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DOE OSTI2026

Pyrodictium abyssi AbpX reveals a calcium-responsive family of microbial biomatrix proteins that form thermostable hydrogels

Evolutionary pressure on microbial communities propagating under extreme environmental conditions often results in unique structural adaptations to promote cell survival. In this work, we report an investigation of AbpX, a biomatrix protein identified in cultures of the hyperthermophilic archaeon Pyrodictium abyssi. Under ex vivo and in vitro conditions, AbpX assembles into a paracrystalline lattice composed of semiflexible fibrils. CryoEM analysis of recombinant AbpX fibrils reveals that the precursor protein polymerizes through donor strand complementation (DSC), a process previously reported for chaperone-usher fimbriae in Gram-negative bacteria. Unlike the latter DSC protein polymers, AbpX undergoes chaperone-free polymerization in the presence of calcium ions, which are sequestered at the donor strand-acceptor groove interface between protomers in the fibril. Using a combination of cryoEM and crystallographic information, a structural model is proposed for the AbpX lattice that provides insight into its potential role in biofilm formation. These findings suggest that calcium ion coordination may contribute to fibril assembly and preorganize fibrils for incorporation into the protein lattice. Bioinformatic analysis indicates that AbpX exemplifies a distinct and broadly distributed clade of calcium ion responsive biomatrix proteins within the TasA superfamily that can be fabricated into hydrogel biomaterials in vitro under environmentally benign conditions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Divergent trait controls on soluble sugars and starch underlie global strategies of tree carbohydrate storage

Nonstructural carbohydrate (NSC) stores buffer tree metabolism, osmotic regulation, and defense, thereby mediating tolerance and survival under climate extremes. Yet, the functional and evolutionary determinants of interspecific variation in NSC remain elusive, limiting understanding and prediction of forest carbon allocation and mortality under global change. Here, we present a cross-species synthesis of NSC concentrations across multiple organs for 281 woody species from 102 mixed forest communities worldwide, where we quantified species-specific deviations from community means to disentangle intrinsic trait effects from environmental and methodological variation. We found phylogenetic signals in NSC deviations, with coniferous gymnosperms and evergreen species consistently maintaining lower stem soluble sugars and starch concentrations than co-occurring angiosperms and deciduous species, respectively. A global pattern emerged where greater stomatal sensitivity to leaf water potential was associated with declines in the relative concentrations of both sugars and starch. In contrast, xylem hydraulic safety traits showed weak and organ-dependent relationships with NSC concentrations. Sugars increased with photosynthetic capacity and declined with wood density, whereas starch showed the reverse pattern, which aligned with the distinct functional-metabolic roles of sugars and starch. By integrating trait-based ecology with a community-centered framework, our study provides global evidence that stomatal regulation, photosynthetic capacity, specific leaf area, and wood density jointly govern interspecific NSC variation, through contrasting effects on sugars and starch. These are among the most broadly measured traits globally, thus the emergent carbohydrate–trait relationships can have broad applications toward understanding and predicting forest growth and survival under climate change.

tropic system↗

DOE OSTI2015

Crossover from quantum to classical transport

Understanding the crossover from quantum to classical transport phenomena has become of fundamental importance not only for technological applications due to the creation of sub-10nm transistors – an important building block of our modern life – but also for elucidating the role played by quantum mechanics in the evolutionary fitness of biological complexes. This article provides a basic introduction into the nature of charge and energy transport in the quantum and classical regimes. Here, it will identify the characteristic transport properties in both limits, and demonstrate how they can be connected through the loss of quantum mechanical coherence. I will identify the salient features of the crossover physics, and demonstrate their importance in opening new transport regimes and for understanding efficient and robust energy transport in biological complexes.

