Exploring the rate-limiting steps in visual phototransduction recovery by bottom-up kinetic modeling

Phototransduction in vertebrate photoreceptor cells represents a paradigm of signaling pathways mediated by G-protein-coupled receptors (GPCRs), which share common modules linking the initiation of the cascade to the final response of the cell. In this work, we focused on the recovery phase of the visual photoresponse, which is comprised of several interacting mechanisms. We employed current biochemical knowledge to investigate the response mechanisms of a comprehensive model of the visual phototransduction pathway. In particular, we have improved the model by implementing a more detailed representation of the recoverin (Rec)-mediated calcium feedback on rhodopsin kinase and including a dynamic arrestin (Arr) oligomerization mechanism. The model was successfully employed to investigate the rate limiting steps in the recovery of the rod photoreceptor cell after illumination. Simulation of experimental conditions in which the expression levels of rhodospin kinase (RK), of the regulator of the G-protein signaling (RGS), of Arr and of Rec were altered individually or in combination revealed severe kinetic constraints to the dynamics of the overall network. Our simulations confirm that RGS-mediated effector shutdown is the rate-limiting step in the recovery of the photoreceptor and show that the dynamic formation and dissociation of Arr homodimers and homotetramers at different light intensities significantly affect the timing of rhodopsin shutdown. The transition of Arr from its oligomeric storage forms to its monomeric form serves to temper its availability in the functional state. Our results may explain the puzzling evidence that overexpressing RK does not influence the saturation time of rod cells at bright light stimuli. The approach presented here could be extended to the study of other GPCR signaling pathways.

Integrative analysis of the Regulatory Region of the FGFR3 Oncogene

The study of transcriptional regulation often needs the integration of diverse yet independent data. In the present work, sequence conservation, predic-tion of transcription factor binding sites (TFBS) and gene expression analysis have been applied to the detection of putative transcription factor (TF) modules in the regulatory region of the FGFR3 oncogene. Several TFs with conserved binding sites in the FGFR3 regulatory region have shown high positive or negative corre-lation with FGFR3 expression both in urothelial carcinoma and in benign nevi. By means of conserved TF cluster analysis, two different TF modules have been iden-tified in the promoter and first intron of FGFR3 gene. These modules contain acti-vating AP2, E2F, E47 and SP1 binding sites plus motifs for EGR with possible repressor function.

On the connectivity of the escaping set for complex exponential Misiurewicz parameters

Let $ E_{\lambda}(z)=\lambda {\rm exp}(z), \lambda\in \mathbb{C}$, be the complex exponential family. For all functions in the family there is a unique asymptotic value at 0 (and no critical values). For a fixed $ \lambda$, the set of points in $ \mathbb{C}$ with orbit tending to infinity is called the escaping set. We prove that the escaping set of $ E_{\lambda}$ with $ \lambda$ Misiurewicz (that is, a parameter for which the orbit of the singular value is strictly preperiodic) is a connected set.

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

The death receptor antagonist FAIM promotes neurite outgrowth by a mechanism that depends on ERK and NF-κB signaling

Fas apoptosis inhibitory molecule (FAIM) is a protein identified as an antagonist of Fas-induced cell death. We show that FAIM overexpression fails to rescue neurons from trophic factor deprivation, but exerts a marked neurite growth–promoting action in different neuronal systems. Whereas FAIM overexpression greatly enhanced neurite outgrowth from PC12 cells and sympathetic neurons grown with nerve growth factor (NGF), reduction of endogenous FAIM levels by RNAi decreased neurite outgrowth in these cells. FAIM overexpression promoted NF-κB activation, and blocking this activation by using a super-repressor IκBα or by carrying out experiments using cortical neurons from mice that lack the p65 NF-κB subunit prevented FAIM-induced neurite outgrowth. The effect of FAIM on neurite outgrowth was also blocked by inhibition of the Ras–ERK pathway. Finally, we show that FAIM interacts with both Trk and p75 neurotrophin receptor NGF receptors in a ligand-dependent manner. These results reveal a new function of FAIM in promoting neurite outgrowth by a mechanism involving activation of the Ras–ERK pathway and NF-κB.

