21 research outputs found
Insights into Genome Functional Organisation through the Analysis of Interaction Networks
Using computational techniques to identify orthology and operon structure, it is possible to find functional interactions between genes, which, together, define the genetic interactome. These large networks contain information about the relationships between phenotypes in organisms as genes responsible for related abilities are often co-regulated and reasserting of these genes can be detected in the operon structure. However, these networks are too large to analyse by hand In order to practically analyse the networks, a computational tool, gisql, was developed and, using this tool, the connectivity patterns in the genetic interactome can be analysed to understand high-level organisation of the genome and to narrow the list of candidate genes for wet lab analysis. The many strains of Escherichia coli are interesting subjects as there are many sequenced strains and they show highly variable pathogenic abilities. Analysis shows that the pathogenic genes have a strong tendency to connect to genes ubiquitous in the E. coli pan-genome. The Rhizobiales, including Sinorhizobium meliloti and Ochrobactrum anthropi, are multi-chromosomal eukaryote-associated bacteria and a significant history of horizontal transfer. Regions of the pSymB megaplasmid of S. meliloti which cannot be deleted via transposon-targeted homologous recombination were shown to be significantly more connected to the main chromosome. Targets for functional complementation of deletions in pSymB in S. meliloti using genes from O. anthropi were identified and unusual connectivity patterns of orthologs were identified. Finally, a putative cytokinin receptor in the Rhizobiaceæ, likely involved in symbiosis with plant hosts, was identified. Thanks to the flexibility of gisql, these analyses were straight-forward and fast to develop
Aquarium Nitrification Revisited: Thaumarchaeota Are the Dominant Ammonia Oxidizers in Freshwater Aquarium Biofilters
Ammonia-oxidizing archaea (AOA) outnumber ammonia-oxidizing bacteria (AOB) in many terrestrial and aquatic environments. Although nitrification is the primary function of aquarium biofilters, very few studies have investigated the microorganisms responsible for this process in aquaria. This study used quantitative real-time PCR (qPCR) to quantify the ammonia monooxygenase (amoA) and 16S rRNA genes of Bacteria and Thaumarchaeota in freshwater aquarium biofilters, in addition to assessing the diversity of AOA amoA genes by denaturing gradient gel electrophoresis (DGGE) and clone libraries. AOA were numerically dominant in 23 of 27 freshwater biofilters, and in 12 of these biofilters AOA contributed all detectable amoA genes. Eight saltwater aquaria and two commercial aquarium nitrifier supplements were included for comparison. Both thaumarchaeal and bacterial amoA genes were detected in all saltwater samples, with AOA genes outnumbering AOB genes in five of eight biofilters. Bacterial amoA genes were abundant in both supplements, but thaumarchaeal amoA and 16S rRNA genes could not be detected. For freshwater aquaria, the proportion of amoA genes from AOA relative to AOB was inversely correlated with ammonium concentration. DGGE of AOA amoA genes revealed variable diversity across samples, with nonmetric multidimensional scaling (NMDS) indicating separation of freshwater and saltwater fingerprints. Composite clone libraries of AOA amoA genes revealed distinct freshwater and saltwater clusters, as well as mixed clusters containing both freshwater and saltwater amoA gene sequences. These results reveal insight into commonplace residential biofilters and suggest that aquarium biofilters may represent valuable biofilm microcosms for future studies of AOA ecology
PANDAseq: paired-end assembler for illumina sequences
Abstract Background Illumina paired-end reads are used to analyse microbial communities by targeting amplicons of the 16S rRNA gene. Publicly available tools are needed to assemble overlapping paired-end reads while correcting mismatches and uncalled bases; many errors could be corrected to obtain higher sequence yields using quality information. Results PANDAseq assembles paired-end reads rapidly and with the correction of most errors. Uncertain error corrections come from reads with many low-quality bases identified by upstream processing. Benchmarks were done using real error masks on simulated data, a pure source template, and a pooled template of genomic DNA from known organisms. PANDAseq assembled reads more rapidly and with reduced error incorporation compared to alternative methods. Conclusions PANDAseq rapidly assembles sequences and scales to billions of paired-end reads. Assembly of control libraries showed a 4-50% increase in the number of assembled sequences over naïve assembly with negligible loss of "good" sequence.</p
