PacBio Hi-Fi genome assembly of Sipha maydis, a model for the study of multipartite mutualism in insects.

Dependence on multiple nutritional endosymbionts has evolved repeatedly in insects feeding on unbalanced diets. However, reference genomes for species hosting multi-symbiotic nutritional systems are lacking, even though they are essential for deciphering the processes governing cooperative life between insects and anatomically integrated symbionts. The cereal aphid Sipha maydis is a promising model for addressing these issues, as it has evolved a nutritional dependence on two bacterial endosymbionts that complement each other. In this study, we used PacBio High fidelity (HiFi) long-read sequencing to generate a highly contiguous genome assembly of S. maydis with a length of 410 Mb, 3,570 contigs with a contig N50 length of 187 kb, and BUSCO completeness of 95.5%. We identified 117 Mb of repetitive sequences, accounting for 29% of the genome assembly, and predicted 24,453 protein-coding genes, of which 2,541 were predicted enzymes included in an integrated metabolic network with the two aphid-associated endosymbionts. These resources provide valuable genetic and metabolic information for understanding the evolution and functioning of multi-symbiotic systems in insects.

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

Predicting and understanding plant responses to perturbations require 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 (Solanum lycopersicum) plant during vegetative growth, named Virtual Young TOmato Plant (VYTOP) 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 6,689 reactions and 6,326 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 impacts exchanges between the different organs. The model was also able to predict how nitrogen limitation affects vegetative growth and the metabolic behavior of transgenic tomato lines with altered expression 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.

Polyamines: double agents in disease and plant immunity.

Polyamines (PAs) are ubiquitous amine molecules found in all living organisms. In plants, beside their role in signaling and protection against abiotic stresses, there is increasing evidence that PAs have a major role in the interaction between plants and pathogens. Plant PAs are involved in immunity against pathogens, notably by amplifying pattern-triggered immunity (PTI) responses through the production of reactive oxygen species (ROS). In response, pathogens use phytotoxins and effectors to manipulate the levels of PAs in the plant, most likely to their own benefit. It also appears that pathogenic microorganisms produce PAs during infection, sometimes in large quantities. This may reflect different infectious strategies based on the selective exploitation of these molecules and the functions they perform in the cell.

Unravelling physiological signatures of tomato bacterial wilt and xylem metabolites exploited by Ralstonia solanacearum.

The plant pathogen Ralstonia solanacearum uses plant resources to intensely proliferate in xylem vessels and provoke plant wilting. We combined automatic phenotyping and tissue/xylem quantitative metabolomics of infected tomato plants to decipher the dynamics of bacterial wilt. Daily acquisition of physiological parameters such as transpiration and growth were performed. Measurements allowed us to identify a tipping point in bacterial wilt dynamics. At this tipping point, the reached bacterial density brutally disrupts plant physiology and rapidly induces its death. We compared the metabolic and physiological signatures of the infection with drought stress, and found that similar changes occur. Quantitative dynamics of xylem content enabled us to identify glutamine (and asparagine) as primary resources R. solanacearum consumed during its colonization phase. An abundant production of putrescine was also observed during the infection process and was strongly correlated with in planta bacterial growth. Dynamic profiling of xylem metabolites confirmed that glutamine is the favoured substrate of R. solanacearum. On the other hand, a triple mutant strain unable to metabolize glucose, sucrose and fructose appears to be only weakly reduced for in planta growth and pathogenicity.

Genome-Scale Investigation of the Metabolic Determinants Generating Bacterial Fastidious Growth.

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.

Physiological responses of three mono-species phototrophic biofilms exposed to copper and zinc.

In freshwater ecosystem, phototrophic biofilms play a crucial role through adsorption and sequestration of organic and inorganic pollutants. However, extracellular polymeric substance (EPS) secretion by phototrophic biofilms exposed to metals is poorly documented. This work evaluated the physiological responses of phototrophic biofilms by exposing three microorganisms (cyanobacterium Phormidium autumnale, diatom Nitzschia palea and green alga Uronema confervicolum) to 20 and 200 µg L-1 of Cu or 60 and 600 µg L-1 of Zn, both individually and in combination. Analysis of metal effects on algal biomass and photosynthetic efficiency showed that metals were toxic at higher concentrations for these two parameters together and that all the strains were more sensitive to Cu than to Zn. U. confervicolum was the most impacted in terms of growth, while P. autumnale was the most impacted in terms of photosynthetic efficiency. In consequence to metal exposure at higher concentrations (Cu200, Zn600 and Cu200Zn600), a higher EPS production was measured in diatom and cyanobacterium biofilms, essentially caused by an overproduction of protein-like polymers. On the other hand, the amount of secreted polysaccharides decreased during metal exposure of the diatom and green alga biofilms. Size exclusion chromatography revealed specific EPS molecular fingerprints in P. autumnale and N. palea biofilms that have secreted different protein-like polymers during their development in the presence of Zn600. These proteins were not detected in the presence of Cu200 despite an increase of proteins in the EPS extracts compared to the control. These results highlight interesting divergent responses between the three mono-species biofilms and suggest that increasing protein production in EPS biofilms may be a fingerprint of natural biofilm against metal pollutants in freshwater rivers.