A novel genomics approach for the identification of drug targets in pathogens, with special reference to Pseudomonas aeruginosa

Complete genome sequences of several pathogenic bacteria have been determined, and many more such projects are currently under way. While these data potentially contain all the determinants of host-pathogen interactions and possible drug targets, computational tools for selecting suitable candidates for further experimental analyses are currently limited. Detection of bacterial genes that are non-homologous to human genes, and are essential for the survival of the pathogen represents a promising means of identifying novel drug targets. We have used three-way genome comparisons to identify essential genes from Pseudomonas aeruginosa. Our approach identified 306 essential genes that may be considered as potential drug targets. The resultant analyses are in good agreement with the results of systematic gene deletion experiments. This approach enables rapid potential drug target identification, thereby greatly facilitating the search for new antibiotics. These results underscore the utility of large genomic databases for in silico systematic drug target identification in the post-genomic era.     

Differential genome analyses of metabolic enzymes in Pseudomonas aeruginosa for drug target identification

Complete genome sequences of several pathogenic bacteria have been determined, and many more such projects are currently under way. While these data potentially contain all the determinants of host-pathogen interactions and possible drug targets, computational tools for selecting suitable candidates for further experimental analyses are currently limited. Detection of bacterial genes that are non-homologous to human genes, and are essential for the survival of the pathogen represents a promising means of identifying novel drug targets. We used a differential pathway analyses approach (based on KEGG data) to identify essential genes from Pseudomonas aeruginosa. Our approach identified 214 unique enzymes in P. aeruginosa that may be potential drug targets and can be considered for rational drug design. About 40% of these putative targets have been reported as essential by transposon mutagenesis data elsewhere. Homology model for one of the proteins (LpxC) is presented as a case study and can be explored for in silico docking with suitable inhibitors. This approach is a step towards facilitating the search for new antibiotics.     

Identification and modeling of a drug target for Clostridium perfringens SM101

In the present study, comparative genome analysis between Clostridium perfringens and the human genome was carried out to identify genes that are essential for the pathogen's survival, and non-homologous to the genes of human host, that can be used as potential drug targets. The study resulted in the identification of 426 such genes. The number of these potential drug targets thus identified is significantly lower than the genome's protein coding capacity (2558 protein coding genes). The 426 genes of C. perfringens were further analyzed for overall similarities with the essential genes of 14 different bacterial species present in Database of Essential Genes (DEG). Our results show that there are only 5 essential genes of C. perfringens that exhibit similarity with 12 species of the 14 different bacterial species present in DEG database. Of these, 1 gene was similar in 12 species and 4 genes were similar in 11 species. Thus, the study opens a new avenue for the development of potential drugs against the highly pathogenic bacterium. Further, by selecting these essential genes of C. perfringens, which are common and essential for other pathogenic microbial species, a broad spectrum anti-microbial drug can be developed. As a case study, we have built a homology model of one of the potential drug targets, ABC transporter-ATP binding protein, which can be employed for in silico docking studies by suitable inhibitors.     

Searching for drug targets in microbial genomes

Comparative analysis of the complete genome sequences of 10 bacterial pathogens available in the public databases offers the first insights into the drug discovery approaches of the near future. Genes that are conserved in different genomes often turn out to be essential, which makes them attractive targets for new broad-spectrum antibiotics. Subtractive genome analysis reveals the genes that are conserved in all or most of the pathogenic bacteria but not in eukaryotes; these are the most obvious candidates for drug targets. Species-specific genes, on the other hand, may offer the possibility to design drugs against a particular, narrow group of pathogens.     

