Wild-Type Phosphoribosylpyrophosphate Synthase (PRS) from Mycobacterium tuberculosis: A Bacterial Class II PRS?

The 5-phospho-α-D-ribose 1-diphosphate (PRPP) metabolite plays essential roles in several biosynthetic pathways, including histidine, tryptophan, nucleotides, and, in mycobacteria, cell wall precursors. PRPP is synthesized from α-D-ribose 5-phosphate (R5P) and ATP by the Mycobacterium tuberculosis prsA gene product, phosphoribosylpyrophosphate synthase (MtPRS). Here, we report amplification, cloning, expression and purification of wild-type MtPRS. Glutaraldehyde cross-linking results suggest that MtPRS predominates as a hexamer, presenting varied oligomeric states due to distinct ligand binding. MtPRS activity measurements were carried out by a novel coupled continuous spectrophotometric assay. MtPRS enzyme activity could be detected in the absence of Pi. ADP, GDP and UMP inhibit MtPRS activity. Steady-state kinetics results indicate that MtPRS has broad substrate specificity, being able to accept ATP, GTP, CTP, and UTP as diphosphoryl group donors. Fluorescence spectroscopy data suggest that the enzyme mechanism for purine diphosphoryl donors follows a random order of substrate addition, and for pyrimidine diphosphoryl donors follows an ordered mechanism of substrate addition in which R5P binds first to free enzyme. An ordered mechanism for product dissociation is followed by MtPRS, in which PRPP is the first product to be released followed by the nucleoside monophosphate products to yield free enzyme for the next round of catalysis. The broad specificity for diphosphoryl group donors and detection of enzyme activity in the absence of Pi would suggest that MtPRS belongs to Class II PRS proteins. On the other hand, the hexameric quaternary structure and allosteric ADP inhibition would place MtPRS in Class I PRSs. Further data are needed to classify MtPRS as belonging to a particular family of PRS proteins. The data here presented should help augment our understanding of MtPRS mode of action. Current efforts are toward experimental structure determination of MtPRS to provide a solid foundation for the rational design of specific inhibitors of this enzyme

In vivo and in silico determination of essential genes of Campylobacter jejuni

<p>Abstract</p> <p>Background</p> <p>In the United Kingdom, the thermophilic <it>Campylobacter </it>species <it>C. jejuni </it>and <it>C. coli </it>are the most frequent causes of food-borne gastroenteritis in humans. While campylobacteriosis is usually a relatively mild infection, it has a significant public health and economic impact, and possible complications include reactive arthritis and the autoimmune diseases Guillain-Barré syndrome. The rapid developments in "omics" technologies have resulted in the availability of diverse datasets allowing predictions of metabolism and physiology of pathogenic micro-organisms. When combined, these datasets may allow for the identification of potential weaknesses that can be used for development of new antimicrobials to reduce or eliminate <it>C. jejuni </it>and <it>C. coli </it>from the food chain.</p> <p>Results</p> <p>A metabolic model of <it>C. jejuni </it>was constructed using the annotation of the NCTC 11168 genome sequence, a published model of the related bacterium <it>Helicobacter pylori</it>, and extensive literature mining. Using this model, we have used <it>in silico </it>Flux Balance Analysis (FBA) to determine key metabolic routes that are essential for generating energy and biomass, thus creating a list of genes potentially essential for growth under laboratory conditions. To complement this <it>in silico </it>approach, candidate essential genes have been determined using a whole genome transposon mutagenesis method. FBA and transposon mutagenesis (both this study and a published study) predict a similar number of essential genes (around 200). The analysis of the intersection between the three approaches highlights the shikimate pathway where genes are predicted to be essential by one or more method, and tend to be network hubs, based on a previously published <it>Campylobacter </it>protein-protein interaction network, and could therefore be targets for novel antimicrobial therapy.</p> <p>Conclusions</p> <p>We have constructed the first curated metabolic model for the food-borne pathogen <it>Campylobacter jejuni </it>and have presented the resulting metabolic insights. We have shown that the combination of <it>in silico </it>and <it>in vivo </it>approaches could point to non-redundant, indispensable genes associated with the well characterised shikimate pathway, and also genes of unknown function specific to <it>C. jejuni</it>, which are all potential novel <it>Campylobacter </it>intervention targets.</p

The Mycobacterium tuberculosis Drugome and Its Polypharmacological Implications

We report a computational approach that integrates structural bioinformatics, molecular modelling and systems biology to construct a drug-target network on a structural proteome-wide scale. The approach has been applied to the genome of Mycobacterium tuberculosis (M.tb), the causative agent of one of today's most widely spread infectious diseases. The resulting drug-target interaction network for all structurally characterized approved drugs bound to putative M.tb receptors, we refer to as the ‘TB-drugome’. The TB-drugome reveals that approximately one-third of the drugs examined have the potential to be repositioned to treat tuberculosis and that many currently unexploited M.tb receptors may be chemically druggable and could serve as novel anti-tubercular targets. Furthermore, a detailed analysis of the TB-drugome has shed new light on the controversial issues surrounding drug-target networks [1]–[3]. Indeed, our results support the idea that drug-target networks are inherently modular, and further that any observed randomness is mainly caused by biased target coverage. The TB-drugome (http://funsite.sdsc.edu/drugome/TB) has the potential to be a valuable resource in the development of safe and efficient anti-tubercular drugs. More generally the methodology may be applied to other pathogens of interest with results improving as more of their structural proteomes are determined through the continued efforts of structural biology/genomics