Explore the vast range of titles available.

Background Microbiome recruitment is influenced by plant host, but how host plant impacts the assembly, functions, and interactions of perennial plant root microbiomes is poorly understood. Here we examined prokaryotic and fungal communities between rhizosphere soils and the root endophytic compartment in two native Miscanthus species ( Miscanthus sinensis and Miscanthus floridulus ) of Taiwan and further explored the roles of host plant on root-associated microbiomes. Results Our results suggest that host plant genetic variation, edaphic factors, and site had effects on the root endophytic and rhizosphere soil microbial community compositions in both Miscanthus sinensis and Miscanthus floridulus , with a greater effect of plant genetic variation observed for the root endophytic communities. Host plant genetic variation also exerted a stronger effect on core prokaryotic communities than on non-core prokaryotic communities in each microhabitat of two Miscanthus species. From rhizosphere soils to root endophytes, prokaryotic co-occurrence network stability increased, but fungal co-occurrence network stability decreased. Furthermore, we found root endophytic microbial communities in two Miscanthus species were more strongly driven by deterministic processes rather than stochastic processes. Root-enriched prokaryotic OTUs belong to Gammaproteobacteria, Alphaproteobacteria, Betaproteobacteria, Sphingobacteriia, and [Saprospirae] both in two Miscanthus species, while prokaryotic taxa enriched in the rhizosphere soil are widely distributed among different phyla. Conclusions We provide empirical evidence that host genetic variation plays important roles in root-associated microbiome in Miscanthus . The results of this study have implications for future bioenergy crop management by providing baseline data to inform translational research to harness the plant microbiome to sustainably increase agriculture productivity. 7yeh-8ahY_T_UpG1ho_dZs Video Abstract

The endoplasmic reticulum (ER) network consists of tubules with high membrane curvature in cross-section, generated by the reticulons and REEPs. These proteins have two pairs of trans-membrane (TM) segments, followed by an amphipathic helix (APH), but how they induce curvature is poorly understood. Here, we show that REEPs form homodimers by interaction within the membrane. When overexpressed or reconstituted at high concentrations with phospholipids, REEPs cause extreme curvature through their TMs, generating lipoprotein particles instead of vesicles. The APH facilitates curvature generation, as its mutation prevents ER network formation of reconstituted proteoliposomes, and synthetic L- or D-amino acid peptides abolish ER network formation in Xenopus egg extracts. In Schizosaccharomyces japonicus , the APH is required for reticulon’s exclusive ER-tubule localization and restricted mobility. Thus, the TMs and APH cooperate to generate high membrane curvature. We propose that the formation of splayed REEP/reticulon dimers is responsible for ER tubule formation. The endoplasmic reticulum network consists of tubules with high membrane curvature in cross-section, generated by the reticulons and REEPs, but how they introduce curvature is poorly understood. Here authors show that REEPs form homodimers and use their amphipathic helix and trans-membrane segments to introduce high membrane curvature that can even lead to the formation of lipoprotein particles.

Like all warfare, drone warfare is deeply gendered. This article explores how this military technology sediments or disrupts existing conceptualizations of women who kill in war. The article using the concept of motherhood as a narrative organizing trope and introduces a ‘fictional’ account of motherhood and drone warfare and data from a ‘real life’ account of a pregnant British Reaper operator. The article considers the way trauma experienced by Reaper drone crews is reported in a highly gendered manner, reflecting the way women’s violence is generally constructed as resulting from personal failures, lost love and irrational emotionality. This irrational emotionality is tied to a long history of medicalizing women’s bodies and psychologies because of their reproductive capacities and, specifically, their wombs – explored in this article under the historico-medical term of ‘hysteria’. The article argues that where barriers to women’s participation in warfare have, in the past, hinged upon their (argued) physical weakness, and where technology renders these barriers obsolete, there remains the tenacious myth that women are emotionally incapable of conducting lethal operations – a myth based on (mis)conceptions of the ‘naturalness’ of motherhood and the feminine capacity to give life.

Background Given the economic and environmental importance of allopolyploids and other species with highly duplicated genomes, there is a need for methods to distinguish paralogs, i.e. duplicate sequences within a genome, from Mendelian loci, i.e. single copy sequences that pair at meiosis. The ratio of observed to expected heterozygosity is an effective tool for filtering loci but requires genotyping to be performed first at a high computational cost, whereas counting the number of sequence tags detected per genotype is computationally quick but very ineffective in inbred or polyploid populations. Therefore, new methods are needed for filtering paralogs. Results We introduce a novel statistic, H ind / H E , that uses the probability that two reads sampled from a genotype will belong to different alleles, instead of observed heterozygosity. The expected value of H ind / H E is the same across all loci in a dataset, regardless of read depth or allele frequency. In contrast to methods based on observed heterozygosity, it can be estimated and used for filtering loci prior to genotype calling. In addition to filtering paralogs, it can be used to filter loci with null alleles or high overdispersion, and identify individuals with unexpected ploidy and hybrid status. We demonstrate that the statistic is useful at read depths as low as five to 10, well below the depth needed for accurate genotype calling in polyploid and outcrossing species. Conclusions Our methodology for estimating H ind / H E across loci and individuals, as well as determining reasonable thresholds for filtering loci, is implemented in polyRAD v1.6, available at https://github.com/lvclark/polyRAD . In large sequencing datasets, we anticipate that the ability to filter markers and identify problematic individuals prior to genotype calling will save researchers considerable computational time.

