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At least 487 records · Page 27

Floodplain nitrifiers harbor the genetic potential for utilizing a wide range of organic nitrogen compounds

Organic compounds such as urea and cyanate can serve as nitrogen (N) sources for nitrifying microorganisms, including ammonia-oxidizing archaea (AOA) and bacteria (AOB), complete ammonia-oxidizing (comammox) bacteria, and nitrite-oxidizing bacteria (NOB). Here we investigated metagenome-assembled genomes (MAGs) for all four nitrifier guilds generated from hydrologically variable floodplain sediments of the Wind River Basin (WRB; Riverton, WY, USA) for their genetic potential to utilize organic N compounds. A vast majority of WRB nitrifier MAGs harbored urease (ure) and at least one urea transporter ( utp, urt, dur3 ). AOA were the most abundant and phylogenetically diverse nitrifiers in WRB floodplain sediments. Several AOA MAGs encoded cyanase ( cynS ), nitrilase ( nit1 ), omega-amidase ( nit2 ), nitrile hydratase ( nthA ), and genes related to purine degradation, including biuret hydrolase ( biuH ), oxamic transcarbamylase ( allFGH ), and catabolic carbamate kinase ( allK ). AOA often encoded an uncharacterized amidohydrolase collocated with biuH , rather than allophanate hydrolase ( atzF ). A small number of AOA encoded atzF , functioning in an unknown pathway. AOB and comammox were of relatively low abundance and taxonomic diversity and were present only at certain depths in WRB; however, they encoded triuret/biuret degradation genes ( trtA, biuH , and atzH ), and in comammox, these genes were also collocated with allFGHK . The genetic potential of ammonia oxidizers in the WRB floodplain suggests that organic N may support nitrification in this system. The proposed pathways for utilizing purine degradation products other than urea potentially expand the known metabolic capabilities of AOA, AOB, and comammox bacteria and reveal the possibility for cryptic N cycling between microbial community members.

floodplain↗

Comparison of phage-derived recombinases for genetic manipulation of Pseudomonas species

ABSTRACT Several strains in the Pseudomonas genus are categorized as plant growth-promoting rhizobacteria (PGPR). Although several of these strains are strong candidates for applications as biofertilizers or biopesticides, genome editing approaches are generally limited and require further development. Editing genomes in PGPR could enable more robust agricultural applications, persistence, and biosafety measures. In this study, we investigate the use of five phage-encoded recombinases to develop a recombineering workflow in three PGPR strains: Pseudomonas protegens Pf-5, Pseudomonas protegens CHA0, and Pseudomonas putida KT2440. Using point mutations in the rpoB gene, we reach maximum recombineering efficiencies of 1.5 × 10 −4 , 3 × 10 −4 , and 5 × 10 −5 , respectively, in these strains using λ-Red Beta recombinase from Escherichia coli . We further examine recombineering efficiencies across these strains as a function of selected mutation, editing template concentration, and phosphorothiolate bond protection. This work validates the use of these tools across several environmentally and biotechnologically relevant strains to expand the possibilities of genetic manipulation in the Pseudomonas genus. IMPORTANCE The Pseudomonas genus contains many members currently being investigated for applications in biodegradation, biopesticides, biocontrol, and synthetic biology. Though several strains have been identified with beneficial properties, chromosomal manipulations to further improve these strains for commercial applications have been limited due to the lack of efficient genetic tools that have been tested across this genus. Here, we test the recombineering efficiencies of five phage-derived recombinases across three biotechnologically relevant Pseudomonas strains: P. putida KT2440, P. protegens Pf-5, and P. protegens CHA0. These results demonstrate a method to generate targeted mutations quickly and efficiently across these strains, ideally introducing a method that can be implemented across the Pseudomonas genus and a strategy that may be applied to develop analogous systems in other nonmodel bacteria.

