Systems biology of tuberculosis

Early Drug Development and Evaluation of Putative Antitubercular Compounds in the -Omics Era

Tuberculosis (TB) is an infectious disease caused by the bacterium Mycobacterium tuberculosis. According to the WHO, the disease is one of the top 10 causes of death of people worldwide. Mycobacterium tuberculosis is an intracellular pathogen with an unusually thick, waxy cell wall and a complex life cycle. These factors, combined with M. tuberculosis ability to enter prolonged periods of latency, make the bacterium very difficult to eradicate. The standard treatment of TB requires 6-20months, depending on the drug susceptibility of the infecting strain. The need to take cocktails of antibiotics to treat tuberculosis effectively and the emergence of drug-resistant strains prompts the need to search for new antitubercular compounds. This review provides a perspective on how modern -omic technologies facilitate the drug discovery process for tuberculosis treatment. We discuss how methods of DNA and RNA sequencing, proteomics, and genetic manipulation of organisms increase our understanding of mechanisms of action of antibiotics and allow the evaluation of drugs. We explore the utility of mathematical modeling and modern computational analysis for the drug discovery process. Finally, we summarize how -omic technologies contribute to our understanding of the emergence of drug resistance.

THE GROWTH RATE PHENOTYPIC PROPERTY OF MYCOBACTERIUM TUBERCULOSIS CLINICAL STRAINS: DEPENDENCE ON TUBERCULOSIS LOCALIZATION, TREATMENT, DRUG SUSCEPTIBILITY

The phenotypic properties of the M. tuberculosis strains obtained from patients with pulmonary or extra-pulmonary tuberculosis are  determined by a complex set of factors: the genetic characteristics  of the pathogen, its ability to adapt in vivo and in vitro, the influence of the host’s immune system and chemotherapy. The growth rate as  the phenotypic property is the most accessible for the study of the  host-pathogen relationships at the level of host/strain population  interactions. The aim of the study is to assess in vitro of the growth  rate of M. tuberculosis strains isolated from patients with pulmonary  and extra-pulmonary tuberculosis: untreated and treated (with  surgical and non-surgical treatment) and also sensitive and resistant isolates in comparison with the reference strain H37Rv. To estimate  the growth rate of 116 clinical isolates we have used the modified  method originally developed by von Groll and co-authors: to get the  bacteria growth curve the fluorescence intensity of growing strains  (with indicator resazurin) has been measured daily for 8 days in 96- well plate. The growth rate is determined as the slope of the growth  curve. The mean values of the growth rate have been calculated in  the following groups of patients: 1 — untreated patients with  pulmonary tuberculosis (PT), respiratory material; 2 — non-surgical  treated PT patients, respiratory material; 3 — surgical treated PT  patients (mainly with chronic and hyperchronic process), respiratory  material; 4 — patients like in 3rd group, surgical material; 5 — bone  and joint tuberculosis (BJT), surgical material. In addition, groups of  sensitive and resistant strains have been examined, but there are no  significant differences in growth rates. It has been obtained that  the growth rate of strains isolated from the PT patients is higher than in BJT patients: it can be explained less favorable  conditions for the pathogen vegetation in the BJT. In the case of a  closed tuberculous lesion where the pathogen transmission to  another host is impossible, then the selection of strains with the  property to survive in the tissues of the osteoarticular system is  impossible too, therefor it should be observed only an adaptation of  the pathogen strain population to the individual host. The growth  rate of isolates from untreated PT patients is higher than that of the  treated ones. Comparison of the growth parameters of only MDR  strains 1–5 groups to eliminate the influence of the  sensitivity/resistance has resulted in the same conclusions. We  suggest that the decrease in the growth rate of strains from the  treated PT patients is in not only result of the treatment, but also is  conditioned by adaptation of the pathogen to its external  environment, which is the internal environment of the  macroorganism. To confirm this assumption, the bacterial load of  1,083 diagnostic specimens grouped in a similar manner has been  estimated, taking into account only MDR/XDR strains. In the group  of treated patients the frequency of high bacterial load (CFU ≥ 100)  reached 52.5–63.8% that shows the conserved fitness of bacteria in  such patients. The mean values of the growth rate of the strain  H37Rv non-adapted to the macroorganism (due to numerous  passages on artificial media) are higher than in all groups of clinical  strains. Thus, heterogeneity of phenotypic properties of M.  tuberculosis clinical strains on the basis of growth rate has been  obtained. The growth rate of M. tuberculosis clinical strains is  depended on the tuberculosis localization (PT, BJT) and on the joint  effect of patient treatment and pathogen adaptation to the host. 

