Detection of operons

Operons are clusters of genes that are transcribed as a single message, and regulated by the same gene expression machinery. They are found primarily in prokaryotic genomes. Because genes in the same operon are likely to have related functions, identification of the operon structure is potentially useful for assigning gene function. We report the development and benchmarking of two different methods for detecting operons, based on an analysis of 42 fully sequenced prokaryotic organisms. The Gene Neighbor method (GNM) utilizes the relatively high conservation of gene order in operons, compared with genes in general. The Gene Gap Method (GGM) makes use of the relatively short gap between genes in operons compared with that otherwise found between adjacent genes. The methods have been benchmarked using KEGG pathway data and RegulonDB Escherichia coli operon data. With optimum parameters, the specificity of the GNM is 93% and the sensitivity is 70%. For the GGM, the specificity is 95% and the sensitivity is 68%. Together, the two methods have a sensitivity of 87.2%, while joint predictions have a sensitivity of 50% and a specificity of 98%. The methods are used to infer possible functions for some hypothetical genes in prokaryotic genomes. The methods have proven a useful addition to structure information in deriving protein function in a structural genomics project.     

Archaeal rRNA operons

Ribosomal RNA (rRNA) operons of the archaea reflect both the unity and the diversity of this third primary taxon. They have proven to be a rich source of both molecular biological and phylogenetic information.     

Opinion: Re-evaluating prokaryotic species

There is no widely accepted concept of species for prokaryotes, and assignment of isolates to species is based on measures of phenotypic or genome similarity. The current methods for defining prokaryotic species are inadequate and incapable of keeping pace with the levels of diversity that are being uncovered in nature. Prokaryotic taxonomy is being influenced by advances in microbial population genetics, ecology and genomics, and by the ease with which sequence data can be obtained. Here, we review the classical approaches to prokaryotic species definition and discuss the current and future impact of multilocus nucleotide-sequence-based approaches to prokaryotic systematics. We also consider the potential, and difficulties, of assigning species status to biologically or ecologically meaningful sequence clusters.     

The life-cycle of operons

Operons are a major feature of all prokaryotic genomes, but how and why operon structures vary is not well understood. To elucidate the life-cycle of operons, we compared gene order between Escherichia coli K12 and its relatives and identified the recently formed and destroyed operons in E. coli. This allowed us to determine how operons form, how they become closely spaced, and how they die. Our findings suggest that operon evolution may be driven by selection on gene expression patterns. First, both operon creation and operon destruction lead to large changes in gene expression patterns. For example, the removal of lysA and ruvA from ancestral operons that contained essential genes allowed their expression to respond to lysine levels and DNA damage, respectively. Second, some operons have undergone accelerated evolution, with multiple new genes being added during a brief period. Third, although genes within operons are usually closely spaced because of a neutral bias toward deletion and because of selection against large overlaps, genes in highly expressed operons tend to be widely spaced because of regulatory fine-tuning by intervening sequences. Although operon evolution may be adaptive, it need not be optimal: new operons often comprise functionally unrelated genes that were already in proximity before the operon formed.     

CONSORF: a consensus prediction system for prokaryotic coding sequences

CONSORF is a fully automatic high-accuracy identification system that provides consensus prokaryotic CDS information. It first predicts the CDSs supported by consensus alignments. The alignments are derived from multiple genome-to-proteome comparisons with other prokaryotes using the FASTX program. Then, it fills the empty genomic regions with the CDSs supported by consensus ab initio predictions. From those consensus results, CONSORF provides prediction reliability scores, predicted frame-shifts, alternative start sites and best pair-wise match information against other prokaryotes. These results are easily accessed from a website.     

Carbon cycling: the prokaryotic contribution

Although the debate continues, the concept of global warming as a consequence of the increased production of 'greenhouse gases' via human activities is now widely accepted. The role of microbes, especially the prokaryotes, in the formation, trapping and retention of 'greenhouse gases' has, for the most part, been overlooked. The future requires that we pay close attention to these organisms for possible solutions to adverse global changes.     

