Computational assessment of pigment epithelium-derived factor as an anti-cancer protein during its interaction with the receptors.

Pigment epithelium-derived factor (PEDF) is a member of the serine proteinase inhibitor (serpin) with antiangiogenic, anti-tumorigenic, antioxidant, anti-atherosclerosis, antithrombotic, anti-inflammatory, and neuroprotective properties. The PEDF can bind to low-density lipoprotein receptor-related protein 6 (LRP6), laminin (LR), vascular endothelial growth factor receptor 1 (VEGFR1), vascular endothelial growth factor receptor 2 (VEGFR2), and ATP synthase ß-subunit receptors. In this study, we aimed to investigate the structural basis of the interaction between PEDF and its receptors using bioinformatics approaches to identify the critical amino acids for designing anticancer peptides. The human ATP synthase ß-subunit was predicted by homology modeling. The molecular docking, molecular dynamics (MD) simulation, and Molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) were used to study this protein-receptor complex. The molecular docking showed PEDF could bind to the Laminin and VEGFR2 much stronger than ATP synthase ß-subunit, VEGFR1, and LRP6. The PEDF could effectively interact with various receptors during the simulation. The N-terminal of PEDF has an important role in the interaction with the receptors. The MM/PBSA showed the electrostatic (ΔEElec) and van der Waals interactions (ΔEVdW) contributed positively to the binding process of the complexes. The critical amino acids in the binding interaction of PEDF to its receptors in the MD simulation were determined. The interaction mode of 34-mer PEDF to laminin, VEGFR2, and LRP6 were different from VEGFR1, ATP synthase ß-subunit. The 34-mer PEDF has an important role in the interaction with different receptors and these critical amino acids can be used for designing peptides for future therapeutic aims.Communicated by Ramaswamy H. Sarma.

Analysis of gene expression profiles of lung cancer subtypes with machine learning algorithms.

Lung cancer is one of the most common cancer types worldwide and causes more than one million deaths annually. Lung adenocarcinoma (AC) and lung squamous cell cancer (SCC) are two major lung cancer subtypes and have different characteristics in several aspects. Identifying their differentially expressed genes and different gene expression patterns can deepen our understanding of these two subtypes at the transcriptomic level. In this work, we used several machine learning algorithms to investigate the gene expression profiles of lung AC and lung SCC samples retrieved from Gene Expression Omnibus. First, the profiles were analyzed by using a powerful feature selection method, namely, Monte Carlo feature selection. A feature list, ranking all features according to their importance, and some informative features were obtained. Then, the feature list was used in the incremental feature selection method to extract optimal features, which can allow the support vector machine (SVM) to yield the best performance for classifying lung AC and lung SCC samples. Some top genes (CSTA, TP63, SERPINB13, CLCA2, BICD2, PERP, FAT2, BNC1, ATP11B, FAM83B, KRT5, PARD6G, PKP1) were extensively analyzed to prove that they can be differentially expressed genes between lung AC and lung SCC. Meanwhile, a rule learning procedure was applied on informative features to construct the classification rules. These rules provide a clear procedure of classification and show some different gene expression patterns between lung AC and lung SCC.

Functional Assessment of Patient-Derived Retinal Pigment Epithelial Cells Edited by CRISPR/Cas9.

Retinitis pigmentosa is the most common form of inherited blindness and can be caused by a multitude of different genetic mutations that lead to similar phenotypes. Specifically, mutations in ubiquitously expressed splicing factor proteins are known to cause an autosomal dominant form of the disease, but the retina-specific pathology of these mutations is not well understood. Fibroblasts from a patient with splicing factor retinitis pigmentosa caused by a missense mutation in the PRPF8 splicing factor were used to produce three diseased and three CRISPR/Cas9-corrected induced pluripotent stem cell (iPSC) clones. We differentiated each of these clones into retinal pigment epithelial (RPE) cells via directed differentiation and analyzed the RPE cells in terms of gene and protein expression, apicobasal polarity, and phagocytic ability. We demonstrate that RPE cells can be produced from patient-derived and corrected cells and they exhibit morphology and functionality similar but not identical to wild-type RPE cells in vitro. Functionally, the RPE cells were able to establish apicobasal polarity and phagocytose photoreceptor outer segments at the same capacity as wild-type cells. These data suggest that patient-derived iPSCs, both diseased and corrected, are able to differentiate into RPE cells with a near normal phenotype and without differences in phagocytosis, a result that differs from previous mouse models. These RPE cells can now be studied to establish a disease-in-a-dish system relevant to retinitis pigmentosa.

