The structural insights of 16.3 kDa heat shock protein (HSP16.3) from Mycobacterium tuberculosis via in silico study

Mycobacterium tuberculosis (Mtb) is capable of surviving in dormancy before developing to tuberculosis (TB). One of the major challenges of TB management is the identification of patients, making TB diagnosis critical for disease management. This study focuses on the 16 kDa heat shock protein (HSP16.3; a potential biomarker for latent TB infection) that is expressed during the latent phase of Mtb growth. In order to explore the dynamics and interactions of HSP16.3, the 3-D structure of HSP16.3 was built via comparative modelling. The predicted structure shows a predominantly beta-sheet dodecamer with alpha-helical folds at its N-terminal. A known protein-hydrophobic probe (1,1′-Bi(4-anilino)naphthalene-5,5′-disulfonic acid; bisANS) was docked to the HSP16.3 model. Interacting residues predicted from docking and MD simulations are in good accordance with experimental data reported in the literature. MMPBSA calculation from MD simulation also showed favourable binding free energy of ?29.90 kcal/mol, driven mainly by van der waals and non-polar solvation energies. The statistical evaluation and results from the computational study on HSP16.3 indicate the reliability of the built model, which is potentially useful for further structural studies of HSP16.3 for latent TB diagnostics.     

The predicted Arabidopsis interactome resource and network topology-based systems biology analyses

Predicted interactions are a valuable complement to experimentally reported interactions in molecular mechanism studies, particularly for higher organisms, for which reported experimental interactions represent only a small fraction of their total interactomes. With careful engineering consideration of the lessons from previous efforts, the predicted arabidopsis interactome resource (PAIR; ) presents 149,900 potential molecular interactions, which are expected to cover approximately 24% of the entire interactome with approximately 40% precision. This study demonstrates that, although PAIR still has limited coverage, it is rich enough to capture many significant functional linkages within and between higher-order biological systems, such as pathways and biological processes. These inferred interactions can nicely power several network topology-based systems biology analyses, such as gene set linkage analysis, protein function prediction, and identification of regulatory genes demonstrating insignificant expression changes. The drastically expanded molecular network in PAIR has considerably improved the capability of these analyses to integrate existing knowledge and suggest novel insights into the function and coordination of genes and gene networks.     

Guinea pig model of Mycobacterium tuberculosis latent/dormant infection

Although guinea pigs are considered one of the best animal models of tuberculosis, little data exist describing latent or dormant tuberculosis infection in these animals. Here we address this issue using a streptomycin auxotrophic mutant of Mycobacterium tuberculosis. This mutant grows unimpaired in the presence of streptomycin but in its absence shifts to latency/dormancy (lack growth and over-expression of alpha-crystallin). To establish infection animals are inoculated with the mutant followed by daily administration of streptomycin (three weeks), which allows initial microbial multiplication in the animal's tissues. Withdrawal of streptomycin establishes latency/dormancy and few viable organisms are recovered from the animals' lungs and spleen six months later. During the infectious process guinea pigs steadily gained weight and presented no clinical signs (scuff fur and lethargy) of disease. Histopathology of organs mimicked tuberculous lesions in humans and PBMC from infected animals strongly responded to stimulation with PPD. Finally, tuberculin skin test (a hallmark of latent infection diagnosis) performed in infected animals was strongly positive (>or=15 mm induration). These results point to an interesting and reliable model of latent/dormant tuberculosis infection in guinea pigs.     

Not to wake a sleeping giant: new insights into host-pathogen interactions identify new targets for vaccination against latent Mycobacterium tuberculosis infection

Mycobacterium tuberculosis is one of the worlds' most successful and sophisticated pathogens. It is estimated that over 2 billion people today harbour latent M. tuberculosis infection without any clinical symptoms. As most new cases of active tuberculosis (TB) arise from this (growing) number of latently infected individuals, urgent measures to control TB reactivation are required, including post-exposure/therapeutic vaccines. The current bacille Calmette-Guérin (BCG) vaccine and all new generation TB vaccines being developed and tested are essentially designed as prophylactic vaccines. Unfortunately, these vaccines are unlikely to be effective in individuals already latently infected with M. tuberculosis. Here, we argue that detailed analysis of M. tuberculosis genes that are switched on predominantly during latent stage infection may lead to the identification of new antigenic targets for anti-TB strategies. We will describe essential host-pathogen interactions in TB with particular emphasis on TB latency and persistent infection. Subsequently, we will focus on novel groups of late-stage specific genes, encoded amongst others by the M. tuberculosis dormancy (dosR) regulon, and summarise recent studies describing human T-cell recognition of these dormancy antigens in relation to (latent) M. tuberculosis infection. We will discuss the possible relevance of these new classes of antigens for vaccine development against TB.     

