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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

FluxRETAP: a REaction TArget Prioritization genome-scale modeling technique for selecting genetic targets

MOTIVATION: Metabolic engineering is rapidly evolving as a result of new advances in synthetic biology tools and automation platforms that enable high throughput strain construction, as well as the development of machine learning tools (ML) for biology. However, selecting genetic engineering targets that effectively guide the metabolic engineering process is still challenging. ML can provide predictive power for synthetic biology, but current technical limitations prevent the independent use of ML approaches without previous biological knowledge. RESULTS: Here, we present FluxRETAP, a simple and computationally inexpensive method that leverages the prior mechanistic knowledge embedded in genome-scale models for suggesting targets for genetic overexpression, downregulation or deletion, with the final goal of increasing the production of a desired metabolite. This method can provide a list of desirable engineering targets that can be combined with current ML pipelines. FluxRETAP captured 100% of reaction targets experimentally verified to improve Escherichia coli isoprenol production, 50% of targets that experimentally improved taxadiene production in E. coli and ∼60% of genetic targets from a verified minimal constrained cut-set in Pseudomonas putida, while providing additional high priority targets that could be tested. Overall, FluxRETAP is an efficient algorithm for identifying a prioritized list of testable genetic and reaction targets. AVAILABILITY AND IMPLEMENTATION: FluxRETAP is implemented in python and released under the creative commons license. The implementation and code are freely available at: https://github.com/JBEI/FluxRETAP.

Czajka, Jeffrey J↗
DOE OSTI2026

Correlational selection and genetic architecture shape the evolution of the leaf economics spectrum in a perennial grass

The generality of the worldwide leaf economics spectrum (LES) has made it a pillar of trait-based ecological research. Yet, few studies have examined the processes shaping the evolution of the LES within species, in part, because most species occupy only a small portion of the LES. Here, to address this gap, we took advantage of the distinct leaf economics strategies present in different ecotypes of the phenotypically diverse perennial grass Panicum virgatum (switchgrass) to generate a genetic mapping population, which we planted in common gardens at three sites spanning 12 degrees of latitude in the central United States. With this genetic mapping population, we evaluated two potentially interacting causes of LES evolution: 1) genetic architecture, where multiple traits are influenced by either the same gene (pleiotropy) or by genes in close physical proximity (genetic linkage), and 2) correlational selection, where selection acts on traits in combination rather than in isolation. We found that shared genetic architecture influenced covariation between photosynthetic rate (A MASS ) and leaf nitrogen (N MASS ) and between A MASS and leaf mass per area (LMA). We also found that correlational selection favored the trait combinations predicted by the LES (e.g., high LMA with low N MASS or low LMA with high N MASS ) and disfavored other, mismatched trait combinations at two of the three sites. Together, these results demonstrate how the evolution of an integrated LES within species can arise from multiple evolutionary causes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Directed Evolution of an Adenylation Domain Alters Substrate Specificity and Generates a New Catechol Siderophore in Escherichia coli

Nonribosomal peptide synthetases (NRPS) biosynthesize numerous natural products with therapeutic, agricultural, and industrial significance. Reliably altering substrate selection in these enzymes has been a longstanding goal, as this would enable the production of tailor-made peptides with desired activities. In this study, the NRPS EntF and the associated biosynthesis of the siderophore enterobactin (ENT) were used as a model system to interrogate substrate selection by an adenylation (A) domain. We employed a directed evolution pipeline that harnesses an in vivo genetic selection for siderophore production to alter A domain substrate selection. Surprisingly, this led to the formation of a new, physiologically active catechol siderophore in Escherichia coli. We characterized the enzyme variants in vitro and demonstrated transferability of our findings to the well-studied TycC and GrsB NRPSs. Furthermore, this work identifies critical binding pocket residues that allow for altered substrate selection in our model system and expands upon our understanding of iron acquisition in E. coli.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2017

