nifH pyrosequencing reveals the potential for location-specific soil chemistry to influence N2-fixing community dynamics

A dataset of 87 020 nifH reads and 16 782 unique nifH protein sequences obtained over 2 years from four locations across a gradient of agricultural soil types in Argentina were analysed to provide a detailed and comprehensive picture of the diversity, abundance and responses of the N2-fixing community in relation to differences in soil chemistry and agricultural practices. Phylogenetic analysis revealed an expected high proportion of Alphaproteobacteria, Betaproteobacteria and Deltaproteobacteria, mainly relatives to Bradyrhizobium and Methylosinus/Methylocystis, but a surprising paucity of Gammaproteobacteria. Analysis of variance and stepwise regression modelling suggested location and treatment-specific influences of soil type on diazotrophic community composition and organic carbon concentrations on nifH diversity. nifH gene abundance, determined by quantitative real-time polymerase chain reaction, was higher in agricultural soils than in non-agricultural soils, and was influenced by soil chemistry under intensive crop rotation but not under monoculture. At some locations, sustainable increased crop yields might be possible through the management of soil chemistry to improve the abundance and diversity of N2-fixing bacteriaFil: Collavino, Mónica Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Nordeste. Instituto de Botánica del Nordeste (i); Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Instituto de Biotecnología y Biología Molecular; ArgentinaFil: Tripp, H. James. University of California. Department of Ocean Sciences; Estados UnidosFil: Frank, Ildiko E.. University of California. Department of Ocean Sciences; Estados UnidosFil: Vidoz, María Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Nordeste. Instituto de Botánica del Nordeste (i); ArgentinaFil: Calderoli, Priscila Anabel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Instituto de Biotecnología y Biología Molecular; ArgentinaFil: Donato, Mariano Humberto. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Laboratorio de Sistemática y Biología Evolutiva; ArgentinaFil: Zehr, Jonathan P.. University of California. Department of Ocean Sciences; Estados UnidosFil: Aguilar, Orlando Mario. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico La Plata. Instituto de Biotecnología y Biología Molecular; Argentin

nifH pyrosequencing reveals the potential for location-specific soil chemistry to influence N₂-fixing community dynamics

A dataset of 87 020 nifH reads and 16 782 unique nifH protein sequences obtained over 2 years from four locations across a gradient of agricultural soil types in Argentina were analysed to provide a detailed and comprehensive picture of the diversity, abundance and responses of the N₂-fixing community in relation to differences in soil chemistry and agricultural practices. Phylogenetic analysis revealed an expected high proportion of Alphaproteobacteria, Betaproteobacteria and Deltaproteobacteria, mainly relatives to Bradyrhizobium and Methylosinus/Methylocystis, but a surprising paucity of Gammaproteobacteria. Analysis of variance and stepwise regression modelling suggested location and treatment-specific influences of soil type on diazotrophic community composition and organic carbon concentrations on nifH diversity. nifH gene abundance, determined by quantitative real-time polymerase chain reaction, was higher in agricultural soils than in non-agricultural soils, and was influenced by soil chemistry under intensive crop rotation but not under monoculture. At some locations, sustainable increased crop yields might be possible through the management of soil chemistry to improve the abundance and diversity of N₂-fixing bacteria.Facultad de Ciencias ExactasInstituto de Biotecnologia y Biologia MolecularFacultad de Ciencias Naturales y MuseoLaboratorio de Sistemática y Biología Evolutiv

Rapid Classification of NifH Protein Sequences using Classification and Regression Trees

Grouping and classifying nifH gene sequences, molecular proxies for studying nitrogen fixation, are essential steps in diazotroph community analysis, and the increasing size of environmental sequence libraries necessitates a fast and automated solution. We present a novel approach to classify NifH protein sequences into well-defined phylogenetic clusters that provide a common platform for cross-ecosystem comparative analysis. Cluster membership can be accurately predicted with Classification and Regression Trees (CART) statistical models that identify and utilize signature residues in the protein sequences. The decision tree-based classification models were trained and evaluated with the publicly available cluster-annotated nifH gene database and further assessed with model-independent sequence sets from diverse ecosystems. Network graph-based exploration of cluster structures led to models for sequence classification even at finer taxonomic levels. We demonstrate the utility of this novel sequence binning approach in a comparative study where joint treatment of diazotroph assemblages from a wide range of habitats identified specialists and generalists and revealed a marine - terrestrial distinction in the community composition. Our rapid and automated cluster assignment circumvents extensive analysis of the nifH database and calculating phylogenies; hence, saves time and resources in studying nitrogen fixation

Rapid annotation of nifH gene sequences using classification and regression trees facilitates environmental functional gene analysis.

