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At least 1,387 records · Page 77

Human Liver Epithelial Cells (HuH7) Response to HCoV-229E Infection Epigenomics (ATAC-Seq) (ACS-DP4)

The purpose of this experiment was to evaluate how wild-type Human coronavirus strain 229E (HCoV-299E) infection alters chromatin accessibility in infected cells. Sample data was obtained from mock-infected cells, UV-inactivated virus treated cells, and replication competent HCoV-229E infected immortalized human liver cells (HuH7) at 24 hours post infection. Samples were processed using ATAC-seq methods for reported bar coded libraries. Sample data was acquired using an Illumina Hi-Seq 2500 sequencer system and further processed for ATAC-Seq expression analysis.

59 BASIC BIOLOGICAL SCIENCES↗

SFA-VirOmics

PNNL's Soil Microbiome Science Focus Area (SFA) is focused on understanding the basic biology underpinning how interactions among various soil microbial community members, across trophic levels, lead to the emergence of community functions. Moisture, in particular, drives microbial interactions and influences everything from cell function to substrate fate within soils. The group predicts this results in repeatable, predictable phenotypes. The sum of these phenotypes comprises the “soil metaphenome”. Understanding how the soil metaphenome shifts in response to moisture will provide a basis for modeling and predicting these shifts in reaction network responses. Visit the PNNL Soil Microbiome Science Focus Area Program homepage for more information. PNNL’s Soil Microbiome SFA Virome Dataset Annotation page is an extension to the PNNL Soil Microbiome SFA repository on DataHub allows for exploring and downloading integrated experimental omics dataset annotations, associated experimental metadata, pre- and post-processed viral data files, and other associated materials directly related to experimental viral project data.

59 BASIC BIOLOGICAL SCIENCES↗

Beyond microbial abundance: metadata integration enhances disease prediction in human microbiome studies

Multiple studies have highlighted the interaction of the human microbiome with physiological systems such as the gut, immune, liver, and skin, via key axes. Advances in sequencing technologies and high-performance computing have enabled the analysis of large-scale metagenomic data, facilitating the use of machine learning to predict disease likelihood from microbiome profiles. However, challenges such as compositionality, high dimensionality, sparsity, and limited sample sizes have hindered the development of actionable models. One strategy to improve these models is by incorporating key metadata from both the human host and sample collection/processing protocols. This remains challenging due to sparsity and inconsistency in metadata annotation and availability. In this paper, we introduce a machine learning-based pipeline for predicting human disease states by integrating host and protocol metadata with microbiome abundance profiles from 68 different studies, processed through a consistent pipeline. Our findings indicate that metadata can enhance machine learning predictions, particularly at higher taxonomic ranks like Kingdom and Phylum, though this effect diminishes at lower ranks. Our study leverages a large collection of microbiome datasets comprising 11,208 samples, therefore enhancing the robustness and statistical confidence of our findings. This work is a critical step toward utilizing microbiome and metadata for predicting diseases such as gastrointestinal infections, diabetes, cancer, and neurological disorders.

Mathematics and Computing↗

A Structural Perspective on the RNA Editing of Plant Respiratory Complexes

The last steps of respiration, a core energy-harvesting process, are carried out by a chain of multi-subunit complexes in the inner mitochondrial membrane. Several essential subunits of the respiratory complexes are RNA-edited in plants, frequently leading to changes in the encoded amino acids. While the impact of RNA editing is clear at the sequence and phenotypic levels, the underlying biochemical explanations for these effects have remained obscure. Here, we used the structures of plant respiratory complex I, complex III2 and complex IV to analyze the impact of the amino acid changes of RNA editing in terms of their location and biochemical features. Through specific examples, we demonstrate how the structural information can explain the phenotypes of RNA-editing mutants. This work shows how the structural perspective can bridge the gap between sequence and phenotype and provides a framework for the continued analysis of RNA-editing mutants in plant mitochondria and, by extension, in chloroplasts.

59 BASIC BIOLOGICAL SCIENCES↗

Are High-redshift Galaxies Hot? Temperature of z > 5 Galaxies and Implications for Their Dust Properties

Recent studies have found a significant evolution and scatter in the relationship between the UV spectral slope ( β {sub UV}) and the infrared excess (IRX; L {sub IR}/ L {sub UV}) at z > 4, suggesting different dust properties of these galaxies. The total far-infrared (FIR) luminosity is key for this analysis, but it is poorly constrained in normal (main-sequence) star-forming z > 5 galaxies, where often only one single FIR point is available. To better inform estimates of the FIR luminosity, we construct a sample of local galaxies and three low-redshift analogues of z > 5 systems. The trends in this sample suggest that normal high-redshift galaxies have a warmer infrared (IR) spectral energy distribution (SED) compared to average z < 4 galaxies that are used as priors in these studies. The blueshifted peak and mid-IR excess emission could be explained by a combination of a larger fraction of metal-poor interstellar medium being optically thin to ultraviolet (UV) light and a stronger UV radiation field due to high star formation densities. Assuming a maximally warm IR SED suggests a 0.6 dex increase in total FIR luminosities, which removes some tension between the dust attenuation models and observations of the IRX− β relation at z > 5. Despite this, some galaxies still fall below the minimum IRX− β relation derived with standard dust cloud models. We propose that radiation pressure in these highly star-forming galaxies causes a spatial offset between dust clouds and young star-forming regions within the lifetime of O/B stars. These offsets change the radiation balance and create viewing-angle effects that can change UV colors at fixed IRX. We provide a modified model that can explain the location of these galaxies on the IRX− β diagram.

79 ASTRONOMY AND ASTROPHYSICS↗

Hybrid deep learning architecture for general disruption prediction across tokamaks

In this paper, we present a new deep learning disruption prediction algorithm based on important findings from explorative data analysis which effectively allows knowledge transfer from existing devices to new ones, thereby predicting disruptions using very limited disruptive data from the new devices. The explorative data analysis conducted via unsupervised clustering techniques confirms that time-sequence data are much better separators of disruptive and non-disruptive behavior than the instantaneous plasma state data with further advantageous implications for a sequence-based predictor. Based on such important findings, we have designed a new algorithm for multi-machine disruption prediction that achieves high predictive accuracy on the C-Mod (AUC=0.801), DIII-D (AUC=0.947) and EAST (AUC=0.973). tokamaks with limited hyperparameter tuning. Through numerical experiments, we show that boosted accuracy (AUC=0.959) is achieved on EAST predictions by including in the training only 20 disruptive discharges, thousands of non-disruptive discharges from EAST, and combining this with more than a thousand discharges from DIII-D and C-Mod. The improvement of predictive ability obtained by combining disruptive data from other devices is found to be true for all permutations of the three devices. Furthermore, by comparing the predictive performance of each individual numerical experiment, we find that non-disruptive data are machine-specific while disruptive data from multiple devices contain device-independent knowledge that can be used to inform predictions for disruptions occurring on a new device.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Altering translation allows E. coli to overcome chemically stabilized G-quadruplexes

To investigate the effects of stabilizing G-quadruplexes on Escherichia coli, cells were grown in the presence of the G-quadruplex stabilizing compound, NMM, and RNA-seq was performed. This was done for the control cell strain (MG1655 dtolC) as well as a strain with a decrease in a translation elongation factor (MG1655 dtolC tufA::kan). TPM values were used for differential gene expression analysis between each growth condition. All samples were grown and sequenced in triplicate.

Keck, James L.↗

Flow cytometric detection method for DNA samples

Disclosed herein are two methods for rapid multiplex analysis to determine the presence and identity of target DNA sequences within a DNA sample. Both methods use reporting DNA sequences, e.g., modified conventional Taqman.RTM. probes, to combine multiplex PCR amplification with microsphere-based hybridization using flow cytometry means of detection. Real-time PCR detection can also be incorporated. The first method uses a cyanine dye, such as, Cy3.TM., as the reporter linked to the 5' end of a reporting DNA sequence. The second method positions a reporter dye, e.g., FAM.TM. on the 3' end of the reporting DNA sequence and a quencher dye, e.g., TAMRA.TM., on the 5' end.

59 BASIC BIOLOGICAL SCIENCES↗

Hardware Architectures for Data-Intensive Computing Problems: A Case Study for String Matching

DNA analysis is an emerging application of high performance bioinformatic. Modern sequencing machinery are able to provide, in few hours, large input streams of data, which needs to be matched against exponentially growing databases of known fragments. The ability to recognize these patterns effectively and fastly may allow extending the scale and the reach of the investigations performed by biology scientists. Aho-Corasick is an exact, multiple pattern matching algorithm often at the base of this application. High performance systems are a promising platform to accelerate this algorithm, which is computationally intensive but also inherently parallel. Nowadays, high performance systems also include heterogeneous processing elements, such as Graphic Processing Units (GPUs), to further accelerate parallel algorithms. Unfortunately, the Aho-Corasick algorithm exhibits large performance variability, depending on the size of the input streams, on the number of patterns to search and on the number of matches, and poses significant challenges on current high performance software and hardware implementations. An adequate mapping of the algorithm on the target architecture, coping with the limit of the underlining hardware, is required to reach the desired high throughputs. In this paper, we discuss the implementation of the Aho-Corasick algorithm for GPU-accelerated high performance systems. We present an optimized implementation of Aho-Corasick for GPUs and discuss its tradeoffs on the Tesla T10 and he new Tesla T20 (codename Fermi) GPUs. We then integrate the optimized GPU code, respectively, in a MPI-based and in a pthreads-based load balancer to enable execution of the algorithm on clusters and large sharedmemory multiprocessors (SMPs) accelerated with multiple GPUs.

Tumeo, Antonino↗

Population structure of Miscanthus sacchariflorus reveals two major polyploidization events, tetraploid-mediated unidirectional introgression from diploid M. sinensis, and diversity centred around the Yellow Sea

Abstract Background and Aims Miscanthus, a C4 perennial grass native to East Asia, is a promising biomass crop. Miscanthus sacchariflorus has a broad geographic range, is used to produce paper in China and is one of the parents (along with Miscanthus sinensis) of the important biomass species Miscanthus × giganteus. The largest study of M. sacchariflorus population genetics to date is reported here. Methods Collections included 764 individuals across East Asia. Samples were genotyped with 34 605 single nucleotide polymorphisms (SNPs) derived from restriction site-associated DNA sequencing (RAD-seq) and ten plastid microsatellites, and were subjected to ploidy analysis by flow cytometry. Key Results Six major genetic groups within M. sacchariflorus were identified using SNP data: three diploid groups, comprising Yangtze (M. sacchariflorus ssp. lutarioriparius), N China and Korea/NE China/Russia; and three tetraploid groups, comprising N China/Korea/Russia, S Japan and N Japan. Miscanthus sacchariflorus ssp. lutarioriparius was derived from the N China group, with a substantial bottleneck. Japanese and mainland tetraploids originated from independent polyploidization events. Hybrids between diploid M. sacchariflorus and M. sinensis were identified in Korea, but without introgression into either parent species. In contrast, tetraploid M. sacchariflorus in southern Japan and Korea exhibited substantial hybridization and introgression with local diploid M. sinensis. Conclusions Genetic data indicated that the land now under the Yellow Sea was a centre of diversity for M. sacchariflorus during the last glacial maximum, followed by a series of migrations as the climate became warmer and wetter. Overall, M. sacchariflorus has greater genetic diversity than M. sinensis, suggesting that breeding and selection within M. sacchariflorus will be important for the development of improved M. × giganteus. Ornamental M. sacchariflorus genotypes in Europe and North America represent a very narrow portion of the species’ genetic diversity, and thus do not well represent the species as a whole.

Clark, Lindsay V.↗

Lake Arrowhead Microbial Genomics Conference

The Lake Arrowhead Microbial Genomics Conference (formerly the E. coli and Small Genomes Conference, and the Microbial Genomes Conference) was held September 11-15, 2022, at the UCLA Conference Center at Lake Arrowhead, California. This conference is part of a yearly meeting initiated in 1991 to bring together genome sequencers, bioinformatics specialists, biologists, and geneticists, to forge interactions that would result in meaningful functional genomics. The goal of the meeting was to translate the influx of new genome sequencing information into useful biological studies. The Lake Arrowhead 2022 meeting had a major focus on microbial communities, the human microbiome, pathogens, phage therapy, bioinformatic methods of analysis, bioenergenics, and environmental microbiology. The field of genomics has reached the point where deriving the sequence of an organism’s entire genome is now seen as a beginning rather than an endpoint. Moreover, understanding the sequences of whole communities, and particularly those that make up different microbiomes, is now a central point of the field. The 2022 meeting covered microorganisms for which extensive analyses exist, and those for which new biological and technical strategies are being developed. The focus on biodiversity, the human microbiome, pathogenic organisms and methods of countering them, and bioenergetics added special significance to this meeting. This meeting was designed to have a mix of 36 invited presentations and poster sessions with more than 80 posters, and had 147 participants. This meeting has become established as a major annual microbial genomics conference during the last 29 years and has assured status and quality. It offers a major opportunity for young investigators and students to attend, present posters, and give talks. In fact, 50% of the invited speakers were early career stage scientists. An important impact of the conference was the forging of new collaborations between scientists and particularly young scientists with the array of multidisciplinary researchers at the meeting.