Identification and analysis of cation channel homologues in human pathogenic fungi

Fungi are major causes of human, animal and plant disease. Human fungal infections can be fatal, but there are limited options for therapy, and resistance to commonly used anti-fungal drugs is widespread. The genomes of many fungi have recently been sequenced, allowing identification of proteins that may become targets for novel therapies. We examined the genomes of human fungal pathogens for genes encoding homologues of cation channels, which are prominent drug targets. Many of the fungal genomes examined contain genes encoding homologues of potassium (K(+)), calcium (Ca(2+)) and transient receptor potential (Trp) channels, but not sodium (Na(+)) channels or ligand-gated channels. Some fungal genomes contain multiple genes encoding homologues of K(+) and Trp channel subunits, and genes encoding novel homologues of voltage-gated K(v) channel subunits are found in Cryptococcus spp. Only a single gene encoding a homologue of a plasma membrane Ca(2+) channel was identified in the genome of each pathogenic fungus examined. These homologues are similar to the Cch1 Ca(2+) channel of Saccharomyces cerevisiae. The genomes of Aspergillus spp. and Cryptococcus spp., but not those of S. cerevisiae or the other pathogenic fungi examined, also encode homologues of the mitochondrial Ca(2+) uniporter (MCU). In contrast to humans, which express many K(+), Ca(2+) and Trp channels, the genomes of pathogenic fungi encode only very small numbers of K(+), Ca(2+) and Trp channel homologues. Furthermore, the sequences of fungal K(+), Ca(2+), Trp and MCU channels differ from those of human channels in regions that suggest differences in regulation and susceptibility to drugs.     

Microbial genomics: rhetoric or reality?

The availability of complete genome sequences of many bacterial species is facilitating numerous computational approaches for understanding bacterial genomes. One of the major incentives behind the genome sequencing of many pathogenic bacteria is the desire to better understand their diversity and to develop new approaches for controlling human diseases caused by these microorganisms. This task has become even more urgent with the rapid evolution of antibiotic resistance among many bacterial pathogens. Novel drug targets are required in order to design new antimicrobials against antibiotic-resistant pathogens. The complete genome sequences of an ever increasing number of pathogenic microbes constitute an invaluable resource and provide lead information on potential drug targets. This review focuses on in silico analyses of microbial genomes, their host-specific adaptations, with specific reference to genome architecture, design, evolution, and trends in computational identification of microbial drug targets. These trends underscore the utility of genomic data for systematic in silico drug target identification in the post-genomic era.     

NEAT: a domain duplicated in genes near the components of a putative Fe3+ siderophore transporter from Gram-positive pathogenic bacteria

Background  

Iron uptake from the host is essential for bacteria that infect animals. To find potential targets for drugs active against pathogenic bacteria, we have searched all completely sequenced genomes of pathogenic bacteria for genes relevant for iron transport.     

PcrA/UvrD/Rep DNA helicases in bacterial genomes

Helicases, which utilize the energy liberated by the hydrolysis of nucleotides to unwind nucleic acids, are involved in many aspects of nucleic acid metabolism. Various DNA helicases from the PcrA/UvrD/Rep subfamily are essential for the survival of different pathogenic bacteria and we have recently shown that they can be inhibited with small synthetic molecules. Altogether this suggests that these enzymes are potential new drug targets. Since little is known about the presence of these enzymes in bacterial genomes, 99 bacterial genomes were analyzed in the present study. This analysis reveals which and how many of these enzymes are found in bacteria, but more important, it identifies several of these enzymes as potential drug target candidates. In addition, this work identifies several proteins, called here PURL, that have a high homology with the PcrA/UvrD/Rep proteins and that may form an additional group in this helicase subfamily.     

Identification of intracellular and plasma membrane calcium channel homologues in pathogenic parasites

Ca(2+) channels regulate many crucial processes within cells and their abnormal activity can be damaging to cell survival, suggesting that they might represent attractive therapeutic targets in pathogenic organisms. Parasitic diseases such as malaria, leishmaniasis, trypanosomiasis and schistosomiasis are responsible for millions of deaths each year worldwide. The genomes of many pathogenic parasites have recently been sequenced, opening the way for rational design of targeted therapies. We analyzed genomes of pathogenic protozoan parasites as well as the genome of Schistosoma mansoni, and show the existence within them of genes encoding homologues of mammalian intracellular Ca(2+) release channels: inositol 1,4,5-trisphosphate receptors (IP(3)Rs), ryanodine receptors (RyRs), two-pore Ca(2+) channels (TPCs) and intracellular transient receptor potential (Trp) channels. The genomes of Trypanosoma, Leishmania and S. mansoni parasites encode IP(3)R/RyR and Trp channel homologues, and that of S. mansoni additionally encodes a TPC homologue. In contrast, apicomplexan parasites lack genes encoding IP(3)R/RyR homologues and possess only genes encoding TPC and Trp channel homologues (Toxoplasma gondii) or Trp channel homologues alone. The genomes of parasites also encode homologues of mammalian Ca(2+) influx channels, including voltage-gated Ca(2+) channels and plasma membrane Trp channels. The genome of S. mansoni also encodes Orai Ca(2+) channel and STIM Ca(2+) sensor homologues, suggesting that store-operated Ca(2+) entry may occur in this parasite. Many anti-parasitic agents alter parasite Ca(2+) homeostasis and some are known modulators of mammalian Ca(2+) channels, suggesting that parasite Ca(2+) channel homologues might be the targets of some current anti-parasitic drugs. Differences between human and parasite Ca(2+) channels suggest that pathogen-specific targeting of these channels may be an attractive therapeutic prospect.     

