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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The structural basis of bacterial manganese import

Metal ions are essential for all forms of life. In prokaryotes, ATP-binding cassette (ABC) permeases serve as the primary import pathway for many micronutrients including the first-row transition metal manganese. However, the structural features of ionic metal transporting ABC permeases have remained undefined. Here, we present the crystal structure of the manganese transporter PsaBC from Streptococcus pneumoniae in an open-inward conformation. The type II transporter has a tightly closed transmembrane channel due to “extracellular gating” residues that prevent water permeation or ion reflux. Below these residues, the channel contains a hitherto unreported metal coordination site, which is essential for manganese translocation. Mutagenesis of the extracellular gate perturbs manganese uptake, while coordination site mutagenesis abolishes import. These structural features are highly conserved in metal-specific ABC transporters and are represented throughout the kingdoms of life. Collectively, our results define the structure of PsaBC and reveal the features required for divalent cation transport.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Comparing field and lab quantitative stable isotope probing for nitrogen assimilation in soil microbes

ABSTRACT Soil microbial communities play crucial roles in nutrient cycling and can help retain nitrogen in agricultural soils. Quantitative stable isotope probing (qSIP) is a useful method for investigating taxon-specific microbial growth and utilization of specific nutrients, such as nitrogen (N). Typically, qSIP is performed in a highly controlled lab setting, so the field relevance of lab qSIP studies remains unknown. We conducted and compared tandem lab and field qSIP to quantify the assimilation of 15 N by maize-associated soil prokaryotic communities at two agricultural sites. Here, we show that field qSIP with 15 N can be used to measure taxon-specific microbial N assimilation. Relative 15 N assimilation rates were generally lower in the field, and the magnitude of this difference varied by site. Rates differed by method (lab vs field) for 19% of the top N assimilating genera. The field and lab measures were more comparable when relative assimilation rates were weighted by relative abundance to estimate the proportion of N assimilated by each genus with only ~10% of taxa differing by method. Of those that differed, the taxa consistently higher in the lab were inclined to have opportunistic lifestyle strategies, whereas those higher in the field had niches reliant on plant roots or in-tact soil structure (biofilms, mycelia). This study demonstrates that 15 N-qSIP can be successfully performed using field-incubated soils to identify microbial allies in N retention and highlights the strengths and limitations of field and lab qSIP approaches. IMPORTANCE Soil microbes are responsible for critical biogeochemical processes in natural and agricultural ecosystems. Despite their importance, the functional traits of most soil organisms remain woefully under-characterized, limiting our ability to understand how microbial populations influence the transformation of elements such as nitrogen (N) in soil. Quantitative stable isotope probing (qSIP) is a powerful tool to measure the traits of individual taxa. This method has rarely been applied in the field or with 15 N to measure nitrogen assimilation. In this study, we measured genus-specific microbial nitrogen assimilation in two agricultural soils and compared field and lab 15 N qSIP methods. Our results identify taxa important for nitrogen assimilation in agricultural soils, shed light on the field relevance of lab qSIP studies, and provide guidance for the future application of qSIP to measure microbial traits in the field.

Reed, Kinsey (ORCID:0000000155178664)↗
DOE OSTI2023

Identification of recG genetic interactions in Escherichia coli by transposon sequencing

ABSTRACT Maintaining the integrity of the genome is of utmost importance for cell division and propagation. In Escherichia coli , the RecG protein has been implicated in processing branched recombination intermediates during DNA repair processes, but the primary cellular role(s) of RecG and the repair pathways in which it acts have been difficult to define. To gain additional insight into RecG function, we employed transposon sequencing to identify recG genetic interactions and reveal complementary or redundant functions. The strongest hits from the screen were the dam , uvrD , rnhA , radA , and rep genes. The conditional importance of these five genes in cells lacking recG was confirmed using a plasmid-based assay, revealing synthetic lethal interactions for most double deletion strains. Several of the synthetic lethal gene combinations (with uvrD, rep, and radA , but not rnhA or dam ) were suppressed by deletion of recF or recO , indicating that their genetic relationships involved roles in post-replication gap repair. Additionally, loss of the RecG/SSB interaction phenocopied a recG deletion when combined with dam , uvrD , radA , or rnhA deletions but not with rep . The results reinforce the idea of RecG as a general genome guardian. RecG has at least two functions. It plays an important role in the resolution of joint molecules behind the fork, formed during post-replication gap repair. RecG is also required to suppress genome over-replication caused by unscheduled replication initiation at R-loops, at double-strand breaks caused by dam inactivation, and during replication termination. IMPORTANCE DNA damage and subsequent DNA repair processes are mutagenic in nature and an important driver of evolution in prokaryotes, including antibiotic resistance development. Genetic screening approaches, such as transposon sequencing (Tn-seq), have provided important new insights into gene function and genetic relationships. Here, we employed Tn-seq to gain insight into the function of the recG gene, which renders Escherichia coli cells moderately sensitive to a variety of DNA-damaging agents when they are absent. The reported recG genetic interactions can be used in combination with future screens to aid in a more complete reconstruction of DNA repair pathways in bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Many paths, similar destinations: viruses and bacterial microcompartments form polyhedra inside cells

