Systems biology of tuberculosis

Systems biology seeks to study biological systems as a whole, by adopting an integrated approach to study and understand the function of biological systems, particularly, the response of such systems to various perturbations. In this article, we focus on the Indian efforts towards systems-level studies of Mycobacterium tuberculosis and its interaction with the host. Availability of a variety of genome-scale experimental data, providing first level `omics' descriptions of the pathogen, render it feasible to study it at a systems level. Various aspects of the pathogen, from metabolic pathways to protein-protein interaction networks have been modelled and simulated, while host-pathogen interactions have been studied experimentally using siRNA-based techniques. These studies have been useful in obtaining a global perspective of the pathogen and its interactions with the host in many ways. For example, significant insights have been gained about different aspects such as proteins essential for bacterial survival, proteins that are highly influential in the network, pathways that are highly connected, host factors responsible for maintaining the TB infection and key factors involved in autophagy and pathogenesis. A rational pipeline developed for drug target identification incorporating analyses of the interactome, reactome, genome, pocketome and the transcriptome is discussed. Finally, exploring host factors as drug targets and insights about the emergence of drug resistance are also discussed. (C) 2011 Elsevier Ltd. All rights reserved.

Network, nodes and nexus: systems approach to multitarget therapeutics

Systems biology is revealing multiple layers of regulatory networks that manifest spatiotemporal variations. Since genes and environment also influence the emergent property of a cell, the biological output requires dynamic understanding of various molecular circuitries. The metabolic networks continually adapt and evolve to cope with the changing milieu of the system, which could also include infection by another organism. Such perturbations of the functional networks can result in disease phenotypes, for instance tuberculosis and cancer. In order to develop effective therapeutics, it is important to determine the disease progression profiles of complex disorders that can reveal dynamic aspects and to develop mutitarget systemic therapies that can help overcome pathway adaptations and redundancy.

targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis

Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

A Need for FSH in Maintaining Fertility of Adult Male Subhuman Primates

Adult fertile male bonnet monkeys (Macaca radiata) were continuously deprived of endogenous follicle stimulating hormone (FSH) support for 240 days by injecting them with 1 ml of characterized monkey antiserum to oFSH every 48 hr; control monkeys received during the same period normal monkey serum instead. Testicular function was assessed at periodic intervals by (a) carrying out differential counting of sperm in the ejaculate obtained and (b) determining the hyaluronidase activity as well as in vitro 3H thymidine incorporation into DNA of testicular tissue removed at biopsy. Both the quality (viability and motility) of the sperms voided and the total sperm counts showed marked decreases as a function of time of immunization, the first significant reduction being noted by 100 days. FSH deprivation affected both the biochemical parameters used to test testicular functionality they being reduced at ∼200 days by 50%-60%. The fertility of these monkeys was evaluated at periodic times after 90 days of treatment by means of mating studies. FSH deprivation had rendered the monkeys incapable of impregnating any of the females used. Testosterone and luteinizing hormone (LH) levels remained unchanged following FSH antiserum injection. With cessation of antiserum treatment testicular function and fertility were completely restored to normalcy, indicating that the observed effect was specifically due to FSH deprivation. This study thus provides conclusive evidence for the involvement of FSH in maintenance of testicular function and fertility in the adult male primate.

Analysis of connectivity map: Control to glutamate injured and phenobarbital treated neuronal network

We study the responses of a cultured neural network when it is exposed to epileptogenesis glutamate injury causing epilepsy and subsequent treatment with phenobarbital by constructing connectivity map of neurons using correlation matrix. This study is particularly useful in understanding the pharmaceutical drug induced changes in the neuronal network properties with insights into changes at the systems biology level. (C) 2010 American Institute of Physics. [doi:10.1063/1.3398025]

Studies on reactivation of regressing bonnet monkey corpus luteum on day 1 of menses: A pilot study

Studies on functional characteristics of the regressing primate corpus luteum (CL) to luteotrophic stimulus on day 1 of the non-fertile menstrual cycle are scarce. Recombinant human luteinizing hormone (rhLH) (20 IU/Kg BW; n = 10) or human chorionic gonadotropin (hCG) (180 IU; n = 6) were administered intravenously to female bonnet monkeys on day 1 of menses. Exogenous treatment of rhLH or hCG caused a significant increase in circulating progesterone (P4) levels 2-4 hours post treatment (P < 0.05). Lutectomy prior to onset of menses confirmed that CL is the site of the increased P4 concentrations. Increased levels of phosphorylated P44/42 MAPK, MKK3/6 activation and concomitant histological changes were observed within 4 hours in CL of monkeys receiving hCG treatment. The results from this study demonstrate the acute progesterone synthesizing capacity of regressing monkey CL after LH or hCG challenge. This has potential implications for interpreting the steroidogenic response after gonadotropin stimulation tests in the early follicular phase of the normal ovulatory and anovulatory women undergoing controlled ovarian stimulation protocols as part of assisted reproductive technology (ART) and in women with polycystic ovarian syndrome.

Cyclic nucleotide signaling in intestinal epithelia: getting to the gut of the matter

The intestine is the primary site of nutrient absorption, fluid-ion secretion, and home to trillions of symbiotic microbiota. The high turnover of the intestinal epithelia also renders it susceptible to neoplastic growth. These diverse processes are carefully regulated by an intricate signaling network. Among the myriad molecules involved in intestinal epithelial cell homeostasis are the second messengers, cyclic AMP (cAMP) and cyclic GMP (cGMP). These cyclic nucleotides are synthesized by nucleotidyl cyclases whose activities are regulated by extrinsic and intrinsic cues. Downstream effectors of cAMP and cGMP include protein kinases, cyclic nucleotide gated ion channels, and transcription factors, which modulate key processes such as ion-balance, immune response, and cell proliferation. The web of interaction involving the major signaling pathways of cAMP and cGMP in the intestinal epithelial cell, and possible cross-talk among the pathways, are highlighted in this review. Deregulation of these pathways occurs during infection by pathogens, intestinal inflammation, and cancer. Thus, an appreciation of the importance of cyclic nucleotide signaling in the intestine furthers our understanding of bowel disease, thereby aiding in the development of therapeutic approaches.

Information and Efficiency in the Nervous System-A Synthesis

In systems biology, questions concerning the molecular and cellular makeup of an organism are of utmost importance, especially when trying to understand how unreliable components-like genetic circuits, biochemical cascades, and ion channels, among others-enable reliable and adaptive behaviour. The repertoire and speed of biological computations are limited by thermodynamic or metabolic constraints: an example can be found in neurons, where fluctuations in biophysical states limit the information they can encode-with almost 20-60% of the total energy allocated for the brain used for signalling purposes, either via action potentials or by synaptic transmission. Here, we consider the imperatives for neurons to optimise computational and metabolic efficiency, wherein benefits and costs trade-off against each other in the context of self-organised and adaptive behaviour. In particular, we try to link information theoretic (variational) and thermodynamic (Helmholtz) free-energy formulations of neuronal processing and show how they are related in a fundamental way through a complexity minimisation lemma.

A multi-level multi-scale approach to study essential genes in Mycobacterium tuberculosis

Background: The set of indispensable genes that are required by an organism to grow and sustain life are termed as essential genes. There is a strong interest in identification of the set of essential genes, particularly in pathogens, not only for a better understanding of the pathogen biology, but also for identifying drug targets and the minimal gene set for the organism. Essentiality is inherently a systems property and requires consideration of the system as a whole for their identification. The available experimental approaches capture some aspects but each method comes with its own limitations. Moreover, they do not explain the basis for essentiality in most cases. A powerful prediction method to recognize this gene pool including rationalization of the known essential genes in a given organism would be very useful. Here we describe a multi-level multi-scale approach to identify the essential gene pool in a deadly pathogen, Mycobacterium tuberculosis. Results: The multi-level workflow analyses the bacterial cell by studying (a) genome-wide gene expression profiles to identify the set of genes which show consistent and significant levels of expression in multiple samples of the same condition, (b) indispensability for growth by using gene expression integrated flux balance analysis of a genome-scale metabolic model, (c) importance for maintaining the integrity and flow in a protein-protein interaction network and (d) evolutionary conservation in a set of genomes of the same ecological niche. In the gene pool identified, the functional basis for essentiality has been addressed by studying residue level conservation and the sub-structure at the ligand binding pockets, from which essential amino acid residues in that pocket have also been identified. 283 genes were identified as essential genes with high-confidence. An agreement of about 73.5% is observed with that obtained from the experimental transposon mutagenesis technique. A large proportion of the identified genes belong to the class of intermediary metabolism and respiration. Conclusions: The multi-scale, multi-level approach described can be generally applied to other pathogens as well. The essential gene pool identified form a basis for designing experiments to probe their finer functional roles and also serve as a ready shortlist for identifying drug targets.

