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Amplification-based gene characterization allows for sensitive and specific quantification of functional genes. There is often a large diversity of genes represented for functional gene groups, and multiple primers may be necessary to target associated genes.
Abstract Viruses impact microbial systems through killing hosts, horizontal gene transfer, and altering cellular metabolism, consequently impacting nutrient cycles. A virus-infected cell, a “virocell,” is distinct from its uninfected sister cell as the virus commandeers cellular machinery to produce viruses rather than replicate cells. Problematically, virocell responses to the nutrient-limited conditions that abound in nature are poorly understood. Here we used a systems biology approach to investigate virocell metabolic reprogramming under nutrient limitation. Using transcriptomics, proteomics, lipidomics, and endo- and exo-metabolomics, we assessed how low phosphate (low-P) conditions impacted virocells of a marine Pseudoalteromonas host when independently infected by two unrelated phages (HP1 and HS2). With the combined stresses of infection and nutrient limitation, a set of nested responses were observed. First, low-P imposed common cellular responses on all cells (virocells and uninfected cells), including activating the canonical P-stress response, and decreasing transcription, translation, and extracellular organic matter consumption. Second, low-P imposed infection-specific responses (for both virocells), including enhancing nitrogen assimilation and fatty acid degradation, and decreasing extracellular lipid relative abundance. Third, low-P suggested virocell-specific strategies. Specifically, HS2-virocells regulated gene expression by increasing transcription and ribosomal protein production, whereas HP1-virocells accumulated host proteins, decreased extracellular peptide relative abundance, and invested in broader energy and resource acquisition. These results suggest that although environmental conditions shape metabolism in common ways regardless of infection, virocell-specific strategies exist to support viral replication during nutrient limitation, and a framework now exists for identifying metabolic strategies of nutrient-limited virocells in nature.
Antarctica's extreme environmental conditions impose selection pressures on microbial communities. Indeed, a previous study revealed that bacterial assemblages at the Cierva Point Wetland Complex (CPWC) are shaped by strong homogeneous selection. Yet which bacterial phylogenetic clades are shaped by selection processes and their ecological strategies to thrive in such extreme conditions remain unknown. Here, we applied the phyloscore and feature-level βNTI indexes coupled with phylofactorization to successfully detect bacterial monophyletic clades subjected to homogeneous (HoS) and heterogenous (HeS) selection. Remarkably, only the HoS clades showed high relative abundance across all samples and signs of putative microdiversity. The majority of the amplicon sequence variants (ASVs) within each HoS clade clustered into a unique 97% sequence similarity operational taxonomic unit (OTU) and inhabited a specific environment (lotic, lentic or terrestrial). Our findings suggest the existence of microdiversification leading to sub-taxa niche differentiation, with putative distinct ecotypes (consisting of groups of ASVs) adapted to a specific environment. We hypothesize that HoS clades thriving in the CPWC have phylogenetically conserved traits that accelerate their rate of evolution, enabling them to adapt to strong spatio-temporally variable selection pressures. Variable selection appears to operate within clades to cause very rapid microdiversification without losing key traits that lead to high abundance. Variable and homogeneous selection, therefore, operate simultaneously but on different aspects of organismal ecology. The result is an overall signal of homogeneous selection due to rapid within-clade microdiversification caused by variable selection. It is unknown whether other systems experience this dynamic, and we encourage future work evaluating the transferability of our results.
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The outline for this presentation includes: Motivation, Test hardware and loads, Modal test of RC on 6 DOF test fixture, and Analysis--develop one specification accounting for unit-to-unit variability and develop independently tailored test specifications for unit-to-unit variability.
Cyber security has been difficult to quantify from the perspective of defenders. The effort to develop a cyber-attack with some ability, function, or consequence has not been rigorously investigated in Operational Technologies. This specification defines a testing structure that allows conformal and repeatable cyber testing on equipment. The purpose of the ETE is to provide data necessary to analyze and reconstruct cyber-attack timelines, effects, and observables for training and development of Cyber Security Operation Centers. Standardizing the manner in which cyber security on equipment is investigated will allow a greater understanding of the progression of cyber attacks and potential mitigation and detection strategies in a scientifically rigorous fashion.
