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At least 667 records · Page 37

Phage-specific metabolic reprogramming of virocells

Ocean viruses are abundant and infect 20–40% of surface microbes. Infected cells, termed virocells, are thus a predominant microbial state. Yet, virocells and their ecosystem impacts are understudied, thus precluding their incorporation into ecosystem models. Here we investigated how unrelated bacterial viruses (phages) reprogram one host into contrasting virocells with different potential ecosystem footprints. We independently infected the marine Pseudoalteromonas bacterium with siphovirus PSA-HS2 and podovirus PSA-HP1. Time-resolved multi-omics unveiled drastically different metabolic reprogramming and resource requirements by each virocell, which were related to phage–host genomic complementarity and viral fitness. Namely, HS2 was more complementary to the host in nucleotides and amino acids, and fitter during infection than HP1. Functionally, HS2 virocells hardly differed from uninfected cells, with minimal host metabolism impacts. HS2 virocells repressed energy-consuming metabolisms, including motility and translation. Contrastingly, HP1 virocells substantially differed from uninfected cells. They repressed host transcription, responded to infection continuously, and drastically reprogrammed resource acquisition, central carbon and energy metabolisms. Ecologically, this work suggests that one cell, infected versus uninfected, can have immensely different metabolisms that affect the ecosystem differently. Finally, we relate phage–host genome complementarity, virocell metabolic reprogramming, and viral fitness in a conceptual model to guide incorporating viruses into ecosystem models.

Environmental Sciences & Ecology↗

Large-scale genome sequencing of mycorrhizal fungi provides insights into the early evolution of symbiotic traits

Mycorrhizal fungi are mutualists that play crucial roles in nutrient acquisition in terrestrial ecosystems. Mycorrhizal symbioses arose repeatedly across multiple lineages of Mucoromycotina, Ascomycota, and Basidiomycota. Considerable variation exists in the capacity of mycorrhizal fungi to acquire carbon from soil organic matter. Here, we present a combined analysis of 135 fungal genomes from 73 saprotrophic, endophytic and pathogenic species, and 62 mycorrhizal species, including 29 new mycorrhizal genomes. This study samples ecologically dominant fungal guilds for which there were previously no symbiotic genomes available, including ectomycorrhizal Russulales, Thelephorales and Cantharellales. Our analyses show that transitions from saprotrophy to symbiosis involve (1) widespread losses of degrading enzymes acting on lignin and cellulose, (2) co-option of genes present in saprotrophic ancestors to fulfill new symbiotic functions, (3) diversification of novel, lineage-specific symbiosis-induced genes, (4) proliferation of transposable elements and (5) divergent genetic innovations underlying the convergent origins of the ectomycorrhizal guild.

59 BASIC BIOLOGICAL SCIENCES↗

The learnability of Pauli noise

Recently, several quantum benchmarking algorithms have been developed to characterize noisy quantum gates on today’s quantum devices. A fundamental issue in benchmarking is that not everything about quantum noise is learnable due to the existence of gauge freedom, leaving open the question what information is learnable and what is not, which is unclear even for a single CNOT gate. Here we give a precise characterization of the learnability of Pauli noise channels attached to Clifford gates using graph theoretical tools. Our results reveal the optimality of cycle benchmarking in the sense that it can extract all learnable information about Pauli noise. We experimentally demonstrate noise characterization of IBM’s CNOT gate up to 2 unlearnable degrees of freedom, for which we obtain bounds using physical constraints. In addition, we show that an attempt to extract unlearnable information by ignoring state preparation noise yields unphysical estimates, which is used to lower bound the state preparation noise.

97 MATHEMATICS AND COMPUTING↗

A small core in Vesta inferred from Dawn’s observations

Vesta’s large-scale interior structure had previously been constrained primarily using the gravity and shape data from the Dawn mission. However, these data alone still allow a wide range of possibilities for the differentiation state of the body. The moment of inertia is arguably the most diagnostic parameter related to the radial density distribution of a planetary body, making it crucial for assessing the body’s state of internal differentiation. Determining the moment of inertia requires additional measurements of the amplitudes of small rotational motions, such as precession and nutation. Here we report an updated estimate of the moment of inertia of Vesta inferred from Dawn’s Doppler tracking via the Deep Space Network and onboard imaging data. The recovered value for Vesta’s normalized polar moment of inertia is $\overline{C}$/MR 2 = 0.4208 ± 0.0047 (where M is the mass of Vesta and R is the reference radius), which is only 6.6% lower than the homogeneous value of 0.4505. This value, combined with the gravity field and global shape, suggests that Vesta’s interior has limited density stratification beneath its howardite–eucrite–diogenite-dominated crust. We propose two possible origin scenarios that are consistent with the observed constraints. In the first scenario, Vesta’s interior did not undergo full differentiation due to late accretion. In the second scenario, Vesta originated as an impact remnant of a larger differentiated body re-accreted with non-chondritic bulk composition produced from a catastrophic impact. Vesta did not experience complete differentiation in either scenario, suggesting that its current state reflects a complex interplay between its accretion timing, thermal evolution, redistribution of 26 Al bearing melt and/or impact processes.

