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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Patterns in extracellular enzyme activity and microbial diversity in deep-sea Mediterranean sediments

Deep-sea sediments are populated by diverse microbial communities that derive their nutritional requirements from the degradation of organic matter. Extracellular hydrolytic enzymes play a key role in the survival of microbes by enabling them to access and degrade complex organic compounds that are found in seafloor sediments. Despite their importance, extracellular enzymatic activity is poorly characterized at water depths greater than a few hundred meters where physical properties, such as pressure and temperature, create a unique environment for influencing enzyme behavior. In this work, we investigated microbial communities and enzyme activities in surface sediment collected at four sampling stations in the central Mediterranean Sea at water depths ranging from 800 to 2200 m. Fluorometric assays revealed that extracellular hydrolytic activity varied according to substrate type and water depth which suggests that the distributions of these enzymes within this basin are not homogenous. Furthermore, enzyme activities indicated substantial demand for phosphomonoesters and proteins, with measurable but much lower demand for polysaccharides. Barcoded amplicon sequencing of bacterial and archaeal SSU genes revealed that microbial communities varied across sampling stations and some groups displayed water-depth related trends. Our results demonstrate that heterotrophic capabilities of microbes in deep-sea Mediterranean sediments can differ substantially even within the same region.

16S rRNA↗
DOE OSTI2024

Phyllosticta paracitricarpa is synonymous with the EU quarantine fungus P. citricarpa based on phylogenomic analyses

Phyllosticta citricarpa is an important citrus-pathogen and a quarantine organism in the European Union. Its recently described relative, P. paracitricarpa, is very closely related and not listed as a quarantine organism. P. paracitricarpa is very difficult to distinguish from P. citricarpa, since its morphological features overlap and the barcoding gene sequences that were originally used to delimit them as distinct species have a low number of species-specific polymorphisms that have subsequently been shown to overlap between the two clades. Therefore, we performed extensive genomic analyses to determine whether the genetic variation between P. citricarpa and P. paracitricarpa strains should be considered to represent infraspecific variation within P. citricarpa, or whether it is indicative of distinct species. Using a phylogenomic analysis with 3,000 single copy ortholog genes and whole-genome comparisons, we determined that the variation between P. citricarpa and P. paracitricarpa can be considered as infraspecies variation within P. citricarpa. We also determined the level of variation in mitochondrial assemblies of several Phyllosticta species and concluded there are only minimal differences between the assemblies of P. citricarpa and P. paracitricarpa. Thus, using several orthogonal approaches, we here demonstrate that variation within the nuclear and mitochondrial genomes of other Phyllosticta species is larger than variation between genomes obtained from P. citricarpa and P. paracitricarpa strains. Thus, P. citricarpa and P. paracitricarpa should be considered as conspecific.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

High-throughput, single-microbe genomics with strain resolution, applied to a human gut microbiome

We present Microbe-seq, a high-throughput single-microbe method that yields strain-resolved genomes from complex microbial communities. We encapsulate individual microbes into droplets with microfluidics and liberate their DNA, which we amplify, tag with droplet-specific barcodes, and sequence. We use Microbe-seq to explore the human gut microbiome; we collect stool samples from a single individual, sequence over 20,000 microbes, and reconstruct nearly-complete genomes of almost 100 bacterial species, including several with multiple subspecies strains. We use these genomes to probe genomic signatures of microbial interactions: we reconstruct the horizontal gene transfer (HGT) network within the individual and observe far greater exchange within the same bacterial phylum than between different phyla. We probe bacteria-virus interactions; unexpectedly, we identify a significant in vivo association between crAssphage, an abundant bacteriophage, and a single strain of Bacteroides vulgatus. Microbe-seq contributes high-throughput culture-free capabilities to investigate genomic blueprints of complex microbial communities with single-microbe resolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

RB-TnSeq elucidates dicarboxylic-acid-specific catabolism in β-proteobacteria for improved plastic monomer upcycling

