Complete Microbial Genomes Research Articles

Applying automatically derived gene-groups to automatically predict and refine metabolic pathways

This paper describes an automated technique to predict integrated pathways and refine existing metabolic pathways using the information of automatically derived, functionally similar gene-groups and orthologs (functionally equivalent genes) derived by the comparison of complete microbial genomes archived in GenBank. The described method integrates automatically derived orthologous and homologous gene-groups (http://www.mcs.kent.edu//spl sim/arvind/orthos.html) with the biochemical pathway template available at the KEGG database (http://www.genome.ad.jp), the enzyme information derived from the SwissProt enzyme database (http:// expasys.hcuge.ch/), and the Ligand database (http://www.genome.ad.jp). The technique refines existing pathways (based upon the network of reactions of enzymes) by associating corresponding nonenzymatic and regulatory proteins to enzymes and operons and by identifying substituting homologs. The technique is suitable for building and refining integrated pathways using evolutionary diverse organisms. A methodology and the corresponding algorithm are presented. The technique is illustrated by comparing the genomes of E coli and B. subtilis with M. tuberculosis. The findings about integrated pathways are briefly discussed.

The genome sequence of Haemophilus influenzae.

Publication of the complete 1.83-Mb genome sequence of the bacterium Haemophilus influenzae strain Rd in 1995 () heralded a revolution in the study of microorganisms. The availability of a complete microbial genome sequence enormously facilitates computer-based and experimental investigations of the respective organism by providing complete lists of genes, their genetic contexts, and their predicted functions. The significance of the H. influenzae sequence was not just that it presented for the first time a complete genome from a free-living organism, but that it proved that complete genomes could be sequenced rapidly and effectively at a low cost. This was achieved through the novel approach taken by Venter and his colleagues at The Institute for Genomic Research (TIGR) to sequence the H. influenzae genome. Randomly generated small chromosomal fragments, 1–2 kb in length, were cloned into a high-copy-number plasmid vector and then both ends of the clone were sequenced using plasmid specific primers. The vast amount of DNA sequence obtained from the shotgun clones was assembled into large contiguous sequences by computers using specifically developed software. The equivalent to sequencing the entire genome 6 times was required for sufficient accuracy and coverage of the majority of the chromosome. To obtain a final contiguous sequence, gaps between contigs (tracts of contiguous sequence) were closed using homology comparisons between end sequences, the polymerase chain reaction, and sequencing of larger DNA inserts from lambda libraries. The shotgun method was rapid, as it circumvented the need for construction of a physical map of the genome, a prerequisite of the ordered approach taken to other bacterial sequencing projects.

Identifying functional links between genes using conserved chromosomal proximity

Conservation of proximity of a pair of genes across multiple genomes generally indicates that their functions could be linked. Here, we present a systematic evaluation using 42 complete microbial genomes from 25 phylogenetic groups to test the reliability of this observation in predicting function for genes. We find a relationship between the number of phylogenetic groups in which a gene pair is proximate and the probability that the pair belongs to a common pathway. Our method produces 1586 links between ortholog families substantiated by observed proximity in genomes representing at least three phylogenetic groups. Of the pairs annotated in the KEGG database, 80% are in the same biological pathway in KEGG.

Sequencing and analysis of a 63 kb bacterial artificial chromosome insert from the Wolbachia endosymbiont of the human filarial parasite Brugia malayi

Wolbachia endosymbiotic bacteria are widespread in filarial nematodes and are directly involved in the immune response of the host. In addition, antibiotics which disrupt Wolbachia interfere with filarial nematode development thus, Wolbachia provide an excellent target for control of filariasis. A 63.1 kb bacterial artificial chromosome insert, from the Wolbachia endosymbiont of the human filarial parasite Brugia malayi, has been sequenced using the New England Biolabs Inc. Genome Priming System™ transposition kit in conjunction with primer walking methods. The bacterial artificial chromosome insert contains approximately 57 potential ORFs which have been compared by individual protein BLAST analysis with the 35 published complete microbial genomes in the Comprehensive Microbial Resource database at The Institute for Genomic Research and in the NCBI GenBank database, as well as to data from 22 incomplete genomes from the DOE Joint Genome Institute. Twenty five of the putative ORFs have significant similarity to genes from the α-proteobacteria Rickettsia prowazekii, the most closely related completed genome, as well as to the newly sequenced α-proteobacteria endosymbiont Sinorhizobium meliloti. The bacterial artificial chromosome insert sequence however has little conserved synteny with the R. prowazekii and S. meliloti genomes. Significant sequence similarity was also found in comparisons with the currently available sequence data from the Wolbachia endosymbiont of Drosophila melanogaster. Analysis of this bacterial artificial chromosome insert provides useful gene density and comparative genomic data that will contribute to whole genome sequencing of Wolbachia from the B. malayi host. This will also lead to a better understanding of the interactions between the endosymbiont and its host and will offer novel approaches and drug targets for elimination of filarial disease.