59 BASIC BIOLOGICAL SCIENCES↗

Pharmacologic or genetic interference with atrogene signaling protects against glucocorticoid-induced musculoskeletal and cardiac disease

Despite their beneficial actions as immunosuppressants, glucocorticoids (GC) have devastating effects on the musculoskeletal and cardiac systems, as long-term treated patients exhibit high incidence of falls, bone fractures, and cardiovascular events. Herein, we show that GC upregulate simultaneously in bone, skeletal muscle, and the heart the expression of E3 ubiquitin ligases (atrogenes), known to stimulate the proteasomal degradation of proteins. Activation of vitamin D receptor (VDR) signaling with the VDR ligands calcitriol or eldecalcitol prevented GC-induced atrogene upregulation in vivo and ex vivo in bone/muscle organ cultures and preserved tissue structure/mass and function of the 3 tissues in vivo. Direct pharmacologic inhibition of the proteasome with carfilzomib also conferred musculoskeletal protection. Genetic loss of the atrogene MuRF1-mediated protein ubiquitination in ΔRING mice afforded temporary or sustained protection from GC excess in bone or skeletal and heart muscle. We concluded that the atrogene pathway downstream of MuRF1 underlies GC action in bone, muscle, and the heart, and it can be pharmacologically or genetically targeted to confer protection against the damaging actions of GC simultaneously in the 3 tissues.

Research & Experimental Medicine↗

An FDA-approved drug structurally and phenotypically corrects the K210del mutation in genetic cardiomyopathy models

Dilated cardiomyopathy (DCM) due to genetic disorders results in decreased myocardial contractility, leading to high morbidity and mortality rates. There are several therapeutic challenges in treating DCM, including poor understanding of the underlying mechanism of impaired myocardial contractility and the difficulty of developing targeted therapies to reverse mutation-specific pathologies. In this report, we focused on K210del, a DCM-causing mutation, due to 3-nucleotide deletion of sarcomeric troponin T (TnnT), resulting in loss of Lysine210. We resolved the crystal structure of the troponin complex carrying the K210del mutation. K210del induced an allosteric shift in the troponin complex resulting in distortion of activation Ca 2+ -binding domain of troponin C (TnnC) at S69, resulting in calcium discoordination. Next, we adopted a structure-based drug repurposing approach to identify bisphosphonate risedronate as a potential structural corrector for the mutant troponin complex. Cocrystallization of risedronate with the mutant troponin complex restored the normal configuration of S69 and calcium coordination. Risedronate normalized force generation in K210del patient-induced pluripotent stem cell–derived (iPSC-derived) cardiomyocytes and improved calcium sensitivity in skinned papillary muscles isolated from K210del mice. Systemic administration of risedronate to K210del mice normalized left ventricular ejection fraction. Collectively, these results identify the structural basis for decreased calcium sensitivity in K210del and highlight structural and phenotypic correction as a potential therapeutic strategy in genetic cardiomyopathies.

Research & Experimental Medicine↗

Assembled genomic and tissue-specific transcriptomic data resources for two genetically distinct lines of Cowpea (Vigna unguiculata (L.) Walp)

Cowpea (Vigna unguiculata (L.) Walp) is an important legume crop for food security in areas of low-input and smallholder farming throughout Africa and Asia. Genetic improvements are required to increase yield and resilience to biotic and abiotic stress and to enhance cowpea crop performance. An integrated cowpea genomic and gene expression data resource has the potential to greatly accelerate breeding and the delivery of novel genetic traits for cowpea. Extensive genomic resources for cowpea have been absent from the public domain; however, a recent early release reference genome for IT97K-499-35 (Vigna unguiculata v1.0, NSF, UCR, USAID, DOE-JGI, http://phytozome.jgi.doe.gov/) has now been established in a collaboration between the Joint Genome Institute (JGI) and University California (UC) Riverside. Here we release supporting genomic and transcriptomic data for IT97K-499-35 and a second transformable cowpea variety, IT86D-1010. The transcriptome resource includes six tissue-specific datasets for each variety, with particular emphasis on reproductive tissues that extend and support the V. unguiculata v1.0 reference. Annotations have been included in our resource to allow direct mapping to the v1.0 cowpea reference. Access to this resource provided here is supported by raw and assembled data downloads.