charge↗

DOE OSTI2026

Divergent Rickettsia species exhibit distinct mechanisms of actin-based motility

Many Rickettsia species undergo actin-based motility to promote cell-cell spread during infection. Rickettsial genomes often encode two motility effectors, RickA and Sca2, which in the spotted fever group I species, Rickettsia parkeri act by activating the host Arp2/3 complex and by mimicking eukaryotic formins, respectively. The function of RickA and Sca2 orthologs in the distantly related species Rickettsia bellii was unclear. We report that R. bellii RickA activates the host Arp2/3 complex but has no discernible role in bacterial motility. The R. bellii Sca2 ortholog, Sca2/6, nucleates and elongates actin with a flexible structure and an unusual actin monomer-binding motif in a mechanism distinct from formins or other microbial actin nucleators. R. bellii motility is solely correlated with Sca2/6 localization and, compared with R. parkeri motility, is slow and meandering, generating distinctly organized actin tails. The evolutionary flexibility in the mechanism and regulation of rickettsial actin-based motility suggests similar adaptability for other microbes.

Bacher, Meghan C↗

DOE OSTI2025

Genetic programming for the nuclear many-body problem: a guide

Genetic Programming (GP) is an evolutionary algorithm that generates computer programs, or mathematical expressions, to solve complex problems. In this Guide, we demonstrate how to use GP to develop surrogate models to mitigate the computational costs of modeling atomic nuclei with ever increasing complexity. The computational burden escalates when uncertainty quantification is pursued, or when observables must be globally computed for thousands of nuclei. By studying three models in which the mean field depends on the total particle density self-consistently, we show that by constructing reduced order models supported by GP one can speed up many-body computations by several orders of magnitude with a negligible loss in accuracy.

dimensionality reduction↗

DOE OSTI2026

Heavy dark matter in rapidly evolving massive stars

We study the impact of heavy dark matter (DM) captured in massive stars via scattering(s) with the star constituents. We focus on the first stars and use stellar evolution simulations to track down how DM capture evolves over time from the zero-age main sequence to the late metal-rich stages of stellar evolution. During the early hydrogen-helium-dominated phase, the capture process is well described by scattering with two targets. As a star evolves, metal production leads to the formation of a dense core surrounded by a lighter envelope. The core significantly enhances the capture of ultra-heavy DM; in this case, three distinct nuclear species are required to accurately describe multiple-scattering capture. We use the Eddington inversion method to obtain a realistic DM velocity distribution, better suited when the star is near the center of a halo, than the widely used Maxwell-Boltzmann distribution. We find that heavy DM would be able to thermalize and achieve capture-annihilation equilibrium within a massive star's lifetime for regions of the parameter space not excluded by direct detection. For non-annihilating DM, because of the high amount of targets available for capture and despite massive stars being short-lived, it would even be possible for DM to achieve self-gravitation and collapse to a black hole, which eventually could swallow the star from within before the expected end of the star's life, for non-excluded regions of the parameter space. Our results highlight the dependence of DM capture on the stellar evolutionary stage, composition, and halo location, demonstrating that accurate modeling of massive stars is essential for constraining heavy DM with primordial stellar populations.

dark matter theory↗

DOE OSTI2026

Experimental study of ECH pre-ionization on J-TEXT

An experimental study on electron cyclotron heating (ECH) pre-ionization has been conducted on J-TEXT in support of the joint experiment research for ITER plasma initiation. In this experiment, ECH power was injected to the vessel before the application of loop voltage ionize the neutral gas and form the initial plasma or so-called pre-plasma. The impact of several significant factors, such as magnetic field configuration, pre-fill gas pressure, ECH toroidal injection angle and ECH power on the evolution of pre-plasma are systematically studied, aiming to identify shared features, clarify their potential relationship and optimize the discharge parameters to generate a rather high pre-plasma density. By separating ECH power from the inductive start-up, the effect of pre-plasma on tokamak start-up can be observed. A dynamic magnetic configuration facilitates the transition of pre-plasma to tokamak plasma. To assess the influence of pre-plasma density on tokamak start-up, two kinds of magnetic field configurations are examined. While the effect of different pre-plasma densities on tokamak start-up is negligible, a significant difference is observed between pure ohmic start-up and start-up with pre-ionization. The studies presented here show evolutionary trends and threshold values needed to optimize ECH pre-ionization and also a feasible way to improve pre-plasma density and a configuration to stabilize pre-plasma for transition. Eventually, these results may contribute to multi-machine research and physics analysis that can assist ITER with its optimal preparation for first plasma operation.

