Quantifying bioirrigation using ecological parameters: a stochastic approach†

Irrigation by benthic macrofauna has a major influence on the biogeochemistry and microbial community structure of sediments. Existing quantitative models of bioirrigation rely primarily on chemical, rather than ecological, information and the depth-dependence of bioirrigation intensity is either imposed or constrained through a data fitting procedure. In this study, stochastic simulations of 3D burrow networks are used to calculate mean densities, volumes and wall surface areas of burrows, as well as their variabilities, as a function of sediment depth. Burrow networks of the following model organisms are considered: the polychaete worms Nereis diversicolor and Schizocardium sp., the shrimp Callianassa subterranea, the echiuran worm Maxmuelleria lankesteri, the fiddler crabs Uca minax, U. pugnax and U. pugilator, and the mud crabs Sesarma reticulatum and Eurytium limosum. Consortia of these model organisms are then used to predict burrow networks in a shallow water carbonate sediment at Dry Tortugas, FL, and in two intertidal saltmarsh sites at Sapelo Island, GA. Solute-specific nonlocal bioirrigation coefficients are calculated from the depth-dependent burrow surface areas and the radial diffusive length scale around the burrows. Bioirrigation coefficients for sulfate obtained from network simulations, with the diffusive length scales constrained by sulfate reduction rate profiles, agree with independent estimates of bioirrigation coefficients based on pore water chemistry. Bioirrigation coefficients for O(2 )derived from the stochastic model, with the diffusion length scales constrained by O(2 )microprofiles measured at the sediment/water interface, are larger than irrigation coefficients based on vertical pore water chemical profiles. This reflects, in part, the rapid attenuation with depth of the O(2 )concentration within the burrows, which reduces the driving force for chemical transfer across the burrow walls. Correction for the depletion of O(2 )in the burrows results in closer agreement between stochastically-derived and chemically-derived irrigation coefficient profiles

ALADIN is Required for the Production of Fertile Mouse Oocytes

Asymmetric cell divisions depend on the precise placement of the spindle apparatus. In mammalian oocytes, spindles assemble close to the cell's center, but chromosome segregation takes place at the cell periphery where half of the chromosomes are expelled into small, nondeveloping polar bodies at anaphase. By dividing so asymmetrically, most of the cytoplasmic content within the oocyte is preserved, which is critical for successful fertilization and early development. Recently we determined that the nucleoporin ALADIN participates in spindle assembly in somatic cells, and we have also shown that female mice homozygously null for ALADIN are sterile. In this study we show that this protein is involved in specific meiotic stages, including meiotic resumption, spindle assembly, and spindle positioning. In the absence of ALADIN, polar body extrusion is compromised due to problems in spindle orientation and anchoring at the first meiotic anaphase. ALADIN null oocytes that mature far enough to be fertilized in vitro are unable to support embryonic development beyond the two-cell stage. Overall, we find that ALADIN is critical for oocyte maturation and appears to be far more essential for this process than for somatic cell divisions

The MicroRNA and MessengerRNA Profile of the RNA-Induced Silencing Complex in Human Primary Astrocyte and Astrocytoma Cells

GW/P bodies are cytoplasmic ribonucleoprotein-rich foci involved in microRNA (miRNA)-mediated messenger RNA (mRNA) silencing and degradation. The mRNA regulatory functions within GW/P bodies are mediated by GW182 and its binding partner hAgo2 that bind miRNA in the RNA-induced silencing complex (RISC). To date there are no published reports of the profile of miRNA and mRNA targeted to the RISC or a comparison of the RISC-specific miRNA/mRNA profile differences in malignant and non-malignant cells.RISC mRNA and miRNA components were profiled by microarray analysis of malignant human U-87 astrocytoma cells and its non-malignant counterpart, primary human astrocytes. Total cell RNA as well as RNA from immunoprecipitated RISC was analyzed. The novel findings were fourfold: (1) miRNAs were highly enriched in astrocyte RISC compared to U-87 astrocytoma RISC, (2) astrocytoma and primary astrocyte cells each contained unique RISC miRNA profiles as compared to their respective cellular miRNA profiles, (3) miR-195, 10b, 29b, 19b, 34a and 455-3p levels were increased and the miR-181b level was decreased in U-87 astrocytoma RISC as compared to astrocyte RISC, and (4) the RISC contained decreased levels of mRNAs in primary astrocyte and U-87 astrocytoma cells.The observation that miR-34a and miR-195 levels were increased in the RISC of U-87 astrocytoma cells suggests an oncogenic role for these miRNAs. Differential regulation of mRNAs by specific miRNAs is evidenced by the observation that three miR34a-targeted mRNAs and two miR-195-targeted mRNAs were downregulated while one miR-195-targeted mRNA was upregulated. Biological pathway analysis of RISC mRNA components suggests that the RISC plays a pivotal role in malignancy and other conditions. This study points to the importance of the RISC and ultimately GW/P body composition and function in miRNA and mRNA deregulation in astrocytoma cells and possibly in other malignancies

