Biology subjects

Cottret, L.

Publications and source records attributed to Cottret, L..

8 recordsLinked to original sources

bioRxiv2023

Insights into the metabolic specificities of pathogenic strains from the Ralstonia solanacearum species complex

All the strains grouped under the species Ralstonia solanacearum represent a species complex which collectively constitute a devastating plant pathogen responsible of many diseases on agricultural crops throughout the world. The strains have different lifestyles and host range. Here we sought whether specific metabolic pathways contribute to strain diversification. To this end, we carried out systematic comparisons, followed by manual expertise on 11 strains representing the diversity of the species complex. We reconstructed the metabolic network of each strain from its genome sequence and looked for the metabolic pathways differentiating the different reconstructed networks and, by extension, the different strains. Finally, we conducted an experimental validation by determining the metabolic profile of each strain with the Biolog technology, also in a comparative approach. Results revealed that the metabolism is conserved between strains, with a core-metabolism composed of 82% of the pan-reactome. The 3 species composing the species complex could be distinguished according to the presence/absence of some metabolic pathways, in particular one implying salicylic acid degradation. Phenotypic assays revealed that the trophic preferences on organic acids and several amino acids such as glutamine, glutamate, aspartate and asparagine are conserved between strains. Finally, the generation and assessment of the transcription factor phcA regulating virulence in each specie showed that the faster growth compared to the WT strain was conserved across Ralstonia solanacearum species complex. Author summaryRalstonia solanacearum is one of the most important threats to plant health worldwide, causing disease on a very large range of agricultural crops such as tomato or potato. Behind the Ralstonia solanacearum name are hundreds of strains with different host range and lifestyle, classified into three species. Studying the differences between strain allows to better apprehend the biology of the pathogen and the specificity of some strains. None of the published genomic comparative studies have focused on the metabolism of the strains so far. We developed a new bioinformatic pipeline to build high-quality metabolic networks and used a combination of metabolic modeling and high-throughput phenotypic Biolog microplates to look for the metabolic differences between 11 strains across the three species. Our study revealed that genes encoding for enzymes are overall conserved, with few variations between strains. However, at the level of the phenotype, more variations were observed. These variations probably result from regulation rather than the presence or absence of enzymes in the genome.

systems biology↗

bioRxiv2022

Rhizocarpon geographicum lichen discloses a highly diversified microbiota carrying antibiotic resistance and Persistent Organic Pollutants tolerance

As rock-inhabitants, lichens are exposed to extreme and fluctuating abiotic conditions associated with poor sources of nutriments. These extreme conditions confer to lichens the unique ability to develop protective mechanisms. Consequently, lichen-associated microbes disclose highly versatile lifestyles and ecological plasticity, enabling them to withstand extreme environments. Because of their ability to grow on poor and extreme habitats, bacteria associated with lichens can tolerate a wide range of pollutants and on the other hand secrete antimicrobial compounds. In addition, lichen-associated bacteria were described to harbor ecological functions crucial for the evolution of the lichen holobiont. Nevertheless, the ecological features of lichen-associated microbes are still underestimated. To explore the untapped ecological diversity of lichen-associated bacteria, we adopted a novel culturomic approach on the crustose lichen Rhizocarpon geographicum. We sampled R. geographicum in French habitats exposed to oil spill and we combined 9 culturing methods with 16S rRNA sequencing to capture the largest bacterial diversity. A deep functional analysis of the lichen-associated bacterial collection showed the presence of a set of bacterial strains resistant to a wide range of antibiotics and displaying tolerance to Persistent Organic Pollutants (POP). Our study is a starting point to explore the ecological features of the lichen microbiota.

microbiology↗

bioRxiv2021

A multi-organ metabolic model of tomato predicts plant responses to nutritional and genetic perturbations

