Screening Efficient Tandem Organic Solar Cells with Machine Learning and Genetic Algorithms
Not Available
14 SOLAR ENERGY↗
SEARCH · Engineering Papers
Results for “genetics”
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.
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Comparative Genomic and Genetic Evidence on a Role for the OarX Protein in Thiamin Salvage
Not Available
59 BASIC BIOLOGICAL SCIENCES↗
Knowledge graph-aided Bayesian active learning for top- K genetic interaction discovery
In silico methods for predicting the effects of multi-gene perturbations hold great promise for advancing functional genomics, computational drug discovery, and disease modeling. However, the development of these predictive algorithms for mammalian systems has been hampered by limited datasets and high experimental costs. In this study, we present a Bayesian active learning framework designed to discover pairwise host gene knockdowns that effectively inhibit viral proliferation in an in vitro HIV-1 infection model. Our method leverages a biological knowledge graph as side information and employs a computationally efficient batch diversification approach. We evaluated this framework using a dataset of viral load measurements obtained from multi-day dual-gene depletion experiments, encompassing all possible pairwise knockdowns of over 350 host genes associated with HIV infection. We demonstrate that our framework rapidly identifies the most effective gene knockdown pairs for reducing viral load. Furthermore, we show that incorporating side information enhances performance during the early stages of active learning (low data regime), while our batch diversification strategy significantly boosts performance in later stages (high data regime). This framework is general and can be adapted to explore gene interactions in other contexts, such as synthetic lethality prediction and mapping epistatic effects across quantitative trait loci.
Computational biology and bioinformatics↗
Genetic structure of Miscanthus sinensis and Miscanthus sacchariflorus in Japan indicates a gradient of bidirectional but asymmetric introgression
Unilateral introgression from diploids to tetraploids has been hypothesized to be an important evolutionary mechanism in plants. However, few examples have been definitively identified, perhaps because data of sufficient depth and breadth were difficult to obtain before the advent of affordable high-density genotyping. Throughout Japan, tetraploid Miscanthus sacchariflorus and diploid Miscanthus sinensis are common, and occasionally hybridize. In this study, 667 M. sinensis and 78 M. sacchariflorus genotypes from Japan were characterized using 20 704 SNPs and ten plastid microsatellites. Similarity of SNP genotypes between diploid and tetraploid M. sacchariflorus indicated that the tetraploids originated through autopolyploidy. Structure analysis indicated a gradient of introgression from diploid M. sinensis into tetraploid M. sacchariflorus throughout Japan; most tetraploids had some M. sinensis DNA. Among phenotypically M. sacchariflorus tetraploids, M. sinensis ancestry averaged 7% and ranged from 1-39%, with introgression greatest in southern Japan. Unexpectedly, rare (~1%) diploid M. sinensis individuals from northern Japan were found with 6-27% M. sacchariflorus ancestry. Population structure of M. sinensis in Japan included three groups, and was driven primarily by distance, and secondarily by geographic barriers such as mountains and straits. Miscanthus speciation is a complex and dynamic process. In contrast to limited introgression between diploid M. sacchariflorus and M. sinensis in northern China, selection for adaptation to a moderate maritime climate probably favoured cross-ploidy introgressants in southern Japan. Ultimately, these results will help guide the selection of Miscanthus accessions for the breeding of biomass cultivars.
59 BASIC BIOLOGICAL SCIENCES↗
Genetic analysis of Physcomitrella patens identifies ABSCISIC ACID NON-RESPONSIVE , a regulator of ABA responses unique to basal land plants and required for desiccation tolerance
The anatomically simple plants that first colonized land must have acquired molecular and biochemical adaptations to drought stress. Abscisic acid (ABA) coordinates responses leading to desiccation tolerance in all land plants. We identified ABA nonresponsive mutants in the model bryophyte Physcomitrella patens and genotyped a segregating population to map and identify the ABA NON-RESPONSIVE (ANR) gene encoding a modular protein kinase comprising an N-terminal PAS domain, a central EDR domain, and a C-terminal MAPKKK-like domain. anr mutants fail to accumulate dehydration tolerance-associated gene products in response to drought, ABA, or osmotic stress and do not acquire ABA-dependent desiccation tolerance. The crystal structure of the PAS domain, determined to 1.7-Å resolution, shows a conserved PAS-fold that dimerizes through a weak dimerization interface. Targeted mutagenesis of a conserved tryptophan residue within the PAS domain generates plants with ABA nonresponsive growth and strongly attenuated ABA-responsive gene expression, whereas deleting this domain retains a fully ABA-responsive phenotype. ANR orthologs are found in early-diverging land plant lineages and aquatic algae but are absent from more recently diverged vascular plants. Lastly, we propose that ANR genes represent an ancestral adaptation that enabled drought stress survival of the first terrestrial colonizers but were lost during land plant evolution.