Genes encoding putative biogenic amine receptors in the parasitic nematode <Emphasis Type="Italic">Brugia </Emphasis><Emphasis Type="Italic">malayi</Emphasis>

Filarial nematodes, such as Brugia malayi, cause major health problems worldwide. The lack of a vaccine against B. malayi, combined with ineffective chemotherapy against the adult has prompted the examination of biogenic amine receptors (BARs) as possible targets for drug discovery. We employed bioinformatics to identify genes encoding putative B. malayi BARs. Surprisingly, the B. malayi genome contains half of the genes predicted to encode BARs in the genomes of free-living nematodes such as Caenorhabditis elegans or C. briggsae; however, all of the predicted B. malayi receptors have clear orthologues in C. elegans. The B. malayi genes encode each of the major BAR subclasses, including three serotonin, two dopamine and two tyramine/octopamine receptors and the structure of orthologous BAR genes is conserved. We find that potential G-protein coupling and ligand-specificity of individual BARs may be predicted by phylogenetic comparisons. Our results provide a framework for how G-protein coupled receptors may be targeted for drug development in medically important parasitic nematodes.     

Do we need new antibiotics? The search for new targets and new compounds

Resistance to antibiotics and other antimicrobial compounds continues to increase. There are several possibilities for protection against pathogenic microorganisms, for instance, preparation of new vaccines against resistant bacterial strains, use of specific bacteriophages, and searching for new antibiotics. The antibiotic search includes: (1) looking for new antibiotics from nontraditional or less traditional sources, (2) sequencing microbial genomes with the aim of finding genes specifying biosynthesis of antibiotics, (3) analyzing DNA from the environment (metagenomics), (4) reexamining forgotten natural compounds and products of their transformations, and (5) investigating new antibiotic targets in pathogenic bacteria.     

Predicting conserved essential genes in bacteria: in silico identification of putative drug targets

Many genes have been listed as putatively essential for bacterial viability in the Database of Essential Genomes (DEG), although few have been experimentally validated. By prioritising targets according to the criteria suggested by the Research and Training in Tropical Diseases (TDR) Targets database, we have developed a modified down-selection tool to identify essential genes conserved across diverse genera. Using this approach we identified 52 proteins conserved to 7 or more of the 14 genomes in DEG. We confirmed the validity of the down-selection by attempting to make mutants of 8 of these targets in a model organism, Yersinia pseudotuberculosis, which is not closely related to any of the bacteria in DEG. Mutants were recovered for only one of the 8 targets, suggesting that the other 7 were essential in Y. pseudotuberculosis, an impressive success rate compared to other approaches of identification for such targets. Identification of essential proteins common in diverse bacterial genera can then be used to facilitate the selection of effective targets for novel broad-spectrum antibiotics.     

