Gene delivery is the science of transferring genetic material into cells by means of a vector to alter cellular function or structure at a molecular level. In this context, a number of nucleic acid-based drugs have been proposed and experimented so far and, as they act on distinct steps along the gene transcription–translation pathway, specific delivery strategies are required to elicit the desired outcome. Cationic lipids and polymers, collectively known as non-viral delivery systems, have thus made their breakthrough in basic and medical research. Albeit they are promising alternatives to viral vectors, their therapeutic application is still rather limited as high transfection efficiencies are normally associated to adverse cytotoxic side effects. In this scenario, drawing inspiration from processes naturally occurring in vivo, major strides forward have been made in the development of more effective materials for gene delivery applications. Specifically, smart vectors sensitive to a variety of physiological stimuli such as cell enzymes, redox status, and pH are substantially changing the landscape of gene delivery by helping to overcome some of the systemic and intracellular barriers that viral vectors naturally evade. Herein, after summarizing the state-of-the-art information regarding the use of nucleic acids as drugs, we review the main bottlenecks still limiting the overall effectiveness of non-viral gene delivery systems. Finally, we provide a critical outline of emerging stimuli-responsive strategies and discuss challenges still existing on the road toward conceiving more efficient and safer multifunctional vectors.
Breast cancer is one of the most important causes of cancer-related deaths worldwide in women. In addition to gene expression studies, the progressing work in the miRNA area including miRNA microarray studies, brings new aspects to the research on the cancer development and progression. Microarray technology has been widely used to find new biomarkers in research and many transcriptomic microarray studies are available in public databases. In this study, the breast cancer miRNA and mRNA microarray studies were collected according to the availability of their data and clinical information, and combined by a newly developed ranking-based meta-analysis approach to find out candidate miRNA biomarkers (meta-miRNAs) that classify breast cancers according to their grades and explain the relation between miRNAs and mRNAs. This approach provided meta-miRNAs specific to breast cancer grades, pointing out let-7 family members as grade classifiers. The qRT-PCR studies performed with independent breast tumors confirmed the potential biomarker role of let-7 family members (meta-miRNAs). The concordance between the meta-mRNAs and miRNA target genes specific to tumor grade (common genes) supported the idea of mRNAs as miRNA targets. The pathway analysis results showed that most of the let-7 family miRNA targets, and also common genes, were significantly taking part in cancer-related pathways. The qRT-PCR studies, together with bioinformatic analyses, confirmed the results of meta-analysis approach, which is dynamic and allows combining datasets from different platforms.
β-globin gene disorders are the most prevalent inherited diseases worldwide and result from abnormal β-globin synthesis or structure. Novel therapeutic approaches are being developed in an effort to move beyond palliative management. Gene therapy, by ex vivo lentiviral transfer of a therapeutic β- globin gene derivative (β AT87Q - globin ) to hematopoietic stem cells, driven by cis-regulatory elements that confer high, erythroid-specific expression, has been evaluated in human clinical trials over the past 8 years. β AT87Q -globin is used both as a strong inhibitor of HbS polymerization and as a biomarker. While long-term studies are underway in multiple centers in Europe and in the United States, proof-of-principle of efficacy and safety has already been obtained in multiple patients with β-thalassemia and sickle cell disease.
Background: The Pregnancy-associated glycoproteins (PAGs) belong to a large family of aspartic peptidases expressed exclusively in the placenta of species in the Artiodactyla order. In cattle, the PAG gene family is comprised of at least 22 transcribed genes, as well as some variants. Phylogenetic analyses have shown that the PAG family segregates into 'ancient' and 'modern' groupings. Along with sequence differences between family members, there are clear distinctions in their spatio-temporal distribution and in their relative level of expression. In this report, 1) we performed an in silico analysis of the bovine genome to further characterize the PAG gene family, 2) we scrutinized proximal promoter sequences of the PAG genes to evaluate the evolution pressures operating on them and to identify putative regulatory regions, 3) we determined relative transcript abundance of selected PAGs during pregnancy and, 4) we performed preliminary characterization of the putative regulatory elements for one of the candidate PAGs, bovine (bo) PAG-2. Results: From our analysis of the bovine genome, we identified 18 distinct PAG genes and 14 pseudogenes. We observed that the first 500 base pairs upstream of the translational start site contained multiple regions that are conserved among all boPAGs. However, a preponderance of conserved regions, that harbor recognition sites for putative transcriptional factors (TFs), were found to be unique to the modern boPAG grouping, but not the ancient boPAGs. We gathered evidence by means of Q-PCR and screening of EST databases to show that boPAG-2 is the most abundant of all boPAG transcripts. Finally, we provided preliminary evidence for the role of ETS- and DDVL-related TFs in the regulation of the boPAG-2 gene. Conclusion: PAGs represent a relatively large gene family in the bovine genome. The proximal promoter regions of these genes display differences in putative TF binding sites, likely contributing to observed differences in spatial and temporal expression. We also discovered that boPAG-2 is the most abundant of all boPAG transcripts and provided evidence for the role of ETS and DDVL TFs in its regulation. These experiments mark the crucial first step in discerning the complex transcriptional regulation operating within the boPAG gene family.
