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 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Dissecting the metabolic reprogramming of maize root under nitrogen-deficient stress conditions

The growth and development of maize (Zea mays L.) largely depends on its nutrient uptake through the root. Hence, studying its growth, response, and associated metabolic reprogramming to stress conditions is becoming an important research direction. A genome-scale metabolic model (GSM) for the maize root was developed to study its metabolic reprogramming under nitrogen stress conditions. The model was reconstructed based on the available information from KEGG, UniProt, and MaizeCyc. Transcriptomics data derived from the roots of hydroponically grown maize plants were used to incorporate regulatory constraints in the model and simulate nitrogen-non-limiting (N+) and nitrogen-deficient (N-) condition. Model-predicted flux-sum variability analysis achieved 70% accuracy compared with the experimental change of metabolite levels. In addition to predicting important metabolic reprogramming in central carbon, fatty acid, amino acid, and other secondary metabolism, maize root GSM predicted several metabolites (l-methionine, l-asparagine, l-lysine, cholesterol, and l-pipecolate) playing a regulatory role in the root biomass growth. Furthermore, this study revealed eight phosphatidylcholine and phosphatidylglycerol metabolites which, even though not coupled with biomass production, played a key role in the increased biomass production under N-deficient conditions. Overall, the omics-integrated GSM provides a promising tool to facilitate stress condition analysis for maize root and engineer better stress-tolerant maize genotypes.

Plant Sciences↗
DOE OSTI2018

Asparagine synthetase gene regulatory network and plant nitrogen metabolism

This DOE project concerns the molecular mechanisms by which plants coordinate carbon (C) and nitrogen (N) metabolism. Specifically, it focuses on a histone methyltransferase protein that targets C/N-metabolism genes for chromatin modifications. How the dynamic changes of chromatin regulate energy metabolism in response to developmental and environmental cues is a new area of study. We have filled this knowledge-gap with our studies of SDG8, a histone methyltransferase, that targets light, C and N metabolism genes. We aimed to understand how plants allocate C resources to assimilate inorganic N onto C-skeletons -- the most energy-intensive pathway in plants – in order to balance energy production and consumption in a changing environment. In order to achieve more C-efficient N-storage under low energy conditions, plants convert assimilated N from “reactive” Gln (C5:N2) into “inert” Asn (C4:N2) through the enzyme ASN1. To identify regulatory factors in this pathway, we used the ASN1 promoter in a genetic selection and discovered SDG8, a histone methyltransferase. We discovered that histone modification by SDG8 coordinates the expression of genes involved in energy generation (light-harvesting and C fixation) with energy consumption (N assimilation and sulfur metabolism). We used this opportunity to explore how histone modifications control energy metabolism genome-wide. Our aims focus on various levels of the regulation of energy related genes at the level of: 1) Chromatin; 2) Transcription; and 3) Metabolites of the C/N regulatory network. Specifically, we asked: 1) How does histone methylation regulate energy metabolism during the N response? 2) How does histone methylation control transcription of the energy metabolism genes? And 3) how does the histone methyltransferase SDG8 and other TF regulators affect C/N metabolism and N use efficiency? Our study indicates that N supply triggers genome-wide changes in chromatin modification via the histone methyltransferase SDG8 which impacts on gene expression, RNA processing, chlorophyll synthesis, N uptake and metabolism. Our study thus revealed a previously overlooked layer of chromatin regulation during nutrient signaling. In broad terms, our study provides a framework to understand how chromatin modifications influence responses to environmental changes and provides unique opportunities for breeding and engineering resilient crops with better performance in the current climate model. Accomplishments AIM 1 CHROMATIN: Role of histone methylation in the ASN1 energy metabolism network. This aim focuses on understanding the role of chromatin modification in response to the environment. We studied the targeting mechanism of histone methylation by SDG8, in particular the role of the CW domain in reading histone methylation status. We also began to study the effect of nitrogen-treatment on genome-wide chromatin modifications in WT and sdg8 mutant plants. AIM 2 TRANSCRIPTION: Transcription control of the ASN1 energy metabolism network. This aim investigated whether SDG8 and the histone modification it mediates affects mRNA processing. We performed genome-wide profiling that uncovered that histone methylation by SDG8 affects the co-transcriptional RNA processing of downstream genes involved in energy and photosynthesis. AIM 3 METABOLISM: A gene regulatory network controlling energy, C/N metabolism and N use efficiency. In Aim 3A, we showed that SDG8 affects the chromatin modification and expression of a transcription factor, CCT, which in turn affects the regulation of carbon responsive genes. In Aim 3B we showed that C and N metabolism is perturbed in the sdg8 mutant through differences in the chlorophyll content, free amino acids, and N uptake. Project activities In Aim 1, we uncovered that the histone methyltransferase SDG8 affects chromatin modification in response to N treatments. The N treatments causes changes in the H3K36me3 distribution off ~200 genes in WT plants, while the N-triggered changes in H3K36me3 of these genes is abrogated in the sdg8-5 mutant. The functional annotation of these 200 genes shows significant enrichment of N-related pathways. Overall, our study suggests that SDG8 mediates chromatin-level adaption of functionally relevant genes in response to changes in N. In Aim 2, we tested if SDG8 plays a role in transcriptional elongation and/or RNA processing. We detected more N-triggered isoform shifting events in the sdg8-5 mutant than in WT, which provides supports for SDG8 being required for proper RNA processing in response to N signaling. In Aim 3, we identified the gene network controlled by a CCT transcription factor under the epigenetic control of SDG8. Isoform abundance of the CCT protein is regulated by SDG8, which leads to an altered response of energy related genes to N level changes. Using physiological, metabolic and genetic approaches, we found that responses to N, including chlorophyll accumulation, N uptake and free amino acids, are altered in sdg8 mutants. Finally, this project provided training to a high school student who performed experiments on the complex interaction of photosynthesis and N availability. The student was named a semi-finalist in both the Regeneron and Siemens National Science competitions for her work.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Investigation of inter- and intraspecies variation through genome sequencing of Aspergillus section Nigri

