Dany J. V. Beste

GSMN-TB: a web-based genome scale network model of Mycobacterium tuberculosis metabolism

BackgroundAn impediment to the rational development of novel drugs against tuberculosis (TB) is a general paucity of knowledge concerning the metabolism of Mycobacterium tuberculosis, particularly during infection. Constraint-based modeling provides a novel approach to investigating microbial metabolism but has not yet been applied to genome-scale modeling of M. tuberculosis.ResultsGSMN-TB, a genome-scale metabolic model of M. tuberculosis, was constructed, consisting of 849 unique reactions and 739 metabolites, and involving 726 genes. The model was calibrated by growing Mycobacterium bovis bacille Calmette Guérin in continuous culture and steady-state growth parameters were measured. Flux balance analysis was used to calculate substrate consumption rates, which were shown to correspond closely to experimentally determined values. Predictions of gene essentiality were also made by flux balance analysis simulation and were compared with global mutagenesis data for M. tuberculosis grown in vitro. A prediction accuracy of 78% was achieved. Known drug targets were predicted to be essential by the model. The model demonstrated a potential role for the enzyme isocitrate lyase during the slow growth of mycobacteria, and this hypothesis was experimentally verified. An interactive web-based version of the model is available.ConclusionThe GSMN-TB model successfully simulated many of the growth properties of M. tuberculosis. The model provides a means to examine the metabolic flexibility of bacteria and predict the phenotype of mutants, and it highlights previously unexplored features of M. tuberculosis metabolism.

The Genetic Requirements for Fast and Slow Growth in Mycobacteria

Mycobacterium tuberculosis infects a third of the worlds population. Primary tuberculosis involving active fast bacterial replication is often followed by asymptomatic latent tuberculosis, which is characterised by slow or non-replicating bacteria. Reactivation of the latent infection involving a switch back to active bacterial replication can lead to post-primary transmissible tuberculosis. Mycobacterial mechanisms involved in slow growth or switching growth rate provide rational targets for the development of new drugs against persistent mycobacterial infection. Using chemostat culture to control growth rate, we screened a transposon mutant library by Transposon site hybridization (TraSH) selection to define the genetic requirements for slow and fast growth of Mycobacterium bovis (BCG) and for the requirements of switching growth rate. We identified 84 genes that are exclusively required for slow growth (69 hours doubling time) and 256 genes required for switching from slow to fast growth. To validate these findings we performed experiments using individual M. tuberculosis and M. bovis BCG knock out mutants. We have demonstrated that growth rate control is a carefully orchestrated process which requires a distinct set of genes encoding several virulence determinants, gene regulators, and metabolic enzymes. The mce1 locus appears to be a component of the switch to slow growth rate, which is consistent with the proposed role in virulence of M. tuberculosis. These results suggest novel perspectives for unravelling the mechanisms involved in the switch between acute and persistent TB infections and provide a means to study aspects of this important phenomenon in vitro.

C metabolic flux analysis identifies an unusual route for pyruvate dissimilation in mycobacteria which requires isocitrate lyase and carbon dioxide fixation.

Mycobacterium tuberculosis requires the enzyme isocitrate lyase (ICL) for growth and virulence in vivo. The demonstration that M. tuberculosis also requires ICL for survival during nutrient starvation and has a role during steady state growth in a glycerol limited chemostat indicates a function for this enzyme which extends beyond fat metabolism. As isocitrate lyase is a potential drug target elucidating the role of this enzyme is of importance; however, the role of isocitrate lyase has never been investigated at the level of in vivo fluxes. Here we show that deletion of one of the two icl genes impairs the replication of Mycobacterium bovis BCG at slow growth rate in a carbon limited chemostat. In order to further understand the role of isocitrate lyase in the central metabolism of mycobacteria the effect of growth rate on the in vivo fluxes was studied for the first time using 13C-metabolic flux analysis (MFA). Tracer experiments were performed with steady state chemostat cultures of BCG or M. tuberculosis supplied with 13C labeled glycerol or sodium bicarbonate. Through measurements of the 13C isotopomer labeling patterns in protein-derived amino acids and enzymatic activity assays we have identified the activity of a novel pathway for pyruvate dissimilation. We named this the GAS pathway because it utilizes the Glyoxylate shunt and Anapleurotic reactions for oxidation of pyruvate, and Succinyl CoA synthetase for the generation of succinyl CoA combined with a very low flux through the succinate – oxaloacetate segment of the tricarboxylic acid cycle. We confirm that M. tuberculosis can fix carbon from CO2 into biomass. As the human host is abundant in CO2 this finding requires further investigation in vivo as CO2 fixation may provide a point of vulnerability that could be targeted with novel drugs. This study also provides a platform for further studies into the metabolism of M. tuberculosis using 13C-MFA.

