignment algorithm, (ii) extension algorithm for largest common substring, (iii) graphical simple alignment tree (GSA tree). The approach firstly obtains a graphical representation of scores of DNA sequences by the scoring equation R₀*R−S₀*S−T₀*(a+bk). Then a GSA tree is constructed to facilitate solving the problem for global alignment of 2 DNA sequences. Finally we give several practical examples to illustrate the utility and practicality of the approach.     

基于多次重复液相质谱生物实验数据校准方法研究

在蛋白质组学中,进行液相质谱(LC-MS)实验谱数据处理,发现并分析生物标志物的复杂肽或蛋白质样本的差异是重点,而校准相同样本的多次重复实验中肽链产生的洗脱时间峰信号(LC峰)是进行量化、分析差异的关键。目前多个重复实验数据的校准通常是在重复的实验数据集中根据液相二级质谱(LC-MS/MS)实验标识LC峰的时间特征,然后使用翘曲函数对时间特征进行对齐。由于多重数据的洗脱时间误差产生是随机的,统一使用翘曲函数校准会产生较大误差。为了解决这个问题,本研究重点研究了多个重复实验数据中LC峰的时间校准算法。我们选取了两个重复实验数据,采用机器学习的思路,通过选用两个数据的LC-MS/MS中重复检测到的肽链数据作为可信数据,部分选为训练序列,部分作为测试序列,建立统计数学模型,提出了一种新的校准算法,并采用测试序列对该统计模型进行准确率测试,表明算法的准确性达到95%以上;然后,将该模型应用在两个实验数据的所有LC-MS/MS肽链检测值上,提高检测值在多个数据中的覆盖率,表明覆盖率可以到达85%以上。     

Marker-free method for accurate alignment between correlated light,cryo-light,and electron cryo-microscopy data using sample support features

Combining fluorescence microscopy with electron cryo-tomography allows, in principle, spatial localization of tagged macromolecular assemblies and structural features within the cellular environment. To allow precise localization and scale integration between the two disparate imaging modalities, accurate alignment procedures are needed. Here, we describe a marker-free method for aligning images from light or cryo-light fluorescence microscopy and from electron cryo-microscopy that takes advantage of sample support features, namely the holes in the carbon film. We find that the accuracy of this method, as judged by prediction errors of the hole center coordinates, is better than 100?nm.     

A new method for alignment of LC-MALDI-TOF data

Background

In proteomics studies, liquid chromatography coupled to mass spectrometry (LC-MS) has proven to be a powerful technology to investigate differential expression of proteins/peptides that are characterized by their peak intensities, mass-to-charge ratio (m/z), and retention time (RT). The variable complexity of peptide mixtures and occasional drifts lead to substantial variations in m/z and RT dimensions. Thus, label-free differential protein expression studies by LC-MS technology require alignment with respect to both RT and m/z to ensure that same proteins/peptides are compared from multiple runs.

Methods

In this study, we propose a new strategy to align LC-MALDI-TOF data by combining quality threshold cluster analysis and support vector regression. Our method performs alignment on the basis of measurements in three dimensions (RT, m/z, intensity).

Results and conclusions

We demonstrate the suitability of our proposed method for alignment of LC-MALDI-TOF data through a previously published spike-in dataset and a new in-house generated spike-in dataset. A comparison of our method with other methods that utilize only RT and m/z dimensions reveals that the use of intensity measurements enhances alignment performance.

     