Tuberculosis and nature's pharmacy of putative anti-tuberculosis agents

Due to the growing problem of drug resistant Mycobacterium tuberculosis strains, coupled with the twinning of tuberculosis (TB) to human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS), the burden of TB is now difficult to manage. Therefore, new antimycobacterial agents are being sought from natural sources. This review focuses on natural antimycobacterial agents from endophytes and medicinal plants of Africa, Europe, Asia, South America and Canada. In the countries mentioned in this review, numerous plant species display putative anti-TB activity. Several antimycobacterial chemical compounds have also been isolated, including: ellagitannin punicalagin, allicin, anthraquinone glycosides, iridoids, phenylpropanoids, beta-sitosterol, galanthimine, crinine, friedelin, gallic acid, ellagic acids, anthocyanidin, taraxerol, termilignan B, arjunic acid, glucopyranosides, 1-epicatechol, leucopelargonidol, hydroxybenzoic acids, benzophenanthridine alkaloids, neolignans, and decarine. These compounds may provide leads to novel and more efficacious drugs to lessen the global burden of TB and drug-resistant M. tuberculosis strains. If there is a long-term remedy for TB, it must lie in nature's pharmacy of putative antimycobacterial agents.

Architectural plan of transcriptional regulation in Mycobacterium tuberculosis

Transcriptional regulation enables adaptation in bacteria. Typically, only a few transcriptional events are well understood, leaving many others unidentified. The recent genome-wide identification of transcription factor binding sites in Mycobacterium tuberculosis has changed this by deciphering a molecular road-map of transcriptional control, indicating active events and their immediate downstream effects.

Bio/chemoinformatics in India: an outlook

With the advent of significant establishment and development of Internet facilities and computational infrastructure, an overview on bio/chemoinformatics is presented along with its multidisciplinary facts, promises and challenges. The Government of India has paved the way for more profound research in biological field with the use of computational facilities and schemes/projects to collaborate with scientists from different disciplines. Simultaneously, the growth of available biomedical data has provided fresh insight into the nature of redundant and compensatory data. Today, bioinformatics research in India is characterized by a powerful grid computing systems, great variety of biological questions addressed and the close collaborations between scientists and clinicians, with a full spectrum of focuses ranging from database building and methods development to biological discoveries. In fact, this outlook provides a resourceful platform highlighting the funding agencies, institutes and industries working in this direction, which would certainly be of great help to students seeking their career in bioinformatics. Thus, in short, this review highlights the current bio/chemoinformatics trend, educations, status, diverse applicability and demands for further development.

Cloning, expression, purification and preliminary X-ray diffraction studies of a mycobacterial protein implicated in bacterial survival in macrophages

Mycobacterium species have developed numerous strategies to avoid the antimycobacterial actions of macrophages, enabling them to survive within the generally inhospitable environment of the cell. The recently identified MSMEG_5817 protein from M. smegmatis is highly conserved in Mycobacterium spp. and is required for bacterial survival in macrophages. Here, the cloning, expression, purification and crystallization of MSMEG_5817 is reported. Crystals of MSMEG_5817 were grown in 1.42 M Li2SO4, 0.1 M Tris-HCl pH 7.7, 0.1 M sodium citrate tribasic dihydrate. Native and multiple-wavelength anomalous dispersion (MAD) data sets have been collected and structure determination is in progress.

Crowd sourcing a new paradigm for interactome driven drug target identification in Mycobacterium tuberculosis

A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative 'Connect to Decode' (C2D) to generate the first and largest manually curated interactome of Mtb termed 'interactome pathway' (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

Creativity in tuberculosis research and discovery

The remarkable advances in TB vaccinology over the last decade have been driven by a pragmatic approach to moving candidates along the development pipeline to clinical trials, fuelled by encouraging data on protection in animal models. Efficacy data from Phase IIb trials of the first generation of new candidates are anticipated over the next 1-2 years. As outlined in the TB Vaccines Strategic Blueprint, to exploit this information and to inspire design of next generation candidates, it is important that this empirical approach is complemented by progress in understanding of fundamental immune mechanisms and improved translational modalities. Current trends towards improved experimental and computational approaches for studying biological complexity will be an important element in the developing science of TB vaccinology.