59 BASIC BIOLOGICAL SCIENCES↗
An Improved Genetic Algorithm approach to the Unit Commitment/Economic Dispatch problem
The deployment of new technologies, the importance of accurately modeling the dynamics of the generating units and the introduction of new policies are making the solution of the Unit Commitment/Economic Dispatch problem more and more complicated.In the present scenario, traditionally followed scheduling criteria might not lead to the optimal fleet configuration any more. In addition, most of the widely used techniques have limited capabilities at modeling the nonlinear dynamics of committed power plants. When realistic power systems comprising of several tens of generating units are modeled, the resulting optimization problem turns to be computationally intensive for the current computing capabilities. In this paper, an improved version of a GA-based optimization algorithm is presented. A detailed methodology aimed at obtaining a more efficient version of the GA, and a more detailed and accurate description of the flexible operation flexibility of the power plants is described.
genetic algorithm↗
Genetic control of photoprotection and photosystem II operating efficiency in plants
Summary Photoprotection against excess light via nonphotochemical quenching (NPQ) is indispensable for plant survival. However, slow NPQ relaxation under low light conditions can decrease yield of field‐grown crops up to 40%. Using semi‐high‐throughput assay, we quantified the kinetics of NPQ and photosystem II operating efficiency (ΦPSII) in a replicated field trial of more than 700 maize ( Zea mays ) genotypes across 2 yr. Parametrized kinetics data were used to conduct genome‐wide association studies. For six candidate genes involved in NPQ and ΦPSII kinetics in maize the loss of function alleles of orthologous genes in Arabidopsis ( Arabidopsis thaliana ) were characterized: two thioredoxin genes, and genes encoding a transporter in the chloroplast envelope, an initiator of chloroplast movement, a putative regulator of cell elongation and stomatal patterning, and a protein involved in plant energy homeostasis. Since maize and Arabidopsis are distantly related, we propose that genes involved in photoprotection and PSII function are conserved across vascular plants. The genes and naturally occurring functional alleles identified here considerably expand the toolbox to achieving a sustainable increase in crop productivity.
59 BASIC BIOLOGICAL SCIENCES↗
A split ribozyme system for in vivo plant RNA imaging and genetic engineering
RNA plays a central role in plants, governing various cellular and physiological processes. Monitoring its dynamic abundance provides a discerning understanding of molecular mechanisms underlying plant responses to internal (developmental) and external (environmental) stimuli, paving the way for advances in plant biotechnology to engineer crops with improved resilience, quality and productivity. In general, traditional methods for analysis of RNA abundance in plants require destructive, labour-intensive and time-consuming assays. To overcome these limitations, we developed a transformative innovation for in vivo RNA imaging in plants. Specifically, we established a synthetic split ribozyme system that converts various RNA signals to orthogonal protein outputs, enabling in vivo visualisation of various RNA signals in plants. We demonstrated the utility of this system in transient expression experiments (i.e., leaf infiltration in Nicotiana benthamiana ) to detect RNAs derived from transgenes and tobacco rattle virus, respectively. Also, we successfully engineered a split ribozyme-based biosensor in Arabidopsis thaliana for in vivo visualisation of endogenous gene expression at the cellular level, demonstrating the feasibility of multi-scale (e.g., cellular and tissue level) RNA imaging in plants. Furthermore, we developed a platform for easy incorporation of different protein outputs, allowing for flexible choice of reporters to optimise the detection of target RNAs.
59 BASIC BIOLOGICAL SCIENCES↗
Automatic Identification of Closed-Loop Wind Turbine Dynamics via Genetic Programming
Wind turbines are nonlinear systems that operate in turbulent environments. As such, their behavior is difficult to characterize accurately across a wide range of operating conditions by physically meaningful models. Customarily, data-based models of wind turbines are defined in 'black box' format, lacking in both conciseness and physical intelligibility. To address this deficiency, we identify models of a modern horizontal-axis wind turbine in symbolic form using a recently developed symbolic regression method. The method used relies on evolutionary multi-objective optimization to produce succinct dynamic models from operational data without 'a priori' knowledge of the system. We compare the produced models with models derived by other methods for their estimation capacity and evaluate the tradeoff between model intelligibility and accuracy. Several succinct models are found that predict wind turbine behavior as well as or better than more complex alternatives derived by other methods.
