Plant Cell Wall Enzymatic Deconstruction: Bridging the Gap Between Micro and Nano Scales

Abstract

Understanding and overcoming the resistance of plant cell wall to enzymatic deconstruction is crucial to achieve a sustainable and economical conversion of plant biomass to bio-based products as alternatives to petroleum-based products. Despite the significant scientific advances over the past decades, the plant cell wall deconstruction at cell and tissue scales has remained under-investigated. In this study, to quantitatively characterize plant cell wall deconstruction, we set up an original imaging pipeline by combining time-lapse 4D (space + time) fluorescence confocal imaging, and a novel computational tool, to track and quantify cell wall deconstruction at cell and tissue scales offering a digital representation of cell wall deconstruction. Using this pipeline on poplar wood sections, we computed dynamics of several cellular parameters (e.g. cell wall volume, surface area, and number of cell neighbors) while measuring cellulose conversion. The results showed that the effect of enzymatic deconstruction at the cell scale is predominantly noticeable in terms of cell wall volume reduction rather than a significant decrease in surface area and accessible surface area. The results also revealed a negative correlation between pre-hydrolysis 3D cell wall compactness measures and volumetric cell wall deconstruction. The strength of this correlation was modulated by enzymatic activity. Combining cell wall compactness with the number of neighboring cells as a tissue-scale parameter yielded a stronger correlation. Our results also revealed a strong positive correlation between average volumetric cell wall deconstruction and cellulose conversion, thus establishing a link between key parameters and bridging the gap between nano and micro scales.

Plant phenotyping relevance

植物細胞壁の分解状態を定量化する4D蛍光画像パイプラインと計算ツールの開発が研究の中心であり、細胞壁体積・表面積・細胞隣接数などの植物組織形質を抽出している。

Code and data availability

The supplied blocks describe the WallTrack pipeline, 4D confocal imaging of poplar wood sections, and correlation analyses, but contain no public dataset, image, code, or model deposit with an authors' URL. Only the paper's own DOI appears; no availability statements for WallTrack code or data are present.

No evidence-backed public reproduction asset is currently recorded.