Correction of murine SCID-X1 by lentiviral gene therapy using a codon-optimized IL2RG gene and minimal pretransplant conditioning

Clinical trials have demonstrated the potential of ex vivo hematopoietic stem cell gene therapy to treat X-linked severe combined immunodeficiency (SCID-X1) using γ-retroviral vectors, leading to immune system functionality in the majority of treated patients without pretransplant conditioning. The success was tempered by insertional oncogenesis in a proportion of the patients. To reduce the genotoxicity risk, a self-inactivating (SIN) lentiviral vector (LV) with improved expression of a codon optimized human interleukin-2 receptor γ gene (IL2RG) cDNA (coγc), regulated by its 1.1 kb promoter region (γcPr), was compared in efficacy to the viral spleen focus forming virus (SF) and the cellular phosphoglycerate kinase (PGK) promoters. Pretransplant conditioning of Il2rg-/-mice resulted in long-term reconstitution of T and B lymphocytes, normalized natural antibody titers, humoral immune responses, ConA/IL-2 stimulated spleen cell proliferation, and polyclonal T-cell receptor gene rearrangements with a clear integration preference of the SF vector for proto-oncogenes, contrary to the PGK and γcPr vectors. We conclude that SIN lentiviral gene therapy using coγc driven by the γcPr or PGK promoter corrects the SCID phenotype, potentially with an improved safety profile, and that low-dose conditioning proved essential for immune competence, allowing for a reduced threshold of cell numbers required

Web-Based Arabidopsis Functional and Structural Genomics Resources

As plant research moves to a “post-genomic” era, many diverse internet resources become available to the international research community. Arabidopsis thaliana, because of its small size, rapid life cycle and simple genome, has been a model system for decades, with much research funding and many projects devoted to creation of functional and structural genomics resources. Different types of data, including genome, transcriptome, proteome, phenome, metabolome and ionome are stored in these resources. In this chapter, a variety of genomics resources are introduced, with simple descriptions of how some can be accessed by laboratory researchers via the internet