Pseudomonas aeruginosa AMPR transcriptional regulatory network

In Enterobacteriaceae, the transcriptional regulator AmpR, a member of the LysR family, regulates the expression of a chromosomal β-lactamase AmpC. The regulatory repertoire of AmpR is broader in Pseudomonas aeruginosa, an opportunistic pathogen responsible for numerous acute and chronic infections including cystic fibrosis. Previous studies showed that in addition to regulating ampC, P. aeruginosa AmpR regulates the sigma factor AlgT/U and production of some quorum sensing (QS)-regulated virulence factors. In order to better understand the ampR regulon, the transcriptional profiles generated using DNA microarrays and RNA-Seq of the prototypic P. aeruginosa PAO1 strain with its isogenic ampR deletion mutant, PAOΔampR were analyzed. Transcriptome analysis demonstrates that the AmpR regulon is much more extensive than previously thought influencing the differential expression of over 500 genes. In addition to regulating resistance to β-lactam antibiotics via AmpC, AmpR also regulates non-β-lactam antibiotic resistance by modulating the MexEF-OprN efflux pump. Virulence mechanisms including biofilm formation, QS-regulated acute virulence, and diverse physiological processes such as oxidative stress response, heat-shock response and iron uptake are AmpR-regulated. Real-time PCR and phenotypic assays confirmed the transcriptome data. Further, Caenorhabditis elegans model demonstrates that a functional AmpR is required for full pathogenicity of P. aeruginosa. AmpR, a member of the core genome, also regulates genes in the regions of genome plasticity that are acquired by horizontal gene transfer. The extensive AmpR regulon included other transcriptional regulators and sigma factors, accounting for the extensive AmpR regulon. Gene expression studies demonstrate AmpR-dependent expression of the QS master regulator LasR that controls expression of many virulence factors. Using a chromosomally tagged AmpR, ChIP-Seq studies show direct AmpR binding to the lasR promoter. The data demonstrates that AmpR functions as a global regulator in P. aeruginosa and is a positive regulator of acute virulence while negatively regulating chronic infection phenotypes. In summary, my dissertation sheds light on the complex regulatory circuit in P. aeruginosa to provide a better understanding of the bacterial response to antibiotics and how the organism coordinately regulates a myriad of virulence factors.

Pseudomonas Aeruginosa AmpR Transcriptional Regulatory Network

In Enterobacteriaceae, the transcriptional regulator AmpR, a member of the LysR family, regulates the expression of a chromosomal β-lactamase AmpC. The regulatory repertoire of AmpR is broader in Pseudomonas aeruginosa, an opportunistic pathogen responsible for numerous acute and chronic infections including cystic fibrosis. Previous studies showed that in addition to regulating ampC, P. aeruginosa AmpR regulates the sigma factor AlgT/U and production of some quorum sensing (QS)-regulated virulence factors. In order to better understand the ampR regulon, the transcriptional profiles generated using DNA microarrays and RNA-Seq of the prototypic P. aeruginosa PAO1 strain with its isogenic ampR deletion mutant, PAO∆ampR were analyzed. Transcriptome analysis demonstrates that the AmpR regulon is much more extensive than previously thought influencing the differential expression of over 500 genes. In addition to regulating resistance to β-lactam antibiotics via AmpC, AmpR also regulates non-β-lactam antibiotic resistance by modulating the MexEF-OprN efflux pump. Virulence mechanisms including biofilm formation, QS-regulated acute virulence, and diverse physiological processes such as oxidative stress response, heat-shock response and iron uptake are AmpR-regulated. Real-time PCR and phenotypic assays confirmed the transcriptome data. Further, Caenorhabditis elegans model demonstrates that a functional AmpR is required for full pathogenicity of P. aeruginosa. AmpR, a member of the core genome, also regulates genes in the regions of genome plasticity that are acquired by horizontal gene transfer. The extensive AmpR regulon included other transcriptional regulators and sigma factors, accounting for the extensive AmpR regulon. Gene expression studies demonstrate AmpR-dependent expression of the QS master regulator LasR that controls expression of many virulence factors. Using a chromosomally tagged AmpR, ChIP-Seq studies show direct AmpR binding to the lasR promoter. The data demonstrates that AmpR functions as a global regulator in P. aeruginosa and is a positive regulator of acute virulence while negatively regulating chronic infection phenotypes. In summary, my dissertation sheds light on the complex regulatory circuit in P. aeruginosa to provide a better understanding of the bacterial response to antibiotics and how the organism coordinately regulates a myriad of virulence factors.

Characterization of the amp genes involved in the regulation of beta-lactamase expression in Pseudomonas aeruginosa

