Dataset Information

Genome-wide discovery of missing genes in biological pathways of prokaryotes.

ABSTRACT:

Background

Reconstruction of biological pathways is typically done through mapping well-characterized pathways of model organisms to a target genome, through orthologous gene mapping. A limitation of such pathway-mapping approaches is that the mapped pathway models are constrained by the composition of the template pathways, e.g., some genes in a target pathway may not have corresponding genes in the template pathways, the so-called "missing gene" problem.

Methods

We present a novel pathway-expansion method for identifying additional genes that are possibly involved in a target pathway after pathway mapping, to fill holes caused by missing genes as well as to expand the mapped pathway model. The basic idea of the algorithm is to identify genes in the target genome whose homologous genes share common operons with homologs of any mapped pathway genes in some reference genome, and to add such genes to the target pathway if their functions are consistent with the cellular function of the target pathway.

Results

We have implemented this idea using a graph-theoretic approach and demonstrated the effectiveness of the algorithm on known pathways of E. coli in the KEGG database. On all KEGG pathways containing at least 5 genes, our method achieves an average of 60% positive predictive value (PPV) and the performance is increased with more seed genes added. Analysis shows that our method is highly robust.

Conclusions

An effective method is presented to find missing genes in biological pathways of prokaryotes, which achieves high prediction reliability on E. coli at a genome level. Numerous missing genes are found to be related to known E. coli pathways, which can be further validated through biological experiments. Overall this method is robust and can be used for functional inference.

SUBMITTER: Chen Y

PROVIDER: S-EPMC3044263 | biostudies-literature | 2011 Feb

REPOSITORIES: biostudies-literature

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Publications

Genome-wide discovery of missing genes in biological pathways of prokaryotes.

Chen Yong Y Mao Fenglou F Li Guojun G Xu Ying Y

BMC bioinformatics 20110215

<h4>Background</h4>Reconstruction of biological pathways is typically done through mapping well-characterized pathways of model organisms to a target genome, through orthologous gene mapping. A limitation of such pathway-mapping approaches is that the mapped pathway models are constrained by the composition of the template pathways, e.g., some genes in a target pathway may not have corresponding genes in the template pathways, the so-called "missing gene" problem.<h4>Methods</h4>We present a nov ...[more]

PMID: 21342538

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Project description:BACKGROUND: Overlapping genes (OGs) are defined as adjacent genes whose coding sequences overlap partially or entirely. In fact, they are ubiquitous in microbial genomes and more conserved between species than non-overlapping genes. Based on this property, we have previously implemented a web server, named OGtree, that allows the user to reconstruct genome trees of some prokaryotes according to their pairwise OG distances. By analogy to the analyses of gene content and gene order, the OG distance between two genomes we defined was based on a measure of combining OG content (i.e., the normalized number of shared orthologous OG pairs) and OG order (i.e., the normalized OG breakpoint distance) in their whole genomes. A shortcoming of using the concept of breakpoints to define the OG distance is its inability to analyze the OG distance of multi-chromosomal genomes. In addition, the amount of overlapping coding sequences between some distantly related prokaryotic genomes may be limited so that it is hard to find enough OGs to properly evaluate their pairwise OG distances. RESULTS: In this study, we therefore define a new OG order distance that is based on more biologically accurate rearrangements (e.g., reversals, transpositions and translocations) rather than breakpoints and that is applicable to both uni-chromosomal and multi-chromosomal genomes. In addition, we expand the term "gene" to include both its coding sequence and regulatory regions so that two adjacent genes whose coding sequences or regulatory regions overlap with each other are considered as a pair of overlapping genes. This is because overlapping of regulatory regions of distinct genes suggests that the regulation of expression for these genes should be more or less interrelated. Based on these modifications, we have reimplemented our OGtree as a new web server, named OGtree2, and have also evaluated its accuracy of genome tree reconstruction on a testing dataset consisting of 21 Proteobacteria genomes. Our experimental results have finally shown that our current OGtree2 indeed outperforms its previous version OGtree, as well as another similar server, called BPhyOG, significantly in the quality of genome tree reconstruction, because the phylogenetic tree obtained by OGtree2 is greatly congruent with the reference tree that coincides with the taxonomy accepted by biologists for these Proteobacteria. CONCLUSIONS: In this study, we have introduced a new web server OGtree2 at http://bioalgorithm.life.nctu.edu.tw/OGtree2.0/ that can serve as a useful tool for reconstructing more precise and robust genome trees of prokaryotes according to their overlapping genes.

Project description:Uropathogenic Escherichia coli (UPEC) is a major cause of urinary tract and bloodstream infections and possesses an array of virulence factors for colonization, survival, and persistence. One such factor is the polysaccharide K capsule. Among the different K capsule types, the K1 serotype is strongly associated with UPEC infection. In this study, we completely sequenced the K1 UPEC urosepsis strain PA45B and employed a novel combination of a lytic K1 capsule-specific phage, saturated Tn5 transposon mutagenesis, and high-throughput transposon-directed insertion site sequencing (TraDIS) to identify the complement of genes required for capsule production. Our analysis identified known genes involved in capsule biosynthesis, as well as two additional regulatory genes (mprA and lrhA) that we characterized at the molecular level. Mutation of mprA resulted in protection against K1 phage-mediated killing, a phenotype restored by complementation. We also identified a significantly increased unidirectional Tn5 insertion frequency upstream of the lrhA gene and showed that strong expression of LrhA induced by a constitutive Pcl promoter led to loss of capsule production. Further analysis revealed loss of MprA or overexpression of LrhA affected the transcription of capsule biosynthesis genes in PA45B and increased sensitivity to killing in whole blood. Similar phenotypes were also observed in UPEC strains UTI89 (K1) and CFT073 (K2), demonstrating that the effects were neither strain nor capsule type specific. Overall, this study defined the genome of a UPEC urosepsis isolate and identified and characterized two new regulatory factors that affect UPEC capsule production.IMPORTANCE Urinary tract infections (UTIs) are among the most common bacterial infections in humans and are primarily caused by uropathogenic Escherichia coli (UPEC). Many UPEC strains express a polysaccharide K capsule that provides protection against host innate immune factors and contributes to survival and persistence during infection. The K1 serotype is one example of a polysaccharide capsule type and is strongly associated with UPEC strains that cause UTIs, bloodstream infections, and meningitis. The number of UTIs caused by antibiotic-resistant UPEC is steadily increasing, highlighting the need to better understand factors (e.g., the capsule) that contribute to UPEC pathogenesis. This study describes the original and novel application of lytic capsule-specific phage killing, saturated Tn5 transposon mutagenesis, and high-throughput transposon-directed insertion site sequencing to define the entire complement of genes required for capsule production in UPEC. Our comprehensive approach uncovered new genes involved in the regulation of this key virulence determinant.

Dataset Information

Genome-wide discovery of missing genes in biological pathways of prokaryotes.

Background

Methods

Results

Conclusions

Publications

Genome-wide discovery of missing genes in biological pathways of prokaryotes.

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