(Are) you coming? Parent Question Types to their Children in the Earliest Stages of Grammatical Development

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Differential RhoA Dynamics in Migratory and Stationary Cells Measured by FRET and Automated Image Analysis

Genetically-encoded biosensors based on fluorescence resonance energy transfer (FRET) have been widely applied to study the spatiotemporal regulation of molecular activity in live cells with high resolution. The efficient and accurate quantification of the large amount of imaging data from these single-cell FRET measurements demands robust and automated data analysis. However, the nonlinear movement of live cells presents tremendous challenge for this task. Based on image registration of the single-cell movement, we have developed automated image analysis methods to track and quantify the FRET signals within user-defined subcellular regions. In addition, the subcellular pixels were classified according to their associated FRET signals and the dynamics of the clusters analyzed. The results revealed that the EGF-induced reduction of RhoA activity in migratory HeLa cells is significantly less than that in stationary cells. Furthermore, the RhoA activity is polarized in the migratory cells, with the gradient of polarity oriented toward the opposite direction of cell migration. In contrast, there is a lack of consistent preference in RhoA polarity among stationary cells. Therefore, our image analysis methods can provide powerful tools for high-throughput and systematic investigation of the spatiotemporal molecular activities in regulating functions of live cells with their shapes and positions continuously changing in time

Complementary Metagenomic Approaches Improve Reconstruction of Microbial Diversity in a Forest Soil.

Soil ecosystems harbor diverse microorganisms and yet remain only partially characterized as neither single-cell sequencing nor whole-community sequencing offers a complete picture of these complex communities. Thus, the genetic and metabolic potential of this "uncultivated majority" remains underexplored. To address these challenges, we applied a pooled-cell-sorting-based mini-metagenomics approach and compared the results to bulk metagenomics. Informatic binning of these data produced 200 mini-metagenome assembled genomes (sorted-MAGs) and 29 bulk metagenome assembled genomes (MAGs). The sorted and bulk MAGs increased the known phylogenetic diversity of soil taxa by 7.2% with respect to the Joint Genome Institute IMG/M database and showed clade-specific sequence recruitment patterns across diverse terrestrial soil metagenomes. Additionally, sorted-MAGs expanded the rare biosphere not captured through MAGs from bulk sequences, exemplified through phylogenetic and functional analyses of members of the phylum Bacteroidetes Analysis of 67 Bacteroidetes sorted-MAGs showed conserved patterns of carbon metabolism across four clades. These results indicate that mini-metagenomics enables genome-resolved investigation of predicted metabolism and demonstrates the utility of combining metagenomics methods to tap into the diversity of heterogeneous microbial assemblages.IMPORTANCE Microbial ecologists have historically used cultivation-based approaches as well as amplicon sequencing and shotgun metagenomics to characterize microbial diversity in soil. However, challenges persist in the study of microbial diversity, including the recalcitrance of the majority of microorganisms to laboratory cultivation and limited sequence assembly from highly complex samples. The uncultivated majority thus remains a reservoir of untapped genetic diversity. To address some of the challenges associated with bulk metagenomics as well as low throughput of single-cell genomics, we applied flow cytometry-enabled mini-metagenomics to capture expanded microbial diversity from forest soil and compare it to soil bulk metagenomics. Our resulting data from this pooled-cell sorting approach combined with bulk metagenomics revealed increased phylogenetic diversity through novel soil taxa and rare biosphere members. In-depth analysis of genomes within the highly represented Bacteroidetes phylum provided insights into conserved and clade-specific patterns of carbon metabolism

One Complete and Seven Draft Genome Sequences of Subdivision 1 and 3 Acidobacteria Isolated from Soil.

We report eight genomes from representatives of the phylum Acidobacteria subdivisions 1 and 3, isolated from soils. The genome sizes range from 4.9 to 6.7 Mb. Genomic analysis reveals putative genes for low- and high-affinity respiratory oxygen reductases, high-affinity hydrogenases, and the capacity to use a diverse collection of carbohydrates

Biological Consequences of Ancient Gene Acquisition and Duplication in the Large Genome of Candidatus Solibacter usitatus Ellin6076

Members of the bacterial phylum Acidobacteria are widespread in soils and sediments worldwide, and are abundant in many soils. Acidobacteria are challenging to culture in vitro, and many basic features of their biology and functional roles in the soil have not been determined. Candidatus Solibacter usitatus strain Ellin6076 has a 9.9 Mb genome that is approximately 2–5 times as large as the other sequenced Acidobacteria genomes. Bacterial genome sizes typically range from 0.5 to 10 Mb and are influenced by gene duplication, horizontal gene transfer, gene loss and other evolutionary processes. Our comparative genome analyses indicate that the Ellin6076 large genome has arisen by horizontal gene transfer via ancient bacteriophage and/or plasmid-mediated transduction, and widespread small-scale gene duplications, resulting in an increased number of paralogs. Low amino acid sequence identities among functional group members, and lack of conserved gene order and orientation in regions containing similar groups of paralogs, suggest that most of the paralogs are not the result of recent duplication events. The genome sizes of additional cultured Acidobacteria strains were estimated using pulsed-field gel electrophoresis to determine the prevalence of the large genome trait within the phylum. Members of subdivision 3 had larger genomes than those of subdivision 1, but none were as large as the Ellin6076 genome. The large genome of Ellin6076 may not be typical of the phylum, and encodes traits that could provide a selective metabolic, defensive and regulatory advantage in the soil environment