Spriggs, Andrew↗

Data for "Anti-Pdc1p Nanobody as a Genetically Encoded Inhibitor of Ethanol Production Enables Dual Transcriptional and Post-translational Controls of Yeast Fermentations"

Microbial fermentation provides a sustainable method of producing valuable chemicals. Adding dynamic control to fermentations can significantly improve titers, but most systems rely on transcriptional controls of metabolic enzymes, leaving existing intracellular enzymes unregulated. This limits the ability of transcriptional controls to switch off metabolic pathways, especially when metabolic enzymes have long half-lives. We developed a two-layer transcriptional/post-translational control system for yeast fermentations. Specifically, the system uses blue light to transcriptionally activate the major pyruvate decarboxylase PDC1 , required for cell growth and concomitant ethanol production. Switching to darkness transcriptionally inactivates PDC1 and instead activates the anti-Pdc1p nanobody, NbJRI, to act as a genetically encoded inhibitor of Pdc1p accumulated during the growth phase. This dual transcriptional/post-translational control improves the production of 2,3-BDO and citramalate by up to 100 and 92% compared to using transcriptional controls alone in dynamic two-phase fermentations. This study establishes the NbJRI nanobody as an effective genetically encoded inhibitor of Pdc1p that can enhance the production of pyruvate-derived chemicals.

metabolic engineering↗

Data for "RT-EZ: A Golden Gate Assembly Toolkit for Streamlined Genetic Engineering of Rhodotorula toruloides"

For economic and sustainable biomanufacturing, the oleaginous yeast Rhodotorula toruloides has emerged as a promising platform for producing biofuels, pharmaceuticals, and other valuable chemicals. However, genetic manipulation of R. toruloides has been limited by its high GC content and the lack of a replicating plasmid, necessitating gene integration into the genome of the yeast. To address these challenges, we developed the RT-EZ ( R. toruloides Efficient Zipper) toolkit, a versatile tool based on Golden Gate assembly, designed to streamline R. toruloides engineering with improved efficiency and flexibility. The RT-EZ toolkit simplifies vector construction by incorporating new features such as bidirectional promoters and 2A peptides, color-based screening using RFP, and sequences optimized for both Agrobacterium tumefaciens-mediated transformation (ATMT) and easy linearization, enabling straightforward selection and transformation. Notably, the RT-EZ kit can be used to construct an expression cassette with four different genes in one assembly reaction, significantly improving vector construction speed and efficiency. The utility of the RT-EZ toolkit was demonstrated through the successful synthesis of arachidonic acid in R. toruloides by coexpressing fatty acid elongases and desaturases. This result underscores the potential of the RT-EZ toolkit to advance synthetic biology in R. toruloides , providing a streamlined method for addressing genetic engineering challenges in the yeast.

gene editing↗

Genetic algorithm-based optimisation of the few-group structure for lead fast reactors analysis

The optimal choice of the few-group structure for full-core transient analyses is still an open issue in reactor physics, especially for fast system like the lead fast reactor. One possible approach to select the group boundaries is represented by heuristic search algorithms, such as evolutionary ones. In this paper, a genetic algorithm coupled with the SIMMER code is employed to determine optimized six-group boundaries for the analysis of the ALFRED reactor. The Serpent Monte Carlo code is adopted to produce both the fine-group cross section library and the fine-group flux, used as a figure of merit to drive the genetic optimisation. The results show that the algorithm is indeed able to find satisfactory solutions that comply with the set objectives and can be reasonably interpreted in light of the underlying physics of the considered core. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A sensitive and specific genetically-encoded potassium ion biosensor for in vivo applications across the tree of life

Potassium ion (K + ) plays a critical role as an essential electrolyte in all biological systems. Genetically-encoded fluorescent K + biosensors are promising tools to further improve our understanding of K + -dependent processes under normal and pathological conditions. Here, we report the crystal structure of a previously reported genetically-encoded fluorescent K + biosensor, GINKO1, in the K + -bound state. Using structure-guided optimization and directed evolution, we have engineered an improved K + biosensor, designated GINKO2, with higher sensitivity and specificity. We have demonstrated the utility of GINKO2 for in vivo detection and imaging of K + dynamics in multiple model organisms, including bacteria, plants, and mice.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic Selection for Context-Dependent Stochastic Phenotypes: Sp1 and TATA Mutations Increase Phenotypic Noise in HIV-1 Gene Expression