We have developed a simple and highly efficient method to disrupt chromosomal genes in Escherichia coli in which PCR primers provide the homology to the targeted gene(s). In this procedure, recombination requires the phage λ Red recombinase, which is synthesized under the control of an inducible promoter on an easily curable, low copy number plasmid. To demonstrate the utility of this approach, we generated PCR products by using primers with 36- to 50-nt extensions that are homologous to regions adjacent to the gene to be inactivated and template plasmids carrying antibiotic resistance genes that are flanked by FRT (FLP recognition target) sites. By using the respective PCR products, we made 13 different disruptions of chromosomal genes. Mutants of the arcB, cyaA, lacZYA, ompR-envZ, phnR, pstB, pstCA, pstS, pstSCAB-phoU, recA, and torSTRCAD genes or operons were isolated as antibiotic-resistant colonies after the introduction into bacteria carrying a Red expression plasmid of synthetic (PCR-generated) DNA. The resistance genes were then eliminated by using a helper plasmid encoding the FLP recombinase which is also easily curable. This procedure should be widely useful, especially in genome analysis of E. coli and other bacteria because the procedure can be done in wild-type cells.
Fire blight is a destructive bacterial disease caused by affecting plants in the family Rosaceae, including apple. Host resistance to fire blight is present mainly in accessions of spp. and is thought to be quantitative in this pathosystem. In this study we analyzed the importance of the effector , a homolog of , for resistance of × 5 (Mr5). The deletion mutant Ea1189Δ was able to overcome the fire blight resistance of Mr5. One single nucleotide polymorphism (SNP), resulting in an exchange of cysteine to serine in the encoded protein, was detected in of several strains differing in virulence to Mr5. strains encoding serine (S-allele) were able to overcome resistance of Mr5, whereas strains encoding cysteine (C-allele) were not. Allele specificity was also observed in a coexpression assay with RIN4 in . A homolog of RIN4 has been detected and isolated in Mr5. These results suggest a system similar to the interaction of RPS2 from and AvrRpt2 from with RIN4 as guard. Our data are suggestive of a gene-for-gene relationship for the host–pathogen system Mr5 and .
Following the identification of several disease-associated polymorphisms by genome-wide association (GWA) analysis, interest is now focusing on the detection of effects that, owing to their interaction with other genetic or environmental factors, might not be identified by using standard single-locus tests. In addition to increasing the power to detect associations, it is hoped that detecting interactions between loci will allow us to elucidate the biological and biochemical pathways that underpin disease. Here I provide a critical survey of the methods and related software packages currently used to detect the interactions between genetic loci that contribute to human genetic disease. I also discuss the difficulties in determining the biological relevance of statistical interactions.
Summary Verticillium wilt (VW), caused by soil‐borne fungi of the genus Verticillium, is a serious disease affecting a wide range of plants and leading to a constant and major challenge to agriculture worldwide. Cotton (Gossypium hirsutum) is the world's most important natural textile fibre and oil crop. VW of cotton is a highly devastating vascular disease; however, few resistant germplasms have been reported in cotton. An increasing number of studies have shown that RNA interference (RNAi)‐based host‐induced gene silencing (HIGS) is an effective strategy for improving plant resistance to pathogens by silencing genes essential for the pathogenicity of these pathogens. Here, we have identified and characterized multifunctional regulators of G protein signalling (RGS) in the Verticillium dahliae virulence strain, Vd8. Of eight VdRGS genes, VdRGS1 showed the most significant increase in expression in V. dahliae after treating with the roots of cotton seedlings. Based on the phenotype detection of VdRGS1 deletion and complementation mutants, we found that VdRGS1 played crucial roles in spore production, hyphal development, microsclerotia formation and pathogenicity. Tobacco rattle virus‐mediated HIGS in cotton plants silenced VdRGS1 transcripts in invaded V. dahliae strains and enhanced broad‐spectrum resistance to cotton VW. Our data demonstrate that VdRGS1 is a conserved and essential gene for V. dahliae virulence. HIGS of VdRGS1 provides effective control against V. dahliae infection and could obtain the durable disease resistance in cotton and in other VW‐susceptible host crops by developing the stable transformants.
Multiple genes, gene-by-gene interactions, and gene-by-environment interactions are believed to underlie most complex diseases. However, such interactions are difficult to identify. Although there have been recent successes in identifying genetic variants for complex diseases, it still remains difficult to identify gene-gene and gene-environment interactions. To overcome this difficulty, we propose a forest-based approach and a concept of variable importance. The proposed approach is demonstrated by simulation study for its validity and illustrated by a real data analysis for its use. Analyses of both real data and simulated data based on published genetic models show the effectiveness of our approach. For example, our analysis of a published data set on age-related macular degeneration (AMD) not only confirmed a known genetic variant (P value = 2E-6) for AMD, but also revealed an unreported haplotype surrounding single-nucleotide polymorphism (SNP) rs10272438 on chromosome 7 that was significantly associated with AMD (P value = 0.0024). These significance levels are obtained after the consideration for a large number of SNPs. Thus, the importance of this work is twofold: it proposes a powerful and flexible method to identify high-risk haplotypes and their interactions and reveals a potentially protective variant for AMD.