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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 235 records · Page 13

Improved photosynthetic capacity and photosystem I oxidation via heterologous metabolism engineering in cyanobacteria

Significance Cyanobacteria have been increasingly explored as a biotechnological platform, although their economic feasibility relies in part on the capacity to maximize their photosynthetic, solar-to-biomass energy conversion efficiency. Here we show that cyanobacterial photosynthetic capacity can be increased by diverting cellular resources toward heterologous, energy-storing metabolic pathways and by reducing electron flow to photoprotective, but energy-dissipating, oxygen reduction reactions. We further show that these heterologous sinks can partially contribute to photosystem I (PSI) oxidation, suggesting an engineering strategy to improve both energy storage capacity and robustness by selective diversion of excess photosynthetic capacity to productive processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Chromosome-level genome assembly of Quercus variabilis provides insights into the molecular mechanism of cork thickness

Quercus variabilis is a deciduous woody species with high ecological and economic value and is a major source of cork in East Asia. Cork from thick softwood sheets have higher commercial value than those from thin sheets. It is extremely difficult to genetically improve Q. variabilis to produce high quality softwood due to the lack of genomic information. Here, we present a high-quality chromosomal genome assembly for Q. variabilis with length of 791,89 Mb and 54,606 predicted genes. Comparative analysis of protein sequences of Q. variabilis with 11 other species revealed that specific and expanded gene families were significantly enriched in the "fatty acid biosynthesis" pathway in Q. variabilis, which may contribute to the formation of its unique cork. Additionally, based on weighted correlation network analysis of time-course (i.e., five important developmental ages) gene expression data in thick-cork versus thin-cork genotypes of Q. variabilis, we identified one co-expression gene module associated with the thick-cork trait. Within this co-expression gene module, 10 hub genes were associated with suberin biosynthesis. Furthermore, we identified a total of 198 suberin biosynthesis-related new candidate genes that were up-regulated in trees with a thick cork layer relative to those with a thin cork layer. Also, we found that some genes related to cell expansion and cell division were highly expressed in trees with a thick cork layer. Collectively, our results revealed that two metabolic pathways (i.e., suberin biosynthesis, fatty acid biosynthesis), along with other genes involved in cell expansion, cell division, and transcriptional regulation, were associated with the thick-cork trait in Q. variabilis, providing insights into the molecular basis of cork development and knowledge for informing genetic improvement of cork thickness in Q. variabilis and closely related species.

59 BASIC BIOLOGICAL SCIENCES↗

Corn stover variability drives differences in bisabolene production by engineered Rhodotorula toruloides

Microbial conversion of lignocellulosic biomass represents an alternative route for production of biofuels and bioproducts. While researchers have mostly focused on engineering strains such as Rhodotorula toruloides for better bisabolene production as a sustainable aviation fuel, less is known about the impact of the feedstock heterogeneity on bisabolene production. Critical material attributes like feedstock composition, nutritional content, and inhibitory compounds can all influence bioconversion. Further, the given feedstocks can have a marked influence on selection of suitable pretreatment and hydrolysis technologies, optimizing the fermentation conditions, and possibly even modifying the microorganism's metabolic pathways, to better utilize the available feedstock. Here, this work aimed to examine and understand how variations in corn stover batches, anatomical fractions, and storage conditions impact the efficiency of bisabolene production by R. toruloides. All of these represent different facets of feedstock heterogeneity. Deacetylation, mechanical refining, and enzymatic hydrolysis of these variable feedstocks served as the basis of this research. The resulting hydrolysates were converted to bisabolene via fermentation, a sustainable aviation fuel precursor, using an engineered R. toruloides strain. This study showed that different sources of feedstock heterogeneity can influence microbial growth and product titer in counterintuitive ways, as revealed through global analysis of protein expression. The maximum bisabolene produced by R. toruloides was on the stalk fraction of corn stover hydrolysate (8.89 ± 0.47 g/L). Further, proteomics analysis comparing the protein expression between the anatomic fractions showed that proteins relating to carbohydrate metabolism, energy production, and conversion as well as inorganic ion transport metabolism were either significantly upregulated or downregulated. Specifically, downregulation of proteins related to the iron–sulfur cluster in stalk fraction suggests a coordinated response by R. toruloides to maintain overall metabolic balance, and this was corroborated by the concentration of iron in the feedstocks.