Antibiotic resistance, production of alginate and virulence factors, and altered host immune responses are the hallmarks of chronic Pseudomonas aeruginosa infection. Failure of antibiotic therapy has been attributed to the emergence of P. aeruginosa strains that produce β-lactamase constitutively. In Enterobacteriaceae, β-lactamase induction involves four genes with known functions: ampC, ampR, ampD, and ampG, encoding the enzyme, transcriptional regulator, amidase and permease, respectively. In addition to all these amp genes, P. aeruginosa possesses two ampG paralogs, designated ampG and ampP. In this study, P. aeruginosa ampC, ampR, ampG and ampP were analyzed. Inactivation of ampC in the prototypic PAO1 failed to abolish the β-lactamase activity leading to the discovery of P. aeruginosa oxacillinase PoxB. Cloning and expression of poxB in Escherichia coli confers β-lactam resistance. Both AmpC and PoxB contribute to P. aeruginosa resistance against a wide spectrum of β-lactam antibiotics. The expression of PoxB and AmpC is regulated by a LysR-type transcriptional regulator AmpR that up-regulates AmpC but down-regulates PoxB activities. Analyses of P. aeruginosa ampR mutant demonstrate that AmpR is a global regulator that modulates the expressions of Las and Rhl quorum sensing (QS) systems, and the production of pyocyanin, LasA protease and LasB elastase. Introduction of the ampR mutation into an alginate-producing strain reveals the presence of a complex co-regulatory network between antibiotic resistance, QS alginate and other virulence factor production. Using phoA and lacZ protein fusion analyses, AmpR, AmpG and AmpP were localized to the inner membrane with one, 16 and 10 transmembrane helices, respectively. AmpR has a cytoplasmic DNA-binding and a periplasmic substrate binding domains. AmpG and AmpP are essential for the maximal expression of β-lactamase. Analysis of the murein breakdown products suggests that AmpG exports UDP-N-acetylmuramyl-L-alanine-γ-D-glutamate-meso-diaminopimelic acid-D-alanine-D-alanine (UDP-MurNAc-pentapeptide), the corepressor of AmpR, whereas AmpP imports N-acetylglucosaminyl-beta-1,4-anhydro-N-acetylmuramic acid-Ala-γ-D-Glu-meso-diaminopimelic acid (GlcNAc-anhMurNAc-tripeptide) and GlcNAc-anhMurNAc-pentapeptide, the co-inducers of AmpR. This study reveals a complex interaction between the Amp proteins and murein breakdown products involved in P. aeruginosa β-lactamase induction. In summary, this dissertation takes us a little closer to understanding the P. aeruginosa complex co-regulatory mechanism in the development of β-lactam resistance and establishment of chronic infection. ^

A Study of Stock Market Fluctuations and their Relations to Business Conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

Three essays on hospital efficiency

This dissertation analyzes hospital efficiency using various econometric techniques. The first essay provides additional and recent evidence to the presence of contract management behavior in the U.S. hospital industry. Unlike previous studies, which focus on either an input-demand equation or the cost function of the firm, this paper estimates the two jointly using a system of nonlinear equations. Moreover, it addresses the longitudinal problem of institutions adopting contract management in different years, by creating a matched control group of non-adopters with the same longitudinal distribution as the group under study. The estimation procedure then finds that labor, and not capital, is the preferred input in U.S. hospitals regardless of managerial contract status. With institutions that adopt contract management benefiting from lower labor inefficiencies than the simulated non-contract adopters. These results suggest that while there is a propensity for expense preference behavior towards the labor input, contract managed firms are able to introduce efficiencies over conventional, owner controlled, firms. Using data for the years 1998 through 2007, the second essay investigates the production technology and cost efficiency faced by Florida hospitals. A stochastic frontier multiproduct cost function is estimated in order to test for economies of scale, economies of scope, and relative cost efficiencies. The results suggest that small-sized hospitals experience economies of scale, while large and medium sized institutions do not. The empirical findings show that Florida hospitals enjoy significant scope economies, regardless of size. Lastly, the evidence suggests that there is a link between hospital size and relative cost efficiency. The results of the study imply that state policy makers should be focused on increasing hospital scale for smaller institutions while facilitating the expansion of multiproduct production for larger hospitals. The third and final essay employs a two staged approach in analyzing the efficiency of hospitals in the state of Florida. In the first stage, the Banker, Charnes, and Cooper model of Data Envelopment Analysis is employed in order to derive overall technical efficiency scores for each non-specialty hospital in the state. Additionally, input slacks are calculated and reported in order to identify the factors of production that each hospital may be over utilizing. In the second stage, we employ a Tobit regression model in order to analyze the effects a number of structural, managerial, and environmental factors may have on a hospital’s efficiency. The results indicated that most non-specialty hospitals in the state are operating away from the efficient production frontier. The results also indicate that the structural make up, managerial choices, and level of competition Florida hospitals face have an impact on their overall technical efficiency.

Cooperative and adaptive medium access control in multi-hop wireless networks

Due to low cost and easy deployment, multi-hop wireless networks become a very attractive communication paradigm. However, IEEE 802.11 medium access control (MAC) protocol widely used in wireless LANs was not designed for multi-hop wireless networks. Although it can support some kinds of ad hoc network architecture, it does not function efficiently in those wireless networks with multi-hop connectivity. Therefore, our research is focused on studying the medium access control in multi-hop wireless networks. The objective is to design practical MAC layer protocols for supporting multihop wireless networks. Particularly, we try to prolong the network lifetime without degrading performances with small battery-powered devices and improve the system throughput with poor quality channels. ^ In this dissertation, we design two MAC protocols. The first one is aimed at minimizing energy-consumption without deteriorating communication activities, which provides energy efficiency, latency guarantee, adaptability and scalability in one type of multi-hop wireless networks (i.e. wireless sensor network). Methodologically, inspired by the phase transition phenomena in distributed networks, we define the wake-up probability, which maintained by each node. By using this probability, we can control the number of wireless connectivity within a local area. More specifically, we can adaptively adjust the wake-up probability based on the local network conditions to reduce energy consumption without increasing transmission latency. The second one is a cooperative MAC layer protocol for multi-hop wireless networks, which leverages multi-rate capability by cooperative transmission among multiple neighboring nodes. Moreover, for bidirectional traffic, the network throughput can be further increased by using the network coding technique. It is a very helpful complement for current rate-adaptive MAC protocols under the poor channel conditions of direct link. Finally, we give an analytical model to analyze impacts of cooperative node on the system throughput. ^