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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Data for Cloning and Characterization of a Panel of Mitochondrial Targeting Sequences for Compartmentalization Engineering in Saccharomyces cerevisiae

Mitochondrion is generally considered as the most promising subcellular organelle for compartmentalization engineering. Much progress has been made in reconstituting whole metabolic pathways in the mitochondria of yeast to harness the precursor pools (i.e., pyruvate and acetyl-CoA), bypass competing pathways, and minimize transportation limitations. However, only a few mitochondrial targeting sequences (MTSs) have been characterized (i.e., MTS of COX4), limiting the application of compartmentalization engineering for multigene biosynthetic pathways in the mitochondria of yeast. In the present study, based on the mitochondrial proteome, a total of 20 MTSs were cloned and the efficiency of these MTSs in targeting heterologous proteins, including the Escherichia coli FabI and enhanced green fluorescence protein (EGFP) into the mitochondria was evaluated by growth complementation and confocal microscopy. After systematic characterization, six of the well-performed MTSs were chosen for the colocalization of complete biosynthetic pathways into the mitochondria. As proof of concept, the full α-santalene biosynthetic pathway consisting of 10 expression cassettes capable of converting acetyl-coA to α-santalene was compartmentalized into the mitochondria, leading to a 3.7-fold improvement in the production of α-santalene. The newly characterized MTSs should contribute to the expanded metabolic engineering and synthetic biology toolbox for yeast mitochondrial compartmentalization engineering.

Conversion↗
DOE OSTI2021

High Throughput expression and characterization of laccases in Saccharomyces cerevisiae [Poster]

We are working to generate fundamental understanding of enzymatic depolymerization of lignin and using this understanding to engineer mixtures of enzymes that catalyze the reactions necessary to efficiently depolymerize lignin into defined fragments. Over the years the enzymes involved in these processes have been difficult to study, because 1) the enzymes thought to be most important, fungal laccases and peroxidases, are very difficult to express in soluble, active form; 2) the full complement of required enzymes and whether or not they act synergistically is not known; 3) analysis of bond cleavage events is difficult due to the lack of analytical tools for measuring bond cleavage events in either polymeric lignin or model lignin-like compounds.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Tracking alternative versions of the galactose gene network in the genus Saccharomyces and their expansion after domestication

In this yeast, the study of trait variation at the population level led to the detection of distinct sets of GAL structural genes. Besides the reference version, present in most strains, alternative highly divergent alleles supporting faster growth on galactose were recently uncovered in strains associated with dairy products and also in some wild strains.

Genetics↗
NASA NTRS2017

The Transcriptional Response of Diverse Saccharomyces Cerevisiae Strains to Simulated Microgravity

Spaceflight imposes multiple stresses on biological systems resulting in genome-scale adaptations. Understanding these adaptations and their underlying molecular mechanisms is important to clarifying and reducing the risks associated with spaceflight. One such risk is infection by microbes present in spacecraft and their associated systems and inhabitants. This risk is compounded by results suggesting that some microbes may exhibit increased virulence after exposure to spaceflight conditions. The yeast, S. cerevisiae, is a powerful microbial model system, and its response to spaceflight has been studied for decades. However, to date, these studies have utilized common lab strains. Yet studies on trait variation in S. cerevisiae demonstrate that these lab strains are not representative of wild yeast and instead respond to environmental stimuli in an atypical manner. Thus, it is not clear how transferable these results are to the wild S. cerevisiae strains likely to be encountered during spaceflight. To determine if diverse S. cerevisiae strains exhibit a conserved response to simulated microgravity, we will utilize a collection of 100 S. cerevisiae strains isolated from clinical, environmental and industrial settings. We will place selected S. cerevisiae strains in simulated microgravity using a high-aspect rotating vessel (HARV) and document their transcriptional response by RNA-sequencing and quantify similarities and differences between strains. Our research will have a strong impact on the understanding of how genetic diversity of microorganisms effects their response to spaceflight, and will serve as a platform for further studies.

yeast↗
NASA NTRS2017

The Transcriptional Response of Diverse Saccharomyces Cerevisiae Strains to Simulated Microgravity