09 BIOMASS FUELS↗

Engineering of increased L-Threonine production in bacteria by combinatorial cloning and machine learning

The goal of this study is to develop a general strategy for bacterial engineering using an integrated synthetic biology and machine learning (ML) approach. This strategy was developed in the context of increasing L-threonine production in Escherichia coli ATCC 21277. A set of 16 genes was initially selected based on metabolic pathway relevance to threonine biosynthesis and used for combinatorial cloning to construct a set of 385 strains to generate training data (i.e., a range of L-threonine titers linked to each of the specific gene combinations). Hybrid (regression/classification) deep learning (DL) models were developed and used to predict additional gene combinations in subsequent rounds of combinatorial cloning for increased L-threonine production based on the training data. As a result, E. coli strains built after just three rounds of iterative combinatorial cloning and model prediction generated higher L-threonine titers (from 2.7 g/L to 8.4 g/L) than those of patented L-threonine strains being used as controls (4-5 g/L). Interesting combinations of genes in L-threonine production included deletions of the tdh, metL, dapA, and dhaM genes as well as overexpression of the pntAB, ppc, and aspC genes. Mechanistic analysis of the metabolic system constraints for the best performing constructs offers ways to improve the models by adjusting weights for specific gene combinations. Graph theory analysis of pairwise gene modifications and corresponding levels of L-threonine production also suggests additional rules that can be incorporated into future ML models.

60 APPLIED LIFE SCIENCES↗

Genome-Resolved Metaproteomics Decodes the Microbial and Viral Contributions to Coupled Carbon and Nitrogen Cycling in River Sediments

Rivers have a significant role in global carbon and nitrogen cycles, serving as a nexus for nutrient transport between terrestrial and marine ecosystems. Although rivers have a small global surface area, they contribute substantially to worldwide greenhouse gas emissions through microbially mediated processes within the river hyporheic zone. Despite this importance, research linking microbial and viral communities to specific biogeochemical reactions is still nascent in these sediment environments. To survey the metabolic potential and gene expression underpinning carbon and nitrogen biogeochemical cycling in river sediments, we collected an integrated data set of 33 metagenomes, metaproteomes, and paired metabolomes. We reconstructed over 500 microbial metagenome-assembled genomes (MAGs), which we dereplicated into 55 unique, nearly complete medium- and high-quality MAGs spanning 12 bacterial and archaeal phyla. We also reconstructed 2,482 viral genomic contigs, which were dereplicated into 111 viral MAGs (vMAGs) of >10 kb in size. As a result of integrating gene expression data with geochemical and metabolite data, we created a conceptual model that uncovered new roles for microorganisms in organic matter decomposition, carbon sequestration, nitrogen mineralization, nitrification, and denitrification. We show how these metabolic pathways, integrated through shared resource pools of ammonium, carbon dioxide, and inorganic nitrogen, could ultimately contribute to carbon dioxide and nitrous oxide fluxes from hyporheic sediments. Further, by linking viral MAGs to these active microbial hosts, we provide some of the first insights into viral modulation of river sediment carbon and nitrogen cycling.

