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  1. Systematic engineering for production of anti-aging sunscreen compound in Pseudomonas putida

    Sunscreen has been used for thousands of years to protect skin from ultraviolet radiation. However, the use of modern commercial sunscreen containing oxybenzone, ZnO, and TiO2 has raised concerns due to their negative effects on human health and the environment. In this study, we aim to establish an efficient microbial platform for production of shinorine, a UV light absorbing compound with anti-aging properties. First, we methodically selected an appropriate host for shinorine production by analyzing central carbon flux distribution data from prior studies alongside predictions from genome-scale metabolic models (GEMs). We enhanced shinorine productivity through CRISPRi-mediated downregulation and utilized shotgunmore » proteomics to pinpoint potential competing pathways. Simultaneously, we improved the shinorine biosynthetic pathway by refining its design, optimizing promoter usage, and altering the strength of ribosome binding sites. Finally, we conducted amino acid feeding experiments under various conditions to identify the key limiting factors in shinorine production. The study combines meta-analysis of 13C-metabolic flux analysis, GEMs, synthetic biology, CRISPRi-mediated gene downregulation, and omics analysis to improve shinorine production, demonstrating the potential of Pseudomonas putida KT2440 as platform for shinorine production.« less
  2. Genome-scale model development and genomic sequencing of the oleaginous clade Lipomyces

    The Lipomyces clade contains oleaginous yeast species with advantageous metabolic features for biochemical and biofuel production. Limited knowledge about the metabolic networks of the species and limited tools for genetic engineering have led to a relatively small amount of research on the microbes. Here, a genome-scale metabolic model (GSM) of Lipomyces starkeyi NRRL Y-11557 was built using orthologous protein mappings to model yeast species. Phenotypic growth assays were used to validate the GSM (66% accuracy) and indicated that NRRL Y-11557 utilized diverse carbohydrates but had more limited catabolism of organic acids. The final GSM contained 2,193 reactions, 1,909 metabolites, andmore » 996 genes and was thus named iLst996. The model contained 96 of the annotated carbohydrate-active enzymes. iLst996 predicted a flux distribution in line with oleaginous yeast measurements and was utilized to predict theoretical lipid yields. Twenty-five other yeasts in the Lipomyces clade were then genome sequenced and annotated. Sixteen of the Lipomyces species had orthologs for more than 97% of the iLst996 genes, demonstrating the usefulness of iLst996 as a broad GSM for Lipomyces metabolism. Pathways that diverged from iLst996 mainly revolved around alternate carbon metabolism, with ortholog groups excluding NRRL Y-11557 annotated to be involved in transport, glycerolipid, and starch metabolism, among others. Overall, this study provides a useful modeling tool and data for analyzing and understanding Lipomyces species metabolism and will assist further engineering efforts in Lipomyces.« less
  3. Advances in genome-scale metabolic models of industrially important fungi

    Many fungal species have been used in industrial production for biofuels and bioproducts. Developing strains with better performance in biomanufacturing requires systematic understanding of cellular metabolism. Genome-scale metabolic models (GEMs) offer a comprehensive view of interconnected pathways and a mathematical framework for downstream analysis. Recently, GEMs have been developed or updated in several industrially important fungi. Some of them incorporate enzyme constraints, enabling improved predictions of cell states and proteome allocation. In this report we provide an overview of these newly developed GEMs and computational methods that facilitate construction of enzyme-constrained GEMs and utilize flux predictions from GEMs. Furthermore, wemore » highlight the pivotal roles of these GEMs in iterative design-build-test- learn cycles, ultimately advancing the field of fungal biomanufacturing.« less
  4. Identification of a specific exporter that enables high production of aconitic acid in Aspergillus pseudoterreus

    Aconitic acid is an unsaturated tricarboxylic acid that is attractive for its potential use in the manufacture of biodegradable and biocompatible polymers, plasticizers, and surfactants. Previously Aspergillus pseudoterreus was engineered as a platform to produce aconitic acid by deleting the cadA (cis-aconitic acid decarboxylase) gene in the itaconic acid biosynthetic pathway. In this study aconitic acid transporter gene (aexA) was identified using comparative global discovery proteomics analysis between the wild-type and cadA deletion strains. Deletion of aexA almost eliminated aconitic acid secretion, while its overexpression led to a significant increase in aconitic acid production. Transportation of aconitic acid across themore » plasma membrane is a key limiting step. In vitro proteoliposome transport assay further validated AexA’s function and its substrate specificity. This research provides new approaches to efficiently pinpoint and characterize exporters of fungal organic acids and accelerate the metabolic engineering to improve secretion capability and lower cost for bioproduction.« less
  5. Rapid and robust squashed spore/colony PCR of industrially important fungi

    Fungi have been utilized for centuries in medical, agricultural, and industrial applications. Development of systems biology techniques has enabled the design and metabolic engineering of these fungi to produce novel fuels, chemicals, and enzymes from renewable feedstocks. Many genetic tools have been developed for manipulating the genome and creating mutants rapidly. However, screening and confirmation of transformants remain an inefficient step within the design, build, test, and learn cycle in many industrial fungi because extracting fungal genomic DNA is laborious, time-consuming, and involves toxic chemicals. In this study we developed a rapid and robust technique called “Squash-PCR” to break openmore » the spores and release fungal genomic DNA as a template for PCR. The efficacy of Squash-PCR was investigated in eleven different filamentous fungal strains. Clean PCR products with high yields were achieved in all tested fungi. Spore age and type of DNA polymerase did not affect the efficiency of Squash-PCR. However, spore concentration was found to be the crucial factor for Squash-PCR in Aspergillus niger, with the dilution of starting material often resulting in higher PCR product yield. We then further evaluated the applicability of the squashing procedure for nine different yeast strains. We found that Squash-PCR can be used to improve the quality and yield of colony PCR in comparison to direct colony PCR in the tested yeast strains. The developed technique will enhance the efficiency of screening transformants and accelerate genetic engineering in filamentous fungi and yeast.« less
  6. A High-Quality Genome-Scale Model for Rhodococcus opacus Metabolism

