Early events of Bacillus anthracis germination identified by time-course quantitative proteomics

Germination of Bacillus anthracis spores involves rehydration of the spore interior and rapid degradation of several of the protective layers, including the spore coat. Here, we examine the temporal changes that occur during B. anthracis spore germination using an isobaric tagging system. Over the course of 17 min from the onset of germination, the levels of at least 19 spore proteins significantly decrease. Included are acid-soluble proteins, several known and predicted coat proteins, and proteins of unknown function. Over half of these proteins are small (less than 100 amino acids) and would have been undetectable by conventional gel-based analysis. We also identified 20 proteins, whose levels modestly increased at the later time points when metabolism has likely resumed. Taken together, our data show that isobaric labeling of complex mixtures is particularly effective for temporal studies. Furthermore, we describe a rigorous statistical approach to define relevant changes that takes into account the nature of data obtained from multidimensional protein identification technology coupled with the use of isobaric tags. This study provides an expanded list of the proteins that may be involved in germination of the B. anthracis spore and their relative levels during germination.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/55849/1/5199_ftp.pd

Topological self-similarity on the random binary-tree model

Asymptotic analysis on some statistical properties of the random binary-tree model is developed. We quantify a hierarchical structure of branching patterns based on the Horton-Strahler analysis. We introduce a transformation of a binary tree, and derive a recursive equation about branch orders. As an application of the analysis, topological self-similarity and its generalization is proved in an asymptotic sense. Also, some important examples are presented

Quantifying loopy network architectures

Biology presents many examples of planar distribution and structural networks having dense sets of closed loops. An archetype of this form of network organization is the vasculature of dicotyledonous leaves, which showcases a hierarchically-nested architecture containing closed loops at many different levels. Although a number of methods have been proposed to measure aspects of the structure of such networks, a robust metric to quantify their hierarchical organization is still lacking. We present an algorithmic framework, the hierarchical loop decomposition, that allows mapping loopy networks to binary trees, preserving in the connectivity of the trees the architecture of the original graph. We apply this framework to investigate computer generated graphs, such as artificial models and optimal distribution networks, as well as natural graphs extracted from digitized images of dicotyledonous leaves and vasculature of rat cerebral neocortex. We calculate various metrics based on the Asymmetry, the cumulative size distribution and the Strahler bifurcation ratios of the corresponding trees and discuss the relationship of these quantities to the architectural organization of the original graphs. This algorithmic framework decouples the geometric information (exact location of edges and nodes) from the metric topology (connectivity and edge weight) and it ultimately allows us to perform a quantitative statistical comparison between predictions of theoretical models and naturally occurring loopy graphs.Comment: 17 pages, 8 figures. During preparation of this manuscript the authors became aware of the work of Mileyko at al., concurrently submitted for publicatio

Remotely sensed albedo allows the identification of two ecosystem states along aridity gradients in Africa

Empirical verification of multiple states in drylands is scarce, impeding the design of indicators to anticipate the onset of desertification. Remote sensing‐derived indicators of ecosystem states are gaining new ground due to the possibilities they bring to be applied inexpensively over large areas. Remotely sensed albedo has been often used to monitor drylands due to its close relationship with ecosystem status and climate. Here, we used a space‐for‐time‐substitution approach to evaluate whether albedo (averaged from 2000 to 2016) can identify multiple ecosystem states in African drylands spanning from the Saharan desert to tropical Africa. By using latent class analysis, we found that albedo showed two states (low and high; the cut‐off level was 0.22 at the shortwave band). Potential analysis revealed that albedo exhibited an abrupt and discontinuous increase with increased aridity (1 − [precipitation/potential evapotranspiration]). The two albedo states co‐occurred along aridity values ranging from 0.72 to 0.78, during which vegetation cover exhibited a rapid, continuous decrease from ~90% to ~50%. At aridity values of 0.75, the low albedo state started to exhibit less attraction than the high albedo state. Low albedo areas beyond this aridity value were considered as vulnerable regions where abrupt shifts in albedo may occur if aridity increases, as forecasted by current climate change models. Our findings indicate that remotely sensed albedo can identify two ecosystem states in African drylands. They support the suitability of albedo indices to inform us about discontinuous responses to aridity experienced by drylands, which can be linked to the onset of land degradation.This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant XDA19030500), the National Key Research and Development Program of China (Grant 2016YFC0503302), the European Research Council (BIODESERT project, ERC Grant Agreement 647038), the Joint PhD, Training Program of the University of Chinese Academy of Sciences, and the Research Foundation of Henan University of Technology (Grant 31401178)

A Multimetric Assessment of Stream Condition in the Northern Lakes and Forests Ecoregion Using Spatially Explicit Statistical Modeling and Regional Normalization

