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At least 199 records · Page 11

Novel genetic risk factors influence progression of islet autoimmunity to type 1 diabetes

Type 1 diabetes arises from the autoimmune destruction of insulin-producing beta-cells of the pancreas, resulting in dependence on exogenously administered insulin to maintain glucose homeostasis. In this study, our aim was to identify genetic risk factors that contribute to progression from islet autoimmunity to clinical type 1 diabetes. We analyzed 6.8 million variants derived from whole genome sequencing of 160 islet autoantibody positive subjects, including 87 who had progressed to type 1 diabetes. The Cox proportional-hazard model for survival analysis was used to identify genetic variants associated with progression. We identified one novel region, 20p12.1 (TASP1; genome-wide P < 5 × 10 –8 ) and three regions, 1q21.3 (MRPS21–PRPF3), 2p25.2 (NRIR), 3q22.1 (COL6A6), with suggestive evidence of association (P < 8.5 × 10 –8 ) with progression from islet autoimmunity to type 1 diabetes. Once islet autoimmunity is initiated, functional mapping identified two critical pathways, response to viral infections and interferon signaling, as contributing to disease progression. These results provide evidence that genetic pathways involved in progression from islet autoimmunity differ from those pathways identified once disease has been established. These results support the need for further investigation of genetic risk factors that modulate initiation and progression of subclinical disease to inform efforts in development of novel strategies for prediction and intervention of type 1 diabetes.

59 BASIC BIOLOGICAL SCIENCES↗

High-throughput mapping of the phage resistance landscape in E. coli

Bacteriophages (phages) are critical players in the dynamics and function of microbial communities and drive processes as diverse as global biogeochemical cycles and human health. Phages tend to be predators finely tuned to attack specific hosts, even down to the strain level, which in turn defend themselves using an array of mechanisms. However, to date, efforts to rapidly and comprehensively identify bacterial host factors important in phage infection and resistance have yet to be fully realized. Here, we globally map the host genetic determinants involved in resistance to 14 phylogenetically diverse double-stranded DNA phages using two model Escherichia coli strains (K-12 and BL21) with known sequence divergence to demonstrate strain-specific differences. Using genome-wide loss-of-function and gain-of-function genetic technologies, we are able to confirm previously described phage receptors as well as uncover a number of previously unknown host factors that confer resistance to one or more of these phages. We uncover differences in resistance factors that strongly align with the susceptibility of K-12 and BL21 to specific phage. We also identify both phage specific mechanisms, such as the unexpected role of cyclic-di-GMP in host sensitivity to phage N4, and more generic defenses, such as the overproduction of colanic acid capsular polysaccharide that defends against a wide array of phages. Our results indicate that host responses to phages can occur via diverse cellular mechanisms. Our systematic and high-throughput genetic workflow to characterize phage-host interaction determinants can be extended to diverse bacteria to generate datasets that allow predictive models of how phage-mediated selection will shape bacterial phenotype and evolution. The results of this study and future efforts to map the phage resistance landscape will lead to new insights into the coevolution of hosts and their phage, which can ultimately be used to design better phage therapeutic treatments and tools for precision microbiome engineering.

59 BASIC BIOLOGICAL SCIENCES↗

Data from: "Ecophysiological variation in two provenances of Pinus flexilis seedlings across an elevation gradient from forest to alpine"