13C-flux spectral analysis of host-pathogen metabolism reveals a mixed diet for intracellular Mycobacterium tuberculosis.

Summary Whereas intracellular carbon metabolism has emerged as an attractive drug target, the carbon sources of intracellularly replicating pathogens, such as the tuberculosis bacillus Mycobacterium tuberculosis, which causes long-term infections in one-third of the world’s population, remain mostly unknown. We used a systems-based approach—13C-flux spectral analysis (FSA) complemented with manual analysis—to measure the metabolic interaction between M. tuberculosis and its macrophage host cell. 13C-FSA analysis of experimental data showed that M. tuberculosis obtains a mixture of amino acids, C1 and C2 substrates from its host cell. We experimentally confirmed that the C1 substrate was derived from CO2. 13C labeling experiments performed on a phosphoenolpyruvate carboxykinase mutant revealed that intracellular M. tuberculosis has access to glycolytic C3 substrates. These findings provide constraints for developing novel chemotherapeutics.

Compiling a Molecular Inventory for Mycobacterium bovis BCG at Two Growth Rates: Evidence for Growth Rate-Mediated Regulation of Ribosome Biosynthesis and Lipid Metabolism

An experimental system of Mycobacterium tuberculosis growth in a carbon-limited chemostat has been established by the use of Mycobacterium bovis BCG as a model organism. For this model, carbon-limited chemostats with low concentrations of glycerol were used to simulate possible growth rates during different stages of tuberculosis. A doubling time of 23 h (D = 0.03 h(-1)) was adopted to represent cells during the acute phase of infection, whereas a lower dilution rate equivalent to a doubling time of 69 h (D = 0.01 h(-1)) was used to model mycobacterial persistence. This chemostat model allowed the specific response of the mycobacterial cell to carbon limitation at different growth rates to be elucidated. The macromolecular (RNA, DNA, carbohydrate, and lipid) and elemental (C, H, and N) compositions of the biomass were determined for steady-state cultures, revealing that carbohydrates and lipids comprised more than half of the dry mass of the BCG cell, with only a quarter of the dry weight consisting of protein and RNA. Consistent with studies of other bacteria, the specific growth rate impacts on the macromolecular content of BCG and the proportions of lipid, RNA, and protein increased significantly with the growth rate. The correlation of RNA content with the growth rate indicates that ribosome production in carbon-limited M. bovis BCG cells is subject to growth rate-dependent control. The results also clearly show that the proportion of lipids in the mycobacterial cell is very sensitive to changes in the growth rate, probably reflecting changes in the amounts of storage lipids. Finally, this study demonstrates the utility of the chemostat model of mycobacterial growth for functional genomic, physiology, and systems biology studies.

Transcriptomic Analysis Identifies Growth Rate Modulation as a Component of the Adaptation of Mycobacteria to Survival inside the Macrophage

The adaptation of the tubercle bacillus to the host environment is likely to involve a complex set of gene regulatory events and physiological switches in response to environmental signals. In order to deconstruct the physiological state of Mycobacterium tuberculosis in vivo, we used a chemostat model to study a single aspect of the organisms in vivo state, slow growth. Mycobacterium bovis BCG was cultivated at high and low growth rates in a carbon-limited chemostat, and transcriptomic analysis was performed to identify the gene regulation events associated with slow growth. The results demonstrated that slow growth was associated with the induction of expression of several genes of the dormancy survival regulon. There was also a striking overlap between the transcriptomic profile of BCG in the chemostat model and the response of M. tuberculosis to growth in the macrophage, implying that a significant component of the response of the pathogen to the macrophage environment is the response to slow growth in carbon-limited conditions. This demonstrated the importance of adaptation to a low growth rate to the virulence strategy of M. tuberculosis and also the value of the chemostat model for deconstructing components of the in vivo state of this important pathogen.

