Recombineering and stable integration of the Pseudomonas syringae pv. syringae 61 hrp/hrc cluster into the genome of the soil bacterium Pseudomonas fluorescens Pf0-1

Many Gram-negative bacteria use a type III secretion system (T3SS) to establish associations with their hosts. The T3SS is a conduit for direct injection of type-III effector proteins into host cells, where they manipulate the host for the benefit of the infecting bacterium. For plant-associated pathogens, the variations in number and amino acid sequences of type-III effectors, as well as their functional redundancy, make studying type-III effectors challenging. To mitigate this challenge, we developed a stable delivery system for individual or defined sets of type-III effectors into plant cells. We used recombineering and Tn5-mediated transposition to clone and stably integrate, respectively, the complete hrp/hrc region from Pseudomonas syringae pv. syringae 61 into the genome of the soil bacterium Pseudomonas fluorescens Pf0-1. We describe our development of Effector-to-Host Analyzer (EtHAn), and demonstrate its utility for studying effectors for their in planta functions.Keywords: Pseudomonas syringae, plant defense, virulence, type-III secretion system, hrp/hrc, type-III effector

An improved, high-quality draft genome sequence of the Germination-Arrest Factor-producing Pseudomonas fluorescens WH6

<p>Abstract</p> <p>Background</p> <p><it>Pseudomonas fluorescens </it>is a genetically and physiologically diverse species of bacteria present in many habitats and in association with plants. This species of bacteria produces a large array of secondary metabolites with potential as natural products. <it>P. fluorescens </it>isolate WH6 produces Germination-Arrest Factor (GAF), a predicted small peptide or amino acid analog with herbicidal activity that specifically inhibits germination of seeds of graminaceous species.</p> <p>Results</p> <p>We used a hybrid next-generation sequencing approach to develop a high-quality draft genome sequence for <it>P. fluorescens </it>WH6. We employed automated, manual, and experimental methods to further improve the draft genome sequence. From this assembly of 6.27 megabases, we predicted 5876 genes, of which 3115 were core to <it>P. fluorescens </it>and 1567 were unique to WH6. Comparative genomic studies of WH6 revealed high similarity in synteny and orthology of genes with <it>P. fluorescens </it>SBW25. A phylogenomic study also placed WH6 in the same lineage as SBW25. In a previous non-saturating mutagenesis screen we identified two genes necessary for GAF activity in WH6. Mapping of their flanking sequences revealed genes that encode a candidate anti-sigma factor and an aminotransferase. Finally, we discovered several candidate virulence and host-association mechanisms, one of which appears to be a complete type III secretion system.</p> <p>Conclusions</p> <p>The improved high-quality draft genome sequence of WH6 contributes towards resolving the <it>P. fluorescens </it>species, providing additional impetus for establishing two separate lineages in <it>P. fluorescens</it>. Despite the high levels of orthology and synteny to SBW25, WH6 still had a substantial number of unique genes and represents another source for the discovery of genes with implications in affecting plant growth and health. Two genes are demonstrably necessary for GAF and further characterization of their proteins is important for developing natural products as control measure against grassy weeds. Finally, WH6 is the first isolate of <it>P. fluorescens </it>reported to encode a complete T3SS. This gives us the opportunity to explore the role of what has traditionally been thought of as a virulence mechanism for non-pathogenic interactions with plants.</p

Higher order asymptotics for negative binomial regression inferences from RNA-sequencing data

RNA sequencing (RNA-Seq) is the current method of choice for characterizing transcriptomes and quantifying gene expression changes. This next generation sequencing-based method provides unprecedented depth and resolution. The negative binomial (NB) probability distribution has been shown to be a useful model for frequencies of mapped RNA-Seq reads and consequently provides a basis for statistical analysis of gene expression. Negative binomial exact tests are available for two-group comparisons but do not extend to negative binomial regression analysis, which is important for examining gene expression as a function of explanatory variables and for adjusted group comparisons accounting for other factors. We address the adequacy of available large-sample tests for the small sample sizes typically available from RNA-Seq studies and consider a higher-order asymptotic (HOA) adjustment to likelihood ratio tests. We demonstrate that 1) the HOA-adjusted likelihood ratio test is practically indistinguishable from the exact test in situations where the exact test is available, 2) the type I error of the HOA test matches the nominal specification in regression settings we examined via simulation, and 3) the power of the likelihood ratio test does not appear to be affected by the HOA adjustment. This work helps clarify the accuracy of the unadjusted likelihood ratio test and the degree of improvement available with the HOA adjustment. Furthermore, the HOA test may be preferable even when the exact test is available because it does not require ad hoc library size adjustments.Keywords: Regression, RNA-Seq, Overdispersion, Extra- Poisson variation, Negative binomial, Higher-order asymptotic

