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At least 703 records · Page 39

Towards engineering ectomycorrhization into switchgrass bioenergy crops via a lectin receptor‐like kinase

Summary Soil‐borne microbes can establish compatible relationships with host plants, providing a large variety of nutritive and protective compounds in exchange for photosynthesized sugars. However, the molecular mechanisms mediating the establishment of these beneficial relationships remain unclear. Our previous genetic mapping and whole‐genome resequencing studies identified a gene deletion event of a Populus trichocarpa lectin receptor‐like kinase gene PtLecRLK1 in Populus deltoides that was associated with poor‐root colonization by the ectomycorrhizal fungus Laccaria bicolor . By introducing PtLecRLK1 into a perennial grass known to be a non‐host of L. bicolor , switchgrass ( Panicum virgatum L.), we found that L. bicolor colonizes ZmUbipro‐PtLecRLK1 transgenic switchgrass roots, which illustrates that the introduction of PtLecRLK1 has the potential to convert a non‐host to a host of L. bicolor . Furthermore, transcriptomic and proteomic analyses on inoculated‐transgenic switchgrass roots revealed genes/proteins overrepresented in the compatible interaction and underrepresented in the pathogenic defence pathway, consistent with the view that pathogenic defence response is down‐regulated during compatible interaction. Metabolomic profiling revealed that root colonization in the transgenic switchgrass was associated with an increase in N‐containing metabolites and a decrease in organic acids, sugars, and aromatic hydroxycinnamate conjugates, which are often seen in the early steps of establishing compatible interactions. These studies illustrate that PtLecRLK1 is able to render a plant susceptible to colonization by the ectomycorrhizal fungus L. bicolor and shed light on engineering mycorrhizal symbiosis into a non‐host to enhance plant productivity and fitness on marginal lands.

59 BASIC BIOLOGICAL SCIENCES↗

Biosystems Design by Machine Learning

Biosystems such as enzymes, pathways, and whole cells have been increasingly explored for biotechnological applications. Yet, the intricate connectivity and complexity of biosystems pose a major hurdle in designing biosystems with desired features. As -omics and other high throughput technologies have been rapidly developed, the promise of applying machine learning (ML) techniques in biosystems design has started to become a reality. ML models enable the identification of patterns within complicated biological data across multiple scales of analysis and can augment biosystems design applications by predicting new candidates for optimized performance. ML is being used at every stage of biosystems design to help find non-obvious engineering solutions with fewer design iterations. In this review, we first describe commonly used models and modeling paradigms within ML. We then discuss some applications of these models that have already shown success in biotechnological applications. Moreover, we discuss successful applications at all scales of biosystems design, including nucleic acids, genetic circuits, proteins, pathways, genomes, and bioprocess. Lastly, we discuss some limitations of these methods and potential solutions as well as prospects of the combination of ML and biosystems design.

59 BASIC BIOLOGICAL SCIENCES↗

3D Construction of Biologically Derived Materials

System for the 3D Construction of Biologically Derived Materials, Structures, and Parts NASA has developed a novel approach for macroscale biomaterial production by combining synthetic biology with 3D printing. Cells are biologically engineered to deposit desired materials, such as proteins or metals, derived from locally available resources. The bioengineered cells build different materials in a specified 3D pattern to produce novel microstructures with precise molecular composition, thickness, print pattern, and shape. Scaffolds and reagents can be used for further control over material product. This innovation provides modern design and fabrication techniques for custom-designed organic or organic-inorganic composite biomaterials produced from limited resources. Benefits Conserves resources. Few raw or bulk starting materials needed Enables custom design of diverse materials Fast, portable, macroscale, on-demand manufacturing High-fidelity microstructures Uses commercially available parts Applications Biomaterials, biotechnology Organic-inorganic composite materials On-demand manufacturing In situ resource utilization Space stations Military Infrastructure materials The Technology Once genes for a desired material type, delivery mode, control method and affinity have been chosen, assembling the genetic components and creating the cell lines can be done with well-established synthetic biology techniques. A 3D microdeposition system is used to make a 3D array of these cells in a precise, microstructure pattern and shape. The engineered cells are suspended in a printable 'ink'. The 3D microdeposition system deposits minute droplets of the cells onto a substrates surface in a designed print pattern. Additional printer passes thicken the material. The cell array is fed nutrients and reagents to activate the engineered genes within the cells to create and deposit the desired molecules. These molecules form the designed new material. If desired, the cells may be removed by flushing. The end product is thus a 3D composite microstructure comprising the novel material. This innovation provides a fast, controlled production of natural, synthetic, and novel biomaterials with minimum resource overhead and reduced pre- and post-processing requirements.