Aspergillus section Nigri comprises filamentous fungi relevant to biomedicine, bioenergy, health, and biotechnology. In order to learn more about fungal speciation, as well as potential for applications in biotechnology and biomedicine, we sequenced 23 genomes de novo, forming a full genome compendium for the section (26 species), as well as six A. niger isolates. This allowed us to quantify both inter- and intra-species genomic variation. We further predicted 17,903 CAZymes and 2,717 secondary metabolite gene clusters, which we condensed into 455 distinct families corresponding to compound classes, 49% of which are only found in single species. We performed metabolomics and genetic engineering to correlate genotypes to phenotypes, as demonstrated for the metabolite aurasperone, and by heterologous transfer of citrate production to A. nidulans. Experimental and computational analyses all supported a role in speciation for secondary metabolism and regulators and allowed us to propose a three-step model for fungal speciation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Data for Influence of Particle Size on NIR Spectroscopic Characterization of Sorghum Biomass for the Biofuel Industry

NIR spectroscopy is a rapid and accurate green technology for high-throughput biomass characterization, including sorghum ( Sorghum bicolor ), a promising energy crop for the biofuel industry. This study assessed the influence of particle size on NIR spectroscopic analysis (wavelength range: 867–2535 nm) of sorghum biomass composition. Grown under field conditions, a total of 113 types of genetically diverse sorghum accessions were dried, ground, and sieved (<250, 250–600, 600–850, and > 850 µm particle size) for developing partial least square regression (PLSR) prediction models for moisture, ash, extractive, glucan, xylan, acid-soluble lignin (ASL), acid-insoluble lignin (AIL), and total lignin (ASL + AIL). Overall, smaller particle sizes provided better model performance, while no single particle size provided the best performance for all the selected components. With only 9 selected bands and 4 latent variables (LVs), the best PLSR model was obtained for moisture with particle size of 600–850 µm with the square root of the coefficient of determination (R) of 0.85, the ratio of prediction to deviation (RPD) of 2.2, and the root mean square error (RMSE) of 0.46 % in external validation. Similar model performances were also obtained for ash, extractive, glucan, and xylan. This study showed that size reduction could effectively improve NIR spectroscopic analysis for lipid-producing sorghum biomass for the biofuel industry.

