Silvia Restrepo

Gene expression profile in response to Xanthomonas axonopodis pv. manihotis infection in cassava using a cDNA microarray.

A cassava cDNA microarray based on a large cassava EST database was constructed and used to study the incompatible interaction between cassava and Xanthomonas axonopodis pv. manihotis (Xam) strain CIO151. For microarray construction, 5700 clones from the cassava unigene set were amplified by polymerase chain reaction (PCR) and printed on glass slides. Microarray hybridization was performed using cDNA from cassava plants (resistant variety MBra685) collected at 12, 24, 48xa0h and 7 and 15xa0days post-infection as treatment and cDNA from mock-inoculated plants as control. A total of 199 genes were found to be differentially expressed (126 up-regulated and 73 down-regulated). A greater proportion of differentially-expressed genes was observed at 7xa0days after inoculation. Expression profiling and cluster analyses indicate that, in response to inoculation with Xam, cassava induces dozens of genes, including principally those involved in oxidative burst, protein degradation and pathogenesis-related (PR) genes. In contrast, genes encoding proteins that are involved in photosynthesis and metabolism were down regulated. In addition, various other genes encoding proteins with unknown function or showing no similarity to other proteins were also induced. Quantitative real time PCR experiments confirmed the reliability of our microarray data. In addition we showed that some genes are induced more rapidly in the resistant than in the susceptible cultivar.

A unigene catalogue of 5700 expressed genes in cassava

Two economically important characters, starch content and cassava bacterial blight resistance, were targeted to generate a large collection of cassava ESTs. Two libraries were constructed from cassava root tissues of varieties with high and low starch contents. Other libraries were constructed from plant tissues challenged by the pathogen Xanthomonas axonopodis pv.manihotis. We report here the single pass sequencing of 11 954 cDNA clones from the 5’ ends, including 111 from the 3’ ends. Cluster analysis permitted the identification of a unigene set of 5700 sequences. Sequence analyses permitted the assignment of a putative functional category for 37% of sequences whereas ~ 16% sequences did not show any significant similarity with other proteins present in the database and therefore can be considered as cassava specific genes. A group of genes belonging to a large multigene family was identified. We characterize a set of genes detected only in infected libraries putatively involved in the defense response to pathogen infection. By comparing two libraries obtained from cultivars contrasting in their starch content a group of genes associated to starch biosynthesis and differentially expressed was identified. This is the first large cassava EST resource developed today and publicly available thus making a significant contribution to genomic knowledge of cassava.

AFLP fingerprinting : An efficient technique for detecting genetic variation of Xanthomonas axonopodis pv. manihotis

Xanthomonas axonopodis pv. manihotis (Xam) is the causative agent of cassava bacterial blight (CBB), a worldwide disease that is particularly destructive in South America and Africa. CBB is controlled essentially through the use of resistant varieties. To develop an appropriate disease management strategy, the genetic diversity of the pathogens populations must be assessed. Until now, the genetic diversity of Xam was characterized by RFLP analyses using ribotyping, and plasmid and genomic Xam probes. We used AFLP (amplified fragment length polymorphism), a novel PCR-based technique, to characterize the genetic diversity of Colombian Xam isolates. Six Xam strains were tested with 65 AFLP primer combinations to identify the best selective primers. Eight primer combinations were selected according to their reproducibility, number of polymorphic bands and polymorphism detected between Xam strains. Forty-seven Xam strains, originating from different Colombian ecozones, were analysed with the selected combinations. Results obtained with AFLP are consistent with those obtained with RFLP, using plasmid DNA as a probe. Some primer combinations differentiated Xam strains that were not distinguished by RFLP analyses, thus AFLP fingerprinting allowed a better definition of the genetic relationships between Xam strains.

Measuring the genetic diversity of Xanthomonas axonopodis pv. manihotis within different fields in Colombia.

ABSTRACT Cassava bacterial blight, caused by Xanthomonas axonopodis pv. manihotis, is a widespread disease that affects cassava (Manihot esculenta). We collected 238 X. axonopodis pv. manihotis strains by intensively sampling single fields in four edaphoclimatic zones (ECZs) in Colombia. DNA polymorphism of different X. axonopodis pv. manihotis populations was assessed by restriction fragment length polymorphism (RFLP) analyses, repetitive sequence-based polymerase chain reaction (rep-PCR), and amplified fragment length polymorphism (AFLP) assays. Genetic diversity, phenetic relationships among strains, and the coefficient of genetic differentiation were determined. All strains were tested for aggressiveness on the susceptible cassava cv. MCOL 1522. Strains were also tested for virulence on cassava differentials adapted to the strains respective ECZs. Our study showed that the Colombian X. axonopodis pv. manihotis population has a high degree of genetic diversity. The hierarchical analysis of diversity showed genotypic differentiation at all levels, among ECZs, among fields within ECZs, and among strains within fields planted to several cassava genotypes. New RFLP haplotypes were detected, leading to the characterization of a new pathotype. Dendrograms from AFLP were more robust than those from RFLP data. A close association between the strains geographical origin and DNA polymorphism was obtained using RFLP and AFLP data. We suggest that the host played a role in causing pathogen differentiation.