The sequence of a promoter within a genome does not uniquely determine gene expression levels and their variability; rather, promoter sequence can additionally interact with its location in the genome, or genomic context, to shape eukaryotic gene expression. Retroviruses, such as human immunodeficiency virus-1 (HIV), integrate their genomes into those of their host and thereby provide a biomedically-relevant model system to quantitatively explore the relationship between promoter sequence, genomic context, and noise-driven variability on viral gene expression. Using an in vitro model of the HIV Tat-mediated positive-feedback loop, we previously demonstrated that fluctuations in viral Tattransactivating protein levels generate integration-site-dependent, stochastically-driven phenotypes, in which infected cells randomly ‘switch’ between high and low expressing states in a manner that may be related to viral latency. Here we extended this model and designed a forward genetic screen to systematically identify genetic elements in the HIV LTR promoter that modulate the fraction of genomic integrations that specify ‘Switching’ phenotypes. Our screen identified mutations in core promoter regions, including Sp1 and TATA transcription factor binding sites, which increased the Switching fraction several fold. By integrating single-cell experiments with computational modeling, we further investigated the mechanism of Switching-fraction enhancement for a selected Sp1 mutation. Our experimental observations demonstrated that the Sp1 mutation both impaired Tat-transactivated expression and also altered basal expression in the absence of Tat. Computational analysis demonstrated that the observed change in basal expression could contribute significantly to the observed increase in viral integrations that specify a Switching phenotype, provided that the selected mutation affected Tat-mediated noise amplification differentially across genomic contexts. Our study thus demonstrates a methodology to identify and characterize promoter elements that affect the distribution of stochastic phenotypes over genomic contexts, and advances our understanding of how promoter mutations may control the frequency of latent HIV infection.

59 BASIC BIOLOGICAL SCIENCES↗

A Multi-scale Computational Platform to Mechanistically Assess the Effect of Genetic Variation on Drug Responses in Human Erythrocyte Metabolism

Progress in systems medicine brings promise to addressing patient heterogeneity and individualized therapies. Recently, genome-scale models of metabolism have been shown to provide insight into the mechanistic link between drug therapies and systems-level off-target effects while being expanded to explicitly include the three-dimensional structure of proteins. The integration of these molecular-level details, such as the physical, structural, and dynamical properties of proteins, notably expands the computational description of biochemical network-level properties and the possibility of understanding and predicting whole cell phenotypes. In this study, we present a multi-scale modeling framework that describes biological processes which range in scale from atomistic details to an entire metabolic network. Using this approach, we can understand how genetic variation, which impacts the structure and reactivity of a protein, influences both native and drug-induced metabolic states. As a proof-of-concept, we study three enzymes (catechol-O-methyltransferase, glucose-6-phosphate dehydrogenase, and glyceraldehyde-3-phosphate dehydrogenase) and their respective genetic variants which have clinically relevant associations. Using all-atom molecular dynamic simulations enables the sampling of long timescale conformational dynamics of the proteins (and their mutant variants) in complex with their respective native metabolites or drug molecules. We find that changes in a protein’s structure due to a mutation influences protein binding affinity to metabolites and/or drug molecules, and inflicts large-scale changes in metabolism

59 BASIC BIOLOGICAL SCIENCES↗

Filling gaps in bacterial catabolic pathways with computation and high-throughput genetics

To discover novel catabolic enzymes and transporters, we combined high-throughput genetic data from 29 bacteria with an automated tool to find gaps in their catabolic pathways. GapMind for carbon sources automatically annotates the uptake and catabolism of 62 compounds in bacterial and archaeal genomes. For the compounds that are utilized by the 29 bacteria, we systematically examined the gaps in GapMind’s predicted pathways, and we used the mutant fitness data to find additional genes that were involved in their utilization. We identified novel pathways or enzymes for the utilization of glucosamine, citrulline, myo-inositol, lactose, and phenylacetate, and we annotated 299 diverged enzymes and transporters. We also curated 125 proteins from published reports. For the 29 bacteria with genetic data, GapMind finds high-confidence paths for 85% of utilized carbon sources. In diverse bacteria and archaea, 38% of utilized carbon sources have high-confidence paths, which was improved from 27% by incorporating the fitness-based annotations and our curation. GapMind for carbon sources is available as a web server ( http://papers.genomics.lbl.gov/carbon ) and takes just 30 seconds for the typical genome.