3D↗

Utilization of lignocellulosic hydrolysates for photomixotrophic chemical production in Synechococcus elongatus PCC 7942

Abstract To meet the need for environmentally friendly commodity chemicals, feedstocks for biological chemical production must be diversified. Lignocellulosic biomass are an carbon source with the potential for effective use in a large scale and cost-effective production systems. Although the use of lignocellulosic biomass lysates for heterotrophic chemical production has been advancing, there are challenges to overcome. Here we aim to investigate the obligate photoautotroph cyanobacterium Synechococcus elongatus PCC 7942 as a chassis organism for lignocellulosic chemical production. When modified to import monosaccharides, this cyanobacterium is an excellent candidate for lysates-based chemical production as it grows well at high lysate concentrations and can fix CO 2 to enhance carbon efficiency. This study is an important step forward in enabling the simultaneous use of two sugars as well as lignocellulosic lysate. Incremental genetic modifications enable catabolism of both sugars concurrently without experiencing carbon catabolite repression. Production of 2,3-butanediol is demonstrated to characterize chemical production from the sugars in lignocellulosic hydrolysates. The engineered strain achieves a titer of 13.5 g L −1 of 2,3-butanediol over 12 days under shake-flask conditions. This study can be used as a foundation for industrial scale production of commodity chemicals from a combination of sunlight, CO 2 , and lignocellulosic sugars.

59 BASIC BIOLOGICAL SCIENCES↗

Launch Vehicle Propulsion Design with Multiple Selection Criteria

The approach and techniques described herein define an optimization and evaluation approach for a liquid hydrogen/liquid oxygen single-stage-to-orbit system. The method uses Monte Carlo simulations, genetic algorithm solvers, a propulsion thermo-chemical code, power series regression curves for historical data, and statistical models in order to optimize a vehicle system. The system, including parameters for engine chamber pressure, area ratio, and oxidizer/fuel ratio, was modeled and optimized to determine the best design for seven separate design weight and cost cases by varying design and technology parameters. Significant model results show that a 53% increase in Design, Development, Test and Evaluation cost results in a 67% reduction in Gross Liftoff Weight. Other key findings show the sensitivity of propulsion parameters, technology factors, and cost factors and how these parameters differ when cost and weight are optimized separately. Each of the three key propulsion parameters; chamber pressure, area ratio, and oxidizer/fuel ratio, are optimized in the seven design cases and results are plotted to show impacts to engine mass and overall vehicle mass.

Shelton, Joey D.↗

Targeted engineering of camelina and pennycress seeds for ultrahigh accumulation of acetyl-TAG

Acetyl-TAG (3-acetyl-1,2-diacylglycerol), unique triacylglycerols (TAG) possessing an acetate group at the sn -3 position, exhibit valuable properties, such as reduced viscosity and freezing points. Previous attempts to engineer acetyl-TAG production in oilseed crops did not achieve the high levels found in naturally producing Euonymus seeds. Here, we demonstrate the successful generation of camelina and pennycress transgenic lines accumulating nearly pure acetyl-TAG at 93 mol% and 98 mol%, respectively. These ultrahigh acetyl-TAG synthesizing lines were created using gene-edited FATTY ACID ELONGASE1 ( FAE1 ) mutant lines as an improved genetic background to increase levels of acetyl-CoA available for acetyl-TAG synthesis mediated by the expression of EfDAcT, a high-activity diacylglycerol acetyltransferase isolated from Euonymus fortunei . Combining EfDAcT expression with suppression of the competing TAG-synthesizing enzyme DGAT1 further enhanced acetyl-TAG accumulation. These ultrahigh levels of acetyl-TAG exceed those in earlier engineered oilseeds and are equivalent or greater than those in Euonymus seeds. Imaging of lipid localization in transgenic seeds revealed that the low amounts of residual TAG were mostly confined to the embryonic axis. Similar spatial distributions of specific TAG and acetyl-TAG molecular species, as well as their probable diacylglycerol (DAG) precursors, provide additional evidence that acetyl-TAG and TAG are both synthesized from the same tissue-specific DAG pools. Remarkably, this ultrahigh production of acetyl-TAG in transgenic seeds exhibited minimal negative effects on seed properties, highlighting the potential for production of designer oils required for economical biofuel industries.