A large number of biological entities assemble into icosahedral structures, and these are ubiquitous throughout nature. Examples include eukaryotic and prokaryotic viral capsids and more recently discovered bacterial microcompartments. Viral capsids and bacterial microcompartments are both composed of pentameric and hexameric subunits; however, they differ in the type of cargo they encapsulate: nucleic acid or protein. Also, both depart from strict icosahedral symmetry: while this is less common in viruses, among bacterial microcompartments, diverse and heterogeneous polyhedra are common. We review shared principles and key distinctions between the self-directed assembly of various icosahedral architectures and their polyhedral variants in nature and explore the concept that there are multiple paths, influenced by their cargo, to arriving at similar protein cage morphologies.

bacterial microcompartments↗
DOE OSTI2025

Investigation of the Cyanothece nitrogenase cluster in Synechocystis : a blueprint for engineering nitrogen-fixing photoautotrophs

ABSTRACT The nitrogenase gene cluster of unicellular diazotrophic cyanobacteria, such asCyanothece, is frequently selected by nature for nitrogen-fixing partnerships with eukaryotic phototrophs. The essential cluster components that confer an advantage in such partnerships remain underexplored. To use this cluster for the development of synthetic, phototrophic nitrogen-fixing systems, a thorough and systematic analysis of its constituent genes is necessary. An initial effort to assess the possibility of engineering this cluster into non-diazotrophic phototrophs led to the generation of aSynechocystis6803 strain with significant nitrogenase activity. In the current study, a refactoring approach was taken to determine the dispensability of the non-structural genes in the cluster and define a minimal gene set for constructing a functional nitrogenase for phototrophs. Using a bottom-up strategy, thenifgenes fromCyanothece51142 were re-organized to form new operons. The genes were then seamlessly removed to determine their essentiality in the nitrogen fixation process. We demonstrate that besides the structural genesnifHDK,nifBSUENPVZTXW, as well ashesAB, are important for optimal nitrogenase function in a phototroph. We also show that optimal expression of these genes is crucial for efficient nitrogenase activity. Our findings provide a solid foundation for generating synthetic systems that will facilitate solar-powered conversion of atmospheric nitrogen into nitrogen-rich compounds, a stride toward a greener world. IMPORTANCE Integrating nitrogen fixation genes into various photosynthetic organisms is an exciting strategy for converting atmospheric nitrogen into nitrogen-rich products in a green and energy-efficient way. In order to facilitate this process, it is essential that we understand the fundamentals of the functioning of a prokaryotic nitrogen-fixing machinery in a non-diazotrophic, photoautotrophic cell. This study examines a nitrogenase gene cluster that has been naturally selected on multiple occasions for a nitrogen-fixing partnership by eukaryotic photoautotrophs and provides a basic blueprint for designing a photosynthetic organism with nitrogen-fixing ability.

Microbiology↗
DOE OSTI2025

Intestinal microbiome profile of the brown rock sea cucumber ( Holothuria glaberrima ) using ITS and 16S rDNA amplicons from direct mechanical, enzymatic, and chemical metagenomic extraction

Using direct mechanical, enzymatic, and chemical extraction methods, the intestinal microbiome of the marine invertebrate Holothuria glaberrima was obtained. ITS and 16S rDNA regions were sequenced to enrich and investigate the prokaryotic and fungal diversity profiles from different anatomical regions within the sea cucumber’s intestinal biology.

