Low-Resolution Molecular Models Reveal the Oligomeric State of the PPAR and the Conformational Organization of Its Domains in Solution

The peroxisome proliferator-activated receptors (PPARs) regulate genes involved in lipid and carbohydrate metabolism, and are targets of drugs approved for human use. Whereas the crystallographic structure of the complex of full length PPAR gamma and RXR alpha is known, structural alterations induced by heterodimer formation and DNA contacts are not well understood. Herein, we report a small-angle X-ray scattering analysis of the oligomeric state of hPPAR gamma alone and in the presence of retinoid X receptor (RXR). The results reveal that, in contrast with other studied nuclear receptors, which predominantly form dimers in solution, hPPAR gamma remains in the monomeric form by itself but forms heterodimers with hRXR alpha. The low-resolution models of hPPAR gamma/RXR alpha complexes predict significant changes in opening angle between heterodimerization partners (LBD) and extended and asymmetric shape of the dimer (LBD-DBD) as compared with X-ray structure of the full-length receptor bound to DNA. These differences between our SAXS models and the high-resolution crystallographic structure might suggest that there are different conformations of functional heterodimer complex in solution. Accordingly, hydrogen/deuterium exchange experiments reveal that the heterodimer binding to DNA promotes more compact and less solvent-accessible conformation of the receptor complex.

Regulation of squamous cell differentiation in human head and neck carcinoma cells by retinoids

Retinoids have been found to be effective in the prevention of premalignant lesions and second primary cancers in the upper aerodigestive tract. Further development of retinoids for prevention and therapy of head and neck squamous cell carcinoma (HNSCC) requires a better understanding of their mechanism of action on the growth and differentiation of such cells. I have chosen to employ cultured HNSCC cell lines as a model system for investigating the mechanism underlying the effects of retinoids. These cells are useful because all-trans retinoic acid (ATRA) inhibits their proliferation. Furthermore, two HNSCC cell lines were found to express three squamous differentiation (SqD) markers characteristic of normal keratinocytes and ATRA suppressed the expression of these markers as reported for normal keratinocytes. It is thought that nuclear retinoic acid receptors (RARs and RXRs), which act as DNA-binding transcription modulating factors, mediate the effects of retinoids on the growth and differentiation of normal and tumor cells. I found that all four cell lines examined expressed RAR-$\alpha ,$ RAR-$\tau ,$ and RXR-$\alpha$ and three of four expressed RAR-$\beta .$ ATRA treatment increased the level of RAR-$\alpha ,$ -$\beta ,$ and -$\tau$ in four cell lines. Two HNSCC cell lines that exhibited a progressive increase in the expression of SqD markers during growth in culture also showed a concurrent decrease in RAR-$\beta$ level. Moreover, increasing concentrations of RA suppressed the SqD marker while inducing RAR-$\beta$ mRNA. Several synthetic retinoids which exhibit a preference for binding to specific nuclear RARs showed a differential ability to inhibit cell proliferation, transactivate transcription of the reporter genes (CAT and luciferase) from the RA response element (RARE) of the RAR-$\beta$ gene, and induce RAR-$\beta$ expression. Those retinoids that were effective inducers of RAR-$\beta$ also suppressed SqD effectively, indicating an inverse relationship exists between the expression of RAR-$\beta$ and SqD. This inverse relationship suggests a role for RAR-$\beta$ in the suppression of SqD. ^

Conditional site-specific recombination in mammalian cells using a ligand-dependent chimeric Cre recombinase.

We have developed a strategy to generate mutant genes in mammalian cells in a conditional manner by employing a fusion protein, Cre-ER, consisting of the loxP site-specific Cre recombinase linked to the ligand-binding domain of the human estrogen receptor. We have established homozygous retinoid X receptor alpha-negative (RXR alpha-/-) F9 embryonal carcinoma cells constitutively expressing Cre-ER and have shown that estradiol or the estrogen agonist/antagonist 4-hydroxytamoxifen efficiently induced the recombinase activity, whereas no activity was detected in the absence of ligand or in the presence of the antiestrogen ICI 164,384. Furthermore, using a targeting vector containing a selection marker flanked by loxP sites, we have inactivated one retinoic acid receptor alpha allele in such a line, demonstrating that the presence of the recombinase does not inhibit homologous recombination. Combining this conditional site-specific recombination system with tissue-specific expression of Cre-ER may allow modification of the mammalian genome in vivo in a spatiotemporally regulated manner.