LC-MS method for screening unknown microbial carotenoids and isoprenoid quinones

The structure of secondary metabolites from microorganisms provides a useful tool for microbial characterization and chemotaxonomic classification. Microbial isoprenoid quinones, for example, are well described and used to distinguish among photosynthetic microorganism groups. In addition, isoprenoid quinones can also be found, together with carotenoids, in non-photosynthetic microorganisms. The aim of the present study was to develop a LC-MS/MS method which can analyze and identify these microbial isoprenoids.Positive atmospheric pressure chemical ionization (APCI) together with collisionally induced dissociation was applied for generation of informative fragment spectra by mass spectrometry. Enhanced product ion (EPI) scan in a linear ion trap with information dependent data acquisition (IDA) enabled generation of MS fragment data even from minor isoprenoids. The developed liquid chromatography method enabled separation of isoprenoid patterns from their ester derivatives. Discovery and structural characterization of isoprenoid quinones and carotenoids were carried out by comparing characteristics of fragment spectra from unknown compounds with fragment spectra of a range of isoprenoid standard compounds and using published data. Throughout the study 17 microorganisms (e.g., Acremonium butyri, Arthrobacter spp., Brevibacterium linens, Bullera variabilis, Exophiala dermatitidis, Lecythophora hoffmannii, Panthoea agglomerans, Rhodotorula spp., Xanthophyllomyces dendrorhous) were screened and probable structures of isoprenoid quinones and carotenoids were suggested. The method lays some foundations on the analysis of yet unknown isoprenoids in microorganisms by using LCMS/MS techniques.     

A high-throughput processing service for retention time alignment of complex proteomics and metabolomics LC-MS data

Warp2D is a novel time alignment approach, which uses the overlapping peak volume of the reference and sample peak lists to correct misleading peak shifts. Here, we present an easy-to-use web interface for high-throughput Warp2D batch processing time alignment service using the Dutch Life Science Grid, reducing processing time from days to hours. This service provides the warping function, the sample chromatogram peak list with adjusted retention times and normalized quality scores based on the sum of overlapping peak volume of all peaks. Heat maps before and after time alignment are created from the arithmetic mean of the sum of overlapping peak area rearranged with hierarchical clustering, allowing the quality control of the time alignment procedure. Taverna workflow and command line tool are provided for remote processing of local user data. AVAILABILITY: online data processing service is available at http://www.nbpp.nl/warp2d.html. Taverna workflow is available at myExperiment with title '2D Time Alignment-Webservice and Workflow' at http://www.myexperiment.org/workflows/1283.html. Command line tool is available at http://www.nbpp.nl/Warp2D_commandline.zip. CONTACT: p.l.horvatovich@rug.nl SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

SFESA: a web server for pairwise alignment refinement by secondary structure shifts

Background

Protein sequence alignment is essential for a variety of tasks such as homology modeling and active site prediction. Alignment errors remain the main cause of low-quality structure models. A bioinformatics tool to refine alignments is needed to make protein alignments more accurate.

Results

We developed the SFESA web server to refine pairwise protein sequence alignments. Compared to the previous version of SFESA, which required a set of 3D coordinates for a protein, the new server will search a sequence database for the closest homolog with an available 3D structure to be used as a template. For each alignment block defined by secondary structure elements in the template, SFESA evaluates alignment variants generated by local shifts and selects the best-scoring alignment variant. A scoring function that combines the sequence score of profile-profile comparison and the structure score of template-derived contact energy is used for evaluation of alignments. PROMALS pairwise alignments refined by SFESA are more accurate than those produced by current advanced alignment methods such as HHpred and CNFpred. In addition, SFESA also improves alignments generated by other software.

Conclusions

SFESA is a web-based tool for alignment refinement, designed for researchers to compute, refine, and evaluate pairwise alignments with a combined sequence and structure scoring of alignment blocks. To our knowledge, the SFESA web server is the only tool that refines alignments by evaluating local shifts of secondary structure elements. The SFESA web server is available at http://prodata.swmed.edu/sfesa.     

A multiple regression method for analysing stage-frequency data

A linear regression method that allows survival rates to vary from stage to stage is described for the analysis of stage-frequency data. It has advantages over previously suggested methods since the calculations are not iterative, and it is not necessary to have independent estimates of stage durations, numbers entering stages, or the rate of entry to stage 1. Simulation is proposed to determine standard errors for estimates of population parameters, and to assess the goodness of fit of models.     

Island method for estimating the statistical significance of profile-profile alignment scores

Background  

In the last decade, a significant improvement in detecting remote similarity between protein sequences has been made by utilizing alignment profiles in place of amino-acid strings. Unfortunately, no analytical theory is available for estimating the significance of a gapped alignment of two profiles. Many experiments suggest that the distribution of local profile-profile alignment scores is of the Gumbel form. However, estimating distribution parameters by random simulations turns out to be computationally very expensive.     

