A systems perspective of host-pathogen interactions: predicting disease outcome in tuberculosis

The complex web of interactions between the host immune system and the pathogen determines the outcome of any infection. A computational model of this interaction network, which encodes complex interplay among host and bacterial components, forms a useful basis for improving the understanding of pathogenesis, in filling knowledge gaps and consequently to identify strategies to counter the disease. We have built an extensive model of the Mycobacterium tuberculosis host-pathogen interactome, consisting of 75 nodes corresponding to host and pathogen molecules, cells, cellular states or processes. Vaccination effects, clearance efficiencies due to drugs and growth rates have also been encoded in the model. The system is modelled as a Boolean network. Virtual deletion experiments, multiple parameter scans and analysis of the system's response to perturbations, indicate that disabling processes such as phagocytosis and phagolysosome fusion or cytokines such as TNF-alpha and IFN-gamma, greatly impaired bacterial clearance, while removing cytokines such as IL-10 alongside bacterial defence proteins such as SapM greatly favour clearance. Simulations indicate a high propensity of the pathogen to persist under different conditions.

A systems perspective of host-pathogen interactions: predicting disease outcome in tuberculosis

The complex web of interactions between the host immune system and the pathogen determines the outcome of any infection. A computational model of this interaction network, which encodes complex interplay among host and bacterial components, forms a useful basis for improving the understanding of pathogenesis, in filling knowledge gaps and consequently to identify strategies to counter the disease. We have built an extensive model of the Mycobacterium tuberculosis host-pathogen interactome, consisting of 75 nodes corresponding to host and pathogen molecules, cells, cellular states or processes. Vaccination effects, clearance efficiencies due to drugs and growth rates have also been encoded in the model. The system is modelled as a Boolean network. Virtual deletion experiments, multiple parameter scans and analysis of the system's response to perturbations, indicate that disabling processes such as phagocytosis and phagolysosome fusion or cytokines such as TNF-alpha and IFN-gamma, greatly impaired bacterial clearance, while removing cytokines such as IL-10 alongside bacterial defence proteins such as SapM greatly favour clearance. Simulations indicate a high propensity of the pathogen to persist under different conditions.

Intracellular Pathogen Sensor NOD2 Programs Macrophages to Trigger Notch1 Activation

Intracellular pathogen sensor, NOD2, has been implicated in regulation of wide range of anti-inflammatory responses critical during development of a diverse array of inflammatory diseases; however, underlying molecular details are still imprecisely understood. In this study, we demonstrate that NOD2 programs macrophages to trigger Notch1 signaling. Signaling perturbations or genetic approaches suggest signaling integration through cross-talk between Notch1-PI3K during the NOD2-triggered expression of a multitude of immunological parameters including COX-2/PGE(2) and IL-10. NOD2 stimulation enhanced active recruitment of CSL/RBP-Jk on the COX-2 promoter in vivo. Intriguingly, nitric oxide assumes critical importance in NOD2-mediated activation of Notch1 signaling as iNOS(-/-) macrophages exhibited compromised ability to execute NOD2-triggered Notch1 signaling responses. Correlative evidence demonstrates that this mechanism operates in vivo in brain and splenocytes derived from wild type, but not from iNOS(-/-) mice. Importantly, NOD2-driven activation of the Notch1-PI3K signaling axis contributes to its capacity to impart survival of macrophages against TNF-alpha or IFN-gamma-mediated apoptosis and resolution of inflammation. Current investigation identifies Notch1-PI3K as signaling cohorts involved in the NOD2-triggered expression of a battery of genes associated with anti-inflammatory functions. These findings serve as a paradigm to understand the pathogenesis of NOD2-associated inflammatory diseases and clearly pave a way toward development of novel therapeutics.

