A Pipeline for Insertion Sequence Detection and Study for Bacterial Genome

International audienceInsertion Sequences (ISs) are small DNA segments that have the ability of moving themselves into genomes. These types of mobile genetic elements (MGEs) seem to play an essential role in genomes rearrange-ments and evolution of prokaryotic genomes, but the tools that deal with discovering ISs in an efficient and accurate way are still too few and not totally precise. Two main factors have big effects on IS discovery, namely: genes annotation and functionality prediction. Indeed, some specific genes called "transposases" are enzymes that are responsible of the production and catalysis for such transposition, but there is currently no fully accurate method that could decide whether a given predicted gene is either a real transposase or not. This is why authors of this article aim at designing a novel pipeline for ISs detection and classification, which embeds the most recently available tools developed in this field of research, namely OASIS (Optimized Annotation System for Insertion Sequence) and ISFinder database (an up-to-date and accurate repository of known insertion sequences). As this latter depend on predicted coding sequences, the proposed pipeline will encompass too various kinds of bacterial genes annotation tools (that is, Prokka, BASys, and Prodigal). A complete IS detection and classification pipeline is then proposed and tested on a set of 23 complete genomes of Pseudomonas aeruginosa. This pipeline can also be used as an investigator of annotation tools performance, which has led us to conclude that Prodigal is the best software for IS prediction. A deepen study regarding IS elements in P.aeruginosa has then been conducted, leading to the conclusion that close genomes inside this species have also a close numbers of IS families and groups. A Pipeline for Insertion Sequence Detection and Study for Bacterial Genome - ResearchGate. Available from: http://www.researchgate.net/publication/265914086_A_Pipeline_for_Insertion_Sequence_Detection_and_Study_for_Bacterial_Genome [accessed Apr 22, 2015]

Enhanced heterogeneity of rpoB in Mycobacterium tuberculosis found at low pH.

OBJECTIVES: The aim of this study was to gain an insight into the molecular mechanisms of the evolution of rifampicin resistance in response to controlled changes in the environment. METHODS: We determined the proportion of rpoB mutants in the chemostat culture and characterized the sequence of mutations found in the rifampicin resistance-determining region of rpoB in a steady-state chemostat at pH 7.0 and 6.2. RESULTS: The overall proportion of rpoB mutants of strain H37Rv remained constant for 37 days at pH 7.0, ranging between 3.6 x 10(-8) and 8.9 x 10(-8); however, the spectrum of mutations varied. The most commonly detected mutation, serine to leucine mutation at codon 531 (S531L), increased from 40% to 89%, while other mutations (S531W, H526Y, H526D, H526R, S522L and D516V) decreased over the 37 day sampling period. Changing the pH from 7.0 to 6.2 did not significantly alter the overall proportion of mutants, but resulted in a decrease in the percentage of strains harbouring S531L (from 89% to 50%) accompanied by an increase in the range of different mutations from 4 to 12. CONCLUSIONS: The data confirm that the fitness of strains with the S531L mutation is greater than that of strains containing other mutations. We also conclude that at low pH the environment is permissive for a wider spectrum of mutations, which may provide opportunities for a successful mutant to survive

At the nexus of three kingdoms: the genome of the mycorrhizal fungus Gigaspora margarita provides insights into plant, endobacterial and fungal interactions.

As members of the plant microbiota, arbuscular mycorrhizal fungi (AMF, Glomeromycotina) symbiotically colonize plant roots. AMF also possess their own microbiota, hosting some uncultivable endobacteria. Ongoing research has revealed the genetics underlying plant responses to colonization by AMF, but the fungal side of the relationship remains in the dark. Here, we sequenced the genome of Gigaspora margarita, a member of the Gigasporaceae in an early diverging group of the Glomeromycotina. In contrast to other AMF, G. margarita may host distinct endobacterial populations and possesses the largest fungal genome so far annotated (773.104 Mbp), with more than 64% transposable elements. Other unique traits of the G. margarita genome include the expansion of genes for inorganic phosphate metabolism, the presence of genes for production of secondary metabolites and a considerable number of potential horizontal gene transfer events. The sequencing of G. margarita genome reveals the importance of its immune system, shedding light on the evolutionary pathways that allowed early diverging fungi to interact with both plants and bacteria

Genome analysis of a highly virulent serotype 1 strain of streptococcus pneumoniae from West Africa