This archive contains data used to support conclusions drawn in “Ecophysiological variation in two provenances of Pinus flexilis seedlings across an elevation gradient from forest to alpine”, by Reinhardt et al., 2011. Data were collected over one summer season in plots within the Alpine Treeline Warming Experiment (ATWE), before climate manipulations began. The experiment was located on Niwot Ridge, in the Front Range of the Colorado Rocky Mountains. This data package includes five comma-separated-values (.csv) files, five Microsoft Excel (.xlsx) files, one .pdf file, and two types of geospatial files: keyhole markup language (.kml), and ESRI shapefiles (.shp). .csv files can be opened using any simple text-editing software (such as Notepad and TextEdit), R, and Microsoft Excel. .xlsx files can only be opened using Microsoft Excel. The .pdf file can be opened using Adobe Acrobat Reader or any other compatible file viewing software. The .kml file can be opened using Google Earth and Google Maps, and shapefiles can be opened using any software compatible with the file type, such as ESRI’s ArcGIS suite and QGIS.Data archived contain gas exchange and plant physiology measurements, non-structural carbohydrate data, among others. Geospatial files are also provided for additional locational context. The files and their contents in this data package are summarized under "Data Summary" in the included Data User's Guide. All files (excluding geospatial) are available in both Microsoft Excel and in .csv format, and are indicated in the Data Summary list as well.-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Climate change is predicted to cause upward shifts in forest tree distributions, which will require seedling recruitment beyond current forest boundaries. However, predicting the likelihood of successful plant establishment beyond current species’ ranges under changing climate is complicated by the interaction of genetic and environmental controls on seedling establishment. To determine how genetics and climate may interact to affect seedling establishment, we transplanted recently germinated seedlings from high- and low-elevation provenances (HI and LO, respectively) of Pinus flexilis in common gardens arrayed along an elevation and canopy gradient from subalpine forest into the alpine zone and examined differences in physiology and morphology between provenances and among sites. Plant dry mass, projected leaf area and shoot:root ratios were 12–40% greater in LO compared with HI seedlings at each elevation. There were no significant changes in these variables among sites except for decreased dry mass of LO seedlings in the alpine site. Photosynthesis, carbon balance (photosynthesis/respiration) and conductance increased >2× with elevation for both provenances, and were 35–77% greater in LO seedlings compared with HI seedlings. There were no differences in dark-adapted chlorophyll fluorescence (Fv/Fm) among sites or between provenances. Our results suggest that for P. flexilis seedlings, provenances selected for above-ground growth may outperform those selected for stress resistance in the absence of harsh climatic conditions, even well above the species’ range limits in the alpine zone. This indicates that forest genetics may be important to understanding and managing species’ range adjustments due to climate change.

54 ENVIRONMENTAL SCIENCES↗

Genome-Scale Transcription-Translation Mapping Reveals Features of Zymomonas mobilis Transcription Units and Promoters

Efforts to rationally engineer synthetic pathways in Zymomonas mobilis are impeded by a lack of knowledge and tools for predictable and quantitative programming of gene regulation at the transcriptional, posttranscriptional, and posttranslational levels. With the detailed functional characterization of the Z. mobilis genome presented in this work, we provide crucial knowledge for the development of synthetic genetic parts tailored to Z. mobilis . This information is vital as researchers continue to develop Z. mobilis for synthetic biology applications. Our methods and statistical analyses also provide ways to rapidly advance the understanding of poorly characterized bacteria via empirical data that enable the experimental validation of sequence-based prediction for genome characterization and annotation.

59 BASIC BIOLOGICAL SCIENCES↗

Identification and genetic characterization of mitochondrial citrate transporters in Aspergillus niger

Aspergillus niger is a major cell factory for citric acid production, and the process of citrate export from mitochondria to cytoplasm is predicted to be one of rate-limiting steps in citric acid accumulation. Currently, the mitochondrial citrate transporters (Ctps) in A. niger are not fully characterized. Here, six putative Ctp encoding genes ( ctpA to ctpF ) were identified based on their homology with a mitochondrial citrate transporter Sc Ctp1 from Saccharomyces cerevisiae . Disruption of individual ctpA to ctpF caused varying degrees of decline in citric acid accumulation at different fermentation stages, whereas a mutant strain S1696 with disruption of all six ctp s showed complete loss of citiric acid production. S1696 also exhibited delayed growth, reduced conidia formation, and decreased pigmentogenesis. Exogenous addition of citrate partially restored the conidia formation and pigmentogenesis in S1696 mutant. Reintroduction of individual ctp s ( ctpA to ctpF ) into S1696 at the amyA locus showed that ctpA , ctpB , and ctpD restored the citric acid titers to 88.5, 93.8, and 94.6% of the parent strain, respectively. Additionally, the formation of conidia and pigment production was partially restored after reintroduction of ctpA , ctpB , or ctpD . Overexpression of respective ctpA , ctpB , and ctpD in the parent strain resulted in increases in citric acid accumulation by 32.8, 19.3, and 24.2%, respectively. These results demonstrate that CtpA, CtpB, and CtpD play important roles in citric acid transport across the mitochondrial membrane and function in a redundant manner. Enhancement of citric acid transport process can serve as a target for boosting citric acid accumulation in A. niger .