59 BASIC BIOLOGICAL SCIENCES↗

Scanning the landscape of genome architecture of non-O1 and non-O139 Vibrio cholerae by whole genome mapping reveals extensive population genetic diversity

Historically, cholera outbreaks have been linked to V. cholerae O1 serogroup strains or its derivatives of the O37 and O139 serogroups. A genomic study on the 2010 Haiti cholera outbreak strains highlighted the putative role of non O1/non-O139 V. cholerae in causing cholera and the lack of genomic sequences of such strains from around the world. Here we address these gaps by scanning a global collection of V. cholerae strains as a first step towards understanding the population genetic diversity and epidemic potential of non O1/non-O139 strains. Whole Genome Mapping (Optical Mapping) based bar coding produces a high resolution, ordered restriction map, depicting a complete view of the unique chromosomal architecture of an organism. To assess the genomic diversity of non-O1/non-O139 V. cholerae , we applied a Whole Genome Mapping strategy on a well-defined and geographically and temporally diverse strain collection, the Sakazaki serogroup type strains. Whole Genome Map data on 91 of the 206 serogroup type strains support the hypothesis that V. cholerae has an unprecedented genetic and genomic structural diversity. Interestingly, we discovered chromosomal fusions in two unusual strains that possess a single chromosome instead of the two chromosomes usually found in V. cholerae . We also found pervasive chromosomal rearrangements such as duplications and indels in many strains. The majority of Vibrio genome sequences currently in public databases are unfinished draft sequences. The Whole Genome Mapping approach presented here enables rapid screening of large strain collections to capture genomic complexities that would not have been otherwise revealed by unfinished draft genome sequencing and thus aids in assembling and finishing draft sequences of complex genomes. Furthermore, Whole Genome Mapping allows for prediction of novel V. cholerae non-O1/non-O139 strains that may have the potential to cause future cholera outbreaks.

59 BASIC BIOLOGICAL SCIENCES↗

Real-Time Pathogen Detection in the Era of Whole-Genome Sequencing and Big Data: Comparison of k-mer and Site-Based Methods for Inferring the Genetic Distances among Tens of Thousands of Salmonella Samples

The adoption of whole-genome sequencing within the public health realm for molecular characterization of bacterial pathogens has been followed by an increased emphasis on real-time detection of emerging outbreaks (e.g., food-borne Salmonellosis). In turn, large databases of whole-genome sequence data are being populated. These databases currently contain tens of thousands of samples and are expected to grow to hundreds of thousands within a few years. For these databases to be of optimal use one must be able to quickly interrogate them to accurately determine the genetic distances among a set of samples. Being able to do so is challenging due to both biological (evolutionary diverse samples) and computational (petabytes of sequence data) issues. We evaluated seven measures of genetic distance, which were estimated from either k-mer profiles (Jaccard, Euclidean, Manhattan, Mash Jaccard, and Mash distances) or nucleotide sites (NUCmer and an extended multi-locus sequence typing (MLST) scheme). Finally, when analyzing empirical data (wholegenome sequence data from 18,997 Salmonella isolates) there are features (e.g., genomic, assembly, and contamination) that cause distances inferred from k-mer profiles, which treat absent data as informative, to fail to accurately capture the distance between samples when compared to distances inferred from differences in nucleotide sites. Thus, site-based distances, like NUCmer and extended MLST, are superior in performance, but accessing the computing resources necessary to perform them may be challenging when analyzing large databases.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic stability of foot-and-mouth disease virus during long-term infections in natural hosts

Foot-and-mouth disease (FMD) is a severe infection caused by a picornavirus that affects livestock and wildlife. Persistence in ruminants is a well-documented feature of Foot-andmouth disease virus (FMDV) pathogenesis and a major concern for disease control. Persistently infected animals harbor virus for extended periods, providing a unique opportunity to study within-host virus evolution. This study investigated the genetic dynamics of FMDV during persistent infections of naturally infected Asian buffalo. Using next-generation sequencing (NGS) we obtained 21 near complete FMDV genome sequences from 12 sub-clinically infected buffalo over a period of one year. Four animals yielded only one virus isolate and one yielded two isolates of different serotype suggesting a serial infection. Seven persistently infected animals yielded more than one virus of the same serotype showing a longterm intra-host viral genetic divergence at the consensus level of less than 2.5%. Quasi-species analysis showed few nucleotide variants and non-synonymous substitutions of progeny virus despite intra-host persistence of up to 152 days. Phylogenetic analyses of serotype Asia-1 VP1 sequences clustered all viruses from persistent animals with Group VII viruses circulating in Pakistan in 2011, but distinct from those circulating on 2008–2009. Furthermore, signature amino acid (aa) substitutions were found in the antigenically relevant VP1 of persistent viruses compared with viruses from 2008–2009. Intra-host purifying selective pressure was observed, with few codons in structural proteins undergoing positive selection. However, FMD persistent viruses did not show a clear pattern of antigenic selection. Our findings provide insight into the evolutionary dynamics of FMDV populations within naturally occurring subclinical and persistent infections that may have implications to vaccination strategies in the region.

