"Toward Holobiomics: Advanced Metabolomics and Integrative Omics for Unveiling Microbial-Host Complexity"

Abstract :

Omics technologies have revolutionized our understanding of living organisms, revealing that most host complex microbiomes—communities of microorganisms that co-evolve with their hosts. These partnerships create holobionts, intricate biological entities where the microbiome plays a pivotal role in immunity, metabolic regulation, and disease development. Deciphering holobiont interactions holds transformative potential for advances in health, agriculture, and ecological restoration. However, current methods for detecting microbial metabolites and understanding their roles in complex biological systems remain limited, hindering comprehensive insights into these interactions in their native contexts. Additionally, ex vivo isolation and analysis of these microorganisms are often laborious and incomplete.

To tackle these challenges, our research focuses on developing innovative experimental and computational methodologies that enhance the resolution and depth of metabolomics and integrated multi-omics analyses. Central to our approach is the systematic annotation of metabolite fragmentation spectra systems, alongside emerging experimental techniques that integrate single-cell analysis, advanced analytics, multi-omics, and artificial intelligence (AI) for deep mass spectrometry exploration.

In this presentation, I will first outline the main challenges facing the field of metabolomics and introduce the research objectives of the Holobiomics Lab at the Institut de Chimie de Nice and the 3iA Côte d’Azur. I will then highlight our discovery of novel bile acid conjugates produced by the human gut microbiota (Hoffmann, Nothias, Ludwig, et al., Nature Biotechnology, 2022), a study that showcases the power of combining combinatorial chemistry with deep learning to reveal previously unknown biological processes. Then, our project combines single-cell omics with mass spectrometry to facilitate the access and understanding of the diversity and function of microbial species within holobionts. Finally, I will discuss our collaborative efforts with the INRIA to develop next-generation AI systems that enable intuitive, dialogue-based exploration of molecular omics data, and our efforts to design scientifically-grounded generative AI systems that accelerate discovery and foster active learning.