Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Genome engineering”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Enzyme-mediated depletion of serum L -Met abrogates prostate cancer growth via multiple mechanisms without evidence of systemic toxicity

Extensive studies in prostate cancer and other malignancies have revealed that L -methionine ( L -Met) and its metabolites play a critical role in tumorigenesis. Preclinical and clinical studies have demonstrated that systemic restriction of serum L -Met, either via partial dietary restriction or with bacterial L -Met–degrading enzymes exerts potent antitumor effects. However, administration of bacterial L -Met–degrading enzymes has not proven practical for human therapy because of problems with immunogenicity. As the human genome does not encode L -Met–degrading enzymes, we engineered the human cystathionine-γ-lyase (hMGL-4.0) to catalyze the selective degradation of L -Met. At therapeutically relevant dosing, hMGL-4.0 reduces serum L -Met levels to >75% for >72 h and significantly inhibits the growth of multiple prostate cancer allografts/xenografts without weight loss or toxicity. We demonstrate that in vitro, hMGL-4.0 causes tumor cell death, associated with increased reactive oxygen species, S-adenosyl-methionine depletion, global hypomethylation, induction of autophagy, and robust poly(ADP-ribose) polymerase (PARP) cleavage indicative of DNA damage and apoptosis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Integration of Yeast Episomal/Integrative Plasmid Causes Genotypic and Phenotypic Diversity and Improved Sesquiterpene Production in Metabolically Engineered Saccharomyces cerevisiae

The variability in phenotypic outcomes among biological replicates in engineered microbial factories presents a captivating mystery. Establishing the association between phenotypic variability and genetic drivers is important to solve this intricate puzzle. Here, we applied a previously developed auxin-inducible depletion of hexokinase 2 as a metabolic engineering strategy for improved nerolidol production in Saccharomyces cerevisiae, and biological replicates exhibit a dichotomy in nerolidol production of either 3.5 or 2.5 g L –1 nerolidol. Harnessing Oxford Nanopore’s long-read genomic sequencing, we reveal a potential genetic cause—the chromosome integration of a 2μ sequence-based yeast episomal plasmid, encoding the expression cassettes for nerolidol synthetic enzymes. This finding was reinforced through chromosome integration revalidation, engineering nerolidol and valencene production strains, and generating a diverse pool of yeast clones, each uniquely fingerprinted by gene copy numbers, plasmid integrations, other genomic rearrangements, protein expression levels, growth rate, and target product productivities. Τhe best clone in two strains produced 3.5 g L –1 nerolidol and ~0.96 g L –1 valencene. Comparable genotypic and phenotypic variations were also generated through the integration of a yeast integrative plasmid lacking 2μ sequences. Our work shows that multiple factors, including plasmid integration status, subchromosomal location, gene copy number, sesquiterpene synthase expression level, and genome rearrangement, together play a complicated determinant role on the productivities of sesquiterpene product. Integration of yeast episomal/integrative plasmids may be used as a versatile method for increasing the diversity and optimizing the efficiency of yeast cell factories, thereby uncovering metabolic control mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Development of a CRISPR/Cas9 system for high efficiency multiplexed gene deletion in Rhodosporidium toruloides

The oleaginous yeast Rhodosporidium toruloides is considered a promising candidate for production of chemicals and biofuels thanks to its ability to grow on lignocellulosic biomass, and its high production of lipids and carotenoids. However, efforts to engineer this organism are hindered by a lack of suitable genetic tools. In this paper, we report the development of a CRISPR/Cas9 system for genome editing in R. toruloides based on a fusion 5S rRNA–tRNA promoter for guide RNA (gRNA) expression, capable of greater than 95% gene knockout for various genetic targets. Additionally, multiplexed double-gene knockout mutants were obtained using this method with an efficiency of 78%. Finally, this tool can be used to accelerate future metabolic engineering work in this yeast.