Biomass Analytics↗
DOE OSTI2018

2nd International Conference on Plant Synthetic Biology, Bioengineering, and Biotechnology

Plant synthetic biology uses enabling approaches from engineering and plants as platforms to produce self-sustaining and photosynthetic driven traits and bio-production. The field is rapidly expanding, as many technologies have the potential of solving problems from a variety of industries, such as energy, healthcare, agriculture, and more. The goal of the 2nd International Conference on Plant Synthetic Biology, Bioengineering, and Biotechnology was to bring together scientists and engineers from universities, industry and government working in all aspects of plant synthetic biology, plant bioengineering and plant biotechnology. The conference addressed different aspects of the field from tools to design predictable functions and precision genome editing, to designed photosynthesis, plant bioengineering techniques, and rational design of novel plant traits.

Levesque-Tremblay, Gabriel↗
DOE OSTI2022

Computational design and engineering of an Escherichia coli strain producing the nonstandard amino acid para -aminophenylalanine

Introducing heterologous pathways into host cells constitutes a promising strategy for synthesizing nonstandard amino acids (nsAAs) to enable the production of proteins with expanded chemistries. However, this strategy has proven challenging, as the expression of heterologous pathways can disrupt cellular homeostasis of the host cell. Here, we sought to optimize the heterologous production of the nsAA para -aminophenylalanine (pAF) in Escherichia coli . First, we incorporated a heterologous pAF biosynthesis pathway into a genome-scale model of E. coli metabolism and computationally identified metabolic interventions in the host’s native metabolism to improve pAF production. Next, we explored different approaches of imposing these flux interventions experimentally and found that the upregulation of flux in the chorismate biosynthesis pathway through the elimination of feedback inhibition mechanisms could significantly raise pAF titers (~20-fold) while maintaining a reasonable pAF production-growth rate trade-off. Overall, this study provides a promising strategy for the biosynthesis of nsAAs in engineered cells.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Population Level Analysis of Evolved Mutations Underlying Improvements in Plant Hemicellulose and Cellulose Fermentation by Clostridium phytofermentans

The complexity of plant cell walls creates many challenges for microbial decomposition. Clostridium phytofermentans, an anaerobic bacterium isolated from forest soil, directly breaks down and utilizes many plant cell wall carbohydrates. The objective of this research is to understand constraints on rates of plant decomposition by Clostridium phytofermentans and identify molecular mechanisms that may overcome these limitations. Experimental evolution via repeated serial transfers during exponential growth was used to select for C. phytofermentans genotypes that grow more rapidly on cellobiose, cellulose and xylan. To identify the underlying mutations an average of 13,600,000 paired-end reads were generated per population resulting in ~300 fold coverage of each site in the genome. Mutations with allele frequencies of 5% or greater could be identified with statistical confidence. Many mutations are in carbohydrate-related genes including the promoter regions of glycoside hydrolases and amino acid substitutions in ABC transport proteins involved in carbohydrate uptake, signal transduction sensors that detect specific carbohydrates, proteins that affect the export of extracellular enzymes, and regulators of unknown specificity. Structural modeling of the ABC transporter complex proteins suggests that mutations in these genes may alter the recognition of carbohydrates by substrate-binding proteins and communication between the intercellular face of the transmembrane and the ATPase binding proteins. Experimental evolution was effective in identifying molecular constraints on the rate of hemicellulose and cellulose fermentation and selected for putative gain of function mutations that do not typically appear in traditional molecular genetic screens. The results reveal new strategies for evolving and engineering microorganisms for faster growth on plant carbohydrates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Genetic variation at transcription factor binding sites largely explains phenotypic heritability in maize