Prediction of protein-protein interactions between human host and a pathogen and its application to three pathogenic bacteria

Molecular understanding of disease processes can be accelerated if all interactions between the host and pathogen are known. The unavailability of experimental methods for large-scale detection of interactions across host and pathogen organisms hinders this process. Here we apply a simple method to predict protein-protein interactions across a host and pathogen organisms. We use homology detection approaches against the protein-protein interaction databases. DIP and iPfam in order to predict interacting proteins in a host-pathogen pair. In the present work, we first applied this approach to the test cases involving the pairs phage T4 - Escherichia coli and phage lambda - E. coli and show that previously known interactions could be recognized using our approach. We further apply this approach to predict interactions between human and three pathogens E. coli, Salmonella enterica typhimurium and Yersinia pestis. We identified several novel interactions involving proteins of host or pathogen that could be thought of as highly relevant to the disease process. Serendipitously, many interactions involve hypothetical proteins of yet unknown function. Hypothetical proteins are predicted from computational analysis of genome sequences with no laboratory analysis on their functions yet available. The predicted interactions involving such proteins could provide hints to their functions. (C) 2011 Elsevier B.V. All rights reserved.

Pathogen-specific TLR2 Protein Activation Programs Macrophages to Induce Wnt-beta-Catenin Signaling

Innate immunity recognizes and resists various pathogens; however, the mechanisms regulating pathogen versus non-pathogen discrimination are still imprecisely understood. Here, we demonstrate that pathogen-specific activation of TLR2 upon infection with Mycobacterium bovis BCG, in comparison with other pathogenic microbes, including Salmonella typhimurium and Staphylococcus aureus, programs macrophages for robust up-regulation of signaling cohorts of Wnt-beta-catenin signaling. Signaling perturbations or genetic approaches suggest that infection-mediated stimulation of Wnt-beta-catenin is vital for activation of Notch1 signaling. Interestingly, inducible NOS (iNOS) activity is pivotal for TLR2-mediated activation of Wnt-beta-catenin signaling as iNOS(-/-) mice demonstrated compromised ability to trigger activation of Wnt-beta-catenin signaling as well as Notch1-mediated cellular responses. Intriguingly, TLR2-driven integration of iNOS/NO, Wnt-beta-catenin, and Notch1 signaling contributes to its capacity to regulate the battery of genes associated with T(Reg) cell lineage commitment. These findings reveal a role for differential stimulation of TLR2 in deciding the strength of Wnt-beta-catenin signaling, which together with signals from Notch1 contributes toward the modulation of a defined set of effector functions in macrophages and thus establishes a conceptual framework for the development of novel therapeutics.

Distinct mechanisms of DNA repair in mycobacteria and their implications in attenuation of the pathogen growth

About a third of the human population is estimated to be infected with Mycobacterium tuberculosis. Emergence of drug resistant strains and the protracted treatment strategies have compelled the scientific community to identify newer drug targets, and to develop newer vaccines. In the host macrophages, the bacterium survives within an environment rich in reactive nitrogen and oxygen species capable of damaging its genome. Therefore, for its successful persistence in the host, the pathogen must need robust DNA repair mechanisms. Analysis of M. tuberculosis genome sequence revealed that it lacks mismatch repair pathway suggesting a greater role for other DNA repair pathways such as the nucleotide excision repair, and base excision repair pathways. In this article, we summarize the outcome of research involving these two repair pathways in mycobacteria focusing primarily on our own efforts. Our findings, using Mycobacterium smegmatis model, suggest that deficiency of various DNA repair functions in single or in combinations severely compromises their DNA repair capacity and attenuates their growth under conditions typically encountered in macrophages. (C) 2011 Elsevier Ireland Ltd. All rights reserved.

Salmonella enterica serovars Typhimurium and Typhi as model organisms Revealing paradigm of host-pathogen interactions

The lifestyle of intracellular pathogens has always questioned the skill of a microbiologist in the context of finding the permanent cure to the diseases caused by them. The best tool utilized by these pathogens is their ability to reside inside the host cell, which enables them to easily bypass the humoral immunity of the host, such as the complement system. They further escape from the intracellular immunity, such as lysosome and inflammasome, mostly by forming a protective vacuole-bound niche derived from the host itself. Some of the most dreadful diseases are caused by these vacuolar pathogens, for example, tuberculosis by Mycobacterium or typhoid fever by Salmonella. To deal with such successful pathogens therapeutically, the knowledge of a host-pathogen interaction system becomes primarily essential, which further depends on the use of a model system. A well characterized pathogen, namely Salmonella, suits the role of a model for this purpose, which can infect a wide array of hosts causing a variety of diseases. This review focuses on various such aspects of research on Salmonella which are useful for studying the pathogenesis of other intracellular pathogens.

