Motivation: The increasing availability of metabolomics data enables to better understand the metabolic processes involved in the immediate response of an organism to environmental changes and stress. The data usually come in the form of a list of metabolites whose concentrations significantly changed under some conditions, and are thus not easy to interpret without being able to precisely visualize how such metabolites are interconnected.
Results: We present a method that enables to organize the data from any metabolomics experiment into metabolic stories.
PLoS One
September 2013
Endosymbiont-bearing trypanosomatids have been considered excellent models for the study of cell evolution because the host protozoan co-evolves with an intracellular bacterium in a mutualistic relationship. Such protozoa inhabit a single invertebrate host during their entire life cycle and exhibit special characteristics that group them in a particular phylogenetic cluster of the Trypanosomatidae family, thus classified as monoxenics. In an effort to better understand such symbiotic association, we used DNA pyrosequencing and a reference-guided assembly to generate reads that predicted 16,960 and 12,162 open reading frames (ORFs) in two symbiont-bearing trypanosomatids, Angomonas deanei (previously named as Crithidia deanei) and Strigomonas culicis (first known as Blastocrithidia culicis), respectively.
View Article and Find Full Text PDFBackground: A large number of genome-scale metabolic networks is now available for many organisms, mostly bacteria. Previous works on minimal gene sets, when analysing host-dependent bacteria, found small common sets of metabolic genes. When such analyses are restricted to bacteria with similar lifestyles, larger portions of metabolism are expected to be shared and their composition is worth investigating.
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