Abstract Comprehensive maps of functional variation at transcription factor (TF) binding sites (cis-elements) are crucial for elucidating how genotype shapes phenotype. Here, we report the construction of a pan-cistrome of the maize leaf under well-watered and drought conditions. We quantified haplotype-specific TF footprints across a pan-genome of 25 maize hybrids and mapped over 200,000 variants, genetic, epigenetic, or both (termed binding quantitative trait loci (bQTL)), linked tocis-element occupancy. Three lines of evidence support the functional significance of bQTL: (1) coincidence with causative loci that regulate traits, includingvgt1,ZmTRE1and the MITE transposon nearZmNAC111under drought; (2) bQTL allelic bias is shared between inbred parents and matches chromatin immunoprecipitation sequencing results; and (3) partitioning genetic variation across genomic regions demonstrates that bQTL capture the majority of heritable trait variation across ~72% of 143 phenotypes. Our study provides an auspicious approach to make functionalcis-variation accessible at scale for genetic studies and targeted engineering of complex traits.

Genetics & Heredity↗
DOE OSTI2018

Uncovering secondary metabolite evolution and biosynthesis using gene cluster networks and genetic dereplication

Abstract The increased interest in secondary metabolites (SMs) has driven a number of genome sequencing projects to elucidate their biosynthetic pathways. As a result, studies revealed that the number of secondary metabolite gene clusters (SMGCs) greatly outnumbers detected compounds, challenging current methods to dereplicate and categorize this amount of gene clusters on a larger scale. Here, we present an automated workflow for the genetic dereplication and analysis of secondary metabolism genes in fungi. Focusing on the secondary metabolite rich genus Aspergillus , we categorize SMGCs across genomes into SMGC families using network analysis. Our method elucidates the diversity and dynamics of secondary metabolism in section Nigri , showing that SMGC diversity within the section has the same magnitude as within the genus. Using our genome analysis we were able to predict the gene cluster responsible for biosynthesis of malformin, a potentiator of anti-cancer drugs, in 18 strains. To proof the general validity of our predictions, we developed genetic engineering tools in Aspergillus brasiliensis and subsequently verified the genes for biosynthesis of malformin.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

DRAM for distilling microbial metabolism to automate the curation of microbiome function

Abstract Microbial and viral communities transform the chemistry of Earth's ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotation of Metabolism), a framework to translate the deluge of microbiome-based genomic information into a catalog of microbial traits. To demonstrate the applicability of DRAM across metabolically diverse genomes, we evaluated DRAM performance on a defined, in silico soil community and previously published human gut metagenomes. We show that DRAM accurately assigned microbial contributions to geochemical cycles and automated the partitioning of gut microbial carbohydrate metabolism at substrate levels. DRAM-v, the viral mode of DRAM, established rules to identify virally-encoded auxiliary metabolic genes (AMGs), resulting in the metabolic categorization of thousands of putative AMGs from soils and guts. Together DRAM and DRAM-v provide critical metabolic profiling capabilities that decipher mechanisms underpinning microbiome function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Elucidating Mechanisms of Rust Pathogenesis for Engineering Resistance in Poplar

The overall objective of this research was to elucidate the molecular basis for the virulence of Melampsora larici-populina towards Populus spp. in order to address the formidable challenge of engineering durable resistance in poplar against leaf rust. Our original research plan was built on the technically innovative approach of using dual host systems and known host defense proteins and pathogen avirulent effectors along with genome-wide approaches to identify key pathogenesis effectors of Melampsora larici-populina that target poplar defense and nutrient acquisition. Our efforts focused on developing high-throughput experimental approaches and systems to enable us to address our overarching hypothesis that rust effectors with homology to other fungal effectors will either bypass the poplar immune system and/or suppress effector-triggered immunity through conserved mechanisms, and that an analysis of these interaction networks would provide for new approaches to develop rust-resistant poplar. Three main objectives were originally proposed: (1) mine key rust effectors that suppress host immunity; (2) elucidate interaction networks in poplar targeted by key rust effectors; (3) generate transgenic poplar resources for identification of genes involved in pathogen infection or host defense triggered by rust. Generally, we worked towards all three objectives by developing and applying complementary molecular, genomic, biochemical and plant transformation approaches.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Addressing genome scale design tradeoffs in Pseudomonas putida for bioconversion of an aromatic carbon source

Genome-scale metabolic models (GSMM) are commonly used to identify gene deletion sets that result in growth coupling and pairing product formation with substrate utilization and can improve strain performance beyond levels typically accessible using traditional strain engineering approaches. However, sustainable feedstocks pose a challenge due to incomplete high-resolution metabolic data for non-canonical carbon sources required to curate GSMM and identify implementable designs. Here we address a four-gene deletion design in the Pseudomonas putida KT2440 strain for the lignin-derived non-sugar carbon source, p-coumarate (p-CA), that proved challenging to implement. We examine the performance of the fully implemented design for p-coumarate to glutamine, a useful biomanufacturing intermediate. In this study glutamine is then converted to indigoidine, an alternative sustainable pigment and a model heterologous product that is commonly used to colorimetrically quantify glutamine concentration. Through proteomics, promoter-variation, and growth characterization of a fully implemented gene deletion design, we provide evidence that aromatic catabolism in the completed design is rate-limited by fumarase hydratase (FUM) enzyme activity in the citrate cycle and requires careful optimization of another fumarate hydratase protein (PP_0897) expression to achieve growth and production. A double sensitivity analysis also confirmed a strict requirement for fumarate hydratase activity in the strain where all genes in the growth coupling design have been implemented. Metabolic cross-feeding experiments were used to examine the impact of complete removal of the fumarase hydratase reaction and revealed an unanticipated nutrient requirement, suggesting additional functions for this enzyme. While a complete implementation of the design was achieved, this study highlights the challenge of completely inactivating metabolic reactions encoded by under-characterized proteins, especially in the context of multi-gene edits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Heritable gene editing in tomato through viral delivery of isopentenyl transferase and single-guide RNAs to latent axillary meristematic cells

Realizing the full potential of genome editing for crop improvement has been slow due to inefficient methods for reagent delivery and the reliance on tissue culture for creating gene-edited plants. RNA viral vectors offer an alternative approach for delivering gene engineering reagents and bypassing the tissue culture requirement. Viruses, however, are often excluded from the shoot apical meristem, making virus-mediated gene editing inefficient in some species. Here, we developed effective approaches for generating gene-edited shoots in Cas9-expressing transgenic tomato plants using RNA virus-mediated delivery of single-guide RNAs (sgRNAs). RNA viral vectors expressing sgRNAs were either delivered to leaves or sites near axillary meristems. Trimming of the apical and axillary meristems induced new shoots to form from edited somatic cells. To further encourage the induction of shoots, we used RNA viral vectors to deliver sgRNAs along with the cytokinin biosynthesis gene, isopentenyl transferase. Abundant, phenotypically normal, gene-edited shoots were induced per infected plant with single and multiplexed gene edits fixed in the germline. The use of viruses to deliver both gene editing reagents and developmental regulators overcomes the bottleneck in applying virus-induced gene editing to dicotyledonous crops such as tomato and reduces the dependency on tissue culture.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Novel cis-regulatory elements as synthetic promoters to drive recombinant protein expression from the Chlamydomonas reinhardtii nuclear genome

