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GBOpt: Grain boundary structure optimization using Monte Carlo and evolutionary algorithms

Polycrystalline materials are made of many small crystals separated by grain boundaries (GBs), whose atomic structure strongly influences material properties. Because the structure of a GB determines its properties, the optimal structure must be known in order to determine those impacts. There are many ways of placing atoms in the GB region, but the optimal structure is defined as the one that gives the lowest value of a target property (typically energy). GB structure optimization has been successfully demonstrated using stochastic and evolutionary methods, but no reusable, community-maintained open-source workflow has been developed. GBOpt (Grain Boundary Optimization) is an open-source Python package that creates that workflow, where we have presently implemented two approaches: Markov Chain Monte Carlo, and genetic algorithm based on elite selection. We demonstrate this capability by successfully reproducing the known optimal structures of a specific GB in two materials, and point interested readers to the GitHub repository for additional examples, including optimization for different properties. Both of the implemented approaches recovered the known structures, with the genetic algorithm approach finding the optimal structure faster on average.

99 - GENERAL AND MISCELLANEOUS

Patterns of genomic variation reveal a single evolutionary origin of the wild allotetraploid Mimulus sookensis

Abstract Polyploidy occurs across the tree of life and is especially common in plants. Because newly formed cytotypes are often incompatible with their progenitors, polyploidy is also said to trigger “instantaneous” speciation. If a polyploid can self-fertilize or reproduce asexually, it is even possible for one individual to produce an entirely new lineage, but how often this scenario occurs is unclear. Here, we investigate the evolutionary history of the wild allotetraploid Mimulus sookensis, which was formed through hybridization between self-compatible, diploid species in the Mimulus guttatus complex. We generate a chromosome-scale reference assembly for M. sookensis and define its distinct subgenomes. Despite previous reports suggesting multiple origins of this highly selfing polyploid, we discover patterns of population genomic variation that provide unambiguous support for a single origin. One M. sookensis subgenome is clearly derived from the selfer Mimulus nasutus, which organellar variation suggests is the maternal progenitor. The ancestor of the other subgenome is less certain, but it shares variation with both Mimulus decorus and M. guttatus, two outcrossing diploids with geographic ranges that overlap broadly with M. sookensis. This study establishes M. sookensis as an example of instantaneous speciation, likely facilitated by the polyploid’s predisposition to self-fertilize.

Environmental Sciences & Ecology

Evolutionary conservation of the presumptive neural plate markers AmphiSox1/2/3 and AmphiNeurogenin in the invertebrate chordate amphioxus

Amphioxus, as the closest living invertebrate relative of the vertebrates, can give insights into the evolutionary origin of the vertebrate body plan. Therefore, to investigate the evolution of genetic mechanisms for establishing and patterning the neuroectoderm, we cloned and determined the embryonic expression of two amphioxus transcription factors, AmphiSox1/2/3 and AmphiNeurogenin. These genes are the earliest known markers for presumptive neuroectoderm in amphioxus. By the early neurula stage, AmphiNeurogenin expression becomes restricted to two bilateral columns of segmentally arranged neural plate cells, which probably include precursors of motor neurons. This is the earliest indication of segmentation in the amphioxus nerve cord. Later, expression extends to dorsal cells in the nerve cord, which may include precursors of sensory neurons. By the midneurula, AmphiSox1/2/3 expression becomes limited to the dorsal part of the forming neural tube. These patterns resemble those of their vertebrate and Drosophila homologs. Taken together with the evolutionarily conserved expression of the dorsoventral patterning genes, BMP2/4 and chordin, in nonneural and neural ectoderm, respectively, of chordates and Drosophila, our results are consistent with the evolution of the chordate dorsal nerve cord and the insect ventral nerve cord from a longitudinal nerve cord in a common bilaterian ancestor. However, AmphiSox1/2/3 differs from its vertebrate homologs in not being expressed outside the CNS, suggesting that additional roles for this gene have evolved in connection with gene duplication in the vertebrate lineage. In contrast, expression in the midgut of AmphiNeurogenin together with the gene encoding the insulin-like peptide suggests that amphioxus may have homologs of vertebrate pancreatic islet cells, which express neurogenin3. In addition, AmphiNeurogenin, like its vertebrate and Drosophila homologs, is expressed in apparent precursors of epidermal chemosensory and possibly mechanosensory cells, suggesting a common origin for protostome and deuterostome epidermal sensory cells in the ancestral bilaterian. Copyright 2000 Academic Press.

