New workflow for multimodal and multiscale analysis of the parietal structure of maize stem, combining AFM, Raman, and MSI
ORIANE MOREL (France)1 2; Mathieu Fanuel (France)1 2; David Legland (France)1 2; Angélina D’Orlando (France)1 2; Hélène Rogniaux (France)1 2;
1 - INRAE, UR1268 Biopolymères Interactions Assemblages, F-44300 Nantes, France; 2 - INRAE, PROBE research infrastructure, BIBS facility, F-44300 Nantes, France;
Keywords: Multi-scale imaging; Biomass recalcitrance;
Abstract Topics: Theme 10: Tools, Imaging, and Omics for Cell Wall Research
Type of Presentation: Oral Communication

Abstract text: Biomass recovery represents a promising pathway toward renewable energy production, yet requires a thorough understanding of biomass structure to identify factors that govern the resistance to conversion. The hypothesis is that the spatial distribution, tissular organization and nanoscale interactions of plant cell wall polymers play a critical role in optimizing conversion processes and that advanced imaging techniques can be employed to explore in depth these structures at multiple scales: Atomic Force Microscopy (AFM) allows nanoscale topographical and mechanical characterization, while Raman spectroscopy provides insights into chemical composition and molecular organization; and Mass spectrometry imaging enables the direct monitoring of the enzymatic activity.
The complementarity of these imaging methods has motivated the present study, which aims to combine them to achieve an integrated and detailed view of cell wall. However, each technique imposes constraints on sample preparation and data interpretation. In that context, our work defined the experimental conditions that best accommodate the requirements of each method. The presentation will outline the difficulties encountered and experimental compromises that were achieved Corn stalk sections from two genotypes with contrasting levels of recalcitrance were used as models for this methodological development.
The project was funded though the FR2030 PEPR BBEST project “FillingGaps”.