Biology subjects

Gracy, J.

Publications and source records attributed to Gracy, J..

8 recordsLinked to original sources

bioRxiv2024

Understanding evolutionary and functional relationships of RNA polymerases in plant and fungal viruses through structural modeling and divergence date estimations

RNA-dependent RNA polymerases (RdRps) are crucial for RNA virus replication and serve as key marker genes for defining deep taxonomic ranks and for understanding viral evolutionary history. Despite their conserved functions and motifs, the high genetic diversity of RdRps complicates precise sequence comparisons across viral families, hindering accurate taxonomic classification of new species. Three-dimensional (3D) RdRp structures can help overcome these challenges through structure-guided alignments. However, such data are rare for myco- and phytoviruses, limiting investigation of their ecological and evolutionary links. In this study, we focused on the highly divergent order Sobelivirales, which includes sobemoviruses infecting plants -- a taxon known for its ancient origin -- and barnaviruses infecting fungi, which remain relatively unknown. Using deep-learning structural modeling, we generated reliable 3D models for 44 sobemoviral and sobelivirad species. Structure-guided alignments, together with new barnaviral and relevant outgroup sequences, enabled robust phylogenetic reconstruction, allowing us to propose revisions of existing viral families and suggest new evolutionary scenarios. Divergence dates were estimated for the first time at this taxonomical rank using the Prisoner of War model, which revealed a divergence of plant and fungal sobelivirads 27.0 {+/-} 10 million years ago -- much more recent than the separation of their respective hosts. This result suggests that cross-kingdom host shifts have contributed more likely to the evolutionary history of Sobelivirales than strict virus-host codivergence. Based on an extended dataset of 127 species, structure and sequence conservation analyses identified molecular signatures of sobeliviral families. These conserved and extented RdRp motifs will facilitate future taxonomic assignments and the development of diagnostic tools. Our interdisciplinary approach, integrating structure modeling and divergence dating, offers new insights into the evolutionary divergence of plant and fungal viruses, with potential applications to other viral orders and families. Author summaryRNA-dependent RNA polymerases (RdRps) are essential for RNA virus replication and serve as important markers for classifying viruses and understanding their evolution. However, with metagenomic studies that rapidly expand the known diversity of RNA viruses, it is increasingly difficult to compare highly divergent RdRps and accurately classify new species. When available, 3D structures of RdRps can help overcome this challenge through structure-guided alignments. Here, we focused on the highly divergent order Sobelivirales, which groups phytoviruses and mycoviruses. Deep-learning models were used to generate reliable 3D structures for 44 representative viral species. Structure-guided alignments combined with the identification of new barnaviruses and outgroups allowed us to build a more accurate viral phylogeny. Based on this finding, we proposed updates to existing viral families and genera within the order Sobelivirales. We estimated divergence dates using a model that previously uncovered the ancient origins of sobemovirus. Notably, we provided the first estimate of when these plant and fungal viruses diverged [~]27.0 {+/-} 10 million years ago, suggesting cross-kingdom host shifts rather than strict virus-host codivergence. We also identified molecular signatures that are useful for future virus classification and diagnosis, with potential applications to other viral groups.

evolutionary biology↗

bioRxiv2024

Zymoseptoria tritici proteins structurally related to UmV-KP4 and UmV-KP6 are toxic to fungi, and define novel structural families of fungal effectors