CNEOS 2014-01-08 bolide↗

The synthesis and characterization of an iron(VII) nitrido complex

Abstract Complexes of iron in high oxidation states are captivating research subjects due to their pivotal role as active intermediates in numerous catalytic processes. Structural and spectroscopic studies of well-defined model complexes often provide evidence of these intermediates. In addition to the fundamental molecular and electronic structure insights gained by these complexes, their reactivity also affects our understanding of catalytic reaction mechanisms for small molecule and bond-activation chemistry. Here, we report the synthesis, structural and spectroscopic characterization of a stable, octahedral Fe(VI) nitrido complex and an authenticated, unique Fe(VII) species, prepared by one-electron oxidation. The super-oxidized Fe(VII) nitride rearranges to an Fe(V) imide through an intramolecular amination mechanism and ligand exchange, which is characterized spectroscopically and computationally. This enables combined reactivity and stability studies on a single molecular system of a rare high-valent complex redox pair. Quantum chemical calculations complement the spectroscopic parameters and provide evidence for a diamagnetic ( S = 0) d 2 Fe(VI) and a genuine S = 1/2, d 1 Fe(VII) configuration of these super-oxidized nitrido complexes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Historical and Future Learning for the New Era of Multi-Terawatt Photovoltaics

Solar photovoltaics (PV) is entering a new era of multi-terawatt deployment, with 2 TW already in service and more than 75 TW predicted in many scenarios by 2050. This next era has been enabled by over five decades of cumulative advances in PV module cost reduction, performance and reliability. The current scale of deployment also introduces new needs, opportunities and challenges. In this Perspective we frame a path forwards based on learning, broadly defined as a combination of expansion of knowledge and advances through research and development, experience and collaboration. We discuss historical topics where learning has driven PV deployment until now, and emerging areas that are required to sustain high levels of future deployment. We expect progress to continue in terms of module price, performance and reliability, driven by advances in PV cell and module design, the emergence of tandem devices and increased focus on extending module lifetimes. Large-scale deployment also means large-scale sustainability and responsibility. We therefore posit that additional metrics, such as the impact on global CO2 emissions, resource consumption and design for reuse and recycling, will become increasingly important to the PV industry and provide opportunities for further learning.

14 SOLAR ENERGY↗

Bedrock weathering contributes to subsurface reactive nitrogen and nitrous oxide emissions

Atmospheric nitrous oxide contributes directly to global warming, yet models of the nitrogen cycle do not account for bedrock, the largest pool of terrestrial nitrogen, as a source of nitrous oxide. Although it is known that release rates of nitrogen from bedrock are large, there is an incomplete understanding of the connection between bedrock-hosted nitrogen and atmospheric nitrous oxide. Here, we quantify nitrogen fluxes and mass balances at a hillslope underlain by marine shale. We found that, at this site, bedrock weathering contributes 78% of the subsurface reactive nitrogen, while atmospheric sources (commonly regarded as the sole sources of reactive nitrogen in pristine environments) account for only the remaining 22%. About 56% of the total subsurface reactive nitrogen denitrifies, including 14% emitted as nitrous oxide. The remaining reactive nitrogen discharges in porewaters to a floodplain where additional denitrification probably occurs. We also found that the release of bedrock nitrogen occurs primarily within the zone of the seasonally fluctuating water table and suggest that the accumulation of nitrate in the vadose zone, often attributed to fertilization and soil leaching, may also include contributions from weathered nitrogen-rich bedrock. Our hillslope study suggests that, under oxygenated and moisture-rich conditions, weathering of deep, nitrogen-rich bedrock makes an important contribution to the nitrogen cycle.

