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At least 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Bioavailable iron titrations reveal oceanic Synechococcus ecotypes optimized for different iron availabilities

Abstract The trace metal iron (Fe) controls the diversity and activity of phytoplankton across the surface oceans, a paradigm established through decades of in situ and mesocosm experimental studies. Despite widespread Fe-limitation within high-nutrient, low chlorophyll (HNLC) waters, significant contributions of the cyanobacterium Synechococcus to the phytoplankton stock can be found. Correlations among differing strains of Synechococcus across different Fe-regimes have suggested the existence of Fe-adapted ecotypes. However, experimental evidence of high- versus low-Fe adapted strains of Synechococcus is lacking, and so we investigated the transcriptional responses of microbial communities inhabiting the HNLC, sub-Antarctic region of the Southern Ocean during the Spring of 2018. Analysis of metatranscriptomes generated from on-deck incubation experiments reflecting a gradient of Fe-availabilities reveal transcriptomic signatures indicative of co-occurring Synechococcus ecotypes adapted to differing Fe-regimes. Functional analyses comparing low-Fe and high-Fe conditions point to various Fe-acquisition mechanisms that may allow persistence of low-Fe adapted Synechococcus under Fe-limitation. Comparison of in situ surface conditions to the Fe-titrations indicate ecological relevance of these mechanisms as well as persistence of both putative ecotypes within this region. This Fe-titration approach, combined with transcriptomics, highlights the short-term responses of the in situ phytoplankton community to Fe-availability that are often overlooked by examining genomic content or bulk physiological responses alone. These findings expand our knowledge about how phytoplankton in HNLC Southern Ocean waters adapt and respond to changing Fe supply.

Gilbert, Naomi E. (ORCID:0000000256915547)↗
DOE OSTI2020

CRAGE-mediated insertion of fluorescent chromosomal markers for accurate and scalable measurement of co-culture dynamics in Escherichia coli

Monitoring population dynamics in co-culture is necessary in engineering microbial consortia involved in distributed metabolic processes or biosensing applications. However, it remains difficult to measure strain-specific growth dynamics in high-throughput formats. This is especially vexing in plate-based functional screens leveraging whole-cell biosensors to detect specific metabolic signals. Here, we develop an experimental high-throughput co-culture system to measure and model the relationship between fluorescence and cell abundance, combining chassis-independent recombinase-assisted genome engineering (CRAGE) and whole-cell biosensing with a PemrR-green fluorescent protein (GFP) monoaromatic reporter used in plate-based functional screening. CRAGE was used to construct Escherichia coli EPI300 strains constitutively expressing red fluorescent protein (RFP) and the relationship between RFP expression and optical density (OD600) was determined throughout the EPI300 growth cycle. A linear equation describing the increase of normalized RFP fluorescence during deceleration phase was derived and used to predict biosensor strain dynamics in co-culture. Measured and predicted values were compared using flow cytometric detection methods. Induction of the biosensor lead to increased GFP fluorescence normalized to biosensor cell abundance, as expected, but a significant decrease in relative abundance of the biosensor strain in co-culture and a decrease in bulk GFP fluorescence. Taken together, these results highlight sensitivity of population dynamics to variations in metabolic activity in co-culture and the potential effect of these dynamics on the performance of functional screens in plate-based formats. The engineered strains and model used to evaluate these dynamics provide a framework for optimizing growth of synthetic co-cultures used in screening, testing and pathway engineering applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

3′ RNA-seq is superior to standard RNA-seq in cases of sparse data but inferior at identifying toxicity pathways in a model organism

The application of RNA-sequencing has led to numerous breakthroughs related to investigating gene expression levels in complex biological systems. Among these are knowledge of how organisms, such as the vertebrate model organism zebrafish (Danio rerio), respond to toxicant exposure. Recently, the development of 3' RNA-seq has allowed for the determination of gene expression levels with a fraction of the required reads compared to standard RNA-seq. While 3' RNA-seq has many advantages, a comparison to standard RNA-seq has not been performed in the context of whole organism toxicity and sparse data. Here, we examined samples from zebrafish exposed to perfluorobutane sulfonamide (FBSA) with either 3' or standard RNA-seq to determine the advantages of each with regards to the identification of functionally enriched pathways. We found that 3' and standard RNA-seq showed specific advantages when focusing on annotated or unannotated regions of the genome. We also found that standard RNA-seq identified more differentially expressed genes (DEGs), but that this advantage disappeared under conditions of sparse data. We also found that standard RNA-seq had a significant advantage in identifying functionally enriched pathways via analysis of DEG lists but that this advantage was minimal when identifying pathways via gene set enrichment analysis of all genes. These results show that each approach has experimental conditions where they may be advantageous. Our observations can help guide others in the choice of 3' RNA-seq vs standard RNA sequencing to query gene expression levels in a range of biological systems.