09 BIOMASS FUELS↗
DOE OSTI2024

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, and 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 .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Engineered Microorganisms for Enhanced Rare Earth Element Bio-mining and Separations (Final Technical Report)

Rare earth elements (REE) are critical ingredients of sustainable energy technologies, but their extraction from ore and separation from one another pose formidable challenges. To solve the challenge of REE supply, we used advanced genomics, high-throughput screening with synthetic REE minerals, and synthetic biology to engineer two sets of exotic microbes to (1) extract REE from ores, spent cracking catalysts, coal ash and electronic waste with high efficiency and selectivity, and (2) to purify REE into single element batches, all under benign conditions without the need of harsh solvents and high temperatures. This work integrated our expertise in systems and synthetic biology (Buz Barstow); rare-earth geochemistry (Esteban Gazel) and mineral synthesis (Megan Holycross); and microsystems engineering (Mingming Wu) by first elucidating the set of rules that predict an organism’s phenotype and then applying them to solve this critical problem in sustainable energy. These new technologies could help to revitalize the US rare earth industry and provide a new source of these critical elements for future energy technologies. We have already had some big success in tech transfer. Two of our team members (postdoctoral fellow Alexa Schmitz and graduate student Sean Medin) were able to study the supply chain for REE in the United States, and identify an opportunity to commercialize our REE mineral-dissolution technology. Alexa and Sean recently founded REEgen, Inc., an REE biomining company. Dr. Schmitz was recently awarded a fellowship from the Activate Foundation to support the first two years of REEgen. Cornell showed its support for this technology and company, and Dr. Schmitz was awarded the Rising Women Innovator’s award. These two awards unlocked support from Cornell’s Praxis Incubator.

58 GEOSCIENCES↗
DOE OSTI2024

DOE BSSD Performance Management Metrics Report Q1

Microbes play key roles in our biosphere, from driving global nutrient cycling to impacting plant, animal and human health and disease. Complex data from microbial genomes, proteins, and metabolites provide a window into these tiny engines that drive life on our planet. Yet these data are dispersed among researchers’ laboratories and various repositories, making it difficult to access. This calls for new ways of managing data, improving data interoperability, advancing community standards, and creating an infrastructure where data are shared efficiently. We have built the National Microbiome Data Collaborative (NMDC) to advance how scientists create, use, and reuse data to redefine the way we understand and harness the power of microbes. The vision of the National Microbiome Data Collaborative (NMDC) is to drive a microbiome data sharing network connecting data, people, and ideas to advance microbiome innovation and discovery. The NMDC was launched in 2019 and brought together DOE National Laboratories to collaborate across resources, capabilities, and expertise. The NMDC team was strategically assembled to include software developers, microbial researchers, metadata experts, and multi-omics specialists. The diversity of the NMDC team reflects the inherently interdisciplinary nature of microbiome science, and we leverage the strengths of the DOE National Laboratory system. Towards BER’s goal of advancing an iterative systems biology approach to the understanding of microbial genomes, the NMDC serves as a foundation for infrastructure, data standards, and community building. Together with the flagship DOE User Facilities, the Joint Genome Institute (JGI) and the Environmental Molecular Sciences Laboratory (EMSL), we are developing core capabilities in metadata standards for environmental descriptors and sample handling and processing; standardized bioinformatic workflows; an interface for data search and access; and robust community engagement activities. The NMDC production platform supports long-term data infrastructure and community building for BER’s bioenergy and environmental research goals. Our approach leverages lessons learned and an ambitious framework for collaborative, interdisciplinary data infrastructure to support microbiome research. The NMDC supports data, information, and knowledge access through three defined software tools – the Submission Portal, NMDC EDGE, and the Data Portal – driven by community needs. Herein, we describe the value proposition for the microbiome research community, our overarching strategy, and challenges and opportunities for developing the NMDC as both an infrastructure and community engagement program.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Data for "RT-EZ: A Golden Gate Assembly Toolkit for Streamlined Genetic Engineering of Rhodotorula toruloides"