Microbiological Horticultural Internship Final Abstract

GMO dwarf plum (Prunus domestica) is being evaluated as a candidate food crop for long duration space flight missions. A project was undertaken to develop a protocol for transferring selected genetic lines of GMO plum (previously maintained in pots and propagated by cuttings at NASA's Kennedy Space Center in Florida) into in vitro tissue culture. In vitro culture may reduce the space, materials, and labor required to maintain the current lines of GMO plum and better preserve them for future study. Fresh plant material from three selected GMO plum lines (NASA-5, NASA-10, and NASA-11) and a non-modified control line (Control-5) were processed aseptically into in vitro culture on four separate occasions. The impact of multiple treatments on the successful growth of GMO plum tissue in vitro were tested: Parent explant tissue type (leaf petioles, stem nodes containing buds and internodes without buds), tissue sterilization method [soaking in 10 bleach only (5 min for petioles or 10 min for nodesinternodes), or soaking in 70 EtOH (30 sec) followed by 10 bleach (5 min for petioles and 10 min for nodesinternodes)], and media type [three Murashige and Skoog-based medias (SGM, SRM, and SRM+2,4-D) and one recipe containing woody plant media (WPM)]. 22.2 of the plates containing tissue sterilized with bleach alone developed microbial contamination after two weeks, while only 11.8 of plates containing tissue sterilized sequentially with EtOH and bleach developed contamination. Node bud tissue from all four genetic lines of plum produced leafy plantlets on SGM and SRM media after 4-6 weeks. The most numerous and well-developed plantlets were present on SGM. Upon reaching suitable size, plantlets were transferred to larger media containers for further growth. Some node bud growth occurred on SRM+2,4-D and WPM 2.5 weeks after plating, however as of yet no pieces on SRM+2,4-D have adequate development for transferring. Tissue pieces from NASA-5 plated on WPM are developing leaves and will be ready for transferring soon. Petioles and internode tissue lacking bud meristem failed to produce any plantlets on any plates, however petioles developed large masses of undifferentiated callus tissue on SRM+2,4-D media. These callused pieces were then transferred to SRM+TDZ media, which resulted in even larger callus growth but no differentiation. All four selected plum lines were successfully transitioned into in vitro culture. Nodes from NASA-5 and NASA-10 lines produced the most numerous and well-developed leafy plantlets in vitro, while those from NASA-11 and Control-5 were generally smaller, slower growing and less numerous. The best method overall was to use young stem node tissue with buds, surface sterilize the pieces sequentially with 70 EtOH and 10 bleach, and then plate them onto SGM media. Future areas of study will include introducing additional genetic lines of GMO plum into in vitro culture, attempting to induce shoot growth in petiole callus tissue, testing methods (such as cold storage) that extend the time interval between transferring explants into new media, and testing viability of plantlets transferred from in vitro culture back to traditional pot culture.

bioregenerative life support↗
NASA NTRS2000

JavaGenes: Evolving Graphs with Crossover

Genetic algorithms usually use string or tree representations. We have developed a novel crossover operator for a directed and undirected graph representation, and used this operator to evolve molecules and circuits. Unlike strings or trees, a single point in the representation cannot divide every possible graph into two parts, because graphs may contain cycles. Thus, the crossover operator is non-trivial. A steady-state, tournament selection genetic algorithm code (JavaGenes) was written to implement and test the graph crossover operator. All runs were executed by cycle-scavagging on networked workstations using the Condor batch processing system. The JavaGenes code has evolved pharmaceutical drug molecules and simple digital circuits. Results to date suggest that JavaGenes can evolve moderate sized drug molecules and very small circuits in reasonable time. The algorithm has greater difficulty with somewhat larger circuits, suggesting that directed graphs (circuits) are more difficult to evolve than undirected graphs (molecules), although necessary differences in the crossover operator may also explain the results. In principle, JavaGenes should be able to evolve other graph-representable systems, such as transportation networks, metabolic pathways, and computer networks. However, large graphs evolve significantly slower than smaller graphs, presumably because the space-of-all-graphs explodes combinatorially with graph size. Since the representation strongly affects genetic algorithm performance, adding graphs to the evolutionary programmer's bag-of-tricks should be beneficial. Also, since graph evolution operates directly on the phenotype, the genotype-phenotype translation step, common in genetic algorithm work, is eliminated.

