On a Direct Approach to the Solution of Inverse Optical Problems

The evaluation from experimental data, of physical quantities, which enter into the electromagnetic Maxwell equations, is described as inverse optical problem. The functional relations between the dependent and independent variables are of transcendental character and numeric procedures for evaluation of the unknowns are largely used. Herein, we discuss a direct approach to the solution, illustrated by a specific example of determination of thin films optical constants from spectrophotometric data. New algorithm is proposed for the parameters evaluation, which does not need an initial guess of the unknowns and does not use iterative procedures. Thus we overcome the intrinsic deficiency of minimization techniques, such as gradient search methods, Simplex methods, etc. The price of it is a need of more computing power, but our algorithm is easily implemented in structures such as grid clusters. We show the advantages of this approach and its potential for generalization to other inverse optical problems

Modeling Optical Response of Thin Films: Choice of the Refractive Index Dispersion Law

Determination of the so-called optical constants (complex refractive index N, which is usually a function of the wavelength, and physical thickness D) of thin films from experimental data is a typical inverse non-linear problem. It is still a challenge to the scientific community because of the complexity of the problem and its basic and technological significance in optics. Usually, solutions are looked for models with 3-10 parameters. Best estimates of these parameters are obtained by minimization procedures. Herein, we discuss the choice of orthogonal polynomials for the dispersion law of the thin film refractive index. We show the advantage of their use, compared to the Selmeier, Lorentz or Cauchy models

Information Modelling of Two-Dimensional Optical Parameters Measurement

A method for measurement and visualization of the complex transmission coefficient of 2-D micro- objects is proposed. The method is based on calculation of the transmission coefficient from the diffraction pattern and the illumination aperture function for monochromatic light. A phase-stepping method was used for diffracted light phase determination

De novo prediction of PTBP1 binding and splicing targets reveals unexpected features of its RNA recognition and function.

The splicing regulator Polypyrimidine Tract Binding Protein (PTBP1) has four RNA binding domains that each binds a short pyrimidine element, allowing recognition of diverse pyrimidine-rich sequences. This variation makes it difficult to evaluate PTBP1 binding to particular sites based on sequence alone and thus to identify target RNAs. Conversely, transcriptome-wide binding assays such as CLIP identify many in vivo targets, but do not provide a quantitative assessment of binding and are informative only for the cells where the analysis is performed. A general method of predicting PTBP1 binding and possible targets in any cell type is needed. We developed computational models that predict the binding and splicing targets of PTBP1. A Hidden Markov Model (HMM), trained on CLIP-seq data, was used to score probable PTBP1 binding sites. Scores from this model are highly correlated (ρ = -0.9) with experimentally determined dissociation constants. Notably, we find that the protein is not strictly pyrimidine specific, as interspersed Guanosine residues are well tolerated within PTBP1 binding sites. This model identifies many previously unrecognized PTBP1 binding sites, and can score PTBP1 binding across the transcriptome in the absence of CLIP data. Using this model to examine the placement of PTBP1 binding sites in controlling splicing, we trained a multinomial logistic model on sets of PTBP1 regulated and unregulated exons. Applying this model to rank exons across the mouse transcriptome identifies known PTBP1 targets and many new exons that were confirmed as PTBP1-repressed by RT-PCR and RNA-seq after PTBP1 depletion. We find that PTBP1 dependent exons are diverse in structure and do not all fit previous descriptions of the placement of PTBP1 binding sites. Our study uncovers new features of RNA recognition and splicing regulation by PTBP1. This approach can be applied to other multi-RRM domain proteins to assess binding site degeneracy and multifactorial splicing regulation

The Musashi 1 Controls the Splicing of Photoreceptor-Specific Exons in the Vertebrate Retina

Alternative pre-mRNA splicing expands the coding capacity of eukaryotic genomes, potentially enabling a limited number of genes to govern the development of complex anatomical structures. Alternative splicing is particularly prevalent in the vertebrate nervous system, where it is required for neuronal development and function. Here, we show that photoreceptor cells, a type of sensory neuron, express a characteristic splicing program that affects a broad set of transcripts and is initiated prior to the development of the light sensing outer segments. Surprisingly, photoreceptors lack prototypical neuronal splicing factors and their splicing profile is driven to a significant degree by the Musashi 1 (MSI1) protein. A striking feature of the photoreceptor splicing program are exons that display a switch-like pattern of high inclusion levels in photoreceptors and near complete exclusion outside of the retina. Several ubiquitously expressed genes that are involved in the biogenesis and function of primary cilia produce highly photoreceptor specific isoforms through use of such “switchlike” exons. Our results suggest a potential role for alternative splicing in the development of photoreceptors and the conversion of their primary cilia to the light sensing outer segments

Characterization of novel inhibitors of HIV-1 replication that function via alteration of viral RNA processing and rev function

