Engineering topics
Lim, Hyun Gyu
Publications and source records attributed to Lim, Hyun Gyu.
Biocomposite thermoplastic polyurethanes containing evolved bacterial spores as living fillers to facilitate polymer disintegration
The field of hybrid engineered living materials seeks to pair living organisms with synthetic materials to generate biocomposite materials with augmented function since living systems can provide highly-programmable and complex behavior. Engineered living materials have typically been fabricated using techniques in benign aqueous environments, limiting their application. In this work, biocomposite fabrication is demonstrated in which spores from polymer-degrading bacteria are incorporated into a thermoplastic polyurethane using high-temperature melt extrusion. Bacteria are engineered using adaptive laboratory evolution to improve their heat tolerance to ensure nearly complete cell survivability during manufacturing at 135 °C. Furthermore, the overall tensile properties of spore-filled thermoplastic polyurethanes are substantially improved, resulting in a significant improvement in toughness. The biocomposites facilitate disintegration in compost in the absence of a microbe-rich environment. Finally, embedded spores demonstrate a rationally programmed function, expressing green fluorescent protein. This research provides a scalable method to fabricate advanced biocomposite materials in industrially-compatible processes.
Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440
ABSTRACT There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules (“functional modules”), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida . Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.
Revealing oxidative pentose metabolism in new Pseudomonas putida isolates
Abstract The Pseudomonas putida group in the Gammaproteobacteria has been intensively studied for bioremediation and plant growth promotion. Members of this group have recently emerged as promising hosts to convert intermediates derived from plant biomass to biofuels and biochemicals. However, most strains of P. putida cannot metabolize pentose sugars derived from hemicellulose. Here, we describe three isolates that provide a broader view of the pentose sugar catabolism in the P. putida group. One of these isolates clusters with the well‐characterized P. alloputida KT2440 (Strain BP6); the second isolate clustered with plant growth‐promoting strain P. putida W619 (Strain M2), while the third isolate represents a new species in the group (Strain BP8). Each of these isolates possessed homologous genes for oxidative xylose catabolism ( xylDXA ) and a potential xylonate transporter. Strain M2 grew on arabinose and had genes for oxidative arabinose catabolism ( araDXA ). A CRISPR interference (CRISPRi) system was developed for strain M2 and identified conditionally essential genes for xylose growth. A glucose dehydrogenase was found to be responsible for initial oxidation of xylose and arabinose in strain M2. These isolates have illuminated inherent diversity in pentose catabolism in the P. putida group and may provide alternative hosts for biomass conversion.
Machine-learning from Pseudomonas putida KT2440 transcriptomes reveals its transcriptional regulatory network
Bacterial gene expression is orchestrated by numerous transcription factors (TFs). Elucidating how gene expression is regulated is fundamental to understanding bacterial physiology and engineering it for practical use. In this study, a machine-learning approach was applied to uncover the genome-scale transcriptional regulatory network (TRN) in Pseudomonas putida KT2440, an important organism for bioproduction. We performed independent component analysis of a compendium of 321 high-quality gene expression profiles, which were previously published or newly generated in this study. We identified 84 groups of independently modulated genes (iModulons) that explain 75.7% of the total variance in the compendium. With these iModulons, we (i) expand our understanding of the regulatory functions of 39 iModulon associated TFs (e.g., HexR, Zur) by systematic comparison with 1993 previously reported TF-gene interactions; (ii) outline transcriptional changes after the transition from the exponential growth to stationary phases; (iii) capture group of genes required for utilizing diverse carbon sources and increased stationary response with slower growth rates; (iv) unveil multiple evolutionary strategies of transcriptome reallocation to achieve fast growth rates; and (v) define an osmotic stimulon, which includes the Type VI secretion system, as coordination of multiple iModulon activity changes. Taken together, this study provides the first quantitative genome-scale TRN for P. putida KT2440 and a basis for a comprehensive understanding of its complex transcriptome changes in a variety of physiological states.
Generation of Pseudomonas putida KT2440 Strains with Efficient Utilization of Xylose and Galactose via Adaptive Laboratory Evolution
While Pseudomonas putida KT2440 has great potential for biomass-converting processes, its inability to utilize the biomass abundant sugars xylose and galactose has limited its applications. Here, in this study, we utilized Adaptive Laboratory Evolution (ALE) to optimize engineered KT2440 with heterologous expression of xylD encoding xylonate dehydratase from Caulobacter crescentus and galETKM encoding UDP-glucose 4-epimerase, galactose-1-phosphate uridylyltransferase, galactokinase, and galactose-1-epimerase from Escherichia coli K-12 MG1655. Poor starting strain growth (<0.1 h –1 or none) was evolutionarily optimized to rates of up to 0.25 h –1 on xylose and 0.52 h –1 on galactose. Whole-genome sequencing, transcriptomic analysis, and growth screens revealed significant roles of kguT encoding a 2-ketogluconate operon repressor and 2-ketogluconate transporter, and gtsABCD encoding an ATP-binding cassette (ABC) sugar transporting system in xylose and galactose growth conditions, respectively. Finally, we expressed the heterologous indigoidine production pathway in the evolved and unevolved engineered strains and successfully produced 3.2 g/L and 2.2 g/L from 10 g/L of either xylose or galactose in the evolved strains whereas the unevolved strains did not produce any detectable product. Thus, the generated KT2440 strains have the potential for broad application as optimized platform chassis to develop efficient microorganism-based biomass-utilizing bioprocesses.
Generation of ionic liquid tolerant Pseudomonas putida KT2440 strains via adaptive laboratory evolution
Although the use of ionic liquids (ILs) for the pretreatment of lignocellulosic biomass has been limited due to high costs, recent efforts to develop low-cost protic ILs show promise for achieving cost-effectiveness for biorefineries. However, an additional challenge remains in that ILs present in biomass hydrolysates are toxic to most microbial hosts, resulting in poor growth phenotypes. To address this issue, we applied an adaptive laboratory evolution (ALE) approach for tolerizing Pseudomonas putida KT2440, an industrially relevant bacterial host, to two low-cost ILs (triethanolammonium acetate [TEOH][OAc] and triethylammonium hydrogen sulfate [TEA][HS]). After continuous cultivations with gradually increased IL levels, we obtained evolved strains showing significant improvements in their growth performance under high concentrations of the ILs (maximum 4% [TEOH][OAc] and 8% [TEA][HS], in w/v) at which the wild-type strain cannot grow. Sequencing of evolved strains revealed multiple regions where mutations were associated with improved performance in minimal media conditions (relA, gacS, oprB/PP_1446, fleQ, tktA, and uvrY/PP_4100) and in IL-specific conditions (PP_5350, PP_4929/emrE, oprD, and PP_5324). We further validated the causality of the PP_5350 and emrE genes for improved IL tolerance via reverse engineering and transcriptomic analysis. Here, a common mutation in the PP_5350 gene, encoding a RpiR family transcriptional regulator, was shown to significantly upregulate the glyoxylate cycle for efficient acetate catabolism. In addition, it was suggested that the emrE gene encodes an efflux pump which can export [TEA][HS]. Finally, the cultivation of two of the best performing evolved strains with IL-treated biomass hydrolysates demonstrated their considerable potential to be used as platform strains. Taken as a whole, this work provides strains for utilization of IL-treated biomass and a mechanistic understanding that could be further leveraged to develop efficient microbial bioprocesses.