We establish bounds on quantum correlations in many-body systems. They reveal what sort of information about a quantum system can be simultaneously recorded in different parts of its environment. Specifically, independent agents who monitor environment fragments can eavesdrop only on amplified and redundantly disseminated—hence, effectively classical—information about the decoherence-resistant pointer observable. We also show that the emergence of classical objectivity is signaled by a distinctive scaling of the conditional mutual information, bypassing hard numerical optimizations. Our results validate the core idea of quantum Darwinism: objective classical reality does not need to be postulated and is not accidental, but rather a compelling emergent feature of quantum theory that otherwise—in the absence of decoherence and amplification—leads to “quantum weirdness.” In particular, a lack of consensus between agents that access environment fragments is bounded by the information deficit, a measure of the incompleteness of the information about the system.
“Quantile-dependent expressivity” occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g. adiponectin) is high or low relative to its distribution. We have previously shown that the heritability ( h 2 ) of adiposity, lipoproteins, postprandial lipemia, pulmonary function, and coffee and alcohol consumption are quantile-specific. Whether adiponectin heritability is quantile specific remains to be determined. Plasma adiponectin concentrations from 4,182 offspring-parent pairs and 1,662 sibships from the Framingham Heart Study were analyzed. Quantile-specific heritability from offspring-parent (β OP , h 2 = 2 β OP /(1 + r spouse )) and full-sib regression slopes ( β FS , h 2 = {(1 + 8r spouse β FS ) 0.05 -1}/(2r spouse )) were robustly estimated by quantile regression with nonparametric significance assigned from 1,000 bootstrap samples. Quantile-specific h 2 (± SE) increased with increasing percentiles of the offspring’s age- and sex-adjusted adiponectin distribution when estimated from β OP ( P trend = 2.2 × 10 -6 ): 0.30 ± 0.03 at the 10th, 0.33 ± 0.04 at the 25th, 0.43 ± 0.04 at the 50th, 0.55 ± 0.05 at the 75th, and 0.57 ± 0.08 at the 90th percentile, and when estimated from β FS (P trend = 7.6 × 10 -7 ): 0.42 ± 0.03 at the 10th, 0.44 ± 0.04 at the 25th, 0.56 ± 0.05 at the 50th, 0.73 ± 0.08 at the 75th, and 0.79 ± 0.11 at the 90th percentile. Consistent with quantile-dependent expressivity, adiponectin’s: (1) heritability was greater in women in accordance with their higher adiponection concentrations; (2) relationships to ADIPOQ polymorphisms were modified by adiposity in accordance with its adiponectin-lowering effect; (3) response to rosiglitazone was predicted by the 45T> G ADIPOQ polymorphism; (4) difference by ADIPOQ haplotypes increased linearly with increasing postprandial adiponectin concentrations. Adiponectin heritability is quantile dependent, which may explain sex-specific heritability, gene-environment and gene-drug interactions, and postprandial response by haplotypes.
Soil microbial communities in the Arctic play a critical role in regulating the global carbon (C) cycle. Vast amounts of C are stored in northern latitude soils, and rising temperatures in the Arctic threaten to thaw permafrost, making relatively inaccessible C sources more available for mineralization by soil microbes. Few studies have characterized how microbial community structure responds to thawing permafrost in the context of varying soil chemistries associated with contrasting tundra landscapes. Here, we subjected active layer and permafrost soils from upland and lowland tundra sites on the North Slope of Alaska to a soil-warming incubation experiment and compared soil bacterial community profiles (obtained by 16S rRNA amplicon sequencing) before and after incubation. The influence of soil composition (characterized by mid-infrared [MIR] spectroscopy) on bacterial community structure and class abundance was analyzed using redundancy and correlation analyses. We found increased abundances of Alphaproteobacteria, Gammaproteobacteria, and Bacteroidetes [Sphingobacteriia] post incubation, particularly in permafrost soils. The categorical descriptors site and soil layer had the most explanatory power in our predictive models of bacterial community structure, highlighting the close relationship between soil bacteria and the soil environment. Specific soil chemical attributes characterizing the soil environments that were found to be the best predictors include MIR spectral bands associated with inorganic C, silicates, amide II (C=N stretch), and carboxylics (C-O stretch), and MIR peak ratios representing C substrate quality. Overall, these results further characterize soil bacterial community shifts that may occur as a frozen environment with limited access to C sources, such as is found in undisturbed permafrost, transitions to warmer and more C-available environments, such as is predicted in thawing permafrost due to climate change.