16S↗
DOE OSTI2024

The direct and indirect drivers shaping RNA viral communities in grassland soils

ABSTRACT Recent studies have revealed diverse RNA viral communities in soils. Yet, how environmental factors influence soil RNA viruses remains largely unknown. Here, we recovered RNA viral communities from bulk metatranscriptomes sequenced from grassland soils managed for 5 years under multiple environmental conditions including water content, plant presence, cultivar type, and soil depth. More than half of the unique RNA viral contigs (64.6%) were assigned with putative hosts. About 74.7% of these classified RNA viral contigs are known as eukaryotic RNA viruses suggesting eukaryotic RNA viruses may outnumber prokaryotic RNA viruses by nearly three times in this grassland. Of the identified eukaryotic RNA viruses and the associated eukaryotic species, the most dominant taxa were Mitoviridae with an average relative abundance of 72.4%, and their natural hosts, Fungi with an average relative abundance of 56.6%. Network analysis and structural equation modeling support that soil water content, plant presence, and type of cultivar individually demonstrate a significant positive impact on eukaryotic RNA viral richness directly as well as indirectly on eukaryotic RNA viral abundance via influencing the co-existing eukaryotic members. A significant negative influence of soil depth on soil eukaryotic richness and abundance indirectly impacts soil eukaryotic RNA viral communities. These results provide new insights into the collective influence of multiple environmental and community factors that shape soil RNA viral communities and offer a structured perspective of how RNA virus diversity and ecology respond to environmental changes. IMPORTANCE Climate change has been reshaping the soil environment as well as the residing microbiome. This study provides field-relevant information on how environmental and community factors collectively shape soil RNA communities and contribute to ecological understanding of RNA viral survival under various environmental conditions and virus-host interactions in soil. This knowledge is critical for predicting the viral responses to climate change and the potential emergence of biothreats.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Decomposing a San Francisco estuary microbiome using long-read metagenomics reveals species- and strain-level dominance from picoeukaryotes to viruses

ABSTRACT Although long-read sequencing has enabled obtaining high-quality and complete genomes from metagenomes, many challenges still remain to completely decompose a metagenome into its constituent prokaryotic and viral genomes. This study focuses on decomposing an estuarine metagenome to obtain a more accurate estimate of microbial diversity. To achieve this, we developed a new bead-based DNA extraction method, a novel bin refinement method, and obtained 150 Gbp of Nanopore sequencing. We estimate that there are ~500 bacterial and archaeal species in our sample and obtained 68 high-quality bins (>90% complete, <5% contamination, ≤5 contigs, contig length of >100 kbp, and all ribosomal and tRNA genes). We also obtained many contigs of picoeukaryotes, environmental DNA of larger eukaryotes such as mammals, and complete mitochondrial and chloroplast genomes and detected ~40,000 viral populations. Our analysis indicates that there are only a few strains that comprise most of the species abundances. IMPORTANCE Ocean and estuarine microbiomes play critical roles in global element cycling and ecosystem function. Despite the importance of these microbial communities, many species still have not been cultured in the lab. Environmental sequencing is the primary way the function and population dynamics of these communities can be studied. Long-read sequencing provides an avenue to overcome limitations of short-read technologies to obtain complete microbial genomes but comes with its own technical challenges, such as needed sequencing depth and obtaining high-quality DNA. We present here new sampling and bioinformatics methods to attempt decomposing an estuarine microbiome into its constituent genomes. Our results suggest there are only a few strains that comprise most of the species abundances from viruses to picoeukaryotes, and to fully decompose a metagenome of this diversity requires 1 Tbp of long-read sequencing. We anticipate that as long-read sequencing technologies continue to improve, less sequencing will be needed.

Lui, Lauren M.↗
DOE OSTI2024

MVP: a modular viromics pipeline to identify, filter, cluster, annotate, and bin viruses from metagenomes