Fungal effectors play crucial roles in plant infection. Despite low sequence identity, effectors were recently classified into structural families. In this study, we have elucidated the structures of Zt-NIP1 and Mycgr3-91409 effectors of the wheat fungal pathogen Zymoseptoria tritici, using X-ray crystallography and NMR. These effectors displayed a structural homology with, respectively, KP4 and KP6 killer toxins, from UmV dsRNA viruses infecting the corn fungal pathogen Ustilago maydis. Consequently, Zt-NIP1 and Mycgr3-91409 were renamed Zt-KP4-1 and Zt-KP6-1. Orthologs and paralogs of Zt-KP4-1 and Zt-KP6-1 were identified in Zymoseptoria, but not in other fungi, except Ecp2 effectors related to Zt-KP4-1. Assessment of the biological activities of Zt-KP6-1 and Zt-KP4-1 revealed their toxicity to fungi such as Botrytis cinerea and Z. tritici, but not to wheat. A novel pipeline relying on Foldseek and cysteine-pattern constrained HMM searches of AlphaFold2 predicted structures from Uniprot generated a comprehensive inventory of KP4 and KP6 proteins in fungi and plants. A structure-based classification of these proteins revealed four KP4 and three KP6 structural super families. This classification provided far-reaching hypotheses on their biological function and evolution. This unifying structural framework highlights the power of structure determination for the classification of effectors, and their functional investigation.

biochemistry↗

bioRxiv2023

The structural landscape and diversity of Pyricularia oryzae MAX effectors revisited

Magnaporthe AVRs and ToxB-like (MAX) effectors constitute a family of secreted virulence proteins in the fungus Pyricularia oryzae (syn. Magnaporthe oryzae), which causes blast disease on numerous cereals and grasses. In spite of high sequence divergence, MAX effectors share a common fold characterized by a {beta}-sandwich core stabilized by a conserved disulfide bond. In this study, we investigated the structural landscape and diversity within the MAX effector repertoire of P. oryzae. Combining experimental protein structure determination and in silico structure modeling we validated the presence of the conserved MAX effector core domain in 77 out of 94 groups of orthologs (OG) identified in a previous population genomic study. Four novel MAX effector structures determined by NMR were in remarkably good agreement with AlphaFold2 (AF2) predictions. Based on the comparison of the AF2-generated 3D models we propose a classification of the MAX effectors superfamily in 20 structural groups that vary in the canonical MAX fold, disulfide bond patterns, and additional secondary structures in N- and C-terminal extensions. About one-third of the MAX family members remain singletons, without strong structural relationship to other MAX effectors. Analysis of the surface properties of the AF2 MAX models also highlights the high variability within the MAX family at the structural level, potentially reflecting the wide diversity of their virulence functions and host targets. Author summaryMAX effectors are a family of virulence proteins from the plant pathogenic fungus Pyricularia (syn. Magnaporthe) oryzae that share a similar 3D structure despite very low amino-acid sequence identity. Characterizing the function and evolution of these proteins requires a detailed understanding of their structural diversity. With this in mind, we have determined the NMR structures of four new MAX effectors and shown a near-perfect match with the corresponding AlphaFold2 (AF2) models. We then applied a prediction pipeline based on similarity searches with structural modeling using the AF2 software to predict MAX effectors in a collection of 120 P. oryzae genomes. The resulting models and experimental structures revealed that the MAX core while preserved is highly permissive to secondary structure variations and may coexists with extensive structural diversity in terms of structured N- or C-terminal extensions permitting their classification. For a subset of AF2 models, we have also analyzed the physico-chemical properties of the core domain surfaces, adding another, more functional perspective, notably surface electrostatics and stickiness. This work constitutes a major step in understanding the relationships among MAX effectors by analyzing their structural landscape and cataloguing specific physico-chemical properties. It also provides valuable insights for guiding research into the putative targets of these effectors in infected plant hosts.

bioinformatics↗

bioRxiv2023

SecretoMyc, a web-based database on mycobacteria secreted proteins and structure-based homology identification using bio-informatics tools.

To better understand the interaction between the host and the Mycobacterium tuberculosis pathogen, it is critical to identify its potential secreted proteins. While various experimental methods have been successful in identifying proteins under specific culture conditions, they have not provided a comprehensive characterisation of the secreted proteome. We utilized a combination of bioinformatics servers and in-house software to identify all potentially secreted proteins from six mycobacterial genomes through the three secretion systems: SEC, TAT, and T7SS. The results are presented in a database that can be crossed with selected proteomics and transcriptomics studies (https://secretomyc.cbs.cnrs.fr/myc). In addition, thanks to the recent availability of Alphafold models, we developed a tool in order to identify the structural homologues among the mycobacterial genomes.

