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At least 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Neutrino heating in 1D, 2D, and 3D core-collapse supernovae: characterizing the explosion of high-compactness stars

Massive stars can end their lives with a successful supernova explosion (leaving behind a neutron star or, more rarely, a black hole), or a failed explosion that leaves behind a black hole. The density structure of the pre-collapse progenitor star already encodes much of the information regarding the outcome and properties of the explosion. However, the complexity of the collapse and subsequent shock expansion phases prevents drawing a straightforward connection between the pre-collapse and post-explosion properties. In order to derive such a connection several explodability studies have been performed in recent years. However, different studies can predict different explosion outcomes. In this article, we show how compactness, which is related to the average density of the star’s core, has an important role in determining the efficiency of neutrino heating, and therefore the outcome of the explosion. Commonly, high-compactness progenitors are assumed to yield failed explosions, due to their large mass accretion rates, preventing the shock from expanding. We show by analysing ~150 2D flash and F ornax simulations and 20 3D F ornax simulations that this is not the case. Instead, due to the rapid increase of neutrino heating with compactness, high-compactness progenitors lead to successful shock revival. We also show that 1D+ simulations that include v-driven convection using a mixing-length theory approach correctly reproduce this trend. Finally, we compare 1D+ models, which we show can reproduce some aspects of multi-D simulations with reasonable accuracy, with other widely used 1D models in the literature.

neutrinos↗
DOE OSTI2026

First constraints from marked angular power spectra with Subaru Hyper Suprime-Cam Survey First-Year Data

We present the first application of marked power spectra to weak lensing data, using maps from the Subaru Hyper Suprime-Cam Year 1 (HSC-Y1) survey. Marked convergence fields, constructed by weighting the convergence field with non-linear functions of its smoothed version, are designed to encode higher-order information while remaining computationally tractable. Using simulations tailored to the HSC-Y1 data, we test three mark functions that up- or down-weight different density environments. Our results show that combining multiple types of marked auto and cross-spectra improves constraints on the clustering amplitude parameter S8≡σ8Ωm/0.3 by ≈43 per cent compared to standard two-point power spectra. When applied to the HSC-Y1 data, this translates into a constraint on S8=0.807±0.024⁠. We assess the sensitivity of the marked power spectra to systematics, including baryonic effects, intrinsic alignment, photometric redshifts, and multiplicative shear bias. We note that some of the additional information introduced by the marked field originates from scales smaller than the scale cut, and is partly Gaussian in nature. This does not invalidate our systematic tests. These results demonstrate the promise of marked statistics as a practical and powerful tool for extracting non-Gaussian information from weak lensing surveys.

Cowell, Jessica A. [Oxford U.; Tokyo U., IPMU] (OR↗
DOE OSTI2020

The Architecture of Metabolism Maximizes Biosynthetic Diversity in the Largest Class of Fungi

Abstract Ecological diversity in fungi is largely defined by metabolic traits, including the ability to produce secondary or “specialized” metabolites (SMs) that mediate interactions with other organisms. Fungal SM pathways are frequently encoded in biosynthetic gene clusters (BGCs), which facilitate the identification and characterization of metabolic pathways. Variation in BGC composition reflects the diversity of their SM products. Recent studies have documented surprising diversity of BGC repertoires among isolates of the same fungal species, yet little is known about how this population-level variation is inherited across macroevolutionary timescales. Here, we applied a novel linkage-based algorithm to reveal previously unexplored dimensions of diversity in BGC composition, distribution, and repertoire across 101 species of Dothideomycetes, which are considered the most phylogenetically diverse class of fungi and known to produce many SMs. We predicted both complementary and overlapping sets of clustered genes compared with existing methods and identified novel gene pairs that associate with known secondary metabolite genes. We found that variation among sets of BGCs in individual genomes is due to nonoverlapping BGC combinations and that several BGCs have biased ecological distributions, consistent with niche-specific selection. We observed that total BGC diversity scales linearly with increasing repertoire size, suggesting that secondary metabolites have little structural redundancy in individual fungi. We project that there is substantial unsampled BGC diversity across specific families of Dothideomycetes, which will provide a roadmap for future sampling efforts. Our approach and findings lend new insight into how BGC diversity is generated and maintained across an entire fungal taxonomic class.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Functional Divergence in a Multi-gene Family Is a Key Evolutionary Innovation for Anaerobic Growth in Saccharomyces cerevisiae