A new statistical method for haplotype reconstruction from population data

Current routine genotyping methods typically do not provide haplotype information, which is essential for many analyses of fine-scale molecular-genetics data. Haplotypes can be obtained, at considerable cost, experimentally or (partially) through genotyping of additional family members. Alternatively, a statistical method can be used to infer phase and to reconstruct haplotypes. We present a new statistical method, applicable to genotype data at linked loci from a population sample, that improves substantially on current algorithms; often, error rates are reduced by > 50%, relative to its nearest competitor. Furthermore, our algorithm performs well in absolute terms, suggesting that reconstructing haplotypes experimentally or by genotyping additional family members may be an inefficient use of resources.     

A method of estimating varietal stability for data of long-term trials

Summary A method is proposed to analyze the stability of cultivars in long-term varietal trials. The method involves the following steps: (i) regress a standard variety on environmental means; (ii) regress varieties under test on the standard variety; (iii) transform, through a procedure of reparameterization, the regression computed for each variety under test on the standard variety into the regression of the variety on environmental means. Although this method is proposed to analyze data sets from complex designs, it may also possess some advantages over conventional procedures for simpler designs.     

Development of an LC-MS/MS method for the simultaneous quantification of aripiprazole and dehydroaripiprazole in human plasma

A selective, sensitive, and accurate liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for the simultaneous determination of aripiprazole and its active metabolite dehydroaripiprazole in human plasma has been developed using papaverine as internal standard (IS). LC-MS/MS analysis was carried out on a Finnigan LC-TSQ Quantum mass spectrometer using positive ion electrospray ionization (ESI⁺) and selected reaction monitoring (SRM). The assays for aripiprazole and dehydroaripiprazole were linear over the ranges of 0.1 to 600 ng/ml and 0.01 to 60 ng/ml, respectively. The average recoveries in plasma samples both were better than 85%. The intra- and interrun precision and accuracy values were found to be within the assay variability criteria limits according to the US Food and Drug Administration guidelines. The developed method was proved to be suitable for use in a clinical pharmacokinetic study after a single oral administration of a 5-mg aripiprazole tablet in healthy Chinese volunteers.     

An LC-MS/MS method for determination of forsythiaside in rat plasma and application to a pharmacokinetic study

A highly sensitive liquid chromatography-tandem mass spectrometric (LC-MS/MS) method was developed for the determination of forsythiaside in rat plasma using epicatechin as internal standard. The analytes were extracted by solid-phase extraction and chromatographied on a C₁₈ column eluted with a gradient mobile phase of acetonitrile and water both containing 0.2% formic acid. The detection was performed by negative ion electrospray ionization in multiple reaction monitoring mode, monitoring the transitions m/z 623 → 161 and m/z 289 → 109 for forsythiaside and epicatechin, respectively. The assay was linear over the concentration ranges of 2.0–50.0 and 50.0–5000.0 ng/mL with limits of detection and quantification of 0.2 and 1.0 ng/mL, respectively. The precision was <10.8% and the accuracy was >91.9%, and extraction recovery ranged from 81.3% to 85.0%. This method was successfully applied to a pharmacokinetic study of forsythiaside in rats after intravenous (20 mg/kg) and oral (100 mg/kg) administration, and the result showed that the compound was poorly absorbed with an absolute bioavailability being approximately 0.5%.     

A statistical method for predicting classical HLA alleles from SNP data

Genetic variation at classical HLA alleles is a crucial determinant of transplant success and susceptibility to a large number of infectious and autoimmune diseases. However, large-scale studies involving classical type I and type II HLA alleles might be limited by the cost of allele-typing technologies. Although recent studies have shown that some common HLA alleles can be tagged with small numbers of markers, SNP-based tagging does not offer a complete solution to predicting HLA alleles. We have developed a new statistical methodology to use SNP variation within the region to predict alleles at key class I (HLA-A, HLA-B, and HLA-C) and class II (HLA-DRB1, HLA-DQA1, and HLA-DQB1) loci. Our results indicate that a single panel of approximately 100 SNPs typed across the region is sufficient for predicting both rare and common HLA alleles with up to 95% accuracy in both African and non-African populations. Furthermore, we show that HLA alleles can be successfully predicted by using previously genotyped SNPs that are within the MHC and that had not been chosen for their ability to predict HLA alleles, such as those included on genome-wide products. These results indicate that our methodology, combined with an extended database of reference haplotypes, will facilitate large-scale experiments, including disease-association studies and vaccine trials, in which detailed information about HLA type is valuable.     

