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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A KBase Case Study on Genome-wide Transcriptomics and Plant Primary Metabolism in Sorghum

A better understanding of the genetic and metabolic mechanisms that confer stress resistance and tolerance in plants is key to engineering new crops through advanced breeding technologies. This requires a systems biology approach that builds on a genome-wide understanding of the regulation of gene expression, plant metabolism, physiology and growth. In this study, we examine the response to drought stress in Sorghum, as we leverage the tools for transcriptomics and plant metabolic modeling we have implemented at the U.S. Department of Energy Systems Biology Knowledgebase (KBase). KBase enables researchers worldwide to collaborate and advance research by allowing them to upload private or public data into the KBase Narrative Interface, empowering them to analyze this data using a rich, extensible array of computational and data-analytics tools, and allows them to securely share scientific workflows and conclusions. We demonstrate how to use the current RNA-seq tools in KBase, applicable to both plants and microbes, to assemble and quantify long transcripts and identify differentially expressed genes effectively. More specifically, we demonstrate the utility of the platform by identifying key genes that are differentially expressed during drought-stress in Sorghum bicolor, which is an important sustainable production crop plant. We then show how to use KBase tools to predict the membership of genes in metabolic pathways and examine expression data in the context of metabolic subsystems. We demonstrate the power of the platform by making the data analysis and interpretation available to the biologists in the reproducible, re-usable, point-and-click format of a KBase Narrative thus promoting FAIR (Findable, Accessible, Interoperable and Reusable) guiding principles for scientific data management and stewardship.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Elucidation of Triacylglycerol Overproduction in the C4 Bioenergy Crop Sorghum bicolor by Constraint-Based Analysis

Upregulation of triacylglycerols (TAGs) in vegetative plant tissues such as leaves has the potential to drastically increase the energy density and biomass yield of bioenergy crops. In this context, constraint-based analysis has the promise to improve metabolic engineering strategies. Here we present a core metabolism model for the C 4 biomass crop Sorghum bicolor ( iTJC1414 ) along with a minimal model for photosynthetic CO 2 assimilation, sucrose and TAG biosynthesis in C 3 plants. Extending iTJC1414 to a four-cell diel model we simulate C 4 photosynthesis in mature leaves with the principal photo-assimilatory product being replaced by TAG produced at different levels. Independent of specific pathways and per unit carbon assimilated, energy content and biosynthetic demands in reducing equivalents are about 1.3 to 1.4 times higher for TAG than for sucrose. For plant generic pathways, ATP- and NADPH-demands per CO 2 assimilated are higher by 1.3- and 1.5-fold, respectively. If the photosynthetic supply in ATP and NADPH in iTJC1414 is adjusted to be balanced for sucrose as the sole photo-assimilatory product, overproduction of TAG is predicted to cause a substantial surplus in photosynthetic ATP. This means that if TAG synthesis was the sole photo-assimilatory process, there could be an energy imbalance that might impede the process. Adjusting iTJC1414 to a photo-assimilatory rate that approximates field conditions, we predict possible daily rates of TAG accumulation, dependent on varying ratios of carbon partitioning between exported assimilates and accumulated oil droplets (TAG, oleosin) and in dependence of activation of futile cycles of TAG synthesis and degradation. We find that, based on the capacity of leaves for photosynthetic synthesis of exported assimilates, mature leaves should be able to reach a 20% level of TAG per dry weight within one month if only 5% of the photosynthetic net assimilation can be allocated into oil droplets. From this we conclude that high TAG levels should be achievable if TAG synthesis is induced only during a final phase of the plant life cycle.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Unleashing the capacity of Rhodococcus for converting lignin into lipids

