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International audience; The Montecristo wild goat is an endangered feral population that has been on the homonymous island in the Tuscan Archipelago since ancient times. The origins of Montecristo goats are still debated, with authors dating their introduction either back to Neolithic times or between the 6th and 13th century of the Common Era. To investigate the evolutionary history and relationships of this population we assembled a 50K SNP dataset including 55 Mediterranean breeds and two nuclei of Montecristo goats sampled on the island and from an ex situ conservation project. Diversity levels, gene flow, population structure, and genetic relationships were assessed through multiple approaches. The insular population scored the lowest values of both observed and expected heterozygosity, highlighting reduced genetic variation, while the ex situ nucleus highlighted a less severe reduction. Multivariate statistics, network, and population structure analyses clearly separated the insular nucleus from all other breeds, including the population of Montecristo goats from the mainland. Moreover, admixture and gene flow analyses pinpointed possible genetic inputs received by the two Montecristo goat nuclei from different sources, while Runs of Homozygosity (ROHs) indicated an ancient bottleneck/founder effect in the insular population and recent extensive inbreeding in the ex situ one. Overall, our results suggest that Montecristo goats experienced several demographic fluctuations combined with admixture events over time and highlighted a noticeable differentiation between the two nuclei.

International audience; Abstract The evolutionary and adaptive potential of a pathogen is a key determinant for successful host colonization and proliferation but remains poorly known for most of the pathogens. Here, we used experimental evolution combined with phenotyping, genomics, and transcriptomics to estimate the adaptive potential of the bacterial plant pathogen Ralstonia solanacearum to overcome the quantitative resistance of the tomato cultivar Hawaii 7996. After serial passaging over 300 generations, we observed pathogen adaptation to within-plant environment of the resistant cultivar but no plant resistance breakdown. Genomic sequence analysis of the adapted clones revealed few genetic alterations, but we provide evidence that all but one were gain of function mutations. Transcriptomic analyses revealed that even if different adaptive events occurred in independently evolved clones, there is convergence toward a global rewiring of the virulence regulatory network as evidenced by largely overlapping gene expression profiles. A subset of four transcription regulators, including HrpB, the activator of the type 3 secretion system regulon and EfpR, a global regulator of virulence and metabolic functions, emerged as key nodes of this regulatory network that are frequently targeted to redirect the pathogen’s physiology and improve its fitness in adverse conditions. Significant transcriptomic variations were also detected in evolved clones showing no genomic polymorphism, suggesting that epigenetic modifications regulate expression of some of the virulence network components and play a major role in adaptation as well.

International audience

Xylella fastidiosa is one of the most important threats to plant health worldwide, causing disease in the Americas on a range of agricultural crops and trees, and recently associated with a critical epidemic affecting olive trees in Europe. A main challenge for the detection of the pathogen and the development of physiological studies is its fastidious growth, as the generation time can vary from 10 to 100 h for some strains. This physiological peculiarity is shared with several human pathogens and is poorly understood. We performed an analysis of the metabolic capabilities of X. fastidiosa through a genome-scale metabolic model of the bacterium. This model was reconstructed and manually curated using experiments and bibliographical evidence. Our study revealed that fastidious growth most probably results from different metabolic specificities such as the absence of highly efficient enzymes or a global inefficiency in virulence factor production. These results support the idea that the fragility of the metabolic network may have been shaped during evolution to lead to the self-limiting behavior of X. fastidiosa., High proliferation rate and robustness are vital characteristics of bacterial pathogens that successfully colonize their hosts. The observation of drastically slow growth in some pathogens is thus paradoxical and remains unexplained. In this study, we sought to understand the slow (fastidious) growth of the plant pathogen Xylella fastidiosa. Using genome-scale metabolic network reconstruction, modeling, and experimental validation, we explored its metabolic capabilities. Despite genome reduction and slow growth, the pathogen’s metabolic network is complete but strikingly minimalist and lacking in robustness. Most alternative reactions were missing, especially those favoring fast growth, and were replaced by less efficient paths. We also found that the production of some virulence factors imposes a heavy burden on growth. Interestingly, some specific determinants of fastidious growth were also found in other slow-growing pathogens, enriching the view that these metabolic peculiarities are a pathogenicity strategy to remain at a low population level. IMPORTANCE Xylella fastidiosa is one of the most important threats to plant health worldwide, causing disease in the Americas on a range of agricultural crops and trees, and recently associated with a critical epidemic affecting olive trees in Europe. A main challenge for the detection of the pathogen and the development of physiological studies is its fastidious growth, as the generation time can vary from 10 to 100 h for some strains. This physiological peculiarity is shared with several human pathogens and is poorly understood. We performed an analysis of the metabolic capabilities of X. fastidiosa through a genome-scale metabolic model of the bacterium. This model was reconstructed and manually curated using experiments and bibliographical evidence. Our study revealed that fastidious growth most probably results from different metabolic specificities such as the absence of highly efficient enzymes or a global inefficiency in virulence factor production. These results support the idea that the fragility of the metabolic network may have been shaped during evolution to lead to the self-limiting behavior of X. fastidiosa.