Chitosan-dextran sulphate nanocapsule drug delivery system as an effective therapeutic against intraphagosomal pathogen Salmonella

Objectives: The ability to target conventional drugs efficiently inside cells to kill intraphagosomal bacteria has been a major hurdle in treatment of infective diseases. We aimed to develop an efficient drug delivery system for combating infection caused by Salmonella, a well-known intracellular and intraphagosomal pathogen. Chitosan dextran sulphate (CD) nanocapsules were assessed for their efficiency in delivering drugs against Salmonella. Methods: The CD nanocapsules were prepared using the layer-by-layer method and loaded with ciprofloxacin or ceftriaxone. Antibiotic-loaded nanocapsules were analysed in vitro for their ability to enter epithelial and macrophage cells to kill Salmonella. In vivo pharmacokinetics and organ distribution studies were performed to check the efficiency of the delivery system. The in vivo antibacterial activity of free antibiotic and antibiotic loaded into nanocapsules was tested in a murine salmonellosis model. Results: In vitro and in vivo experiments showed that this delivery system can be used effectively to clear Salmonella infection, CD nanocapsules were successfully employed for efficient targeting and killing of the intracellular pathogen at a dosage significantly lower than that of the free antibiotic. The increased retention time of ciprofloxacin in the blood and organs when it was delivered by CD nanocapsules compared with the conventional routes of administration may be the reason underlying the requirement for a reduced dosage and frequency of antibiotic administration. Conclusions: CD nanocapsules can be used as an efficient drug delivery system to treat intraphagosomal pathogens, especially Salmonella infection, This delivery system might be used effectively for other vacuolar pathogens including Mycobacteria, Brucella and Legionella.

From Workstations to Workbenches: Towards Predicting Physicochemically Viable Protein-Protein Interactions Across a Host and a Pathogen

The understanding of protein-protein interactions is indispensable in comprehending most of the biological processes in a cell. Small-scale experiments as well as large-scale high-throughput techniques over the past few decades have facilitated identification and analysis of protein-protein interactions which form the basis of much of our knowledge on functional and regulatory aspects of proteins. However, such rich catalog of interaction data should be used with caution when establishing protein-protein interactions in silico, as the high-throughput datasets are prone to false positives. Numerous computational means developed to pursue genome-wide studies on protein-protein interactions at times overlook the mechanistic and molecular details, thus questioning the reliability of predicted protein-protein interactions. We review the development, advantages, and shortcomings of varied approaches and demonstrate that by providing a structural viewpoint in terms of shape complementarity and interaction energies at protein-protein interfaces coupled with information on expression and localization of proteins homologous to an interacting pair, it is possible to assess the credibility of predicted interactions in biological context. With a focus on human pathogen Mycobacterium tuberculosis H37Rv, we show that such scrupulous use of details at the molecular level can predict physicochemically viable protein-protein interactions across host and pathogen. Such predicted interactions have the potential to provide molecular basis of probable mechanisms of pathogenesis and hence open up ways to explore their usefulness as targets in the light of drug discovery. (c) 2014 IUBMB Life, 66(11):759-774, 2014

Chitosan-dextran sulphate nanocapsule drug delivery system as an effective therapeutic against intraphagosomal pathogen Salmonella

Objectives: The ability to target conventional drugs efficiently inside cells to kill intraphagosomal bacteria has been a major hurdle in treatment of infective diseases. We aimed to develop an efficient drug delivery system for combating infection caused by Salmonella, a well-known intracellular and intraphagosomal pathogen. Chitosan dextran sulphate (CD) nanocapsules were assessed for their efficiency in delivering drugs against Salmonella. Methods: The CD nanocapsules were prepared using the layer-by-layer method and loaded with ciprofloxacin or ceftriaxone. Antibiotic-loaded nanocapsules were analysed in vitro for their ability to enter epithelial and macrophage cells to kill Salmonella. In vivo pharmacokinetics and organ distribution studies were performed to check the efficiency of the delivery system. The in vivo antibacterial activity of free antibiotic and antibiotic loaded into nanocapsules was tested in a murine salmonellosis model. Results: In vitro and in vivo experiments showed that this delivery system can be used effectively to clear Salmonella infection, CD nanocapsules were successfully employed for efficient targeting and killing of the intracellular pathogen at a dosage significantly lower than that of the free antibiotic. The increased retention time of ciprofloxacin in the blood and organs when it was delivered by CD nanocapsules compared with the conventional routes of administration may be the reason underlying the requirement for a reduced dosage and frequency of antibiotic administration. Conclusions: CD nanocapsules can be used as an efficient drug delivery system to treat intraphagosomal pathogens, especially Salmonella infection, This delivery system might be used effectively for other vacuolar pathogens including Mycobacteria, Brucella and Legionella.

