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Lee, Namil

Publications and source records attributed to Lee, Namil.

Polyketide synthase-based controlled synthesis of polycyclopropanated fuel molecules

Reducing carbon emissions from aviation and long-distance transportation sectors requires the development of sustainable biofuels with suitable energy density, freezing point, and other physical properties. We previously demonstrated biological production of high energy polycyclopropanated fatty acids (POP-FAs, class I) using an iterative polyketide synthase (iPKS) pathway in a Streptomyces host. Here, we used a computational model of fuel properties to identify chain length and cyclopropanation control as critical steps to engineer this iPKS for biofuel applications. We next explored the natural diversity of POP biosynthesis by investigating homologous pathways. Then, by in vivo gene exchange, we determined cyclopropanase (CP) catalysis to be key for POP-FA engineering. Leveraging both natural and engineered pathway product diversity, we demonstrate targeted production of improved POP-FAs, namely shortened POP-FAs with predicted superior freezing point properties for aviation, as well as fully cyclopropane-saturated POP-FAs which should have superior energy-density. These precise and controllable modifications to POP-FA structure open the door for bioproduction of designer POP fuels.

Yin, Kevin↗

Engineering controllable alteration of malonyl-CoA levels to enhance polyketide production

Heterologous expression of polyketide synthase (PKS) genes in Escherichia coli has enabled the production of various valuable natural and synthetic products. However, the limited availability of malonyl-CoA (M-CoA) in E. coli remains a substantial impediment to high-titer polyketide production. Here we address this limitation by disrupting the native M-CoA biosynthetic pathway and introducing an orthogonal pathway comprising a malonate transporter and M-CoA ligase, enabling efficient M-CoA biosynthesis under malonate supplementation. This approach substantially increases M-CoA levels, enhancing fatty acid and polyketide titers while reducing the promiscuous activity of PKSs toward undesired acyl-CoA substrates. Subsequent adaptive laboratory evolution of these strains provides insights into M-CoA regulation and identifies mutations that further boost M-CoA and polyketide production. This strategy improves E. coli as a host for polyketide biosynthesis and advances understanding of M-CoA metabolism in microbial systems.

Klass, Sarah H↗

Engineering Pseudomonas putida for production of 3-hydroxyacids using hybrid type I polyketide synthases

Engineered type I polyketide synthases (T1PKSs) are a potentially transformative platform for the biosynthesis of small molecules. Due to their modular nature, T1PKSs can be rationally designed to produce a wide range of bulk or specialty chemicals. While heterologous PKS expression is best studied in microbes of the genus Streptomyces, recent studies have focused on the exploration of non-native PKS hosts. The biotechnological production of chemicals in fast growing and industrial relevant hosts has numerous economic and logistic advantages. With its native ability to utilize alternative feedstocks, Pseudomonas putida has emerged as a promising workhorse for the sustainable production of small molecules. Here, we outline the assessment of P. putida as a host for the expression of engineered T1PKSs and production of 3-hydroxyacids. After establishing the functional expression of an engineered T1PKS, we successfully expanded and increased the pool of available acyl-CoAs needed for the synthesis of polyketides using transposon sequencing and protein degradation tagging. This work demonstrates the potential of T1PKSs in P. putida as a production platform for the sustainable biosynthesis of unnatural polyketides.

Schmidt, Matthias↗

Transcriptome architecture of the three main lineages of agrobacteria

ABSTRACT Agrobacteria are a diverse, polyphyletic group of prokaryotes with multipartite genomes capable of transferring DNA into the genomes of host plants, making them an essential tool in plant biotechnology. Despite their utility in plant transformation, genome-wide transcriptional regulation is not well understood across the three main lineages of agrobacteria. Transcription start sites (TSSs) are a necessary component of gene expression and regulation. In this study, we used differential RNA-seq and a TSS identification algorithm optimized on manually annotated TSS, then validated with existing TSS to identify thousands of TSS with nucleotide resolution for representatives of each lineage. We extend upon the 356 TSSs previously reported in Agrobacterium fabrum C58 by identifying 1,916 TSSs. In addition, we completed genomes and phenotyping of Rhizobium rhizogenes C16/80 and Allorhizobium vitis T60/94, identifying 2,650 and 2,432 TSSs, respectively. Parameter optimization was crucial for an accurate, high-resolution view of genome and transcriptional dynamics, highlighting the importance of algorithm optimization in genome-wide TSS identification and genomics at large. The optimized algorithm reduced the number of TSSs identified internal and antisense to the coding sequence on average by 90.5% and 91.9%, respectively. Comparison of TSS conservation between orthologs of the three lineages revealed differences in cell cycle regulation of ctrA as well as divergence of transcriptional regulation of chemotaxis-related genes when grown in conditions that simulate the plant environment. These results provide a framework to elucidate the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria. IMPORTANCE Transcription start sites (TSSs) are fundamental for understanding gene expression and regulation. Agrobacteria, a group of prokaryotes with the ability to transfer DNA into the genomes of host plants, are widely used in plant biotechnology. However, the genome-wide transcriptional regulation of agrobacteria is not well understood, especially in less-studied lineages. Differential RNA-seq and an optimized algorithm enabled identification of thousands of TSSs with nucleotide resolution for representatives of each lineage. The results of this study provide a framework for elucidating the mechanistic basis and evolution of pathology across the three main lineages of agrobacteria. The optimized algorithm also highlights the importance of parameter optimization in genome-wide TSS identification and genomics at large.

59 BASIC BIOLOGICAL SCIENCES↗