18 resultados para Pathogen origins
em Indian Institute of Science - Bangalore - Índia
Resumo:
Gene expression noise results in protein number distributions ranging from long-tailed to Gaussian. We show how long-tailed distributions arise from a stochastic model of the constituent chemical reactions and suggest that, in conjunction with cooperative switches, they lead to more sensitive selection of a subpopulation of cells with high protein number than is possible with Gaussian distributions. Single-cell-tracking experiments are presented to validate some of the assumptions of the stochastic simulations. We also examine the effect of DNA looping on the shape of protein distributions. We further show that when switches are incorporated in the regulation of a gene via a feedback loop, the distributions can become bimodal. This might explain the bimodal distribution of certain morphogens during early embryogenesis.
Resumo:
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.
Resumo:
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.
Resumo:
Madras triple helix’ was the name assigned by the scientific community in the West, to the molecular model proposed for the fibrous protein collagen, by G N Ramachandran’s group at the University of Madras. As mentioned jocularly in a recent retrospective of this work by Sasisekharan and Yathindra [1], the term was possibly coined due to the difficulty of Western scientists in pronouncing the Indian names of Ramachandran and his associates. The unravelling of the precise nature of collagen structure indeed makes for a fascinating story and as succinctly put by Dickerson [2]: “... to trace the evolution of the structure of collagen is to trace the evolution of fibrous protein crystallography in miniature”. This article is a brief review highlighting the pioneering contributions made by G N Ramachandran in elucidating the correct structure of this important molecule and is a sincere tribute by the author to her mentor, doctoral thesis supervisor and major source of inspiration for embarking on a career in biophysics
Resumo:
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.
Resumo:
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.
Resumo:
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.
Resumo:
A cationic amphiphile, cholest-5en-3 beta-oxyethyl pyridinium bromide (PY(+)-Chol), is able to efficiently disperse exfoliated graphene (GR) in water by the physical adsorption of PY(+)-Chol on the surface of GR to form stable, dark aqueous suspensions at room temperature. The GRPY(+)-Chol suspension can then be used to solubilize Tamoxifen Citrate (TmC), a breast cancer drug, in water. The resulting TmCGRPY(+)-Chol is stable for a long time without any precipitation. Fluorescence emission and UV absorption spectra indicate the existence of noncovalent interactions between TmC, GR, and PY(+)-Chol in these suspensions. Electron microscopy shows the existence of segregated GR sheets and TmC ribbons in the composite suspensions. Atomic force microscopy indicates the presence of extended structures of GRPY(+)-Chol, which grows wider in the presence of TmC. The slow time-dependent release of TmC is noticed in a reconstituted cell culture medium, a property useful as a drug carrier. TmCGRPY(+)-Chol selectively enhanced the cell death (apoptosis) of the transformed cancer cells compared to normal cells. This potency is found to be true for a wide range of transformed cancer cells viz. HeLa, A549, ras oncogene-transformed NIH3T3, HepG2, MDA-MB231, MCF-7, and HEK293T compared to the normal cell HEK293 in vitro. Confocal microscopy confirmed the high efficiency of TmCGRPY(+)-Chol in delivering the drug to the cells, compared to the suspensions devoid of GR.
Resumo:
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.
Resumo:
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.
Resumo:
The El Nino/Southern Oscillation phenomenon, characterized by anomalous sea surface temperatures and winds in the tropical Pacific, affects climate across the globe(1). El Ninos occur every 2-7 years, whereas the El Nino/Southern Oscillation itself varies on decadal timescales in frequency and amplitude, with a different spatial pattern of surface anomalies(2) each time the tropical Pacific undergoes a regime shift. Recent work has shown that Bjerknes feedback(3,4) (coupling of the atmosphere and the ocean through changes in equatorial winds driven by changes in sea surface temperature owing to suppression of equatorial upwelling in the east Pacific) is not necessary(5) for the development of an El Nino. Thus it is unclear what remains constant through regimes and is crucial for producing the anomalies recognized as El Nino. Here we show that the subsurface process of discharging warm waters always begins in the boreal summer/autumn of the year before the event (up to 18 months before the peak) independent of regimes, identifying the discharge process as fundamental to the El Nino onset. It is therefore imperative that models capture this process accurately to further our theoretical understanding, improve forecasts and predict how the El Nino/Southern Oscillation may respond to climate change.
Resumo:
Background: The correlation of genetic distances between pairs of protein sequence alignments has been used to infer protein-protein interactions. It has been suggested that these correlations are based on the signal of co-evolution between interacting proteins. However, although mutations in different proteins associated with maintaining an interaction clearly occur (particularly in binding interfaces and neighbourhoods), many other factors contribute to correlated rates of sequence evolution. Proteins in the same genome are usually linked by shared evolutionary history and so it would be expected that there would be topological similarities in their phylogenetic trees, whether they are interacting or not. For this reason the underlying species tree is often corrected for. Moreover processes such as expression level, are known to effect evolutionary rates. However, it has been argued that the correlated rates of evolution used to predict protein interaction explicitly includes shared evolutionary history; here we test this hypothesis. Results: In order to identify the evolutionary mechanisms giving rise to the correlations between interaction proteins, we use phylogenetic methods to distinguish similarities in tree topologies from similarities in genetic distances. We use a range of datasets of interacting and non-interacting proteins from Saccharomyces cerevisiae. We find that the signal of correlated evolution between interacting proteins is predominantly a result of shared evolutionary rates, rather than similarities in tree topology, independent of evolutionary divergence. Conclusions: Since interacting proteins do not have tree topologies that are more similar than the control group of non-interacting proteins, it is likely that coevolution does not contribute much to, if any, of the observed correlations.
Resumo:
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.