Bioconversion of bioresources/wastes (e.g., lignin, chemical pulping byproducts) represents a promising approach for developing a bioeconomy to help address growing energy and materials demands. Rhodococcus, a promising microbial strain, utilizes numerous carbon sources to produce lipids, which are precursors for synthesizing biodiesel and aviation fuels. However, compared to chemical conversion, bioconversion involves living cells, which is a more complex system that needs further understanding and upgrading. Various wastes amenable to bioconversion are reviewed herein to highlight the potential of Rhodococci for producing lipid-derived bioproducts. In light of the abundant availability of these substrates, Rhodococcus’ metabolic pathways converting them to lipids are analyzed from a “beginning-to-end” view. Based on an in-depth understanding of microbial metabolic routes, genetic modifications of Rhodococcus by employing emerging tools (e.g., multiplex genome editing, biosensors, and genome-scale metabolic models) are presented for promoting the bioconversion. Co-solvent enhanced lignocellulose fractionation (CELF) strategy facilitates the generation of a lignin-derived aromatic stream suitable for the Rhodococcus’ utilization. Novel alkali sterilization (AS) and elimination of thermal sterilization (ETS) approaches can significantly enhance the bioaccessibility of lignin and its derived aromatics in aqueous fermentation media, which promotes lipid titer significantly. In order to achieve value-added utilization of lignin, biodiesel and aviation fuel synthesis from lignin and lipids are further discussed. In conclusion, the possible directions for unleashing the capacity of Rhodococcus through synergistically modifying microbial strains, substrates, and fermentation processes are proposed toward a sustainable biological lignin valorization.

09 BIOMASS FUELS↗
DOE OSTI2021

The sum is greater than the parts: exploiting microbial communities to achieve complex functions

We report multi-species microbial communities are ubiquitous in nature. The widespread prevalence of these communities is due to highly elaborated interactions among their members thereby accomplishing metabolic functions that are unattainable by individual members alone. Harnessing these communal capabilities is an emerging field in biotechnology. The rational intervention of microbial communities for the purpose of improved function has been facilitated in part by developments in multi-omics approaches, synthetic biology, and computational methods. Recent studies have demonstrated the benefits of rational interventions to human and animal health as well as agricultural productivity. Emergent technologies, such as in situ modification of complex microbial community and community metabolic modeling, represent an avenue to engineer sustainable microbial communities. In this opinion, we review relevant computational and experimental approaches to study and engineer microbial communities and discuss their potential for biotechnological applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Microbial Pathways for Cost-Effective Low-Carbon Renewable Indigoidine

Indigoidine is a bioadvantaged platform molecule with diverse applications, including use as a textile dye, biotransistor, biosolar cell, biosensor, and food coloring. There are multiple microbial hosts and carbon sources that can be used and optimized for its production, yet there is limited guidance for which options have the greatest commercial potential. Here, we consider five different host microbes and combine genome-scale metabolic models with techno-economic and lifecycle assessment models. Pseudomonas putida currently outperforms synthetic indigo production and other indigoidine-producing hosts, using glucose, xylose, and lignin-derived aromatics to produce indigoidine at a minimum selling price of $2.9/kg and a greenhouse gas (GHG) footprint of 3.5 kgCO 2e /kg. Optimizing pathways-achieving 90% of the theoretical indigoidine yield from sugars and aromatics-can reduce costs 6-7-fold and GHG emissions 3-10-fold. From a cost perspective, microbes that co-utilize aromatics are advantageous, while selecting hosts that coproduce other value-added molecules can reduce GHG emissions. System-wide improvements and the use of a low-cost, low-carbon nitrogen source are crucial for commercial viability in all cases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Reduced methane emissions in transgenic rice genotypes are associated with altered rhizosphere microbial hydrogen cycling