54 ENVIRONMENTAL SCIENCES↗

Tracking Metabolic Changes in Microbial Culture using Redox Measurements

During long-term space missions, microbial cultures accumulate the effects of low-dose radiation, microgravity, and other factors; altered growth and metabolic activity may occur before viability effects. This could affect functionality of bioreactors or other bio-enabled mission systems, as well as shed light on human health. Spaceflight microbiology studies beyond the low Earth orbit exposure afforded by the ISS have been limited. Nanosatellites offer an increasingly popular alternative for deep space missions. However, the communications delay requires biofluidic automation of a pre-defined experimental protocol, and the lack of sample return (reliance on sensors in flight) can significantly limit feasible investigations. Previous biological CubeSats (PharmaSat, O/OREOS, EcAMSat) have used alamarBlue, an off-the-shelf formulation of the redox indicator dye resazurin, to track metabolic activity, as will BioSentinel, the upcoming interplanetary microbiology experiment. A series of ground experiments (see abstracts by Liddell, Santa Maria, and A. Kim) were conducted using a microbial culture system outfitted with an electrochemical sensor array (electrical conductivity, pH, oxidation-reduction potential, and dissolved oxygen) with alamarBlue and the same strain of Saccharomyces cerevisiae as BioSentinel. By improving mapping of measured changes in alamarBlue kinetics to physicochemical changes, and ultimately to biological alterations such as shifted metabolic pathways, this work supplements data analyses from past missions and planning for future missions using alamarBlue to characterize space radiation effects. Initial results indicate that alamarBlue acts like a redox buffer; its presence significantly changes redox kinetics in otherwise identical cultures. The initial color change (blue resazurin reduced to red/pink resorufin) appears as a redox plateau. A second plateau, likely corresponding to the second color transition (resorufin to the colorless hydroresorufin), occurs at a lower redox value. The relationship to carbon source exhaustion, dissolved oxygen depletion, cell death, and measured redox potential is complex and still under study.

Tracking↗

Variation on a theme: the structures and biosynthesis of specialized fatty acid natural products in plants

SUMMARY Plants are able to construct lineage‐specific natural products from a wide array of their core metabolic pathways. Considerable progress has been made toward documenting and understanding, for example, phenylpropanoid natural products derived from phosphoenolpyruvate via the shikimate pathway, terpenoid compounds built using isopentyl pyrophosphate, and alkaloids generated by the extensive modification of amino acids. By comparison, natural products derived from fatty acids have received little attention, except for unusual fatty acids in seed oils and jasmonate‐like oxylipins. However, scattered but numerous reports show that plants are able to generate many structurally diverse compounds from fatty acids, including some with highly elaborate and unique structural features that have novel bioproduct functionalities. Furthermore, although recent work has shed light on multiple new fatty acid natural product biosynthesis pathways and products in diverse plant species, these discoveries have not been reviewed. The aims of this work, therefore, are to (i) review and systematize our current knowledge of the structures and biosynthesis of fatty acid‐derived natural products that are not seed oils or jasmonate‐type oxylipins, specifically, polyacetylenic, very‐long‐chain, and aromatic fatty acid‐derived natural products, and (ii) suggest priorities for future investigative steps that will bring our knowledge of fatty acid‐derived natural products closer to the levels of knowledge that we have attained for other phytochemical classes.

54 ENVIRONMENTAL SCIENCES↗

Diatom volatile organic compound production is driven by diel metabolism and the cell cycle

Introduction: Volatile organic compounds (VOCs) are small, low-vapor-pressure molecules emitted from the surface ocean into the atmosphere. In the atmosphere, VOCs can change OH reactivity and condense onto particles to become cloud condensation nuclei. VOCs are produced by phytoplankton, but the conditions leading to VOC accumulation in the surface ocean are poorly understood.Methods: In this study, VOC accumulation was measured in real time over a 12 h day−12 h night cycle in the model diatom Phaeodactylum tricornutum during exponential growth.Results: Sixty-three m/z signals were produced in higher concentrations than in cell-free controls. All VOCs, except methanol, were continuously produced over 24 h. All VOCs accumulated to higher concentrations during the day compared to the night, and 11 VOCs exhibited distinct accumulation patterns during the morning hours. Twenty-seven VOCs were associated with known metabolic pathways in P. tricornutum, with most VOCs involved in amino acid and fatty acid metabolism.Discussion: Patterns of VOC production were strongly associated with diel shifts in cell physiology and the cell cycle. Diel VOC production patterns give a fundamental understanding of the first steps in VOC accumulation in the surface ocean.

