Library search of mass spectra with a new matching algorithm based on substructure similarity

Strategies for structure elucidation of small molecules based on LC–MS/MS data from complex biological samples

LC–MS/MS is a major analytical platform for metabolomics, which has become a recent hotspot in the research fields of life and environmental sciences. By contrast, structure elucidation of small molecules based on LC–MS/MS data remains a major challenge in the chemical and biological interpretation of untargeted metabolomics datasets. In recent years, several strategies for structure elucidation using LC–MS/MS data from complex biological samples have been proposed, these strategies can be simply categorized into two types, one based on structure annotation of mass spectra and for the other on retention time prediction. These strategies have helped many scientists conduct research in metabolite-related fields and are indispensable for the development of future tools. Here, we summarized the characteristics of the current tools and strategies for structure elucidation of small molecules based on LC–MS/MS data, and further discussed the directions and perspectives to improve the power of the tools or strategies for structure elucidation.

Scent emission profiles from Darwin's orchid--Angraecum sesquipedale: Investigation of the aldoxime metabolism using clustering analysis

The display of scent is crucial for plants in attracting pollinating insects to flowers and ensuring successful pollination and reproduction. The large number of aldoxime volatile species present in the scent of the Madagascan orchid Angraecum sesquipedale has been suggested to play a primary role in attracting the sphingid moth Xanthopan morgani praedicta. By solid phase micro-extraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS), we monitored the scent release from different flowers of a single orchid, day and night throughout the entire flowering period. In separate experiments, the diurnal release was monitored in 3h intervals and the tissue specific release from the different floral parts was tracked. Numerous novel compounds related to the aldoxime metabolism not previously detected in A. sesquipedale were identified and positioned into a proposed pathway for aldoxime metabolism. From the results, we hypothesize that (E/Z)-phenylacetaldoxime and its derivatives could be important attractants for the pollinating moth X. morgani praedicta. By applying an untargeted Partitioning Around Medoids (PAM) cluster analysis to the metabolite profiles in the scent, the proposed pathways for the formation of aldoximes were substantiated. With this study, we demonstrate the powerful utility of a bioinformatics tool to aid in the elucidation of the routes of formation for volatiles and provide a benchmark and guidelines for future detailed observations of hawkmoth pollination of Angraecum species, and in particular A. sesquipedale, in the wild.

ARISTO: ontological classification of small molecules by electron ionization-mass spectrometry

Gas chromatography–mass spectrometry (GC–MS) acquisitions routinely yield hundreds to thousands of Electron Ionization (EI) mass spectra. The chemical identification of these spectra typically involves a search protocol that seeks an exact match to a reference spectrum. Reference spectra are found in comprehensive libraries of small molecule EI spectra curated by commercial and public entities. We developed ARISTO (Automatic Reduction of Ion Spectra To Ontology), a webtool, which provides information regarding the general chemical nature of the compound underlying an input EI mass spectrum. Importantly, ARISTO can provide such annotation without necessitating an exact match to a specific compound. ARISTO provides assignments to a subset of the ChEBI (Chemical Entities of Biological Interest) dictionary, an ontology, which aims to cover biologically relevant small molecules. Our system takes as input a mass spectrum represented as a series of mass and intensity pairs; the system returns a graphical representation of the supported ontology as well as a detailed table of suggested annotations along with their associated statistical evidence. ARISTO is accessible at this URL: http://www.ionspectra.org/aristo. The system is free, open to all and does not require registration of any sort.

A component tracking algorithm for accelerated and improved liquid chromatography-mass spectrometry method development

A method for tracking of sample components during liquid chromatography-mass spectrometry (LC-MS) method development has been proposed. The method manages to, fully automatically and without user intervention, find the chromatographic peaks in the data sets, discriminate them to sample components and track them when the separation conditions have been changed. The algorithm utilises the resolution obtained from all considered data sets and has the ability to discriminate the non informative parts. The technique has a great sensitivity even in cases where a majority of the tracked components cannot easily be spotted by means of traditional total ion chromatogram (TIC) or base peak chromatogram (BPC) representations. The method was tested on an experimental sample using six different columns and an average of 79% of the suggested sample components could be successfully tracked at a minimum area of 0.05% of the main component in the sample. 66 components with 79-92% of the total suggested component area were able to be tracked between all data sets. The method could be used to rapidly investigate selectivity during different types of separation conditions.

X-Rank: a robust algorithm for small molecule identification using tandem mass spectrometry

The diversity of experimental workflows involving LC-MS/MS and the extended range of mass spectrometers tend to produce extremely variable spectra. Variability reduces the accuracy of compound identification produced by commonly available software for a spectral library search. We introduce here a new algorithm that successfully matches MS/MS spectra generated by a range of instruments, acquired under different conditions. Our algorithm called X-Rank first sorts peak intensities of a spectrum and second establishes a correlation between two sorted spectra. X-Rank then computes the probability that a rank from an experimental spectrum matches a rank from a reference library spectrum. In a training step, characteristic parameter values are generated for a given data set. We compared the efficiency of the X-Rank algorithm with the dot-product algorithm implemented by MS Search from the National Institute of Standards and Technology (NIST) on two test sets produced with different instruments. Overall the X-Rank algorithm accurately discriminates correct from wrong matches and detects more correct substances than the MS Search. Furthermore, X-Rank could correctly identify and top rank eight chemical compounds in a commercially available test mix. This confirms the ability of the algorithm to perform both a straight single-platform identification and a cross-platform library search in comparison to other tools. It also opens the possibility for efficient general unknown screening (GUS) against large compound libraries.