3’ RNA-seq↗
DOE OSTI2022

Determining protein polarization proteome-wide using physical dissection of individual Stentor coeruleus cells

Cellular components are non-randomly arranged with respect to the shape and polarity of the whole cell. Patterning within cells can extend down to the level of individual proteins and mRNA. But how much of the proteome is actually localized with respect to cell polarity axes? Proteomics combined with cellular fractionation has shown that most proteins localize to one or more organelles but does not tell us how many proteins have a polarized localization with respect to the large-scale polarity axes of the intact cell. Genome-wide localization studies in yeast found that only a few percent of proteins have a localized position relative to the cell polarity axis defined by sites of polarized cell growth. Here, we describe an approach for analyzing protein distribution within a cell with a visibly obvious global patterning - the giant ciliate Stentor coeruleus. Ciliates, including Stentor, have highly polarized cell shapes with visible surface patterning. A Stentor cell is roughly 2mmlong, allowing a ‘‘proteomic dissection’’ in which microsurgery is used to separate cellular fragments along the anterior-posterior axis, followed by comparative proteomic analysis. In our analysis, 25% of the proteome, including signaling proteins, centrin/SFI proteins, and GAS2 orthologs, shows a polarized location along the cell’s anterior-posterior axis. We conclude that a large proportion of all proteins are polarized with respect to global cell polarity axes and that proteomic dissection provides a simple and effective approach for spatial proteomics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

To have value, comparisons of high-throughput phenotyping methods need statistical tests of bias and variance

The gap between genomics and phenomics is narrowing. The rate at which it is narrowing, however, is being slowed by improper statistical comparison of methods. Quantification using Pearson’s correlation coefficient ( r ) is commonly used to assess method quality, but it is an often misleading statistic for this purpose as it is unable to provide information about the relative quality of two methods. Using r can both erroneously discount methods that are inherently more precise and validate methods that are less accurate. These errors occur because of logical flaws inherent in the use of r when comparing methods, not as a problem of limited sample size or the unavoidable possibility of a type I error. A popular alternative to using r is to measure the limits of agreement (LOA). However both r and LOA fail to identify which instrument is more or less variable than the other and can lead to incorrect conclusions about method quality. An alternative approach, comparing variances of methods, requires repeated measurements of the same subject, but avoids incorrect conclusions. Variance comparison is arguably the most important component of method validation and, thus, when repeated measurements are possible, variance comparison provides considerable value to these studies. Statistical tests to compare variances presented here are well established, easy to interpret and ubiquitously available. The widespread use of r has potentially led to numerous incorrect conclusions about method quality, hampering development, and the approach described here would be useful to advance high throughput phenotyping methods but can also extend into any branch of science. The adoption of the statistical techniques outlined in this paper will help speed the adoption of new high throughput phenotyping techniques by indicating when one should reject a new method, outright replace an old method or conditionally use a new method.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

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

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

09 BIOMASS FUELS↗
DOE OSTI2026

Hydrazinoacetic acid is a biosynthetic precursor of the bacterially produced nitramine, N -nitroglycine

Nitramines [R(R′)N–NO 2 ; R,R′=H or alkyl] are valuable synthetic products, but knowledge of the biosynthetic processes that generate these compounds is limited. This work sought to elucidate the biosynthesis of a nitramine natural product, N-nitroglycine (NNG) by Streptomyces noursei . Stable isotope studies showed that S. noursei cells supplemented with L-(ε- 15 N)lysine, ( 15 N)glycine, or ( 13 C)hydrazinoacetic acid (HAA) incorporated 67%, 88%, and 67% of the isotope label into NNG, respectively, indicating that these compounds are biosynthetic precursors of NNG. Liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) of 15 N-Lys-labeled NNG confirmed that the nitro nitrogen of NNG originates from Lys. Bioinformatics analysis of the S. noursei genome showed evidence for a biosynthetic gene cluster (BGC) that contained machinery for HAA biosynthesis ( nngKLM ), consistent with the results of the isotope labeling. In vitro reconstitution of the gene products produced HAA. The borders of this BGC were defined by cross-referencing the predicted BGC with previously published differential proteomics data. Furthermore, we show that azaserine is produced alongside NNG in S. noursei cultures, linking the two biosynthetic pathways via a proposed nitrosamine biosynthetic intermediate. Finally, the oxygen balance for NNG is −20.2% for the formation of carbon dioxide (CO 2 ), which is comparable to that of hexahydro-1,3,5- trinitro-1,3,5-triazene (common name: RDX; −21.6%). Crystal structure data of NNG indicate that the unit crystalizes as a pure material, not a hydrate, suggesting a favorable energetic crystallization phase. The combined results suggest a route that, with further development, could lead to sustainable production of energetic nitramines via synthetic biology or biocatalytic approaches.