Aktivierung der alpha-Sekretase ADAM10 als neuer therapeutischer Ansatz zur Behandlung der Alzheimer-Erkrankung

Die Stimulation der APP-prozessierenden α-Sekretase ADAM10 eröffnet eine vielversprechende Möglichkeit zur medizinischen Behandlung der Alzheimer-Krankheit. In dieser Arbeit wurden drei unterschiedliche Strategien zur therapeutischen Aktivierung von ADAM10 verfolgt: Die Aktivierung des G-Protein-gekoppelten Rezeptors PAC1 durch PACAP, die Gentherapie mit ADAM10-cDNA und die ADAM10-Promotorstimulation durch Retinoid-Rezeptor-Aktivierung. PACAP-38 stimuliert die α-Sekretase-vermittelte APPsα-Sekretion in humanen Neuroblastomzellen. Durch Aktivierung des PAC-1-Rezeptors via intranasal verabreichtem PACAP-38, konnte eine erhöhte α-sekretorische APP-Prozessierung bzw. verminderte Ablagerung von amyloiden Plaques in Mäusen gezeigt werden. Weiterhin sollte durch Immunoliposomen-basierte Transfektion die humane ADAM10-cDNA in den Neuronen der Maus überexprimiert werden. Hiefür wurde die DNA in Liposomen eingeschlossen, welche an ihrer Oberfläche mit anti-Transferrin-Antikörpern zur Überwindung der Blut-Hirn-Schranke gekoppelt waren. Für die Herstellung des DNA-Transportsystems wurden die Einzelschritte wie DNA-Einschluss mit einem Reportergen-Vektor, Konjugation mit verschiedenen Antikörpern und Größe der Liposomen erprobt und optimiert. Es konnte allerdings weder in vitro noch in vivo eine Immunoliposomen-vermittelte Transfektion nachgewiesen werden. In dieser Arbeit wurde zudem die Retinoid-basierte Expressionssteigerung von ADAM10 untersucht. Dafür wurden die beiden potentiellen Retinoid-Rezeptor-Bindestellen auf dem ADAM10-Promotor durch Verwendung selektiver nukleärer Rezeptor-Agonisten charakterisiert. Hierbei konnte erstmals gezeigt werden, dass der ADAM10-Promotor durch ein Dimer der nukleären Rezeptoren RAR und RXR aktiviert wird, wodurch eine erhöhte α-sekretorischen APP-Prozessierung in Neuroblastoma-Zellen resultiert. Weiterhin konnte gezeigt werden, dass die RAR/RXR-Heterodimeraktivierung sowohl auf dem humanen wie auf dem murinen ADAM10-Promotor identisch ist, so dass am Mausmodell entwickelte Retinoid-basierte Therapien auf den Menschen übertragbar sind. Für das Modell einer solchen Therapie wurde Acitretin verwendet, welches für die medizinische Behandlung humaner Hautkrankheiten seit Jahrzehnten eingesetzt wird. In dieser Arbeit konnte erstmals gezeigt werden, dass Acitretin in humanen und murinen Neuroblastoma-Zellen die Menge an ADAM10 erhöht, wodurch die α-sekretorische APP-Prozessierung gesteigert wird. Zudem wurden Mäuse mit Acitretin oral, subcutan und intranasal behandelt, wobei jedoch weder eine Veränderung in der APP-Prozessierung noch der Blut-Hirn-Transport von Acitretin eindeutig belegt werden konnten. Dennoch erschließt die α-Sekretase-erhöhende Eigenschaft von Acitretin einen neuen Therapieansatz, zur Behandlung von Demenzformen vom Typ des Morbus Alzheimer.

Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.