Genome Information Broker (GIB): data retrieval and comparative analysis system for completed microbial genomes and more.

Genome Information Broker (GIB) is a powerful tool for the study of comparative genomics. GIB allows users to retrieve and display partial and/or whole genome sequences together with the relevant biological annotation. GIB has accumulated all the completed microbial genome and has recently been expanded to include Arabidopsis thaliana genome data from DDBJ/EMBL/GenBank. In the near future, hundreds of genome sequences will be determined. In order to handle such huge data, we have enhanced the GIB architecture by using XML, CORBA and distributed RDBs. We introduce the new GIB here. GIB is freely accessible at http://gib.genes.nig.ac.jp/.

DNA Data Bank of Japan (DDBJ) for genome scale research in life science

The DNA Data Bank of Japan (DDBJ, http://www.ddbj.nig.ac.jp) has made an effort to collect as much data as possible mainly from Japanese researchers. The increase rates of the data we collected, annotated and released to the public in the past year are 43% for the number of entries and 52% for the number of bases. The increase rates are accelerated even after the human genome was sequenced, because sequencing technology has been remarkably advanced and simplified, and research in life science has been shifted from the gene scale to the genome scale. In addition, we have developed the Genome Information Broker (GIB, http://gib.genes.nig.ac.jp) that now includes more than 50 complete microbial genome and Arabidopsis genome data. We have also developed a database of the human genome, the Human Genomics Studio (HGS, http://studio.nig.ac.jp). HGS provides one with a set of sequences being as continuous as possible in any one of the 24 chromosomes. Both GIB and HGS have been updated incorporating newly available data and retrieval tools.

On the total number of genes and their length distribution in complete microbial genomes

In sequenced microbial genomes, some of the annotated genes are actually not protein-coding genes, but rather open reading frames that occur by chance. Therefore, the number of annotated genes is higher than the actual number of genes for most of these microbes. Comparison of the length distribution of the annotated genes with the length distribution of those matching a known protein reveals that too many short genes are annotated in many genomes. Here we estimate the true number of protein-coding genes for sequenced genomes. Although it is often claimed that Escherichia coli has about 4300 genes, we show that it probably has only ∼3800 genes, and that a similar discrepancy exists for almost all published genomes.

Genomics-based identification of targets in pathogenic bacteria for potential therapeutic and diagnostic use

The availability of numerous complete microbial genome sequences has profoundly altered our understanding of a number of fundamental biological processes. For example the enzymes involved in aminoacyl-tRNA (AA-tRNA) synthesis, the key process responsible for the accuracy of protein synthesis, have been found to be highly species-specific. In particular, a number of pathogens contain certain pathways of AA-tRNA synthesis that are unrelated to those found in their mammalian hosts. Since AA-tRNA synthesis is indispensable for cell viability, the discovery of pathogen-specific pathways and enzymes presents novel therapeutic and diagnostic targets. Here we will review recent advances in the elucidation of AA-tRNA synthesis pathways and discuss the possible pharmaceutical exploitation of these discoveries. In particular, the integration of genomic and biochemical approaches to identify novel targets for the treatment of Chlamydial infections and the diagnosis and treatment of Lyme disease will be presented.

Many Genbank entries for complete microbial genomes violate the Genbank standard

A survey of Genbank entries for complete microbial genomes reveals that the majority do not conform to the Genbank standard. Typical deviations from the Genbank standard include records with information in incorrect fields, addition of extraneous and confusing information within a field, and omission of useful fields. This situation results from two principal causes: genome centres do not submit Genbank records in the proper form and the Genbank, EMBL and DDBJ staffs do not enforce the database standards that they have defined.

A clustering method for repeat analysis in DNA sequences.

A computational system for analysis of the repetitive structure of genomic sequences is described. The method uses suffix trees to organize and search the input sequences; this data structure has been used previously for efficient computation of exact and degenerate repeats. The resulting software tool collects all repeat classes and outputs summary statistics as well as a file containing multiple sequences (multi fasta), that can be used as the target of searches. Its use is demonstrated here on several complete microbial genomes, the entire Arabidopsis thaliana genome, and a large collection of rice bacterial artificial chromosome end sequences. We propose a new clustering method for analysis of the repeat data captured in suffix trees. This method has been incorporated into a system that can find repeats in individual genome sequences or sets of sequences, and that can organize those repeats into classes. It quickly and accurately creates repeat databases from small and large genomes. The associated software (RepeatFinder), should prove helpful in the analysis of repeat structure for both complete and partial genome sequences.

The Comprehensive Microbial Resource.