The amplification and diversification of genes into large multi-gene families often mark key evolutionary innovations, but this process often creates genetic redundancy that hinders functional investigations. When the model budding yeast Saccharomyces cerevisiae transitions to anaerobic growth conditions, the cell massively induces the expression of seven serine/threonine-rich anaerobically-induced cell wall mannoproteins (anCWMPs): TIP1, TIR1, TIR2, TIR3, TIR4, DAN1, and DAN4. Here, we show that these genes likely derive evolutionarily from a single ancestral anCWMP locus, which was duplicated and translocated to new genomic contexts several times both prior to and following the budding yeast whole genome duplication (WGD) event. Based on synteny and their phylogeny, we separate the anCWMPs into four gene subfamilies. To resolve prior inconclusive genetic investigations of these genes, we constructed a set of combinatorial deletion mutants to determine their contributions toward anaerobic growth in S. cerevisiae. We found that two genes, TIR1 and TIR3, were together necessary and sufficient for the anCWMP contribution to anaerobic growth. Overexpressing either gene alone was insufficient for anaerobic growth, implying that they encode non-overlapping functional roles in the cell during anaerobic growth. We infer from the phylogeny of the anCWMP genes that these two important genes derive from an ancient duplication that predates the WGD event, whereas the TIR1 subfamily experienced gene family amplification after the WGD event. Taken together, the genetic and molecular evidence suggests that one key anCWMP gene duplication event, several auxiliary gene duplication events, and functional divergence underpin the evolution of anaerobic growth in budding yeasts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

The development and use of metal-based probes for X-ray fluorescence microscopy

Abstract X-ray fluorescence microscopy (XFM) has become a widely used technique for imaging the concentration and distribution of metal ions in cells and tissues. Recent advances in synchrotron sources, optics, and detectors have improved the spatial resolution of the technique to <10 nm with attogram detection sensitivity. However, to make XFM most beneficial for bioimaging—especially at the nanoscale—the metal ion distribution must be visualized within the subcellular context of the cell. Over the years, a number of approaches have been taken to develop X-ray-sensitive tags that permit the visualization of specific organelles or proteins using XFM. In this review, we examine the types of X-ray fluorophore used, including nanomaterials and metal ions, and the approaches used to incorporate the metal into their target binding site via antibodies, genetically encoded metal-binding peptides, affinity labeling, or cell-specific peptides. We evaluate their advantages and disadvantages, review the scientific findings, and discuss the needs for future development.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Zn deficiency disrupts Cu and S homeostasis in Chlamydomonas resulting in over accumulation of Cu and Cysteine

Growth of Chlamydomonas reinhardtii in zinc (Zn) limited medium leads to disruption of copper (Cu) homeostasis, resulting in up to 40-fold Cu over-accumulation relative to its typical Cu quota. Here, we show that Chlamydomonas controls its Cu quota by balancing Cu import and export, which is disrupted in a Zn deficient cell, thus establishing a mechanistic connection between Cu and Zn homeostasis. Transcriptomics, proteomics and elemental profiling revealed that Zn-limited Chlamydomonas cells up-regulate a subset of genes encoding “first responder” proteins involved in sulfur (S) assimilation and consequently accumulate more intracellular S, which is incorporated into L-cysteine, γ-glutamylcysteine, and homocysteine. Most prominently, in the absence of Zn, free L-cysteine is increased ~80-fold, corresponding to ~2.8 × 10 9 molecules/cell. Interestingly, classic S-containing metal binding ligands like glutathione and phytochelatins do not increase. X-ray fluorescence microscopy showed foci of S accumulation in Zn-limited cells that co-localize with Cu, phosphorus and calcium, consistent with Cu-thiol complexes in the acidocalcisome, the site of Cu(I) accumulation. Notably, cells that have been previously starved for Cu do not accumulate S or Cys, causally connecting cysteine synthesis with Cu accumulation. We suggest that cysteine is an in vivo Cu(I) ligand, perhaps ancestral, that buffers cytosolic Cu.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Synchrotron X-rays reveal the modes of Fe binding and trace metal storage in the brown algae Laminaria digitata and Ectocarpus siliculosus

