Project description:The biodegradation of lignite (brown coal) by microorganisms has the potential for bioremediation of contaminated mining sites and to generate alternative ways to valorize lignite, such as by producing humic acids or building block chemicals. Previously, a lignite-degrading strain of Trichoderma was isolated, but the genomic and transcriptomic basis of its lignite-degrading ability remained unknown. Here we report that the sequenced genome of the T. cf. simile WF8 strain encoded for enzymes with roles in the degradation of lignite, and potentially tolerance to lignite-breakdown products. There was only a small number of annotated unique genes in the T. cf. simile WF8 genome compared to other fungi, and likely the expression of gene families shared with other fungi is a key factor in lignite biosolubilization by T. cf. simile. The transcriptomes were analyzed of T. cf. simile cultured at two time-points with the lignite-breakdown model compounds 4-phenoxybenzoic acid (which was growth inhibitory), and phenetole and 9-10-dibutoxyanthracene (neither of which inhibited growth), and showed ~20% of genes up-regulated by one or more of these compounds. The analysis highlights candidates for characterization and engineering enzyme over-expressing T. cf. simile strains with potentially improved degradation capacity, e.g., laccases and peroxidases, or tolerance and catabolism of breakdown products, e.g., cytochrome P450s, and ring cleavage dioxygenases.
Project description:Here we present the first characterisation of small RNAs in honey bee reproductive tissues. We conclude that small RNAs are likely to play an integral role in honey bee gametogenesis and reproduction and provide a plausible mechanism for parent-of origin-effects on gene expression and reproductive physiology. present in honey bee reproductive tissues: ovaries, spermatheca, semen, fertilised and unfertilised eggs, and testes.
Project description:Interrelating small molecules according to their aligned fragmentation spectra is central to tandem mass spectrometry-based untargeted metabolomics. Current alignment algorithms do not provide statistical significance and compounds that have multiple delocalized structural differences and therefore often fail to have their fragment ions aligned. Here we align fragmentation spectra with both statistical significance and allowance for multiple chemical differences using Significant Interrelation of MS/MS Ions via Laplacian Embedding (SIMILE). SIMILE yields spectral alignment inferred structural connections in molecular networks that are not found with cosine-based scoring algorithms. In addition, it is now possible to rank spectral alignments based on p-values in the exploration of structural relationships between compounds and enhance the chemical connectivity that can be obtained with molecular networking.