The authors report a 2.6 Å resolution crystal structure of the human CB1 cannabinoid receptor trapped in the inactive conformation and bound to the antagonist taranabant. CB1 cannabinoid receptor structure The human cannabinoid G-protein-coupled receptors (GPCRs) CB1 and CB2 mediate the responses to endocannabinoids and the plant cannabinoid Δ 9 -tetrahydrocannabinol (THC). They are important drug discovery targets because of the therapeutic potential of receptor modulators for controlling disorders such as pain, epilepsy and obesity. Daniel Rosenbaum and colleagues determine a crystal structure of the human CB1 receptor bound to the inhibitor taranabant. The extracellular surface of the receptor is distinct from other lipid-activated GPCRs and forms a critical part of the ligand-binding pocket. Docking studies demonstrate how this pocket might accommodate tetrahydrocannabinol. The structure should aid drug discovery efforts for novel cannabinoid system modulators as potential therapeutics. The human cannabinoid G-protein-coupled receptors (GPCRs) CB1 and CB2 mediate the functional responses to the endocannabinoids anandamide and 2-arachidonyl glycerol (2-AG) and to the widely consumed plant phytocannabinoid Δ 9 -tetrahydrocannabinol (THC) 1 . The cannabinoid receptors have been the targets of intensive drug discovery efforts, because modulation of these receptors has therapeutic potential to control pain 2 , epilepsy 3 , obesity 4 , and other disorders. Although much progress in understanding the biophysical properties of GPCRs has recently been made, investigations of the molecular mechanisms of the cannabinoids and their receptors have lacked high-resolution structural data. Here we report the use of GPCR engineering and lipidic cubic phase crystallization to determine the structure of the human CB1 receptor bound to the inhibitor taranabant at 2.6-Å resolution. We found that the extracellular surface of CB1, including the highly conserved membrane-proximal N-terminal region, is distinct from those of other lipid-activated GPCRs, forming a critical part of the ligand-binding pocket. Docking studies further demonstrate how this same pocket may accommodate the cannabinoid agonist THC. Our CB1 structure provides an atomic framework for studying cannabinoid receptor function and will aid the design and optimization of therapeutic modulators of the endocannabinoid system.

The mycobacterial outer membrane (OM) creates a formidable permeability barrier, and whether drugs traverse it by mechanisms other than passive diffusion remains unclear. The proline-glutamic acid (PE) and proline-proline-glutamic acid (PPE) proteins of pathogenic mycobacteria include several OM transporters. Because bacterial transporters are also major contributors to drug resistance, we tested the role of PE/PPE proteins in Mycobacterium tuberculosis ( Mtb ) drug susceptibility. We identified mutations in multiple pe/ppe genes that were strongly associated with drug resistance in a genetic association study. A mutation in ppe42 linked to clinical amikacin resistance also conferred higher amikacin resistance in vitro. Deletion of ppe51 led to in vitro resistance to multiple drugs and was accompanied by upregulation of inner membrane efflux pumps. Deletion of a pe/ppe pair that responded transcriptionally to drug exposure, pe25/ppe41 , led to increased resistance to isoniazid (INH) in strains across all major Mtb lineages and accelerated the emergence of INH resistance in vitro. These data show a role of several Mtb PE/PPE proteins in drug resistance consistent with the PE/PPE transporter paradigm and suggest a wider role of the PE/PPE family in Mtb drug susceptibility and clinical drug resistance. Mycobacterium tuberculosis has a complex outer membrane that often blocks antibiotics from entering the cell. A special class of proteins called PE/PEE, contains transporters that might aid in drug susceptibility. Here, they identify key mutations in these proteins that correspond to increased antibiotic resistance.