Miller, Jeffrey H.↗

Investigation of the notch sensitivity of tailorable long fiber discontinuous prepreg composite laminates

Tailorable discontinuous fiber composite laminates provide relative formability beyond that of continuous fiber laminates, while achieving improved mechanical performance over comparable stochastic systems. Here, in this work, the notch sensitivity of engineered prepreg platelet molded composite (PPMC) laminates is investigated using the open-hole tension (OHT) test and compared to available data for stochastic PPMCs and continuous fiber laminates made with the same material. The press-formed thermoplastic composites (AS4/PEKK) were molded with a quasi-isotropic stacking sequence. The discontinuous PPMC laminate was found to be notch insensitive with OHT strengths ranging from 145.4 MPa (CV $=$ 7%) for d/w $=$ 0.5 to 229.3 MPa (CV $=$ 9%) for d/w $=$ 0.25. The highly ordered meso-structure of the engineered PPMC laminate yields comparatively excellent mechanical properties for relatively thin laminates in contrast to stochastic systems. Both net- and gross-section failures were observed for d/w $=$ 0.25, which suggests that the engineered PPMC laminates studied here maintain a degree of inherent, internal stress concentrations that compete with those caused by geometric features such as a circular hole. Computational simulations of the OHT tests with explicitly represented platelets were found to be in good agreement with experimental measurements. The progressive failure analysis was used to conduct a numerical investigation of the stacking sequence and platelet meso-morphology.

36 MATERIALS SCIENCE↗

A REVISED AGE FOR UPPER SCORPIUS AND THE STAR FORMATION HISTORY AMONG THE F-TYPE MEMBERS OF THE SCORPIUS-CENTAURUS OB ASSOCIATION

We present an analysis of the ages and star formation history of the F-type stars in the Upper Scorpius (US), Upper Centaurus-Lupus (UCL), and Lower Centaurus-Crux (LCC) subgroups of Scorpius-Centaurus (Sco-Cen), the nearest OB association. Our parent sample is the kinematically selected Hipparcos sample of de Zeeuw et al., restricted to the 138 F-type members. We have obtained classification-resolution optical spectra and have also determined the spectroscopic accretion disk fraction. With Hipparcos and 2MASS photometry, we estimate the reddening and extinction for each star and place the candidate members on a theoretical H-R diagram. For each subgroup we construct empirical isochrones and compare to published evolutionary tracks. We find that (1) our empirical isochrones are consistent with the previously published age-rank of the Sco-Cen subgroups; (2) subgroups LCC and UCL appear to reach the main-sequence turn-on at spectral types {approx}F4 and {approx}F2, respectively. An analysis of the A-type stars shows US reaching the main sequence at about spectral type {approx}A3. (3) The median ages for the pre-main-sequence members of UCL and LCC are 16 Myr and 17 Myr, respectively, in agreement with previous studies, however we find that (4) Upper Sco is much older than previously thought. The luminosities of the F-type stars in US are typically a factor of {approx}2.5 less luminous than predicted for a 5 Myr old population for four sets of evolutionary tracks. We re-examine the evolutionary state and isochronal ages for the B-, A-, and G-type Upper Sco members, as well as the evolved M supergiant Antares, and estimate a revised mean age for Upper Sco of 11 {+-} 1 {+-} 2 Myr (statistical, systematic). Using radial velocities and Hipparcos parallaxes we calculate a lower limit on the kinematic expansion age for Upper Sco of >10.5 Myr (99% confidence). However, the data are statistically consistent with no expansion. We reevaluate the inferred masses for the known substellar companions in Upper Sco using the revised age and find that the inferred masses are typically {approx}20%-70% higher than the original estimates which had assumed a much younger age; specifically, we estimate the mass of 1RXS J1609-2105b to be 14{sup +2}{sub -3} M{sub Jup}, suggesting that it is a brown dwarf rather than a planet. Finally, we find the fraction of F-type stars exhibiting H{alpha} emission and/or a K-band excess consistent with accretion to be 0/17 (<19%; 95% CL) in US at {approx}11 Myr, while UCL has 1/41 (2{sup +5}{sub -1}%; 68% CL) accretors and LCC has 1/50 (2{sup +4}{sub -1}%; 68% CL) accretors at {approx}16 Myr and {approx}17 Myr, respectively.