Cao, Wei↗

Kinetic modeling of microbial growth, enzyme activity, and gene deletions: An integrated model of β-glucosidase function in Cellvibrio japonicus

Understanding the complex growth and metabolic dynamics in microorganisms requires advanced kinetic models containing both metabolic reactions and enzymatic regulation to predict phenotypic behaviors under different conditions and perturbations. Most current kinetic models lack gene expression dynamics and are separately calibrated to distinct media, which consequently makes them unable to account for genetic perturbations or multiple substrates. This challenge limits our ability to gain a comprehensive understanding of microbial processes towards advanced metabolic optimizations that are desired for many biotechnology applications. Here, we present an integrated computational and experimental approach for the development and optimization of mechanistic kinetic models for microbial growth and metabolic and enzymatic dynamics. Our approach integrates growth dynamics, gene expression, protein secretion, and gene-deletion phenotypes. We applied this methodology to build a dynamic model of the growth kinetics in batch culture of the bacterium Cellvibrio japonicus grown using either cellobiose or glucose media. The model parameters were inferred from an experimental data set using an evolutionary computation method. The resulting model was able to explain the growth dynamics of C. japonicus using either cellobiose or glucose media and was also able to accurately predict the metabolite concentrations in the wild-type strain as well as in β-glucosidase gene deletion mutant strains. We validated the model by correctly predicting the non-diauxic growth and metabolite consumptions of the wild-type strain in a mixed medium containing both cellobiose and glucose, made further predictions of mutant strains growth phenotypes when using cellobiose and glucose media, and demonstrated the utility of the model for designing industrially-useful strains. Importantly, the model is able to explain the role of the different β-glucosidases and their behavior under genetic perturbations. Here, this integrated approach can be extended to other metabolic pathways to produce mechanistic models for the comprehensive understanding of enzymatic functions in multiple substrates.

59 BASIC BIOLOGICAL SCIENCES↗

Designing efficient genetic code expansion in Bacillus subtilis to gain biological insights

Abstract Bacillus subtilis is a model gram-positive bacterium, commonly used to explore questions across bacterial cell biology and for industrial uses. To enable greater understanding and control of proteins in B. subtilis , here we report broad and efficient genetic code expansion in B. subtilis by incorporating 20 distinct non-standard amino acids within proteins using 3 different families of genetic code expansion systems and two choices of codons. We use these systems to achieve click-labelling, photo-crosslinking, and translational titration. These tools allow us to demonstrate differences between E. coli and B. subtilis stop codon suppression, validate a predicted protein-protein binding interface, and begin to interrogate properties underlying bacterial cytokinesis by precisely modulating cell division dynamics in vivo. We expect that the establishment of this simple and easily accessible chemical biology system in B. subtilis will help uncover an abundance of biological insights and aid genetic code expansion in other organisms.

59 BASIC BIOLOGICAL SCIENCES↗

Pressure-induced superconductivity in the hydrogen-rich pseudobinary CaB - H n compounds

Here, the crystal structures of CaB – Hn compounds with n = 1 – 12 in a pressure range of 50–300 GPa were studied using the genetic algorithm method and first-principles density-function theory calculations. Stable structures with stoichiometry of CaB H 6 and CaB H 7 were predicted in different pressure range. BH 4 , BH 5 , and BH 6 units were found to be the main motifs in these compounds. Moreover, metastable Imm2 CaB H 7 is dynamically stable above 180 GPa, with the formation of tetrahedral BH 4 unit surrounded by Ca atom and H 3 unit. Electron-phonon coupling (EPC) calculations reveal that the superconducting properties are closely related to the strong hydrogen-boron bonding of the BH 4 unit in Imm2, and T c can reach ~200 K at 200 GPa. As the major units, BH 4 , BH 5 , and BH 6 units exist in the Imm2, P 2 , and P2 1 /m phases of CaB H 7 at 300 GPa, respectively; the corresponding EPC parameter λ decreases with the increase of hydrogen content in CaB H 7 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Secure biosystems design in Saccharomyces cerevisiae establishes effective biocontainment strategies and mechanisms of escape

