RESUMEN
Dopamine, an adhesive protein can be covalently deposited onto biomaterials. In this study, we evaluated the ability of dopamine-coated surfaces for small interfering RNA (siRNA) immobilization and release. Dopamine was deposited onto 316L stainless steel discs either as a monolayer at acidic pH or as polydopamine at alkaline pH, following which siRNA was immobilized onto these discs. To investigate the RNA interference ability of immobilized siRNA, reduction of luciferase expression in HeLa, and reduction of Egr-1 expression and cell proliferation in human aortic smooth muscle cells (HAoSMCs) were determined. Dopamine treatment of 316L stainless steel discs under both the acidic and alkaline conditions resulted in the deposition of amino (NH2) groups, which enabled electrostatic immobilization of siRNA. The immobilized siRNA was released from both types of coatings, and enhanced the percent suppression of firefly luciferase activity of HeLa significantly up to ~96.5% compared to HeLa on non-dopamine controls (18%). Both the release of siRNA and the percent suppression of firefly luciferase activity were sustained for at least 7 days. In another set of experiments, siRNA sequences targeting to inhibit the activity of the transcription factor Egr-1 were eluted from dopamine-coated surfaces to HAoSMCs. Egr-1 siRNA eluted from dopamine-coated surfaces, significantly reduced the proliferation of HAoSMCs and their protein expression of Egr-1. Therefore, this method of surface immobilization of siRNA onto dopamine-coated surfaces might be effective for nucleic acid delivery from stents.
Asunto(s)
Dopamina/química , ARN Interferente Pequeño/administración & dosificación , Acero Inoxidable , Células HeLa , Humanos , Propiedades de SuperficieRESUMEN
Hydrophobins are small proteins, characterised by the presence of eight positionally conserved cysteine residues, and are present in all filamentous asco- and basidiomycetes. They are found on the outer surfaces of cell walls of hyphae and conidia, where they mediate interactions between the fungus and the environment. Hydrophobins are conventionally grouped into two classes (class I and II) according to their solubility in solvents, hydropathy profiles and spacing between the conserved cysteines. Here we describe a novel set of hydrophobins from Trichoderma spp. that deviate from this classification in their hydropathy, cysteine spacing and protein surface pattern. Phylogenetic analysis shows that they form separate clades within ascomycete class I hydrophobins. Using T. atroviride as a model, the novel hydrophobins were found to be expressed under conditions of glucose limitation and to be regulated by differential splicing.
Asunto(s)
Proteínas Fúngicas/clasificación , Trichoderma/genética , Secuencia de Aminoácidos , Ascomicetos/genética , Cisteína/química , Cisteína/genética , Cisteína/metabolismo , Evolución Molecular , Proteínas Fúngicas/química , Proteínas Fúngicas/genética , Proteínas Fúngicas/metabolismo , Glucosa/metabolismo , Hypocrea/química , Hypocrea/genética , Hypocrea/metabolismo , Datos de Secuencia Molecular , Filogenia , Empalme de Proteína , Alineación de Secuencia , Solubilidad , Espectrometría de Masa por Láser de Matriz Asistida de Ionización Desorción , Trichoderma/química , Trichoderma/metabolismoRESUMEN
BACKGROUND: Phylogenetic analysis can be used to divide a protein family into subfamilies in the absence of experimental information. Most phylogenetic analysis methods utilize multiple alignment of sequences and are based on an evolutionary model. However, multiple alignment is not an automated procedure and requires human intervention to maintain alignment integrity and to produce phylogenies consistent with the functional splits in underlying sequences. To address this problem, we propose to use the alignment-free Relative Complexity Measure (RCM) combined with reduced amino acid alphabets to cluster protein families into functional subtypes purely on sequence criteria. Comparison with an alignment-based approach was also carried out to test the quality of the clustering. RESULTS: We demonstrate the robustness of RCM with reduced alphabets in clustering of protein sequences into families in a simulated dataset and seven well-characterized protein datasets. On protein datasets, crotonases, mandelate racemases, nucleotidyl cyclases and glycoside hydrolase family 2 were clustered into subfamilies with 100% accuracy whereas acyl transferase domains, haloacid dehalogenases, and vicinal oxygen chelates could be assigned to subfamilies with 97.2%, 96.9% and 92.2% accuracies, respectively. CONCLUSIONS: The overall combination of methods in this paper is useful for clustering protein families into subtypes based on solely protein sequence information. The method is also flexible and computationally fast because it does not require multiple alignment of sequences.