Biological and medical sciences↗

Genome-Scale Metabolic Modeling Enables In-Depth Understanding of Big Data

Genome-scale metabolic models (GEMs) enable the mathematical simulation of the metabolism of archaea, bacteria, and eukaryotic organisms. GEMs quantitatively define a relationship between genotype and phenotype by contextualizing different types of Big Data (e.g., genomics, metabolomics, and transcriptomics). In this review, we analyze the available Big Data useful for metabolic modeling and compile the available GEM reconstruction tools that integrate Big Data. We also discuss recent applications in industry and research that include predicting phenotypes, elucidating metabolic pathways, producing industry-relevant chemicals, identifying drug targets, and generating knowledge to better understand host-associated diseases. In addition to the up-to-date review of GEMs currently available, we assessed a plethora of tools for developing new GEMs that include macromolecular expression and dynamic resolution. Finally, we provide a perspective in emerging areas, such as annotation, data managing, and machine learning, in which GEMs will play a key role in the further utilization of Big Data.

59 BASIC BIOLOGICAL SCIENCES↗

Insights into genetic determinants of volatile fatty acid catabolism in Cupriavidus necator H16

The soil bacterium Cupriavidus necator H16 is a promising host for upgrading waste-derived volatile fatty acids (VFAs) into renewable biochemicals. While bacterial VFA metabolic pathways are well understood, the C. necator genome encodes multiple enzymes for each catabolic step, and the degree of substrate specificity among these homologs is currently unknown. To gain insight into the catabolism of VFA substrates in C. necator, we performed transcriptomics on cells grown with acetate, propionate, butyrate, valerate, or hexanoate as the sole source of carbon and energy. These data revealed that C. necator upregulates multiple sets of genes putatively involved in substrate activation and β-oxidation in response to VFAs. To better understand this redundancy, we performed biochemical and genetic deletion studies of acyl-CoA synthetase enzymes upregulated during growth on VFA substrates. These results demonstrated the functional redundancy of the C. necator VFA catabolism and led to the identification of a gene cluster, H16_B1332-H16_B1337, that contains several genes that are important for the efficient catabolism of hexanoate. Constitutive expression of a second copy of these hexanoate catabolism genes did not improve growth of C. necator on hexanoate, suggesting that other factors (e.g., redox, transport, or toxicity) may be limiting for growth. Collectively, this work provides new insight into how C. necator uses metabolic regulation to effectively utilize VFA substrates and uncovers the important role of the gene cluster H16_B1332-H16_B1337 in the catabolism of hexanoate.

09 BIOMASS FUELS↗

Photosynthetic Electron Flows and Networks of Metabolite Trafficking to Sustain Metabolism in Photosynthetic Systems

Photosynthetic eukaryotes have metabolic pathways that occur in distinct subcellular compartments. However, because metabolites synthesized in one compartment, including fixed carbon compounds and reductant generated by photosynthetic electron flows, may be integral to processes in other compartments, the cells must efficiently move metabolites among the different compartments. This review examines the various photosynthetic electron flows used to generate ATP and fixed carbon and the trafficking of metabolites in the green alga Chlamydomomas reinhardtii; information on other algae and plants is provided to add depth and nuance to the discussion. We emphasized the trafficking of metabolites across the envelope membranes of the two energy powerhouse organelles of the cell, the chloroplast and mitochondrion, the nature and roles of the major mobile metabolites that move among these compartments, and the specific or presumed transporters involved in that trafficking. These transporters include sugar-phosphate (sugar-P)/inorganic phosphate (Pi) transporters and dicarboxylate transporters, although, in many cases, we know little about the substrate specificities of these transporters, how their activities are regulated/coordinated, compensatory responses among transporters when specific transporters are compromised, associations between transporters and other cellular proteins, and the possibilities for forming specific ‘megacomplexes’ involving interactions between enzymes of central metabolism with specific transport proteins. Finally, we discuss metabolite trafficking associated with specific biological processes that occur under various environmental conditions to help to maintain the cell’s fitness. These processes include C4 metabolism in plants and the carbon concentrating mechanism, photorespiration, and fermentation metabolism in algae.

