Accurate metabolite identification remains one of the primary challenges in a metabolomics study. A reliable chemical spectral library increases the confidence in annotation, and the availability of raw and annotated data in public databases facilitates the transfer of Liquid chromatography coupled to mass spectrometry (LC–MS) methods across laboratories. Here, we illustrate how the combination of MS2 spectra, accurate mass, and retention time can improve the confidence of annotation and provide techniques to create a reliable library for all ion fragmentation (AIF) data with a focus on the characterization of the retention time. The resulting spectral library incorporates information on adducts and in-source fragmentation in AIF data, while noise peaks are effectively minimized through multiple deconvolution processes. We also report the development of the Mass Spectral LIbrary MAnager (MS-LIMA) tool to accelerate library sharing and transfer across laboratories. This library construction strategy improves the confidence in annotation for AIF data in LC–MS-based metabolomics and will facilitate the sharing of retention time and mass spectral data in the metabolomics community.

To the Editor: We formulated mass spectral fragmentations of lipids across 117 lipid subclasses and included ion mobility tandem mass spectrometry (MS/MS) to provide a comprehensive lipidome atlas with retention time, collision cross section, and MS/MS information. The all-in-one solution from import of raw MS data to export of a common output format (mztab-M) was packaged in MS-DIAL 4 ( http://prime.psc.riken.jp/ ) providing an enhanced standardized untargeted lipidomics procedure following lipidomics standards initiative (LSI) semi-quantitative definitions and shorthand notation system of lipid structures with a 1–2% estimated false discovery rate, which will contribute to harmonizing lipidomics data across laboratories to accelerate lipids research.

Background: Genomes are subjected to rearrangements that change the orientation and ordering of genes during evolution. The most common rearrangements that occur in uni-chromosomal genomes are inversions (or reversals) to adapt to the changing environment. Since genome rearrangements are rarer than point mutations, gene order with sequence data can facilitate more robust phylogenetic reconstruction. Helicobacter pylori is a good model because of its unique evolution in niche environment. Results: We have developed a method to identify genome rearrangements by comparing almost-conserved genes among closely related strains. Orthologous gene clusters, rather than the gene sequences, are used to align the gene order so that comparison of large number of genomes becomes easier. Comparison of 72 Helicobacter pylori strains revealed shared as well as strain-specific reversals, some of which were found in different geographical locations. Conclusion: Degree of genome rearrangements increases with time. Therefore, gene orders can be used to study the evolutionary relationship among species and strains. Multiple genome comparison helps to identify the strain-specific as well as shared reversals. Identification of the time course of rearrangements can provide insights into evolutionary events.

Standard graphical tools for whole genome comparison require a reference genome. However, any reference is also subject to annotation biases and rearrangements, and may not serve as the standard except for those of extensively studied model species. To fully exploit the rapidly accumulating sequence data from the recent sequencing technologies, genome comparison without any reference has been anticipated. We introduce a circular genome visualizer to compare complete genomes of closely related species. This tool visualizes the position of orthologous gene clusters rather than actual sequences or their features, thereby achieving the comparative view without using a single reference genome. The essential information is the matrix of orthologous gene clusters whose positions (not sequences) are color-coded in circular graphics. As a demonstration, comparison of 14 Lactobacillus paracasei strains and one L. casei strain revealed not only large-scale rearrangements but also genomic islands that are strain-specific. Comparison of 73 Helicobacter pylori strains confirmed their genetic consistency and also revealed the three general patterns of large-scale genome inversions. From the ample sequence information in the GenBank/ENA/DDBJ repository, we can reconstruct a genomic consensus for particular species. By visualizing multiple strains at a glance, we can identify conserved as well as strain-specific regions in multiply sequenced genomes. Positional consistency for orthologous genes provides information orthogonal to major sequence features such as the GC content or sequence similarity of marker genes. The positional comparison is therefore useful for identifying large-scale genome rearrangements or gene transfers.

The draft genome sequence of Lactobacillus paracasei strain LC-Ikematsu, isolated from a pineapple in Okinawa, was determined. The total length of the 87 contigs was 3.08 Mb with a G+C content of 46.2% and 2,946 coding sequences. The genome analysis revealed its biosynthetic ability of 11 amino acids.