Expression of the complete HIV-1 genome depends on the appropriate processing of viral RNA. Altering the balance of viral RNA processing impairs replication of the virus. In this report, we characterize two small molecule modulators of HIV-1 RNA processing, 8-azaguanine and 2-(2-(5-nitro-2-thienyl)vinyl)quinoline (5350150), which function by distinct mechanisms to suppress viral gene expression. Although only 8-Azaguanine dramatically decreased accumulation of HIV-1 unspliced and singly spliced RNAs and altered splice site usage, both compounds blocked Gag and Env expression without affecting production of Tat (p16) and Rev regulatory proteins. Subsequent analyses suggest that these compounds affect Rev-mediated RNA transport by different mechanisms. Both compounds induced cytoplasmic accumulation of Rev, suggesting that they function, in part, by impairing Rev function. This conclusion is supported by the determination that both drugs block the nuclear export of genomic HIV-1 RNA to the cytoplasm. Testing confirmed that these compounds suppress HIV-1 expression in T cells at doses below those previously used in humans for tumour chemotherapy. Together, our observations demonstrate that small molecules can be used to inhibit HIV-1 replication by altering another avenue of viral RNA processing, offering the potential for the development of novel therapeutics for controlling this disease

De Novo Prediction of PTBP1 Binding and Splicing Targets Reveals Unexpected Features of Its RNA Recognition and Function

The splicing regulator Polypyrimidine Tract Binding Protein (PTBP1) has four RNA binding domains that each binds a short pyrimidine element, allowing recognition of diverse pyrimidine-rich sequences. This variation makes it difficult to evaluate PTBP1 binding to particular sites based on sequence alone and thus to identify target RNAs. Conversely, transcriptome-wide binding assays such as CLIP identify many in vivo targets, but do not provide a quantitative assessment of binding and are informative only for the cells where the analysis is performed. A general method of predicting PTBP1 binding and possible targets in any cell type is needed. We developed computational models that predict the binding and splicing targets of PTBP1. A Hidden Markov Model (HMM), trained on CLIP-seq data, was used to score probable PTBP1 binding sites. Scores from this model are highly correlated (ρ = −0.9) with experimentally determined dissociation constants. Notably, we find that the protein is not strictly pyrimidine specific, as interspersed Guanosine residues are well tolerated within PTBP1 binding sites. This model identifies many previously unrecognized PTBP1 binding sites, and can score PTBP1 binding across the transcriptome in the absence of CLIP data. Using this model to examine the placement of PTBP1 binding sites in controlling splicing, we trained a multinomial logistic model on sets of PTBP1 regulated and unregulated exons. Applying this model to rank exons across the mouse transcriptome identifies known PTBP1 targets and many new exons that were confirmed as PTBP1-repressed by RT-PCR and RNA-seq after PTBP1 depletion. We find that PTBP1 dependent exons are diverse in structure and do not all fit previous descriptions of the placement of PTBP1 binding sites. Our study uncovers new features of RNA recognition and splicing regulation by PTBP1. This approach can be applied to other multi-RRM domain proteins to assess binding site degeneracy and multifactorial splicing regulation

ADP-Ribosylation Factor-Like 2 (ARL2) regulates cilia stability and development of outer segments in rod photoreceptor neurons

Photoreceptor cells are specialized neurons with a sensory cilium carrying an elaborate membrane structure, the outer segment (OS). Inherited mutations in genes involved in ciliogenesis frequently result in OS malformation and blindness. ADP-ribosylation factor-like 2 (ARL2) has recently been implicated in OS formation through its association with Binder of ARL2 (BART or ARL2BP), a protein linked to inherited blinding disease. To test the role of ARL2 in vision we created a transgenic mouse model expressing a tagged-dominant active form of human ARL2 (ARL2-Q70L) under a rod-specific promoter. Transgenic ARL2-Q70L animals exhibit reduced photoreceptor cell function as early as post-natal day 16 and progressive rod degeneration. We attribute loss of photoreceptor function to the defective OS morphogenesis in the ARL2-Q70L transgenic model. ARL2-Q70L expression results in shortened inner and outer segments, shortened and mislocalized axonemes and cytoplasmic accumulation of rhodopsin. In conclusion, we show that ARL2-Q70L is crucial for photoreceptor neuron sensory cilium development. Future research will expand upon our hypothesis that ARL2-Q70L mutant interferes with microtubule maintenance and tubulin regulation resulting in impaired growth of the axoneme and elaboration of the photoreceptor outer segment

Grainyhead-like 2 inhibits the coactivator p300, suppressing tubulogenesis and the epithelial–mesenchymal transition

Developmental morphogenesis and tumor progression require a transient or stable breakdown of epithelial junctional complexes to permit programmed migration, invasion, and anoikis resistance, characteristics endowed by the epithelial–mesenchymal transition (EMT). The epithelial master-regulatory transcription factor Grainyhead-like 2 (GRHL2) suppresses and reverses EMT, causing a mesenchymal–epithelial transition to the default epithelial phenotype. Here we investigated the role of GRHL2 in tubulogenesis of Madin–Darby canine kidney cells, a process requiring transient, partial EMT. GRHL2 was required for cystogenesis, but it suppressed tubulogenesis in response to hepatocyte growth factor. Surprisingly, GRHL2 suppressed this process by inhibiting the histone acetyltransferase coactivator p300, preventing the induction of matrix metalloproteases and other p300-dependent genes required for tubulogenesis. A 13–amino acid region of GRHL2 was necessary for inhibition of p300, suppression of tubulogenesis, and interference with EMT. The results demonstrate that p300 is required for partial or complete EMT occurring in tubulogenesis or tumor progression and that GRHL2 suppresses EMT in both contexts through inhibition of p300