AUTHOR=Kim Joonhoon , Coradetti Samuel T. , Kim Young-Mo , Gao Yuqian , Yaegashi Junko , Zucker Jeremy D. , Munoz Nathalie , Zink Erika M. , Burnum-Johnson Kristin E. , Baker Scott E. , Simmons Blake A. , Skerker Jeffrey M. , Gladden John M. , Magnuson Jon K. TITLE=Multi-Omics Driven Metabolic Network Reconstruction and Analysis of Lignocellulosic Carbon Utilization in Rhodosporidium toruloides JOURNAL=Frontiers in Bioengineering and Biotechnology VOLUME=8 YEAR=2021 URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2020.612832 DOI=10.3389/fbioe.2020.612832 ISSN=2296-4185 ABSTRACT=

An oleaginous yeast Rhodosporidium toruloides is a promising host for converting lignocellulosic biomass to bioproducts and biofuels. In this work, we performed multi-omics analysis of lignocellulosic carbon utilization in R. toruloides and reconstructed the genome-scale metabolic network of R. toruloides. High-quality metabolic network models for model organisms and orthologous protein mapping were used to build a draft metabolic network reconstruction. The reconstruction was manually curated to build a metabolic model using functional annotation and multi-omics data including transcriptomics, proteomics, metabolomics, and RB-TDNA sequencing. The multi-omics data and metabolic model were used to investigate R. toruloides metabolism including lipid accumulation and lignocellulosic carbon utilization. The developed metabolic model was validated against high-throughput growth phenotyping and gene fitness data, and further refined to resolve the inconsistencies between prediction and data. We believe that this is the most complete and accurate metabolic network model available for R. toruloides to date.