09 BIOMASS FUELS↗

Unifying themes and distinct features of carbon and nitrogen assimilation by polysaccharide-degrading bacteria: a summary of four model systems

Our current understanding of enzymatic polysaccharide degradation has come from a huge number of in vitro studies with purified enzymes. While this vast body of work has been invaluable in identifying and characterizing novel mechanisms of action and engineering desirable traits into these enzymes, a comprehensive picture of how these enzymes work as part of a native in vivo system is less clear. Recently, several model bacteria have emerged with genetic systems that allow for a more nuanced study of carbohydrate active enzymes (CAZymes) and how their activity affects bacterial carbon metabolism. With these bacterial model systems it is now possible to not only study a single nutrient system in isolation (i.e. carbohydrate degradation and carbon metabolism), but also how multiple systems are integrated. Given that most environmental polysaccharides are carbon rich but nitrogen poor (e.g. lignocellulose), the interplay between carbon and nitrogen metabolism in polysaccharide-degrading bacteria can now be studied in a physiologically relevant manner. Therefore, in this review we have summarized what has been experimentally determined for CAZyme regulation, production, and export in relation to nitrogen metabolism for two Gram-positive (Caldicellulosiruptor bescii and Clostridium thermocellum) and two Gram-negative (Bacteroides thetaiotaomicron and Cellvibrio japonicus) polysaccharide-degrading bacteria. By comparing and contrasting these four bacteria we have highlighted the shared and unique features of each, with a focus on in vivo studies, in regard to carbon and nitrogen assimilation. Finally, we conclude with what we believe are two important questions that can act as guideposts for future work to better understand the integration of carbon and nitrogen metabolism in polysaccharide-degrading bacteria.

Cellvibrio japonicus↗

A fluorescent-protein spin qubit

Quantum bits (qubits) are two-level quantum systems that support initialization, readout and coherent control1. Optically addressable spin qubits form the foundation of an emerging generation of nanoscale sensors. The engineering of these qubits has mainly focused on solid-state systems. However, fluorescent proteins, rather than exogenous fluorescent probes, have become the gold standard for in vivo microscopy because of their genetic encodability. Although fluorescent proteins possess a metastable triplet state, they have not been investigated as qubits. Here we realize an optically addressable spin qubit in enhanced yellow fluorescent protein. A near-infrared laser pulse enables triggered readout of the triplet state with up to 20% spin contrast. Using coherent microwave control of the enhanced-yellow-fluorescent-protein spin at liquid-nitrogen temperatures, we measure a (16 ± 2) μs coherence time under Carr–Purcell–Meiboom–Gill decoupling. We express the qubit in mammalian cells, maintaining contrast and coherent control despite the complex intracellular environment. Finally, we demonstrate optically detected magnetic resonance in bacterial cells at room temperature with contrast up to 8%. Our results introduce fluorescent proteins as a powerful qubit platform that paves the way for applications in the life sciences, such as nanoscale field sensing and spin-based imaging modalities.

Feder, Jacob S. [Univ. of Chicago, IL (United Stat↗

Biological Parts for Plant Biodesign to Enhance Land-Based Carbon Dioxide Removal

A grand challenge facing society is climate change caused mainly by rising CO 2 concentration in Earth’s atmosphere. Terrestrial plants are linchpins in global carbon cycling, with a unique capability of capturing CO 2 via photosynthesis and translocating captured carbon to stems, roots, and soils for long-term storage. However, many researchers postulate that existing land plants cannot meet the ambitious requirement for CO 2 removal to mitigate climate change in the future due to low photosynthetic efficiency, limited carbon allocation for long-term storage, and low suitability for the bioeconomy. To address these limitations, there is an urgent need for genetic improvement of existing plants or construction of novel plant systems through biosystems design (or biodesign). Here, we summarize validated biological parts (e.g., protein-encoding genes and noncoding RNAs) for biological engineering of carbon dioxide removal (CDR) traits in terrestrial plants to accelerate land-based decarbonization in bioenergy plantations and agricultural settings and promote a vibrant bioeconomy. Specifically, we first summarize the framework of plant-based CDR (e.g., CO 2 capture, translocation, storage, and conversion to value-added products). Then, we highlight some representative biological parts, with experimental evidence, in this framework. Finally, we discuss challenges and strategies for the identification and curation of biological parts for CDR engineering in plants.

59 BASIC BIOLOGICAL SCIENCES↗

Tissue Engineering and Cellular Regeneration at NASA Report to Regenetech SAB

A project overview describing three dimensional tissue models is shown. The topics include: 1) cellular regeneration; 2) haemopoietic replacement; 3) novel vaccine development; 4) pharmacology and toxicology interventions; 5) development of synthetic viruses; and 6) molecular genetics and proteomics of recapitulated models.

