Plant cell wall enzymatic hydrolysis: Predicting yield dynamics from autofluorescence and morphological temporal...

Area of Science:

• Biotechnology
• Plant Science
• Biochemistry

Background:

• Enzymatic hydrolysis of plant cell walls is crucial for biotechnological conversion.
• Cell wall recalcitrance and complex mechanisms hinder accurate prediction of sugar yields.
• Conventional methods for yield prediction are labor-intensive and time-consuming.

Purpose of the Study:

• To develop an innovative pipeline for quantifying cell wall autofluorescence and morphological descriptors during enzymatic hydrolysis.
• To establish plant cell wall autofluorescence and morphological descriptors as real-time biomarkers for predicting sugar conversion yields.
• To provide a framework for accelerating the optimization of biotechnological conversion processes.

Main Methods:

• Developed an innovative pipeline to quantify cell wall autofluorescence intensity and morphological descriptors.
• Incorporated a novel adaptive drift compensation strategy for robust analysis.
• Applied the pipeline to time-lapse images of spruce wood enzymatic deconstruction.

Main Results:

• Strong negative correlations were found between conversion yields and the dynamics of cell wall autofluorescence intensity and morphological descriptors.
• Phase-specific analysis revealed distinct correlation patterns based on hydrolysis stage and sugar type.
• The developed pipeline demonstrated accurate prediction of sugar conversion yields.

Conclusions:

• Plant cell wall autofluorescence and morphological descriptors serve as accurate, non-destructive, real-time biomarkers for predicting sugar conversion yields.
• The developed pipeline eliminates the need for extensive sampling and time-consuming chemical assays.
• This approach accelerates the development of optimized biotechnological conversion processes.