From genetic footprinting to antimicrobial drug targets: examples in cofactor biosynthetic pathways

Novel drug targets are required in order to design new defenses against antibiotic-resistant pathogens. Comparative genomics provides new opportunities for finding optimal targets among previously unexplored cellular functions, based on an understanding of related biological processes in bacterial pathogens and their hosts. We describe an integrated approach to identification and prioritization of broad-spectrum drug targets. Our strategy is based on genetic footprinting in Escherichia coli followed by metabolic context analysis of essential gene orthologs in various species. Genes required for viability of E. coli in rich medium were identified on a whole-genome scale using the genetic footprinting technique. Potential target pathways were deduced from these data and compared with a panel of representative bacterial pathogens by using metabolic reconstructions from genomic data. Conserved and indispensable functions revealed by this analysis potentially represent broad-spectrum antibacterial targets. Further target prioritization involves comparison of the corresponding pathways and individual functions between pathogens and the human host. The most promising targets are validated by direct knockouts in model pathogens. The efficacy of this approach is illustrated using examples from metabolism of adenylate cofactors NAD(P), coenzyme A, and flavin adenine dinucleotide. Several drug targets within these pathways, including three distantly related adenylyltransferases (orthologs of the E. coli genes nadD, coaD, and ribF), are discussed in detail.     

In silico prediction of drug targets in <Emphasis Type="Italic">Vibrio cholerae</Emphasis>

Identification of potential drug targets is the first step in the process of modern drug discovery, subjected to their validation and drug development. Whole genome sequences of a number of organisms allow prediction of potential drug targets using sequence comparison approaches. Here, we present a subtractive approach exploiting the knowledge of global gene expression along with sequence comparisons to predict the potential drug targets more efficiently. Based on the knowledge of 155 known virulence and their coexpressed genes mined from microarray database in the public domain, 357 coexpressed probable virulence genes for Vibrio cholerae were predicted. Based on screening of Database of Essential Genes using blastn, a total of 102 genes out of these 357 were enlisted as vitally essential genes, and hence good putative drug targets. As the effective drug target is a protein which is only present in the pathogen, similarity search of these 102 essential genes against human genome sequence led to subtraction of 66 genes, thus leaving behind a subset of 36 genes whose products have been called as potential drug targets. The gene ontology analysis using Blast2GO of these 36 genes revealed their roles in important metabolic pathways of V. cholerae or on the surface of the pathogen. Thus, we propose that the products of these genes be evaluated as target sites of drugs against V. cholerae in future investigations.     

Identification of 113 conserved essential genes using a high-throughput gene disruption system in Streptococcus pneumoniae

The recent availability of bacterial genome sequence information permits the identification of conserved genes that are potential targets for novel antibiotic drug discovery. Using a coupled bioinformatic/experimental approach, a list of candidate conserved genes was generated using a Microbial Concordance bioinformatics tool followed by a targeted disruption campaign. Pneumococcal sequence data allowed for the design of precise PCR primers to clone the desired gene target fragments into the pEVP3 ‘suicide vector’. An insertion–duplication approach was employed that used the pEVP3 constructs and resulted in the introduction of a selectable chloramphenicol resistance marker into the chromosome. In the case of non-essential genes, cells can survive the disruption and form chloramphenicol-resistant colonies. A total of 347 candidate reading frames were subjected to disruption analysis, with 113 presumed to be essential due to lack of recovery of antibiotic-resistant colonies. In addition to essentiality determination, the same high-throughput methodology was used to overexpress gene products and to examine possible polarity effects for all essential genes.     

A systems biology approach to drug targets in Pseudomonas aeruginosa biofilm

Antibiotic resistance is an increasing problem in the health care system and we are in a constant race with evolving bacteria. Biofilm-associated growth is thought to play a key role in bacterial adaptability and antibiotic resistance. We employed a systems biology approach to identify candidate drug targets for biofilm-associated bacteria by imitating specific microenvironments found in microbial communities associated with biofilm formation. A previously reconstructed metabolic model of Pseudomonas aeruginosa (PA) was used to study the effect of gene deletion on bacterial growth in planktonic and biofilm-like environmental conditions. A set of 26 genes essential in both conditions was identified. Moreover, these genes have no homology with any human gene. While none of these genes were essential in only one of the conditions, we found condition-dependent genes, which could be used to slow growth specifically in biofilm-associated PA. Furthermore, we performed a double gene deletion study and obtained 17 combinations consisting of 21 different genes, which were conditionally essential. While most of the difference in double essential gene sets could be explained by different medium composition found in biofilm-like and planktonic conditions, we observed a clear effect of changes in oxygen availability on the growth performance. Eight gene pairs were found to be synthetic lethal in oxygen-limited conditions. These gene sets may serve as novel metabolic drug targets to combat particularly biofilm-associated PA. Taken together, this study demonstrates that metabolic modeling of human pathogens can be used to identify oxygen-sensitive drug targets and thus, that this systems biology approach represents a powerful tool to identify novel candidate antibiotic targets.     