Predicting and understanding plant responses to perturbations requires integrating the interactions between nutritional sources, genes, cell metabolism and physiology in the same model. This can be achieved using metabolic modeling calibrated by experimental data. In this study, we developed a multi-organ metabolic model of a tomato plant during vegetative growth, named VYTOP (Virtual Young TOmato Plant) that combines genome-scale metabolic models of leaf, stem and root and integrates experimental data acquired from metabolomics and high-throughput phenotyping of tomato plants. It is composed of 6689 reactions and 6326 metabolites. We validated VYTOP predictions on five independent use cases. The model correctly predicted that glutamine is the main organic nutrient of xylem sap. The model estimated quantitatively how stem photosynthetic contribution impact exchanges between the different organs. The model was also able to predict how nitrogen limitation affects the plant vegetative growth, and to predict the metabolic behavior of transgenic tomato lines with altered expressions of core metabolic enzymes. The integration of different components such as a metabolic model, physiological constraints and experimental data generates a powerful predictive tool to study plant behavior, which will be useful for several other applications such as plant metabolic engineering or plant nutrition. One sentence summaryA multi-organ metabolic model of tomato gives biological insights into the functioning of a plant such as xylem composition, the role of the stem and the response to environmental or genetic perturbation.

systems biology↗

bioRxiv2020

Rhizobium leguminosarum symbiovar viciae strains are natural wheat endophytes and can stimulate root development and colonization by arbuscular mycorrhizal fungi

O_LIAlthough rhizobia establishing a nitrogen-fixing symbiosis with legumes are also known to promote growth in non-legumes, studies on rhizobia association with wheat roots are scarce. C_LIO_LIWe searched for Rhizobium leguminosarum symbiovar viciae (Rlv) strains naturally competent for wheat roots colonization. We isolated 20 strains and tested the ability of a subset for wheat roots colonization when co-inoculated with other Rlv. We also measured the effect of these strains on wheat root architecture and Arbuscular Mycorrhizal Fungal (AMF) colonization. C_LIO_LIWe found a low diversity of Rlv in wheat roots compared to that observed in the Rlv species complex. Only a few strains, including those isolated from wheat roots, and one strain isolated from pea nodules, were efficient to colonize wheat roots in co-inoculation conditions. These strains had a high ability for endophytic colonization of wheat root and were able to stimulate root development and AMF colonization in single strain inoculation conditions. C_LIO_LIThese results suggest that wheat is an alternative host for some Rlv; nevertheless, there is a strong competition between Rlv strains for wheat root colonization. Furthermore, our study suggests that the level of endophytic colonization is critical for Rlv ability to promote wheat growth. C_LI

microbiology↗

bioRxiv2019

EffectorK, a comprehensive resource to mine for pathogen effector targets in the Arabidopsis proteome

Pathogens deploy effector proteins that interact with host proteins to manipulate the host physiology to the pathogens own benefit. However, effectors can also be recognized by host immune proteins leading to the activation of defense responses. Effectors are thus essential components in determining the outcome of plant-pathogen interactions. Despite major efforts to decipher effector functions, our current knowledge on effector biology is scattered and often limited. In this study, we conducted two systematic large-scale yeast two-hybrid screenings to detect interactions between Arabidopsis thaliana proteins and effectors from two vascular bacterial pathogens: Ralstonia pseudosolanacearum and Xanthomonas campestris. We then constructed an interactomic network focused on Arabidopsis and effector proteins from a wide variety of bacterial, oomycete, fungal and animal pathogens. This network contains our experimental data and protein-protein interactions from 2,035 peer-reviewed publications (48,200 Arabidopsis-Arabidopsis and 1,300 Arabidopsis-effector protein interactions). Our results show that effectors from different species interact with both common and specific Arabidopsis targets suggesting dual roles as modulators of generic and adaptive host processes. Network analyses revealed that effector targets, particularly effector hubs and bacterial core effector targets, occupy important positions for network organization as shown by their larger number of protein interactions and centrality. These interactomic data were incorporated in EffectorK, a new graph-oriented knowledge database that allows users to navigate the network, search for homology or find possible paths between host and/or effector proteins. EffectorK is available at www.effectork.org and allows users to submit their own interactomic data. Author summaryPlant pests and diseases caused by bacteria, oomycetes, fungi or animals are threatening food security worldwide. Understanding how these pathogens infect and manipulate the host is key to develop sustainable crop resistance in the long term. Effector proteins are secreted by pathogens to subvert the host immune responses. The roles of several effector proteins have been described; however, it is yet poorly understood how effectors interact with host proteins at a global level. To address this issue, we have generated EffectorK, an interactive database focused on the model plant species Arabidopsis thaliana. This database contains manually curated Arabidopsis-effector protein interactions from the available literature on a wide variety of pathogens. It also contains new experimental data on effectors from two vascular pathogens: Ralstonia pseudosolanacearum and Xanthomonas campestris. This work integrates all the gathered knowledge over the last decades and allows to identify general patterns of how effectors interact with the host proteome. This knowledge is easily accessible and searchable at www.effectork.org.