The widespread application of recombinant DNA and synthetic biology approaches for microbial metabolic engineering pursuits has motivated the development of biocontainment strategies, targeting safe and secure deployment of genetically modified microorganisms (GMMs). However, the design rules and mechanistic drivers governing biocontainment efficacy, as well as impacts of biocontainment upon microbial fitness, remain to be comprehensively evaluated, hindering predictive design and application of these strategies. We have developed a platform for high-resolution analysis of a transactivated kill switch in laboratory and industrial strains of Saccharomyces cerevisiae to assess modes of biocontainment escape and establish design rules for development of kill switch systems in diverse microbes. A camphor-regulated, RelE toxin system was systematically deployed to assess the impacts of differential kill switch copy number and ploidy in laboratory vs industrial strains. CRISPR-mediated integration of the biocontainment system at various loci revealed rapid escape events driven, in part, by mutations to both the Cam-transactivator (cam-TA) and RelE toxin. Genetic engineering enabled recapitulation of escape phenotypes, confirming mechanisms of escape and establishing structure-function relationships in the cam-TA system. Interestingly, genomic resequencing of escape mutants also revealed a series of off-target mutations, implicating additional modes of kill switch escape. Multi-copy integration of the kill switch system mitigated these effects by orders of magnitude, without compromising the biosynthetic capacity of the microbes, but proved insufficient to establish sustained biocontainment. The resultant data define a series of key design rules for next-generation biocontainment strategies and add to a growing foundational knowledge base targeting establishment of secure biosystems designs.

59 BASIC BIOLOGICAL SCIENCES↗

Theoretical search for possible Li–Ni–B crystal structures using an adaptive genetic algorithm

The structural diversity of rare-earth and transition metal borides indicates that alkali-transition metal borides (A-T-B) show tremendous promise in exhibiting a variety of crystal structures with different dimensionalities of T-B frameworks. On the other hand, the A-T-B ternary systems are severely underexplored because of the synthetic challenges associated with their preparation. Accurate and efficient computational predictions of low-energy stable and metastable phases can identify the optimal compositions of the hypothetical compounds in the A-T-B systems to guide the synthesis. As such, in this work, we have computationally discovered several new phases in the Li–Ni–B ternary system. The newly discovered LiNiB, Li 2 Ni 3 B, and Li 2 NiB phases expand the existing theoretical database, and the convex-hull surface of Li–Ni–B has been re-constructed. The lowest energy structure of the LiNiB compound has been found by an adaptive genetic algorithm with layered motif, which matches with the experimentally determined structure. According to our electrochemical calculations, LiNiB and another predicted layered Li 2 NiB compounds have great potential as anode materials for lithium batteries. The Li 2 Ni 3 B compound with the space group P4 3 32 was predicted to crystallize in a cubic structure composed of distorted octahedral units of BNi 6 , which is isostructural to two noncentrosymmetric superconductors Li 2 Pd 3 B and Li 2 Pt 3 B. While we were unable to experimentally confirm the Li 2 Ni 3 B compound utilizing the hydride synthetic route, attempts to synthesize this compound by alternate methods remain highly desirable, considering its potential superconducting properties.

36 MATERIALS SCIENCE↗

Symbolic regression development of empirical equations for diffusion in Lennard-Jones fluids

Symbolic regression (SR) with a multi-gene genetic program has been used to elucidate new empirical equations describing diffusion in Lennard-Jones (LJ) fluids. Some examples include equations to predict self-diffusion in pure LJ fluids and equations describing the finite-size correction for self-diffusion in binary LJ fluids. The performance of the SR-obtained equations was compared to that of both the existing empirical equations in the literature and to the results from artificial neural net (ANN) models recently reported. It is found that the SR equations have improved predictive performance in comparison to the existing empirical equations, even though employing a smaller number of adjustable parameters, but show an overall reduced performance in comparison to more extensive ANNs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pressured cytotoxic T cell epitope strength among SARS-CoV-2 variants correlates with COVID-19 severity

Heterogeneity in susceptibility among individuals to COVID-19 has been evident through the pandemic worldwide. Cytotoxic T lymphocyte (CTL) responses generated against pathogens in certain individuals are known to impose selection pressure on the pathogen, thus driving emergence of new variants. In this study, we probe the role played by host genetic heterogeneity in terms of HLA-genotypes in determining differential COVID-19 severity in patients. We use bioinformatic tools for CTL epitope prediction to identify epitopes under immune pressure. Using HLA-genotype data of COVID-19 patients from a local cohort, we observe that the recognition of pressured epitopes from the parent strain Wuhan-Hu-1 correlates with COVID-19 severity. We also identify and rank list HLA-alleles and epitopes that offer protectivity against severe disease in infected individuals. Finally, we shortlist a set of 6 pressured and protective epitopes that represent regions in the viral proteome that are under high immune pressure across SARS-CoV-2 variants. In conclusion, identification of such epitopes, defined by the distribution of HLA-genotypes among members of a population, could potentially aid in prediction of indigenous variants of SARS-CoV-2 and other pathogens.

