X-ray crystal structure of the passenger domain of plasmid encoded toxin(Pet), an autotransporter enterotoxin from enteroaggregative Escherichia coli (EAEC)
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Background: Cost effective next generation sequencing technologies now enable the production of genomic datasets for many novel planktonic eukaryotes, representing an understudied reservoir of genetic diversity. O. tauri is the smallest free-living photosynthetic eukaryote known to date, a coccoid green alga that was first isolated in 1995 in a lagoon by the Mediterranean sea. Its simple features, ease of culture and the sequencing of its 13 Mb haploid nuclear genome have promoted this microalga as a new model organism for cell biology. Here, we investigated the quality of genome assemblies of Illumina GAIIx 75 bp paired-end reads from Ostreococcus tauri, thereby also improving the existing assembly and showing the genome to be stably maintained in culture. Results: The 3 assemblers used, ABySS, CLCBio and Velvet, produced 95% complete genomes in 1402 to 2080 scaffolds with a very low rate of misassembly. Reciprocally, these assemblies improved the original genome assembly by filling in 930 gaps. Combined with additional analysis of raw reads and PCR sequencing effort, 1194 gaps have been solved in total adding up to 460 kb of sequence. Mapping of RNAseq Illumina data on this updated genome led to a twofold reduction in the proportion of multi-exon protein coding genes, representing 19% of the total 7699 protein coding genes. The comparison of the DNA extracted in 2001 and 2009 revealed the fixation of 8 single nucleotide substitutions and 2 deletions during the approximately 6000 generations in the lab. The deletions either knocked out or truncated two predicted transmembrane proteins, including a glutamate-receptor like gene. Conclusion: High coverage (>80 fold) paired-end Illumina sequencing enables a high quality 95% complete genome assembly of a compact ~13 Mb haploid eukaryote. This genome sequence has remained stable for 6000 generations of lab culture.
Based on color–magnitude diagrams (CMDs) from the Hubble Space Telescope Hubble Tarantula Treasury Project (HTTP) survey, we present the star formation history of Hodge 301, the oldest star cluster in the Tarantula Nebula. The HTTP photometry extends faint enough to reach, for the first time, the cluster pre-main sequence (PMS) turn-on, where the PMS joins the main sequence. Using the location of this feature, along with synthetic CMDs generated with the latest PARSEC models, we find that Hodge 301 is older than previously thought, with an age between 26.5 and 31.5 Myr. From this age, we also estimate that between 38 and 61 Type II supernovae exploded in the region. The same age is derived from the main sequence turn-off, whereas the age derived from the post-main sequence stars is younger and between 20 and 25 Myr. Other relevant parameters are a total stellar mass of ≈8800 ± 800 M {sub ⊙} and average reddening E ( B − V ) ≈ 0.22–0.24 mag, with a differential reddening δE ( B − V ) ≈ 0.04 mag.
Metal halide perovskite (MHP) solar cells exhibit a metastable response to bias governed by coupled ionic–electronic processes, complicating the conventional reciprocity relation between luminescence intensity and device open-circuit voltage (V oc ). This limits the use of luminescence as a diagnostic for device screening or accelerated stress testing, motivating new approaches that can interpret photoluminescence (PL) signals under nonequilibrium conditions. From the artificial intelligence perspective, we develop an explainable deep learning framework that integrates convolutional neural networks (CNN), long short-term memory (LSTM) layers, and an attention mechanism to learn spatiotemporal features from operando photoluminescence PL image sequences. The model achieves a mean absolute error of ±0.027 V in predicting open-circuit voltage transients and reduces extreme-tail errors by up to 78% compared to physics-based reciprocity calculations. Gradient-weighted Class Activation Mapping (Grad-CAM) provides interpretability by highlighting physically meaningful regions such as electrode edges and emergent defect features. From the engineering application perspective, this framework enables accurate, contactless prediction of device V oc and identification of degradation-relevant features during accelerated aging of perovskite solar cells. This approach demonstrates how explainable AI can enhance operando diagnostics and reliability analysis in photovoltaic devices under nonequilibrium conditions.