Assessment of insecticide resistance in eggs and neonate larvae of Cydia pomonella (Lepidoptera: Tortricidae)

Spanish Cydia pomonella (L.) field populations have developed resistance to several insecticide groups. Diagnostic concentrations were established as the LC90 calculated on a susceptible strain (S_Spain) for five and seven insecticides and tested on eggs and neonate larvae field populations, respectively. The three most relevant enzymatic detoxification systems (mixed-function oxidases (MFO), glutathione S-tranferases (GST) and esterases (EST)) were studied for neonate larvae. In eggs, 96% of the field populations showed a significantly lower efficacy when compared with the susceptible strain (S_Spain) and the most effective insecticides were fenoxycarb and thiacloprid. In neonate larvae, a significant loss of susceptibility to the insecticides was detected. Flufenoxuron, azinphos-methyl and phosmet showed the lowest efficacy, while lambda-cyhalothrin, alpha-cypermethrin and chlorpyrifos-ethyl showed the highest. Biochemical assays showed that the most important enzymatic system involved in insecticide detoxification was MFO, with highest enzymatic activity ratios (5.1–16.6 for neonates from nine field populations). An enhanced GST and EST activities was detected in one field population, with enzymatic activity ratios of threefold and fivefold for GST and EST, respectively, when compared with the susceptible strain. The insecticide bioassays showed that the LC90 used were effective as diagnostic concentrations. Measures of MFO activity alongside bioassays with insecticide diagnostic concentrations could be used as tools for monitoring insecticide resistance in neonate larvae of C. pomonella.

On the origin of the selectivity of plasmidic H-NS towards horizontally acquired DNA: Linking H-NS oligomerization and cooperative DNA binding

The nucleoid-associated protein H-NS is a global modulator of the expression of genes associated with adaptation to environmental changes. A variant of H-NS expressed in the R27 plasmid was previously shown to selectively modulate the expression of horizontally acquired genes, with minimal effects on core genes that are repressed by the chromosomal form of H-NS. Both H-NS proteins are formed by an oligomerization domain and a DNA-binding domain, which are connected by a linker that is highly flexible in the absence of DNA. We studied DNA binding by means of oligomer-forming chimeric proteins in which domains of the chromosomal and plasmidic variants are exchanged, as well as in monomeric truncated forms containing the DNA-binding domain and variable portions of the linker. Point mutations in the linker were also examined in full-length and truncated H-NS constructs. These experiments show that the linker region contributes to DNA binding affinity and that it is a main component of the distinct DNA binding properties of chromosomal and plasmidic H-NS. We propose that interactions between the linker and DNA limit the flexibility of the connection between H- NS oligomerization and DNA binding and provide an allosteric indirect readout mechanism to detect long- range distortions of DNA, thus enabling discrimination between core and horizontally acquired DNA.

Dual role of LldR in regulation of the lldPRD operon, involved in l-Lactate metabolism in Escherichia coli.

The lldPRD operon of Escherichia coli, involved in L-lactate metabolism, is induced by growth in this compound. We experimentally identified that this system is transcribed from a single promoter with an initiation site located 110 nucleotides upstream of the ATG start codon. On the basis of computational data, it had been proposed that LldR and its homologue PdhR act as regulators of the lldPRD operon. Nevertheless, no experimental data on the function of these regulators have been reported so far. Here we show that induction of an lldP-lacZ fusion by L-lactate is lost in an lldR mutant, indicating the role of LldR in this induction. Expression analysis of this construct in a pdhR mutant ruled out the participation of PdhR in the control of lldPRD. Gel shift experiments showed that LldR binds to two operator sites, O1 (positions 105 to 89) and O2 (positions 22 to 38), with O1 being filled at a lower concentration of LldR. L-Lactate induced a conformational change in LldR that did not modify its DNA binding activity. Mutations in O1 and O2 enhanced the basal transcriptional level. However, only mutations in O1 abolished induction by L-lactate. Mutants with a change in helical phasing between O1 and O2 behaved like O2 mutants. These results were consistent with the hypothesis that LldR has a dual role, acting as a repressor or an activator of lldPRD. We propose that in the absence of L-lactate, LldR binds to both O1 and O2, probably leading to DNA looping and the repression of transcription. Binding of L-lactate to LldR promotes a conformational change that may disrupt the DNA loop, allowing the formation of the transcription open complex.