For economic and sustainable biomanufacturing, the oleaginous yeast Rhodotorula toruloides has emerged as a promising platform for producing biofuels, pharmaceuticals, and other valuable chemicals. However, genetic manipulation of R. toruloides has been limited by its high GC content and the lack of a replicating plasmid, necessitating gene integration into the genome of the yeast. To address these challenges, we developed the RT-EZ ( R. toruloides Efficient Zipper) toolkit, a versatile tool based on Golden Gate assembly, designed to streamline R. toruloides engineering with improved efficiency and flexibility. The RT-EZ toolkit simplifies vector construction by incorporating new features such as bidirectional promoters and 2A peptides, color-based screening using RFP, and sequences optimized for both Agrobacterium tumefaciens-mediated transformation (ATMT) and easy linearization, enabling straightforward selection and transformation. Notably, the RT-EZ kit can be used to construct an expression cassette with four different genes in one assembly reaction, significantly improving vector construction speed and efficiency. The utility of the RT-EZ toolkit was demonstrated through the successful synthesis of arachidonic acid in R. toruloides by coexpressing fatty acid elongases and desaturases. This result underscores the potential of the RT-EZ toolkit to advance synthetic biology in R. toruloides , providing a streamlined method for addressing genetic engineering challenges in the yeast.

gene editing↗
DOE OSTI2020

Genome-Scale Transcription-Translation Mapping Reveals Features of Zymomonas mobilis Transcription Units and Promoters

Efforts to rationally engineer synthetic pathways in Zymomonas mobilis are impeded by a lack of knowledge and tools for predictable and quantitative programming of gene regulation at the transcriptional, posttranscriptional, and posttranslational levels. With the detailed functional characterization of the Z. mobilis genome presented in this work, we provide crucial knowledge for the development of synthetic genetic parts tailored to Z. mobilis . This information is vital as researchers continue to develop Z. mobilis for synthetic biology applications. Our methods and statistical analyses also provide ways to rapidly advance the understanding of poorly characterized bacteria via empirical data that enable the experimental validation of sequence-based prediction for genome characterization and annotation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A KBase Case Study on Genome-wide Transcriptomics and Plant Primary Metabolism in Sorghum

A better understanding of the genetic and metabolic mechanisms that confer stress resistance and tolerance in plants is key to engineering new crops through advanced breeding technologies. This requires a systems biology approach that builds on a genome-wide understanding of the regulation of gene expression, plant metabolism, physiology and growth. In this study, we examine the response to drought stress in Sorghum, as we leverage the tools for transcriptomics and plant metabolic modeling we have implemented at the U.S. Department of Energy Systems Biology Knowledgebase (KBase). KBase enables researchers worldwide to collaborate and advance research by allowing them to upload private or public data into the KBase Narrative Interface, empowering them to analyze this data using a rich, extensible array of computational and data-analytics tools, and allows them to securely share scientific workflows and conclusions. We demonstrate how to use the current RNA-seq tools in KBase, applicable to both plants and microbes, to assemble and quantify long transcripts and identify differentially expressed genes effectively. More specifically, we demonstrate the utility of the platform by identifying key genes that are differentially expressed during drought-stress in Sorghum bicolor, which is an important sustainable production crop plant. We then show how to use KBase tools to predict the membership of genes in metabolic pathways and examine expression data in the context of metabolic subsystems. We demonstrate the power of the platform by making the data analysis and interpretation available to the biologists in the reproducible, re-usable, point-and-click format of a KBase Narrative thus promoting FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles for scientific data management and stewardship.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

CRISPR/Cas9-based gene activation and base editing in Populus

The genus Populus has long been used for environmental, agroforestry and industrial applications worldwide. Today Populus is also recognized as a desirable crop for biofuel production and a model tree for physiological and ecological research. As such, various modern biotechnologies, including CRISPR/Cas9-based techniques, have been actively applied to Populus for genetic and genomic improvements for traits such as increased growth rate and tailored lignin composition. However, CRISPR/Cas9 has been primarily used as the active Cas9 form to create knockouts in the hybrid poplar clone “717-1B4” (P. tremula x P. alba clone INRA 717-1B4). Alternative CRISPR/Cas9-based technologies, e.g. those involving modified Cas9 for gene activation and base editing, have not been evaluated in most Populus species for their efficacy. Here we employed a deactivated Cas9 (dCas9)-based CRISPR activation (CRISPRa) technique to fine-tune the expression of two target genes, TPX2 and LecRLK-G which play important roles in plant growth and defense response, in hybrid poplar clone “717-1B4” and poplar clone “WV94” (P. deltoides “WV94”), respectively. We observed that CRISPRa resulted in 1.2-fold to 7.0-fold increase in target gene expression through transient expression in protoplasts and Agrobacterium-mediated stable transformation, demonstrating the effectiveness of dCas9-based CRISPRa system in Populus. In addition, we applied Cas9 nickase (nCas9)-based cytosine base editor (CBE) to precisely introduce premature stop codons via C-to-T conversion, with an efficiency of 13%–14%, in the target gene PLATZ which encodes a transcription factor involved in plant fungal pathogen response in hybrid poplar clone “717-1B4”. Overall, we showcase the successful application of CRISPR/Cas-based technologies in gene expression regulation and precise gene engineering in two Populus species, facilitating the adoption of emerging genome editing tools in woody species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Camelina sativa , an oilseed at the nexus between model system and commercial crop

The rapid assessment of metabolic engineering strategies in plants is aided by crops that provide simple, high throughput transformation systems, a sequenced genome, and the ability to evaluate the resulting plants in field trials. Camelina sativa provides all of these attributes in a robust oilseed platform. The ability to perform field evaluation of Camelina is a useful, and in some studies essential benefit that allows researchers to evaluate how traits perform outside the strictly controlled conditions of a greenhouse. In the field the plants are subjected to higher light intensities, seasonal diurnal variations in temperature and light, competition for nutrients, and watering regimes dictated by natural weather patterns, all which may affect trait performance. There are difficulties associated with the use of Camelina . The current genetic resources available for Camelina pale in comparison to those developed for the model plant Arabidopsis thaliana; however, the sequence similarity of the Arabidopsis and Camelina genomes often allows the use of Arabidopsis as a reference when additional information is needed. Camelina ’s genome, an allohexaploid, is more complex than other model crops, but the diploid inheritance of its three subgenomes is straightforward. The need to navigate three copies of each gene in genome editing or mutagenesis experiments adds some complexity but also provides advantages for gene dosage experiments. In conclusion, the ability to quickly engineer Camelina with novel traits, advance generations, and bulk up homozygous lines for small-scale field tests in less than a year, in our opinion, far outweighs the complexities associated with the crop.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Tailoring poplar lignin without yield penalty by combining a null and haploinsufficient CINNAMOYL-CoA REDUCTASE2 allele

Lignin causes lignocellulosic biomass recalcitrance to enzymatic hydrolysis. Engineered low-lignin plants have reduced recalcitrance but often exhibit yield penalties, offsetting their gains in fermentable sugar yield. Here, CRISPR/Cas9-generated CCR2(–/*) line 12 poplars have one knockout CCR2 allele while the other contains a 3-bp deletion, resulting in a 114I115A-to-114T conversion in the corresponding protein. Despite having 10% less lignin, CCR2(–/*) line 12 grows normally. On a plant basis, the saccharification efficiency of CCR2(–/*) line 12 is increased by 25–41%, depending on the pretreatment. Analysis of monoallelic CCR2 knockout lines shows that the reduced lignin amount in CCR2(–/*) line 12 is due to the combination of a null and the specific haploinsufficient CCR2 allele. Analysis of another CCR2(–/*) line shows that depending on the specific CCR2 amino-acid change, lignin amount and growth can be affected to different extents. Furthermore, our findings open up new possibilities for stably fine-tuning residual gene function in planta.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Use of Fluorescent Protein Reporters for Assessing and Detecting Genome Editing Reagents and Transgene Expression in Plants

Fluorescent protein reporters have been widely used for monitoring the expression of target genes in various engineered organisms. Although a wide range of analytical approaches (e.g., genotyping PCR, digital PCR, DNA sequencing) have been utilized to detect and identify genome editing reagents and transgene expression in genetically modified plants, these methods are usually limited to use in the late stages of plant transformation and can only be used invasively. Here we describe GFP- and eYGFPuv-based strategies and methods for assessing and detecting genome editing reagents and transgene expression in plants, including protoplast transformation, leaf infiltration, and stable transformation. These methods and strategies enable easy, noninvasive screening of genome editing and transgenic events in plants.

Yuan, Guoliang↗
DOE OSTI2023

Genomic materials design: CALculation of PHAse Dynamics

The CALPHAD system of fundamental phase-level databases, now known as the Materials Genome, has enabled a mature technology of computational materials design and qualification that has already met the acceleration goals of the national Materials Genome Initiative. Here, as first commercialized by QuesTek Innovations, the methodology combines efficient genomic-level parametric design of new material composition and process specifications with multidisciplinary simulation-based forecasting of manufacturing variation, integrating efficient uncertainty management. Recent projects demonstrated under the multi-institutional CHiMaD Design Center notably include novel alloys designed specifically for additive manufacturing. With the proven success of the CALPHAD-based Materials Genome technology, current university research emphasizes new methodologies for affordable accelerated expansion of more accurate CALPHAD databases. Rapid adoption of these new capabilities by US apex corporations has compressed the materials design and development cycle to under 2 years, enabling a new “materials concurrency” integrated into a new level of concurrent engineering supporting an unprecedented level of manufacturing innovation.

36 MATERIALS SCIENCE↗
DOE OSTI2015

A roadmap for research on crassulacean acid metabolism (CAM) to enhance sustainable food and bioenergy production in a hotter, drier world

Crassulacean acid metabolism (CAM) is a specialized mode of photosynthesis that features nocturnal CO₂ uptake, facilitates increased water-use efficiency (WUE), and enables CAM plants to inhabit water-limited environments such as semi-arid deserts or seasonally dry forests. Human population growth and global climate change now present challenges for agricultural production systems to increase food, feed, forage, fiber, and fuel production. One approach to meet these challenges is to increase reliance on CAM crops, such as Agave and Opuntia , for biomass production on semi-arid, abandoned, marginal, or degraded agricultural lands. Major research efforts are now underway to assess the productivity of CAM crop species and to harness the WUE of CAM by engineering this pathway into existing food and bioenergy crops. An improved understanding of CAM gained through intensive and expanded research efforts has potential for high returns on research investment in the foreseeable future. To help realize the potential of sustainable dryland agricultural systems, it is necessary to address scientific questions related to the genomic features, regulatory mechanisms, and evolution of CAM; CAM-into-C3 engineering; and the production of CAM crops. Answering these questions requires collaborative efforts to build infrastructure for CAM model systems, field trials, mutant collections, and data management.

09 BIOMASS FUELS↗
DOE OSTI2025

Inducible flippase-mediated metabolic engineering of Rhodosporidium toruloides for enhanced 3-hydroxypropionic acid production from corn stover hydrolysate

Rhodosporidium toruloides has gained increasing interests as a promising non-model host organism to produce a wide range of bioproducts from lignocellulosic biomass. Increasing the bioproduct titers, rates, and yields remains a challenge, largely due to a lack of robust and well-characterized genetic tools in this host. Here we developed an inducible flippase (FLP) and flippase recognition target (FRT) system that enables genetic manipulations without the need for additional selection markers. Synthetic inducible promoters were established, enabling regulation of FLP expression and efficient antibiotic marker removal. Leveraging this system, we engineered a strain to optimize 3-hydroxypropionic acid (3HP) production. Over four rounds of iterative genomic editing to resolve pathway bottlenecks, we achieved a 3HP titer of 69.4 g/L in fed-batch fermentation - the highest level reported in yeast from lignocellulosic hydrolysates. The engineered high 3HP producing strain offers a robust platform for sustainable bio-based chemical production from lignocellulosic feedstocks.

3-hydroxypropionic acid↗
DOE OSTI2014

The OME Framework for genome-scale systems biology

The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed. However, few of these tools have been forced to deal with the full complexity of genome-scale models along with high throughput genome-scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind. It is also evident that, given the plethora of databases and software efforts, it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models. We work at the forefront of model creation and systems scale data generation. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale metabolic models or for genome-scale data analysis, no implementations exist that explicitly handle data and models concurrently. The OME Framework structures data in a connected loop with models and the components those models are composed of. This results in the first full, practical implementation of a framework that can enable genome-scale design-build-test. Over the coming years many more software packages will be developed and tools will necessarily change. However, we hope that the underlying designs shared here can help to inform the design of future software.

59 BASIC BIOLOGICAL SCIENCES↗