Rice paddies significantly contribute to atmospheric methane (CH 4 ). Here, we show that two independent rice genotypes overexpressing genes for PLANT PEPTIDES CONTAINING SULFATED TYROSINE (PSY) reduce cumulative CH 4 emissions by 38% (PSY1) and 58% (PSY2) over 70 days of growth compared with controls. Genome-resolved metatranscriptomic data from PSY rhizosphere soils reveal lower ratios of gene activities for (mostly hydrogenotrophic) CH 4 production versus consumption, decreased activity of H 2 -producing genes, and increased activity of bacterial H 2 oxidation pathways. Metabolic modeling using metagenomic and metabolomic data predicts elevated H 2 oxidation and suppressed H 2 production in the PSY rhizosphere. Assembled genomes of rhizosphere H 2 -oxidizing bacteria are enriched in genes utilizing gluconeogenic acids compared with H 2 -producing counterparts, and their activities are likely stimulated by elevated levels of gluconeogenic acids, primarily amino acids, in PSY root exudates. Overall, our study indicates that decreased CH 4 emissions are due to a lower amount of H 2 available for hydrogenotrophic methanogenesis and provides a powerful strategy to mitigate CH 4 emissions from increasingly widespread rice cultivation.

Biological and medical sciences↗
DOE OSTI2026

Continental-scale integration of soil metagenomes and organic matter chemistry reveals ubiquitous microbial capacity for chemically-recalcitrant carbon decomposition

Soil organic matter (SOM) decomposition by microorganisms is a major uncertainty in predicting terrestrial carbon–atmosphere feedbacks, partly because we lack understanding of the microbial diversity involved in depolymerizing different carbon pools across environmental gradients. We address this gap using a continental-scale dataset pairing shotgun metagenomes with high-resolution SOM chemistry, assembling 0.76 Tbp of prokaryotic MAGs (828 genomes) and identifying 66,727 SOM molecules from 47 standardized U.S. soil cores selected using respiration rates from 106 soils. Integrating these datasets reveals widespread microbial potential for depolymerizing chemically-recalcitrant SOM previously considered stable. We uncover complementary metabolic specialization between genera affiliated with two abundant bacterial orders, Rhizobiales and Chthoniobacterales, and an archaeal order, Nitrososphaerales. This metabolic partitioning is consistent across soil depths and activity levels, suggesting coordinated decomposition of complex SOM through distinct but complementary biochemical strategies. The metabolic potential for depolymerization of chemically-recalcitrant compounds is supported by the abundance of these molecules across the soils, as indicated by Fourier-Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS), and by flux balance analysis of metabolic models. Our results show that a substantial portion of ostensibly stable SOM remains vulnerable to microbial decomposition, a mechanism not captured in current Earth System Models.

Song, Young C. [Pacific Northwest National Laborat↗
DOE OSTI2022

Erroneous predictions of auxotrophies by CarveMe

We report in their paper, D. Machado et al. claim to identify ‘cooperative’ communities with many amino acid auxotrophies1. A related paper, with many of the same authors, claims that 26% of bacteria from free-living communities are amino acid auxotrophs2. The putative amino acid auxotrophies were derived from genome sequences via the metabolic models of CarveMe3 but were not validated in any way. I checked the predictions of CarveMe for prototrophic bacteria and found a high rate of spurious auxotrophies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Diet outperforms microbial transplant to drive microbiome recovery in mice

A high-fat, low-fibre Western-style diet (WD) induces microbiome dysbiosis characterized by reduced taxonomic diversity and metabolic breadth, which in turn increases risk for a wide array of metabolic, immune and systemic pathologies. Recent work has established that WD can impair microbiome resilience to acute perturbations such as antibiotic treatment, although little is known about the mechanism of impairment and the specific consequences for the host of prolonged post-antibiotic dysbiosis. Here, in this study, we characterize the trajectory by which the gut microbiome recovers its taxonomic and functional profile after antibiotic treatment in mice on regular chow (RC) or WD, and find that only mice on RC undergo a rapid successional process of recovery. Metabolic modelling indicates that a RC diet promotes the development of syntrophic cross-feeding interactions, whereas in mice on WD, a dominant taxon monopolizes readily available resources without releasing syntrophic byproducts. Intervention experiments reveal that an appropriate dietary resource environment is both necessary and sufficient for rapid and robust microbiome recovery, whereas microbial transplant is neither. Furthermore, prolonged post-antibiotic dysbiosis in mice on WD renders them susceptible to infection by the intestinal pathogen Salmonella enterica serovar Typhimurium. Our data challenge widespread enthusiasm for faecal microbiota transplant (FMT) as a strategy to address dysbiosis, and demonstrate that specific dietary interventions are, at a minimum, an essential prerequisite for effective FMT, and may afford a safer, more natural and less invasive alternative.