Plant Sciences↗

Increasing the Thermodynamic Driving Force of the Phosphofructokinase Reaction in Clostridium thermocellum

Glycolysis is an ancient, widespread, and highly conserved metabolic pathway that converts glucose into pyruvate. In the canonical pathway, the phosphofructokinase (PFK) reaction plays an important role in controlling flux through the pathway. Clostridium thermocellum has an atypical glycolysis and uses pyrophosphate (PP i ) instead of ATP as the phosphate donor for the PFK reaction. The reduced thermodynamic driving force of the PP i -PFK reaction shifts the entire pathway closer to thermodynamic equilibrium, which has been predicted to limit product titers. Here, in this study, we replace the PP i -PFK reaction with an ATP-PFK reaction. We demonstrate that the local changes are consistent with thermodynamic predictions: the ratio of fructose 1,6-bisphosphate to fructose-6-phosphate increases, and the reverse flux through the reaction (determined by 13 C labeling) decreases. The final titer and distribution of fermentation products, however, do not change, demonstrating that the thermodynamic constraints of the PP i -PFK reaction are not the sole factor limiting product titer.

59 BASIC BIOLOGICAL SCIENCES↗

Better together: Protein partnerships for lineage-specific oil accumulation

Plant-derived oils are a major agricultural product that exist in both ubiquitous forms such as common vegetable oils and in specialized forms such as castor oil and coconut oil. These specialized oils are the result of lineage-specific metabolic pathways that create oils rich in unusual fatty acids. Considerable progress has been made toward understanding the enzymes that mediate fatty acid biosynthesis, triacylglycerol assembly, and oil storage. However, efforts to translate this knowledge into renewable bioproducts via engineered oil-producing plants and algae have had limited success. Here, we review recent evidence that protein–protein interactions in each of the three major phases of oil formation appear to have profound effects on specialized oil accumulation. We suggest that furthering our knowledge of the noncatalytic attributes of enzymes and other proteins involved in oil formation will be a critical step toward creating renewable bioproducts derived from high performing, engineered oilseeds.

59 BASIC BIOLOGICAL SCIENCES↗

BMC Caller: a webtool to identify and analyze bacterial microcompartment types in sequence data

Bacterial microcompartments (BMCs) are protein-based organelles found across the bacterial tree of life. They consist of a shell, made of proteins that oligomerize into hexagonally and pentagonally shaped building blocks, that surrounds enzymes constituting a segment of a metabolic pathway. The proteins of the shell are unique to BMCs. They also provide selective permeability; this selectivity is dictated by the requirements of their cargo enzymes. We have recently surveyed the wealth of different BMC types and their occurrence in all available genome sequence data by analyzing and categorizing their components found in chromosomal loci using HMM (Hidden Markov Model) protein profiles. To make this a “do-it yourself” analysis for the public we have devised a webserver, BMC Caller (https://bmc-caller.prl.msu.edu), that compares user input sequences to our HMM profiles, creates a BMC locus visualization, and defines the functional type of BMC, if known. Shell proteins in the input sequence data are also classified according to our function-agnostic naming system and there are links to similar proteins in our database as well as an external link to a structure prediction website to easily generate structural models of the shell proteins, which facilitates understanding permeability properties of the shell. Additionally, the BMC Caller website contains a wealth of information on previously analyzed BMC loci with links to detailed data for each BMC protein and phylogenetic information on the BMC shell proteins. Our tools greatly facilitate BMC type identification to provide the user information about the associated organism’s metabolism and enable discovery of new BMC types by providing a reference database of all currently known examples.