TargetSearch--a Bioconductor package for the efficient preprocessing of GC-MS metabolite profiling data

Background

Metabolite profiling, the simultaneous quantification of multiple metabolites in an experiment, is becoming increasingly popular, particularly with the rise of systems-level biology. The workhorse in this field is gas-chromatography hyphenated with mass spectrometry (GC-MS). The high-throughput of this technology coupled with a demand for large experiments has led to data pre-processing, i.e. the quantification of metabolites across samples, becoming a major bottleneck. Existing software has several limitations, including restricted maximum sample size, systematic errors and low flexibility. However, the biggest limitation is that the resulting data usually require extensive hand-curation, which is subjective and can typically take several days to weeks.

Results

We introduce the TargetSearch package, an open source tool which is a flexible and accurate method for pre-processing even very large numbers of GC-MS samples within hours. We developed a novel strategy to iteratively correct and update retention time indices for searching and identifying metabolites. The package is written in the R programming language with computationally intensive functions written in C for speed and performance. The package includes a graphical user interface to allow easy use by those unfamiliar with R.

Conclusions

TargetSearch allows fast and accurate data pre-processing for GC-MS experiments and overcomes the sample number limitations and manual curation requirements of existing software. We validate our method by carrying out an analysis against both a set of known chemical standard mixtures and of a biological experiment. In addition we demonstrate its capabilities and speed by comparing it with other GC-MS pre-processing tools. We believe this package will greatly ease current bottlenecks and facilitate the analysis of metabolic profiling data.

A Detailed Mechanistic Fragmentation Analysis of Methamphetamine and Select Regioisomers by GC/MS

A novel ring-substituted methamphetamine regioisomer, N,alpha,4-trimethyl phenmethylamine, was synthesized in order to study the validity of proposed structures for various mass spectrometry (MS)-derived peaks in a methamphetamine fragmentation pattern. While other research efforts have studied aspects of methamphetamine in detail, a full fragmentation study has not been reported previously. In addition to showing molecular structures represented by fragment peaks, mechanisms for selected processes are detailed. An empirically derived procedure to easily determine by simple spectral peak pattern recognition the geometry of dimethyl- or ethyl-substituted immonium ions (RRC = N+ RR) where m/z = 58 is outlined. These results are platform independent for electron ionization (EI) instruments, but have also proven to be helpful in explaining spectral peaks observed in spectra from ion trap systems. The spectrum for the synthesized methamphetamine regioisomer was accurately predicted using this methodology. While this approach is useful in some casework, the converse may be more useful: when an unexpected or unusual peak pattern arises in a spectrum, being able to analyze it to determine the structure of the molecule. This paper gives an analyst the means to begin such retro-synthetic analyses.

MS2Grouper: group assessment and synthetic replacement of duplicate proteomic tandem mass spectra

Shotgun proteomics experiments require the collection of thousands of tandem mass spectra; these sets of data will continue to grow as new instruments become available that can scan at even higher rates. Such data contain substantial amounts of redundancy with spectra from a particular peptide being acquired many times during a single LC-MS/MS experiment. In this article, we present MS2Grouper, an algorithm that detects spectral duplication, assesses groups of related spectra, and replaces these groups with synthetic representative spectra. Errors in detecting spectral similarity are corrected using a paraclique criterion-spectra are only assessed as groups if they are part of a clique of at least three completely interrelated spectra or are subsequently added to such cliques by being similar to all but one of the clique members. A greedy algorithm constructs a representative spectrum for each group by iteratively removing the tallest peaks from the spectral collection and matching to peaks in the other spectra. This strategy is shown to be effective in reducing spectral counts by up to 20% in LC-MS/MS datasets from protein standard mixtures and proteomes, reducing database search times without a concomitant reduction in identified peptides.

Study of Thermal Behavior of Vitamin D3 by Pyrolysis - GC - MS in Combination with Boiling Point - Retention Time Correlation

The thermal behavior of vitamin D3 was studied based on pyrolysis-GC-MS technique. It was pyrolyzed at 600 degrees C, 750 degrees C, 900 degrees C, respectively. The pyrolysis product were separated With an HP-5 column and identified by the NIST mass spectral search program in combination with the correlation of boiling point and retention time (BP-RT). There are totally 50 components, including mono aromatics and polycyclic aromatic hydrocarbons (PAHs), were determined. It is shown that the contents of the PAHs are increasing with the increasing of the pyrolysis temperature. The contents of the determined components vary from 0.04% to 37.08%.