A statistical test for differences in sexual dimorphism between populations

Many studies involve comparison of measures of sexual dimorphism between two samples. This comparison is used to test a variety of hypotheses, such as changing environmental conditions. Methods for testing the significance of the difference between two populations tend to be complex, and/or require access to complete original data. We offer a simplified approach which is based on a linear regression model using dummy variables. Our method is computationally simple and can be used with summary statistics (sample size, means, standard deviations) instead of raw data. We present three examples of the application of our method to problems in physical anthropology. We also note that our method has a broader range of applications apart from that of sexual dimorphism.     

Synthesis,spectroscopic and chromatographic studies of sunflower oil biodiesel using optimized base catalyzed methanolysis

Methyl esters from vegetable oils have attracted a great deal of interest as substitute for petrodiesel to reduce dependence on imported petroleum and provide an alternate and sustainable source for fuel with more benign environmental properties. In the present study biodiesel was prepared from sunflower seed oil by transesterification by alkali-catalyzed methanolysis. The fuel properties of sunflower oil biodiesel were determined and discussed in the light of ASTM D6751 standards for biodiesel. The sunflower oil biodiesel was chemically characterized with analytical techniques like FT-IR, and NMR (¹H and ¹³C). The chemical composition of sunflower oil biodiesel was determined by GC–MS. Various fatty acid methyl esters (FAMEs) were identified by retention time data and verified by mass fragmentation patterns. The percentage conversion of triglycerides to the corresponding methyl esters determined by ¹H NMR was 87.33% which was quite in good agreement with the practically observed yield of 85.1%.     

A context dependent pair hidden Markov model for statistical alignment

This article proposes a novel approach to statistical alignment of nucleotide sequences by introducing a context dependent structure on the substitution process in the underlying evolutionary model. We propose to estimate alignments and context dependent mutation rates relying on the observation of two homologous sequences. The procedure is based on a generalized pair-hidden Markov structure, where conditional on the alignment path, the nucleotide sequences follow a Markov distribution. We use a stochastic approximation expectation maximization (saem) algorithm to give accurate estimators of parameters and alignments. We provide results both on simulated data and vertebrate genomes, which are known to have a high mutation rate from CG dinucleotide. In particular, we establish that the method improves the accuracy of the alignment of a human pseudogene and its functional gene.     

Enantioselective LC-MS/MS method for the determination of cloperastine enantiomers in rat plasma and its pharmacokinetic application

Cloperastine is a central antitussive used to reduce the frequency and intensity of coughing on a short-term basis. In this study, a reliable chiral LC-MS/MS technology has been developed for the quantification of cloperastine enantiomers in the rat plasma. Carbinoxamine was selected as the internal standard. The enantioseparation of cloperastine was performed on a Chiralpak IA column with a mobile phase composed of acetonitrile-water-ammonium hydroxide (80:20:0.1, v/v/v) at a flow rate of 0.6 mL/min. Cloperastine enantiomers were detected by mass spectrometry in multiple reaction monitoring mode with a positive electrospray ionization source. The method was validated over the linear concentration range of 0.05 to 10.0 ng/mL (5.0 × 10⁻⁴ ng to 0.10 ng) for both enantiomers. The lower limit of quantification (LLOQ) for each analyte was determined as 0.05 ng/mL. The relative standard deviations (RSDs) of intraday and interday precision was less than 13.9%, and the relative error (RE) of accuracy ranged from −5.4% to 6.1%, which were within the acceptance criteria. Finally, an application to the stereoselective pharmacokinetics of cloperastine in rats was successfully realized in our assay. The developed method on a commercially available Chiralpak IA column under isocratic mobile phase is advantageous to analyze cloperastine enantiomers in plasma samples collected for enantioselective metabolism or drug interaction studies.