The nifH gene is a widely used molecular proxy for studying nitrogen fixation. Phylogenetic classification of nifH gene sequences is an essential step in diazotroph community analysis that requires a fast automated solution due to increasing size of environmental sequence libraries and increasing yield of nifH sequences from high-throughput technologies. A novel approach to rapidly classify nifH amino acid sequences into well-defined phylogenetic clusters that provides a common platform for comparative analysis across studies is presented. Phylogenetic group membership can be accurately predicted with decision tree-type statistical models that identify and utilize signature residues in the amino acid sequences. Our classification models were trained and evaluated with a publicly available and manually curated nifH gene database containing cluster annotations. Model-independent sequence sets from diverse ecosystems were used for further assessment of the models' prediction accuracy. The utility of this novel sequence binning approach was demonstrated in a comparative study where joint treatment of diazotroph assemblages from a wide range of habitats identified habitat-specific and widely-distributed diazotrophs and revealed a marine - terrestrial distinction in community composition. Our rapid and automated phylogenetic cluster assignment circumvents extensive phylogenetic analysis of nifH sequences; hence, it saves substantial time and resources in nitrogen fixation studies

Rapid annotation of nifH gene sequences using classification and regression trees facilitates environmental functional gene analysis.

The nifH gene is a widely used molecular proxy for studying nitrogen fixation. Phylogenetic classification of nifH gene sequences is an essential step in diazotroph community analysis that requires a fast automated solution due to increasing size of environmental sequence libraries and increasing yield of nifH sequences from high-throughput technologies. A novel approach to rapidly classify nifH amino acid sequences into well-defined phylogenetic clusters that provides a common platform for comparative analysis across studies is presented. Phylogenetic group membership can be accurately predicted with decision tree-type statistical models that identify and utilize signature residues in the amino acid sequences. Our classification models were trained and evaluated with a publicly available and manually curated nifH gene database containing cluster annotations. Model-independent sequence sets from diverse ecosystems were used for further assessment of the models' prediction accuracy. The utility of this novel sequence binning approach was demonstrated in a comparative study where joint treatment of diazotroph assemblages from a wide range of habitats identified habitat-specific and widely-distributed diazotrophs and revealed a marine - terrestrial distinction in community composition. Our rapid and automated phylogenetic cluster assignment circumvents extensive phylogenetic analysis of nifH sequences; hence, it saves substantial time and resources in nitrogen fixation studies

nifH pyrosequencing reveals the potential for location-specific soil chemistry to influence N2 -fixing community dynamics.

A dataset of 87 020 nifH reads and 16 782 unique nifH protein sequences obtained over 2 years from four locations across a gradient of agricultural soil types in Argentina were analysed to provide a detailed and comprehensive picture of the diversity, abundance and responses of the N2 -fixing community in relation to differences in soil chemistry and agricultural practices. Phylogenetic analysis revealed an expected high proportion of Alphaproteobacteria, Betaproteobacteria and Deltaproteobacteria, mainly relatives to Bradyrhizobium and Methylosinus/Methylocystis, but a surprising paucity of Gammaproteobacteria. Analysis of variance and stepwise regression modelling suggested location and treatment-specific influences of soil type on diazotrophic community composition and organic carbon concentrations on nifH diversity. nifH gene abundance, determined by quantitative real-time polymerase chain reaction, was higher in agricultural soils than in non-agricultural soils, and was influenced by soil chemistry under intensive crop rotation but not under monoculture. At some locations, sustainable increased crop yields might be possible through the management of soil chemistry to improve the abundance and diversity of N2 -fixing bacteria

The methyltransferase Setdb2 mediates virus-induced susceptibility to bacterial superinfection

Immune responses are tightly regulated to ensure efficient pathogen clearance while avoiding tissue damage. Here we report that SET domain bifurcated 2 (Setdb2) was the only protein lysine methyltransferase induced during influenza virus infection. Setdb2 expression depended on type-I interferon signaling and it repressed the expression of the neutrophil attractant Cxcl1 and other NF-κB target genes. This coincided with Setdb2 occupancy at the Cxcl1 promoter, which in the absence of Setdb2 displayed reduced H3K9 tri-methylation. Setdb2 hypomorphic gene-trap mice exhibited increased neutrophil infiltration in sterile lung inflammation and were less sensitive to bacterial superinfection upon influenza virus infection. This suggests that a Setdb2-mediated regulatory crosstalk between the type-I interferon and NF-κB pathways represents an important mechanism for virus-induced susceptibility to bacterial superinfection