Optimal control analysis of the dynamic growth behavior of microorganisms

Understanding the growth behavior of microorganisms using modeling and optimization techniques is an active area of research in the fields of biochemical engineering and systems biology. In this paper, we propose a general modeling framework, based on Monad model, to model the growth of microorganisms. Utilizing the general framework, we formulate an optimal control problem with the objective of maximizing a long-term cellular goal and solve it analytically under various constraints for the growth of microorganisms in a two substrate batch environment. We investigate the relation between long term and short term cellular goals and show that the objective of maximizing cellular concentration at a fixed final time is equivalent to maximization of instantaneous growth rate. We then establish the mathematical connection between the generalized framework and optimal and cybernetic modeling frameworks and derive generalized governing dynamic equations for optimal and cybernetic models. We finally illustrate the influence of various constraints in the cybernetic modeling framework on the optimal growth behavior of microorganisms by solving several dynamic optimization problems using genetic algorithms. (C) 2014 Published by Elsevier Inc.

Comparative proteomic analysis of primordial follicles from ovaries of immature and aged rats

Age related decline in reproductive performance in women is well documented and apoptosis has been considered as one of the reasons for the decline of primordial follicle reserve. Recently we observed a decline in the efficiency of DNA repair ability in aged rat primordial follicles as demonstrated by decreased mRNA levels of DNA repair genes BRCA1 and H2AX. In the present study, a two-dimensional electrophoresis (2DE) proteomic approach was employed to identify differentially expressed proteins in primordial follicles isolated from ovaries of immature (approximate to 20 days) and aged (approximate to 400-450 days) rats. Using MALDI-TOF/TOF MS, we identified 13 differentially expressed proteins (p<0.05) which included seven up-regulated and six down-regulated proteins in aged primordial follicles. These proteins are involved in a wide range of biological functions including apoptosis, DNA repair, and the immune system. Interestingly, the differentially expressed proteins such as FIGNL1 (DNA repair) and BOK (apoptotic protein) have not been previously reported in the rat primordial follicles and these proteins can be related to some common features of ovarian aging such as loss of follicle reserve and genome integrity. The quantitative differences of two important proteins BOK and FIGNL1 observed by the proteomic analysis were correlated with the transcript levels, as determined by semi-quantitative RT-PCR. Our results improve the current knowledge about protein factors associated with molecular changes in rat primordial follicles as a function of aging and our understanding of the proteomic processes involved in degenerative changes observed in aging primordial follicles.

Computational systems approach for drug target discovery

Importance of the field: The shift in focus from ligand based design approaches to target based discovery over the last two to three decades has been a major milestone in drug discovery research. Currently, it is witnessing another major paradigm shift by leaning towards the holistic systems based approaches rather the reductionist single molecule based methods. The effect of this new trend is likely to be felt strongly in terms of new strategies for therapeutic intervention, new targets individually and in combinations, and design of specific and safer drugs. Computational modeling and simulation form important constituents of new-age biology because they are essential to comprehend the large-scale data generated by high-throughput experiments and to generate hypotheses, which are typically iterated with experimental validation. Areas covered in this review: This review focuses on the repertoire of systems-level computational approaches currently available for target identification. The review starts with a discussion on levels of abstraction of biological systems and describes different modeling methodologies that are available for this purpose. The review then focuses on how such modeling and simulations can be applied for drug target discovery. Finally, it discusses methods for studying other important issues such as understanding targetability, identifying target combinations and predicting drug resistance, and considering them during the target identification stage itself. What the reader will gain: The reader will get an account of the various approaches for target discovery and the need for systems approaches, followed by an overview of the different modeling and simulation approaches that have been developed. An idea of the promise and limitations of the various approaches and perspectives for future development will also be obtained. Take home message: Systems thinking has now come of age enabling a `bird's eye view' of the biological systems under study, at the same time allowing us to `zoom in', where necessary, for a detailed description of individual components. A number of different methods available for computational modeling and simulation of biological systems can be used effectively for drug target discovery.

Interplay between multiple length and time scales in complex chemical systems

Processes in complex chemical systems, such as macromolecules, electrolytes, interfaces, micelles and enzymes, can span several orders of magnitude in length and time scales. The length and time scales of processes occurring over this broad time and space window are frequently coupled to give rise to the control necessary to ensure specificity and the uniqueness of the chemical phenomena. A combination of experimental, theoretical and computational techniques that can address a multiplicity of length and time scales is required in order to understand and predict structure and dynamics in such complex systems. This review highlights recent experimental developments that allow one to probe structure and dynamics at increasingly smaller length and time scales. The key theoretical approaches and computational strategies for integrating information across time-scales are discussed. The application of these ideas to understand phenomena in various areas, ranging from materials science to biology, is illustrated in the context of current developments in the areas of liquids and solvation, protein folding and aggregation and phase transitions, nucleation and self-assembly.