Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils.

Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allow the elucidation of the main metabolic processes that determine the performance of microbial communities under different environmental conditions and perturbations. Here we present the first compartmentalized metabolic reconstruction at a metagenomics scale of a microbial ecosystem. This systematic approach conceives a meta-organism without boundaries between individual organisms and allows the in silico evaluation of the effect of agricultural intervention on soils at a metagenomics level. To characterize the microbial ecosystems, topological properties, taxonomic and metabolic profiles, as well as a Flux Balance Analysis (FBA) were considered. Furthermore, topological and optimization algorithms were implemented to carry out the curation of the models, to ensure the continuity of the fluxes between the metabolic pathways, and to confirm the metabolite exchange between subcellular compartments. The proposed models provide specific information about ecosystems that are generally overlooked in non-compartmentalized or non-curated networks, like the influence of transport reactions in the metabolic processes, especially the important effect on mitochondrial processes, as well as provide more accurate results of the fluxes used to optimize the metabolic processes within the microbial community.

Major Novel QTL for Resistance to Cassava Bacterial Blight Identified through a Multi-Environmental Analysis.

Cassava, Manihot esculenta Crantz, has been positioned as one of the most promising crops world-wide representing the staple security for more than one billion people mainly in poor countries. Cassava production is constantly threatened by several diseases, including cassava bacterial blight (CBB) caused by Xanthomonas axonopodis pv. manihotis (Xam), it is the most destructive disease causing heavy yield losses. Here, we report the detection and localization on the genetic map of cassava QTL (Quantitative Trait Loci) conferring resistance to CBB. An F1 mapping population of 117 full sibs was tested for resistance to two Xam strains (Xam318 and Xam681) at two locations in Colombia: La Vega, Cundinamarca and Arauca. The evaluation was conducted in rainy and dry seasons and additional tests were carried out under controlled greenhouse conditions. The phenotypic evaluation of the response to Xam revealed continuous variation. Based on composite interval mapping analysis, 5 strain-specific QTL for resistance to Xam explaining between 15.8 and 22.1% of phenotypic variance, were detected and localized on a high resolution SNP-based genetic map of cassava. Four of them show stability among the two evaluated seasons. Genotype by environment analysis detected three QTL by environment interactions and the broad sense heritability for Xam318 and Xam681 were 20 and 53%, respectively. DNA sequence analysis of the QTL intervals revealed 29 candidate defense-related genes (CDRGs), and two of them contain domains related to plant immunity proteins, such as NB-ARC-LRR and WRKY.

RNAseq analysis of cassava reveals similar plant responses upon infection with pathogenic and non-pathogenic strains of Xanthomonas axonopodis pv. manihotis.

KEY MESSAGE: An RNAseq-based analysis of the cassava plants inoculated with Xam allowed the identification of transcriptional upregulation of genes involved in jasmonate metabolism, phenylpropanoid biosynthesis and putative targets for a TALE. Cassava bacterial blight, a disease caused by the gram-negative bacterium Xanthomonas axonopodis pv. manihotis (Xam), is a major limitation to cassava production worldwide and especially in developing countries. The molecular mechanisms underlying cassava susceptibility to Xam are currently unknown. To identify host genes and pathways leading to plant susceptibility, we analyzed the transcriptomic responses occurring in cassava plants challenged with either the non-pathogenic Xam strain ORST4, or strain ORST4(TALE1 Xam ) which is pathogenic due to the major virulence transcription activator like effector TALE1 Xam . Both strains triggered similar responses, i.e., induction of genes related to photosynthesis and phenylpropanoid biosynthesis, and repression of genes related to jasmonic acid signaling. Finally, to search for TALE1 Xam virulence targets, we scanned the list of cassava genes induced upon inoculation of ORST4(TALE1 Xam ) for candidates harboring a predicted TALE1 Xam effector binding element in their promoter. Among the six genes identified as potential candidate targets of TALE1 Xam a gene coding for a heat shock transcription factor stands out as the best candidate based on their induction in presence of TALE1 Xam and contain a sequence putatively recognized by TALE1 Xam .