Computational identification of protein-protein interactions in rice based on the predicted rice interactome network

Plant protein-protein interaction networks have not been identified by large-scale experiments. In order to better understand the protein interactions in rice, the Predicted Rice Interactome Network (PRIN; http://bis.zju.edu.cn/prin/) presented 76,585 predicted interactions involving 5,049 rice proteins. After mapping genomic features of rice (GO annotation, subcellular localization prediction, and gene expression), we found that a well-annotated and biologically significant network is rich enough to capture many significant functional linkages within higher-order biological systems, such as pathways and biological processes. Furthermore, we took MADS-box domain-containing proteins and circadian rhythm signaling pathways as examples to demonstrate that functional protein complexes and biological pathways could be effectively expanded in our predicted network. The expanded molecular network in PRIN has considerably improved the capability of these analyses to integrate existing knowledge and provide novel insights into the function and coordination of genes and gene networks.     

Large Mg(2+)-dependent currents are associated with the increased expression of ALR1 in Saccharomyces cerevisiae

Mycobacteria adapt to a decrease in oxygen tension by entry into a non-replicative persistent phase. It was shown earlier that the two-component system, DevR-DevS, was induced in Mycobacterium tuberculosis and Mycobacterium bovis BCG cultures during hypoxia, suggesting that it may play a regulatory role in their adaptation to oxygen limitation. The presence of a homologous genetic system in Mycobacterium smegmatis was predicted by scanning its unfinished genome sequence with devR and devS genes of M. tuberculosis. Rv3134c, which is cotranscribed with devR-devS in M. tuberculosis, was also present in M. smegmatis at a similar location upstream from devR. The expression of all three genes was induced at the RNA and protein levels in M. smegmatis cultures grown under microaerobic and anaerobic conditions. The M. smegmatis genome also contained the hspX gene, encoding chaperone alpha-crystallin, Acr, that was induced during hypoxia. The similarity in sequences and hypoxia-responsive behaviour of devR-devS, Rv3134c and hspX genes in M. smegmatis and M. tuberculosis suggests that the molecular mechanisms involved in the dormancy response are likely conserved in these two species. M. smegmatis could therefore serve as a useful model for the delineation of the hypoxia response in general and DevR-DevS regulated pathways in particular.     

Mycobacterium tuberculosis DosR regulon gene Rv0079 encodes a putative, 'dormancy associated translation inhibitor (DATIN)'

Mycobacterium tuberculosis is a major human pathogen that has evolved survival mechanisms to persist in an immune-competent host under a dormant condition. The regulation of M. tuberculosis metabolism during latent infection is not clearly known. The dormancy survival regulon (DosR regulon) is chiefly responsible for encoding dormancy related functions of M. tuberculosis. We describe functional characterization of an important gene of DosR regulon, Rv0079, which appears to be involved in the regulation of translation through the interaction of its product with bacterial ribosomal subunits. The protein encoded by Rv0079, possibly, has an inhibitory role with respect to protein synthesis, as revealed by our experiments. We performed computational modelling and docking simulation studies involving the protein encoded by Rv0079 followed by in vitro translation and growth curve analysis experiments, involving recombinant E. coli and Bacille Calmette Guérin (BCG) strains that overexpressed Rv0079. Our observations concerning the interaction of the protein with the ribosomes are supportive of its role in regulation/inhibition of translation. We propose that the protein encoded by locus Rv0079 is a 'dormancy associated translation inhibitor' or DATIN.     

A model to predict cell-mediated immune regulatory mechanisms during human infection with Mycobacterium tuberculosis

A key issue for the study of tuberculosis infection (TB) is to understand why individuals infected with Mycobacterium tuberculosis experience different clinical outcomes. Elaborating the immune mechanisms that determine whether an infected individual will suffer active TB or latent infection can aid in developing treatment and prevention strategies. To better understand the dynamics of M. tuberculosis infection and immunity, we have developed a virtual human model that qualitatively and quantitatively characterizes the cellular and cytokine control network operational during TB infection. Using this model, we identify key regulatory elements in the host response. In particular, factors affecting cell functions, such as macrophage activation and bactericidal capabilities, and effector T cell functions such as cytotoxicity and cytokine production can each be determinative. The model indicates, however, that even if latency is achieved, it may come at the expense of tissue damage if the response is not properly regulated. A balance in Th1 and Th2 immune responses governed by IFN-gamma, IL-10, and IL-4 facilitate this down-regulation. These results are further explored through virtual deletion and depletion experiments.     