58 GEOSCIENCES↗

Vertical and horizontal gene transfer shaped plant colonization and biomass degradation in the fungal genus Armillaria

The fungal genus Armillaria contains necrotrophic pathogens and some of the largest terrestrial organisms that cause tremendous losses in diverse ecosystems, yet how they evolved pathogenicity in a clade of dominantly non-pathogenic wood degraders remains elusive. Here we show that Armillaria species, in addition to gene duplications and de novo gene origins, acquired at least 1,025 genes via 124 horizontal gene transfer events, primarily from Ascomycota. Horizontal gene transfer might have affected plant biomass degrading and virulence abilities of Armillaria, and provides an explanation for their unusual, soft rot-like wood decay strategy. Furthermore, combined multi-species expression data revealed extensive regulation of horizontally acquired and wood-decay related genes, putative virulence factors and two novel conserved pathogenicity-induced small secreted proteins, which induced necrosis in planta. Overall, this study details how evolution knitted together horizontally and vertically inherited genes in complex adaptive traits of plant biomass degradation and pathogenicity in important fungal pathogens.

60 APPLIED LIFE SCIENCES↗

Multi-omics reveals nitrogen dynamics associated with soil microbial blooms during snowmelt

Snowmelt triggers a soil microbial bloom and crash that affects nitrogen (N) export in high-elevation watersheds. The mechanisms underlying these microbial dynamics are uncertain, making soil nitrogen processes difficult to predict as snowpack declines globally. Here, integration of genome-resolved metagenomics, metatranscriptomics and metabolomics in a high-elevation watershed revealed ecologically distinct soil microorganisms linked across the snowmelt time-period by their unique nitrogen cycling capacities. The molecular properties and transformations of dissolved organic N suggested that degradation or recycling of microbial biomass provided N for biosynthesis during the microbial bloom. Winter-adapted Bradyrhizobia spp. oxidized amino acids anaerobically and had the highest gene expression for denitrification during the microbial bloom. A pulse of nitrate was driven by spring-adapted Nitrososphaerales after snowmelt, but dissimilatory nitrate reduction to ammonia (DNRA) gene expression indicated significant nitrate retention potential. These findings inform our understanding of nitrogen cycling in environments sensitive to snowpack decline due to global change.

Sorensen, Patrick O↗

Cognitive analysis of metabolomics data for systems biology

Cognitive computing is revolutionizing the way big data are processed and integrated, with artificial intelligence (AI) natural language processing (NLP) platforms helping researchers to efficiently search and digest the vast scientific literature. Most available platforms have been developed for biomedical researchers, but new NLP tools are emerging for biologists in other fields and an important example is metabolomics. NLP provides literature-based contextualization of metabolic features that decreases the time and expert-level subject knowledge required during the prioritization, identification and interpretation steps in the metabolomics data analysis pipeline. Here, we describe and demonstrate four workflows that combine metabolomics data with NLP-based literature searches of scientific databases to aid in the analysis of metabolomics data and their biological interpretation. Additionally, the four procedures can be used in isolation or consecutively, depending on the research questions. The first, used for initial metabolite annotation and prioritization, creates a list of metabolites that would be interesting for follow-up. The second workflow finds literature evidence of the activity of metabolites and metabolic pathways in governing the biological condition on a systems biology level. The third is used to identify candidate biomarkers, and the fourth looks for metabolic conditions or drug-repurposing targets that the two diseases have in common. The protocol can take 1–4 h or more to complete, depending on the processing time of the various software used.

59 BASIC BIOLOGICAL SCIENCES↗

The global spectrum of plant form and function: enhanced species-level trait dataset

Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.

54 ENVIRONMENTAL SCIENCES↗

Long-term patterns of cave-exiting activity of hibernating bats in western North America

Understanding frequency and variation of cave-exiting activity after arousal from torpor of hibernating bats is important for bat ecology and conservation, especially considering white-nose syndrome. In winter from 2011 to 2018, we acoustically monitored, and counted in hibernacula, two species of conservation concern—western small-footed myotis ( Myotis ciliolabrum ) and Townsend’s big-eared bats ( Corynorhinus townsendii )—in 9 caves located in important habitat for these species in western North America. We investigated if cave-exiting activity differed by species, cave, number of hibernating bats, moon phase, and weather variables. Both species exited hibernacula during all winter months, but most activity occurred in March followed by November. Although we counted almost 15 times more Townsend’s big-eared bats during hibernacula surveys, we documented western small-footed myotis exiting caves 3 times more than Townsend’s big-eared bats. Cave-exiting activity increased with increasing number of hibernating bats, but more so for western small-footed myotis. Both species of bats were active during warm weather and low wind speeds. Western small-footed myotis were more active during colder temperatures, higher wind speeds, and greater change in barometric pressure than Townsend’s big-eared bats. Our results provide a long-term dataset of cave-exiting activity after arousal from torpor during hibernation for these species before the arrival of white-nose syndrome.