One challenge presented by large-scale genome sequencing efforts is effective display of uniform information to the scientific community. The Comprehensive Microbial Resource (CMR) contains robust annotation of all complete microbial genomes and allows for a wide variety of data retrievals. The bacterial information has been placed on the Web at http://www.tigr.org/CMR for retrieval using standard web browsing technology. Retrievals can be based on protein properties such as molecular weight or hydrophobicity, GC-content, functional role assignments and taxonomy. The CMR also has special web-based tools to allow data mining using pre-run homology searches, whole genome dot-plots, batch downloading and traversal across genomes using a variety of datatypes.

EMGLib: the enhanced microbial genomes library (update 2000).

As the number of complete microbial genomes publicly available is still growing, the problem of annotation quality in these very large sequences remains unsolved. Indeed, the number of annotations associated with complete genomes is usually lower than those of the shorter entries encountered in the repository collections. Moreover, classical sequence database management systems have difficulties in handling entries of such size. In this context, the Enhanced Microbial Genomes Library (EMGLib) was developed to try to alleviate these problems. This library contains all the complete genomes from prokaryotes (bacteria and archaea) already sequenced and the yeast genome in GenBank format. The annotations are improved by the introduction of data on codon usage, gene orientation on the chromosome and gene families. It is possible to access EMGLib through two database systems set up on WWW servers: the PBIL server at http://pbil.univ-lyon1.fr/emglib.html and the MICADO server at http://locus.jouy.inra.fr/micado

Testing ancient RNA–protein interactions

The past decade in molecular biology has seen remarkable advances in the study of the origin and early evolution of life. The mathematical tools for analyzing DNA and protein sequences, coupled with the availability of complete microbial genome sequences, provide insight almost as far back as the age of the nucleic acids themselves. Experimental evolution in the laboratory and especially in vitro evolution of RNA provide insight into a hypothetical world where RNA, or a close relative, may have debuted as a primary functional and informational molecule. The ability to isolate new functional RNAs from random sequences now ultimately makes the world of possible primitive chemical interactions accessible even when the molecules or reactions are no longer present in modern species. Thus we can at last form direct experimental tests of specific models for the origin of RNA-protein associations, such as those that influenced the genetic code. This marks a turning point for probing the origin and early history of life at the molecular level.

Significance of Z-value statistics of Smith–Waterman scores for protein alignments

The Z-value is an attempt to estimate the statistical significance of a Smith–Waterman dynamic alignment score (SW-score) through the use of a Monte–Carlo process. It partly reduces the bias induced by the composition and length of the sequences. This paper is not a theoretical study on the distribution of SW-scores and Z-values. Rather, it presents a statistical analysis of Z-values on large datasets of protein sequences, leading to a law of probability that the experimental Z-values follow. First, we determine the relationships between the computed Z-value, an estimation of its variance and the number of randomizations in the Monte–Carlo process. Then, we illustrate that Z-values are less correlated to sequence lengths than SW-scores. Then we show that pairwise alignments, performed on ‘quasi-real’ sequences (i.e., randomly shuffled sequences of the same length and amino acid composition as the real ones) lead to Z-value distributions that statistically fit the extreme value distribution, more precisely the Gumbel distribution (global EVD, Extreme Value Distribution). However, for real protein sequences, we observe an over-representation of high Z-values. We determine first a cutoff value which separates these overestimated Z-values from those which follow the global EVD. We then show that the interesting part of the tail of distribution of Z-values can be approximated by another EVD (i.e., an EVD which differs from the global EVD) or by a Pareto law. This has been confirmed for all proteins analysed so far, whether extracted from individual genomes, or from the ensemble of five complete microbial genomes comprising altogether 16956 protein sequences.

Whole genome protein domain analysis using a new method for domain clustering

We present the outcome of a systematic analysis of protein domain shuffling in 17 completed microbial genomes. This analysis has been performed using MKDOM Version 2, a completely new version of the domain clustering program MKDOM based on PSI-BLAST recursive homology searches. It allows to delineate the most frequent protein domain building blocks, which domains are found specifically in Bacteria, Archaea or yeast, and which domains are shared between two or all three domains of life. The latter are good candidates as the basic protein building blocks underlying all forms of cellular life. Statistics of multi-domain proteins indicate that some organisms such as Bacillus subtilis or Mycobacterium tuberculosis contain an abnormally high number of large multi-domain proteins. We also provide examples of highly shuffled or circularly permutated domains. A WWW graphical interface has been made available to interactively browse domain arrangements of proteins in all 17 genomes, at http://www.toulouse.inra.fr/prodomCG.html.

Recent improvements of the ProDom database of protein domain families.