Microbial Community Structure and Functional Potential Along a Hypersaline Gradient

Salinity is one of the strongest environmental drivers of microbial evolution and community composition. Here we aimed to determine the impact of salt concentrations (2.5, 7.5, and 33.2%) on the microbial community structure of reclaimed saltern ponds near San Francisco, California, and to discover prospective enzymes with potential biotechnological applications. Community compositions were determined by 16S rRNA amplicon sequencing revealing both higher richness and evenness in the pond sediments compared to the water columns. Co-occurrence network analysis additionally uncovered the presence of microbial seed bank communities, potentially primed to respond to rapid changes in salinity. In addition, functional annotation of shotgun metagenomic DNA showed different capabilities if the microbial communities at different salinities for methanogenesis, amino acid metabolism, and carbohydrate-active enzymes. There was an overall shift with increasing salinity in the functional potential for starch degradation, and a decrease in degradation of cellulose and other oligosaccharides. Further, many carbohydrate-active enzymes identified have acidic isoelectric points that have potential biotechnological applications, including deconstruction of biofuel feedstocks under high ionic conditions. Metagenome-assembled genomes (MAGs) of individual halotolerant and halophilic microbes were binned revealing a variety of carbohydrate-degrading potential of individual pond inhabitants

Mutualistic Co-evolution of Type III Effector Genes in Sinorhizobium fredii and Bradyrhizobium japonicum

Two diametric paradigms have been proposed to model the molecular co-evolution of microbial mutualists and their eukaryotic hosts. In one, mutualist and host exhibit an antagonistic arms race and each partner evolves rapidly to maximize their own fitness from the interaction at potential expense of the other. In the opposing model, conflicts between mutualist and host are largely resolved and the interaction is characterized by evolutionary stasis. We tested these opposing frameworks in two lineages of mutualistic rhizobia, Sinorhizobium fredii and Bradyrhizobium japonicum. To examine genes demonstrably important for host-interactions we coupled the mining of genome sequences to a comprehensive functional screen for type III effector genes, which are necessary for many Gram-negative pathogens to infect their hosts. We demonstrate that the rhizobial type III effector genes exhibit a surprisingly high degree of conservation in content and sequence that is in contrast to those of a well characterized plant pathogenic species. This type III effector gene conservation is particularly striking in the context of the relatively high genome-wide diversity of rhizobia. The evolution of rhizobial type III effectors is inconsistent with the molecular arms race paradigm. Instead, our results reveal that these loci are relatively static in rhizobial lineages and suggest that fitness conflicts between rhizobia mutualists and their host plants have been largely resolved

The path from root input to mineral-associated soil carbon is dictated by habitat-specific microbial traits and soil moisture

