Peeking into a symbiotic conversation

Exploring the molecular logic of communication between species

At the Symbiotic Systems Biology (SysBioSym) Group, we investigate how metabolic and regulatory mechanisms connect hosts and symbionts, whether these are mutualists or pathogens, shaping the structure and function of symbiotic communities. By combining different layers of data with computational modeling and comparative genomics, the SysBioSym Group aims to uncover the molecular “rules” that make these interactions robust, adaptable, and evolutionarily successful.

A central focus of the group is insect–bacteria nutrient symbiosis, particularly in Coleoptera (in collaboration with other groups from the department and the BF2i lab from INSA-Lyon). We explore how metabolic cooperation contributes to host adaptation and ecological specialization. Rather than simply extending known models, we aim to identify conserved versus lineage-specific metabolic strategies, revealing how biological interconnections from symbiotic partners are jointly coordinated to thrive in diverse environments. Our work complements ongoing research in the department by providing a systems-level understanding of these symbiotic networks.
 

Hypothetically speaking

A key aspect of our work is deciphering the hidden functions of hypothetical proteins, uncharacterized yet essential participants of a larger metabolic conversation. To do so, we integrate comparative modeling, domain annotation, and metabolic context analysis with state-of-the-art protein structure prediction tools (e.g., AlphaFold2, ESMFold). This multi-layered approach allows us to connect protein function with metabolic roles, shedding light on previously uncharacterized components of symbiotic metabolism.

Uninvited harmful speakers

Collaborations with Lucas Gentil Azevedo, Pablo Ivan Pereira Ramos (Fiocruz IGM); Andréa Ávila, Sheila Nardelli, Letusa Albrecht, Fabíola Holetz, Helisson Faoro (Fiocruz ICC)

We also explore how pathogenic molecular mechanisms adapt and are rewired during infection, focusing on the dynamic interplay between pathogens (whether they are protozoan parasites or bacteria) and their hosts. Lucas’s PhD work, for instance, focuses on the comparative metabolic network reconstruction of Leishmania braziliensis, integrating parasite and human host metabolisms. By combining enzymatic predictions, omics data, and flux balance analyses, this work aims at deciphering how infection reconfigures metabolic pathways within both parasite and host cells. These networks not only advance mechanistic understanding of Trypanosomatid biology, but also provide a transferable framework for studying metabolic adaptation across diverse microbe–host systems. The resulting models can highlight metabolic vulnerabilities and nominate targets for drug discovery, building on approaches previously applied to Toxoplasma gondii (Figure below, e.g. PMID:33408226)

When molecules talk the same language

Collaboration with Nahim A. de Souza, Renata Wassermann (USP); Marie-France Sagot (Inria)

In biology, meaning often lies not in single genes or molecules, but in how they connect and interact — much like words only make sense through grammar. Nahim’s PhD work uses ontology-based approaches to describe this hidden structure of biological information: the rules and relationships that make metabolic models intelligible across systems. Just as grammar allows speakers of different languages to translate ideas without losing meaning — to ensure they are not lost in translation — ontologies give biological data a shared “semantics,” allowing discoveries about metabolism, regulation, or symbiosis to be compared and understood across species and disciplines. By studying this grammar of knowledge, we aim to make biology more interoperable: a field where molecules, models, and datasets can finally speak the same language.