Complex diseases cannot be understood only on the basis of single gene, single mRNA transcript or single protein but the effect of their collaborations. The combination consequence in molecular level can be captured by the alterations of metabolites. With the rapidly developing of biomedical instruments and analytical platforms, a large number of metabolite signatures of complex diseases were identified and documented in the literature. Biologists' hardship in the face of this large amount of papers recorded metabolic signatures of experiments' results calls for an automated data repository. Therefore, we developed MetSigDis aiming to provide a comprehensive resource of metabolite alterations in various diseases. MetSigDis is freely available at http://www.bio-annotation.cn/MetSigDis/. By reviewing hundreds of publications, we collected 6849 curated relationships between 2420 metabolites and 129 diseases across eight species involving Homo sapiens and model organisms. All of these relationships were used in constructing a metabolite disease network (MDN). This network displayed scale-free characteristics according to the degree distribution (power-law distribution with R2 = 0.909), and the subnetwork of MDN for interesting diseases and their related metabolites can be visualized in the Web. The common alterations of metabolites reflect the metabolic similarity of diseases, which is measured using Jaccard index. We observed that metabolite-based similar diseases are inclined to share semantic associations of Disease Ontology. A human disease network was then built, where a node represents a disease, and an edge indicates similarity of pair-wise diseases. The network validated the observation that linked diseases based on metabolites should have more overlapped genes.
WAM‐1 is a cathelicidin antimicrobial peptide found on the Macropus eugenii (Tammar wallaby) genome. It possesses antibiotic activity against a broad spectrum of bacteria and fungi. In order to investigate the impact of this WAM‐1 antimicrobial peptide on development and midgut microbial composition of Plutella xylostella (DBM) larvae, the WAM‐1 was introduced into Arabidopsis thaliana using the Agrobacterium‐mediated floral‐dip transformation method. WAM‐1 expression was confirmed by reverse transcriptase PCR analysis. The larval growth and developmental variations and midgut microbial compositions were analysed after DBM larvae had fed on transgenic plants. Transgenic plant‐fed DBM larvae showed significantly higher mortality, a prolonged developmental period and less weight gain. Enterobacteriaceae was the highest dominating family in all samples including transgenic and non‐transgenic plants fed larvae. However, its abundance was substantially lower in the WAM‐1 Arabidopsis‐fed larvae. Furthermore, Moraxellaceae and Bacillaceae were the next dominating families in the WAM‐1 transgenic Arabidopsis‐fed larvae whereas Enterococcaceae and Xanthomonadaceae were dominant in the non‐transgenic Arabidopsis‐fed larvae. Abundance of Pseudomonadaceae was also relatively higher in WAM‐1 transgenic‐fed larvae whereas it was much lower in other samples. Therefore, our findings suggest that WAM‐1 has an impact on gut microbial composition but a minor effect on larval development.
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