Dicarboxylic acids are key components of many polymers and plastics, making them a target for both engineered microbial degradation and sustainable bioproduction. In this study, we generated a comprehensive data set of functional evidence for the genetic basis of dicarboxylic and fatty acid metabolism using randomly barcoded transposon sequencing (RB-TnSeq). We identified four β-proteobacteria that displayed robust growth with dicarboxylic acid sole carbon source and cultured their mutant libraries with dicarboxylic and fatty acids with carbon chain lengths from C3 to C12. The resulting fitness data suggested that dicarboxylic and fatty acid metabolisms are largely distinct, and different sets of β-oxidation genes are required for catabolizing dicarboxylic versus fatty acids of the same carbon chain lengths. In addition, we identified transcriptional regulators and transporters with strong fitness phenotypes related to dicarboxylic acid utilization. In Ralstonia sp. UNC404CL21Col (R. CL21), we deleted two transcriptional repressors to improve its utilization of short-chain dicarboxylic acids. We exploited the diacid-utilizing catabolism of R. CL21 to upcycle a mock mixture of the dicarboxylic acids produced when polyethylene is oxidized. After introducing a heterologous indigoidine production pathway, this engineered Ralstonia produced 0.56 ± 0.02 g/L indigoidine from a mixture of dicarboxylic acids as a carbon source, demonstrating the potential of R. CL21 to upcycle plastic wastes to products derived from tricarboxylic acid (TCA) cycle intermediates. IMPORTANCE: Upcycling the carbon in plastic wastes to value-added products is a promising approach to address the plastic waste and climate crises, and dicarboxylic acid metabolism is an important facet of several approaches. Improving our understanding of the genetic basis of this metabolism has the potential to uncover new enzymes and genetic parts for engineered pathways involving dicarboxylic acids. Our data set is the most comprehensive interrogation of dicarboxylic acid catabolism to date, and this work will be of utility to researchers interested in both plastics bioproduction and upcycling applications.

Pearson, Allison N↗
DOE OSTI2020

A large accessory protein interactome is rewired across environments

To characterize how protein-protein interaction (PPI) networks change, we quantified the relative PPI abundance of 1.6 million protein pairs in the yeast Saccharomyces cerevisiae across 9 growth conditions, with replication, for a total of 44 million measurements. Our multi-condition screen identified 13,764 pairwise PPIs, a 3-fold increase over PPIs identified in one condition. A few 'immutable' PPIs are present across all conditions, while most 'mutable' PPIs are rarely observed. Immutable PPIs aggregate into highly connected 'core' network modules, with most network remodeling occurring within a loosely connected 'accessory' module. Mutable PPIs are less likely to co-express, co-localize, and be explained by simple mass action kinetics, and more likely to contain proteins with intrinsically disordered regions, implying that environment-dependent association and binding is critical to cellular adaptation. Our results show that protein interactomes are larger than previously thought and contain highly dynamic regions that reorganize to drive or respond to cellular changes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Machine learning analysis of RB-TnSeq fitness data predicts functional gene modules in Pseudomonas putida KT2440

ABSTRACT There is growing interest in engineering Pseudomonas putida KT2440 as a microbial chassis for the conversion of renewable and waste-based feedstocks, and metabolic engineering of P. putida relies on the understanding of the functional relationships between genes. In this work, independent component analysis (ICA) was applied to a compendium of existing fitness data from randomly barcoded transposon insertion sequencing (RB-TnSeq) of P. putida KT2440 grown in 179 unique experimental conditions. ICA identified 84 independent groups of genes, which we call fModules (“functional modules”), where gene members displayed shared functional influence in a specific cellular process. This machine learning-based approach both successfully recapitulated previously characterized functional relationships and established hitherto unknown associations between genes. Selected gene members from fModules for hydroxycinnamate metabolism and stress resistance, acetyl coenzyme A assimilation, and nitrogen metabolism were validated with engineered mutants of P. putida . Additionally, functional gene clusters from ICA of RB-TnSeq data sets were compared with regulatory gene clusters from prior ICA of RNAseq data sets to draw connections between gene regulation and function. Because ICA profiles the functional role of several distinct gene networks simultaneously, it can reduce the time required to annotate gene function relative to manual curation of RB-TnSeq data sets. IMPORTANCE This study demonstrates a rapid, automated approach for elucidating functional modules within complex genetic networks. While Pseudomonas putida randomly barcoded transposon insertion sequencing data were used as a proof of concept, this approach is applicable to any organism with existing functional genomics data sets and may serve as a useful tool for many valuable applications, such as guiding metabolic engineering efforts in other microbes or understanding functional relationships between virulence-associated genes in pathogenic microbes. Furthermore, this work demonstrates that comparison of data obtained from independent component analysis of transcriptomics and gene fitness datasets can elucidate regulatory-functional relationships between genes, which may have utility in a variety of applications, such as metabolic modeling, strain engineering, or identification of antimicrobial drug targets.