Soil microorganisms help transform plant inputs into mineral-associated soil organic carbon (SOC) – the largest and slowest-cycling pool of organic carbon on land. However, the microbial traits that influence this process are widely debated. While current theory and biogeochemical models have settled on carbon-use efficiency (CUE) and growth rate as positive predictors of mineral-associated SOC, empirical tests are sparse, with contradictory observations. Using 13C-labeling of an annual grass (Avena barbata) under two moisture regimes, we found that microbial traits associated with formation of 13C-mineral-associated SOC varied by soil habitat, as did active microbial taxa and SOC chemical composition. In the rhizosphere, bacterial-dominated communities with fast growth, high biomass, and high extracellular polymeric substance (EPS) production were positively associated with 13C-mineral-associated SOC. In contrast, the detritusphere held communities dominated by fungi and more filamentous bacteria, and with greater exoenzyme activity; there, 13C-mineral-associated SOC was associated with slower microbial growth and lower microbial biomass. CUE was a negative predictor of 13C-mineral-associated SOC in both habitats. Using 13C-quantitative stable isotope probing, we found that the majority of 13C assimilation in the rhizosphere and detritusphere at week 12 of the experiment was performed by very few bacterial and fungal taxa (3–5% of the total taxa that assimilated 13C). Several complementary chemical analyses (13C-NMR, FTICR-MS, and STXM-NEXAFS) suggested that SOC in the rhizosphere had a more oxidized chemical signature, while SOC in the detritusphere had a less oxidized, more lignin-like chemical signature. Our findings challenge current theory by demonstrating that microbial traits linked with mineral-associated SOC are not universal, but vary with soil habitat and moisture conditions, and are shaped by a small number of active taxa. Emerging SOC models that explicitly reflect these interactions may better predict SOC storage, since climate change causes shifts in soil moisture regimes and the ratio of living versus decaying roots

The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes

In the Abstract, the url https://modelseed.org has been replaced with https://modelseed.org/biochem

Metagenomics reveals sediment microbial community response to Deepwater Horizon oil spill

The Deepwater Horizon (DWH) oil spill in the spring of 2010 resulted in an input of ∼4.1 million barrels of oil to the Gulf of Mexico; >22% of this oil is unaccounted for, with unknown environmental consequences. Here we investigated the impact of oil deposition on microbial communities in surface sediments collected at 64 sites by targeted sequencing of 16S rRNA genes, shotgun metagenomic sequencing of 14 of these samples and mineralization experiments using (14)C-labeled model substrates. The 16S rRNA gene data indicated that the most heavily oil-impacted sediments were enriched in an uncultured Gammaproteobacterium and a Colwellia species, both of which were highly similar to sequences in the DWH deep-sea hydrocarbon plume. The primary drivers in structuring the microbial community were nitrogen and hydrocarbons. Annotation of unassembled metagenomic data revealed the most abundant hydrocarbon degradation pathway encoded genes involved in degrading aliphatic and simple aromatics via butane monooxygenase. The activity of key hydrocarbon degradation pathways by sediment microbes was confirmed by determining the mineralization of (14)C-labeled model substrates in the following order: propylene glycol, dodecane, toluene and phenanthrene. Further, analysis of metagenomic sequence data revealed an increase in abundance of genes involved in denitrification pathways in samples that exceeded the Environmental Protection Agency (EPA)'s benchmarks for polycyclic aromatic hydrocarbons (PAHs) compared with those that did not. Importantly, these data demonstrate that the indigenous sediment microbiota contributed an important ecosystem service for remediation of oil in the Gulf. However, PAHs were more recalcitrant to degradation, and their persistence could have deleterious impacts on the sediment ecosystem

GENE-Counter: A Computational Pipeline for the Analysis of RNA-Seq Data for Gene Expression Differences

GENE-counter is a complete Perl-based computational pipeline for analyzing RNA-Sequencing (RNA-Seq) data for differential gene expression. In addition to its use in studying transcriptomes of eukaryotic model organisms, GENE-counter is applicable for prokaryotes and non-model organisms without an available genome reference sequence. For alignments, GENE-counter is configured for CASHX, Bowtie, and BWA, but an end user can use any Sequence Alignment/Map (SAM)-compliant program of preference. To analyze data for differential gene expression, GENE-counter can be run with any one of three statistics packages that are based on variations of the negative binomial distribution. The default method is a new and simple statistical test we developed based on an over-parameterized version of the negative binomial distribution. GENE-counter also includes three different methods for assessing differentially expressed features for enriched gene ontology (GO) terms. Results are transparent and data are systematically stored in a MySQL relational database to facilitate additional analyses as well as quality assessment. We used next generation sequencing to generate a small-scale RNA-Seq dataset derived from the heavily studied defense response of Arabidopsis thaliana and used GENE-counter to process the data. Collectively, the support from analysis of microarrays as well as the observed and substantial overlap in results from each of the three statistics packages demonstrates that GENE-counter is well suited for handling the unique characteristics of small sample sizes and high variability in gene counts

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder