Comprehensive Identification of Protein Substrates of the Dot/Icm Type IV Transporter of Legionella pneumophila

A large number of proteins transferred by the Legionella pneumophila Dot/Icm system have been identified by various strategies. With no exceptions, these strategies are based on one or more characteristics associated with the tested proteins. Given the high level of diversity exhibited by the identified proteins, it is possible that some substrates have been missed in these screenings. In this study, we took a systematic method to survey the L. pneumophila genome by testing hypothetical orfs larger than 300 base pairs for Dot/Icm-dependent translocation. 798 of the 832 analyzed orfs were successfully fused to the carboxyl end of β-lactamase. The transfer of the fusions into mammalian cells was determined using the β-lactamase reporter substrate CCF4-AM. These efforts led to the identification of 164 proteins positive in translocation. Among these, 70 proteins are novel substrates of the Dot/Icm system. These results brought the total number of experimentally confirmed Dot/Icm substrates to 275. Sequence analysis of the C-termini of these identified proteins revealed that Lpg2844, which contains few features known to be important for Dot/Icm-dependent protein transfer can be translocated at a high efficiency. Thus, our efforts have identified a large number of novel substrates of the Dot/Icm system and have revealed the diverse features recognizable by this protein transporter

Inhibition of Host Vacuolar H+-ATPase Activity by a Legionella pneumophila Effector

Legionella pneumophila is an intracellular pathogen responsible for Legionnaires' disease. This bacterium uses the Dot/Icm type IV secretion system to inject a large number of bacterial proteins into host cells to facilitate the biogenesis of a phagosome permissive for its intracellular growth. Like many highly adapted intravacuolar pathogens, L. pneumophila is able to maintain a neutral pH in the lumen of its phagosome, particularly in the early phase of infection. However, in all cases, the molecular mechanisms underlying this observation remain unknown. In this report, we describe the identification and characterization of a Legionella protein termed SidK that specifically targets host v-ATPase, the multi-subunit machinery primarily responsible for organelle acidification in eukaryotic cells. Our results indicate that after being injected into infected cells by the Dot/Icm secretion system, SidK interacts with VatA, a key component of the proton pump. Such binding leads to the inhibition of ATP hydrolysis and proton translocation. When delivered into macrophages, SidK inhibits vacuole acidification and impairs the ability of the cells to digest non-pathogenic E. coli. We also show that a domain located in the N-terminal portion of SidK is responsible for its interactions with VatA. Furthermore, expression of sidK is highly induced when bacteria begin to enter new growth cycle, correlating well with the potential temporal requirement of its activity during infection. Our results indicate that direct targeting of v-ATPase by secreted proteins constitutes a virulence strategy for L. pneumophila, a vacuolar pathogen of macrophages and amoebae

Identification of neutral biochemical network models from time series data

<p>Abstract</p> <p>Background</p> <p>The major difficulty in modeling biological systems from multivariate time series is the identification of parameter sets that endow a model with dynamical behaviors sufficiently similar to the experimental data. Directly related to this parameter estimation issue is the task of identifying the structure and regulation of ill-characterized systems. Both tasks are simplified if the mathematical model is canonical, <it>i.e</it>., if it is constructed according to strict guidelines.</p> <p>Results</p> <p>In this report, we propose a method for the identification of admissible parameter sets of canonical S-systems from biological time series. The method is based on a Monte Carlo process that is combined with an improved version of our previous parameter optimization algorithm. The method maps the parameter space into the network space, which characterizes the connectivity among components, by creating an ensemble of decoupled S-system models that imitate the dynamical behavior of the time series with sufficient accuracy. The concept of sloppiness is revisited in the context of these S-system models with an exploration not only of different parameter sets that produce similar dynamical behaviors but also different network topologies that yield dynamical similarity.</p> <p>Conclusion</p> <p>The proposed parameter estimation methodology was applied to actual time series data from the glycolytic pathway of the bacterium <it>Lactococcus lactis </it>and led to ensembles of models with different network topologies. In parallel, the parameter optimization algorithm was applied to the same dynamical data upon imposing a pre-specified network topology derived from prior biological knowledge, and the results from both strategies were compared. The results suggest that the proposed method may serve as a powerful exploration tool for testing hypotheses and the design of new experiments.</p