biosynthesis↗
DOE OSTI2022

TbasCO: trait-based comparative ‘omics identifies ecosystem-level and niche-differentiating adaptations of an engineered microbiome

A grand challenge in microbial ecology is disentangling the traits of individual populations within complex communities. Various cultivation-independent approaches have been used to infer traits based on the presence of marker genes. However, marker genes are not linked to traits with complete fidelity, nor do they capture important attributes, such as the timing of gene expression or coordination among traits. To address this, we present an approach for assessing the trait landscape of microbial communities by statistically defining a trait attribute as a shared transcriptional pattern across multiple organisms. Leveraging the KEGG pathway database as a trait library and the Enhanced Biological Phosphorus Removal (EBPR) model microbial ecosystem, we demonstrate that a majority (65%) of traits present in 10 or more genomes have niche-differentiating expression attributes. For example, while many genomes containing high-affinity phosphorus transporter pstABCS display a canonical attribute (e.g. up-regulation under phosphorus starvation), we identified another attribute shared by many genomes where transcription was highest under high phosphorus conditions. Taken together, we provide a novel framework for unravelling the functional dynamics of uncultivated microorganisms by assigning trait-attributes through genome-resolved time-series metatranscriptomics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Growth-associated polyhydroxybutyrate accumulation in Azospira suillum PS during aerobic and perchlorate respiration

Polyhydroxyalkanoates (PHAs) are widespread microbial storage polymers increasingly recognized for roles beyond carbon and energy storage, including redox homeostasis and stress physiology. While PHA accumulation is classically associated with stationary-phase metabolism under severe nutrient imbalance, comparatively little is known about growth-associated PHA synthesis in facultative anaerobes with unusual respiratory strategies. Here, we investigated polyhydroxybutyrate (PHB) metabolism in Azospira suillum PS, a genetically tractable perchlorate-reducing bacterium capable of both aerobic and anaerobic respiration. Using physiological growth experiments, targeted gene deletions, PHB extractions, and intracellular redox measurements, we examined PHB accumulation under varying respiratory and nutrient conditions. We demonstrate that PHB accumulates during exponential growth under moderately nitrogen-limited conditions, both aerobically and during perchlorate respiration, representing a rare example of growth-associated PHB synthesis under anaerobic conditions. Genomic analysis revealed four phaC homologs, one of which could not be deleted under the experimental conditions tested and co-localized with phaB and phaR. Redox profiling further revealed a strong positive correlation between PHB accumulation and intracellular NADPH/NADP+ ratios. Together, these findings expand the physiological contexts in which PHB synthesis is known to occur and highlight perchlorate-respiring bacteria as underexplored model systems for studying growth-integrated carbon and redox storage strategies.

Meier, David A O↗
DOE OSTI2024

Comparison of genotyping assays for detection of targeted CRISPR/Cas mutagenesis in highly polyploid sugarcane

Sugarcane (Saccharum spp.) is an important biofuel feedstock and a leading source of global table sugar. Saccharum hybrid cultivars are highly polyploid (2n = 100–130), containing large numbers of functionally redundant hom(e)ologs in their genomes. Genome editing with sequence-specific nucleases holds tremendous promise for sugarcane breeding. However, identification of plants with the desired level of co-editing within a pool of primary transformants can be difficult. While DNA sequencing provides direct evidence of targeted mutagenesis, it is cost-prohibitive as a primary screening method in sugarcane and most other methods of identifying mutant lines have not been optimized for use in highly polyploid species. In this study, non-sequencing methods of mutant screening, including capillary electrophoresis (CE), Cas9 RNP assay, and high-resolution melt analysis (HRMA), were compared to assess their potential for CRISPR/Cas9-mediated mutant screening in sugarcane. These assays were used to analyze sugarcane lines containing mutations at one or more of six sgRNA target sites. All three methods distinguished edited lines from wild type, with co-mutation frequencies ranging from 2% to 100%. Cas9 RNP assays were able to identify mutant sugarcane lines with as low as 3.2% co-mutation frequency, and samples could be scored based on undigested band intensity. CE was highlighted as the most comprehensive assay, delivering precise information on both mutagenesis frequency and indel size to a 1 bp resolution across all six targets. This represents an economical and comprehensive alternative to sequencing-based genotyping methods which could be applied in other polyploid species.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Temporal regulation of cold transcriptional response in switchgrass