  7. Engineering Rhodosporidium toruloides for production of 3-hydroxypropionic acid from lignocellulosic hydrolysate

    Microbial production of valuable bioproducts is a promising route towards green and sustainable manufacturing. The oleaginous yeast, Rhodosporidium toruloides, has emerged as an attractive host for the production of biofuels and bioproducts from lignocellulosic hydrolysates. 3-hydroxypropionic acid (3HP) is an attractive platform molecule that can be used to produce a wide range of commodity chemicals. This study focuses on establishing and optimizing the production of 3HP in R. toruloides. As R. toruloides naturally has a high metabolic flux towards malonyl-CoA, we exploited this pathway to produce 3HP. Upon finding the yeast capable of catabolizing 3HP, we then implemented functional genomicsmore » and metabolomic analysis to identify the catabolic pathways. Deletion of a putative malonate semialdehyde dehydrogenase gene encoding an oxidative 3HP pathway was found to significantly reduce 3HP degradation. We further explored monocarboxylate transporters to promote 3HP transport and identified a novel 3HP transporter in Aspergillus pseudoterreus by RNA-seq and proteomics. Combining these engineering efforts with media optimization in a fed-batch fermentation resulted in 45.4 g/L 3HP production. This represents one of the highest 3HP titers reported, and the highest titer produced from lignocellulosic hydrolysate to the best of our knowledge. This work demonstrates microbial production of 3HP in R. toruloides from lignocellulosic hydrolysate at high titers, and it represents a significant step toward enabling industrial production of 3HP in the future.« less
  8. Metabolic engineering to improve production of 3-hydroxypropionic acid from corn-stover hydrolysate in Aspergillus species

    Fuels and chemicals derived from non-fossil sources are needed to lessen human impacts on the environment while providing a healthy and growing economy. 3-hydroxypropionic acid (3-HP) is an important chemical building block that can be used for many products. Biosynthesis of 3-HP is possible; however, low production is typically observed in those natural systems. Biosynthetic pathways have been designed to produce 3-HP from a variety of feedstocks in different microorganisms. In this study, the 3-HP β-alanine pathway consisting of aspartate decarboxylase, β-alanine-pyruvate aminotransferase, and 3-hydroxypropionate dehydrogenase from selected microorganisms were codon optimized for Aspergillus species and placed under the controlmore » of constitutive promoters. The pathway was introduced into Aspergillus pseudoterreus and subsequently into Aspergillus niger, and 3-HP production was assessed in both hosts. A. niger produced higher initial 3-HP yields and fewer co-product contaminants and was selected as a suitable host for further engineering. Proteomic and metabolomic analysis of both Aspergillus species during 3-HP production identified genetic targets for improvement of flux toward 3-HP including pyruvate carboxylase, aspartate aminotransferase, malonate semialdehyde dehydrogenase, succinate semialdehyde dehydrogenase, oxaloacetate hydrolase, and a 3-HP transporter. Overexpression of pyruvate carboxylase improved yield in shake-flasks from 0.09 to 0.12 C-mol 3-HP C-mol-1 glucose in the base strain expressing 12 copies of the β-alanine pathway. Deletion or overexpression of individual target genes in the pyruvate carboxylase overexpression strain improved yield to 0.22 C-mol 3-HP C-mol-1 glucose after deletion of the major malonate semialdehyde dehydrogenase. Further incorporation of additional β-alanine pathway genes and optimization of culture conditions (sugars, temperature, nitrogen, phosphate, trace elements) for 3-HP production from deacetylated and mechanically refined corn stover hydrolysate improved yield to 0.48 C-mol 3-HP C-mol-1 sugars and resulted in a final titer of 36.0 g/L 3-HP. The results of this study establish A. niger as a host for 3-HP production from a lignocellulosic feedstock in acidic conditions and demonstrates that 3-HP titer and yield can be improved by a broad metabolic engineering strategy involving identification and modification of genes participated in the synthesis of 3-HP and its precursors, degradation of intermediates, and transport of 3-HP across the plasma membrane.« less
  9. PeakDecoder enables machine learning-based metabolite annotation and accurate profiling in multidimensional mass spectrometry measurements

    Multidimensional measurements using state-of-the-art separations and mass spectrometry provide advantages in untargeted metabolomics analyses for studying biological and environmental bio-chemical processes. However, the lack of rapid analytical methods and robust algorithms for these heterogeneous data has limited its application. Here, we develop and evaluate a sensitive and high-throughput analytical and computational workflow to enable accurate metabolite profiling. Our workflow combines liquid chromatography, ion mobility spectrometry and data-independent acquisition mass spectrometry with PeakDecoder, a machine learning-based algorithm that learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates. We apply PeakDecoder for metabolite profiling ofmore » various engineered strains of Aspergillus pseudoterreus, Aspergillus niger, Pseudomonas putida and Rhodosporidium toruloides. Results, validated manually and against selected reaction monitoring and gas-chromatography platforms, show that 2683 features could be confidently annotated and quantified across 116 microbial sample runs using a library built from 64 standards.« less
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"Kim, Joonhoon"

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