Microbial communities play important roles in the function and maintenance of various biosystems, ranging from the human body to the environment. A major challenge in microbiome research is the classification of microbial communities of different environments or host phenotypes. The most common and cost-effective approach for such studies to date is 16S rRNA gene sequencing. Recent falls in sequencing costs have increased the demand for simple, efficient and accurate methods for rapid detection or diagnosis with proved applications in medicine, agriculture and forensic science. We describe a reference- and alignment-free approach for predicting environments and host phenotypes from 16S rRNA gene sequencing based on k-mer representations that benefits from a bootstrapping framework for investigating the sufficiency of shallow sub-samples. Deep learning methods as well as classical approaches were explored for predicting environments and host phenotypes. A k-mer distribution of shallow sub-samples outperformed Operational Taxonomic Unit (OTU) features in the tasks of body-site identification and Crohn’s disease prediction. Aside from being more accurate, using k-mer features in shallow sub-samples allows (i) skipping computationally costly sequence alignments required in OTU-picking and (ii) provided a proof of concept for the sufficiency of shallow and short-length 16S rRNA sequencing for phenotype prediction. In addition, k-mer features predicted representative 16S rRNA gene sequences of 18 ecological environments, and 5 organismal environments with high macro-F1 scores of 0.88 and 0.87. For large datasets, deep learning outperformed classical methods such as Random Forest and Support Vector Machine.
GLARE (Genomic Language model for Annotation of Repetitive Elements) is a tool that classifies transposable elements (TEs)—the mobile, repetitive DNA sequences that make up large fractions of eukaryotic genomes. GLARE fine-tunes the NTv3-650M genomic language model on a harmonized collection of curated TE sequences from the PanTEon and Repbase reference databases, assigning each input sequence to one of 11 orders and 32 superfamilies in a Wicker-compatible taxonomy. Features. From nucleotide FASTA input, GLARE outputs per-sequence predictions, class summaries, composition figures, and an annotated FASTA. It provides calibrated confidence scores with optional abstention and runs on CPU or GPU. Uses. GLARE serves as a classification component in genome-annotation pipelines, downstream of TE discovery, supporting genome annotation and comparative and evolutionary genomics. Advantages. GLARE is the first repeat-element classifier to leverage a pretrained genomic language model. Combined with multi-database training, this approach outperformed all nine classifiers in the PanTEon benchmark, generalized better to unseen taxonomic clades, and remained robust to sequence orientation—a common failure mode of existing tools.
The ages and sizes of a sex-determination region (SDR) are difficult to determine in non-model species. Due to the lack of recombination and enrichment of repetitive elements in SDRs, the quality of assembly with short sequencing reads is universally low. Unique features present in the SDRs help provide clues about how SDRs are established and how they evolve in the absence of recombination. Several Populus species have been reported with a male heterogametic configuration of sex (XX/XY system) mapped on chromosome 19, but the exact location of the SDR has been inconsistent among species, and thus far, none of these SDRs has been fully assembled in a genomic context. Here we identify the Y-SDR from a Y-linked contig directly from a long-read PacBio assembly of a Populus trichocarpa male individual. We also identified homologous gene sequences in the SDR of P. trichocarpa and the SDR of the W chromosome in Salix purpurea. We show that inverted repeats (IRs) found in the Y-SDR and the W-SDR are lineage-specific. We hypothesize that, although the two IRs are derived from the same orthologous gene within each species, they likely have independent evolutionary histories. Furthermore, the truncated inverted repeats in P. trichocarpa may code for small RNAs that target the homologous gene for RNA-directed DNA methylation. These findings support the hypothesis that diverse sex-determining systems may be achieved through similar evolutionary pathways, thereby providing a possible mechanism to explain the lability of sex-determination systems in plants in general.
This dataset comprises dynamic graph sequences derived from simulated in-situ neutron reflectometry measurements, capturing the gradual evolution of a layer structure over time. Each graph sequence represents a synthetic sample, with node features detailing the scattering vector and corresponding reflectivity measurements, while adjacency matrices have corresponding reference material parameters attached as metadata. The dataset spans multiple sets, each with a different number of sequences, offering a comprehensive basis for training models that handle dynamic input sequences with embedded physics. This dataset is particularly suited for tackling inverse problems with hidden physical states that evolve over time, challenges that are typically difficult to address using conventional iterative fitting methods.
Ensifer (syn. Sinorhizobium) meliloti is an important symbiotic bacterial species that fixes nitrogen. Strains BO21CC and AK58 were previously investigated for their substrate utilization and their plant-growth promoting abilities showing interesting features. Here, we describe the complete genome sequence and annotation of these strains. BO21CC and AK58 genomes are 6,985,065 and 6,974,333 bp long with 6,746 and 6,992 genes predicted, respectively.