microbiology↗

bioRxiv2023

Adaptive evolution in virulence effectors of the rice blast fungus Pyricularia oryzae

Plant pathogens secrete proteins called effectors that target host cellular processes to promote disease. Recently, structural genomics has identified several families of fungal effectors that share a similar three-dimensional structure despite remarkably variable amino-acid sequences and surface properties. To explore the selective forces that underlie the sequence variability of structurally-analogous effectors, we focused on MAX effectors, a structural family of effectors that are major determinants of virulence in the rice blast fungus Pyricularia oryzae. Using structure-informed gene annotation, we identified 58 to 78 MAX effector genes per genome in a set of 120 isolates representing seven host-associated lineages. The expression of MAX effector genes was primarily restricted to the early biotrophic phase of infection and strongly influenced by the host plant. Pangenome analyses of MAX effectors demonstrated extensive presence/absence polymorphism and identified gene loss events possibly involved in host range adaptation. However, gene knock-in experiments did not reveal a strong effect on virulence phenotypes suggesting that other evolutionary mechanisms are the main drivers of MAX effector losses. MAX effectors displayed high levels of standing variation and high rates of non-synonymous substitutions, pointing to widespread positive selection shaping the molecular diversity of MAX effectors. The combination of these analyses with structural data revealed that positive selection acts mostly on residues located in particular structural elements and at specific positions. By providing a comprehensive catalog of amino acid polymorphism, and by identifying the structural determinants of the sequence diversity, our work will inform future studies aimed at elucidating the function and mode of action of MAX effectors. AUTHOR SUMMARYFungal plant pathogens use small secreted proteins, called effectors, to manipulate to their own advantage their hosts physiology and immunity. The evolution of these effectors, whether spontaneously or in response to human actions, can lead to epidemics or the emergence of new diseases. It is therefore crucial to understand the mechanisms underlying this evolution. In this article, we report on the evolution of effectors in one of the prime experimental model systems of plant pathology, Pyricularia oryzae, the fungus causing blast diseases in rice, wheat, and other cereals or grasses. We further characterize in this fungus a particular class of effectors, called MAX effectors, using structural models based on experimental protein structures of effectors. We show that this class of effector is produced by the pathogen during the early stages of infection, when plant cells are still alive. By comparing the gene content of isolates infecting different plant species, we show that the MAX effector arsenal is highly variable from one isolate to another. Finally, using the inferential framework of population genetics, we demonstrate that MAX effectors exhibit very high genetic variability and that this results from the action of natural selection.

evolutionary biology↗

bioRxiv2021

A synthetic receptor platform enables rapid and portable monitoring of liver dysfunction via engineered bacteria.

Bacterial biosensors, or bactosensors, are promising field-deployable agents for medical and environmental diagnostics. However, the lack of scalable frameworks to systematically program ligand detection limits their applications. Here we present a synthetic receptor platform, termed EMeRALD (Engineered Modularized Receptors Activated via Ligand-induced Dimerization) which supports the modular assembly of sensing modules onto a high-performance, generic signaling scaffold controlling gene expression in E. coli. We applied EMeRALD to detect bile salts, a biomarker of liver dysfunction, by repurposing sensing modules from enteropathogenic Vibrio species. We improved the sensitivity and lowered the limit-of-detection of the sensing module by directed evolution. We then engineered a colorimetric bactosensor detecting pathological bile salt levels in serum from patients having undergone liver transplant, providing an output detectable by the naked-eye. The EMeRALD technology enables functional exploration of natural sensing modules and rapid engineering of synthetic receptors for diagnostics, environmental monitoring, and control of therapeutic microbes.

synthetic biology↗

bioRxiv2021

A Mycobacterium tuberculosis effector targets mitochondrion, controls energy metabolism and limits cytochrome c exit.