NASA Discipline Evolutionary Biology

Evolutionary design of corrugated horn antennas

An evolutionary progranirnitzg (EP) algorithm is used to optimize pattern of a corrugated circularhorn subject to various constraints on return loss and antenna beamwidth and pattern circularity and low crosspolarization. The EP algorithm uses a Gaussian mutation operator. Examples on design synthesis of a 45 section corrugated horn, with a total of 90 optimization parameters, are presented. The results show excellent and efficient optimization of the desired horn parameters.

optimization corrugated horn antennas evolutionary

Evolutionary computing for the design search and optimization of space vehicle power subsystems

Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment.

evolutionary computing genetic algorithms optimiza

Evolutionary computing for the design search and optimization of space vehicle power subsystems

Evolutionary computing has proven to be a straightforward and robust approach for optimizing a wide range of difficult analysis and design problems. This paper discusses the application of these techniques to an existing space vehicle power subsystem resource and performance analysis simulation in a parallel processing environment. Out preliminary results demonstrate that this approach has the potential to improve the space system trade study process by allowing engineers to statistically weight subsystem goals of mass, cost and performance then automatically size power elements based on anticipated performance of the subsystem rather than on worst-case estimates.

power

Design and Optimization of Low-thrust Orbit Transfers Using Q-law and Evolutionary Algorithms

Future space missions will depend more on low-thrust propulsion (such as ion engines) thanks to its high specific impulse. Yet, the design of low-thrust trajectories is complex and challenging. Third-body perturbations often dominate the thrust, and a significant change to the orbit requires a long duration of thrust. In order to guide the early design phases, we have developed an efficient and efficacious method to obtain approximate propellant and flight-time requirements (i.e., the Pareto front) for orbit transfers. A search for the Pareto-optimal trajectories is done in two levels: optimal thrust angles and locations are determined by Q-law, while the Q-law is optimized with two evolutionary algorithms: a genetic algorithm and a simulated-annealing-related algorithm. The examples considered are several types of orbit transfers around the Earth and the asteroid Vesta.

low-thrust orbit transfer

Tuning of MEMS Devices using Evolutionary Computation and Open-loop Frequency Response

We propose a tuning method for MEMS gyroscopes based on evolutionary computation that has the capacity to efficiently increase the sensitivity of MEMS gyroscopes through tuning and, furthermore, to find the optimally tuned configuration for this state of increased sensitivity. The tuning method was tested for the second generation JPL/Boeing Post-resonator MEMS gyroscope using the measurement of the frequency response of the MEMS device in open-loop operation.

evolvable hardware

Optimizing Grain Boundary Structures with LAMMPS Using Evolutionary Algorithms

Grain boundary structure optimization is an important part of materials modeling. Current methods for grain boundary structure optimization involve inefficient, time-consuming processes that do not fully explore the interface parameter space. Evolutionary algorithms have recently been demonstrated to be effective at determining both stable and metastable grain boundary interface structures. In this work, we demonstrate the use of GBOpt, a grain boundary structure optimization software designed to use the Large-scale Atomic/Molecular Massively Parallel Simulation (LAMMPS) software to efficiently determine grain boundary structures. We demonstrate that a only a few manipulations, namely atom insertion, atom removal, and relative grain displacement, are sufficient to explore much of the grain boundary structure parameter space. The efficacy of this approach is demonstrated on an FCC Ni system, and a BCC Fe system. The computational cost is compared against the gamma-surface sampling approach to demonstrate performance improvement.