09 BIOMASS FUELS↗
DOE OSTI2024

LevSeq: Rapid Generation of Sequence-Function Data for Directed Evolution and Machine Learning

Sequence-function data provides valuable information about the protein functional landscape but is rarely obtained during directed evolution campaigns. Here, we present Long-read every variant Sequencing (LevSeq), a pipeline that combines a dual barcoding strategy with nanopore sequencing to rapidly generate sequence-function data for entire protein-coding genes. LevSeq integrates into existing protein engineering workflows and comes with open-source software for data analysis and visualization. The pipeline facilitates data-driven protein engineering by consolidating sequence-function data to inform directed evolution and provide the requisite data for machine learning-guided protein engineering (MLPE). LevSeq enables quality control of mutagenesis libraries prior to screening, which reduces time and resource costs. Simulation studies demonstrate LevSeq’s ability to accurately detect variants under various experimental conditions. Lastly, we show LevSeq’s utility in engineering protoglobins for new-to-nature chemistry. Widespread adoption of LevSeq and sharing of the data will enhance our understanding of protein sequence-function landscapes and empower data-driven directed evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Dual transposon sequencing profiles the genetic interaction landscape in bacteria

Gene redundancy complicates systematic characterization of gene function as single-gene deletions may not produce discernible phenotypes. We report dual transposon sequencing (dual Tn-seq), a platform for assaying the fitness of a comprehensive double mutant pool in parallel. Dual Tn-seq couples random barcode transposon site sequencing with the Cre-lox system, enabling deep sampling of 73% of the 1.3 million possible double gene deletions in Streptococcus pneumoniae. The genetic interactions identified span a wide range of biochemical processes, revealing new factors in presumably well-studied pathways, exemplified by a cytidine triphosphate synthase PyrJ. Moreover, this approach should permit further investigation of growth condition–specific genetic interactions. Because dual Tn-seq does not require the construction of a large array of single mutants, it should be readily adaptable to various microorganisms.

CTP synthesis↗
DOE OSTI2020

Multiplexed binary assembly and quantitative tracking of bacterial populations

Compositions and methods for tracking combinations of mutations in populations by coupling DNA assembly and paired-end sequencing technology with high-throughput sequencing. This allows for an unlimited number of mutation sites in a population of microorganisms to be identified, and allows sites to be sequenced across several replicates. Unique identifiers (DNA barcodes) can be used to measure fitness data by sequencing of the barcodes multiplexed with the mutation sites with high-throughput short sequencing read technology, allowing selections to be rapidly performed on populations of known combinatorial genotypes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Discovery, characterization, and metabolic engineering of Rieske non-heme iron monooxygenases for guaiacol O-demethylation

Aryl-O-demethylation is a common rate-limiting step in the catabolism of lignin-related compounds, including guaiacol. In this work, we used randomly barcoded transposon insertion sequencing (RB-TnSeq) in the bacterium Novosphingobium aromaticivorans to identify a Rieske-type guaiacol O-demethylase, GdmA. Similarity searches identified GdmA homologs in other bacteria, along with candidate reductase partners, denoted GdmB. GdmAB combinations were biochemically characterized for activity with several lignin-related substrates. Structural and sequence comparisons of vanillate- and guaiacol-specific O-demethylase active sites revealed conserved hallmarks of substrate specificity. GdmAB combinations were also evaluated in Pseudomonas putida KT2440, which does not natively utilize guaiacol. GdmAB from Cupriavidus necator N-1 demonstrated the highest rate of guaiacol turnover in vitro and in engineered P. putida strains and notably higher catalytic efficiency than a cytochrome P450 system (GcoAB) and the vanillate Rieske-type O-demethylase from P. putida (VanAB). The GdmAB O-demethylases described here expand the suite of options for microbial conversion of a model lignin-derived substrate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

RB-TnSeq identifies genetic targets for improved tolerance of Pseudomonas putida towards compounds relevant to lignin conversion

We report lignin-derived mixtures intended for bioconversion commonly contain high concentrations of aromatic acids, aliphatic acids, and salts. The inherent toxicity of these chemicals places a significant bottleneck upon the effective use of microbial systems for the valorization of these mixtures. Pseudomonas putida KT2440 can tolerate stressful quantities of several lignin-related compounds, making this bacterium a promising host for converting these chemicals to valuable bioproducts. Nonetheless, further increasing P. putida tolerance to chemicals in lignin-rich substrates has the potential to improve bioprocess performance. Accordingly, we employed random barcoded transposon insertion sequencing (RB-TnSeq) to reveal genetic determinants in P. putida KT2440 that influence stress outcomes during exposure to representative constituents found in lignin-rich process streams. The fitness information obtained from the RB-TnSeq experiments informed engineering of strains via deletion or constitutive expression of several genes. Namely, ΔgacAS, ΔfleQ, ΔlapAB, ΔttgR::P tac :ttgABC, Ptac:PP_1150:PP_1152, ..delta..relA, and ΔPP_1430 mutants showed growth improvement in the presence of single compounds, and some also exhibited greater tolerance when grown using a complex chemical mixture representative of a lignin-rich chemical stream. Overall, this work demonstrates the successful implementation of a genome-scale screening tool for the identification of genes influencing stress tolerance against notable compounds within lignin-enriched chemical streams, and the genetic targets identified herein offer promising engineering targets for improving feedstock tolerance in lignin valorization strains of P. putida KT2440.

09 BIOMASS FUELS↗
DOE OSTI2025

Bacterial fitness for plant colonization is influenced by plant growth substrate

Despite advances in our understanding of bacterial plant colonization, the extent to which growth substrate influences the molecular mechanisms enabling bacteria to efficiently colonize plants remains poorly understood. To address this, we used randomly barcoded transposon mutagenesis sequencing (RB-TnSeq) in Paraburkholderia graminis OAS925, an efficient rhizosphere colonizer, and Brachypodium distachyon grown in six different substrates. Of the 382 rhizosphere colonization genes that we identified in OAS925, 348 genes (91.1%) are dependent on the growth substrate evaluated, and 34 genes (8.9%) are shared across all the substrates. Both the core and substrate-dependent colonization genes are from multiple functional categories, demonstrating the multifaceted and major impact that plant growth substrate has on bacterial colonization. The identified colonization genes and their varied importance across plant growth substrates could not be readily explained by differences in root exudate profiles, suggesting that the substrate environment itself plays an outsized role in the ability of a bacterium to colonize the rhizosphere. Our data confirm that bacterial fitness for plant colonization is strongly influenced by plant growth substrate type and highlights the importance of taking this parameter into consideration when engineering bacterial strains for improved host colonization.

Paraburkholderia↗
DOE OSTI2023

ABF DFO with Technology Holding, Inc.

This Agile BioFoundry Directed Funding Opportunity project with Technology Holding and partners focuses on the development of both a strain of Pseudomonas putida KT2440 and a corresponding bioprocess to convert cellulosic sugars to beta-ketoadipic acid, which can be used in performance nylons and polyesters. Our approach follows the Design-Build-Test-Learn cycle wherein we have transferred learnings from muconic acid production in P. putida to develop a glucose and xylose-utilizing beta-ketoadipic acid production strain. This strain achieves 65 g/L of beta-ketoadipic acid at 0.7 g/L/hr and a C-mol yield of 0.40. We are currently on-boarding arabinose utilization as well. To identify non-intuitive strain modifications as well, we are deploying a beta-ketoadipic acid biosensor and building randomly barcoded transposon insertion sequencing (RB-TnSeq) libraries and gene over-expression libraries in beta-ketoadipic acid production strains. Moreover, we are using global metabolomics and other systems biology tools to identify off-target pathways. Lastly, we are scaling up beta-ketoadipic acid production to kg-scale production for Technology Holding to evaluate in performance polymers with their partners.

beta-ketoadipic acid↗
DOE OSTI2024

SynBio QC Dual Barcode QC (DBC) v1.0

This software was designed as a sequence validation tool for the assembly of synthetic constructs, where the constructs have a high degree of similarity and thus are barcoded prior to the sequencing library prep. It demultiplexes each FASTQ file for each barcode, then analyzes the resulting FASTQ files against a list of reference sequences for that barcode/library, combining the results from eight sequencing libraries to generate a summary, and the files needed to view the results in the Integrative Genomics Viewer (IGV) application for manual verification. This was developed for FASTQ files generated by PacBio sequencing, but could be used on any FASTQ files that do not have paired end reads. It can be used to analyze one - eight libraries at a time. Each construct is independently analyzed with only the sequences with the same barcode, in the same pooled library. Then the results are combined into a user friendly summary. This is used to identify which libraries of pooled sequences contains a perfect match, or fixable match to the reference file. This pipeline uses many freely available open source libraries, the value added is that in our application the steps of the pipeline are defined in Workflow Description Language (WDL) and run through the Cromwell workflow engine in Docker containers, for easy distribution and set up, as well as the user friendly html summary that is generated.

Simirenko, Lisa↗
DOE OSTI2024

High-throughput single-cell transcriptomics of bacteria using combinatorial barcoding

Microbial split-pool ligation transcriptomics (microSPLiT) is a high-throughput single-cell RNA sequencing method for bacteria. With four combinatorial barcoding rounds, microSPLiT can profile transcriptional states in hundreds of thousands of Gram-negative and Gram-positive bacteria in a single experiment without specialized equipment. As bacterial samples are fixed and permeabilized before barcoding, they can be collected and stored ahead of time. During the first barcoding round, the fixed and permeabilized bacteria are distributed into a 96-well plate, where their transcripts are reverse transcribed into cDNA and labeled with the first well-specific barcode inside the cells. The cells are mixed and redistributed two more times into new 96-well plates, where the second and third barcodes are appended to the cDNA via in-cell ligation reactions. Finally, the cells are mixed and divided into aliquot sub-libraries, which can be stored until future use or prepared for sequencing with the addition of a fourth barcode. It takes 4 days to generate sequencing-ready libraries, including 1 day for collection and overnight fixation of samples. Here, the standard plate setup enables single-cell transcriptional profiling of up to 1 million bacterial cells and up to 96 samples in a single barcoding experiment, with the possibility of expansion by adding barcoding rounds. The protocol requires experience in basic molecular biology techniques, handling of bacterial samples and preparation of DNA libraries for next-generation sequencing. It can be performed by experienced undergraduate or graduate students. Data analysis requires access to computing resources, familiarity with Unix command line and basic experience with Python or R.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Molecular mechanisms and environmental adaptations of flagellar loss and biofilm growth of Rhodanobacter under environmental stress

Biofilms aid bacterial adhesion to surfaces via direct and indirect mechanisms, and formation of biofilms is considered as an important strategy for adaptation and survival in suboptimal environmental conditions. However, the molecular underpinnings of biofilm formation in subsurface sediment/groundwater ecosystems where microorganisms often experience fluctuations in nutrient input, pH, and nitrate or metal concentrations are underexplored. Here, we examined biofilm formation under different nutrient, pH, metal, and nitrate regimens of 16 Rhodanobacter strains isolated from subsurface groundwater wells spanning diverse levels of pH (3.5 to 5) and nitrates (13.7 to 146 mM). Eight Rhodanobacter strains demonstrated significant biofilm growth under low pH, suggesting adaptations for survival and growth at low pH. Biofilms were intensified under aluminum stress, particularly in strains possessing fewer genetic traits associated with biofilm formation, findings warranting further investigation. Through random barcode transposon-site sequencing (RB-TnSeq), proteomics, use of specific mutants, and transmission electron microscopy analysis, we discovered flagellar loss under aluminum stress, indicating a potential relationship between motility, metal tolerance, and biofilm growth. Comparative genomic analyses revealed the absence of flagella and chemotaxis genes and the presence of a putative type VI secretion system in the highly biofilm-forming strain FW021-MT20. In this study we identified genetic determinants associated with biofilm growth under metal stress in a predominant environmental genus, Rhodanobacter, and identified traits aiding survival and adaptation to contaminated subsurface environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

scifi-ATAC-seq: massive-scale single-cell chromatin accessibility sequencing using combinatorial fluidic indexing

Abstract Single-cell ATAC-seq has emerged as a powerful approach for revealing candidate cis-regulatory elements genome-wide at cell-type resolution. However, current single-cell methods suffer from limited throughput and high costs. Here, we present a novel technique called scifi-ATAC-seq, single-cell combinatorial fluidic indexing ATAC-sequencing, which combines a barcoded Tn5 pre-indexing step with droplet-based single-cell ATAC-seq using the 10X Genomics platform. With scifi-ATAC-seq, up to 200,000 nuclei across multiple samples can be indexed in a single emulsion reaction, representing an approximately 20-fold increase in throughput compared to the standard 10X Genomics workflow.

59 BASIC BIOLOGICAL SCIENCES↗