In vitro nuclear interactome of the HIV-1 Tat protein

<p>Abstract</p> <p>Background</p> <p>One facet of the complexity underlying the biology of HIV-1 resides not only in its limited number of viral proteins, but in the extensive repertoire of cellular proteins they interact with and their higher-order assembly. HIV-1 encodes the regulatory protein Tat (86–101aa), which is essential for HIV-1 replication and primarily orchestrates HIV-1 provirus transcriptional regulation. Previous studies have demonstrated that Tat function is highly dependent on specific interactions with a range of cellular proteins. However they can only partially account for the intricate molecular mechanisms underlying the dynamics of proviral gene expression. To obtain a comprehensive nuclear interaction map of Tat in T-cells, we have designed a proteomic strategy based on affinity chromatography coupled with mass spectrometry.</p> <p>Results</p> <p>Our approach resulted in the identification of a total of 183 candidates as Tat nuclear partners, 90% of which have not been previously characterised. Subsequently we applied <it>in silico </it>analysis, to validate and characterise our dataset which revealed that the Tat nuclear interactome exhibits unique signature(s). First, motif composition analysis highlighted that our dataset is enriched for domains mediating protein, RNA and DNA interactions, and helicase and ATPase activities. Secondly, functional classification and network reconstruction clearly depicted Tat as a polyvalent protein adaptor and positioned Tat at the nexus of a densely interconnected interaction network involved in a range of biological processes which included gene expression regulation, RNA biogenesis, chromatin structure, chromosome organisation, DNA replication and nuclear architecture.</p> <p>Conclusion</p> <p>We have completed the <it>in vitro </it>Tat nuclear interactome and have highlighted its modular network properties and particularly those involved in the coordination of gene expression by Tat. Ultimately, the highly specialised set of molecular interactions identified will provide a framework to further advance our understanding of the mechanisms of HIV-1 proviral gene silencing and activation.</p

Representativeness of Eddy-Covariance flux footprints for areas surrounding AmeriFlux sites

Large datasets of greenhouse gas and energy surface-atmosphere fluxes measured with the eddy-covariance technique (e.g., FLUXNET2015, AmeriFlux BASE) are widely used to benchmark models and remote-sensing products. This study addresses one of the major challenges facing model-data integration: To what spatial extent do flux measurements taken at individual eddy-covariance sites reflect model- or satellite-based grid cells? We evaluate flux footprints—the temporally dynamic source areas that contribute to measured fluxes—and the representativeness of these footprints for target areas (e.g., within 250–3000 m radii around flux towers) that are often used in flux-data synthesis and modeling studies. We examine the land-cover composition and vegetation characteristics, represented here by the Enhanced Vegetation Index (EVI), in the flux footprints and target areas across 214 AmeriFlux sites, and evaluate potential biases as a consequence of the footprint-to-target-area mismatch. Monthly 80% footprint climatologies vary across sites and through time ranging four orders of magnitude from 103 to 107 m2 due to the measurement heights, underlying vegetation- and ground-surface characteristics, wind directions, and turbulent state of the atmosphere. Few eddy-covariance sites are located in a truly homogeneous landscape. Thus, the common model-data integration approaches that use a fixed-extent target area across sites introduce biases on the order of 4%–20% for EVI and 6%–20% for the dominant land cover percentage. These biases are site-specific functions of measurement heights, target area extents, and land-surface characteristics. We advocate that flux datasets need to be used with footprint awareness, especially in research and applications that benchmark against models and data products with explicit spatial information. We propose a simple representativeness index based on our evaluations that can be used as a guide to identify site-periods suitable for specific applications and to provide general guidance for data use