The ProDom database contains protein domain families generated from the SWISS-PROT database by automated sequence comparisons. The current version was built with a new improved procedure based on recursive PSI-BLAST homology searches. ProDom can be searched on the World Wide Web to study domain arrangements within either known families or new proteins, with the help of a user-friendly graphical interface (http://www.toulouse.inra.fr/prodom.html). Recent improvements to the ProDom server include: ProDom queries under the SRS Sequence Retrieval System; links to the PredictProtein server; phylogenetic trees and condensed multiple alignments for a better representation of large domain families, with zooming in and out capabilities. In addition, a similar server was set up to display the outcome of whole genome domain analysis as applied to 17 completed microbial genomes (http://www.toulouse.inra.fr/prodomCG.html ).

How representative are the known structures of the proteins in a complete genome? A comprehensive structural census

Determining how representative the known structures are of the proteins encoded by a complete genome is important for assessing to what extent our current picture of protein stability and folding is overly influenced by biases in the structure databank (PDB). It is also important for improving database-based methods of structure prediction and genome annotation. The known structures are compared to the proteins encoded by eight complete microbial genomes in terms of simple statistics such as sequence length, composition and secondary structure. The known structures are represented by a collection of nonhomologous domains from the PDB and a smaller list of 'biophysical proteins' on which folding experiments have concentrated. The proteins encoded by the genomes are considered as a whole and divided into various regions, such as known-structure homologue, low complexity (nonglobular), transmembrane or linker. Various tests are performed to assess the significance of the reported differences, in both a practical and a statistical sense. The proteins encoded by the genomes are significantly different from those in the PDB. Their sequence lengths, which follow an extreme value distribution, are longer than the PDB proteins and much longer than the biophysical proteins. Their composition differs from the PDB proteins in having more Lys, Ile, Asn and Gln and less Cys and Trp. This is true overall and especially for the regions corresponding to soluble proteins of as yet unknown fold. Secondary-structure prediction on these uncharacterized regions indicates that they contain on average more helical structure than the PDB; differences about this mean are small, with yeast having slightly more sheet structure and Haemophilus influenzae and Helicobacter pylori more helical structure. Further information is available through the GeneCensus system at http://bioinfo.mbb.yale.edu/genome.

Findings emerging from complete microbial genome sequences

Sixteen microorganisms, including one eukaryote, four archaeons, and 11 eubacteria, have been completely sequenced and published. More than 50 genomes are scheduled to be completed by the year 2000. This explosive growth of information is forcing change in many scientific disciplines (e.g. bioinformatics and molecular genetics), spawning new fields, and even changing the way scientific information is used and shared. Novel, global genome sequence comparisons seem slow to appear but the infrastructure for these projects is being built, and we expect exciting developments in the near future.

Abundant microsatellite polymorphism in Saccharomyces cerevisiae, and the different distributions of microsatellites in eight prokaryotes and S. cerevisiae, result from strong mutation pressures and a variety of selective forces.

We examined the distributions of short tandemly repeated DNAs (microsatellites) in nine complete microbial genomes (Saccharomyces cerevisiae, Archaeoglobus fulgidus, Escherichia coli, Haemophilus influenzae, Helicobacter pylori, Methanococcus jannaschii, Mycoplasma pneumoniae, M. genitalium, and Synechocystis PCC6803.) These repeats contribute differently to the global features of these genomes, and we explore the evolutionary implications of these differences by empirical examination of length polymorphisms at 20 long triplet-repeats repeats in S. cerevisiae, and by comparison of observed and expected repeat distributions. All of a sample of 20 microsatellites found in S. cerevisiae are highly polymorphic in length, suggesting that mutation pressure overcomes overall selection for small genome size that will tend to shorten or eliminate unnecessary DNA. By comparison, prokaryotes have fewer long repeats than expected, except for a few statistically improbable repeats that appear to function in gene regulation. Finally, we find that in all these genomes there is an excess of repeats shorter than those traditionally considered to be microsatellites. This finding suggests that even in prokaryotes these repeats are being generated by mutational pressures. These results have important potential implications for understanding genome stability and evolution in these microbial species.

Microbial gene identification using interpolated Markov models.

This paper describes a new system, GLIMMER, for finding genes in microbial genomes. In a series of tests on Haemophilus influenzae , Helicobacter pylori and other complete microbial genomes, this system has proven to be very accurate at locating virtually all the genes in these sequences, outperforming previous methods. A conservative estimate based on experiments on H.pylori and H. influenzae is that the system finds >97% of all genes. GLIMMER uses interpolated Markov models (IMMs) as a framework for capturing dependencies between nearby nucleotides in a DNA sequence. An IMM-based method makes predictions based on a variable context; i.e., a variable-length oligomer in a DNA sequence. The context used by GLIMMER changes depending on the local composition of the sequence. As a result, GLIMMER is more flexible and more powerful than fixed-order Markov methods, which have previously been the primary content-based technique for finding genes in microbial DNA.