Genetic Structure and Population Dynamics of Xanthomonas axonopodis pv. manihotis in Colombia from 1995 to 1999

ABSTRACT Restriction fragment length polymorphisms (RFLPs) were used to study the population genetics and temporal dynamics of the cassava bacterial pathogen Xanthomonas axonopodis pv. manihotis. The population dynamics were addressed by comparing samples collected from 1995 to 1999 from six locations, spanning four different edaphoclimatic zones (ECZs). Forty-five different X. axonopodis pv. manihotis RFLP types or haplotypes were identified between 1995 and 1999. High genetic diversity of the X. axonopodis pv. manihotis strains was evident within most of the fields sampled. In all but one site, diversity decreased over time within fields. Haplotype frequencies significantly differed over the years in all but one location. Studies of the rate of change of X. axonopodis pv. manihotis populations during the cropping cycle in two sites showed significant changes in the haplotype frequencies but not composition. However, variations in pathotype composition were observed from one year to the next at a single site in ECZs 1 and 2 and new pathotypes were described after 1997 in these ECZs, thus revealing the dramatic change in the pathogen population structure of X. axonopodis pv. manihotis. Disease incidence was used to show the progress of cassava bacterial blight in Colombia during the 5-year period in different ecosystems. Low disease incidence values were correlated with low rainfall in 1997 in ECZ 1.

Microbial and Functional Diversity within the Phyllosphere of Espeletia Species in an Andean High-Mountain Ecosystem

ABSTRACT Microbial populations residing in close contact with plants can be found in the rhizosphere, in the phyllosphere as epiphytes on the surface, or inside plants as endophytes. Here, we analyzed the microbiota associated with Espeletia plants, endemic to the Páramo environment of the Andes Mountains and a unique model for studying microbial populations and their adaptations to the adverse conditions of high-mountain neotropical ecosystems. Communities were analyzed using samples from the rhizosphere, necromass, and young and mature leaves, the last two analyzed separately as endophytes and epiphytes. The taxonomic composition determined by performing sequencing of the V5-V6 region of the 16S rRNA gene indicated differences among populations of the leaf phyllosphere, the necromass, and the rhizosphere, with predominance of some phyla but only few shared operational taxonomic units (OTUs). Functional profiles predicted on the basis of taxonomic affiliations differed from those obtained by GeoChip microarray analysis, which separated community functional capacities based on plant microenvironment. The identified metabolic pathways provided insight regarding microbial strategies for colonization and survival in these ecosystems. This study of novel plant phyllosphere microbiomes and their putative functional ecology is also the first step for future bioprospecting studies in search of enzymes, compounds, or microorganisms relevant to industry or for remediation efforts.

Metabolomic profile and nucleoside composition of Cordyceps nidus sp. nov. (Cordycipitaceae): A new source of active compounds

Cordyceps sensu lato is a genus of arthropod-pathogenic fungi, which have been used traditionally as medicinal in Asia. Within the genus, Ophiocordyceps sinensis is the most coveted and expensive species in China. Nevertheless, harvesting wild specimens has become a challenge given that natural populations of the fungus are decreasing and because large-scale culture of it has not yet been achieved. The worldwide demand for products derived from cultivable fungal species with medicinal properties has increased recently. In this study, we propose a new species, Cordyceps nidus, which parasitizes underground nests of trapdoor spiders. This species is phylogenetically related to Cordyceps militaris, Cordyceps pruinosa, and a sibling species of Cordyceps caloceroides. It is found in tropical rainforests from Bolivia, Brazil, Colombia and Ecuador. We also investigated the medicinal potential of this fungus based on its biochemical properties when grown on four different culture media. The metabolic profile particularly that of nucleosides, in polar and non-polar extracts was determined by UPLC, and then correlated to their antimicrobial activity and total phenolic content. The metabolome showed a high and significant dependency on the substrate used for fungal growth. The mass intensities of nucleosides and derivative compounds were higher in natural culture media in comparison to artificial culture media. Among these compounds, cordycepin was the predominant, showing the potential use of this species as an alternative to O. sinensis. Furthermore, methanol fractions showed antimicrobial activity against gram-positive bacteria, and less than 3.00 mg of gallic acid equivalents per g of dried extract were obtained when assessing its total phenolic content by modified Folin-Ciocalteu method. The presence of polyphenols opens the possibility of further exploring the antioxidant capacity and the conditions that may enhance this characteristic. The metabolic composition and biochemical activity indicate potential use of C. nidus in pharmaceutical applications.

Network Analyses in Plant Pathogens

Even in the age of big data in Biology, studying the connections between the biological processes and the molecular mechanisms behind them is a challenging task. Systems biology arose as a transversal discipline between biology, chemistry, computer science, mathematics, and physics to facilitate the elucidation of such connections. A scenario, where the application of systems biology constitutes a very powerful tool, is the study of interactions between hosts and pathogens using network approaches. Interactions between pathogenic bacteria and their hosts, both in agricultural and human health contexts are of great interest to researchers worldwide. Large amounts of data have been generated in the last few years within this area of research. However, studies have been relatively limited to simple interactions. This has left great amounts of data that remain to be utilized. Here, we review the main techniques in network analysis and their complementary experimental assays used to investigate bacterial-plant interactions. Other host-pathogen interactions are presented in those cases where few or no examples of plant pathogens exist. Furthermore, we present key results that have been obtained with these techniques and how these can help in the design of new strategies to control bacterial pathogens. The review comprises metabolic simulation, protein-protein interactions, regulatory control of gene expression, host-pathogen modeling, and genome evolution in bacteria. The aim of this review is to offer scientists working on plant-pathogen interactions basic concepts around network biology, as well as an array of techniques that will be useful for a better and more complete interpretation of their data.

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.