plant biology↗

bioRxiv2019

An ancestral signalling pathway is conserved in plant lineages forming intracellular symbioses

Plants are the foundation of terrestrial ecosystems and their colonization of land was facilitated by mutualistic associations with arbuscular mycorrhizal fungi. Following that founding event, plant diversification has led to the emergence of a tremendous diversity of mutualistic symbioses with microorganisms, ranging from extracellular associations to the most intimate intracellular associations, where fungal or bacterial symbionts are hosted inside plant cells. Through analysis of 271 transcriptomes and 122 plant genomes, we demonstrate that the common symbiosis signalling pathway controlling the association with arbuscular mycorrhizal fungi and with nitrogen-fixing bacteria specifically co-evolved with intracellular endosymbioses, including ericoid and orchid mycorrhizae in angiosperms and ericoid-like associations of bryophytes. In contrast, species forming exclusively extracellular symbioses like ectomycorrhizae or associations with cyanobacteria have lost this signalling pathway. This work unifies intracellular symbioses, revealing conservation in their evolution across 450 million years of plant diversification.

plant biology↗

bioRxiv2018

Computational analysis of the Plasmodiophora brassicae genome: mitochondrial sequence description and metabolic pathway database design

Plasmodiophora brassicae is an obligate biotrophic pathogenic protist responsible for clubroot, a root gall disease of Brassicaceae species. In addition to the reference genome of the P. brassicae European e3 isolate and the draft genomes of Canadian or Chinese isolates, we present the genome of eH, a second European isolate. Refinement of the annotation of the eH genome led to the identification of the mitochondrial genome sequence, which was found to be bigger than that of Spongospora subterranea, another plant parasitic Plasmodiophorid phylogenetically related to P. brassicae. New pathways were also predicted, such as those for the synthesis of spermidine, a polyamine up-regulated in clubbed regions of roots. A P. brassicae pathway genome database was created to facilitate the functional study of metabolic pathways in transcriptomics approaches. These available tools can help in our understanding of the regulation of P. brassicae metabolism during infection and in response to diverse constraints.

genomics↗

bioRxiv2018

Family-Companion: analyse, visualise, browse, query and share your homology clusters

Identifying homology groups in predicted proteomes from different biological sources allows biologists to address questions as diverse as inferring species-specific proteins or retracing the phylogeny of gene families. Nowadays, command-line software exists to infer homology clusters. However, computing and interpreting homology groups with this software remains challenging for biologists and requires computational skills.\n\nWe propose Family-Companion, a web server dedicated to the computation, the analysis and the exploration of homology clusters. Family-Companion aims to fill the gap between analytic software and databases presenting orthologous groups based on a set of public data. It offers a user-friendly interface to launch or upload precomputed homology cluster analysis, to explore and share the results with other users. The exploration of the results is highly facilitated by interactive solutions to visualize proteome intersections via Venn diagrams, phylogenetic trees, multiple alignments, and also by querying the results by blast or by keywords.\n\nFamily-Companion is available at http://family-companion.toulouse.inra.fr with a demo dataset and a set of video tutorials. Source code and installation protocol can be found at https://framagit.org/BBRIC/family-companion/. A container-based package simplifies the installation of the web-suite.

bioinformatics↗