Spaceflight imposes multiple stresses on biological systems resulting in genome-scale adaptations. Understanding these adaptations and their underlying molecular mechanisms is important to clarifying and reducing the risks associated with spaceflight. One such risk is infection by microbes present in spacecraft and their associated systems and inhabitants. This risk is compounded by results suggesting that some microbes may exhibit increased virulence after exposure to spaceflight conditions. The yeast, S. cerevisiae, is a powerful microbial model system, and it's response to spaceflight has been studied for decades. However, to date, these studies have utilized common lab strains. Yet studies on trait variation in S. cerevisiae demonstrate that these lab strains are not representative of wild yeast and instead respond to environmental stimuli in an atypical manner. Thus, it is not clear how transferable these results are to the wild S. cerevisiae strains likely to be encountered during spaceflight. To determine if diverse S. cerevisiae strains exhibit a conserved response to simulated microgravity, we will utilize a collection of 100 S. cerevisiae strains isolated from clinical, environmental and industrial settings. We will place selected S. cerevisiae strains in simulated microgravity using a high-aspect rotating vessel (HARV) and document their transcriptional response by RNA-sequencing and quantify similarities and differences between strains. Our research will have a strong impact on the understanding of how genetic diversity of microorganisms effects their response to spaceflight, and will serve as a platform for further studies.

genetic diversity↗
NASA NTRS2018

The Transcriptional Response of Diverse Saccharomyces cerevisiae Strains to Simulated Microgravity

Spaceflight imposes multiple stresses on biological systems resulting in genome-scale adaptations. Understanding these adaptations and their underlying molecular mechanisms is important to clarifying and reducing the risks associated with spaceflight. One such risk is infection by microbes present in spacecraft and their associated systems and inhabitants. This risk is compounded by results suggesting that some microbes may exhibit increased virulence after exposure to spaceflight conditions. The yeast, S. cerevisiae, is a powerful microbial model system, and it's response to spaceflight has been studied for decades. However, to date, these studies have utilized common lab strains. Yet studies on trait variation in S. cerevisiae demonstrate that these lab strains are not representative of wild yeast and instead respond to environmental stimuli in an a typical manner. Thus, it is not clear how transferable these results are to the wild S. cerevisiae strains likely to be encountered during spaceflight. To determine if diverse S. cerevisiae strains exhibit a conserved response to simulated microgravity, we will utilize a collection of 100 S. cerevisiae strains isolated from clinical, environmental and industrial settings. We will place selected S. cerevisiae strains in simulated microgravity using a high-aspect rotating vessel (HARV) and document their transcriptional response by RNA-sequencing and quantify similarities and differences between strains. Our research will have a strong impact on the understanding of how genetic diversity of microorganisms effects their response to spaceflight, and will serve as a platform for further studies.

spaceflight↗
NASA NTRSDate not supplied

Investigating Biological Responses to Space-like Radiation using the yeast Saccharomyces cerevisiae

As we plan crewed missions to the Moon, Mars, and beyond, it is essential to understand how persistent exposure to space radiation affects biology. Unlike on the International Space Station, where crew support and sample return are possible, experiments for long-duration missions require autonomous systems with no sample return. Human cells would be ideal biosensors, but limitations in culture methods, extended prelaunch storage, and long flight durations make it very difficult to keep human cells alive. Unlike other model systems, yeast can survive the constraints of long-duration spaceflight. Despite a billion years of evolution separating yeast from humans, we share homology in hundreds of genes important for basic cell function, including responses to DNA damage. Thus, yeast are excellent biosensors for detecting types/extent of damage induced by space radiation. BioSentinel is NASA’s latest biological CubeSat, and first interplanetary space bioscience mission. BioSentinel is manifested on Artemis 1, the first test flight of NASA’s Space Launch System, in the coming year. The BioSensor payload within BioSentinel contains two yeast strains. The wild type serves as a control for health and “normal” DNA damage repair (DDR). The rad51 deletion mutant is defective for DDR and will undergo alterations to growth and metabolism as it accumulates radiation damage. Changes in growth and metabolic activity will be measured using a 3-color LED detection system and the metabolic redox dye alamarBlue®. Preliminary tests indicate a significant change in alamarBlue response to space-like, low-dose ionizing radiation. We will discuss these findings in four parts – Introduction to biological CubeSats and the BioSentinel mission (presented by Sergio Santa Maria), preliminary responses to space-like ionizing radiation (presented here), a deeper dive into tracking metabolic changes after exposure to ionizing radiation (presented by Diana Gentry), and a look into methods for correcting flight optical data (presented by Abbey Kim). This work is funded by NASA’s Advanced Exploration Systems.