17 WIND ENERGY↗
Unintended Laboratory-Driven Evolution Reveals Genetic Requirements for Biofilm Formation by Desulfovibrio vulgaris Hildenborough
ABSTRACT Biofilms of sulfate-reducing bacteria (SRB) are of particular interest as members of this group are culprits in corrosion of industrial metal and concrete pipelines as well as being key players in subsurface metal cycling. Yet the mechanism of biofilm formation by these bacteria has not been determined. Here we show that two supposedly identical wild-type cultures of the SRB Desulfovibrio vulgaris Hildenborough maintained in different laboratories have diverged in biofilm formation. From genome resequencing and subsequent mutant analyses, we discovered that a single nucleotide change within DVU1017, the ABC transporter of a type I secretion system (T1SS), was sufficient to eliminate biofilm formation in D. vulgaris Hildenborough. Two T1SS cargo proteins were identified as likely biofilm structural proteins, and the presence of at least one (with either being sufficient) was shown to be required for biofilm formation. Antibodies specific to these biofilm structural proteins confirmed that DVU1017, and thus the T1SS, is essential for localization of these adhesion proteins on the cell surface. We propose that DVU1017 is a member of the lapB category of microbial surface proteins because of its phenotypic similarity to the adhesin export system described for biofilm formation in the environmental pseudomonads. These findings have led to the identification of two functions required for biofilm formation in D. vulgaris Hildenborough and focus attention on the importance of monitoring laboratory-driven evolution, as phenotypes as fundamental as biofilm formation can be altered. IMPORTANCE The growth of bacteria attached to a surface (i.e., biofilm), specifically biofilms of sulfate-reducing bacteria, has a profound impact on the economy of developed nations due to steel and concrete corrosion in industrial pipelines and processing facilities. Furthermore, the presence of sulfate-reducing bacteria in oil wells causes oil souring from sulfide production, resulting in product loss, a health hazard to workers, and ultimately abandonment of wells. Identification of the required genes is a critical step for determining the mechanism of biofilm formation by sulfate reducers. Here, the transporter by which putative biofilm structural proteins are exported from sulfate-reducing Desulfovibrio vulgaris Hildenborough cells was discovered, and a single nucleotide change within the gene coding for this transporter was found to be sufficient to completely stop formation of biofilm.
59 BASIC BIOLOGICAL SCIENCES↗
Genetic modification of the shikimate pathway to reduce lignin content in switchgrass ( Panicum virgatum L.) significantly impacts plant microbiomes
Switchgrass (Panicum virgatum L.) is considered a sustainable biofuel feedstock, given its fast-impact growth, low input requirements, and high biomass yields. Improvements in bioenergy conversion efficiency of switchgrass could be made by reducing its lignin content. Engineered switchgrass that expresses a bacterial 3-dehydroshikimate dehydratase (QsuB) has reduced lignin content and improved biomass saccharification due to the rerouting of the shikimate pathway towards the simple aromatic protocatechuate at the expense of lignin biosynthesis. However, the impacts of this QsuB trait on switchgrass microbiome structure and function remain unclear. To address this, wild-type and QsuB-engineered switchgrass were grown in switchgrass field soils, and samples were collected from inflorescences, leaves, roots, rhizospheres, and bulk soils for microbiome analysis. We investigated how QsuB expression influenced switchgrass-associated fungal and bacterial communities using high-throughput Illumina MiSeq amplicon sequencing of ITS and 16S rDNA. Compared to wild-type, QsuB-engineered switchgrass hosted different microbial communities in roots, rhizosphere, and leaves. Specifically, QsuB-engineered plants had a lower relative abundance of arbuscular mycorrhizal fungi (AMF). Additionally, QsuB-engineered plants had fewer Actinobacteriota in root and rhizosphere samples. These findings may indicate that changes in the plant metabolism impact both AMF and Actinobacteriota similarly or potential interactions between AMF and the bacterial community. This study enhances understanding of plant-microbiome interactions by providing baseline microbial data for developing beneficial bioengineering strategies and by assessing nontarget impacts of engineered plant traits on the plant microbiome.