Systems-Based Approaches to Probing Metabolic Variation within the Mycobacterium tuberculosis Complex

The Mycobacterium tuberculosis complex includes bovine and human strains of the tuberculosis bacillus, including Mycobacterium tuberculosis, Mycobacterium bovis and the Mycobacterium bovis BCG vaccine strain. M. bovis has evolved from a M. tuberculosis-like ancestor and is the ancestor of the BCG vaccine. The pathogens demonstrate distinct differences in virulence, host range and metabolism, but the role of metabolic differences in pathogenicity is poorly understood. Systems biology approaches have been used to investigate the metabolism of M. tuberculosis, but not to probe differences between tuberculosis strains. In this study genome scale metabolic networks of M. bovis and M. bovis BCG were constructed and interrogated, along with a M. tuberculosis network, to predict substrate utilisation, gene essentiality and growth rates. The models correctly predicted 87-88% of high-throughput phenotype data, 75-76% of gene essentiality data and in silico-predicted growth rates matched measured rates. However, analysis of the metabolic networks identified discrepancies between in silico predictions and in vitro data, highlighting areas of incomplete metabolic knowledge. Additional experimental studies carried out to probe these inconsistencies revealed novel insights into the metabolism of these strains. For instance, that the reduction in metabolic capability observed in bovine tuberculosis strains, as compared to M. tuberculosis, is not reflected by current genetic or enzymatic knowledge. Hence, the in silico networks not only successfully simulate many aspects of the growth and physiology of these mycobacteria, but also provide an invaluable tool for future metabolic studies.

Differential Producibility Analysis (DPA) of Transcriptomic Data with Metabolic Networks: Deconstructing the Metabolic Response of M. tuberculosis

A general paucity of knowledge about the metabolic state of Mycobacterium tuberculosis within the host environment is a major factor impeding development of novel drugs against tuberculosis. Current experimental methods do not allow direct determination of the global metabolic state of a bacterial pathogen in vivo, but the transcriptional activity of all encoded genes has been investigated in numerous microarray studies. We describe a novel algorithm, Differential Producibility Analysis (DPA) that uses a metabolic network to extract metabolic signals from transcriptome data. The method utilizes Flux Balance Analysis (FBA) to identify the set of genes that affect the ability to produce each metabolite in the network. Subsequently, Rank Product Analysis is used to identify those metabolites predicted to be most affected by a transcriptional signal. We first apply DPA to investigate the metabolic response of E. coli to both anaerobic growth and inactivation of the FNR global regulator. DPA successfully extracts metabolic signals that correspond to experimental data and provides novel metabolic insights. We next apply DPA to investigate the metabolic response of M. tuberculosis to the macrophage environment, human sputum and a range of in vitro environmental perturbations. The analysis revealed a previously unrecognized feature of the response of M. tuberculosis to the macrophage environment: a down-regulation of genes influencing metabolites in central metabolism and concomitant up-regulation of genes that influence synthesis of cell wall components and virulence factors. DPA suggests that a significant feature of the response of the tubercle bacillus to the intracellular environment is a channeling of resources towards remodeling of its cell envelope, possibly in preparation for attack by host defenses. DPA may be used to unravel the mechanisms of virulence and persistence of M. tuberculosis and other pathogens and may have general application for extracting metabolic signals from other “-omics” data.

Analysis of Genes of Mitochondrial Origin in the Genus Entamoeba

Abstract The amitochondriate protistan parasite Entamoeba histolytica has lost most mitochondrial functions secondarily but has retained a reduced organelle of mitochondrial origin, the mitosome. We here investigate the presence, origins, and expression in other species of Entamoeba of three genes of mitochondrial origin—pyridine nucleotide transhydrogenase and the mitochondrial-type chaperonins cpn60 and hsp70. The genes appear to be present in all species and specifically related, confirming that the E. histolytica mitosomal genes were not acquired recently by lateral transfer from another organism. Detection of expression was not possible in all cases under the culture conditions used, but several genes were induced during recovery from exposure to a heat shock. This includes the transhydrogenase, which to our knowledge has not been shown previously to be a heat-shock protein.

System-level strategies for studying the metabolism of Mycobacterium tuberculosis

Predictive computational models of the metabolism of Mycobacterium tuberculosis facilitate drug discovery and a higher level of understanding of this important pathogen.