CubeSat↗
DOE OSTI2020

Postglacial migration shaped the genomic diversity and global distribution of the wild ancestor of lager-brewing hybrids

The wild, cold-adapted parent of hybrid lager-brewing yeasts, Saccharomyces eubayanus, has a complex and understudied natural history. The exploration of this diversity can be used both to develop new brewing applications and to enlighten our understanding of the dynamics of yeast evolution in the wild. Here, we integrate whole genome sequence and phenotypic data of 200 S. eubayanus strains, the largest collection known to date. S. eubayanus has a multilayered population structure, consisting of two major populations that are further structured into six subpopulations. Four of these subpopulations are found exclusively in the Patagonian region of South America; one is found predominantly in Patagonia and sparsely in Oceania and North America; and one is specific to the Holarctic ecozone. Plant host associations differed between subpopulations and between S. eubayanus and its sister species, Saccharomyces uvarum. S. eubayanus is most abundant and genetically diverse in northern Patagonia, where some locations harbor more genetic diversity than is found outside of South America, suggesting that northern Patagonia east of the Andes was a glacial refugium for this species. All but one subpopulation shows isolation-by-distance, and gene flow between subpopulations is low. However, there are strong signals of ancient and recent outcrossing, including two admixed lineages, one that is sympatric with and one that is mostly isolated from its parental populations. Using our extensive biogeographical data, we build a robust model that predicts all known and a handful of additional regions of the globe that are climatically suitable for S. eubayanus, including Europe where host accessibility and competitive exclusion by other Saccharomyces species may explain its continued elusiveness. We conclude that this industrially relevant species has rich natural diversity with many factors contributing to its complex distribution and natural history.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Lulabcodes/Coarse-grained_Sc_Model

This repository contains the source code for the coarse-grained, systemic, and dynamic model of Saccharomyces cerevisiae. Related publishments: Emergence of Orchestrated and Dynamic Metabolism of Saccharomyces cerevisiae. Coarse-Grained Modeling Elucidates Differential Metabolism of Saccharomyces cerevisiae under Varied Nutrient Limitations.

Lai, Yi-Hui (Cindy)↗
NASA NTRS2006

Studying Functions of All Yeast Genes Simultaneously

A method of studying the functions of all the genes of a given species of microorganism simultaneously has been developed in experiments on Saccharomyces cerevisiae (commonly known as baker's or brewer's yeast). It is already known that many yeast genes perform functions similar to those of corresponding human genes; therefore, by facilitating understanding of yeast genes, the method may ultimately also contribute to the knowledge needed to treat some diseases in humans. Because of the complexity of the method and the highly specialized nature of the underlying knowledge, it is possible to give only a brief and sketchy summary here. The method involves the use of unique synthetic deoxyribonucleic acid (DNA) sequences that are denoted as DNA bar codes because of their utility as molecular labels. The method also involves the disruption of gene functions through deletion of genes. Saccharomyces cerevisiae is a particularly powerful experimental system in that multiple deletion strains easily can be pooled for parallel growth assays. Individual deletion strains recently have been created for 5,918 open reading frames, representing nearly all of the estimated 6,000 genetic loci of Saccharomyces cerevisiae. Tagging of each deletion strain with one or two unique 20-nucleotide sequences enables identification of genes affected by specific growth conditions, without prior knowledge of gene functions. Hybridization of bar-code DNA to oligonucleotide arrays can be used to measure the growth rate of each strain over several cell-division generations. The growth rate thus measured serves as an index of the fitness of the strain.