Abstract Iron is accumulated symplastically in kelp in a non-ferritin core that seems to be a general feature of brown algae. Microprobe studies show that Fe binding depends on tissue type. The sea is generally an iron-poor environment and brown algae were recognized in recent years for having a unique, ferritin-free iron storage system. Kelp (Laminaria digitata) and the filamentous brown alga Ectocarpus siliculosus were investigated using X-ray microprobe imaging and nanoprobe X-ray fluorescence tomography to explore the localization of iron, arsenic, strontium, and zinc, and micro-X-ray absorption near-edge structure (μXANES) to study Fe binding. Fe distribution in frozen hydrated environmental samples of both algae shows higher accumulation in the cortex with symplastic subcellular localization. This should be seen in the context of recent ultrastructural insight by cryofixation–freeze substitution that found a new type of cisternae that may have a storage function but differs from the apoplastic Fe accumulation found by conventional chemical fixation. Zn distribution co-localizes with Fe in E. siliculosus, whereas it is chiefly located in the L. digitata medulla, which is similar to As and Sr. Both As and Sr are mostly found at the cell wall of both algae. XANES spectra indicate that Fe in L. digitata is stored in a mineral non-ferritin core, due to the lack of ferritin-encoding genes. We show that the L. digitata cortex contains mostly a ferritin-like mineral, while the meristoderm may include an additional component.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Crystal structure of an atypical cobalamin riboswitch reveals RNA structural adaptability as basis for promiscuous ligand binding

Cobalamin riboswitches encompass a structurally diverse group of cis-acting, gene regulatory elements found mostly in bacterial messenger RNA and are classified into subtypes based on secondary and tertiary characteristics. An unusual variant of the cobalamin riboswitch with predicted structural features was identified in Bacillus subtilis over a decade ago, but its structure and mechanisms of cobalamin selectivity and translational control have remained unsolved. We present the crystal structure of the aptamer domain of this atypical cobalamin riboswitch and a model for the complete riboswitch, including its expression platform domain. We demonstrate that this riboswitch binds to multiple cobalamin derivatives and correlate its promiscuous behavior to its structure and unique arrangement of peripheral elements. Comparative structural analyses between conventional cobalamin riboswitches and the B. subtilis cobalamin riboswitch reveal that the likely basis for this promiscuous ligand binding is intrinsic structural adaptability encoded in the RNA structure. It suggests that cobalamin selectivity might ultimately be viewed as existing on a spectrum of affinity for each derivative rather than as belonging to distinct types based on ligand specificities. Our work provides an interesting and notable example of functional coupling of ligand-sensing and adaptive folding by a structured RNA molecule.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

DRAM for distilling microbial metabolism to automate the curation of microbiome function

Abstract Microbial and viral communities transform the chemistry of Earth's ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotation of Metabolism), a framework to translate the deluge of microbiome-based genomic information into a catalog of microbial traits. To demonstrate the applicability of DRAM across metabolically diverse genomes, we evaluated DRAM performance on a defined, in silico soil community and previously published human gut metagenomes. We show that DRAM accurately assigned microbial contributions to geochemical cycles and automated the partitioning of gut microbial carbohydrate metabolism at substrate levels. DRAM-v, the viral mode of DRAM, established rules to identify virally-encoded auxiliary metabolic genes (AMGs), resulting in the metabolic categorization of thousands of putative AMGs from soils and guts. Together DRAM and DRAM-v provide critical metabolic profiling capabilities that decipher mechanisms underpinning microbiome function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Deeplasmid: deep learning accurately separates plasmids from bacterial chromosomes

Plasmids are mobile genetic elements that play a key role in microbial ecology and evolution by mediating horizontal transfer of important genes, such as antimicrobial resistance genes. Many microbial genomes have been sequenced by short read sequencers and have resulted in a mix of contigs that derive from plasmids or chromosomes. New tools that accurately identify plasmids are needed to elucidate new plasmid-borne genes of high biological importance. We have developed Deeplasmid, a deep learning tool for distinguishing plasmids from bacterial chromosomes based on the DNA sequence and its encoded biological data. It requires as input only assembled sequences generated by any sequencing platform and assembly algorithm and its runtime scales linearly with the number of assembled sequences. Deeplasmid achieves an AUC–ROC of over 89%, and it was more accurate than five other plasmid classification methods. Finally, as a proof of concept, we used Deeplasmid to predict new plasmids in the fish pathogen Yersinia ruckeri ATCC 29473 that has no annotated plasmids. Deeplasmid predicted with high reliability that a long assembled contig is part of a plasmid. Using long read sequencing we indeed validated the existence of a 102 kb long plasmid, demonstrating Deeplasmid's ability to detect novel plasmids.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Three-dimensional structure of a flavivirus dumbbell RNA reveals molecular details of an RNA regulator of replication