Genomic selection holds the potential to serve as a strategic tool to enhance the genetic gain of complex traits in Miscanthus breeding programs. The development of improved cultivars requires their assessment for various traits across diverse environments to ensure suitable overall performance. Hence, the multi-trait multi-environment (MTME) genomic prediction (GP) models offer an opportunity to improve selection accuracy. This study aims to evaluate the potential of five GP models: (1) three MTME models including genotype-by-trait-by-environment interaction (G×E×T) and (2) two single-trait multi-environment (STME) models (with and without G×E interaction). A Miscanthus sacchariflorus population comprising 336 genotypes evaluated in three environments and scored for four traits (biomass yield YDY, total culm number TCM, average internode length AIL, and culm node number CNN) was analyzed. The predictive ability of the models was evaluated considering three cross-validation schemes resembling realistic scenarios (CV1: predicting new genotypes, CVP: predicting missing traits in a given environment, and CV2: predicting partially observed genotypes). On average, in all cross-validation schemes compared to the STME the predictive ability of the MTME models was 10% to 70% higher for TCM and AIL. On the other hand, for YDY and CNN, both STME models performed similarly or slightly better (between 5 to 64%) than the MTME models in most environments. While the MTME models were not successful for all traits when compared to their STME counterparts, MTME models improved the prediction of the performance of genotypes that were untested across environments or lacked trait information in a specific environment. Overall, our study suggests that MTME GP models can be implemented in Miscanthus breeding programs to improve the predictive ability of the complex traits, shorten breeding cycles, and accelerate selection decisions.
To reduce cost and ease maintenance, industrial control systems (ICS) have adopted Ethernetbased interconnections that integrate operational technology (OT) systems with information technology (IT) networks. This integration has made these critical systems vulnerable to attack. Security solutions tailored to ICS environments are an active area of research. Anomalybased network intrusion detection systems are well-suited for these environments. Often these systems must be optimized for their specific environment. In prior work, we introduced a method for assessing the impact of various anomaly-based network IDS settings on security. This paper reviews the experimental outcomes when we applied our method to a full-scale ICS test bed using actual attacks. Our method provides new and valuable data to operators enabling more informed decisions about IDS configurations.
Abstract Conventional solid lubricants such as MoS 2 , graphite, or diamond-like carbon films demonstrate excellent tribological performance but only in specific environments due to their inherent materials properties. This limitation prohibits using these solid lubricants in environments that change dynamically. This study presents the results of a novel solid lubricant that was developed using a combination of solution-processed 2D-molybdenum disulfide and graphene-oxide (GO) that can be deposited on to stainless steel substrates using a simple spray-coating technique and show exceptional performance in multifarious environments namely, ambient (humid) atmosphere, dry nitrogen, and vacuum. The tribological performance of the coatings was evaluated using a ball-on-disc sliding test and demonstrated an excellent wear/friction performance in all environments and coating survived even after 44 km of linear sliding. Transmission electron microscopy and Raman spectroscopy analysis of the tribolayers suggested in-operando friction-induced re-orientation of MoS 2 layers that were protected by GO layers and, an absence of MoO x peaks indicate a strong resistance to intercalation with moisture and oxygen. The simplicity and robustness of the hybrid MoS 2 –GO solid lubricant in mitigating wear-friction behavior of steel-on-steel tribopair in a multifarious environment is a game-changing and is promising for various applications.
Molecular Dynamics (MD) simulations are used to understand the effects of corrosion on metallic materials in salt brine. Reactive force fields in classical MD enable accurate modeling of bond formation and breakage in the aqueous medium and at the metal-electrolyte interface, while also facilitating dynamic partial charge equilibration. However, MD simulations are computationally intensive and unsuitable for modeling the long time scales characteristic of corrosive phenomena. To address this, we develop reduced-order machine learning models that provide accurate and efficient predictions of charge density in corrosive environments. Specifically, we use Long Short-Term Memory (LSTM) networks to forecast charge density evolution based on atomic environments represented by Smooth Overlap of Atomic Positions (SOAP) descriptors. A physics-informed loss function enforces charge neutrality and electronegativity equivalence. The atomic charges predicted by the deep learning model trained on this work were obtained two orders of magnitude faster than those from molecular dynamics (MD) simulations, with an error of less than 3% compared to the MD-obtained charges, even in extrapolative scenarios, while adhering to physical constraints. This demonstrates the excellent accuracy, computational efficiency, and validity of the developed model. Lastly, even though developed for corrosion, these protocols are formulated in a phenomenon-agnostic manner, allowing application to various variable-charge interatomic potentials and related fields.