60 APPLIED LIFE SCIENCES↗

Lower viral evolutionary pressure under stable versus fluctuating conditions in subzero Arctic brines

Climate change threatens Earth’s ice-based ecosystems which currently offer archives and eco-evolutionary experiments in the extreme. Arctic cryopeg brine (marine-derived, within permafrost) and sea ice brine, similar in subzero temperature and high salinity but different in temporal stability, are inhabited by microbes adapted to these extreme conditions. However, little is known about their viruses (community composition, diversity, interaction with hosts, or evolution) or how they might respond to geologically stable cryopeg versus fluctuating sea ice conditions. We used long- and short-read viromics and metatranscriptomics to study viruses in Arctic cryopeg brine, sea ice brine, and underlying seawater, recovering 11,088 vOTUs (~species-level taxonomic unit), a 4.4-fold increase of known viruses in these brines. More specifically, the long-read-powered viromes doubled the number of longer (≥25 kb) vOTUs generated and recovered more hypervariable regions by >5-fold compared to short-read viromes. Distribution assessment, by comparing to known viruses in public databases, supported that cryopeg brine viruses were of marine origin yet distinct from either sea ice brine or seawater viruses, while 94% of sea ice brine viruses were also present in seawater. A virus-encoded, ecologically important exopolysaccharide biosynthesis gene was identified, and many viruses (~half of metatranscriptome-inferred “active” vOTUs) were predicted as actively infecting the dominant microbial genera Marinobacter and Polaribacter in cryopeg and sea ice brines, respectively. Evolutionarily, microdiversity (intra-species genetic variations) analyses suggested that viruses within the stable cryopeg brine were under significantly lower evolutionary pressures than those in the fluctuating sea ice environment, while many sea ice brine virus-tail genes were under positive selection, indicating virus-host co-evolutionary arms races. Our results confirmed the benefits of long-read-powered viromics in understanding the environmental virosphere through significantly improved genomic recovery, expanding viral discovery and the potential for biological inference. Evidence of viruses actively infecting the dominant microbes in subzero brines and modulating host metabolism underscored the potential impact of viruses on these remote and underexplored extreme ecosystems. Microdiversity results shed light on different strategies viruses use to evolve and adapt when extreme conditions are stable versus fluctuating. Together, these findings verify the value of long-read-powered viromics and provide foundational data on viral evolution and virus-microbe interactions in Earth’s destabilized and rapidly disappearing cryosphere.

59 BASIC BIOLOGICAL SCIENCES↗

Evolutionary inverse design of defects at graphene 2D lateral interfaces

Grain boundaries (GBs) in two-dimensional (2D) materials often have a profound impact on various material properties from mechanical to optical to electronic, yet predicting all possible GB formations is a challenge. Here, we introduce a workflow based on an evolutionary algorithm for exploring possible GBs formed at a lateral 2D interface. In a departure from conventional genetic algorithm based structure optimization methods, we perform genetic operations in the near interface region that allow us to be computationally efficient. We benchmark our method using graphene, which is a well-studied 2D material with a wide range of point defects. An empirical potential was used as the surrogate of the evolutionary search. More than 11.5 × 106 structures in total were evaluated for 128 GB orientations, and for each orientation, the ten best structures are recorded. A subset of low energy GBs predicted by empirical potential based search was relaxed by first-principles calculations and used to validate the energetic rank order. With the validated formation energy, we rank-ordered the best 128 GB structures and performed a detailed statistical analysis of primitive rings to find the correlation between the ring distribution and the formation energy. We found that for low energy GBs (below 0.5eV/Å), Stone–Wales defects will dominate, while structures with a higher energy (0.5–1.1eV/Å) show an increasing population of heptagons and nine-membered rings to form seven-nine defect pairs. For structures with energy higher than 1.1eV/Å, the percentage of octagons and nine-membered rings increases, which indicates that these two types of rings are not energetically favorable. Our proposed methodology is broadly applicable to explore defective low dimensional materials and represents a powerful tool that enables a systematic search of GBs of lateral interfaces for 2D materials.

