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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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Trichoderma harzianum transcriptome in response to the nematode Pratylenchus brachyurus

The root-lesion nematode Pratylenchus brachyurus causes extensive damage in several crops of economic importance. Fungi of Trichoderma genus have been highlighted as biopesticide agents in the control of several plant diseases. Although it is already widely used in agriculture, there are few studies, especially at the molecular level, that evaluate T. harzianum in the control of P. brachyurus . The aim of the present study was to investigate how interaction with the nematode P. brachyurus influences gene expression of T. harzianum , by using RNA-Seq analysis. Of the 13,932 predicted genes in the T. harzianum genome, 2,922 (21%) were differentially expressed in the presence of P. brachyurus , in relation to the absence of the nematode. Among the differentially expressed genes, we found genes encoding Carbohydrate Active EnZymes (CAZy), MEROPS peptidases, and proteins related to secondary metabolite synthesis. 118 pathways were identified as related to the biosynthesis of secondary metabolites. Additionally, the analysis identified 136 metabolic pathways related to these differentially expressed genes, among which we highlight: aminobenzoate degradation, xenobiotic metabolism by cytochrome P450, and sesquiterpenoid and triterpenoid biosynthesis. Our results contribute to a better understanding of the response of T. harzianum to the nematode P. bracyurus , the potential for biocontrol by this fungus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Fermentative conversion of unpretreated plant biomass: A thermophilic threshold for indigenous microbial growth

Here, naturally occurring, microbial contaminants were found in plant biomasses from common bioenergy crops and agricultural wastes. Unexpectedly, indigenous thermophilic microbes were abundant, raising the question of whether they impact thermophilic consolidated bioprocessing fermentations that convert biomass directly into useful bioproducts. Candidate microbial platforms for biomass conversion, Acetivibrio thermocellus (basionym Clostridium thermocellum; T opt 60 °C) and Caldicellulosiruptor bescii (T opt 78 °C), each degraded a wide variety of plant biomasses, but only A. thermocellus was significantly affected by the presence of indigenous microbial populations harbored by the biomass. Indigenous microbial growth was eliminated at ≥75 °C, conditions where C. bescii thrives, but where A. thermocellus cannot survive. Therefore, 75 °C is the thermophilic threshold to avoid sterilizing pre-treatments on the biomass that prevents native microbes from competing with engineered microbes and forming undesirable by-products. Thermophiles that naturally grow at and above 75 °C offer specific advantages as platform microorganisms for biomass conversion into fuels and chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Continuous culture of anaerobic fungi enables growth and metabolic flux tuning without use of genetic tools

Anaerobic gut fungi (AGF) have potential to valorize lignocellulosic biomass owing to their diverse repertoire of carbohydrate-active enzymes (CAZymes). However, AGF metabolism is poorly understood, and no stable genetic tools are available to manipulate growth and metabolic flux to enhance production of specific targets, e.g., cells, CAZymes, or metabolites. Herein, a cost-effective, Arduino-based, continuous-flow anaerobic bioreactor with online optical density control is presented to probe metabolism and predictably tune fluxes in Caecomyces churrovis. Varying the C. churrovis turbidostat setpoint titer reliably controlled growth rate (from 0.04 to 0.20 h −1 ), metabolic flux, and production rates of acetate, formate, lactate, and ethanol. Bioreactor setpoints to maximize production of each product were identified, and all continuous production rates significantly exceed batch rates. Formate spike-ins increased lactate flux and decreased acetate, ethanol, and formate fluxes. The bioreactor and turbidostat culture schemes demonstrated here offer tools to tailor AGF fermentations to application-specific hydrolysate product profiles.

Agriculture↗
DOE OSTI2023

Biological upgrading of biogas assisted with membrane supplied hydrogen gas in a three-phase upflow reactor

Biogas upgrading via CO 2 conversion to CH 4 is an emerging technology for renewable natural gas production and carbon management, but its development is limited by the low H 2 gas to liquid phase transfer. Herein, an innovative biogas upgrading system employing a three-phase design was studied for CO 2 conversion with H 2 supply via gas-permeable membrane. The system produced biogas consisted of 74.1 ± 7.1 % CH 4 and 25.9 ± 7.1 % CO 2 with intermittent injection of H 2 . When H 2 supply was continuous, the CH 4 content increased to 91.6 ± 2.2 % at a H 2 :CO 2 ratio of 4.4. Although a higher ratio of 5.5 could result in a higher CH 4 percentage of 95.2 ± 2.5 %, biogas production rate started to decrease. The removal efficiency of organic contents remained above 90 % throughout the experiment. Microbial community analysis corroborated the findings, showing that hydrogenotrophic Methanobacteriaceae was more prevalent in the biofilm (71.9 %) compared to that in anaerobic digestion (15.8 %) and effluent (14.1 %).

Agriculture↗
DOE OSTI2021

Audacity of huge: overcoming challenges of data scarcity and data quality for machine learning in computational materials discovery

Machine learning (ML)-accelerated discovery requires large amounts of high-fidelity data to reveal predictive structure–property relationships. For many properties of interest in materials discovery, the challenging nature and high cost of data generation has resulted in a data landscape that is both scarcely populated and of dubious quality. Data-driven techniques starting to overcome these limitations include the use of consensus across functionals in density functional theory, the development of new functionals or accelerated electronic structure theories, and the detection of where computationally demanding methods are most necessary. When properties cannot be reliably simulated, large experimental data sets can be used to train ML models. In the absence of manual curation, increasingly sophisticated natural language processing and automated image analysis are making it possible to learn structure–property relationships from the literature. Finally, models trained on these data sets will improve as they incorporate community feedback.

36 MATERIALS SCIENCE↗