Globus, Al↗
NASA NTRS1991

Structural modification of polysaccharides: A biochemical-genetic approach

Polysaccharides have a wide range of industrial and biomedical applications. An industry trend is underway towards the increased use of bacteria to produce polysaccharides. Long term goals of this work are the adaptation and enhancement of saccharide properties for electronic and optic applications. In this report we illustrate the application of enzyme-bearing bacteriophage on strains of the enteric bacterium Klebsiella pneumoniae, which produces a polysaccharide with the relatively rare rheological property of drag-reduction. This has resulted in the production of new polysaccharides with enhanced rheological properties. Our laboratory is developing techniques for processing and structurally modifying bacterial polysaccharides and oligosaccharides which comprise their basic polymeric repeat units. Our research has focused on bacteriophage which produce specific polysaccharide degrading enzymes. This has lead to the development of enzymes generated by bacteriophage as tools for polysaccharide modification and purification. These enzymes were used to efficiently convert the native material to uniform-sized high molecular weight polymers, or alternatively into high-purity oligosaccharides. Enzyme-bearing bacteriophage also serve as genetic selection tools for bacteria that produce new families of polysaccharides with modified structures.

Kern, Roger G.↗
NASA NTRS1993

Biochemical And Genetic Modification Of Polysaccharides

Bacteriophages producing endopolysaccharase-type enzymes used to produce, isolate, and purify high yields of modified polysaccharides from polysaccharides produced by, and incorporated into capsules of, certain bacteria. Bacteriophages used in conversion of native polysaccharide materials into polymers of nearly uniform high molecular weight or, alternatively, into highly pure oligosaccharides. Also used in genetic selection of families of polysaccharides structurally related to native polysaccharide materials, but having altered properties. Resulting new polysaccharides and oligosaccharides prove useful in variety of products, including pharmaceutical chemicals, coating materials, biologically active carbohydrates, and drag-reducing additives for fluids.

Kern, Roger G.↗
NASA NTRS1996

Considerations in miniaturizing simplified agro-ecosystems for advanced life support

Miniaturizing the Earth's biogeochemical cycles to support human life during future space missions is the goal of the NASA research and engineering program in advanced life support. Mission requirements to reduce mass, volume, and power have focused efforts on (1) a maximally simplified agro-ecosystem of humans, food crops, and microbes; and, (2) a design for optimized productivity of food crops with high light levels over long days, with hydroponics, with elevated carbon dioxide and other controlled environmental factors, as well as with genetic selection for desirable crop properties. Mathematical modeling contributes to the goals by establishing trade-offs, by analyzing the growth and development of experimental crops, and by pointing to the possibilities of directed phasic control using modified field crop models to increase the harvest index.

Non-NASA Center↗
NASA NTRS1996

Excess nutrients in hydroponic solutions alter nutrient content of rice, wheat, and potato

Environment has significant effects on the nutrient content of field-grown crop plants. Little is known, however, about compositional changes caused by controlled environments in which plants receive only artificial radiation and soilless, hydroponic culture. This knowledge is essential for developing a safe, nutritious diet in a Controlled Ecological Life-Support System (CELSS). Three crops that are candidates for inclusion in a CELSS (rice, wheat, and white potato) were grown both in the field and in controlled environments where the hydroponic nutrient solution, photosynthetic photon flux (PPF), and CO2 level were manipulated to achieve rapid growth rates. Plants were harvested at maturity, separated into discrete parts, and dried prior to analysis. Plant materials were analyzed for proximate composition (protein, fat, ash, and carbohydrate), total nitrogen (N), nitrate, minerals, and amino-acid composition. The effect of environment on nutrient content varied by crop and plant part. Total N and nonprotein N (NPN) contents of plant biomass generally increased under controlled-environment conditions compared to field conditions, especially for leafy plant parts and roots. Nitrate levels were increased in hydroponically-grown vegetative tissues, but nitrate was excluded from grains and tubers. Mineral content changes in plant tissue included increased phosphorus and decreased levels of certain micronutrient elements under controlled-environment conditions. These findings suggest that cultivar selection, genetic manipulation, and environmental control could be important to obtain highly nutritious biomass in a CELSS.

