Genome sequencing and assessment of plant growth-promoting properties of a Serratia marcescens strain isolated from vermicompost.

BACKGROUND: Plant-bacteria associations have been extensively studied for their potential in increasing crop productivity in a sustainable manner. Serratia marcescens is a species of Enterobacteriaceae found in a wide range of environments, including soil. RESULTS: Here we describe the genome sequencing and assessment of plant growth-promoting abilities of S. marcescens UENF-22GI, a strain isolated from mature cattle manure vermicompost. In vitro, S. marcescens UENF-22GI is able to solubilize P and Zn, to produce indole compounds (likely IAA), to colonize hyphae and counter the growth of two phytopathogenic fungi. Inoculation of maize with this strain remarkably increased seedling growth and biomass under greenhouse conditions. The S. marcescens UENF-22GI genome has 5 Mb, assembled in 17 scaffolds comprising 4662 genes (4528 are protein-coding). No plasmids were identified. S. marcescens UENF-22GI is phylogenetically placed within a clade comprised almost exclusively of non-clinical strains. We identified genes and operons that are likely responsible for the interesting plant-growth promoting features that were experimentally described. The S. marcescens UENF-22GI genome harbors a horizontally-transferred genomic island involved in antibiotic production, antibiotic resistance, and anti-phage defense via a novel ADP-ribosyltransferase-like protein and possible modification of DNA by a deazapurine base, which likely contributes to its competitiveness against other bacteria. CONCLUSIONS: Collectively, our results suggest that S. marcescens UENF-22GI is a strong candidate to be used in the enrichment of substrates for plant growth promotion or as part of bioinoculants for agriculture.

Transcription factors, chromatin proteins and the diversification of Hemiptera.

Availability of complete genomes provides a means to explore the evolution of enormous developmental, morphological, and behavioral diversity among insects. Hemipterans in particular show great diversity of both morphology and life history within a single order. To better understand the role of transcription regulators in the diversification of hemipterans, using sequence profile searches and hidden Markov models we computationally analyzed transcription factors (TFs) and chromatin proteins (CPs) in the recently available Rhodnius prolixus genome along with 13 other insect and 4 non-insect arthropod genomes. We generated a comprehensive collection of TFs and CPs across arthropods including 303 distinct types of domains in TFs and 139 in CPs. This, along with the availability of two hemipteran genomes, R. prolixus and Acyrthosiphon pisum, helped us identify possible determinants for their dramatic morphological and behavioral divergence. We identified five domain families (i.e. Pipsqueak, SAZ/MADF, THAP, FLYWCH and BED finger) as having undergone differential patterns of lineage-specific expansion in hemipterans or within hemipterans relative to other insects. These expansions appear to be at least in part driven by transposons, with the DNA-binding domains of transposases having provided the raw material for emergence of new TFs. Our analysis suggests that while R. prolixus probably retains a state closer to the ancestral hemipteran, A. pisum represents a highly derived state, with the emergence of asexual reproduction potentially favoring genome duplication and transposon expansion. Both hemipterans are predicted to possess active DNA methylation systems. However, in the course of their divergence, aphids seem to have expanded the ancestral hemipteran DNA methylation along with a distinctive linkage to the histone methylation system, as suggested by expansion of SET domain methylases, including those fused to methylated CpG recognition domains. Thus, differential use of DNA methylation and histone methylation might have played a role in emergence of polyphenism and cyclic parthenogenesis from the ancestral hemipteran.

Discovering functional linkages and uncharacterized cellular pathways using phylogenetic profile comparisons: a comprehensive assessment.

BACKGROUND: A widely-used approach for discovering functional and physical interactions among proteins involves phylogenetic profile comparisons (PPCs). Here, proteins with similar profiles are inferred to be functionally related under the assumption that proteins involved in the same metabolic pathway or cellular system are likely to have been co-inherited during evolution. RESULTS: Our experimentation with E. coli and yeast proteins with 16 different carefully composed reference sets of genomes revealed that the phyletic patterns of proteins in prokaryotes alone could be adequate enough to make reasonably accurate functional linkage predictions. A slight improvement in performance is observed on adding few eukaryotes into the reference set, but a noticeable drop-off in performance is observed with increased number of eukaryotes. Inclusion of most parasitic, pathogenic or vertebrate genomes and multiple strains of the same species into the reference set do not necessarily contribute to an improved sensitivity or accuracy. Interestingly, we also found that evolutionary histories of individual pathways have a significant affect on the performance of the PPC approach with respect to a particular reference set. For example, to accurately predict functional links in carbohydrate or lipid metabolism, a reference set solely composed of prokaryotic (or bacterial) genomes performed among the best compared to one composed of genomes from all three super-kingdoms; this is in contrast to predicting functional links in translation for which a reference set composed of prokaryotic (or bacterial) genomes performed the worst. We also demonstrate that the widely used random null model to quantify the statistical significance of profile similarity is incomplete, which could result in an increased number of false-positives. CONCLUSION: Contrary to previous proposals, it is not merely the number of genomes but a careful selection of informative genomes in the reference set that influences the prediction accuracy of the PPC approach. We note that the predictive power of the PPC approach, especially in eukaryotes, is heavily influenced by the primary endosymbiosis and subsequent bacterial contributions. The over-representation of parasitic unicellular eukaryotes and vertebrates additionally make eukaryotes less useful in the reference sets. Reference sets composed of highly non-redundant set of genomes from all three super-kingdoms fare better with pathways showing considerable vertical inheritance and strong conservation (e.g. translation apparatus), while reference sets solely composed of prokaryotic genomes fare better for more variable pathways like carbohydrate metabolism. Differential performance of the PPC approach on various pathways, and a weak positive correlation between functional and profile similarities suggest that caution should be exercised while interpreting functional linkages inferred from genome-wide large-scale profile comparisons using a single reference set.