09 BIOMASS FUELS↗
Genetic tools for advancement of Synechococcus sp. PCC 7002 as a cyanobacterial chassis
Not Available
59 BASIC BIOLOGICAL SCIENCES↗
TSPmap, a tool making use of traveling salesperson problem solvers in the efficient and accurate construction of high-density genetic linkage maps
Not Available
59 BASIC BIOLOGICAL SCIENCES↗
Comprehensive Genetic Search to Clarify the Molecular Mechanism of Drug Resistance Identifies ASCL2-LEF1/TSPAN8 Axis in Colorectal Cancer
Background: Treatment-resistance genes limiting anticancer therapy have not been well clarified in colorectal cancer (CRC). We explored gene expression profiles to identify biomarkers for predicting treatment resistance to an anticancer drug in CRC. Methods: Six CRC cell lines were treated with phenylbutyrate (PB). The gene expression profiles were then compared using microarrays (harboring 54,675 genes), and genes associated with PB resistance were identified. Candidate genes were functionally examined in cell lines and clinically validated for treatment resistance in clinical samples. Results: Both DLD1 and HCT15 cells were PB resistant, while HCT116 cells were identified as PB sensitive. On microarray analysis, among the PB resistance-related genes, the expression of the genes ASCL2, LEF1, and TSPAN8 was clearly associated with PB resistance. PB-sensitive cells transfected with one of these three genes exhibited significant (P < 0.001) augmentation of PB resistance; ASCL2 induced expression of both LEF1 and TSPAN8, while neither LEF1 nor TSPAN8 induced ASCL2. RNA interference via ASCL2 knockdown made PB-resistant cells sensitive to PB and inhibited both genes. ASCL2 knockdown also played a critical role in sensitivity to treatment by 5-fluorouracil and radiotherapy in addition to PB. Finally, ASCL2 expression was significantly correlated with histological grade of rectal cancer with preoperative chemoradiation therapy. Conclusions: ASCL2 was identified as a causative gene involved in therapeutic resistance against anticancer treatments in CRC.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Rational and Evolutionary Engineering Approaches Uncover a Small Set of Genetic Changes Efficient for Rapid Xylose Fermentation in Saccharomyces cerevisiae
Economic bioconversion of plant cell wall hydrolysates into fuels and chemicals has been hampered mainly due to the inability of microorganisms to efficiently co-ferment pentose and hexose sugars, especially glucose and xylose, which are the most abundant sugars in cellulosic hydrolysates. Saccharomyces cerevisiae cannot metabolize xylose due to a lack of xylose-metabolizing enzymes. We developed a rapid and efficient xylose-fermenting S. cerevisiae through rational and inverse metabolic engineering strategies, comprising the optimization of a heterologous xylose-assimilating pathway and evolutionary engineering. Strong and balanced expression levels of the XYL1, XYL2, and XYL3 genes constituting the xyloseassimilating pathway increased ethanol yields and the xylose consumption rates from a mixture of glucose and xylose with little xylitol accumulation. The engineered strain, however, still exhibited a long lag time when metabolizing xylose above 10 g/l as a sole carbon source, defined here as xylose toxicity. Through serial-subcultures on xylose, we isolated evolved strains which exhibited a shorter lag time and improved xylose-fermenting capabilities than the parental strain. Genome sequencing of the evolved strains revealed that mutations in PHO13 causing loss of the Pho13p function are associated with the improved phenotypes of the evolved strains. Crude extracts of a PHO13-overexpressing strain showed a higher phosphatase activity on xylulose-5-phosphate (X-5-P), suggesting that the dephosphorylation of X-5-P by Pho13p might generate a futile cycle with xylulokinase overexpression. While xylose consumption rates by the evolved strains improved substantially as compared to the parental strain, xylose metabolism was interrupted by accumulated acetate. Deletion of ALD6 coding for acetaldehyde dehydrogenase not only prevented acetate accumulation, but also enabled complete and efficient fermentation of xylose as well as a mixture of glucose and xylose by the evolved strain. These findings provide direct guidance for developing industrial strains to produce cellulosic fuels and chemicals
59 BASIC BIOLOGICAL SCIENCES↗
A systematic genetic screen for genes involved in sensing inorganic phosphate availability in Saccharomyces cerevisiae
Not Available
59 BASIC BIOLOGICAL SCIENCES↗