Life at the extreme: Lessons from the genome

© 2012 BioMed Central Ltd. Extremophile plants thrive in places where most plant species cannot survive. Recent developments in high-throughput technologies and comparative genomics are shedding light on the evolutionary mechanisms leading to their adaptation

4C-seq characterization of Drosophila BEAF binding regions provides evidence for highly variable long-distance interactions between active chromatin

© 2018 Shrestha et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Chromatin organization is crucial for nuclear functions such as gene regulation, DNA replication and DNA repair. Insulator binding proteins, such as the Drosophila Boundary Element-Associated Factor (BEAF), are involved in chromatin organization. To further understand the role of BEAF, we detected cis-and trans-interaction partners of four BEAF binding regions (viewpoints) using 4C (circular chromosome conformation capture) and analyzed their association with different genomic features. Previous genome-wide mapping found that BEAF usually binds near transcription start sites, often of housekeeping genes, so our viewpoints were selected to reflect this. Our 4C data show the interaction partners of our viewpoints are highly variable and generally enriched for active chromatin marks. The most consistent association was with housekeeping genes, a feature in common with our viewpoints. Fluorescence in situ hybridization indicated that the long-distance interactions occur even in the absence of BEAF. These data are most consistent with a model in which BEAF is redundant with other factors found at active promoters. Our results point to principles of long-distance interactions made by active chromatin, supporting a previously proposed model in which condensed chromatin is sticky and associates into topologically associating domains (TADs) separated by active chromatin. We propose that the highly variable long-distance interactions we detect are driven by redundant factors that open chromatin to promote transcription, combined with active chromatin filling spaces between TADs while packing of TADs relative to each other varies from cell to cell

The cytoplasmic carbonic anhydrases βCA2 and βCA4 are required for optimal plant growth at low CO\u3csub\u3e2\u3c/sub\u3e

© 2016 American Society of Plant Biologists. All Rights Reserved. Carbonic anhydrases (CAs) are zinc metalloenzymes that interconvert CO2 and HCO3-. In plants, both α-and β-type CAs are present. We hypothesize that cytoplasmic bCAs are required to modulate inorganic carbon forms needed in leaf cells for carbonrequiring reactions such as photosynthesis and amino acid biosynthesis. In this report, we present evidence that βCA2 and βCA4 are the two most abundant cytoplasmic CAs in Arabidopsis (Arabidopsis thaliana) leaves. Previously, βCA4 was reported to be localized to the plasma membrane, but here, we show that two forms of βCA4 are expressed in a tissue-specific manner and that the two proteins encoded by βCA4 localize to two different regions of the cell. Comparing transfer DNA knockout lines with wild-type plants, there was no reduction in the growth rates of the single mutants, βca2 and βca4. However, the growth rate of the double mutant, βca2βca4, was reduced significantly when grown at 200μL L-1 CO2. The reduction in growth of the double mutant was not linked to a reduction in photosynthetic rate. The amino acid content of leaves from the double mutant showed marked reduction in aspartate when compared with the wild type and the single mutants. This suggests the cytoplasmic CAs play an important but not previously appreciated role in amino acid biosynthesis

A Bayesian inverse dynamic approach for impulsive wave loading reconstruction: Theory, laboratory and field application

The measurement of wave forces acting on marine structures is a complicated task, both during physical experiments and, even more so, in the field. Force transducers adopted in laboratory experiments require a minimum level of structural movement, thus violating the main assumption of fully rigid structure and introducing a dynamic response of the system. Sometimes the induced vibrations are so intense that they completely nullify the reliability of the experiments. On-site, it is even more complex, since there are no force transducers of the size and capacity able to measure such massive force intensity acting over the very large domain of a marine structure. To this end, this investigation proposes a Bayesian methodology aimed to remove the undesired effects from the directly (laboratory applications) or indirectly (field applications) measured wave forces. The paper presents three applications of the method: i) a theoretical application on a synthetic signal for which MATLAB® procedures are provided, ii) an experimental application on laboratory data collected during experiments aimed to model broken wave loading on a cylinder upon a shoal and iii) a field application designed to reconstruct the wave force that generated recorded vibrations on the Wolf Rock lighthouse during Hurricane Ophelia. The proposed methodology allows the inclusion of existing information on breaking and broken wave forces through the process-based informative prior distributions, while it also provides the formal framework for uncertainty quantification of the results through the posterior distribution. Notable findings are that the broken wave loading shows similar features for both laboratory and field data. The load time series is characterised by an initial impulsive component constituted by two peaks and followed by a delayed smoother one. The first two peaks are due to the initial impact of the aerated front and to the sudden deceleration of the falling water mass previously upward accelerated by the initial impact. The third, less intense peak, is due to the interaction between the cylinder and remaining water mass carried by the individual wave. Finally, the method allows to properly identify the length of the impulsive loading component. The implications of this length on the use of the impulse theory for the assessment or design of marine structures are discussed

Genome structures and transcriptomes signify niche adaptation for the multiple-ion-tolerant extremophyte Schrenkiella parvula