In Vitro Approaches for the Assessment of Serpin Polymerization.

Serpin polymerization is the result of end-to-end ordered aggregation of serpin monomers into linear unbranched chains. This change in molecular state represents the basis of several conformational diseases with pathological gain-of-function and loss-of-function phenotypes, termed serpinopathies. Tools that enable quantification and characterization of polymer formation are therefore important to the study of serpin behavior in this pathophysiological context. Such methods rely on different manifestations of molecular change: polymerization-the generation of molecules with increasing molecular weight-is accompanied by concomitant structural rearrangements in the constituent subunits. Different approaches may be appropriate dependent on whether measurements are made on static samples, such as tissue or cell culture extracts, or in time-resolved experiments, often undertaken using polymers artificially induced under in vitro destabilizing conditions. In the former category, we describe the application of polyacrylamide electrophoresis, Western blot, ELISA, and negative-stain electron microscopy and in the latter category, Förster resonance energy transfer and fluorescence spectroscopy using environment-sensitive probes.

Human bone marrow stromal cell confluence: effects on cell characteristics and methods of assessment.

BACKGROUND AIMS: Ex vivo expansion and serial passage of human bone marrow stromal cells (BMSCs, also known as bone marrow-derived mesenchymal stem cells) is required to obtain sufficient quantities for clinical therapy. The BMSC confluence criteria used to determine passage and harvest timing vary widely, and the impact of confluence on BMSC properties remains controversial. The effects of confluence on BMSC properties were studied and confluence-associated markers were identified. METHODS: BMSC characteristics were analyzed as they grew from 50% to 100% confluence, including viability, population doubling time, apoptosis, colony formation, immunosuppression, surface marker expression, global gene expression and microRNA expression. In addition, culture supernatant protein, glucose, lactate and pH levels were analyzed. RESULTS: Confluence-dependent changes were detected in the expression of several cell surface markers: 39 culture supernatant proteins, 26 microRNAs and 2078 genes. Many of these surface markers, proteins, microRNAs and genes have been reported to be important in BMSC function. The pigment epithelium-derived factor/vascular endothelial growth factor ratio increased with confluence, but 80% and 100% confluent BMSCs demonstrated a similar level of immunosuppression of mixed lymphocyte reactions. In addition, changes in lactate and glucose levels correlated with BMSC density. CONCLUSIONS: BMSC characteristics change as confluence increases. 100% confluent BMSCs may have compromised pro-angiogenesis properties but may retain their immunomodulatory properties. Supernatant lactate and glucose levels can be used to estimate confluence and ensure consistency in passage and harvest timing. Flow cytometry or microRNA expression can be used to confirm that the BMSCs have been harvested at the appropriate confluence.

Bioinformatic approaches for the identification of serpin genes with multiple reactive site loop coding exons.

In several branches of the tree of life, alternative splicing of a single primary transcript may give rise to multiple serpin isoforms exhibiting different target enzyme specificities. Though the continuously increasing number of genome sequencing projects has been paralleled by a rapidly rising number of serpin genes, the full spectrum of isoforms that some of these genes can encode has often not been recognized in routine database searches. In this chapter, we introduce procedures that enable the systematic extraction of multi-isoform generating serpin genes from genomic sequences. Spot checking of a model organism demonstrates that the phyletic distribution of such genes appears to be largely underestimated. The bioinformatic approach presented here may help to dissect the complete antiproteolytic spectrum of a genome's serpin complement and to register the occurrence of multitasking serpin genes in eukaryotes for functional and evolutionary studies.