Interactive regulation of root exudation and rhizosphere denitrification by plant metabolite content and soil properties

Plant and Soil - Cyperaceae are common on nutrient-poor soils, including in western Japan. We examined the ability of the native Cyperaceae from western Japan to form dauciform roots and assessed...     

Dinucleotides as simple models of the base stacking-unstacking component of DNA ‘breathing’ mechanisms

Regulatory protein access to the DNA duplex ‘interior’ depends on local DNA ‘breathing’ fluctuations, and the most fundamental of these are thermally-driven base stacking-unstacking interactions. The smallest DNA unit that can undergo such transitions is the dinucleotide, whose structural and dynamic properties are dominated by stacking, while the ion condensation, cooperative stacking and inter-base hydrogen-bonding present in duplex DNA are not involved. We use dApdA to study stacking-unstacking at the dinucleotide level because the fluctuations observed are likely to resemble those of larger DNA molecules, but in the absence of constraints introduced by cooperativity are likely to be more pronounced, and thus more accessible to measurement. We study these fluctuations with a combination of Molecular Dynamics simulations on the microsecond timescale and Markov State Model analyses, and validate our results by calculations of circular dichroism (CD) spectra, with results that agree well with the experimental spectra. Our analyses show that the CD spectrum of dApdA is defined by two distinct chiral conformations that correspond, respectively, to a Watson–Crick form and a hybrid form with one base in a Hoogsteen configuration. We find also that ionic structure and water orientation around dApdA play important roles in controlling its breathing fluctuations.     

Evaluating the Mechanisms of Landscape Change on White-Tailed Deer Populations

Understanding how landscape change influences the distribution and densities of species, and the consequences of these changes, is a central question in modern ecology. The distribution of white-tailed deer (Odocoileus virginianus) is expanding across North America, and in some areas, this pattern has led to an increase in predators and consequently higher predation rates on woodland caribou (Rangifer tarandus caribou)—an alternate prey species that is declining across western Canada. Understanding the factors influencing deer distribution has therefore become important for effective conservation of caribou in Canada. Changing climate and anthropogenic landscape alteration are hypothesized to facilitate white-tailed deer expansion. Yet, climate and habitat alteration are spatiotemporally correlated, making these factors difficult to isolate. Our study evaluates the relative effects of snow conditions and human-modified habitat (habitat alteration) across space on white-tailed deer presence and relative density. We modeled deer response to snow depth and anthropogenic habitat alteration across a large latitudinal gradient (49° to 60°) in Alberta, Canada, using motion-sensitive camera data collected in winter and spring from 2015 to 2019. Deer distribution in winter and spring were best explained by models including both snow depth and habitat alteration. Sites with shallower snow had higher deer presence regardless of latitude. Increased habitat alteration increased deer presence in the northern portion of the study area only. Winter deer density was best explained by snow depth only, whereas spring density was best explained by both habitat alteration and the previous winter's snow depth. Our results suggest that limiting future habitat alteration or restoring habitat can alter deer distribution, thereby potentially slowing or reversing expansion, but that climate plays a significant role beyond what managers can influence. © 2020 The Wildlife Society.     

MyD88 oligomer size functions as a physical threshold to trigger IL1R Myddosome signaling

A recurring feature of innate immune receptor signaling is the self-assembly of signaling proteins into oligomeric complexes. The Myddosome is an oligomeric complex that is required to transmit inflammatory signals from TLR/IL1Rs and consists of MyD88 and IRAK family kinases. However, the molecular basis for how Myddosome proteins self-assemble and regulate intracellular signaling remains poorly understood. Here, we developed a novel assay to analyze the spatiotemporal dynamics of IL1R and Myddosome signaling in live cells. We found that MyD88 oligomerization is inducible and initially reversible. Moreover, the formation of larger, stable oligomers consisting of more than four MyD88s triggers the sequential recruitment of IRAK4 and IRAK1. Notably, genetic knockout of IRAK4 enhanced MyD88 oligomerization, indicating that IRAK4 controls MyD88 oligomer size and growth. MyD88 oligomer size thus functions as a physical threshold to trigger downstream signaling. These results provide a mechanistic basis for how protein oligomerization might function in cell signaling pathways.     

PEtab—Interoperable specification of parameter estimation problems in systems biology

Reproducibility and reusability of the results of data-based modeling studies are essential. Yet, there has been—so far—no broadly supported format for the specification of parameter estimation problems in systems biology. Here, we introduce PEtab, a format which facilitates the specification of parameter estimation problems using Systems Biology Markup Language (SBML) models and a set of tab-separated value files describing the observation model and experimental data as well as parameters to be estimated. We already implemented PEtab support into eight well-established model simulation and parameter estimation toolboxes with hundreds of users in total. We provide a Python library for validation and modification of a PEtab problem and currently 20 example parameter estimation problems based on recent studies.     

TMaCS: A hybrid template matching and classification system for partially-automated particle selection

Selection of particle images from electron micrographs presents a bottleneck in determining the structures of macromolecular assemblies by single particle electron cryomicroscopy (cryo-EM). The problem is particularly important when an experimentalist wants to improve the resolution of a 3D map by increasing by tens or hundreds of thousands of images the size of the dataset used for calculating the map. Although several existing methods for automatic particle image selection work well for large protein complexes that produce high-contrast images, it is well known in the cryo-EM community that small complexes that give low-contrast images are often refractory to existing automated particle image selection schemes. Here we develop a method for partially-automated particle image selection when an initial 3D map of the protein under investigation is already available. Candidate particle images are selected from micrographs by template matching with template images derived from projections of the existing 3D map. The candidate particle images are then used to train a support vector machine, which classifies the candidates as particle images or non-particle images. In a final step in the analysis, the selected particle images are subjected to projection matching against the initial 3D map, with the correlation coefficient between the particle image and the best matching map projection used to assess the reliability of the particle image. We show that this approach is able to rapidly select particle images from micrographs of a rotary ATPase, a type of membrane protein complex involved in many aspects of biology.