NASA Discipline Number 61-20↗
NASA NTRS2005

A Method for Aircraft Concept Selection Using Multicriteria Interactive Genetic Algorithms

The problem of aircraft concept selection has become increasingly difficult in recent years as a result of a change from performance as the primary evaluation criteria of aircraft concepts to the current situation in which environmental effects, economics, and aesthetics must also be evaluated and considered in the earliest stages of the decision-making process. This has prompted a shift from design using historical data regression techniques for metric prediction to the use of physics-based analysis tools that are capable of analyzing designs outside of the historical database. The use of optimization methods with these physics-based tools, however, has proven difficult because of the tendency of optimizers to exploit assumptions present in the models and drive the design towards a solution which, while promising to the computer, may be infeasible due to factors not considered by the computer codes. In addition to this difficulty, the number of discrete options available at this stage may be unmanageable due to the combinatorial nature of the concept selection problem, leading the analyst to arbitrarily choose a sub-optimum baseline vehicle. These concept decisions such as the type of control surface scheme to use, though extremely important, are frequently made without sufficient understanding of their impact on the important system metrics because of a lack of computational resources or analysis tools. This paper describes a hybrid subjective/quantitative optimization method and its application to the concept selection of a Small Supersonic Transport. The method uses Genetic Algorithms to operate on a population of designs and promote improvement by varying more than sixty parameters governing the vehicle geometry, mission, and requirements. In addition to using computer codes for evaluation of quantitative criteria such as gross weight, expert input is also considered to account for criteria such as aeroelasticity or manufacturability which may be impossible or too computationally expensive to consider explicitly in the analysis. Results indicate that concepts resulting from the use of this method represent designs which are promising to both the computer and the analyst, and that a mapping between concepts and requirements that would not otherwise be apparent is revealed.

Buonanno, Michael↗
NASA NTRS2000

A Parallel Approach To Optimum Actuator Selection With a Genetic Algorithm

Recent discoveries in smart technologies have created a variety of aerodynamic actuators which have great potential to enable entirely new approaches to aerospace vehicle flight control. For a revolutionary concept such as a seamless aircraft with no moving control surfaces, there is a large set of candidate locations for placing actuators, resulting in a substantially larger number of combinations to examine in order to find an optimum placement satisfying the mission requirements. The placement of actuators on a wing determines the control effectiveness of the airplane. One approach to placement Maximizes the moments about the pitch, roll, and yaw axes, while minimizing the coupling. Genetic algorithms have been instrumental in achieving good solutions to discrete optimization problems, such as the actuator placement problem. As a proof of concept, a genetic has been developed to find the minimum number of actuators required to provide uncoupled pitch, roll, and yaw control for a simplified, untapered, unswept wing model. To find the optimum placement by searching all possible combinations would require 1,100 hours. Formulating the problem and as a multi-objective problem and modifying it to take advantage of the parallel processing capabilities of a multi-processor computer, reduces the optimization time to 22 hours.

Rogers, James L.↗
NASA NTRS2004

Optimum Actuator Selection with a Genetic Algorithm for Aircraft Control

The placement of actuators on a wing determines the control effectiveness of the airplane. One approach to placement maximizes the moments about the pitch, roll, and yaw axes, while minimizing the coupling. For example, the desired actuators produce a pure roll moment without at the same time causing much pitch or yaw. For a typical wing, there is a large set of candidate locations for placing actuators, resulting in a substantially larger number of combinations to examine in order to find an optimum placement satisfying the mission requirements and mission constraints. A genetic algorithm has been developed for finding the best placement for four actuators to produce an uncoupled pitch moment. The genetic algorithm has been extended to find the minimum number of actuators required to provide uncoupled pitch, roll, and yaw control. A simplified, untapered, unswept wing is the model for each application.