Stolc, Viktor↗
DOE OSTI2024

A deep learning-guided automated workflow in LipidOz for detailed characterization of fungal fatty acid unsaturation by ozonolysis

Understanding fungal lipid biology and metabolism is critical for antifungal target discovery as lipids play central roles in cellular processes. Nuances in lipid structural differences can significantly impact their functions, making it necessary to characterize lipids in detail to enable and understanding of their roles in these complex systems. In particular, lipid double bond (DB) locations are an important component of lipid structure that can only be determined using a few specialized analytical techniques. Ozone-induced dissociation mass spectrometry (OzID-MS) is one such technique that uses ozone to break lipid DBs, producing pairs of characteristic fragments that allow the determination of DB positions. In this work we apply OzID-MS and LipidOz software to analyze the complex lipids of Saccharomyces cerevisiae yeast strains transfected with different fatty acid desaturases from Histoplasma capsulatum to determine the specific unsaturated lipids produce. The automated data analysis in LipidOz made the determination of DB positions from this large dataset more practical, but manual verification for all targets was still time-consuming. The DL model reduces manual involvement in data analysis, but since it was trained using mammalian lipid extracts, the prediction accuracy on yeast-derived data was reduced. We addressed both shortcomings by retraining the DL model to act as a pre-filter to prioritize targets for automated analysis, providing confident manually verified results but requiring less computational time and manual effort. Our workflow resulted in the determination of novel DB positions and enzymatic specificity.

mass spectrometry, deep learning, Lipidomics, doub↗
DOE OSTI2025

pH adjustment increases biofuel production from inhibitory switchgrass hydrolysates

Biofuels derived from renewable and sustainable lignocellulosic biomass, such as switchgrass, offer a promising means to limit greenhouse gas emissions. However, switchgrass grown under drought conditions contains high levels of chemical compounds that inhibit microbial conversion to biofuels. Fermentation of drought switchgrass hydrolysates by engineered Saccharomyces cerevisiae and Zymomonas mobilis results in lower ethanol production than does fermentation of hydrolyzed switchgrass from a typical rainfall year. Here, it is demonstrated that this inhibitory effect can be alleviated by altering the pH of drought switchgrass hydrolysates produced by two different pretreatment methods: Ammonia Fiber Expansion (AFEX) and Soaking in Aqueous Ammonia (SAA). Fermentation rates and biofuel production by Saccharomyces cerevisiae and Zymomonas mobilis were higher at pH 5.8 than at pH 5.0 from all feedstock years and following both pretreatment methods. SAA pretreatment of drought switchgrass furthermore enabled increased fermentation rates and biofuel titers compared to AFEX pretreatment. A synthetic mimic of switchgrass hydrolysate was developed and identified relief from pH-dependent inhibition by lignocellulose-derived inhibitors as the cause of increased biofuel production above a pH of 5.0. These results demonstrate that SAA pretreatment and pH adjustment can significantly improve fermentation and biofuel production from inhibitory feedstocks by industrial microorganisms.

09 BIOMASS FUELS↗
DOE OSTI2024

Bridging the gap: linking Torulaspora delbrueckii genotypes to fermentation phenotypes and wine aroma

Abstract Climate change and consumer preferences are driving innovation in winemaking, with a growing interest in non-Saccharomyces species. Among these, Torulaspora delbrueckii (Td) has gained recognition for its ability to reduce volatile acidity and enhance aromatic complexity in wine. However, knowledge regarding its phenotypic and genomic diversity impacting alcoholic fermentation remains limited. Aiming to elucidate the metabolic differences between Td and Saccharomyces cerevisiae (Sc) and the Td intraspecies diversity, we conducted a comprehensive metabolic characterization of 15 Td strains. This analysis delved beyond standard fermentation parameters (kinetics and major metabolites production) to explore non-conventional aromas and establish genotype-phenotype links. Our findings confirmed that most Td strains produce less acetic acid and more succinate and glycerol than Sc. The overall aromatic profiles of Td strains differed from Sc, exhibiting higher levels of monoterpenes and higher alcohols, while producing less acetate esters, fatty acids, their corresponding ethyl esters, and lactones. Moreover, we identified the absence of genes responsible for specific aroma profiles, such as decreased ethyl esters production, as well as the absence of cell wall genes, which might negatively affect Td performance when compared to Sc. This work highlights the significant diversity within Td and underscores potential links between its genotype and phenotype.

Silva-Sousa, Flávia (ORCID:0000000307383190)↗