Phylo SI: a new genome-wide approach for prokaryotic phylogeny

The evolutionary history of all life forms is usually represented as a vertical tree-like process. In prokaryotes, however, the vertical signal is partly obscured by the massive influence of horizontal gene transfer (HGT). The HGT creates widespread discordance between evolutionary histories of different genes as genomes become mosaics of gene histories. Thus, the Tree of Life (TOL) has been questioned as an appropriate representation of the evolution of prokaryotes. Nevertheless a common hypothesis is that prokaryotic evolution is primarily tree-like, and a routine effort is made to place new isolates in their appropriate location in the TOL. Moreover, it appears desirable to exploit non–tree-like evolutionary processes for the task of microbial classification. In this work, we present a novel technique that builds on the straightforward observation that gene order conservation (‘synteny’) decreases in time as a result of gene mobility. This is particularly true in prokaryotes, mainly due to HGT. Using a ‘synteny index’ (SI) that measures the average synteny between a pair of genomes, we developed the phylogenetic reconstruction tool ‘Phylo SI’. Phylo SI offers several attractive properties such as easy bootstrapping, high sensitivity in cases where phylogenetic signal is weak and computational efficiency. Phylo SI was tested both on simulated data and on two bacterial data sets and compared with two well-established phylogenetic methods. Phylo SI is particularly efficient on short evolutionary distances where synteny footprints remain detectable, whereas the nucleotide substitution signal is too weak for reliable sequence-based phylogenetic reconstruction. The method is publicly available at http://research.haifa.ac.il/ssagi/software/PhyloSI.zip.     

MICdb: database of prokaryotic microsatellites

The MICdb (Microsatellites Database) (http://www.cdfd.org.in/micas) is a comprehensive relational database of non-redundant microsatellites extracted from fully sequenced prokaryotic genomes. The current version (1.0) of the database has been compiled from 83 genomes belonging to different phylogenetic groups. This database has been linked to MICAS, the web-based Microstatellite Analysis Server. MICAS provides a user-friendly front-end to systematically extract data on microsatellite tracts from genomes. The database contains the following information pertaining to the microsatellites: the regions (coding/non-coding, if coding, their GenBank annotations) containing microsatellite tracts; the frequencies of their occurrences, the size and the number of repeating motifs; and the sequences of the tracts. MICAS also provides an interface to Autoprimer, a primer design program to automatically design primers for selected microsatellite loci.     

Prophinder: a computational tool for prophage prediction in prokaryotic genomes

Prophinder is a prophage prediction tool coupled with a prediction database, a web server and web service. Predicted prophages will help to fill the gaps in the current sparse phage sequence space, which should cover an estimated 100 million species. Systematic and reliable predictions will enable further studies of prophages contribution to the bacteriophage gene pool and to better understand gene shuffling between prophages and phages infecting the same host. AVAILABILITY: Softare is available at http://aclame.ulb.ac.be/prophinder     

FunSys: Software for functional analysis of prokaryotic transcriptome and proteome

The vast amount of data produced by next-generation sequencing (NGS) has necessitated the development of computational tools to assist in understanding the myriad functions performed by the biological macromolecules involved in heredity. In this work, we developed the FunSys programme, a stand-alone tool with an user friendly interface that enables us to evaluate and correlate differential expression patterns from RNA sequencing and proteomics datasets. The FunSys generates charts and reports based on the results of the analysis of differential expression to aid the interpretation of the results. AVAILABILITY: The database is available for free at https://sourceforge.net/projects/funsysufpa/     

Mining prokaryotic genomes for unknown amino acids: a stop-codon-based approach

Background  

Selenocysteine and pyrrolysine are the 21st and 22nd amino acids, which are genetically encoded by stop codons. Since a number of microbial genomes have been completely sequenced to date, it is tempting to ask whether the 23rd amino acid is left undiscovered in these genomes. Recently, a computational study addressed this question and reported that no tRNA gene for unknown amino acid was found in genome sequences available. However, performance of the tRNA prediction program on an unknown tRNA family, which may have atypical sequence and structure, is unclear, thereby rendering their result inconclusive. A protein-level study will provide independent insight into the novel amino acid.     

MRD: a microsatellite repeats database for prokaryotic and eukaryotic genomes

MRD is a database system to access the microsatellite repeats information of genomes such as archea, eubacteria, and other eukaryotic genomes whose sequence information is available in public domains. MRD stores information about simple tandemly repeated k-mer sequences where k= 1 to 6, i.e. monomer to hexamer. The web interface allows the users to search for the repeat of their interest and to know about the association of the repeat with genes and genomic regions in the specific organism. The data contains the abundance and distribution of microsatellites in the coding and non-coding regions of the genome. The exact location of repeats with respect to genomic regions of interest (such as UTR, exon, intron or intergenic regions) whichever is applicable to organism is highlighted. MRD is available on the World Wide Web at and/or . The database is designed as an open-ended system to accommodate the microsatellite repeats information of other genomes whose complete sequences will be available in future through public domain.