Eukaryotic green microalgae represent a sustainable, photosynthetic biotechnology platform for generating high-value products. The model green alga Chlamydomonas reinhardtii has already been used to generate high value bioproducts such as recombinant proteins and terpenoids. However, low, unstable, and variable nuclear transgene expression has limited the ease and speed of metabolic engineering and recombinant protein expression in this system. Here, novel genetic devices for transgene expression in C. reinhardtii have been developed by identifying cis-regulatory DNA elements capable of driving high transgene expression in C. reinhardtii promoters using de novo motif discovery informatics approaches. Thirteen putative motifs were synthesized as concatemers, linked to a common minimal basal promoter, and assayed for their activity to drive expression of a yellow fluorescent protein reporter gene. Following transformation of the vectors into C. reinhardtii by electroporation, in vivo measurements of yellow fluorescent protein expression by flow cytometry revealed that five of the DNA motifs analyzed displayed significantly higher reporter expression compared to the basal promoter control. Two of the concatemerized motifs, despite being much smaller minimal cis-regulatory elements, drove reporter expression at levels approaching that of the conventionally-used AR1 promoter. This analysis provides insight into C. reinhardtii promoter structure and gene regulation, and provides a new toolbox of cis-regulatory elements that can be used to drive transgene expression at a variety of expression levels.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Knowledge-matching based computational framework for genome-scale metabolic model refinement

Genome-scale metabolic models (GEMs) are mathematically structured knowledge base reconstructed from annotated genome of different organisms. With the advancement of next-generation sequencing technology, many organisms have had their genomes sequenced. However, obtaining a high-quality GEM is highly time-consuming, even with the introduction of several genome-scale reconstruction tools that offer automated draft network generation and gap filling. It has been recognized that the iterative process of manual curation and refinement is the limiting step of GEM development, and how to expedite the GEM refinement is still an open question. As cellular metabolism is a complex system with very high degree of freedom and redundancy, the principles and techniques developed in process systems engineering can be adapted to expedite GEM refinement. In this paper we present a knowledge-matching based computation framework for GEM refinement, and demonstrate the effectiveness of the proposed solution using the refinement of a GEM for Clostridium tyrobutyricum.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Maximal Sum of Metabolic Exchange Fluxes Outperforms Biomass Yield as a Predictor of Growth Rate of Microorganisms

Growth rate has long been considered one of the most valuable phenotypes that can be measured in cells. Aside from being highly accessible and informative in laboratory cultures, maximal growth rate is often a prime determinant of cellular fitness, and predicting phenotypes that underlie fitness is key to both understanding and manipulating life. Despite this, current methods for predicting microbial fitness typically focus on yields [e.g., predictions of biomass yield using GEnomescale metabolic Models (GEMs)] or notably require many empirical kinetic constants or substrate uptake rates, which render these methods ineffective in cases where fitness derives most directly from growth rate. Here we present a new method for predicting cellular growth rate, termed SUMEX, which does not require any empirical variables apart from a metabolic network (i.e., a GEM) and the growth medium. SUMEX is calculated by maximizing the SUM of molar EXchange fluxes (hence SUMEX) in a genome-scale metabolic model. SUMEX successfully predicts relative microbial growth rates across species, environments, and genetic conditions, outperforming traditional cellular objectives (most notably, the convention assuming biomass maximization). The success of SUMEX suggests that the ability of a cell to catabolize substrates and produce a strong proton gradient enables fast cell growth. Easily applicable heuristics for predicting growth rate, such as what we demonstrate with SUMEX, may contribute to numerous medical and biotechnological goals, ranging from the engineering of faster-growing industrial strains, modeling of mixed ecological communities, and the inhibition of cancer growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Genome-wide identification and diversity of FAD2, FAD3 and FAE1 genes in terms of biotechnological importance in Camelina species

False flax, or gold-of-pleasure (Camelina sativa) is an oilseed that has received renewed research interest as a promising vegetable oil feedstock for liquid biofuel production and other non-food uses. This species has also emerged as a model for oilseed biotechnology research that aims to enhance seed oil content and fatty acid quality. To date, a number of genetic engineering and gene editing studies on C. sativa have been reported. Among the most common targets for this research are genes, encoding fatty acid desaturases, elongases, and diacylglycerol acyltransferases. However, the majority of these genes in C. sativa are present in multiple copies due to the allohexaploid nature of the species. Therefore, genetic manipulations require a comprehensive understanding of the diversity of such gene targets.

09 BIOMASS FUELS↗