Genomics and computational molecular biology

There has been a dramatic increase in the number of completely sequenced bacterial genomes during the past two years as a result of the efforts both of public genome agencies and the pharmaceutical industry. The availability of completely sequenced genomes permits more systematic analyses of genes, evolution and genome function than was otherwise possible. Using computational methods - which are used to identify genes and their functions including statistics, sequence similarity, motifs, profiles, protein folds and probabilistic models - it is possible to develop characteristic genome signatures, assign functions to genes, identify pathogenic genes, identify metabolic pathways, develop diagnostic probes and discover potential drug-binding sites. All of these directions are critical to understanding bacterial growth, pathogenicity and host-pathogen interactions.     

Structural characterization of CA1462, the <Emphasis Type="Italic">Candida albicans</Emphasis> thiamine pyrophosphokinase

Background  

In search of new antifungal targets of potential interest for pharmaceutical companies, we initiated a comparative genomics study to identify the most promising protein-coding genes in fungal genomes. One criterion was the protein sequence conservation between reference pathogenic genomes. A second criterion was that the corresponding gene in Saccharomyces cerevisiae should be essential. Since thiamine pyrophosphate is an essential product involved in a variety of metabolic pathways, proteins responsible for its production satisfied these two criteria.     

Computational bacterial genome-wide analysis of phylogenetic profiles reveals potential virulence genes of Streptococcus agalactiae

The phylogenetic profile of a gene is a reflection of its evolutionary history and can be defined as the differential presence or absence of a gene in a set of reference genomes. It has been employed to facilitate the prediction of gene functions. However, the hypothesis that the application of this concept can also facilitate the discovery of bacterial virulence factors has not been fully examined. In this paper, we test this hypothesis and report a computational pipeline designed to identify previously unknown bacterial virulence genes using group B streptococcus (GBS) as an example. Phylogenetic profiles of all GBS genes across 467 bacterial reference genomes were determined by candidate-against-all BLAST searches,which were then used to identify candidate virulence genes by machine learning models. Evaluation experiments with known GBS virulence genes suggested good functional and model consistency in cross-validation analyses (areas under ROC curve, 0.80 and 0.98 respectively). Inspection of the top-10 genes in each of the 15 virulence functional groups revealed at least 15 (of 119) homologous genes implicated in virulence in other human pathogens but previously unrecognized as potential virulence genes in GBS. Among these highly-ranked genes, many encode hypothetical proteins with possible roles in GBS virulence. Thus, our approach has led to the identification of a set of genes potentially affecting the virulence potential of GBS, which are potential candidates for further in vitro and in vivo investigations. This computational pipeline can also be extended to in silico analysis of virulence determinants of other bacterial pathogens.     

Mining virulence genes using metagenomics

When a bacterial genome is compared to the metagenome of an environment it inhabits, most genes recruit at high sequence identity. In free-living bacteria (for instance marine bacteria compared against the ocean metagenome) certain genomic regions are totally absent in recruitment plots, representing therefore genes unique to individual bacterial isolates. We show that these Metagenomic Islands (MIs) are also visible in bacteria living in human hosts when their genomes are compared to sequences from the human microbiome, despite the compartmentalized structure of human-related environments such as the gut. From an applied point of view, MIs of human pathogens (e.g. those identified in enterohaemorragic Escherichia coli against the gut metagenome or in pathogenic Neisseria meningitidis against the oral metagenome) include virulence genes that appear to be absent in related strains or species present in the microbiome of healthy individuals. We propose that this strategy (i.e. recruitment analysis of pathogenic bacteria against the metagenome of healthy subjects) can be used to detect pathogenicity regions in species where the genes involved in virulence are poorly characterized. Using this approach, we detect well-known pathogenicity islands and identify new potential virulence genes in several human pathogens.