54 ENVIRONMENTAL SCIENCES↗

Community detection in hypergraphs via mutual information maximization

Abstract The hypergraph community detection problem seeks to identify groups of related vertices in hypergraph data. We propose an information-theoretic hypergraph community detection algorithm which compresses the observed data in terms of community labels and community-edge intersections. This algorithm can also be viewed as maximum-likelihood inference in a degree-corrected microcanonical stochastic blockmodel. We perform the compression/inference step via simulated annealing. Unlike several recent algorithms based on canonical models, our microcanonical algorithm does not require inference of statistical parameters such as vertex degrees or pairwise group connection rates. Through synthetic experiments, we find that our algorithm succeeds down to recently-conjectured thresholds for sparse random hypergraphs. We also find competitive performance in cluster recovery tasks on several hypergraph data sets.

97 MATHEMATICS AND COMPUTING↗

Disturbance of hibernating bats due to researchers entering caves to conduct hibernacula surveys

Estimating population changes of bats is important for their conservation. Population estimates of hibernating bats are often calculated by researchers entering hibernacula to count bats; however, the disturbance caused by these surveys can cause bats to arouse unnaturally, fly, and lose body mass. We conducted 17 hibernacula surveys in 9 caves from 2013 to 2018 and used acoustic detectors to document cave-exiting bats the night following our surveys. We predicted that cave-exiting flights (i.e., bats flying out and then back into caves) of Townsend’s big-eared bats (Corynorhinus townsendii) and western small-footed myotis (Myotis ciliolabrum) would be higher the night following hibernacula surveys than on nights following no surveys. Those two species, however, did not fly out of caves more than predicted the night following 82% of surveys. Nonetheless, the activity of bats flying out of caves following surveys was related to a disturbance factor (i.e., number of researchers × total time in a cave). We produced a parsimonious model for predicting the probability of Townsend’s big-eared bats flying out of caves as a function of disturbance factor and ambient temperature. That model can be used to help biologists plan for the number of researchers, and the length of time those individuals are in a cave to minimize disturbing bats.

59 BASIC BIOLOGICAL SCIENCES↗

Cross sections of 147–149 Sm( 6 Li,x) reactions for the production of 149 Tb for targeted alpha therapy

Terbium-149g (t 1/2 = 4.12 h) is of particular interest for targeted alpha therapy cancer treatment due to its ability to decay via both alpha and positron emission, making it a potential theranostic nuclide. Due to many challenges facing its production, there are limited facilities worldwide that have demonstrated the ability to produce this nuclide in quantities sufficient for medical research. Since the Cyclotron Institute at Texas A&M University is a specialized accelerator facility capable of accelerating a wide variety of ions, we are investigating production pathway options. One of the major challenges facing its production is the known co-production of the excited isomeric state, 149m Tb (t 1/2 = 4.1 min). However, this state does not decay to the ground state of 149g Tb, negating any potential contribution to its yield. Due to its short-half life, the cross section for the population of this state has never been measured. After calculating several potential reaction yields using predictive models, the reactions of 147–149 Sm( 6 Li,xn) 149 Tb were identified as candidates. Lithium-6 beams of varied energies between 45-65 MeV were impinged on enriched 147 Sm, 148 Sm, and 149 Sm targets at the Cyclotron Institute at Texas A&M University, and the reaction products were measured immediately following irradiation using high-purity germanium detectors, enabling detection of both 149m Tb and 149g Tb. Cross sections for all nuclides produced in sufficient activity in these reactions were also measured and reported here. We conclude that the population of 149m Tb is much preferred over population of the ground state for these 6 Li-induced reactions, and it is necessary to explore other options for 149g Tb production.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Unlocking aquifer sustainability through irrigator-driven groundwater conservation

Groundwater depletion caused by intensive pumping for irrigated agriculture is a global threat to economies, food security, and ecosystems. Pumping reductions are required to confront this threat, but their implementation is a “wicked” problem due to interlinked hydrological, social, and economic factors. In the US High Plains Aquifer, an irrigator-led conservation effort known as the Sheridan 6 Local Enhanced Management Area (SD-6 LEMA) is a rare example of successful collective action in agricultural-groundwater systems. In its first decade, the area has exceeded water use reduction goals and decreased depletion rates by over 50% without significantly affecting net income. In this Perspective, we highlight factors underlying the SD-6 LEMA’s effectiveness, and identify transferable governance tenets for other groundwater dependent regions striving for sustainable management of groundwater resources. These tenets include flexibility through multi-year allocations, regulatory oversight to support the irrigators’ plans, and a strong scientific foundation for sustainable agricultural-groundwater systems.

54 ENVIRONMENTAL SCIENCES↗