Abstract Microorganisms associated with plants can affect nutrient and water acquisition, plant defenses, and ecological interactions, with effects on plant growth that range from beneficial to antagonistic. In Glycine max (soybean), many studies have examined the soil microbiome and the legume–rhizobium relationship, but little is known about foliar endophytes, their effects on plant biomass and fitness, and how plants respond to their presence. To address these questions, we inoculated Glycine max with field-collected isolates of previously isolated, dominant strains of Methylobacterium and Colletotrichum in either sterile or non-sterile soil. We then used RNAseq to compare the transcriptomic responses of plants to single- and co-inoculation of endophytes. We found that all endophyte treatments increased soybean growth compared to control, but only in sterile soil. These results suggest context-dependency, with endophytes serving as facultative mutualists under stress or nutrient deprivation. Similarly, transcriptomic analyses revealed that soybean defense and stress responses depended on the interaction of endophytes; Methylobacterium elicited the strongest response but was modulated by the presence of Colletotrichum. Our findings highlight the environmentally dependent effects of co-existing endophytes within soybean leaves. We explore how microorganism communities associated with plants can affect their host's transcriptome, and change the plant's response to different types of stressors, benefiting the plant and enhancing resilience responses.

Low or uneven read depth is a common limitation of genotyping-by-sequencing (GBS) and restriction site-associated DNA sequencing (RAD-seq), resulting in high missing data rates, heterozygotes miscalled as homozygotes, and uncertainty of allele copy number in heterozygous polyploids. Bayesian genotype calling can mitigate these issues, but previously has only been implemented in software that requires a reference genome or uses priors that may be inappropriate for the population. Here we present several novel Bayesian algorithms that estimate genotype posterior probabilities, all of which are implemented in a new R package, polyRAD. Appropriate priors can be specified for mapping populations, populations in Hardy-Weinberg equilibrium, or structured populations, and in each case can be informed by genotypes at linked markers. The polyRAD software imports read depth from several existing pipelines, and outputs continuous or discrete numerical genotypes suitable for analyses such as genome-wide association and genomic prediction.

Studies have suggested associations between self-reported engagement in health behaviors and reduced risk of cognitive decline. Most studies explore these relationships using one health behavior, often cross-sectionally or with dementia as the outcome. In this study, we explored whether several individual self-reported health behaviors were associated with cognitive decline when considered simultaneously, using data from the Wisconsin Registry for Alzheimer's Prevention (WRAP), an Alzheimer's disease risk-enriched cohort who were non-demented and in late midlife at baseline. We analyzed longitudinal cognitive data from 828 participants in WRAP, with a mean age at baseline cognitive assessment of 57 (range = 36-78, sd = 6.8) and an average of 6.3 years (standard deviation = 1.9, range = 2-10) of follow-up. The primary outcome was a multi-domain cognitive composite, and secondary outcomes were immediate/delayed memory and executive function composites. Predictors of interest were self-reported measures of physical activity, cognitive activity, adherence to a Mediterranean-style diet (MIND), and interactions with each other and age. We conducted linear mixed effects analyses within an Information-theoretic (IT) model averaging (MA) approach on a set of models including covariates and combinations of these 2- and 3-way interactions. The IT approach was selected due to the large number of interactions of interest and to avoid pitfalls of traditional model selection approaches. Model-averaged results identified no significant self-reported health behavior*age interactions in relationship to the primary composite outcome. In secondary outcomes, higher MIND diet scores associated with slower decline in executive function. Men showed faster decline than women on delayed memory, independent of health behaviors. There were no other significant interactions among any other health behaviors and cognitive trajectories. When multiple covariates and health behaviors were considered simultaneously, there were limited weak associations with cognitive decline in this age range. These results may be explained alone or in combination by three alternative explanations: 1) the range of cognitive decline is in middle age is too small to observe relationships with health behaviors, 2) the putative associations of these health behaviors on cognition may not be robust in this age range, or 3) the self-reported measures of the health behaviors may not be optimal for predicting cognitive decline. More study may be needed that incorporates sensitive measures of health behaviors, AD biomarker profiles, and/or other disease comorbidities.

The expanding use of civilian unmanned aerial vehicles (UAVs) has brought forth a crucial need to address the safety risks they pose in the event of failure, especially when flying in populated areas. This paper reviews recent advancements in recovery systems designed for the emergency landing of civilian UAVs. It covers a wide range of recovery methods, categorizing them based on different recovery approaches and UAV types, including multirotor and fixed-wing. The study highlights the diversity of recovery strategies, ranging from parachute and airbag systems to software-based methods and hybrid solutions. It emphasizes the importance of considering UAV-specific characteristics and operational environments when selecting appropriate safety systems. Furthermore, by comparing various emergency landing systems, this study reveals that integrating multiple approaches based on the UAV type and mission requirements can achieve broader cover of emergency situations compared to using a single system for a specific scenario. Examples of UAVs that utilize emergency landing systems are also provided. For each recovery system, three key parameters of operating altitude, flight speed and added weight are presented. Researchers and UAV developers can utilize this information to identify a suitable emergency landing method tailored to their mission requirements and available UAVs. Based on the key trends and challenges found in the literature, this review concludes by proposing specific, actionable recommendations. These recommendations are directed towards researchers, UAV developers, and regulatory bodies, and focus on enhancing the safety of civilian UAV operations through the improvement of emergency landing systems.