Goodwin, Thomas J.↗

Programmable gene regulation for metabolic engineering using decoy transcription factor binding sites

Abstract Transcription factor decoy binding sites are short DNA sequences that can titrate a transcription factor away from its natural binding site, therefore regulating gene expression. In this study, we harness synthetic transcription factor decoy systems to regulate gene expression for metabolic pathways in Escherichia coli. We show that transcription factor decoys can effectively regulate expression of native and heterologous genes. Tunability of the decoy can be engineered via changes in copy number or modifications to the DNA decoy site sequence. Using arginine biosynthesis as a showcase, we observed a 16-fold increase in arginine production when we introduced the decoy system to steer metabolic flux towards increased arginine biosynthesis, with negligible growth differences compared to the wild type strain. The decoy-based production strain retains high genetic integrity; in contrast to a gene knock-out approach where mutations were common, we detected no mutations in the production system using the decoy-based strain. We further show that transcription factor decoys are amenable to multiplexed library screening by demonstrating enhanced tolerance to pinene with a combinatorial decoy library. Our study shows that transcription factor decoy binding sites are a powerful and compact tool for metabolic engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Characterization of Plastic Degrading Bacteria from Environmental Samples by Genetic and Biochemical Analysis

Plastic is the major waste-product during NASA space missions, recycling this waste-stream to produce other beneficial materials would decrease upmass. Bacterial called plastisomes have been demonstrated to metabolize non-biodegradable plastics such as polyethylene and polystyrene. Characterization and engineering of these bacteria, and their eventual incorporation as life support systems would enable space flight beyond lower earth orbit. We will utilize molecular techniques to identify and isolate the most productive plastisome. Environmental samples obtained from locations known to be rich in plastic will be cultured in a laboratory defined-media supplemented with plastic as the sole carbon source. Cultures will be monitored for growth over time. Ribosomal DNA will be amplified from cultures that exhibit growth using PCR. These amplified fragments will be sequenced to determine the identity of the consortia in the cultures. We will then perform bioinformatics analysis on the data to identify the plastisomes and generate phylogenetic trees. Morphological and physiological profile of the plastisomes will also be conducted by microscopy and biochemical tests. Our results would reveal a bacterial strain that can break down plastics efficiently. The implication for this project would not only benefit space exploration but also make a major impact towards sustainability development on Earth.

plastic conversion↗

Data for "Anti-Pdc1p Nanobody as a Genetically Encoded Inhibitor of Ethanol Production Enables Dual Transcriptional and Post-translational Controls of Yeast Fermentations"

Microbial fermentation provides a sustainable method of producing valuable chemicals. Adding dynamic control to fermentations can significantly improve titers, but most systems rely on transcriptional controls of metabolic enzymes, leaving existing intracellular enzymes unregulated. This limits the ability of transcriptional controls to switch off metabolic pathways, especially when metabolic enzymes have long half-lives. We developed a two-layer transcriptional/post-translational control system for yeast fermentations. Specifically, the system uses blue light to transcriptionally activate the major pyruvate decarboxylase PDC1 , required for cell growth and concomitant ethanol production. Switching to darkness transcriptionally inactivates PDC1 and instead activates the anti-Pdc1p nanobody, NbJRI, to act as a genetically encoded inhibitor of Pdc1p accumulated during the growth phase. This dual transcriptional/post-translational control improves the production of 2,3-BDO and citramalate by up to 100 and 92% compared to using transcriptional controls alone in dynamic two-phase fermentations. This study establishes the NbJRI nanobody as an effective genetically encoded inhibitor of Pdc1p that can enhance the production of pyruvate-derived chemicals.

metabolic engineering↗

Data for Impact of Non-Irrigation on 1G and 2G Bioethanol Potential of Oilcane Feedstock: A Field to Fuel Pipeline Study

This study evaluates the bioethanol potential in response to irrigation (IR) and non-irrigation (NIR) of oilcane (OC) during a seasonal drought prior harvest. The juice was extracted through mechanical pressing of stems and fermented by Ethanol Red® yeast to produce first-generation bioethanol. Hydrothermal pretreatment followed by enzymatic hydrolysis of bagasse was performed to produce monomeric sugars from structural carbohydrates. The hydrolysates were fermented with engineered yeast for second-generation bioethanol production. The irrigated oilcane juice (276.3 ± 8.9 g/L) constitutes higher sugar concentrations than non-irrigated oilcane juice (236.5 ± 2.2 g/L). The enzymatic hydrolysis of IR-OC and NIR-OC pretreated bagasse yielded similar concentrations of 247.5 ± 2.22 and 249.7 ± 4.98 g/L fermentable sugars. Industry-relevant bioethanol titers of ≥99 g/L and ≥75 g/L were achieved from juice and hydrolysates, respectively. Therefore, the non-irrigation regime did not impact the 1G and 2G bioethanol titers. However, the overall bioethanol yield can be lower due to the reduction of stem yield (8 %) per hectare.