An empirical Bayesian approach for model-based inference of cellular signaling networks

Background A common challenge in systems biology is to infer mechanistic descriptions of biological process given limited observations of a biological system. Mathematical models are frequently used to represent a belief about the causal relationships among proteins within a signaling network. Bayesian methods provide an attractive framework for inferring the validity of those beliefs in the context of the available data. However, efficient sampling of high-dimensional parameter space and appropriate convergence criteria provide barriers for implementing an empirical Bayesian approach. The objective of this study was to apply an Adaptive Markov chain Monte Carlo technique to a typical study of cellular signaling pathways. Results As an illustrative example, a kinetic model for the early signaling events associated with the epidermal growth factor (EGF) signaling network was calibrated against dynamic measurements observed in primary rat hepatocytes. A convergence criterion, based upon the Gelman-Rubin potential scale reduction factor, was applied to the model predictions. The posterior distributions of the parameters exhibited complicated structure, including significant covariance between specific parameters and a broad range of variance among the parameters. The model predictions, in contrast, were narrowly distributed and were used to identify areas of agreement among a collection of experimental studies. Conclusion In summary, an empirical Bayesian approach was developed for inferring the confidence that one can place in a particular model that describes signal transduction mechanisms and for inferring inconsistencies in experimental measurements

Anaplasma phagocytophilum Ats-1 Is Imported into Host Cell Mitochondria and Interferes with Apoptosis Induction

Anaplasma phagocytophilum, the causative agent of human granulocytic anaplasmosis, infects human neutrophils and inhibits mitochondria-mediated apoptosis. Bacterial factors involved in this process are unknown. In the present study, we screened a genomic DNA library of A. phagocytophilum for effectors of the type IV secretion system by a bacterial two-hybrid system, using A. phagocytophilum VirD4 as bait. A hypothetical protein was identified as a putative effector, hereby named Anaplasma translocated substrate 1 (Ats-1). Using triple immunofluorescence labeling and Western blot analysis of infected cells, including human neutrophils, we determined that Ats-1 is abundantly expressed by A. phagocytophilum, translocated across the inclusion membrane, localized in the host cell mitochondria, and cleaved. Ectopically expressed Ats-1 targeted mitochondria in an N-terminal 17 residue-dependent manner, localized in matrix or at the inner membrane, and was cleaved as native protein, which required residues 55–57. In vitro-translated Ats-1 was imported in a receptor-dependent manner into isolated mitochondria. Ats-1 inhibited etoposide-induced cytochrome c release from mitochondria, PARP cleavage, and apoptosis in mammalian cells, as well as Bax-induced yeast apoptosis. Ats-1(55–57) had significantly reduced anti-apoptotic activity. Bax redistribution was inhibited in both etoposide-induced and Bax-induced apoptosis by Ats-1. Taken together, Ats-1 is the first example of a bacterial protein that traverses five membranes and prevents apoptosis at the mitochondria

Proteomic Analysis of Growth Phase-Dependent Expression of Legionella pneumophila Proteins Which Involves Regulation of Bacterial Virulence Traits

