Coupled enzyme discovery, evolution and synthetic yeast chassis adaptation for microbial biopolymer valorisation
- 1Center for Molecular Biology of Heidelberg University (ZMBH), Heidelberg University
Abstract
The valorisation of biological polymers requires microbial systems that can both access recalcitrant substrates and convert the resulting carbon into useful products. Although microbial genome and metagenome resources provide an expanding reservoir of candidate depolymerizing and modifying enzymes, most discovery workflows remain disconnected from enzyme optimisation and host adaptation. Here we present a coupled sequence-based enzyme discovery, enzyme evolution and synthetic yeast chassis adaptation strategy for microbial biopolymer valorisation. Focusing on laccases for the depolymerisation of lignin as a proof of concept, we combine sequence data mining for enzyme discovery, modular yeast surface display for functional screening, directed evolution for enzyme optimisation and synthetic yeast genome diversification for chassis improvement. In our study, surface display enabled functional benchmarking and recovery of improved laccase variants and synthetic-genome-enabled diversification provided a route to explore host configurations that influence display and enzyme performance. By integrating enzyme-level and chassis-level optimisation, this framework addresses a central bottleneck in converting microbial biodiversity by computational sequence repository mining into deployable biomanufacturing systems. Our results establish laccases as tractable entry points for oxidative biopolymer conversion and provide a generalizable platform for engineering yeast systems for sustainable carbon valorisation.
Related
- Multi-Year Characterisation of Drought Adaptation and Grain Quality in Synthetic Hexaploid Wheat Genotypes
- From molecular evolution to biobricks and synthetic modules: a lesson by the bacterial flagellum.
- The haplotype-resolved T2T genome assembly reveals the evolution and adaptation mechanisms of cold resistance in Rosa beggeriana.
- Parameter-Efficient Adaptation of Protein Language Models for Dual-Target Antimicrobial Peptide Discovery Under Strict Homology Constraints
- La géodiversité en région Île-de-France : inventaire, protection et valorisation
BibTeX
@misc{olmos2026coupled,
title = {{Coupled enzyme discovery, evolution and synthetic yeast chassis adaptation for microbial biopolymer valorisation}},
author = {M. d. C. Sanchez Olmos and J. Gonzales Isa and N. Paczia and M. M. Zambrano and J. Huerta Cepas and E. Garcia-Ruiz and V. Y. de Anda Torres and D. Schindler},
howpublished = {bioRxiv},
year = {2026},
month = sep,
doi = {10.64898/2026.09.28.754783},
url = {https://www.biorxiv.org/content/10.64898/2026.09.28.754783v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - Coupled enzyme discovery, evolution and synthetic yeast chassis adaptation for microbial biopolymer valorisation
AU - M. d. C. Sanchez Olmos
AU - J. Gonzales Isa
AU - N. Paczia
AU - M. M. Zambrano
AU - J. Huerta Cepas
AU - E. Garcia-Ruiz
AU - V. Y. de Anda Torres
AU - D. Schindler
PY - 2026
DA - 2026/09/28
PB - bioRxiv
DO - 10.64898/2026.09.28.754783
UR - https://www.biorxiv.org/content/10.64898/2026.09.28.754783v1
AB - The valorisation of biological polymers requires microbial systems that can both access recalcitrant substrates and convert the resulting carbon into useful products. Although microbial genome and metagenome resources provide an expanding reservoir of candidate depolymerizing and modifying enzymes, most discovery workflows remain disconnected from enzyme optimisation and host adaptation. Here we present a coupled sequence-based enzyme discovery, enzyme evolution and synthetic yeast chassis adaptation strategy for microbial biopolymer valorisation. Focusing on laccases for the depolymerisation of lignin as a proof of concept, we combine sequence data mining for enzyme discovery, modular yeast surface display for functional screening, directed evolution for enzyme optimisation and synthetic yeast genome diversification for chassis improvement. In our study, surface display enabled functional benchmarking and recovery of improved laccase variants and synthetic-genome-enabled diversification provided a route to explore host configurations that influence display and enzyme performance. By integrating enzyme-level and chassis-level optimisation, this framework addresses a central bottleneck in converting microbial biodiversity by computational sequence repository mining into deployable biomanufacturing systems. Our results establish laccases as tractable entry points for oxidative biopolymer conversion and provide a generalizable platform for engineering yeast systems for sustainable carbon valorisation.
ER -