An analysis of the class of gene regulatory functions implied by a biochemical model

Understanding the integrated behavior of genetic regulatory networks, in which genes regulate one another's activities via RNA and protein products, is emerging as a dominant problem in systems biology. One widely studied class of models of such networks includes genes whose expression values assume Boolean values (i.e., on or off). Design decisions in the development of Boolean network models of gene regulatory systems include the topology of the network (including the distribution of input- and output-connectivity) and the class of Boolean functions used by each gene (e.g., canalizing functions, post functions, etc.). For example, evidence from simulations suggests that biologically realistic dynamics can be produced by scale-free network topologies with canalizing Boolean functions. This work seeks further insights into the design of Boolean network models through the construction and analysis of a class of models that include more concrete biochemical mechanisms than the usual abstract model, including genes and gene products, dimerization, cis-binding sites, promoters and repressors. In this model, it is assumed that the system consists of N genes, with each gene producing one protein product. Proteins may form complexes such as dimers, trimers, etc. The model also includes cis-binding sites to which proteins may bind to form activators or repressors. Binding affinities are based on structural complementarity between proteins and binding sites, with molecular binding sites modeled by bit-strings. Biochemically plausible gene expression rules are used to derive a Boolean regulatory function for each gene in the system. The result is a network model in which both topological features and Boolean functions arise as emergent properties of the interactions of components at the biochemical level. A highly biased set of Boolean functions is observed in simulations of networks of various sizes, suggesting a new characterization of the subset of Boolean functions that are likely to appear in gene regulatory networks.     

A Boolean Model of the Pseudomonas syringae hrp Regulon Predicts a Tightly Regulated System

The Type III secretion system (TTSS) is a protein secretion machinery used by certain gram-negative bacterial pathogens of plants and animals to deliver effector molecules to the host and is at the core of the ability to cause disease. Extensive molecular and biochemical study has revealed the components and their interactions within this system but reductive approaches do not consider the dynamical properties of the system as a whole. In order to gain a better understanding of these dynamical behaviours and to create a basis for the refinement of the experimentally derived knowledge we created a Boolean model of the regulatory interactions within the hrp regulon of Pseudomonas syringae pathovar tomato strain DC3000 Pseudomonas syringae. We compared simulations of the model with experimental data and found them to be largely in accordance, though the hrpV node shows some differences in state changes to that expected. Our simulations also revealed interesting dynamical properties not previously predicted. The model predicts that the hrp regulon is a biologically stable two-state system, with each of the stable states being strongly attractive, a feature indicative of selection for a tightly regulated and responsive system. The model predicts that the state of the GacS/GacA node confers control, a prediction that is consistent with experimental observations that the protein has a role as master regulator. Simulated gene “knock out” experiments with the model predict that HrpL is a central information processing point within the network.     

The dormancy regulator DosR controls ribosome stability in hypoxic mycobacteria

It is thought that during latent infection, Mycobacterium tuberculosis bacilli are retained within granulomas in a low-oxygen environment. The dormancy survival (Dos) regulon, regulated by the response regulator DosR, appears to be essential for hypoxic survival in M. tuberculosis, but it is not known how the regulon promotes survival. Here we report that mycobacteria, in contrast to enteric bacteria, do not form higher-order structures (e.g. ribosomal dimers) upon entry into stasis. Instead, ribosomes are stabilized in the associated form (70S). Using a strategy incorporating microfluidic, proteomic, and ribosomal profiling techniques to elucidate the fate of mycobacterial ribosomes during hypoxic stasis, we show that the dormancy regulator DosR is required for optimal ribosome stabilization. We present evidence that the majority of this effect is mediated by the DosR-regulated protein MSMEG_3935 (a S30AE domain protein), which is associated with the ribosome under hypoxic conditions. A Δ3935 mutant phenocopies the ΔdosR mutant during hypoxia, and complementation of ΔdosR with the MSMEG_3935 gene leads to complete recovery of dosR mutant phenotypes during hypoxia. We suggest that this protein is named ribosome-associated factor under hypoxia (RafH) and that it is the major factor responsible for DosR-mediated hypoxic survival in mycobacteria.