Host metabolism reprogramming is a key feature of Mycobacterium tuberculosis (Mtb) infection that enables the survival of this pathogen within phagocytic cells and modulates the immune response facilitating the spread of the tuberculosis disease. Here, we demonstrate that a previously uncharacterized secreted protein from Mtb, Rv1813c manipulates the host metabolism by targeting mitochondria. When expressed in eukaryotic cells, the protein is delivered to the mitochondrial intermembrane space and promotes the enhancement of host ATP production by boosting the oxidative phosphorylation metabolic pathway. Furthermore, the release of cytochrome c from mitochondria, an early apoptotic event in response to short-term oxidative stress, is delayed in Rv1813c expressing cells. This study reveals a novel class of mitochondria targeting effectors from Mtb which might participate in host cells metabolic reprogramming and apoptosis control during Mtb infections.

microbiology↗

bioRxiv2020

A new family of structurally conserved fungal effectors displays epistatic interactions with plant resistance proteins

Recognition of a pathogen avirulence (AVR) effector protein by a cognate plant resistance (R) protein triggers a set of immune responses that render the plant resistant. Pathogens can escape this so-called Effector-Triggered Immunity (ETI) by different mechanisms including the deletion or loss-of-function mutation of the AVR gene, the incorporation of point mutations that allow recognition to be evaded while maintaining virulence function, and the acquisition of new effectors that suppress AVR recognition. The Dothideomycete Leptosphaeria maculans, causal agent of oilseed rape stem canker, is one of the few fungal pathogens where suppression of ETI by an AVR effector has been demonstrated. Indeed, AvrLm4-7 suppresses Rlm3- and Rlm9- mediated resistance triggered by AvrLm3 and AvrLm5-9, respectively. The presence of AvrLm4-7 does not impede AvrLm3 and AvrLm5-9 expression, and the three AVR proteins do not appear to physically interact. To decipher the epistatic interaction between these L. maculans AVR effectors, we determined the crystal structure of AvrLm5-9 and obtained a 3D model of AvrLm3, based on the crystal structure of Ecp11-1, a homologous AVR effector candidate from Fulvia fulva. Despite a lack of sequence similarity, AvrLm5-9 and AvrLm3 are structural analogues of AvrLm4-7 (structure previously characterized). Structure-informed sequence database searches identified a larger number of putative structural analogues among L. maculans effector candidates, including the AVR effector AvrLmS-Lep2, all produced during the early stages of oilseed rape infection, as well as among effector candidates from other phytopathogenic fungi. These structural analogues are named LARS (for Leptosphaeria AviRulence and Suppressing) effectors. Remarkably, transformants of L. maculans expressing one of these structural analogues, Ecp11-1, triggered oilseed rape immunity in several genotypes carrying Rlm3. Furthermore, this resistance could be suppressed by AvrLm4-7. These results suggest that Ecp11-1 shares a common activity with AvrLm3 within the host plant which is detected by Rlm3, or that the Ecp11-1 structure is sufficiently close to that of AvrLm3 to be recognized by Rlm3. Author summaryAn efficient strategy to control fungal diseases in the field is genetic control using resistant crop cultivars. Crop resistance mainly relies on gene-for-gene relationships between plant resistance (R) genes and pathogen avirulence (AVR) genes, as defined by Flor in the 1940s. However, such gene-for-gene relationships can increase in complexity over the course of plant-pathogen co-evolution. Resistance against the plant-pathogenic fungus Leptosphaeria maculans by Brassica napus and other Brassica species relies on the recognition of effector (AVR) proteins by R proteins; however, L. maculans produces an effector that suppresses a subset of these specific resistances. Using a protein structure approach, we revealed structural analogy between several of the resistance-triggering effectors, the resistance-suppressing effector, and effectors from other plant-pathogenic species in the Dothideomycetes and Sordariomycetes classes, defining a new family of effectors called LARS. Notably, cross-species expression of one LARS effector from Fulvia fulva, a pathogen of tomato, in L. maculans resulted in recognition by several resistant cultivars of oilseed rape. These results highlight the need to integrate knowledge on effector structures to improve resistance management and to develop broad-spectrum resistances for multi-pathogen control of diseases.

plant biology↗