Many systems derive their electromagnetic radiation (EMR) environments from Mil-Std-464C or Mil-Std-464D, Electromagnetic Environmental Effects Requirements for Systems. This standard defines several EMR environments based on the type of system and expected application. Many nuclear weapon (NW) systems reference the ordnance environments as the starting point for their functional EMR requirements, since any item intended to go into Department of Defense (DOD) custody is expected to be certified hazards of electromagnetic radiation to ordnance (HERO) safe when exposed to the environments listed in Mil-Std-464 Table 9. This environment is defined as the envelope of all sources any system in DOD custody may ever encounter, however, and may include sources that are not relevant for a particular system. This document is intended to provide additional clarity on the Mil-Std-464C and Mil-Std-464D EMR environments, specifically the driving sources for the maximum ordnance levels. This supplementary information may be used to guide tailoring of relevant environments or application to different systems with the additional consideration of any shielding that may reduce the external environments defined in the military standard.
Greater-than-Class C (GTCC) waste is low-level waste (LLW) that exceeds the Class C concentrations tabulated in Title 10, Code of Federal Regulations (CFR), Part 61. Disposal of GTCC waste in the near surface (i.e. upper 30 m of the earth's surface) is prohibited in the United States. Though GTCC waste disposal is generally prohibited, the Commission can approve disposal according to 10 CFR 61.55(a)(2)(iv) on a case-by-case basis. The waste classification tables, developed in the early 1980's, were based on model projections of dose to an inadvertent intruder in agricultural, construction, and discovery exposure scenarios. The assumptions and parameters used were documented in a series of public reports. Though different disposal facility designs and site conditions were considered, the waste classification tables were based on a disposal facility design located in a specific environment. The tables were based on shallow (i.e., top few meters) trench facility designs and did not consider deeper facilities. To determine the suitability of GTCC waste disposal in the near-surface, site-specific analyses must account for differences between GTCC waste and Class A, B, and C LLW (hereafter, traditional LLW). GTCC waste can have concentrations of radionuclides that are much higher than traditional LLW. Because of these higher concentrations, processes that are typically not significant for traditional LLW may be significant with respect to disposal of GTCC waste. These processes include, but are not limited to, heat generation, criticality, and radiolysis. The form of the waste as well as the barriers to release of the waste (e.g. waste package) could be substantially different than they are for traditional LLW. These barriers need to be considered when assessing the impacts of accidents during receipt and placement and in evaluating long-term performance. Some GTCC radioactivity is either embedded in stainless steel or contained in stainless steel barriers. Stainless steel can have very low corrosion rates under a variety of environmental conditions. Finally, and possibly most importantly, GTCC waste would likely need to be disposed deeper than traditional LLW to reduce the probability of disturbance. The waste classification table values of traditional LLW are based on an inadvertent intruder excavating into the waste and bringing some of the material to the land surface. If waste is deeper than approximately 5 m, the excavation scenario becomes very unlikely. Therefore, other intruder scenarios, such as drilling exposure scenarios, need to be evaluated. This paper summarizes key technical issues for the disposal of GTCC waste. Our previous study shows that certain GTCC waste may be suitable for near surface disposal whereas others may not. This study may support ongoing technical analyses assessing potential disposal of GTCC in a near surface disposal facility. (authors)
ABSTRACT Rhodopseudomonas are a group of phototrophic microbes with a marked metabolic versatility and flexibility that underpins their potential use in the production of value-added products, bioremediation, and plant growth promotion. Members of this group have an average genome size of about 5.5 Mb, but two closely related strains have genome sizes of about 4.0 Mb. To identify the types of genes missing in a reduced genome strain, we compared strain DSM127 with other Rhodopseudomonas isolates at the genomic and phenotypic levels. We found that DSM127 can grow as well as other members of the Rhodopseudomonas genus and retains most of their metabolic versatility, but it has many fewer genes associated with high-affinity transport of nutrients, iron uptake, nitrogen metabolism, and biodegradation of aromatic compounds. This analysis indicates genes that can be deleted in genome reduction campaigns and suggests that DSM127 could be a favorable choice for biotechnology applications using Rhodopseudomonas or as a strain that can be engineered further to reside in a specialized natural environment. IMPORTANCE Rhodopseudomonas are a cohort of phototrophic bacteria with broad metabolic versatility. Members of this group are present in diverse soil and water environments, and some strains are found associated with plants and have plant growth-promoting activity. Motivated by the idea that it may be possible to design bacteria with reduced genomes that can survive well only in a specific environment or that may be more metabolically efficient, we compared Rhodopseudomonas strains with typical genome sizes of about 5.5 Mb to a strain with a reduced genome size of 4.0 Mb. From this, we concluded that metabolic versatility is part of the identity of the Rhodopseudomonas group, but high-affinity transport genes and genes of apparent redundant function can be dispensed with.