KEGGconverter: a tool for the in-silico modelling of metabolic networks of the KEGG Pathways database

Background  

The KEGG Pathway database is a valuable collection of metabolic pathway maps. Nevertheless, the production of simulation capable metabolic networks from KEGG Pathway data is a challenging complicated work, regardless the already developed tools for this scope. Originally used for illustration purposes, KEGG Pathways through KGML (KEGG Markup Language) files, can provide complete reaction sets and introduce species versioning, which offers advantages for the scope of cellular metabolism simulation modelling. In this project, KEGGconverter is described, implemented also as a web-based application, which uses as source KGML files, in order to construct integrated pathway SBML models fully functional for simulation purposes.     

Clustering of Mycobacterium avium subsp. paratuberculosis in Rabbits and the Environment: How Hot Is a Hot Spot?

Clustering of pathogens in the environment leads to hot spots of diseases at local, regional, national, and international levels. Scotland contains regional hot spots of Johne's disease (caused by Mycobacterium avium subsp. paratuberculosis) in rabbits, and there is increasing evidence of a link between paratuberculosis infections in rabbits and cattle. The spatial and temporal dynamics of paratuberculosis in rabbits within a hot spot region were studied with the overall aim of determining environmental patterns of infection and thus the risk of interspecies transmission to livestock. The specific aims were to determine if prevalence of paratuberculosis in rabbits varies temporally between seasons and whether the heterogeneous spatial environmental distribution of M. avium subsp. paratuberculosis on a large scale (i.e., regional hot spots) is replicated at finer resolutions within a hot spot. The overall prevalence of M. avium subsp. paratuberculosis in rabbits was 39.7%; the temporal distribution of infection in rabbits followed a cyclical pattern, with a peak in spring of 55.4% and a low in summer of 19.4%. Spatially, M. avium subsp. paratuberculosis-infected rabbits and, thus, the risk of interspecies transmission were highly clustered in the environment. However, this is mostly due to the clustered distribution of rabbits. The patterns of M. avium subsp. paratuberculosis infection in rabbits are discussed in relation to the host's socioecology and risk to livestock.     

Hormone-induced protection of sunflower photosynthetic apparatus against copper toxicity

The effects of excess Cu as affected by the application of exogenous hormones (gibberellic acid - GA₃ and indole-3-acetic acid - IAA) with respect to sunflower (Helianthus annuus L.) growth, physiology, and metabolism were studied. Application of 100 M IAA lessened the toxic effects of 80 M Cu in roots indicating greater root length and root hair formation, while addition of 100 M GA₃ ameliorated the toxic effect mainly to the shoot. The content of photosynthetic pigments significantly declined under Cu stress, whereas application of hormones led to a substantial preservation of chlorophylls and carotenoids. Under Cu stress, the rate constant of energy trapping by photosystem 2 (PS2) reaction centres (RCs) was reduced as a result of physical dissociation of the light-harvesting complex (LHC) from PS2 core, while application of IAA and especially GA₃ resulted in stability of the LHC of PS2 RCs. The drop in net photosynthetic (PN) and transpiration (E) rates with preserved or slightly reduced variable to maximum fluorescence ratio (F_v/F_m) in the presence of 80 M Cu could be explained by a possible inhibition of the enzymatic processes in the Calvin cycle. Application of 100 M IAA and 100 M GA₃ lessened Cu effects mainly on P _N. Water use efficiency was also improved under hormone exposure.     

MiMiC: a bioinformatic approach for generation of synthetic communities from metagenomes

Environmental and host-associated microbial communities are complex ecosystems, of which many members are still unknown. Hence, it is challenging to study community dynamics and important to create model systems of reduced complexity that mimic major community functions. Therefore, we developed MiMiC, a computational approach for data-driven design of simplified communities from shotgun metagenomes. We first built a comprehensive database of species-level bacterial and archaeal genomes (n = 22 627) consisting of binary (presence/absence) vectors of protein families (Pfam = 17 929). MiMiC predicts the composition of minimal consortia using an iterative scoring system based on maximal match-to-mismatch ratios between this database and the Pfam binary vector of any input metagenome. Pfam vectorization retained enough resolution to distinguish metagenomic profiles between six environmental and host-derived microbial communities (n = 937). The calculated number of species per minimal community ranged between 5 and 11, with MiMiC selected communities better recapitulating the functional repertoire of the original samples than randomly selected species. The inferred minimal communities retained habitat-specific features and were substantially different from communities consisting of most abundant members. The use of a mixture of known microbes revealed the ability to select 23 of 25 target species from the entire genome database. MiMiC is open source and available at https://github.com/ClavelLab/MiMiC .