Kennedy, M. S. [University of Chicago, IL (United ↗
DOE OSTI2020

A genomic catalog of Earth’s microbiomes

Abstract The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Metagenome-assembled genome extraction and analysis from microbiomes using KBase

Uncultivated Bacteria and Archaea account for the vast majority of species on Earth, but obtaining their genomes directly from the environment, using shotgun sequencing, has only become possible recently. In order to realize the hope of capturing Earth’s microbial genetic complement and to facilitate the investigation of the functional roles of specific lineages in a given ecosystem, technologies that accelerate the recovery of high-quality genomes are necessary. We present a series of analysis steps and data products for the extraction of high-quality metagenome-assembled genomes (MAGs) from microbiomes using the U.S. Department of Energy Systems Biology Knowledgebase (KBase) platform (http://www.kbase.us/). Overall, these steps take about a day to obtain extracted genomes when starting from smaller environmental shotgun read libraries, or up to about a week from larger libraries. In KBase, the process is end-to-end, allowing a user to go from the initial sequencing reads all the way through to MAGs, which can then be analyzed with other KBase capabilities such as phylogenetic placement, functional assignment, metabolic modeling, pangenome functional profiling, RNA-Seq and others. While portions of such capabilities are available individually from other resources, the combination of the intuitive usability, data interoperability and integration of tools in a freely available computational resource makes KBase a powerful platform for obtaining MAGs from microbiomes. While this workflow offers tools for each of the key steps in the genome extraction process, it also provides a scaffold that can be easily extended with additional MAG recovery and analysis tools, via the KBase software development kit (SDK).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

TranSyT , an innovative framework for identifying transport systems

The importance and rate of development of genome-scale metabolic models have been growing for the last few years, increasing the demand for software solutions that automate several steps of this process. However, since TRIAGE’s release, software development for the automatic integration of transport reactions into models has stalled. Here, in this paper, we present the Transport Systems Tracker (TranSyT). Unlike other transport systems annotation software, TranSyT does not rely on manual curation to expand its internal database, which is derived from highly curated records retrieved from the Transporters Classification Database and complemented with information from other data sources. TranSyT compiles information regarding transporter families and proteins, and derives reactions into its internal database, making it available for rapid annotation of complete genomes. All transport reactions have GPR associations and can be exported with identifiers from four different metabolite databases. TranSyT is currently available as a plugin for merlin v4.0 and an app for KBase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

eQuilibrator 3.0: a database solution for thermodynamic constant estimation

Abstract eQuilibrator (equilibrator.weizmann.ac.il) is a database of biochemical equilibrium constants and Gibbs free energies, originally designed as a web-based interface. While the website now counts around 1,000 distinct monthly users, its design could not accommodate larger compound databases and it lacked a scalable Application Programming Interface (API) for integration into other tools developed by the systems biology community. Here, we report on the recent updates to the database as well as the addition of a new Python-based interface to eQuilibrator that adds many new features such as a 100-fold larger compound database, the ability to add novel compounds, improvements in speed and memory use, and correction for Mg2+ ion concentrations. Moreover, the new interface can compute the covariance matrix of the uncertainty between estimates, for which we show the advantages and describe the application in metabolic modelling. We foresee that these improvements will make thermodynamic modelling more accessible and facilitate the integration of eQuilibrator into other software platforms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Increasing Rubisco as a simple means to enhance photosynthesis and productivity now without lowering nitrogen use efficiency

