Early infancy microbial and metabolic alterations affect risk of childhood asthma

Metabolomics is a newly emerging field of ‘omics’ research that is concerned with characterizing large numbers of metabolites using NMR, chromatography and mass spectrometry. It is frequently used in biomarker identification and the metabolic profiling of cells, tissues or organisms. The data processing challenges in metabolomics are quite unique and often require specialized (or expensive) data analysis software and a detailed knowledge of cheminformatics, bioinformatics and statistics. In an effort to simplify metabolomic data analysis while at the same time improving user accessibility, we have developed a freely accessible, easy-to-use web server for metabolomic data analysis called MetaboAnalyst. Fundamentally, MetaboAnalyst is a web-based metabolomic data processing tool not unlike many of today's web-based microarray analysis packages. It accepts a variety of input data (NMR peak lists, binned spectra, MS peak lists, compound/concentration data) in a wide variety of formats. It also offers a number of options for metabolomic data processing, data normalization, multivariate statistical analysis, graphing, metabolite identification and pathway mapping. In particular, MetaboAnalyst supports such techniques as: fold change analysis, t-tests, PCA, PLS-DA, hierarchical clustering and a number of more sophisticated statistical or machine learning methods. It also employs a large library of reference spectra to facilitate compound identification from most kinds of input spectra. MetaboAnalyst guides users through a step-by-step analysis pipeline using a variety of menus, information hyperlinks and check boxes. Upon completion, the server generates a detailed report describing each method used, embedded with graphical and tabular outputs. MetaboAnalyst is capable of handling most kinds of metabolomic data and was designed to perform most of the common kinds of metabolomic data analyses. MetaboAnalyst is accessible at http://www.metaboanalyst.ca

First released in 2009, MetaboAnalyst (www.metaboanalyst.ca) was a relatively simple web server designed to facilitate metabolomic data processing and statistical analysis. With continuing advances in metabolomics along with constant user feedback, it became clear that a substantial upgrade to the original server was necessary. MetaboAnalyst 2.0, which is the successor to MetaboAnalyst, represents just such an upgrade. MetaboAnalyst 2.0 now contains dozens of new features and functions including new procedures for data filtering, data editing and data normalization. It also supports multi-group data analysis, two-factor analysis as well as time-series data analysis. These new functions have also been supplemented with: (i) a quality-control module that allows users to evaluate their data quality before conducting any analysis, (ii) a functional enrichment analysis module that allows users to identify biologically meaningful patterns using metabolite set enrichment analysis and (iii) a metabolic pathway analysis module that allows users to perform pathway analysis and visualization for 15 different model organisms. In developing MetaboAnalyst 2.0 we have also substantially improved its graphical presentation tools. All images are now generated using anti-aliasing and are available over a range of resolutions, sizes and formats (PNG, TIFF, PDF, PostScript, or SVG). To improve its performance, MetaboAnalyst 2.0 is now hosted on a much more powerful server with substantially modified code to take advantage the server’s multi-core CPUs for computationally intensive tasks. MetaboAnalyst 2.0 also maintains a collection of 50 or more FAQs and more than a dozen tutorials compiled from user queries and requests. A downloadable version of MetaboAnalyst 2.0, along detailed instructions for local installation is now available as well.

Low total diversity of the gut microbiota during the first year of life is associated with allergic diseases in infancy, but little is known how early microbial diversity is related to allergic disease later in school age. To assess microbial diversity and characterize the dominant bacteria in stool during the first year of life in relation to the prevalence of different allergic diseases in school age, such as asthma, allergic rhinoconjunctivitis (ARC) and eczema. The microbial diversity and composition was analysed with barcoded 16S rDNA 454 pyrosequencing in stool samples at 1 week, 1 month and 12 months of age in 47 infants which were subsequently assessed for allergic disease and skin prick test reactivity at 7 years of age (ClinicalTrials.gov ID NCT01285830). Children developing asthma (n = 8) had a lower diversity of the total microbiota than non-asthmatic children at 1 week (P = 0.04) and 1 month (P = 0.003) of age, whereas allergic rhinoconjunctivitis (n = 13), eczema (n = 12) and positive skin prick reactivity (n = 14) at 7 years of age did not associate with the gut microbiota diversity. Neither was asthma associated with the microbiota composition later in infancy (at 12 months). Children having IgE-associated eczema in infancy and subsequently developing asthma had lower microbial diversity than those that did not. There were no significant differences, however, in relative abundance of bacterial phyla and genera between children with or without allergic disease. Low total diversity of the gut microbiota during the first month of life was associated with asthma but not ARC in children at 7 years of age. Measures affecting microbial colonization of the infant during the first month of life may impact asthma development in childhood. © 2013 John Wiley & Sons Ltd.