Legionella pneumophila, which is a causative pathogen of Legionnaires' disease, expresses its virulent traits in response to growth conditions. In particular, it is known to become virulent at a post-exponential phase in vitro culture. In this study, we performed a proteomic analysis of differences in expression between the exponential phase and post-exponential phase to identify candidates associated with L. pneumophila virulence using 2-Dimentional Fluorescence Difference Gel Electrophoresis (2D-DIGE) combined with Matrix-Assisted Laser Desorption/Ionization–Mass Spectrometry (MALDI-TOF-MS). Of 68 identified proteins that significantly differed in expression between the two growth phases, 64 were up-regulated at a post-exponential phase. The up-regulated proteins included enzymes related to glycolysis, ketone body biogenesis and poly-3-hydroxybutyrate (PHB) biogenesis, suggesting that L. pneumophila may utilize sugars and lipids as energy sources, when amino acids become scarce. Proteins related to motility (flagella components and twitching motility-associated proteins) were also up-regulated, predicting that they enhance infectivity of the bacteria in host cells under certain conditions. Furthermore, 9 up-regulated proteins of unknown function were found. Two of them were identified as novel bacterial factors associated with hemolysis of sheep red blood cells (SRBCs). Another 2 were found to be translocated into macrophages via the Icm/Dot type IV secretion apparatus as effector candidates in a reporter assay with Bordetella pertussis adenylate cyclase. The study will be helpful for virulent analysis of L. pneumophila from the viewpoint of physiological or metabolic modulation dependent on growth phase

A multiscale systems perspective on cancer, immunotherapy, and Interleukin-12

Monoclonal antibodies represent some of the most promising molecular targeted immunotherapies. However, understanding mechanisms by which tumors evade elimination by the immune system of the host presents a significant challenge for developing effective cancer immunotherapies. The interaction of cancer cells with the host is a complex process that is distributed across a variety of time and length scales. The time scales range from the dynamics of protein refolding (i.e., microseconds) to the dynamics of disease progression (i.e., years). The length scales span the farthest reaches of the human body (i.e., meters) down to the range of molecular interactions (i.e., nanometers). Limited ranges of time and length scales are used experimentally to observe and quantify changes in physiology due to cancer. Translating knowledge obtained from the limited scales observed experimentally to predict patient response is an essential prerequisite for the rational design of cancer immunotherapies that improve clinical outcomes. In studying multiscale systems, engineers use systems analysis and design to identify important components in a complex system and to test conceptual understanding of the integrated system behavior using simulation. The objective of this review is to summarize interactions between the tumor and cell-mediated immunity from a multiscale perspective. Interleukin-12 and its role in coordinating antibody-dependent cell-mediated cytotoxicity is used illustrate the different time and length scale that underpin cancer immunoediting. An underlying theme in this review is the potential role that simulation can play in translating knowledge across scales

Activation of the thyroid peroxidase gene in human thyroid cells: Effect of thyrotrophin, forskolin and phorbol ester

The enzyme thyroid peroxidase (TPO) plays a central role in thyroid hormone synthesis and is the target for the autoimmune attack in lymphocytic thyroiditis. We have examined the activation of the TPO gene in cultured human thyrocytes using slot blot hybridization with a synthetic 40 mer oligonucleotide probe derived from the nucleotide sequence of the human TPO gene. The oligonucleotide probe was shown by Northern blotting to hybridize specifically to an approximately 3 kb RNA species from thyroid tissue of patients with Graves' disease, but not to RNA preparations from human or bovine retinal tissue, providing compelling evidence for the specificity of the probe for TPO mRNA. Addition of TSH (10 U/ml) to primary thyroid cultures for 4h led to increased TPO mRNA levels which were maximal after 48 h and significantly higher than basal even after 7 days of co-culture. Activation of TPO mRNA by TSH showed dose dependency over a wide range (0.01-100 mU/ml), with a maximal effect at 10 mU TSH/ml in cells cultured for a period of 72 h. Comparison of TPO mRNA levels with the accumulation of thyroglobulin mRNA levels following stimulation by TSH indicated that the induction of the gene encoding thyroglobulin precedes transcription of the TPO gene. The adenylate cyclase activator forskolin (1-100 μM) mimicked TSH in increasing TPO mRNA levels whilst, in contrast, the phorbol ester 12-O-tetradecanoyl phorbol 13-acetate (TPA; 0.01-1 μM) led to levels of TPO mRNA that were lower than basal. Thus TSH induces a specific dose-dependent activation of TPO mRNA which is mimicked by agents which increase cyclic AMP. In contrast, TPA-induced activation of protein kinase C inhibits this response.link_to_subscribed_fulltex