Zhang, Jianan↗

Borg extrachromosomal elements of methane-oxidizing archaea have conserved and expressed genetic repertoires

Borgs are huge extrachromosomal elements (ECE) of anaerobic methane-consuming “Candidatus Methanoperedens” archaea. Here, we used nanopore sequencing to validate published complete genomes curated from short reads and to reconstruct new genomes. 13 complete and four near-complete linear genomes share 40 genes that define a largely syntenous genome backbone. We use these conserved genes to identify new Borgs from peatland soil and to delineate Borg phylogeny, revealing two major clades. Remarkably, Borg genes encoding nanowire-like electron-transferring cytochromes and cell surface proteins are more highly expressed than those of host Methanoperedens, indicating that Borgs augment the Methanoperedens activity in situ. We reconstructed the first complete 4.00 Mbp genome for a Methanoperedens that is inferred to be a Borg host and predicted its methylation motifs, which differ from pervasive TC and CC methylation motifs of the Borgs. Thus, methylation may enable Methanoperedens to distinguish their genomes from those of Borgs. Very high Borg to Methanoperedens ratios and structural predictions suggest that Borgs may be capable of encapsulation. The findings clearly define Borgs as a distinct class of ECE with shared genomic signatures, establish their diversification from a common ancestor with genetic inheritance, and raise the possibility of periodic existence outside of host cells.

59 BASIC BIOLOGICAL SCIENCES↗

Overestimated prediction using polygenic prediction derived from summary statistics

When polygenic risk score (PRS) is derived from summary statistics, independence between discovery and test sets cannot be monitored. We compared two types of PRS studies derived from raw genetic data (denoted as rPRS) and the summary statistics for IGAP (sPRS). Two variables with the high heritability in UK Biobank, hypertension, and height, are used to derive an exemplary scale effect of PRS. sPRS without APOE is derived from International Genomics of Alzheimer’s Project (IGAP), which records ΔAUC and ΔR 2 of 0.051 ± 0.013 and 0.063 ± 0.015 for Alzheimer’s Disease Sequencing Project (ADSP) and 0.060 and 0.086 for Accelerating Medicine Partnership - Alzheimer’s Disease (AMP-AD). On UK Biobank, rPRS performances for hypertension assuming a similar size of discovery and test sets are 0.0036 ± 0.0027 (ΔAUC) and 0.0032 ± 0.0028 (ΔR 2 ). For height, ΔR 2 is 0.029 ± 0.0037. Considering the high heritability of hypertension and height of UK Biobank and sample size of UK Biobank, sPRS results from AD databases are inflated. Independence between discovery and test sets is a well-known basic requirement for PRS studies. However, a lot of PRS studies cannot follow such requirements because of impossible direct comparisons when using summary statistics. Thus, for sPRS, potential duplications should be carefully considered within the same ethnic group.

97 MATHEMATICS AND COMPUTING↗

Characterizing Integrase-Attachment Site Pairs: A Machine Learning Approach

Genomic islands (GIs) are mobile genetic elements that integrate into host genomes via self-encoded integrases at specific DNA sequences known as attachment (att) sites. The ability to predict the target att site from an integrase's protein sequence is a central challenge in genomics due to the sequence diversity of integrases and the subtlety of their DNA recognition motifs.

59 BASIC BIOLOGICAL SCIENCES↗

Genetic algorithm optimization of nuclear criticality experiment for reduction of intermediate-energy 239 Pu nuclear data uncertainties

Nuclear criticality experiments are conducted to investigate specific nuclear data important for safe handling and storage of fissile materials, reactor design and operation, and the validation of radiation transport codes. Incorrect or uncertain nuclear data can prohibitively impact operational safety limits, reactor licensing, and predictive simulation capability; therefore, integral measurements from criticality experiments are necessary and should be performed frequently. To maximize the impact of the integral measurements, it is important to consider experiment geometry, material selection, and component dimensions. When taking these considerations into account, the experiment design process becomes iterative and very time intensive. This work utilizes a genetic algorithm to efficiently explore potential nuclear criticality experiment designs for the Laboratory Directed Research & Development project PARADIGM (PARallel Approach of Differential and InteGral Measurements) at Los Alamos National Laboratory. In this paper, the building blocks of the genetic algorithm are discussed in detail, the genetic algorithm methodology is verified, and the genetic algorithm is used to produce three candidate experiment models for the final PARADIGM design. The three candidate models produced by the genetic algorithm consist of copper-reflected assemblies containing 14 repeating units of alumina, graphite, boron, and plutonium plates. Furthermore, in addition to the optimization results, final design considerations are also discussed for designs with a height and/or weight very close to or slightly above assembly machine operational limits.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