ECH↗

DOE OSTI2025

Harnessing the power of gradient-based simulations for multi-objective optimization in particle accelerators

Abstract Particle accelerator operation requires simultaneous optimization of multiple objectives. Multi-objective optimization (MOO) is particularly challenging due to trade-offs between the objectives. Evolutionary algorithms, such as genetic algorithms (GAs), have been leveraged for many optimization problems, however, they do not apply to complex control problems by design. This paper demonstrates the power of differentiability for solving MOO problems in particle accelerators using a deep differentiable reinforcement learning (DDRL) algorithm. We compare the DDRL algorithm with model-free reinforcement learning (MFRL), GA, and Bayesian optimization (BO) for simultaneous optimization of heat load and trip rates in the continuous electron beam accelerator facility. The underlying problem enforces strict constraints on both individual states and actions as well as cumulative (global) constraints on energy requirements of the beam. Using historical accelerator data, we develop a physics-based surrogate model which is differentiable and allows for back-propagation of gradients. The results are evaluated in the form of a Pareto-front with two objectives. We show that the DDRL outperforms MFRL, BO, and GA on high dimensional problems.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

What are grana in chloroplasts of vascular plants good for?

All plants and green algae contain stacked grana thylakoid membranes in their chloroplasts, underscoring an evolutionary pressure to maintain this unique structural feature. In addition, numerous studies have demonstrated that particular lateral and vertical dimensions of grana facilitate the function, regulation and repair of the photosynthetic machinery responsible for energy conversion. In this review, we present an updated overview of our understanding concerning the structure of grana thylakoids, the forces that contribute to their formation and their architectural dynamics. After establishing the structural foundation, we continue by reviewing the implications of grana formation on light harvesting, electron transport and protein maintenance in the thylakoid membranes of vascular plants. Regarding light harvesting, we discuss the implications of grana formation on energy spillover, macromolecular crowding, lateral versus vertical excitation energy transfer, and state transition. With respect to electron transport, we summarize recent findings regarding the functional connectivity of spatially separated photosystems facilitated by grana formation through small mobile electron carriers. We also explore how the dynamic responses of grana architecture regulate electron transport. Finally, we address how grana formation contributes to the organization of protein repair and biogenesis within thylakoid membranes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Reference-free structural variant detection in microbiomes via long-read co-assembly graphs

Motivation: The study of bacterial genome dynamics is vital for understanding the mechanisms underlying microbial adaptation, growth, and their impact on host phenotype. Structural variants (SVs), genomic alterations of 50 base pairs or more, play a pivotal role in driving evolutionary processes and maintaining genomic heterogeneity within bacterial populations. While SV detection in isolate genomes is relatively straightforward, metagenomes present broader challenges due to the absence of clear reference genomes and the presence of mixed strains. In response, our proposed method rhea, forgoes reference genomes and metagenome-assembled genomes (MAGs) by encompassing all metagenomic samples in a series (time or other metric) into a single co-assembly graph. The log fold change in graph coverage between successive samples is then calculated to call SVs that are thriving or declining. Results: We show rhea to outperform existing methods for SV and horizontal gene transfer (HGT) detection in two simulated mock metagenomes, particularly as the simulated reads diverge from reference genomes and an increase in strain diversity is incorporated. We additionally demonstrate use cases for rhea on series metagenomic data of environmental and fermented food microbiomes to detect specific sequence alterations between successive time and temperature samples, suggesting host advantage. Our approach leverages previous work in assembly graph structural and coverage patterns to provide versatility in studying SVs across diverse and poorly characterized microbial communities for more comprehensive insights into microbial gene flux.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Inferring demographic and selective histories from population genomic data using a 2-step approach in species with coding-sparse genomes: an application to human data