Switchgrass low-land ecotypes have significantly higher biomass but lower cold tolerance compared to up-land ecotypes. Understanding the molecular mechanisms underlying cold response, including the ones at transcriptional level, can contribute to improving tolerance of high-yield switchgrass under chilling and freezing environmental conditions. Here, by analyzing an existing switchgrass transcriptome dataset, the temporal cis- regulatory basis of switchgrass transcriptional response to cold is dissected computationally. We found that the number of cold-responsive genes and enriched Gene Ontology terms increased as duration of cold treatment increased from 30 min to 24 hours, suggesting an amplified response/cascading effect in cold-responsive gene expression. To identify genomic sequences likely important for regulating cold response, machine learning models predictive of cold response were established using k -mer sequences enriched in the genic and flanking regions of cold-responsive genes but not non-responsive genes. These k -mers, referred to as putative cis -regulatory elements (pCREs) are likely regulatory sequences of cold response in switchgrass. There are in total 655 pCREs where 54 are important in all cold treatment time points. Consistent with this, eight of 35 known cold-responsive CREs were similar to top-ranked pCREs in the models and only these eight were important for predicting temporal cold response. More importantly, most of the top-ranked pCREs were novel sequences in cold regulation. Our findings suggest additional sequence elements important for cold-responsive regulation previously not known that warrant further studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

PlasmidHostFinder: Prediction of Plasmid Hosts Using Random Forest

Plasmids play a major role facilitating the spread of antimicrobial resistance between bacteria. Understanding the host range and dissemination trajectories of plasmids is critical for surveillance and prevention of antimicrobial resistance. Identification of plasmid host ranges could be improved using automated pattern detection methods compared to homology-based methods due to the diversity and genetic plasticity of plasmids. In this study, we developed a method for predicting the host range of plasmids using machine learning—specifically, random forests. We trained the models with 8,519 plasmids from 359 different bacterial species per taxonomic level; the models achieved Matthews correlation coefficients of 0.662 and 0.867 at the species and order levels, respectively. Our results suggest that despite the diverse nature and genetic plasticity of plasmids, our random forest model can accurately distinguish between plasmid hosts. This tool is available online through the Center for Genomic Epidemiology (https://cge.cbs.dtu.dk/services/PlasmidHostFinder/).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Widespread transposon co-option in the Caenorhabditis germline regulatory network

The movement of selfish DNA elements can lead to widespread genomic alterations with potential to create novel functions. We show that transposon expansions in Caenorhabditis nematodes led to extensive rewiring of germline transcriptional regulation. We find that about one-third of Caenorhabditis elegans germline-specific promoters have been co-opted from two related miniature inverted repeat transposable elements (TEs), CERP2 and CELE2. These promoters are regulated by HIM-17, a THAP domain–containing transcription factor related to a transposase. Expansion of CERP2 occurred before radiation of the Caenorhabditis genus, as did fixation of mutations in HIM-17 through positive selection, whereas CELE2 expanded only in C. elegans. Through comparative analyses in Caenorhabditis briggsae, we find not only evolutionary conservation of most CERP2 co-opted promoters but also a substantial fraction that are species-specific. Our work reveals the emergence and evolutionary conservation of a novel transcriptional network driven by TE co-option with a major impact on regulatory evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Synergistic interactions between anammox and dissimilatory nitrate reducing bacteria sustains reactor performance across variable nitrogen loading ratios

Anaerobic ammonium oxidizing (anammox) bacteria are utilized for high efficiency nitrogen removal from nitrogen-laden sidestreams in wastewater treatment plants. The anammox bacteria form a variety of competitive and mutualistic interactions with heterotrophic bacteria that often employ denitrification or dissimilatory nitrate reduction to ammonium (DNRA) for energy generation. These interactions can be heavily influenced by the influent ratio of ammonium to nitrite, NH 4 + :NO 2 - , where deviations from the widely acknowledged stoichiometric ratio (1:1.32) have been demonstrated to have deleterious effects on anammox efficiency. Thus, it is important to understand how variable NH 4 + :NO 2 - ratios impact the microbial ecology of anammox reactors. We observed the response of the microbial community in a lab scale anammox membrane bioreactor (MBR) to changes in the influent NH 4 + :NO 2 - ratio using both 16S rRNA gene and shotgun metagenomic sequencing. Ammonium removal efficiency decreased from 99.77 ± 0.04% when the ratio was 1:1.32 (prior to day 89) to 90.85 ± 0.29% when the ratio was decreased to 1:1.1 (day 89–202) and 90.14 ± 0.09% when the ratio was changed to 1:1.13 (day 169–200). Over this same timespan, the overall nitrogen removal efficiency (NRE) remained relatively unchanged (85.26 ± 0.01% from day 0–89, compared to 85.49 ± 0.01% from day 89–169, and 83.04 ± 0.01% from day 169–200). When the ratio was slightly increased to 1:1.17–1:1.2 (day 202–253), the ammonium removal efficiency increased to 97.28 ± 0.45% and the NRE increased to 88.21 ± 0.01%. Analysis of 16S rRNA gene sequences demonstrated increased relative abundance of taxa belonging to Bacteroidetes, Chloroflexi, and Ignavibacteriae over the course of the experiment. The relative abundance of Planctomycetes, the phylum to which anammox bacteria belong, decreased from 77.19% at the beginning of the experiment to 12.24% by the end of the experiment. Analysis of metagenome assembled genomes (MAGs) indicated increased abundance of bacteria with nrfAH genes used for DNRA after the introduction of lower influent NH 4 + :NO 2 - ratios. The high relative abundance of DNRA bacteria coinciding with sustained bioreactor performance indicates a mutualistic relationship between the anammox and DNRA bacteria. Understanding these interactions could support more robust bioreactor operation at variable nitrogen loading ratios.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A Two-Step PCR Protocol Enabling Flexible Primer Choice and High Sequencing Yield for Illumina MiSeq Meta-Barcoding

High-throughput amplicon sequencing that primarily targets the 16S ribosomal DNA (rDNA) (for bacteria and archaea) and the Internal Transcribed Spacer rDNA (for fungi) have facilitated microbial community discovery across diverse environments. A three-step PCR that utilizes flexible primer choices to construct the library for Illumina amplicon sequencing has been applied to several studies in forest and agricultural systems. The three-step PCR protocol, while producing high-quality reads, often yields a large number (up to 46%) of reads that are unable to be assigned to a specific sample according to its barcode. Here, we improve this technique through an optimized two-step PCR protocol. We tested and compared the improved two-step PCR meta-barcoding protocol against the three-step PCR protocol using four different primer pairs (fungal ITS: ITS1F-ITS2 and ITS1F-ITS4, and bacterial 16S: 515F-806R and 341F-806R). We demonstrate that the sequence quantity and recovery rate were significantly improved with the two-step PCR approach (fourfold more read counts per sample; determined reads ≈90% per run) while retaining high read quality (Q30 > 80%). Given that synthetic barcodes are incorporated independently from any specific primers, this two-step PCR protocol can be broadly adapted to different genomic regions and organisms of scientific interest.

16S rDNA↗
DOE OSTI2020

Deletion of CD2-Like (CD2v) and C-Type Lectin-Like (EP153R) Genes from African Swine Fever Virus Georgia-Δ9GL Abrogates Its Effectiveness as an Experimental Vaccine

African swine fever virus (ASFV) is currently the most dreaded infectious disease affecting the global swine production industry. There is no commercial vaccine available, making the culling of infected animals the current solution to control outbreaks. Effective experimental vaccines have been developed by deleting virus genes associated with virulence. Deletion of the ASFV 9GL gene (Δ9GL) has resulted in the attenuation of different ASFV strains, although the degree of attenuation varies across isolates. Here, we investigated the possibility of the increased safety of the experimental vaccine strain ASFV-G-Δ9GL by deleting two additional virus genes involved in pathogenesis, CD2v, a CD2 like viral encoded gene from the EP402R open reading frame (ORF), and C-type lectin-like viral gene, encoded from the EP153R ORF. Two new recombinant viruses were developed, ASFV-G-Δ9GL/ΔCD2v and ASFV-G-Δ9GL/ΔCD2v/ΔEP153R, harboring two and three gene deletions, respectively. ASFV-G-Δ9GL/ΔCD2v/ΔEP153R, but not ASFV-G-Δ9GL/ΔCD2v, had a decreased ability to replicate in vitro in swine macrophage cultures when compared with parental ASFV-G-Δ9GL. Importantly, ASFV-G-Δ9GL/ΔCD2v and ASFV-G-Δ9GL/ΔCD2v/ΔEP153R induced almost undetectable viremia levels when inoculated into domestic pigs and failed to protect them against challenge with parental virulent ASFV-Georgia, while ASFV-G-Δ9GL offered robust protection during challenge. Therefore, the deletion of CD2-like and C-type lectin-like genes significantly decreased the protective potential of ASFV-G-Δ9GL as a vaccine candidate. This study constitutes an example of the unpredictability of genetic manipulation involving the simultaneous deletion of multiple genes from the ASFV genome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Deletion of the EP402R Gene from the Genome of African Swine Fever Vaccine Strain ASFV-G-ΔI177L Provides the Potential Capability of Differentiating between Infected and Vaccinated Animals

The African swine fever virus (ASFV) mutant ASFV-G-ΔI177L is a safe and efficacious vaccine which induces protection against the challenge of its parental virus, the Georgia 2010 isolate. Although a genetic DIVA (differentiation between infected and vaccinated animals) assay has been developed for this vaccine, still there is not a serological DIVA test for differentiating between animals vaccinated with ASFV-G-ΔI177L and those infected with wild-type viruses. In this report, we describe the development of the ASFV-G-ΔI177L mutant having deleted the EP402R gene, which encodes for the viral protein responsible for mediating the hemadsorption of swine erythrocytes. The resulting virus, ASFV-G-ΔI177L/ΔEP402R, does not have a decreased ability to replicates in swine macrophages when compared with the parental ASFV-G-ΔI177L. Domestic pigs intramuscularly (IM) inoculated with either 10 2 or 10 6 HAD 50 of ASFV-G-ΔI177L/ΔEP402R remained clinically normal, when compared with a group of mock-vaccinated animals, indicating the absence of residual virulence. Interestingly, an infectious virus could not be detected in the blood samples of the ASFV-G-ΔI177L/ΔEP402R-inoculated animals in either group at any of the time points tested. Furthermore, while all of the mock-inoculated animals presented a quick and lethal clinical form of ASF after the intramuscular inoculation challenge with 10 2 HAD 50 of highly virulent parental field isolate Georgia 2010 (ASFV-G), all of the ASFV-G-ΔI177L/ΔEP402R-inoculated animals were protected, remaining clinically normal until the end of the observational period. Most of the ASFV-G-ΔI177L/ΔEP402R-inoculated pigs developed strong virus-specific antibody responses against viral antigens, reaching maximum levels at 28 days post inoculation. Importantly, all of the sera collected at that time point in the ASFV-G-ΔI177L/ΔEP402R-inoculated pigs did not react in a direct ELISA coated with the recombinant EP402R protein. Conversely, the EP402R protein was readily recognized by the pool of sera from the animals immunized with recombinant live attenuated vaccine candidates ASFV-G-ΔI177L, ASFV-G-ΔMGF, or ASFV-G-Δ9GL/ΔUK. Therefore, ASFV-G-ΔI177L/ΔEP402R is a novel, safe and efficacious candidate with potential to be used as an antigenically DIVA vaccine.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The joint automated repository for various integrated simulations (JARVIS) for data-driven materials design

The Joint Automated Repository for Various Integrated Simulations (JARVIS) is an integrated infrastructure to accelerate materials discovery and design using density functional theory (DFT), classical force-fields (FF), and machine learning (ML) techniques. JARVIS is motivated by the Materials Genome Initiative (MGI) principles of developing open-access databases and tools to reduce the cost and development time of materials discovery, optimization, and deployment. The major features of JARVIS are: JARVIS-DFT, JARVIS-FF, JARVIS-ML, and JARVIS-tools. To date, JARVIS consists of ≈40,000 materials and ≈1 million calculated properties in JARVIS-DFT, ≈500 materials and ≈110 force-fields in JARVIS-FF, and ≈25 ML models for material-property predictions in JARVIS-ML, all of which are continuously expanding. JARVIS-tools provides scripts and workflows for running and analyzing various simulations. We compare our computational data to experiments or high-fidelity computational methods wherever applicable to evaluate error/uncertainty in predictions. In addition to the existing workflows, the infrastructure can support a wide variety of other technologically important applications as part of the data-driven materials design paradigm. The JARVIS datasets and tools are publicly available at the website: https://jarvis.nist.gov .

36 MATERIALS SCIENCE↗