We sampled fish communities, water temperature, water chemistry, physical habitat, and catchment characteristics for 94 stream sites selected randomly throughout the Northern Lakes and Forests ecoregion and used those data to explicitly model reference conditions and assess ecological stream condition at each site via a regional normalization framework. The streams we sampled were first order through fourth order, and the catchments ranged from 0.9 to 458 km2. We developed multiple linear regression (MLR) models that predicted fish community metrics, water chemistry characteristics, and local physical habitat from catchment characteristics; we used these models to compare existing conditions with the conditions that would be expected based on the regression models. Our results indicated that the fish communities were relatively unimpaired because the catchment variables associated with human‐induced land use change were important in only 1 of the 10 fish metric models. Agricultural land use was a significant variable in the MLR equation for species of Lepomis (sunfish). Agricultural land use and urban land use were both significant variables in all of the MLR models predicting water chemistry variables; urban land use was a significant variable in the MLR model predicting the percent coverage of all instream cover types. Regional normalization indicated that none of the sites were impaired based on fish community attributes. However, our analysis based on water chemistry metrics indicated that 22– 35% of the sites were impaired and that, based on physical habitat, 6–14% of the sites were impaired. A comparison with other published studies of the ecoregion suggested that the regional normalization process correctly characterized stream condition.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141590/1/tafs0697.pd

Limits on the high-energy gamma and neutrino fluxes from the SGR 1806-20 giant flare of December 27th, 2004 with the AMANDA-II detector

On December 27th 2004, a giant gamma flare from the Soft Gamma-ray Repeater 1806-20 saturated many satellite gamma-ray detectors. This event was by more than two orders of magnitude the brightest cosmic transient ever observed. If the gamma emission extends up to TeV energies with a hard power law energy spectrum, photo-produced muons could be observed in surface and underground arrays. Moreover, high-energy neutrinos could have been produced during the SGR giant flare if there were substantial baryonic outflow from the magnetar. These high-energy neutrinos would have also produced muons in an underground array. AMANDA-II was used to search for downgoing muons indicative of high-energy gammas and/or neutrinos. The data revealed no significant signal. The upper limit on the gamma flux at 90% CL is dN/dE < 0.05 (0.5) TeV^-1 m^-2 s^-1 for gamma=-1.47 (-2). Similarly, we set limits on the normalization constant of the high-energy neutrino emission of 0.4 (6.1) TeV^-1 m^-2 s^-1 for gamma=-1.47 (-2).Comment: 14 pages, 3 figure

Calibration and Characterization of the IceCube Photomultiplier Tube

Over 5,000 PMTs are being deployed at the South Pole to compose the IceCube neutrino observatory. Many are placed deep in the ice to detect Cherenkov light emitted by the products of high-energy neutrino interactions, and others are frozen into tanks on the surface to detect particles from atmospheric cosmic ray showers. IceCube is using the 10-inch diameter R7081-02 made by Hamamatsu Photonics. This paper describes the laboratory characterization and calibration of these PMTs before deployment. PMTs were illuminated with pulses ranging from single photons to saturation level. Parameterizations are given for the single photoelectron charge spectrum and the saturation behavior. Time resolution, late pulses and afterpulses are characterized. Because the PMTs are relatively large, the cathode sensitivity uniformity was measured. The absolute photon detection efficiency was calibrated using Rayleigh-scattered photons from a nitrogen laser. Measured characteristics are discussed in the context of their relevance to IceCube event reconstruction and simulation efforts.Comment: 40 pages, 12 figure

Geodiversity assessment of Paraná state (Brazil): an innovative approach

Geodiversity is considered as the natural range of geological, geomorphological, and soil features, including their assemblages, relationships, properties, interpretations, and systems. A method developed for the quantitative assessment of geodiversity was applied to Parana ́ , a Brazilian state with an area of about 200,000 km2. The method is based on the overlay of a grid over different maps at scales ranging from 1/500,000 to 1/650,000, with the final Geodiversity Index the sum of five partial indexes calculated on a 25 9 25 km grid. The partial indexes represent the main components of geodi- versity, including geology (stratigraphy and lithology), geomorphology, paleontology, and soils. The fifth partial index covers mineral occurrences of geodiversity, such precious stones and metals, energy and industrial minerals, mineral waters, and springs. The Geodiversity Index takes the form of an isoline map that can be used as a tool in land-use planning, particularly in identifying priority areas for conservation, management, and use of natural resources at the state level.The Portuguese authors express their gratitude for the financial support given by the Fundacao para a Ciencia e a Tecnologia to the Centro de Geologia da Universidade do Porto, which partially supports this research. The Brazilian author expresses his gratitude for the financial support given by the CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico) (Process Number 200074/2011-3)