While numerous computational frameworks and workflows are available for recovering prokaryote and eukaryote genomes from metagenome data, only a limited number of pipelines are designed specifically for viromics analysis. With many viromics tools developed in the last few years alone, it can be challenging for scientists with limited bioinformatics experience to easily recover, evaluate quality, annotate genes, dereplicate, assign taxonomy, and calculate relative abundance and coverage of viral genomes using state-of-the-art methods and standards. Here, we describe Modular Viromics Pipeline (MVP) v.1.0, a user-friendly pipeline written in Python and providing a simple framework to perform standard viromics analyses. MVP combines multiple tools to enable viral genome identification, characterization of genome quality, filtering, clustering, taxonomic and functional annotation, genome binning, and comprehensive summaries of results that can be used for downstream ecological analyses. Overall, MVP provides a standardized and reproducible pipeline for both extensive and robust characterization of viruses from large-scale sequencing data including metagenomes, metatranscriptomes, viromes, and isolate genomes. As a typical use case, we show how the entire MVP pipeline can be applied to a set of 20 metagenomes from wetland sediments using only 10 modules executed via command lines, leading to the identification of 11,656 viral contigs and 8,145 viral operational taxonomic units (vOTUs) displaying a clear beta-diversity pattern. Further, acting as a dynamic wrapper, MVP is designed to continuously incorporate updates and integrate new tools, ensuring its ongoing relevance in the rapidly evolving field of viromics. MVP is available at https://gitlab.com/ccoclet/mvp and as versioned packages in PyPi and Conda.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Proteomic Analysis of Methanococcus voltae Grown in the Presence of Mineral and Nonmineral Sources of Iron and Sulfur

Iron sulfur (Fe-S) proteins are essential and ubiquitous across all domains of life, yet the mechanisms underpinning assimilation of iron (Fe) and sulfur (S) and biogenesis of Fe-S clusters are poorly understood. This is particularly true for anaerobic methanogenic archaea, which are known to employ more Fe-S proteins than other prokaryotes. Here, we utilized a deep proteomics analysis of Methanococcus voltae A3 cultured in the presence of either synthetic pyrite (FeS 2 ) or aqueous forms of ferrous iron and sulfide to elucidate physiological responses to growth on mineral or nonmineral sources of Fe and S. The liquid chromatography-mass spectrometry (LCMS) shotgun proteomics analysis included 77% of the predicted proteome. Through a comparative analysis of intra- and extracellular proteomes, candidate proteins associated with FeS 2 reductive dissolution, Fe and S acquisition, and the subsequent transport, trafficking, and storage of Fe and S were identified. The proteomic response shows a large and balanced change, suggesting that M. voltae makes physiological adjustments involving a range of biochemical processes based on the available nutrient source. Among the proteins differentially regulated were members of core methanogenesis, oxidoreductases, membrane proteins putatively involved in transport, Fe-S binding ferredoxin and radical S-adenosylmethionine proteins, ribosomal proteins, and intracellular proteins involved in Fe-S cluster assembly and storage. This work improves our understanding of ancient biogeochemical processes and can support efforts in biomining of minerals. Clusters of iron and sulfur are key components of the active sites of enzymes that facilitate microbial conversion of light or electrical energy into chemical bonds. The proteins responsible for transporting iron and sulfur into cells and assembling these elements into metal clusters are not well understood. Using a microorganism that has an unusually high demand for iron and sulfur, we conducted a global investigation of cellular proteins and how they change based on the mineral forms of iron and sulfur. Understanding this process will answer questions about life on early earth and has application in biomining and sustainable sources of energy.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Evolutionary History of Plant Metabolism

Tremendous chemical diversity is the hallmark of plants and is supported by highly complex biochemical machinery. Plant metabolic enzymes originated and were transferred from eukaryotic and prokaryotic ancestors and further diversified by the unprecedented rates of gene duplication and functionalization experienced in land plants. Unlike microbes, which have frequent horizontal gene transfer events and multiple inputs of energy and organic carbon, land plants predominantly rely on organic carbon generated from CO 2 and have experienced very few, if any, gene transfers during their recent evolutionary history. As such, plant metabolic networks have evolved in a stepwise manner and on existing networks under various evolutionary constraints. This review aims to take a broader view of plant metabolic evolution and lay a framework to further explore evolutionary mechanisms of the complex metabolic network. Understanding the underlying metabolic and genetic constraints is also an empirical prerequisite for rational engineering and redesigning of plant metabolic pathways.