Rogers, James L.↗
NASA NTRS1991

Genetic algorithm based input selection for a neural network function approximator with applications to SSME health monitoring

A genetic algorithm is used to select the inputs to a neural network function approximator. In the application considered, modeling critical parameters of the space shuttle main engine (SSME), the functional relationship between measured parameters is unknown and complex. Furthermore, the number of possible input parameters is quite large. Many approaches have been used for input selection, but they are either subjective or do not consider the complex multivariate relationships between parameters. Due to the optimization and space searching capabilities of genetic algorithms they were employed to systematize the input selection process. The results suggest that the genetic algorithm can generate parameter lists of high quality without the explicit use of problem domain knowledge. Suggestions for improving the performance of the input selection process are also provided.

Peck, Charles C.↗
DOE OSTI2025

Low Mutation Rate and Atypical Mutation Spectrum in Prasinoderma coloniale : Insights From an Early Diverging Green Lineage

Mutations are the ultimate source of genetic diversity on which natural selection and genetic drift act, playing a crucial role in evolution and long-term adaptation. At the molecular level, the spontaneous mutation rate (µ), defined as the number of mutations per base per generation, thus determines the adaptive potential of a species. Through a mutation accumulation experiment, we estimate the mutation rate and spectrum in Prasinoderma coloniale, a phytoplankton species from an early-branching lineage within the Archaeplastida, characterized by an unusually high genomic guanine-cytosine (GC) content (69.8%). We find that P. coloniale has a very low total mutation rate of µ = 2.00 × 10 -10 . The insertion–deletion mutation rate is almost 5 times lesser than the single nucleotide mutation rate with µ ID = 3.40 × 10 -11 and µ SNM = 1.62 × 10 -10 . Prasinoderma coloniale also exhibits an atypical mutational spectrum: While essentially all other eukaryotes show a bias toward GC to AT mutations, no evidence of this AT-bias is observed in P. coloniale. Since cytosine methylation is known to be mutagenic, we hypothesized that this may result from an absence of C-methylation. Surprisingly, we found high levels of C-methylation (14% in 5mC, 25% in 5mCG contexts). Methylated cytosines did not show increased mutation rates compared with unmethylated ones, not supporting the prevailing notion that C-methylation universally leads to higher mutation rates. Overall, P. coloniale combines a GC-rich genome with a low mutation rate and original mutation spectrum, suggesting the almost universal AT-bias may not have been present in the ancestor of the green lineage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Testing for the Genomic Footprint of Conflict Between Life Stages in an Angiosperm and Moss Species

Abstract The maintenance of genetic variation by balancing selection is of considerable interest to evolutionary biologists. An important but understudied potential driver of balancing selection is antagonistic pleiotropy between diploid and haploid stages of the plant life cycle. Despite sharing a common genome, sporophytes (2n) and gametophytes (n) may undergo differential or even opposing selection. Theoretical work suggests antagonistic pleiotropy between life stages can generate balancing selection and maintain genetic variation. Despite the potential for far-reaching consequences of gametophytic selection, empirical tests of its pleiotropic effects (neutral, synergistic, or antagonistic) on sporophytes are generally lacking. Here, we examined the population genomic signals of selection across life stages in the angiosperm Rumex hastatulus and the moss Ceratodon purpureus. We compared gene expression between life stages and sexes, combined with neutral diversity statistics and the analysis of the distribution of fitness effects. In contrast to what would be predicted under balancing selection due to antagonistic pleiotropy, we found that unbiased genes between life stages were under stronger purifying selection, likely explained by a predominance of synergistic pleiotropy between life stages and strong purifying selection on broadly expressed genes. In addition, we found that 30% of candidate genes under balancing selection in R. hastatulus were located within inversion polymorphisms. Our findings provide novel insights into the genome-wide characteristics and consequences of plant gametophytic selection.

Evolutionary Biology↗