Genomic analysis and temperature-dependent transcriptome profiles of the rhizosphere originating strain Pseudomonas aeruginosa M18

<p>Abstract</p> <p>Background</p> <p>Our previously published reports have described an effective biocontrol agent named <it>Pseudomonas </it>sp. M18 as its 16S rDNA sequence and several regulator genes share homologous sequences with those of <it>P. aeruginosa</it>, but there are several unusual phenotypic features. This study aims to explore its strain specific genomic features and gene expression patterns at different temperatures.</p> <p>Results</p> <p>The complete M18 genome is composed of a single chromosome of 6,327,754 base pairs containing 5684 open reading frames. Seven genomic islands, including two novel prophages and five specific non-phage islands were identified besides the conserved <it>P. aeruginosa </it>core genome. Each prophage contains a putative chitinase coding gene, and the prophage II contains a <it>capB </it>gene encoding a putative cold stress protein. The non-phage genomic islands contain genes responsible for pyoluteorin biosynthesis, environmental substance degradation and type I and III restriction-modification systems. Compared with other <it>P. aeruginosa </it>strains, the fewest number (3) of insertion sequences and the most number (3) of clustered regularly interspaced short palindromic repeats in M18 genome may contribute to the relative genome stability. Although the M18 genome is most closely related to that of <it>P. aeruginosa </it>strain LESB58, the strain M18 is more susceptible to several antimicrobial agents and easier to be erased in a mouse acute lung infection model than the strain LESB58. The whole M18 transcriptomic analysis indicated that 10.6% of the expressed genes are temperature-dependent, with 22 genes up-regulated at 28°C in three non-phage genomic islands and one prophage but none at 37°C.</p> <p>Conclusions</p> <p>The <it>P. aeruginosa </it>strain M18 has evolved its specific genomic structures and temperature dependent expression patterns to meet the requirement of its fitness and competitiveness under selective pressures imposed on the strain in rhizosphere niche.</p

Targeted metatranscriptomics of compost derived consortia reveals a GH11 exerting an unusual exo-1,4-β-xylanase activity

Background: Using globally abundant crop residues as a carbon source for energy generation and renewable chemicals production stands out as a promising solution to reduce current dependency on fossil fuels. In nature, such as in compost habitats, microbial communities efficiently degrade the available plant biomass using a diverse set of synergistic enzymes. However, deconstruction of lignocellulose remains a challenge for industry due to recalcitrant nature of the substrate and the inefficiency of the enzyme systems available, making the economic production of lignocellulosic biofuels difficult. Metatranscriptomic studies of microbial communities can unveil the metabolic functions employed by lignocellulolytic consortia and identify new biocatalysts that could improve industrial lignocellulose conversion. Results: In this study, a microbial community from compost was grown in minimal medium with sugarcane bagasse sugarcane bagasse as the sole carbon source. Solid-state nuclear magnetic resonance was used to monitor lignocellulose degradation; analysis of metatranscriptomic data led to the selection and functional characterization of several target genes, revealing the first glycoside hydrolase from Carbohydrate Active Enzyme family 11 with exo-1,4-β-xylanase activity. The xylanase crystal structure was resolved at 1.76 Å revealing the structural basis of exo-xylanase activity. Supplementation of a commercial cellulolytic enzyme cocktail with the xylanase showed improvement in Avicel hydrolysis in the presence of inhibitory xylooligomers. Conclusions: This study demonstrated that composting microbiomes continue to be an excellent source of biotechnologically important enzymes by unveiling the diversity of enzymes involved in in situ lignocellulose degradation

Prediction and estimation of effective population size

Effective population size (Ne) is a key parameter in population genetics. It has important applications in evolutionary biology, conservation genetics, and plant and animal breeding, because it measures the rates of genetic drift and inbreeding and affects the efficacy of systematic evolutionary forces such as mutation, selection and migration. We review the developments in predictive equations and estimation methodologies of effective size. In the prediction part, we focus on the equations for populations with different modes of reproduction, for populations under selection for unlinked or linked loci, and for the specific applications to conservation genetics. In the estimation part, we focus on methods developed for estimating the current or recent effective size from molecular marker or sequence data. We discuss some underdeveloped areas in predicting and estimating Ne for future research