Plant Sciences↗
DOE OSTI2026

Integrase-On-Demand-Pipeline Data Set

Files needed to run the Integrase-On-Demand-Pipeline, a program designed to provide users with a list of putative attachment site and integrase pairs for a prokaryotic genome of interest. isles.pkl: Serialized python-object file, containing a dictionary of attachment site sequences and reference genomic island information extracted from the Genomic island database ints.gff: Gene format file containing annotations for all integrases referenced in isles.pkl. The source genome, gene coordinates, integrase name, protein IDs and amino acid sequence included. reps.msh: Binary file containing 1000 128-bit MurmurHash3 hashes for >80,000 genomes

McClain, Hannah Marie [Sandia National Laboratorie↗
DOE OSTI2020

DelPlasmid: Finding Plasmids with Deep Learning and Machine Learning v1

Extrachromosomal genetic elements or plasmids are an important driver of DNA exchange and genetic innovation in prokaryotes. The success of plasmids has been attributed to their independent replication from host cell chromosomes and their frequent self-transfer. In recent years, the Department of Energy has recognized the importance of plasmid DNA to the viability and success of microbial communities and JGI has responded with funding to support the research and development of new methods and tools for the efficient sequencing of plasmid DNA. LBNL #2019-037 is responsive to this call.

Andreopoulos, William↗
DOE OSTI2023

IMG Annotation Pipeline (IMGAP) v5.1.13

The IMG Annotation Pipeline is a collection of Bash and Python scripts to control a workflow for structural and functional annotation of prokaryotic genomes, metagenomes, and metatranscriptomes. The bash scripts in general control the overall workflow and are wrappers around 3rd party executables (not included in repo) that predict features or functions. Whereas the Python scripts do post-processing of raw output in terms of filtering or format transformation and in some cases contain some logic for picking the correct predictions or resolving overlaps. The pipeline is tailored to produce results required by IMG (https://img.jgi.doe.gov/) and is executed on every dataset submitted to IMG via https://img.jgi.doe.gov/submit. These consist of internal genomes, metagenomes and metatranscriptomes sequenced and assembled at the JGI, as well as datasets submitted by external users (non-lab/JGI affiliates).

Huntemann, Marcel↗
DOE OSTI2025

GenomeFace v1.0

GenomeFace is meta-genome binning software. Metagenomic binning, the process of grouping DNA sequences into taxonomic units, is critical for understanding the functions, interactions, and evolutionary dynamics of microbial communities. We propose a deep learning approach to binning using two neural networks, one based on composition and another on environmental abundance, dynamically weighting the contribution of each based on characteristics of the input data. Trained on over 43,000 prokaryotic genomes, our network for composition-based binning is inspired by metric learning techniques used for facial recognition. Using a task-specific, multi-GPU accelerated algorithm to cluster the embeddings produced by our network, our binner leverages marker genes observed to be universally present in nearly all taxa to grade and select optimal clusters of sequences from a hierarchy of candidates. We evaluate our approach on four simulated datasets with known ground truth. Our linear time integration of marker genes recovers more near complete genomes than state of the art but computationally infeasible solutions using them, while being over an order of magnitude faster. Finally, we demonstrate the scalability and acuity of our approach by testing it on three of the largest metagenome assemblies ever performed. Compared to other binners, we produced 47%-183% more near complete genomes. From these datasets, we find over the genomes of over 3000 new candidate species which have never been previously cataloged, representing a potential 4% expansion of the known bacterial tree of life.

Lettich, Richard [Lawrence Berkeley National Labor↗
DOE OSTI2026

V-HAMSTeR v1.0.0

V-HAMSTeR is a bioinformatics software tool designed to predict the hosts of viruses directly from genomic sequences. It can be used by researchers to predict animal, prokaryotic, plant, protist or fungal viral hosts including viruses that may be fragmented or discovered in environmental metagenomic datasets. Features & Uses: The software employs a novel dual-stream deep learning architecture that dynamically fuses implicit sequence embeddings from a genomic foundation model with 13 explicit, handcrafted biological features (e.g., coding density and strand switch rates). To ensure maximum reliability, V=HAMSTeR deploys a 5-fold deep ensemble calibrated via Joint Temperature Scaling, providing users with statistically rigorous confidence probabilities. It also features an automated sequence chunking and mean-pooling module to seamlessly process variable-length contigs. Advantages Over Similar Technologies: Existing tools (e.g., IPEV, RNAVirHost) typically rely on either basic k-mers or isolated neural networks. V-HAMSTeR's hybrid architecture captures both broad genomic context and specific biological motifs that standalone foundation models often miss. Furthermore, unlike competitor tools that struggle with incomplete data or exhibit extreme overconfidence, V-HAMSTeR is explicitly benchmarked and mathematically calibrated for fragmented assemblies (1kb–10kb). This makes it uniquely robust, accurate, and trustworthy for the messy reality of real-world environmental viromics.

Grigson, Susie [Lawrence Berkeley National Laborat↗