Schrenkiella parvula (formerly Thellungiella parvula), a close relative of Arabidopsis (Arabidopsis thaliana) and Brassica crop species, thrives on the shores of Lake Tuz, Turkey, where soils accumulate high concentrations of multiple-ion salts. Despite the stark differences in adaptations to extreme salt stresses, the genomes of S. parvula and Arabidopsis show extensive synteny. S. parvula completes its life cycle in the presence of Na+, K+, Mg2+, Li+, and borate at soil concentrations lethal to Arabidopsis. Genome structural variations, including tandem duplications and translocations of genes, interrupt the colinearity observed throughout the S. parvula and Arabidopsis genomes. Structural variations distinguish homologous gene pairs characterized by divergent promoter sequences and basal-level expression strengths. Comparative RNA sequencing reveals the enrichment of ion-transport functions among genes with higher expression in S. parvula, while pathogen defense-related genes show higher expression in Arabidopsis. Key stress-related ion transporter genes in S. parvula showed increased copy number, higher transcript dosage, and evidence for subfunctionalization. This extremophyte offers a framework to identify the requisite adjustments of genomic architecture and expression control for a set of genes found in most plants in a way to support distinct niche adaptation and lifestyles. © 2014 American Society of Plant Biologists. All rights reserved

Classical scrapie prions in ovine blood are associated with B lymphocytes and platelet-rich plasma

<p>Abstract</p> <p>Background</p> <p>Classical scrapie is a naturally occurring transmissible spongiform encephalopathy of sheep and goats characterized by cellular accumulation of abnormal isoforms of prion protein (PrP^Sc) in the central nervous system and the follicles of peripheral lymphoid tissues. Previous studies have shown that the whole blood and buffy coat blood fraction of scrapie infected sheep harbor prion infectivity. Although PrP^Schas been detected in peripheral blood mononuclear cells (PBMCs), plasma, and more recently within a subpopulation of B lymphocytes, the infectivity status of these cells and plasma in sheep remains unknown. Therefore, the objective of this study was to determine whether circulating PBMCs, B lymphocytes and platelets from classical scrapie infected sheep harbor prion infectivity using a sheep bioassay.</p> <p>Results</p> <p>Serial rectal mucosal biopsy and immunohistochemistry were used to detect preclinical infection in lambs transfused with whole blood or blood cell fractions from preclinical or clinical scrapie infected sheep. PrP^Scimmunolabeling was detected in antemortem rectal and postmortem lymphoid tissues from recipient lambs receiving PBMCs (15/15), CD72⁺B lymphocytes (3/3), CD21⁺B lymphocytes (3/3) or platelet-rich plasma (2/3) fractions. As expected, whole blood (11/13) and buffy coat (5/5) recipients showed positive PrP^Sclabeling in lymphoid follicles. However, at 549 days post-transfusion, PrP^Scwas not detected in rectal or other lymphoid tissues in three sheep receiving platelet-poor plasma fraction.</p> <p>Conclusions</p> <p>Prion infectivity was detected in circulating PBMCs, CD72⁺pan B lymphocytes, the CD21⁺subpopulation of B lymphocytes and platelet-rich plasma of classical scrapie infected sheep using a sheep bioassay. Combining platelets with B lymphocytes might enhance PrP^Scdetection levels in blood samples.</p

Comparative study of hybrid artificial intelligence approaches for predicting peak shear strength along soil-Geocomposite drainage layer interfaces

Peak shear strength of soil-Geocomposite Drain Layer (GDL) interfaces is an important parameter in the designing and operating related engineering structures. In this paper, a database compiled from 316 large direct shear tests on soil-GDL interfaces has been established. Based on this database, five different machine learning models: Back Propagation Artificial Neural Network (BPANN) and Support Vector Machine (SVM), with hyperparameters optimised by Particle Swarm Optimisation Algorithm (PSO) and Genetic Algorithm (GA), respectively, and Extreme Learning Machine (ELM) optimised by Exhaustive Method, were adopt to assess the peak shear strength of soil-GDL interfaces. Then, a comprehensive investigation and comparison of the predictive performance for the models was conducted. Also, based on the selected optimal machine learning model, sensitivity analysis was conducted, and an empirical equation developed based on it. The research indicated that GA and PSO could significantly increase forecasting precision in a small number of iterations. The BPANN model optimised by PSO has the highest forecasting precision based on the statistics criteria: Root-Mean-Square Error, Correlation Coefficient, Coefficient of Determination, Wilmot’s Index of Agreement, and Mean Absolute Percentage Error. The normal stress has the biggest impact on the peak shear strength, followed by drainage core type, moisture saturation of the soil layer, shearing surface, soil type, consolidation condition, geotextile specification, soil density and drainage core thickness, and the ranking is affected partly by the data distribution of input parameters in the database based on mechanism analysis. An empirical equation developed from the optimal model was proposed to estimate the peak shear strength, which provides convenience for geotechnical engineering personnel with limited knowledge of machine learning technique

Crystal structures and freezing of dipolar fluids

We investigate the crystal structure of classical systems of spherical particles with an embedded point dipole at T=0. The ferroelectric ground state energy is calculated using generalizations of the Ewald summation technique. Due to the reduced symmetry compared to the nonpolar case the crystals are never strictly cubic. For the Stockmayer (i.e., Lennard-Jones plus dipolar) interaction three phases are found upon increasing the dipole moment: hexagonal, body-centered orthorhombic, and body-centered tetragonal. An even richer phase diagram arises for dipolar soft spheres with a purely repulsive inverse power law potential $\sim r^{-n}$. A crossover between qualitatively different sequences of phases occurs near the exponent $n=12$. The results are applicable to electro- and magnetorheological fluids. In addition to the exact ground state analysis we study freezing of the Stockmayer fluid by density-functional theory.Comment: submitted to Phys. Rev.