Draft genome of a commonly misdiagnosed multidrug resistant pathogen Candida auris

Background: Candida auris is a multidrug resistant, emerging agent of fungemia in humans. Its actual global distribution remains obscure as the current commercial methods of clinical diagnosis misidentify it as C. haemulonii. Here we report the first draft genome of C. auris to explore the genomic basis of virulence and unique differences that could be employed for differential diagnosis. Results: More than 99.5 % of the C. auris genomic reads did not align to the current whole (or draft) genome sequences of Candida albicans, Candida lusitaniae, Candida glabrata and Saccharomyces cerevisiae; thereby indicating its divergence from the active Candida clade. The genome spans around 12.49 Mb with 8527 predicted genes. Functional annotation revealed that among the sequenced Candida species, it is closest to the hemiascomycete species Clavispora lusitaniae. Comparison with the well-studied species Candida albicans showed that it shares significant virulence attributes with other pathogenic Candida species such as oligopeptide transporters, mannosyl transfersases, secreted proteases and genes involved in biofilm formation. We also identified a plethora of transporters belonging to the ABC and major facilitator superfamily along with known MDR transcription factors which explained its high tolerance to antifungal drugs. Conclusions: Our study emphasizes an urgent need for accurate fungal screening methods such as PCR and electrophoretic karyotyping to ensure proper management of fungemia. Our work highlights the potential genetic mechanisms involved in virulence and pathogenicity of an important emerging human pathogen namely C. auris. Owing to its diversity at the genomic scale; we expect the genome sequence to be a useful resource to map species specific differences that will help develop accurate diagnostic markers and better drug targets.

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.

Cloning and development of pathotype-specific SCAR marker associated with Sclerospora graminicola isolates from pearl millet

Downy mildew pathogen of pearl millet in India is associated with the spread of the highly virulent Sclerospora graminicola pathotype-1. Twenty-seven S. graminicola isolates were screened using 20 intersimple sequence repeats (ISSR). Dinucleotide repeat primer [17898A-(CA)(6) AC] amplified a similar to 600 bp fragment specific to five isolates of pathotype-1 (Sg 048, Sg 153, Sg 212, DM-11 and DM-90). The ISSR fragment linked with pathotype-1 was cloned successfully and sequenced. To convert ISSR fragments into pathotype-specific sequence characterised amplified region (SCAR) markers, PCR primers were designed using a sequence of the cloned DNA fragment. PCR amplification using SCAR primer pair (UOM3-Sg-Path1-F/R) amplified a single 284 bp band only in isolates of S. graminicola pathotype-1. This SCAR primer pair did not amplify the 284 bp product from the other five S. graminicola pathotypes or a negative control, which demonstrates primer specificity for pathotype-1. The SCAR primer pair (UOM3-Sg-Path1-F/R) obtained in this study will provide a valuable tool for rapid identification and specific detection of S. graminicola pathotype-1.

Studies on "Sappe" disease of the silkworm, Bombyx mori : II. Effect of age of larvae on the manifestation of the disease

The effect of age of the larvae on the manifestation of the "Sappe" disease of the silkworm by oral inoculation of different pathogens, viz., Aerobacter cloacae, Pseudomonas boreopolis, Escherichia freundii, Achromobacter delmarvae, A. Superficialis, Pseudomonas ovalis, and Staphylococcus albus was tested. It was found that the reaction of the larva to the pathogen was influenced by its age. Some, e.g., Escherichia freundii, were more lethal when introduced at early stages whereas certain others, e.g., Aerobacter cloacae and Staphylococcus albus, caused maximum damage when invading older larvae. Irrespective of the age of infection, death of the worms mainly occurred during molting and before spinning. The studies also indicated that growth and mortality of the larvae were affected differentially by the pathogens.