Biology subjects

Giglioli-Guivarc'h, N.

Publications and source records attributed to Giglioli-Guivarc'h, N..

3 recordsLinked to original sources

bioRxiv2026

Geissoschizine scaffolding enzymes shape monoterpene indole alkaloid biosynthesis

For decades, medicinal plants have been an invaluable source of therapeutics for human health. Among plant specialized metabolites, monoterpene indole alkaloids (MIAs) display remarkable chemical diversity and potent bioactivities, including anticancer properties. While the biosynthetic pathways leading to major MIAs such as vincristine, vinblastine, and camptothecin have been extensively studied, the mechanisms regulating metabolic flux within these pathways remain poorly understood. Here, we uncover an unexpected regulatory layer in MIA biosynthesis involving medium-chain dehydrogenase/reductase (MDR) proteins. Using a combination of in vitro biochemical assays, pathway reconstitution in planta, protein-protein interaction analyses, and metabolic engineering in yeast, we show that specific MDRs do not function as classical catalysts but instead enhance both the activity and diversify the stereochemical outputs of geissoschizine synthase (GS). These proteins physically interact with GS and strictosidine {beta}-glucosidase (SGD), forming ternary complexes that likely facilitate substrate channeling of reactive intermediates. Importantly, introduction of these MDRs into engineered yeast strains leads to a dramatic increase in the production of geissoschizine, a central MIA precursor. Collectively, our findings reveal a previously unrecognized role for MDR proteins as regulators of metabolic flux and highlight their potential as powerful tools for metabolic engineering of valuable plant natural products.

plant biology↗

bioRxiv2024

Genome-based discovery of pachysiphine synthases in Tabernaemontana elegans

Plant specialized metabolism represents an inexhaustible source of active molecules, some of which have been used in human health for decades. Among these, monoterpene indole alkaloids (MIAs) include a wide range of valuable compounds with anticancer, antihypertensive, or neuroactive properties. This is particularly the case for the pachysiphine derivatives which show interesting antitumor and anti-alzheimer activities but accumulate at very low levels in several Tabernaemontana species. Unfortunately, genome data in Tabernaemontanaceae are lacking and knowledge on the biogenesis of pachysiphine-related MIAs in planta remains scarce, limiting the prospects for biotechnological supply of many pachysiphine-derived biopharmaceuticals. Here, we report a raw version of the toad tree (Tabernaemontana elegans) genome sequence. These new genomic resources led to the identification and characterization of a couple of genes encoding cytochrome P450 with pachysiphine synthase activity. Our phylogenomic and docking analyses highlights the different evolutionary processes that have been recruited to epoxidize the pachysiphine precursor tabersonine at a specific position and in a dedicated orientation, thus enriching our understanding of the diversification and speciation of the MIA metabolism in plants. These gene discoveries also allowed us to engineer the synthesis of MIAs in yeast through the combinatorial association of metabolic enzymes resulting in the tailor-made synthesis of non-natural MIAs. Overall, this work represents a step forward for the future supply of pachysiphine-derived drugs by microbial cell factories. Significance StatementWhile pachysiphine is a monoterpene indole alkaloid of high interest and the precursor of an anti-Alzheimer compound, its biosynthesis involving the epoxidation of tabersonine remains uncharacterized. By sequencing and assembling the genome of Tabernaemontana elegans, we identified two P450s exhibiting a pachysiphine synthase activity that we modelized to explore the evolutionary scenario leading to the acquisition of this expoxidase activity; and used to engineer yeast cell factories for securing pachysiphine supply and producing new-to-nature alkaloids.

plant biology↗

bioRxiv2018

Ranking genome-wide correlation measurements improves microarray and RNA-seq based global and targeted co-expression networks

Co-expression networks are essential tools to infer biological associations between gene products and predict gene annotation. Global networks can be analyzed at the transcriptome wide scale or after querying them with a set of guide genes to capture the transcriptional landscape of a given pathway in a process named Pathway Level Correlation (PLC). A critical step in network construction remains the definition of gene co-expression. In the present work, we compared how Pearson Correlation Coefficient (PCC), Spearman Correlation Coefficient (SCC), their respective ranked values (Highest Reciprocal Rank (HRR)), Mutual Information (MI) and Partial Correlations (PC) performed on global networks and PLCs. This evaluation was conducted on the model plant Arabidopsis thaliana using microarray and differently pre-processed RNA-seq datasets. We particularly evaluated how dataset x distance measurement combinations performed in 5 PLCs corresponding to 4 well described plant metabolic pathways (phenylpropanoid, carbohydrate, fatty acid and terpene metabolisms) and the cytokinin signaling pathway. Our present work highlights how PCC ranked with HRR is better suited for global network construction and PLC with microarray and RNA-seq data than other distance methods, especially to cluster genes in partitions similar to biological subpathways.

bioinformatics↗