Evolutionary algorithms

Comparative transcriptomics of CAZy enzymes in white- and brown-rot agaricomycetes: Evolutionary insights into lignocellulose degradation and the relevance of GH16 glycoside hydrolase functional divergence

White-rot and brown-rot fungi (WRF and BRF, respectively) decompose lignocellulose, the main structural component of plant biomass, through distinct mechanisms. This study examines the transcriptomic responses of three WRF species (Pleurotus ostreatus, Phanerochaete chrysosporium, and Heterobasidion irregulare) and two BRF species (Fomitopsis schrenkii and Rhodonia placenta) grown on poplar wood (W) and glucose (G) as sole carbon sources. RNA-seq analysis revealed upregulation of carbohydrate-active enzymes (CAZymes) linked to lignocellulose degradation. WRF displayed a broader enzymatic repertoire, whereas BRF employed a more selective approach. Among these responses, GH16 glycoside hydrolases were consistently upregulated across all species, including BRF. Since GH16 enzymes are involved in both plant hemicellulose modification and cell wall remodeling, their wood-induced expression may reflect multiple processes rather than a single conserved wood-decay mechanism. Structural and phylogenetic analyses revealed species-specific divergence, consistent with potential functional specialization. These findings broaden our understanding of fungal enzymatic strategies and highlight GH16 enzymes as candidates for further study. Beyond the immediate context of wood decay, this work has broader implications for fungal ecology, evolutionary biology, and biotechnological applications such as biomass conversion and sustainable bioenergy.

Fungal ecological strategies

Single nucleotide variants drive evolutionary phage-host arms race in anaerobic carbon dioxide-converting microbiome

Microbial bioconversions are shaped by environmental perturbations and the adaptation of resident microbiomes. Prokaryotes coexist with bacteriophages, yet their coevolutionary trajectories remain underexplored. Here, we investigate the effects of a cultivation vessel leak on an anaerobic consortium performing carbon dioxide reduction. Using time-series shotgun metagenomic sequencing, we reconstruct microbial and viral genomes to track community shifts. We further apply single-nucleotide variant profiling and CRISPR array analysis to monitor viral microdiversity and host defense mechanisms. After bioaugmentation restores bioconversion efficiency, the consortium undergoes pronounced restructuring, with new dominant taxa emerging from the rare biosphere. We identify patterns consistent with phage predation selectively removing certain species, while others exhibit resilience to infection. This shift aligns with a widespread viral outbreak and a transient increased frequency of single nucleotide variants in bacterial CRISPR–Cas defense genes. Expansion of CRISPR spacers further supports that CRISPR-mediated processes influence microbial resilience. Concurrently, phages infecting resilient hosts exhibited adaptive evolution, marked by high genetic heterogeneity. Selective pressure varies across their genomes, targeting infectivity genes and protospacer-adjacent motifs. These findings highlight a dynamic evolutionary arms race driven by the selection of beneficial genetic variants, providing a mechanistic framework for multi-omics investigations, and informing biotechnological applications, including phage-based microbiome manipulation.

Ghiotto, G

Comparative genomic analysis of thermophilic fungi reveals convergent evolutionary adaptations and gene losses

Thermophily is a trait scattered across the fungal tree of life, with its highest prevalence within three fungal families (Chaetomiaceae, Thermoascaceae, and Trichocomaceae), as well as some members of the phylum Mucoromycota. We examined 37 thermophilic and thermotolerant species and 42 mesophilic species for this study and identified thermophily as the ancestral state of all three prominent families of thermophilic fungi. Thermophilic fungal genomes were found to encode various thermostable enzymes, including carbohydrate-active enzymes such as endoxylanases, which are useful for many industrial applications. At the same time, the overall gene counts, especially in gene families responsible for microbial defense such as secondary metabolism, are reduced in thermophiles compared to mesophiles. We also found a reduction in the core genome size of thermophiles in both the Chaetomiaceae family and the Eurotiomycetes class. The Gene Ontology terms lost in thermophilic fungi include primary metabolism, transporters, UV response, and O-methyltransferases. Comparative genomics analysis also revealed higher GC content in the third base of codons (GC3) and a lower effective number of codons in fungal thermophiles than in both thermotolerant and mesophilic fungi. Furthermore, using the Support Vector Machine classifier, we identified several Pfam domains capable of discriminating between genomes of thermophiles and mesophiles with 94% accuracy. Using AlphaFold2 to predict protein structures of endoxylanases (GH10), we built a similarity network based on the structures. We found that the number of disulfide bonds appears important for protein structure, and the network clusters based on protein structures correlate with the optimal activity temperature. Thus, comparative genomics offers new insights into the biology, adaptation, and evolutionary history of thermophilic fungi while providing a parts list for bioengineering applications.

59 BASIC BIOLOGICAL SCIENCES

OrthoPhyl—streamlining large-scale, orthology-based phylogenomic studies of bacteria at broad evolutionary scales

Abstract There are a staggering number of publicly available bacterial genome sequences (at writing, 2.0 million assemblies in NCBI's GenBank alone), and the deposition rate continues to increase. This wealth of data begs for phylogenetic analyses to place these sequences within an evolutionary context. A phylogenetic placement not only aids in taxonomic classification but informs the evolution of novel phenotypes, targets of selection, and horizontal gene transfer. Building trees from multi-gene codon alignments is a laborious task that requires bioinformatic expertise, rigorous curation of orthologs, and heavy computation. Compounding the problem is the lack of tools that can streamline these processes for building trees from large-scale genomic data. Here we present OrthoPhyl, which takes bacterial genome assemblies and reconstructs trees from whole genome codon alignments. The analysis pipeline can analyze an arbitrarily large number of input genomes (>1200 tested here) by identifying a diversity-spanning subset of assemblies and using these genomes to build gene models to infer orthologs in the full dataset. To illustrate the versatility of OrthoPhyl, we show three use cases: E. coli/Shigella, Brucella/Ochrobactrum and the order Rickettsiales. We compare trees generated with OrthoPhyl to trees generated with kSNP3 and GToTree along with published trees using alternative methods. We show that OrthoPhyl trees are consistent with other methods while incorporating more data, allowing for greater numbers of input genomes, and more flexibility of analysis.

59 BASIC BIOLOGICAL SCIENCES

Evolutionary and functional relationships between plant and microbial C 1 metabolism in terrestrial ecosystems

One-carbon (C 1 ) metabolism, centered on the universal methyl donor S-adenosyl methionine (SAM), plays critical roles in biosynthesis, redox regulation, and stress responses across plants and microbes. A recently proposed photosynthetic C 1 pathway links SAM methyl groups directly to RuBisCO-mediated CO 2 assimilation and integrates with nitrogen and sulfur metabolism. Light-dependent SAM synthesis may regulate the methylation of biopolymers and specialized metabolites and help mitigate photorespiratory stress under elevated temperature and drought. Phylogenetic analysis of two core enzymes suggests evolutionary continuity from methylotrophic microbes to land plants, supporting microbial origins via endosymbiotic gene transfer. Beyond intracellular roles, C 1 metabolism drives biosphere–atmosphere exchange via gases such as methane, methanol, formic acid, and formaldehyde, and numerous specialized volatiles synthesized through SAM methylation. S-methylmethionine, a mobile C 1 metabolite, may mediate phloem transport of reduced sulfur, nitrogen, and methyl groups, linking above- and belowground C 1 cycling in plants. Advances in real-time gas sensing now allow the high-frequency quantification of C 1 fluxes from leaves, stems, and soils, highlighting C 1 metabolism as a critical and underrecognized component of terrestrial carbon and nutrient cycling. Given its microbial ancestry and the production of diverse volatile biosignatures, C 1 metabolism may also offer unique insights into life's origins and biosignature detection on exoplanets.

54 ENVIRONMENTAL SCIENCES