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.
Accurate three dimensional reconstructions of atomic positions and full quantification of the information contained in atom probe microscopy data rely on understanding the physical processes taking place during field evaporation of atoms from needle-shaped specimens. However, the modeling framework for atom probe microscopy has only limited quantitative justification. Building on the continuum field models previously developed, we introduce a more physical approach with the selection of evaporation events based on density functional theory calculations. This model reproduces key features observed experimentally in terms of sequence of evaporation, evaporation maps, and depth resolution, and provides insights into the physical limit for spatial resolution.
Abstract Background Breast cancer (BC) is the most commonly diagnosed cancer and the leading cause of cancer death among women globally. Despite advances, there is considerable variation in clinical outcomes for patients with non-luminal A tumors, classified as difficult-to-treat breast cancers (DTBC). This study aims to delineate the proteogenomic landscape of DTBC tumors compared to luminal A (LumA) tumors. Methods We retrospectively collected a total of 117 untreated primary breast tumor specimens, focusing on DTBC subtypes. Breast tumors were processed by laser microdissection (LMD) to enrich tumor cells. DNA, RNA, and protein were simultaneously extracted from each tumor preparation, followed by whole genome sequencing, paired-end RNA sequencing, global proteomics and phosphoproteomics. Differential feature analysis, pathway analysis and survival analysis were performed to better understand DTBC and investigate biomarkers. Results We observed distinct variations in gene mutations, structural variations, and chromosomal alterations between DTBC and LumA breast tumors. DTBC tumors predominantly had more mutations inTP53,PLXNB3, Zinc finger genes, and fewer mutations inSDC2,CDH1,PIK3CA,SVIL, andPTEN. Notably, Cytoband 1q21, which contains numerous cell proliferation-related genes, was significantly amplified in the DTBC tumors. LMD successfully minimized stromal components and increased RNA–protein concordance, as evidenced by stromal score comparisons and proteomic analysis. Distinct DTBC and LumA-enriched clusters were observed by proteomic and phosphoproteomic clustering analysis, some with survival differences. Phosphoproteomics identified two distinct phosphoproteomic profiles for high relapse-risk and low relapse-risk basal-like tumors, involving several genes known to be associated with breast cancer oncogenesis and progression, includingKIAA1522,DCK,FOXO3,MYO9B,ARID1A,EPRS,ZC3HAV1, andRBM14. Lastly, an integrated pathway analysis of multi-omics data highlighted a robust enrichment of proliferation pathways in DTBC tumors. Conclusions This study provides an integrated proteogenomic characterization of DTBC vs LumA with tumor cells enriched through laser microdissection. We identified many common features of DTBC tumors and the phosphopeptides that could serve as potential biomarkers for high/low relapse-risk basal-like BC and possibly guide treatment selections.
Leucobacter chironomi strain MM2LBT (Halpern et al., Int J Syst Evol Microbiol 59:665-70 2009) is a Gram-positive, rod shaped, non-motile, aerobic, chemoorganotroph bacterium. L. chironomi belongs to the family Microbacteriaceae, a family within the class Actinobacteria. Strain MM2LBT was isolated from a chironomid (Diptera; Chironomidae) egg mass that was sampled from a waste stabilization pond in northern Israel. In a phylogenetic tree based on 16S rRNA gene sequences, strain MM2LBT formed a distinct branch within the radiation encompassing the genus Leucobacter. Here we describe the features of this organism, together with the complete genome sequence and annotation. We find that the DNA GC content is 69.90%. The chromosome length is 2,964,712 bp. It encodes 2,690 proteins and 61 RNA genes. L. chironomi genome is part of the Genomic Encyclopedia of Type Strains, Phase I: the one thousand microbial genomes (KMG) project.
The primary objective of this project was to leverage the Big Area Additive Manufacturing (BAAM) process and materials into a long term, quick change tooling concept to drastically reduce product lead and development timelines and costs. Current refrigeration foam molds are complicated to manufacture involving casting several aluminum parts in an approximate shape, machining components of the molds and post fitting and shimming of the parts in an articulated fixture. The total process timeline can take over 6 months. The foaming process is slower than required for production, therefore multiple fixtures, 10 to 27, are required per refrigerator model. Molds are particular to a specific product configuration making mixed model assembly challenging for sequencing, mold changes or auto changeover features. The initial goal was to create a tool leveraging the ORNL materials and additive process to build a tool in 4 to 6 weeks or less. A secondary goal was to create common fixture cores and provide lightweight fixture sections that could be revised in a very short time to increase equipment flexibility reduce lead times, lower the barriers to first production trials, and reduce tooling costs.