Summary Global demand for food may rise by 60% mid‐century. A central challenge is to meet this need using less land in a changing climate. Nearly all crop carbon is assimilated through Rubisco, which is catalytically slow, reactive with oxygen, and a major component of leaf nitrogen. Developing more efficient forms of Rubisco, or engineering CO 2 concentrating mechanisms into C 3 crops to competitively repress oxygenation, are major endeavors, which could hugely increase photosynthetic productivity (≥ 60%). New technologies are bringing this closer, but improvements remain in the discovery phase and have not been reduced to practice. A simpler shorter‐term strategy that could fill this time gap, but with smaller productivity increases (c. 10%) is to increase leaf Rubisco content. This has been demonstrated in initial field trials, improving the productivity of C 3 and C 4 crops. Combining three‐dimensional leaf canopies with metabolic models infers that a 20% increase in Rubisco increases canopy photosynthesis by 14% in sugarcane (C 4 ) and 9% in soybean (C 3 ). This is consistent with observed productivity increases in rice, maize, sorghum and sugarcane. Upregulation of Rubisco is calculated not to require more nitrogen per unit yield and although achieved transgenically to date, might be achieved using gene editing to produce transgene‐free gain of function mutations or using breeding.

Plant Sciences↗
DOE OSTI2023

Probing the in situ volumes of Arabidopsis leaf plastids using three‐dimensional confocal and scanning electron microscopy

SUMMARY Leaf plastids harbor a plethora of biochemical reactions including photosynthesis, one of the most important metabolic pathways on Earth. Scientists are eager to unveil the physiological processes within the organelle but also their interconnection with the rest of the plant cell. An increasingly important feature of this venture is to use experimental data in the design of metabolic models. A remaining obstacle has been the limited in situ volume information of plastids and other cell organelles. To fill this gap for chloroplasts, we established three microscopy protocols delivering in situ volumes based on: (i) chlorophyll fluorescence emerging from the thylakoid membrane, (ii) a CFP marker embedded in the envelope, and (iii) calculations from serial block‐face scanning electron microscopy (SBFSEM). The obtained data were corroborated by comparing wild‐type data with two mutant lines affected in the plastid division machinery known to produce small and large mesophyll chloroplasts, respectively. Furthermore, we also determined the volume of the much smaller guard cell plastids. Interestingly, their volume is not governed by the same components of the division machinery which defines mesophyll plastid size. Based on our three approaches, the average volume of a mature Col‐0 wild‐type mesophyll chloroplasts is 93 μm 3 . Wild‐type guard cell plastids are approximately 18 μm 3 . Lastly, our comparative analysis shows that the chlorophyll fluorescence analysis can accurately determine chloroplast volumes, providing an important tool to research groups without access to transgenic marker lines expressing genetically encoded fluorescence proteins or costly SBFSEM equipment.

Knoblauch, Jan↗
DOE OSTI2023

pnnl-predictive-phenomics/concerto

This software was developed to solve the problem of curating and validating individual metabolic models and combining them into different consortia.

Pino, James↗
DOE OSTI2023

MetConSIN

Metabolic Context Species Interaction Networks (MetConSIN) generates microbe-metabolte and metabolite-metabolite interaction networks using constraint based metabolic modeling. To do this, MetConSIN simulates with the dynamic FBA system and saves the sequence of interaction networks implied by that system, as well as the time-average network.

Brunner, James↗
DOE OSTI2023

FriendlyNets

FriendlyNets provides a method for assessing the promotion/inhibition effect on a microbe of a microbial community using a network of community interactions. At its core, FriendlyNets judges how much a network promotes or inhibits one of its nodes. It does this by assuming a set of dynamical systems represented by the network and using the resulting dynamics. FriendlyNets is also packaged with functions for generating a network from a set of genome-scale metabolic models (commonly called GSMs or GEMs) by simulating pairwise growth.

Brunner, James↗