59 BASIC BIOLOGICAL SCIENCES↗

Predicting metabolic modules in incomplete bacterial genomes with MetaPathPredict

The reconstruction of complete microbial metabolic pathways using ‘omics data from environmental samples remains challenging. Computational pipelines for pathway reconstruction that utilize machine learning methods to predict the presence or absence of KEGG modules in incomplete genomes are lacking. Here, we present MetaPathPredict, a software tool that incorporates machine learning models to predict the presence of complete KEGG modules within bacterial genomic datasets. Using gene annotation data and information from the KEGG module database, MetaPathPredict employs deep learning models to predict the presence of KEGG modules in a genome. MetaPathPredict can be used as a command line tool or as a Python module, and both options are designed to be run locally or on a compute cluster. Benchmarks show that MetaPathPredict makes robust predictions of KEGG module presence within highly incomplete genomes.

59 BASIC BIOLOGICAL SCIENCES↗

A distinct class of ferredoxin:NADP + oxidoreductase enzymes driving thermophilic ethanol production

Biofuel production from lignocellulosic biomass offers a transformative solution to reduce global fossil fuel dependency. Certain thermophilic anaerobes, including Clostridium thermocellum, show promise for renewable ethanol production due to their ability to break down plant material at high temperatures. However, achieving commercially viable ethanol yields has proven challenging despite extensive engineering efforts. Here, we characterized 27 ferredoxin:NADP + oxidoreductase (Fnor) enzymes for their enzyme activity, nicotinamide cofactor specificity, thermotolerance, and functional expression in C. thermocellum . We identified a subset of 10 of these enzymes as a novel class of Fnor enzymes suited for metabolic pathways aimed at high-titer ethanol production. When expressed in engineered C. thermocellum , these enzymes increased ethanol production up to 2.2-fold. These findings establish a novel ethanol pathway and provide insights into physiological roles and biotechnological applications of this new class of Fnor enzymes.

09 BIOMASS FUELS↗

Evaluating inkjet dispenser/liquid vortex capture-mass spectrometry for single-cell metabolomics in Hep G2 steatosis caused by tamoxifen

Single-cell mass spectrometry (MS) is advancing our understanding of metabolic pathways in heterogeneous cell populations; however, many techniques are slow or require disruptive sample preparations. This study evaluated coupling a modified HP D100 single-cell inkjet dispenser with liquid vortex capture-mass spectrometry (D100/LVC-MS). The D100 is a single-cell inkjet dispenser capable of titrating solutions and isolating single cells via disposable cassettes equipped with microfluidic channels and an impedance sensor. The LVC-MS enables high-throughput capture, lysis, and ionization of analytes for mass spectrometric analysis. The D100/LVC-MS system was characterized through titration and single-cell experiments. Propranolol titration demonstrated linearity across a broad concentration range using the D100/LVC-MS system. Additionally, Hep G2 hepatocarcinoma cells and Chlamydomonas reinhardtii algae were used to showcase the D100’s high-throughput or low-buffer-volume single-cell dispensing strategies. The D100/LVC-MS system’s performance was validated by evaluating tamoxifen-induced steatosis in Hep G2 cells. Tamoxifen, associated with nonalcoholic fatty liver disease in breast cancer patients following long-term use, was tested in Hep G2 cells at 20 µM for 72 h against DMSO-treated controls. High-throughput analysis of 500 cells per condition, completed in 25 min per run, demonstrated the system’s efficiency. The D100/LVC-MS system simultaneously quantified tamoxifen and measured triglycerides and phosphatidylcholines. Triglycerides were upregulated in the tamoxifen-treated cells and the results indicated two distinct cell populations, differing in tamoxifen and phosphatidylcholines levels, suggesting heterogeneity within the treated population. In conclusion, these findings highlight the D100/LVC-MS system as a cost-effective, high-throughput platform for single-cell metabolomics and lipidomics, with significant potential for evaluating metabolic alterations.

Chromatography↗