Nitrogen Fertilization Has a Stronger Effect on Soil Nitrogen-Fixing Bacterial Communities than Elevated Atmospheric CO2

Biological nitrogen fixation is the primary supply of N to most ecosystems, yet there is considerable uncertainty about how N-fixing bacteria will respond to global change factors such as increasing atmospheric CO2 and N deposition. Using the nifH gene as a molecular marker, we studied how the community structure of N-fixing soil bacteria from temperate pine, aspen, and sweet gum stands and a brackish tidal marsh responded to multiyear elevated CO2 conditions. We also examined how N availability, specifically, N fertilization, interacted with elevated CO2 to affect these communities in the temperate pine forest. Based on data from Sanger sequencing and quantitative PCR, the soil nifH composition in the three forest systems was dominated by species in the Geobacteraceae and, to a lesser extent, Alphaproteobacteria. The N-fixing-bacterial-community structure was subtly altered after 10 or more years of elevated atmospheric CO2, and the observed shifts differed in each biome. In the pine forest, N fertilization had a stronger effect on nifH community structure than elevated CO2 and suppressed the diversity and abundance of N-fixing bacteria under elevated atmospheric CO2 conditions. These results indicate that N-fixing bacteria have complex, interacting responses that will be important for understanding ecosystem productivity in a changing climate

TopFish: topic-based analysis of political position in US electoral campaigns

In this paper we present TopFish, a multilevel computational method that integrates topic detection and political scaling and shows its applicability for a temporal aspect analysis of political campaigns (preprimary elections, primary elections, and general elections). It enables researchers to perform a range of multidimensional empirical analyses, ultimately allowing them to better understand how candidates position themselves during elections, with respect to a specific topic. The approach has been employed and tested on speeches from the 2008, 2012, and the (ongoing) 2016 US presidential campaigns

Complementary Metagenomic Approaches Improve Reconstruction of Microbial Diversity in a Forest Soil

Soil ecosystems harbor diverse microorganisms and yet remain only partially characterized as neither single-cell sequencing nor whole-community sequencing offers a complete picture of these complex communities. Thus, the genetic and metabolic potential of this “uncultivated majority” remains underexplored. To address these challenges, we applied a pooled-cell-sorting-based mini-metagenomics approach and compared the results to bulk metagenomics. Informatic binning of these data produced 200 mini-metagenome assembled genomes (sorted-MAGs) and 29 bulk metagenome assembled genomes (MAGs). The sorted and bulk MAGs increased the known phylogenetic diversity of soil taxa by 7.2% with respect to the Joint Genome Institute IMG/M database and showed clade-specific sequence recruitment patterns across diverse terrestrial soil metagenomes. Additionally, sorted-MAGs expanded the rare biosphere not captured through MAGs from bulk sequences, exemplified through phylogenetic and functional analyses of members of the phylum Bacteroidetes. Analysis of 67 Bacteroidetes sorted-MAGs showed conserved patterns of carbon metabolism across four clades. These results indicate that mini-metagenomics enables genome-resolved investigation of predicted metabolism and demonstrates the utility of combining metagenomics methods to tap into the diversity of heterogeneous microbial assemblages. IMPORTANCE Microbial ecologists have historically used cultivation-based approaches as well as amplicon sequencing and shotgun metagenomics to characterize microbial diversity in soil. However, challenges persist in the study of microbial diversity, including the recalcitrance of the majority of microorganisms to laboratory cultivation and limited sequence assembly from highly complex samples. The uncultivated majority thus remains a reservoir of untapped genetic diversity. To address some of the challenges associated with bulk metagenomics as well as low throughput of single-cell genomics, we applied flow cytometry-enabled mini-metagenomics to capture expanded microbial diversity from forest soil and compare it to soil bulk metagenomics. Our resulting data from this pooled-cell sorting approach combined with bulk metagenomics revealed increased phylogenetic diversity through novel soil taxa and rare biosphere members. In-depth analysis of genomes within the highly represented Bacteroidetes phylum provided insights into conserved and clade-specific patterns of carbon metabolism

3D time series analysis of cell shape using Laplacian approaches

Background: Fundamental cellular processes such as cell movement, division or food uptake critically depend on cells being able to change shape. Fast acquisition of three-dimensional image time series has now become possible, but we lack efficient tools for analysing shape deformations in order to understand the real three-dimensional nature of shape changes. Results: We present a framework for 3D+time cell shape analysis. The main contribution is three-fold: First, we develop a fast, automatic random walker method for cell segmentation. Second, a novel topology fixing method is proposed to fix segmented binary volumes without spherical topology. Third, we show that algorithms used for each individual step of the analysis pipeline (cell segmentation, topology fixing, spherical parameterization, and shape representation) are closely related to the Laplacian operator. The framework is applied to the shape analysis of neutrophil cells. Conclusions: The method we propose for cell segmentation is faster than the traditional random walker method or the level set method, and performs better on 3D time-series of neutrophil cells, which are comparatively noisy as stacks have to be acquired fast enough to account for cell motion. Our method for topology fixing outperforms the tools provided by SPHARM-MAT and SPHARM-PDM in terms of their successful fixing rates. The different tasks in the presented pipeline for 3D+time shape analysis of cells can be solved using Laplacian approaches, opening the possibility of eventually combining individual steps in order to speed up computations