SMRT-mediated co-shuttling enables export of class IIa HDACs independent of their CaM kinase phosphorylation sites

The Class IIa histone deacetylases (HDAC)4 and HDAC5 play a role in neuronal survival and behavioral adaptation in the CNS. Phosphorylation at 2/3 N-terminal sites promote their nuclear export. We investigated whether non-canonical signaling routes to Class IIa HDAC export exist because of their association with the co-repressor Silencing Mediator Of Retinoic And Thyroid Hormone Receptors (SMRT). We found that, while HDAC5 and HDAC4 mutants lacking their N-terminal phosphorylation sites (HDAC4(MUT), HDAC5(MUT)) are constitutively nuclear, co-expression with SMRT renders them exportable by signals that trigger SMRT export, such as synaptic activity, HDAC inhibition, and Brain Derived Neurotrophic Factor (BDNF) signaling. We found that SMRT's repression domain 3 (RD3) is critical for co-shuttling of HDAC5(MUT), consistent with the role for this domain in Class IIa HDAC association. In the context of BDNF signaling, we found that HDAC5(WT), which was more cytoplasmic than HDAC5(MUT), accumulated in the nucleus after BDNF treatment. However, co-expression of SMRT blocked BDNF-induced HDAC5(WT) import in a RD3-dependent manner. In effect, SMRT-mediated HDAC5(WT) export was opposing the BDNF-induced HDAC5 nuclear accumulation observed in SMRT's absence. Thus, SMRT's presence may render Class IIa HDACs exportable by a wider range of signals than those which simply

Optimal Traffic Grooming in WDM using Lighttours

Recent developments in optical communications have allowed simpler optical devices to improve network resource utilization. As such, we propose adding a lambda-monitoring device to a wavelength-routing switch (WRS) allowing better performance when traffic is routed and groomed. This device may allow a WRS to aggregate traffic over optical routes without incurring in optical-electrical-optical conversion for the existing traffic. In other words, optical routes can be taken partially to route demands creating a sort of "lighttours". In this paper, we compare the number of OEO conversions needed to route a complete given traffic matrix using either lighttours or lightpaths

G+: Enhanced Traffic Grooming in WDM Mesh Networks using Lighttours

In this article, a new technique for grooming low-speed traffic demands into high-speed optical routes is proposed. This enhancement allows a transparent wavelength-routing switch (WRS) to aggregate traffic en route over existing optical routes without incurring expensive optical-electrical-optical (OEO) conversions. This implies that: a) an optical route may be considered as having more than one ingress node (all inline) and, b) traffic demands can partially use optical routes to reach their destination. The proposed optical routes are named "lighttours" since the traffic originating from different sources can be forwarded together in a single optical route, i.e., as taking a "tour" over different sources towards the same destination. The possibility of creating lighttours is the consequence of a novel WRS architecture proposed in this article, named "enhanced grooming" (G+). The ability to groom more traffic in the middle of a lighttour is achieved with the support of a simple optical device named lambda-monitor (previously introduced in the RingO project). In this article, we present the new WRS architecture and its advantages. To compare the advantages of lighttours with respect to classical lightpaths, an integer linear programming (ILP) model is proposed for the well-known multilayer problem: traffic grooming, routing and wavelength assignment The ILP model may be used for several objectives. However, this article focuses on two objectives: maximizing the network throughput, and minimizing the number of optical-electro-optical conversions used. Experiments show that G+ can route all the traffic using only half of the total OEO conversions needed by classical grooming. An heuristic is also proposed, aiming at achieving near optimal results in polynomial time