Exploring links between pH and bacterial community composition in soils from the Craibstone Experimental Farm
International audienceSoil pH is an important determinant of microbial community composition and diversity, yet few studies have characterized the specific effects of pH on individual bacterial taxa within bacterial communities, both abundant and rare. We collected composite soil samples over 2 years from an experimentally maintained pH gradient ranging from 4.5 to 7.5 from the Craibstone Experimental Farm (Craibstone, Scotland). Extracted nucleic acids were characterized by bacterial and group-specific denaturing gradient gel electrophoresis and next-generation sequencing of bacterial 16S rRNA genes. Both methods demonstrated comparable and reproducible shifts within higher taxonomic bacterial groups (e.g. Acidobacteria,Alphaproteobacteria,Verrucomicrobia, and Gammaproteobacteria) across the pH gradient. In addition, we used non-negative matrix factorization (NMF) for the first time on 16S rRNA gene data to identify positively interacting (i.e. co-occurring) operational taxonomic unit (OTU) clusters (i.e. ‘components’), with abundances that correlated strongly with pH, and sample year to a lesser extent. All OTUs identified by NMF were visualized within principle coordinate analyses of UNIFRAC distances and subjected to taxonomic network analysis (SSUnique), which plotted OTU abundance and similarity against established taxonomies. Most pH-dependent OTUs identified here would not have been identified by previous methodologies for microbial community profiling and were unrelated to known lineages
BAMQL: a query language for extracting reads from BAM files
Abstract
Background
It is extremely common to need to select a subset of reads from a BAM file based on their specific properties. Typically, a user unpacks the BAM file to a text stream using SAMtools, parses and filters the lines using AWK, then repacks them using SAMtools. This process is tedious and error-prone. In particular, when working with many columns of data, mix-ups are common and the bit field containing the flags is unintuitive. There are several libraries for reading BAM files, such as Bio-SamTools for Perl and pysam for Python. Both allow access to the BAM’s read information and can filter reads, but require substantial boilerplate code; this is high overhead for mostly ad hoc filtering.
Results
We have created a query language that gathers reads using a collection of predicates and common logical connectives. Queries run faster than equivalents and can be compiled to native code for embedding in larger programs.
Conclusions
BAMQL provides a user-friendly, powerful and performant way to extract subsets of BAM files for ad hoc analyses or integration into applications. The query language provides a collection of predicates beyond those in SAMtools, and more flexible connectives
Structural, dynamical, and transport properties of the hydrated halides: How do At<sup>-</sup> bulk properties compare with those of the other halides, from F<sup>-</sup> to I<sup>-</sup>?
International audienceThe properties of halides from the lightest, Fuoride (F-), to the heaviest, astatide (At-), have been studied in water using a polarizable force-field approach based on molecular dynamics (MD) simulations at the 10 ns scale. The selected force-field explicitly treats the cooperativity within the halide-water hydrogen bond networks. The force- eld parameters have been adjusted to ab initio data on anion/water clusters computed at the relativistic Möller-Plesset second-order perturbation theory level of theory. The anion static polarizabilities of the two heaviest halides, I- and At-, were computed in the gas phase using large and diffuse atomic basis sets, and taking into account both electron correlation and spin-orbit coupling within a four-component framework. Our MD simulation results show the solvation properties of I- and At- in aqueous phase to be very close. For instance, their first hydration shells are structured and encompass 9.2 and 9.1 water molecules at about 3.70 ± 0.05 Å, respectively. These values have to be compared to the F-, Cl-, and Br- ones, i.e., 6.3, 8.4, and 9.0 water molecules at 2.74, 3.38, and 3.55 Å, respectively. Moreover our computations predict the solvation free energy of At- in liquid water at ambient conditions to be 68 kcal mol-1, a value also close the I- one, about 70 kcal mol-1. In all, our simulation results for I- are in excellent agreement with the latest neutron- and X-ray diffraction studies. Those for the At- ion are predictive, as no theoretical or experimental data are available to date