60 APPLIED LIFE SCIENCES↗

Fungal Pretreatment and Enzymatic Hydrolysis of Genetically-Modified Populus trichocarpa

Fungal pretreatment of Populus trichocarpa wood genetically modified to reduce lignin and alter lignin chemistry is investigated for its effectiveness as an alternative to common pretreatment methods. The goal of this work is to improve biomass utilization for biofuel and biochemical applications by increasing sugar release. Sugar release after enzymatic hydrolysis was measured after various biomass pretreatments (including wood-rot fungus, hot water, and dilute acid). In the wildtype, and in constructs downregulated in PAL, 4CL, and C3H, the fungal pretreatment resulted in substantial improvements in sugar yields, up to 2.4-fold increase in glucose yield and 6-fold increase in xylose yield after enzymatic hydrolysis compared to the unpretreated control. However, the effects of fungal pretreatment were inconsistent, and in genetic lines down-regulated in 4CL, CCoAOMT, CAld5H, and C3H, fungal pretreatment yielded similar or decreased sugar release after enzymatic hydrolysis.

59 BASIC BIOLOGICAL SCIENCES↗

Programmed Nanomaterial Assemblies in Large Scales: Applications of Synthetic and Genetically- Engineered Peptides to Bridge Nano-Assemblies and Macro-Assemblies

Work is reported in these areas: Large-scale & reconfigurable 3D structures of precise nanoparticle assemblies in self-assembled collagen peptide grids; Binary QD-Au NP 3D superlattices assembled with collagen-like peptides and energy transfer between QD and Au NP in 3D peptide frameworks; Catalytic peptides discovered by new hydrogel-based combinatorial phage display approach and their enzyme-mimicking 2D assembly; New autonomous motors of metal-organic frameworks (MOFs) powered by reorganization of self-assembled peptides at interfaces; Biomimetic assembly of proteins into microcapsules on oil-in-water droplets with structural reinforcement via biomolecular recognition-based cross-linking of surface peptides; and Biomimetic fabrication of strong freestanding genetically-engineered collagen peptide films reinforced by quantum dot joints. We gained the broad knowledge about biomimetic material assembly from nanoscale to microscale ranges by coassembling peptides and NPs via biomolecular recognition. We discovered: Genetically-engineered collagen-like peptides can be self-assembled with Au NPs to generate 3D superlattices in large volumes (> μm{sup 3}); The assembly of the 3D peptide-Au NP superstructures is dynamic and the interparticle distance changes with assembly time as the reconfiguration of structure is triggered by pH change; QDs/NPs can be assembled with the peptide frameworks to generate 3D superlattices and these QDs/NPs can be electronically coupled for the efficient energy transfer; The controlled assembly of catalytic peptides mimicking the catalytic pocket of enzymes can catalyze chemical reactions with high selectivity; and, For the bacteria-mimicking swimmer fabrication, peptide-MOF superlattices can power translational and propellant motions by the reconfiguration of peptide assembly at the MOF-liquid interface.

36 MATERIALS SCIENCE↗

Ternary alloy material prediction using genetic algorithm and cluster expansion

This thesis summarizes our study on the crystal structures prediction of Fe-V-Si system using genetic algorithm and cluster expansion. Our goal is to explore and look for new stable compounds. We started from the current ten known experimental phases, and calculated formation energies of those compounds using density functional theory (DFT) package, namely, VASP. The convex hull was generated based on the DFT calculations of the experimental known phases. Then we did random search on some metal rich (Fe and V) compositions and found that the lowest energy structures were body centered cube (bcc) underlying lattice, under which we did our computational systematic searches using genetic algorithm and cluster expansion. Among hundreds of the searched compositions, thirteen were selected and DFT formation energies were obtained by VASP. The stability checking of those thirteen compounds was done in reference to the experimental convex hull. We found that the composition, 24-8-16, i.e., Fe 3 VSi 2 is a new stable phase and it can be very inspiring to the future experiments.

36 MATERIALS SCIENCE↗