Biomass Analytics↗

Data Mining and Optimization Tools for Developing Engine Parameters Tools

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. From the total budget of $5,000, Tricia and I studied the problem domain for developing ail Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy datasets. From the study and discussion with NASA LERC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of the data for GA based multi-resolution optimal search. Wavelet processing is proposed to create a coarse resolution representation of data providing two advantages in GA based search: 1. We will have less data to begin with to make search sub-spaces. 2. It will have robustness against the noise because at every level of wavelet based decomposition, we will be decomposing the signal into low pass and high pass filters.

Dhawan, Atam P.↗

Data Mining and Optimization Tools for Developing Engine Parameters Tools

This project was awarded for understanding the problem and developing a plan for Data Mining tools for use in designing and implementing an Engine Condition Monitoring System. Tricia Erhardt and I studied the problem domain for developing an Engine Condition Monitoring system using the sparse and non-standardized datasets to be available through a consortium at NASA Lewis Research Center. We visited NASA three times to discuss additional issues related to dataset which was not made available to us. We discussed and developed a general framework of data mining and optimization tools to extract useful information from sparse and non-standard datasets. These discussions lead to the training of Tricia Erhardt to develop Genetic Algorithm based search programs which were written in C++ and used to demonstrate the capability of GA algorithm in searching an optimal solution in noisy, datasets. From the study and discussion with NASA LeRC personnel, we then prepared a proposal, which is being submitted to NASA for future work for the development of data mining algorithms for engine conditional monitoring. The proposed set of algorithm uses wavelet processing for creating multi-resolution pyramid of tile data for GA based multi-resolution optimal search.

Dhawan, Atam P.↗

Metabolic engineering of Caldicellulosiruptor bescii for 2,3-butanediol production from unpretreated lignocellulosic biomass and metabolic strategies for improving yields and titers

ABSTRACT The platform chemical 2,3-butanediol (2,3-BDO) is used to derive products, such as 1,3-butadiene and methyl ethyl ketone, for the chemical and fuel production industries. Efficient microbial 2,3-BDO production at industrial scales has not been achieved yet for various reasons, including product inhibition to host organisms, mixed stereospecificity in product formation, and dependence on expensive substrates (i.e., glucose). In this study, we explore engineering of a 2,3-BDO pathway inCaldicellulosiruptor bescii, an extremely thermophilic (optimal growth temperature = 78°C) and anaerobic bacterium that can break down crystalline cellulose and hemicellulose into fermentable C 5 and C 6 sugars. In addition, C. besciigrows on unpretreated plant biomass, such as switchgrass. Biosynthesis of 2,3-BDO involves three steps: two molecules of pyruvate are condensed into acetolactate; acetolactate is decarboxylated to acetoin, and finally, acetoin is reduced to 2,3-BDO.C. besciinatively produces acetoin; therefore, in order to complete the 2,3-BDO biosynthetic pathway,C. besciiwas engineered to produce a secondary alcohol dehydrogenase (sADH) to catalyze the final step. Two previously characterized, thermostable sADH enzymes with high affinity for acetoin, one from a bacterium and one from an archaeon, were tested independently. When either sADH was present inC. bescii,the recombinant strains were able to produce up to 2.5-mM 2,3-BDO from crystalline cellulose and xylan and 0.2-mM 2,3-BDO directly from unpretreated switchgrass. This serves as the basis for higher yields and productivities, and to this end, limiting factors and potential genetic targets for further optimization were assessed using the genome-scale metabolic model ofC. bescii. IMPORTANCE Lignocellulosic plant biomass as the substrate for microbial synthesis of 2,3-butanediol is one of the major keys toward cost-effective bio-based production of this chemical at an industrial scale. However, deconstruction of biomass to release the sugars for microbial growth currently requires expensive thermochemical and enzymatic pretreatments. In this study, the thermo-cellulolytic bacteriumCaldicellulosiruptor besciiwas successfully engineered to produce 2,3-butanediol from cellulose, xylan, and directly from unpretreated switchgrass. Genome-scale metabolic modeling ofC. besciiwas applied to adjust carbon and redox fluxes to maximize productivity of 2,3-butanediol, thereby revealing bottlenecks that require genetic modifications.

Biotechnology & Applied Microbiology↗