High-throughput genetic screening is frequently employed to rapidly associate gene with phenotype and establish sequence-function relationships. With the advent of CRISPR technology, and the ability to functionally interrogate previously genetically recalcitrant organisms, non-model organisms can be investigated using pooled guide RNA (gRNA) libraries and sequencing-based assays to quantitatively assess fitness of every targeted locus in parallel. To aid the construction of pooled gRNA assemblies, we have developed an in silico design workflow for gRNA selection using the gRNA Sequence Region Extraction Tool (gRNA-SeqRET). Built upon the previously developed CCTop, gRNA-SeqRET enables automated, scalable design of gRNA libraries that target user-specified regions or whole genomes of any prokaryote or eukaryote. Additionally, gRNA-SeqRET automates the bulk extraction of any regions of sequence relative to genes or other features, aiding in the design of homology arms for insertion or deletion constructs. We also assess in silico the application of a designed gRNA library to other closely related genomes and demonstrate that for very closely related organisms Average Nucleotide Identity (ANI) > 95% a large fraction of the library may be of relevance. The gRNA-SeqRET web application pipeline can be accessed at https://grna.jgi.doe.gov. The source code is comprised of freely available software tools and customized Python scripts, and is available at https://bitbucket.org/berkeleylab/grnadesigner/src/master/ under a modified BSD open-source license (https://bitbucket.org/berkeleylab/grnadesigner).
Codon deoptimization (CD) has been recently used as a possible strategy to derive foot-and-mouth disease (FMD) live-attenuated vaccine (LAV) candidates containing DIVA markers. However, reversion to virulence, or loss of DIVA, from possible recombination with wild-type (WT) strains has yet to be analyzed. An in vitro assay was developed to quantitate the levels of recombination between WT and a prospective A24-P2P3 partially deoptimized LAV candidate. By using two genetically engineered non-infectious RNA templates, we demonstrate that recombination can occur within non-deoptimized viral genomic regions (i.e., 3'end of P3 region). The sequencing of single plaque recombinants revealed a variety of genome compositions, including full-length WT sequences at the consensus level and deoptimized sequences at the sub-consensus/consensus level within the 3'end of the P3 region. Notably, after further passage, two recombinants that contained deoptimized sequences evolved to WT. Overall, recombinants featuring large stretches of CD or DIVA markers were less fit than WT viruses. Our results indicate that the developed assay is a powerful tool to evaluate the recombination of FMDV genomes in vitro and should contribute to the improved design of FMDV codon deoptimized LAV candidates.
Measuring the mechanical coupling and rigidity of a large apparatus presents unique challenges for 3D metrology. In this case the motion of well separated points attached to a rotor blade must be rapidly and repeatedly measured and the resulting data synchronized. This presentation describes the methodology and results for the mechanical coupling test of the magnetic field mapping system (FMS) for the Mu2e experiment at Fermi National Accelerator Laboratory (Fermilab). Three laser trackers, 2 API Radians and an API TIII, simultaneously measured the position of three cylindrical corner cube reflectors mounted on the FMS while the system was in motion and after coming to rest. The laser trackers took measurements at 83Hz for the T3 and 100Hz for the Radians, with fine spatial resolution, resulting in over 20,000 points measured per instrument in observation cycle. The laser tracker hardware and utilized software are unable to synchronize the three independent data streams directly during the measurement process. Instead a custom software program was developed to perform this synchronization of the data sequences during post-processing using features of the targets motion common to all three fiducial locations.
The Tank Side Cesium Removal (TSCR) System is a modular, quickly-deployable and passively safe system for efficiently removing solids and cesium from alkaline liquid waste raffinate created by spent fuel reprocessing on the Hanford site. It further describes TSCR component design features, system performance metrics and operational sequences used for liquid waste treatment, as well as spent ion exchange column (IXC) replacement and storage. This presentation should be of great interest to parties responsible for treatment and disposal of liquid waste containing high concentrations of cesium. (authors)