Abstract Mosquito-borne flaviviruses (MBFVs) including dengue, West Nile, yellow fever, and Zika viruses have an RNA genome encoding one open reading frame flanked by 5′ and 3′ untranslated regions (UTRs). The 3′ UTRs of MBFVs contain regions of high sequence conservation in structured RNA elements known as dumbbells (DBs). DBs regulate translation and replication of the viral RNA genome, functions proposed to depend on the formation of an RNA pseudoknot. To understand how DB structure provides this function, we solved the x-ray crystal structure of the Donggang virus DB to 2.1Å resolution and used structural modeling to reveal the details of its three-dimensional fold. The structure confirmed the predicted pseudoknot and molecular modeling revealed how conserved sequences form a four-way junction that appears to stabilize the pseudoknot. Single-molecule FRET suggests that the DB pseudoknot is a stable element that can regulate the switch between translation and replication during the viral lifecycle by modulating long-range RNA conformational changes.

Akiyama, Benjamin M.↗
DOE OSTI2021

Deciphering enhancer sequence using thermodynamics-based models and convolutional neural networks

Abstract Deciphering the sequence-function relationship encoded in enhancers holds the key to interpreting non-coding variants and understanding mechanisms of transcriptomic variation. Several quantitative models exist for predicting enhancer function and underlying mechanisms; however, there has been no systematic comparison of these models characterizing their relative strengths and shortcomings. Here, we interrogated a rich data set of neuroectodermal enhancers in Drosophila, representing cis- and trans- sources of expression variation, with a suite of biophysical and machine learning models. We performed rigorous comparisons of thermodynamics-based models implementing different mechanisms of activation, repression and cooperativity. Moreover, we developed a convolutional neural network (CNN) model, called CoNSEPT, that learns enhancer ‘grammar’ in an unbiased manner. CoNSEPT is the first general-purpose CNN tool for predicting enhancer function in varying conditions, such as different cell types and experimental conditions, and we show that such complex models can suggest interpretable mechanisms. We found model-based evidence for mechanisms previously established for the studied system, including cooperative activation and short-range repression. The data also favored one hypothesized activation mechanism over another and suggested an intriguing role for a direct, distance-independent repression mechanism. Our modeling shows that while fundamentally different models can yield similar fits to data, they vary in their utility for mechanistic inference. CoNSEPT is freely available at: https://github.com/PayamDiba/CoNSEPT.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters

Abstract With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Identification and characterization of the WYL BrxR protein and its gene as separable regulatory elements of a BREX phage restriction system

Bacteriophage exclusion (‘BREX’) phage restriction systems are found in a wide range of bacteria. Various BREX systems encode unique combinations of proteins that usually include a site-specific methyltransferase; none appear to contain a nuclease. Here we describe the identification and characterization of a Type I BREX system from Acinetobacter and the effect of deleting each BREX ORF on growth, methylation, and restriction. We identified a previously uncharacterized gene in the BREX operon that is dispensable for methylation but involved in restriction. Biochemical and crystallographic analyses of this factor, which we term BrxR (‘BREX Regulator’), demonstrate that it forms a homodimer and specifically binds a DNA target site upstream of its transcription start site. Deletion of the BrxR gene causes cell toxicity, reduces restriction, and significantly increases the expression of BrxC. In contrast, the introduction of a premature stop codon into the BrxR gene, or a point mutation blocking its DNA binding ability, has little effect on restriction, implying that the BrxR coding sequence and BrxR protein play independent functional roles. We speculate that elements within the BrxR coding sequence are involved in cis regulation of anti-phage activity, while the BrxR protein itself plays an additional regulatory role, perhaps during horizontal transfer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

CRISPR-RNAa: targeted activation of translation using dCas13 fusions to translation initiation factors