Mycobacterium tuberculosis and Clostridium difficille interactomes: demonstration of rapid development of computational system for bacterial interactome prediction

Background

Protein-protein interaction (PPI) networks (interactomes) of most organisms, except for some model organisms, are largely unknown. Experimental methods including high-throughput techniques are highly resource intensive. Therefore, computational discovery of PPIs can accelerate biological discovery by presenting "most-promising" pairs of proteins that are likely to interact. For many bacteria, genome sequence, and thereby genomic context of proteomes, is readily available; additionally, for some of these proteomes, localization and functional annotations are also available, but interactomes are not available. We present here a method for rapid development of computational system to predict interactome of bacterial proteomes. While other studies have presented methods to transfer interologs across species, here, we propose transfer of computational models to benefit from cross-species annotations, thereby predicting many more novel interactions even in the absence of interologs. Mycobacterium tuberculosis (Mtb) and Clostridium difficile (CD) have been used to demonstrate the work.

Results

We developed a random forest classifier over features derived from Gene Ontology annotations and genetic context scores provided by STRING database for predicting Mtb and CD interactions independently. The Mtb classifier gave a precision of 94% and a recall of 23% on a held out test set. The Mtb model was then run on all the 8 million protein pairs of the Mtb proteome, resulting in 708 new interactions (at 94% expected precision) or 1,595 new interactions at 80% expected precision. The CD classifier gave a precision of 90% and a recall of 16% on a held out test set. The CD model was run on all the 8 million protein pairs of the CD proteome, resulting in 143 new interactions (at 90% expected precision) or 580 new interactions (at 80% expected precision). We also compared the overlap of predictions of our method with STRING database interactions for CD and Mtb and also with interactions identified recently by a bacterial 2-hybrid system for Mtb. To demonstrate the utility of transfer of computational models, we made use of the developed Mtb model and used it to predict CD protein-pairs. The cross species model thus developed yielded a precision of 88% at a recall of 8%. To demonstrate transfer of features from other organisms in the absence of feature-based and interaction-based information, we transferred missing feature values from Mtb orthologs into the CD data. In transferring this data from orthologs (not interologs), we showed that a large number of interactions can be predicted.

Conclusions

Rapid discovery of (partial) bacterial interactome can be made by using existing set of GO and STRING features associated with the organisms. We can make use of cross-species interactome development, when there are not even sufficient known interactions to develop a computational prediction system. Computational model of well-studied organism(s) can be employed to make the initial interactome prediction for the target organism. We have also demonstrated successfully, that annotations can be transferred from orthologs in well-studied organisms enabling accurate predictions for organisms with no annotations. These approaches can serve as building blocks to address the challenges associated with feature coverage, missing interactions towards rapid interactome discovery for bacterial organisms.

Availability

The predictions for all Mtb and CD proteins are made available at: http://severus.dbmi.pitt.edu/TB and http://severus.dbmi.pitt.edu/CD respectively for browsing as well as for download.

A genome wide association scan of bovine tuberculosis susceptibility in Holstein-Friesian dairy cattle

Background

Bovine tuberculosis is a significant veterinary and financial problem in many parts of the world. Although many factors influence infection and progression of the disease, there is a host genetic component and dissection of this may enlighten on the wider biology of host response to tuberculosis. However, a binary phenotype of presence/absence of infection presents a noisy signal for genomewide association study.

Methodology/Principal Findings

We calculated a composite phenotype of genetic merit for TB susceptibility based on disease incidence in daughters of elite sires used for artificial insemination in the Irish dairy herd. This robust measure was compared with 44,426 SNP genotypes in the most informative 307 subjects in a genome wide association analysis. Three SNPs in a 65 kb genomic region on BTA 22 were associated (i.e. p<10⁻⁵, peaking at position 59588069, p = 4.02×10⁻⁶) with tuberculosis susceptibility.

Conclusions/Significance

A genomic region on BTA 22 was suggestively associated with tuberculosis susceptibility; it contains the taurine transporter gene SLC6A6, or TauT, which is known to function in the immune system but has not previously been investigated for its role in tuberculosis infection.