International audience

National audience; R. solanacearum is one of the most devastating plant pathogens for agriculture due to its aggressiveness, its wide host spectrum, its vast geographical distribution and its long persistence in the soil. In many countries it infects many important crops (tomato, ginger, potato, bananas, tobacco …). On potato alone, it is responsible for an estimated $1 billion US in losses each year world-wide. It can also survive for years in soil, thus preventing the culture of susceptible hosts for long periods of time. When detected, is a source of major constraints for agriculture. Ralstonia solanacearum is now defined as a species complex composed of hundreds different strains and divided in four major phylotypes. Few strains are described as hostspecific, but most of them have similar lifecycles and can invade many hosts. Recently, we used a systems biology approach to show the existence of a trade-off between growth and virulence for the strain GMI1000 (Peyraud et al., 2016). Indeed, virulence traits such as excretion of exopolysaccharides or construction of a type III secretion system are costly in terms of energy, carbon and nitrogen, impacting the growth rate. The pathogen has to decide how to invest its resources between growth (hence proliferation) and virulence (thus defense/attack against the plant). This trade-off was experimentally validated by showing that avirulent mutants grows faster than the wild type. Here, we will present experimental and systems biology results investigating how much this trade-off is conserved among different strains of the R. solanacearum species complex. We will show that strains have different trophic preferences and metabolic adaptation, which can be linked to their lifestyle.

International audience; To deploy durable plant resistance, we must understand its underlying molecular mechanisms. Type III effectors (T3Es) and their recognition play a central role in the interaction between bacterial pathogens and crops. We demonstrate that the Ralstonia solanacearum species complex (RSSC) T3E ripAX2 triggers specific resistance in eggplant AG91-25, which carries the major resistance locus EBWR9. The eggplant accession AG91-25 is resistant to the wild-type R. pseudosolanacearum strain GMI1000, whereas a ripAX2 defective mutant of this strain can cause wilt. Notably, the addition of ripAX2 from GMI1000 to PSS4 suppresses wilt development, demonstrating that RipAX2 is an elicitor of AG91-25 resistance. RipAX2 has been shown previously to induce effector-triggered immunity (ETI) in the wild relative eggplant Solanum torvum, and its putative zinc (Zn)-binding motif (HELIH) is critical for ETI. We show that, in our model, the HELIH motif is not necessary for ETI on AG91-25 eggplant. The ripAX2 gene was present in 68.1% of 91 screened RSSC strains, but in only 31.1% of a 74-genome collection comprising R. solanacearum and R. syzygii strains. Overall, it is preferentially associated with R. pseudosolanacearum phylotype I. RipAX2(GMI1000) appears to be the dominant allele, prevalent in both R. pseudosolanacearum and R. solanacearum, suggesting that the deployment of AG91-25 resistance could control efficiently bacterial wilt in the Asian, African and American tropics. This study advances the understanding of the interaction between RipAX2 and the resistance genes at the EBWR9 locus, and paves the way for both functional genetics and evolutionary analyses.

Robustness is a key system-level property of living organisms to maintain their functions while tolerating perturbations. We investigate here how a regulatory network controlling multiple virulence factors impacts phenotypic robustness of a bacterial plant pathogen. We reconstruct a cell-scale model of Ralstonia solanacearum connecting a genome-scale metabolic network, a virulence macromolecule network, and a virulence regulatory network, which includes 63 regulatory components. We develop in silico methods to quantify phenotypic robustness under a broad set of conditions in high-throughput simulation analyses. This approach reveals that the virulence regulatory network exerts a control of the primary metabolism to promote robustness upon infection. The virulence regulatory network plugs into the primary metabolism mainly through the control of genes likely acquired via horizontal gene transfer, which results in a functional overlay with ancestral genes. These results support the view that robustness may be a selected trait that promotes pathogenic fitness upon infection., How pathogens maintain phenotypic robustness during infection is poorly understood. Here the authors couple the virulence regulatory network (VRN) of the pathogen R. solanacearum to a model of its metabolic network, and find that the VRN activates functionally redundant primary metabolism genes to promote phenotypic robustness during infection.

National audience; Phytopathogens are responsible of at least 30% of agricultural crop loss. Understanding fundamental pathogenicity mechanisms is essential to find sustainable means of fight against them. Metabolic modeling allows to make a link between genome, physiology and environmental conditions, by integrating molecular biology data in the metabolic reconstruction process and at the same time by predicting quantitative concentrations of metabolites and biomass growth which depends on the environmental conditions applied (mainly substrate availability). Metabolic modeling has already proven useful in the field of bioprocesses, for understanding metabolism and optimizing growth and product yields. Applying metabolic modeling on plants and phytopathogens could help understanding the trophic interactions that occurs between them during an infection. This would ultimately help unraveling pathogens strategy. In our team (Ralstonia Adaptation and Pathogenicity), we have recently developed a good quality metabolic model of the phytopathogen Ralstonia solanacerum. Even if the model was only focused on the pathogen, it has already shown that there is a huge trade-off between pathogenicity and growth, which was experimentally verified. This clearly illustrates that pathogens have to decide how to invest their resources between growth (hence proliferation) and virulence (thus defense/attack against the plant). The next step is to add the plant compartment, to model trophic interactions between the plant and the pathogen. I will present the advances towards the construction of this integrated model and the first experimental and modeling results obtained.