Abstract Tools for synthetically controlling gene expression are a cornerstone of genetic engineering. CRISPRi and CRISPRa technologies have been applied extensively for programmable modulation of gene transcription, but there are few such tools for targeted modulation of protein translation rates. Here, we employ CRISPR-Cas13 as a programmable activator of translation. We develop a novel variant of the catalytically-deactivated Cas13d enzyme dCasRx by fusing it to translation initiation factor IF3. We demonstrate dCasRx-IF3’s ability to enhance expression 21.3-fold above dCasRx when both are targeted to the start of the 5′ untranslated region of mRNA encoding red fluorescent protein in Escherichia coli. Activation of translation is location-dependent, and we show dCasRx-IF3 represses translation when targeted to the ribosomal binding site, rather than enhancing it. We provide evidence that dCasRx-IF3 targeting enhances mRNA stability relative to dCasRx, providing mechanistic insights into how this new tool functions to enhance gene expression. We also demonstrate targeted upregulation of native LacZ 2.6-fold, showing dCasRx-IF3’s ability to enhance expression of endogenous genes. dCasRx-IF3 requires no additional host modification to influence gene expression. This work outlines a novel approach, CRISPR-RNAa, for post-transcriptional control of translation to activate gene expression.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Functional characterization of diverse type I-F CRISPR-associated transposons

CRISPR-Cas systems generally provide adaptive immunity in prokaryotes through RNA-guided degradation of foreign genetic elements like bacteriophages and plasmids. Recently, however, transposon-encoded and nuclease-deficient CRISPR-Cas systems were characterized and shown to be co-opted by Tn7-like transposons for CRISPR RNA-guided DNA transposition. As a genome engineering tool, these CRISPR-Cas systems and their associated transposon proteins can be deployed for programmable, site-specific integration of sizable cargo DNA, circumventing the need for DNA cleavage and homology-directed repair involving endogenous repair machinery. Here, we selected a diverse set of type I-F3 CRISPR-associated transposon systems derived from Gammaproteobacteria, predicted all components essential for transposition activity, and deployed them for functionality testing within Escherichia coli. Our results demonstrate that these systems possess a significant range of integration efficiencies with regards to temperature, transposon size, and flexible PAM requirements. Additionally, our findings support the categorization of these systems into functional compatibility groups for efficient and orthogonal RNA-guided DNA integration. This work expands the CRISPR-based toolbox with new CRISPR RNA-guided DNA integrases that can be applied to complex and extensive genome engineering efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Structure, substrate binding and activity of a unique AAA+ protein: the BrxL phage restriction factor

Abstract Bacteriophage exclusion (‘BREX’) systems are multi-protein complexes encoded by a variety of bacteria and archaea that restrict phage by an unknown mechanism. One BREX factor, termed BrxL, has been noted to display sequence similarity to various AAA+ protein factors including Lon protease. In this study we describe multiple CryoEM structures of BrxL that demonstrate it to be a chambered, ATP-dependent DNA binding protein. The largest BrxL assemblage corresponds to a dimer of heptamers in the absence of bound DNA, versus a dimer of hexamers when DNA is bound in its central pore. The protein displays DNA-dependent ATPase activity, and ATP binding promotes assembly of the complex on DNA. Point mutations within several regions of the protein-DNA complex alter one or more in vitro behaviors and activities, including ATPase activity and ATP-dependent association with DNA. However, only the disruption of the ATPase active site fully eliminates phage restriction, indicating that other mutations can still complement BrxL function within the context of an otherwise intact BREX system. BrxL displays significant structural homology to MCM subunits (the replicative helicase in archaea and eukaryotes), implying that it and other BREX factors may collaborate to disrupt initiation of phage DNA replication.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Eukaryotic RNA-guided endonucleases evolved from a unique clade of bacterial enzymes

Abstract RNA-guided endonucleases form the crux of diverse biological processes and technologies, including adaptive immunity, transposition, and genome editing. Some of these enzymes are components of insertion sequences (IS) in the IS200/IS605 and IS607 transposon families. Both IS families encode a TnpA transposase and a TnpB nuclease, an RNA-guided enzyme ancestral to CRISPR-Cas12s. In eukaryotes, TnpB homologs occur as two distinct types, Fanzor1s and Fanzor2s. We analyzed the evolutionary relationships between prokaryotic TnpBs and eukaryotic Fanzors, which revealed that both Fanzor1s and Fanzor2s stem from a single lineage of IS607 TnpBs with unusual active site arrangement. The widespread nature of Fanzors implies that the properties of this particular lineage of IS607 TnpBs were particularly suited to adaptation in eukaryotes. Biochemical analysis of an IS607 TnpB and Fanzor1s revealed common strategies employed by TnpBs and Fanzors to co-evolve with their cognate transposases. Collectively, our results provide a new model of sequential evolution from IS607 TnpBs to Fanzor2s, and Fanzor2s to Fanzor1s that details how genes of prokaryotic origin evolve to give rise to new protein families in eukaryotes.

59 BASIC BIOLOGICAL SCIENCES↗