79 ASTRONOMY AND ASTROPHYSICS↗

Sonication-based isolation and enrichment of Chlorella protothecoides chloroplasts for illumina genome sequencing

With the increasing world demand for biofuel, a number of oleaginous algal species are being considered as renewable sources of oil. Chlorella protothecoides Krüger synthesizes triacylglycerols (TAGs) as storage compounds that can be converted into renewable fuel utilizing an anabolic pathway that is poorly understood. The paucity of algal chloroplast genome sequences has been an important constraint to chloroplast transformation and for studying gene expression in TAGs pathways. In this study, the intact chloroplasts were released from algal cells using sonication followed by sucrose gradient centrifugation, resulting in a 2.36-fold enrichment of chloroplasts from C. protothecoides, based on qPCR analysis. The C. protothecoides chloroplast genome (cpDNA) was determined using the Illumina HiSeq 2000 sequencing platform and found to be 84,576 Kb in size (8.57 Kb) in size, with a GC content of 30.8 %. This is the first report of an optimized protocol that uses a sonication step, followed by sucrose gradient centrifugation, to release and enrich intact chloroplasts from a microalga (C. prototheocoides) of sufficient quality to permit chloroplast genome sequencing with high coverage, while minimizing nuclear genome contamination. The approach is expected to guide chloroplast isolation from other oleaginous algal species for a variety of uses that benefit from enrichment of chloroplasts, ranging from biochemical analysis to genomics studies.

09 BIOMASS FUELS↗

The reduced genomes of Parcubacteria (OD1) contain signatures of a symbiotic lifestyle

Candidate phylum OD1 bacteria (also referred to as Parcubacteria) have been identified in broad range of anoxic environments through community survey analysis. Although none of these species have been isolated in the laboratory, several genome sequences have been reconstructed from metagenomic sequence data and single-cell sequencing. The organisms have small (generally <1 Mb) genomes with severely reduced metabolic capabilities. We have reconstructed 8 partial to near-complete OD1 genomes from oxic groundwater samples, and compared them against existing genomic data. The conserved core gene set comprises 202 genes, or ~28% of the genomic complement. ‘Housekeeping’ genes and genes for biosynthesis of peptidoglycan and Type IV pilus production are conserved. Gene sets for biosynthesis of cofactors, amino acids, nucleotides and fatty acids are absent entirely or greatly reduced. The only aspects of energy metabolism conserved are the non-oxidative branch of the pentose-phosphate shunt and central glycolysis. These organisms also lack some activities conserved in almost all other known bacterial genomes, including signal recognition particle, pseudouridine synthase A, and FAD synthase. Pan-genome analysis indicates a broad genotypic diversity and perhaps a highly fluid gene complement, indicating historical adaptation to a wide range of growth environments and a high degree of specialization. The genomes were examined for signatures suggesting either a free-living, streamlined lifestyle or a symbiotic lifestyle. The lack of biosynthetic capabilities and DNA repair, along with the presence of potential attachment and adhesion proteins suggest the Parcubacteria are ectosymbionts or parasites of other organisms. The wide diversity of genes that potentially mediate cell-cell contact suggests a broad range of partner/prey organisms across the phylum.

candidate phyla↗

Radioisotope Identification with List-Mode Gamma Ray Data: A rigorous assessment on the value of temporal information applied to radioisotope identification.

This work explores the potential of utilizing temporal data from gamma-ray detectors, known as list-mode data, to enhance radioisotope identification. Traditional identification methods, which rely on full gamma-ray spectrum analysis, often require long dwell times and struggle with “confuser” sources, or spectra with similarly spaced spectral peaks. We hypothesize that by leveraging the probabilistic nature of nuclear decay and the time-encoded information from decay sequences and interactions with surrounding materials, we can improve classification accuracy over static spectral analysis. This research rigorously examines the temporal content of list-mode data through exploratory data analysis via correlation discovery and information theory. We further propose a basic classification model that can utilize spectral or temporal data (or both) to determine if the incorporation of temporal information can improve radioisotope identification. The findings suggest that the temporal information present in list-mode gamma-ray data has merit and should be further investigated.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