Streptococcus pneumoniae is a leading cause of pneumonia, meningitis, and bacteremia, estimated to cause 2 million deaths annually. The majority of pneumococcal mortality occurs in developing countries, with serotype 1 a leading cause in these areas. To begin to better understand the larger impact that serotype 1 strains have in developing countries, we characterized virulence and genetic content of PNI0373, a serotype 1 strain from a diseased patient in The Gambia. PNI0373 and another African serotype 1 strain showed high virulence in a mouse intraperitoneal challenge model, with 20% survival at a dose of 1 cfu. The PNI0373 genome sequence was similar in structure to other pneumococci, with the exception of a 100 kb inversion. PNI0373 showed only15 lineage specific CDS when compared to the pan-genome of pneumococcus. However analysis of non-core orthologs of pneumococcal genomes, showed serotype 1 strains to be closely related. Three regions were found to be serotype 1 associated and likely products of horizontal gene transfer. A detailed inventory of known virulence factors showed that some functions associated with colonization were absent, consistent with the observation that carriage of this highly virulent serotype is unusual. The African serotype 1 strains thus appear to be closely related to each other and different from other pneumococci despite similar genetic content

Reconstructing an ancestral genotype of two hexachlorocyclohexane-degrading Sphingobium species using metagenomic sequence data.

Over the last 60 years, the use of hexachlorocyclohexane (HCH) as a pesticide has resulted in the production of >4 million tons of HCH waste, which has been dumped in open sinks across the globe. Here, the combination of the genomes of two genetic subspecies (Sphingobium japonicum UT26 and Sphingobium indicum B90A; isolated from two discrete geographical locations, Japan and India, respectively) capable of degrading HCH, with metagenomic data from an HCH dumpsite (∼450 mg HCH per g soil), enabled the reconstruction and validation of the last-common ancestor (LCA) genotype. Mapping the LCA genotype (3128 genes) to the subspecies genomes demonstrated that >20% of the genes in each subspecies were absent in the LCA. This includes two enzymes from the 'upper' HCH degradation pathway, suggesting that the ancestor was unable to degrade HCH isomers, but descendants acquired lin genes by transposon-mediated lateral gene transfer. In addition, anthranilate and homogentisate degradation traits were found to be strain (selectively retained only by UT26) and environment (absent in the LCA and subspecies, but prevalent in the metagenome) specific, respectively. One draft secondary chromosome, two near complete plasmids and eight complete lin transposons were assembled from the metagenomic DNA. Collectively, these results reinforce the elastic nature of the genus Sphingobium, and describe the evolutionary acquisition mechanism of a xenobiotic degradation phenotype in response to environmental pollution. This also demonstrates for the first time the use of metagenomic data in ancestral genotype reconstruction, highlighting its potential to provide significant insight into the development of such phenotypes

OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps.

BackgroundOptical mapping is an emerging technology that complements sequencing-based methods in genome analysis. It is widely used in improving genome assemblies and detecting structural variations by providing information over much longer (up to 1 Mb) reads. Current standards in optical mapping analysis involve assembling optical maps into contigs and aligning them to a reference, which is limited to pairwise comparison and becomes bias-prone when analyzing multiple samples.FindingsWe present a new method, OMMA, that extends optical mapping to the study of complex genomic features by simultaneously interrogating optical maps across many samples in a reference-independent manner. OMMA captures and characterizes complex genomic features, e.g., multiple haplotypes, copy number variations, and subtelomeric structures when applied to 154 human samples across the 26 populations sequenced in the 1000 Genomes Project. For small genomes such as pathogenic bacteria, OMMA accurately reconstructs the phylogenomic relationships and identifies functional elements across 21 Acinetobacter baumannii strains.ConclusionsWith the increasing data throughput of optical mapping system, the use of this technology in comparative genome analysis across many samples will become feasible. OMMA is a timely solution that can address such computational need. The OMMA software is available at https://github.com/TF-Chan-Lab/OMTools

REPARATION : ribosome profiling assisted (re-)annotation of bacterial genomes

Prokaryotic genome annotation is highly dependent on automated methods, as manual curation cannot keep up with the exponential growth of sequenced genomes. Current automated methods depend heavily on sequence composition and often underestimate the complexity of the proteome. We developed RibosomeE Profiling Assisted (re-)AnnotaTION (REPARATION), a de novo machine learning algorithm that takes advantage of experimental protein synthesis evidence from ribosome profiling (Ribo-seq) to delineate translated open reading frames (ORFs) in bacteria, independent of genome annotation (https://github.com/Biobix/ REPARATION). REPARATION evaluates all possible ORFs in the genome and estimates minimum thresholds based on a growth curve model to screen for spurious ORFs. We applied REPARATION to three annotated bacterial species to obtain a more comprehensive mapping of their translation landscape in support of experimental data. In all cases, we identified hundreds of novel (small) ORFs including variants of previously annotated ORFs and >70% of all (variants of) annotated protein coding ORFs were predicted by REPARATION to be translated. Our predictions are supported by matching mass spectrometry proteomics data, sequence composition and conservation analysis. REPARATION is unique in that it makes use of experimental translation evidence to intrinsically perform a de novo ORF delineation in bacterial genomes irrespective of the sequence features linked to open reading frames