Abstract The demographic history of a population, and the distribution of fitness effects (DFE) of newly arising mutations in functional genomic regions, are fundamental factors dictating both genetic variation and evolutionary trajectories. Although both demographic and DFE inference has been performed extensively in humans, these approaches have generally either been limited to simple demographic models involving a single population, or, where a complex population history has been inferred, without accounting for the potentially confounding effects of selection at linked sites. Taking advantage of the coding-sparse nature of the genome, we propose a 2-step approach in which coalescent simulations are first used to infer a complex multi-population demographic model, utilizing large non-functional regions that are likely free from the effects of background selection. We then use forward-in-time simulations to perform DFE inference in functional regions, conditional on the complex demography inferred and utilizing expected background selection effects in the estimation procedure. Throughout, recombination and mutation rate maps were used to account for the underlying empirical rate heterogeneity across the human genome. Importantly, within this framework it is possible to utilize and fit multiple aspects of the data, and this inference scheme represents a generalized approach for such large-scale inference in species with coding-sparse genomes.

Soni, Vivak (ORCID:0000000294969562)↗

DOE OSTI2024

Novel Toxin Biosynthetic Gene Cluster in Harmful Algal Bloom-Causing Heteroscytonema crispum : Insights into the Origins of Paralytic Shellfish Toxins

Caused by both eukaryotic dinoflagellates and prokaryotic cyanobacteria, harmful algal blooms are events of severe ecological, economic, and public health consequence, and their incidence has become more common of late. Despite coordinated research efforts to identify and characterize the genomes of harmful algal bloom-causing organisms, the genomic basis and evolutionary origins of paralytic shellfish toxins produced by harmful algal blooms remain at best incomplete. The paralytic shellfish toxin saxitoxin has an especially complex genomic architecture and enigmatic phylogenetic distribution, spanning dinoflagellates and multiple cyanobacterial genera. Using filtration and extraction techniques to target the desired cyanobacteria from nonaxenic culture, coupled with a combination of short- and long-read sequencing, we generated a reference-quality hybrid genome assembly for Heteroscytonema crispum UTEX LB 1556, a freshwater, paralytic shellfish toxin-producing cyanobacterium thought to have the largest known genome in its phylum. We report a complete, novel biosynthetic gene cluster for the paralytic shellfish toxin saxitoxin. Leveraging this biosynthetic gene cluster, we find support for the hypothesis that paralytic shellfish toxin production has appeared in divergent Cyanobacteria lineages through widespread and repeated horizontal gene transfer. This work demonstrates the utility of long-read sequencing and metagenomic assembly toward advancing our understanding of paralytic shellfish toxin biosynthetic gene cluster diversity and suggests a mechanism for the origin of paralytic shellfish toxin biosynthetic genes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Genome evolution and transcriptome plasticity is associated with adaptation to monocot and dicot plants in Colletotrichum fungi

Colletotrichum fungi infect a wide diversity of monocot and dicot hosts, causing diseases on almost all economically important plants worldwide. Colletotrichum is also a suitable model for studying gene family evolution on a fine scale to uncover events in the genome associated with biological changes. Here we present the genome sequences of 30 Colletotrichum species covering the diversity within the genus. Evolutionary analyses revealed that the Colletotrichum ancestor diverged in the late Cretaceous in parallel with the diversification of flowering plants. We provide evidence of independent host jumps from dicots to monocots during the evolution of Colletotrichum, coinciding with a progressive shrinking of the plant cell wall degradative arsenal and expansions in lineage-specific gene families. Comparative transcriptomics of 4 species adapted to different hosts revealed similarity in gene content but high diversity in the modulation of their transcription profiles on different plant substrates. Combining genomics and transcriptomics, we identified a set of core genes such as specific transcription factors, putatively involved in plant cell wall degradation. These results indicate that the ancestral Colletotrichum were associated with dicot plants and certain branches progressively adapted to different monocot hosts, reshaping the gene content and its regulation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Viral niche-partitioning: comparative genomics of giant viruses across environmental gradients in a high Arctic freshwater-saltwater lake

Giant viruses (GVs; Nucleocytoviricota) impact the biology and ecology of a wide range of eukaryotic hosts, with implications for global biogeochemical cycles. Here, we investigated GV niche separation in highly stratified Lake A at the northern coast of Ellesmere Island, Nunavut, Canada. This lake is composed of a layer of ice-covered freshwater that overlies saltwater derived from the ancient Arctic Ocean, and it therefore provides a broad gradient of environmental conditions and ecological habitats, each with a distinct protist community and rich assemblages of associated GVs. The upper layer (mixolimnion) had measurable light and oxygen, and contained diverse GVs linked to photosynthetic protists, indicating adaptation to surface biotic and abiotic conditions. In contrast, the saline lower layer (monimolimnion), lacking oxygen and light, hosted GVs associated with predicted heterotrophic protists, some of which are known for a predatory lifestyle, and with several viral genes suggesting adaptation to deep-water anaerobic conditions. Our observations underscore the coupling between physical and chemical gradients, microeukaryotes and their associated GVs in Lake A, and provide insight into the potential for GVs to directly and indirectly impact host metabolism. There were similarities between the genetic composition of GVs and the metabolic processes of their potential hosts, implying co-evolution and niche-adaptation within the lake habitats. Notably, we found a greater presence of viral rhodopsins in deeper water layers, suggesting an evolutionary relationship with potential hosts capable of supplementing their energetic needs to thrive in low energy, anoxic conditions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Treatment of antibiotic-manufacturing wastewater enriches for Aeromonas veronii, a zoonotic antibiotic-resistant emerging pathogen

Antibiotic-manufacturing wastewater treatment plants primarily target chemical pollutants, but their processes may select for antibiotic-resistant pathogens and antibiotic resistance genes. Leveraging the combined strengths of deep metagenomic sequencing, 16S rRNA gene sequencing, quantitative polymerase chain reaction, and bacterial culturing, we investigated bacterial communities and antibiotic resistomes across eleven treatment units in a full-scale antibiotic-manufacturing wastewater treatment plant processing wastewater from a β-lactam manufacturing facility. Both bacterial communities and antibiotic resistance gene compositions varied across the treatment units, but were associated. Certain antibiotic resistance gene persisted through treatment, either carried by identical bacterial species, or linked to mobile genetic elements in different species. Despite the satisfactory performance in chemical removal, this plant continuously enriched zoonotic antibiotic-resistant Aeromonas veronii (an emerging pathogen responsible for substantial economic losses in aquaculture and human health) from influent to effluent, probably due to prolonged β-lactam selection pressure and aquatic nature of A. veronii. This enrichment resulted in a significantly higher abundance of A. veronii than other aquatic samples worldwide. Furthermore, the closest evolutionary relative to the retrieved A. veronii was an isolate obtained from the stool of a local diarrhea patient. These findings highlighted a substantial public health risk posed by antibiotic-manufacturing wastewater treatment, underlining its potential role in enriching and disseminating zoonotic antibiotic-resistant pathogens. Beyond chemical monitoring, enhanced surveillance of antibiotic-resistant pathogens and antibiotic resistance genes is needed in effluent discharge standard for antibiotic-manufacturing wastewater treatment plants.

Wang, Xingshuo↗

DOE OSTI2024

Massive red spiral galaxies in SDSS-IV MaNGA survey

ABSTRACT Massive red spiral galaxies (MRSGs) are supposed to be the possible progenitors of lenticular galaxies (S0s). We select a large sample of MRSGs ($M_*\gt 10^{10.5}\rm {\rm M}_{\odot }$) from Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) DR17 using the g − r colour versus stellar mass diagram, along with control samples of blue spirals and S0s. Our main results are as follows: (1) After comparing the Sérsic index, concentration parameter, asymmetry parameter distribution, size–mass relation, and Σ1 (stellar mass surface density within the central 1 kpc)−mass relation, we find MRSGs are similar to S0s and have more compact and symmetric structures than blue spirals. MRSGs also resemble S0s in Dn4000, metallicity, Mgb/$\rm \left\langle Fe \right\rangle$, and V/σ radial profile. (2) By using MaNGA 2D spectra data, we separate the spatial regions into inner (R < 0.8Re) and outer (0.8 < R < 1.5Re) regions, and detect residual star formation in the outer regions of MRSGs. (3) When we select a sub-sample of MRSGs with NUV − r > 5, we find that they are completely star formation quenched in both inner and outer regions. Compared to optically selected MRSGs, NUV − r selected MRSGs appear to be more concentrated and have more massive dark matter haloes. The similarities between S0s and MRSGs suggest the possible evolutionary trend between MRSGs and S0s.

Astronomy & Astrophysics↗

DOE OSTI2024

Fate of supernova progenitors in massive binary systems

ABSTRACT How massive stars end their lives depends on the core mass, core angular momentum, and hydrogen envelopes at death. However, these key physical facets of stellar evolution can be severely affected by binary interactions. In turn, the effectiveness of binary interactions itself varies greatly depending on the initial conditions of the binaries, making the situation much more complex. We investigate systematically how binary interactions influence core–collapse progenitors and their fates. Binary evolution simulations are performed to survey the parameter space of supernova progenitors in solar metallicity binary systems and to delineate major evolutionary paths. We first study fixed binary mass ratios ($q=M_2/M_1$ = 0.5, 0.7, and 0.9) to elucidate the impacts of initial mass and initial separation on the outcomes, treating separately Type Ibc supernova, Type II supernova, accretion-induced collapse (AIC), rapidly rotating supernova (Ibc-R), black hole formation, and long gamma ray burst (long GRB). We then conduct 12 binary population synthesis model calculations, varying the initial condition distributions and binary evolution parameters, to estimate various supernova fractions. We obtain a Milky Way supernova rate $R_{\rm SN} = (1.78$–$2.47) \times 10^{-2} \, {\rm yr}^{-1}$ which is consistent with observations. We find the rates of AIC, Ibc-R, and long GRB to be $\sim 1/100$ the rate of regular supernovae. Our estimated long GRB rates are higher than the observed long GRB rate and close to the low luminosity GRB rate, although care must be taken considering our models are computed with solar metallicity. Furthering binary modelling and improving the inputs one by one will enable more detailed studies of these and other transients associated with massive stars.

Astronomy & Astrophysics↗

DOE OSTI2024

SDSS-IV MaNGA: stellar rotational support in disc galaxies versus central surface density and stellar population age

ABSTRACT We investigate how the stellar rotational support changes as a function of spatially resolved stellar population age ($D_n4000$) and relative central stellar surface density ($\Delta \Sigma _1$) for MaNGA isolated/central disc galaxies. We find that the galaxy rotational support indicator $\lambda _{R_\mathrm{e}}$ varies smoothly as a function of $\Delta \Sigma _1$ and $D_n4000$. $D_n4000$ versus $\Delta \Sigma _1$ follows a ‘J-shape’, with $\lambda _{R_\mathrm{e}}$ contributing to the scatters. In this ‘J-shaped’ pattern rotational support increases with central $D_n4000$ when $\Delta \Sigma _1$ is low but decreases with $\Delta \Sigma _1$ when $\Delta \Sigma _1$ is high. Restricting attention to low-$\Delta \Sigma _1$ (i.e. large-radius) galaxies, we suggest that the trend of increasing rotational support with $D_n4000$ for these objects is produced by a mix of two different processes, a primary trend characterized by growth in $\lambda _{R_\mathrm{e}}$ along with mass through gas accretion, on top of which disturbance episodes are overlaid, which reduce rotational support and trigger increased star formation. An additional finding is that star-forming galaxies with low $\Delta \Sigma _1$ have relatively larger radii than galaxies with higher $\Delta \Sigma _1$ at fixed stellar mass. Assuming that these relative radii rankings are preserved while galaxies are star forming then implies clear evolutionary paths in central $D_n4000$ versus $\Delta \Sigma _1$. The paper closes with comments on the implications that these paths have for the evolution of pseudo-bulges versus classical bulges. The utility of using $\rm D_n4000$–$\Delta \Sigma _1$ to study $\lambda _{R_\mathrm{e}}$ reinforces the notion that galaxy kinematics correlate both with structure and with stellar-population state, and indicates the importance of a multidimensional description for understanding bulge and galaxy evolution.

Wang, Xiaohan (ORCID:0009000283121002)↗