Structural basis for the nuclear import of the human androgen receptor

Ligand-dependent nuclear import is crucial for the function of the androgen receptor (AR) in both health and disease. The unliganded AR is retained in the cytoplasm but, on binding 5alpha-dihydrotestosterone, it translocates into the nucleus and alters transcription of its target genes. Nuclear import of AR is mediated by the nuclear import factor importin-alpha, which functions as a receptor that recognises and binds to specific nuclear localisation signal (NLS) motifs on cargo proteins. We show here that the AR binds to importin-alpha directly, albeit more weakly than the NLS of SV40 or nucleoplasmin. We describe the 2.6-angstroms-resolution crystal structure of the importin-alpha-AR-NLS complex, and show that the AR binds to the major NLS-binding site on importin-alpha in a manner different from most other NLSs. Finally, we have shown that pathological mutations within the NLS of AR that are associated with prostate cancer and androgen-insensitivity syndrome reduce the binding affinity to importin-alpha and, subsequently, retard nuclear import; surprisingly, however, the transcriptional activity of these mutants varies widely. Thus, in addition to its function in the nuclear import of AR, the NLS in the hinge region of AR has a separate, quite distinct role on transactivation, which becomes apparent once nuclear import has been achieved.

Active nuclear import and cytoplasmic retention of activation-induced deaminase

The enzyme activation-induced deaminase (AID) triggers antibody diversification in B cells by catalyzing deamination and consequently mutation of immunoglobulin genes. To minimize off-target deamination, AID is restrained by several regulatory mechanisms including nuclear exclusion, thought to be mediated exclusively by active nuclear export. Here we identify two other mechanisms involved in controlling AID subcellular localization. AID is unable to passively diffuse into the nucleus, despite its small size, and its nuclear entry requires active import mediated by a conformational nuclear localization signal. We also identify in its C terminus a determinant for AID cytoplasmic retention, which hampers diffusion to the nucleus, competes with nuclear import and is crucial for maintaining the predominantly cytoplasmic localization of AID in steady-state conditions. Blocking nuclear import alters the balance between these processes in favor of cytoplasmic retention, resulting in reduced isotype class switching.

Biophysical characterization of the recombinant importin-α from neurospora crassa

Neurospora crassa has been widely used as a model organism and contributed to the development of biochemistry and molecular biology by allowing the identification of many metabolic pathways and mechanisms responsible for gene regulation. Nuclear proteins are synthesized in the cytoplasm and need to be translocated to the nucleus to exert their functions which the importin-α receptor has a key role for the classical nuclear import pathway. In an attempt to get structural information of the nuclear transport process in N. crassa, we present herein the cloning, expression, purification and structural studies with N-terminally truncated IMPα from N. crassa (IMPα-Nc). Circular dichroism analysis revealed that the IMPα-Nc obtained is correctly folded and presents a high structural conservation compared to other importins-α. Dynamic light scattering, analytical size-exclusion chromatography experiments and molecular dynamics simulations indicated that the IMPα-Nc unbound to any ligand may present low stability in solution. The IMPα-Nc theoretical model displayed high similarity of its inner concave surface, which binds the cargo proteins containing the nuclear localization sequences, among IMPα from different species. However, the presence of non-conserved amino acids relatively close to the NLS binding region may influence the binding specificity of IMPα-Nc to cargo proteins. Copyright © 2012 Bentham Science Publishers. All Rights Reserved.

Hsp90 nuclear accumulation in quiescence is linked to chaperone function and spore development in yeast.

The 90-kDa heat-shock protein (Hsp90) operates in the context of a multichaperone complex to promote maturation of nuclear and cytoplasmic clients. We have discovered that Hsp90 and the cochaperone Sba1/p23 accumulate in the nucleus of quiescent Saccharomyces cerevisiae cells. Hsp90 nuclear accumulation was unaffected in sba1Delta cells, demonstrating that Hsp82 translocates independently of Sba1. Translocation of both chaperones was dependent on the alpha/beta importin SRP1/KAP95. Hsp90 nuclear retention was coincident with glucose exhaustion and seems to be a starvation-specific response, as heat shock or 10% ethanol stress failed to elicit translocation. We generated nuclear accumulation-defective HSP82 mutants to probe the nature of this targeting event and identified a mutant with a single amino acid substitution (I578F) sufficient to retain Hsp90 in the cytoplasm in quiescent cells. Diploid hsp82-I578F cells exhibited pronounced defects in spore wall construction and maturation, resulting in catastrophic sporulation. The mislocalization and sporulation phenotypes were shared by another previously identified HSP82 mutant allele. Pharmacological inhibition of Hsp90 with macbecin in sporulating diploid cells also blocked spore formation, underscoring the importance of this chaperone in this developmental program.

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.