Faculty Bibliography

Glioblastoma multiforme (GBM) is a deadly primary brain malignancy. Glioblastoma stem cells (GSC), which have the ability to self-renew and differentiate into tumor lineages, are believed to cause tumor recurrence due to their resistance to current therapies. A subset of GSCs is marked by cell surface expression of CD133, a glycosylated pentaspan transmembrane protein. The study of CD133-expressing GSCs has been limited by the relative paucity of genetic tools that specifically target them. Here, we present CD133-LV, a lentiviral vector presenting a single chain antibody against CD133 on its envelope, as a vehicle for the selective transduction of CD133-expressing GSCs. We show that CD133-LV selectively transduces CD133+ human GSCs in dose-dependent manner and that transduced cells maintain their stem-like properties. The transduction efficiency of CD133-LV is reduced by an antibody that recognizes the same epitope on CD133 as the viral envelope and by shRNA-mediated knockdown of CD133. Conversely, the rate of transduction by CD133-LV is augmented by overexpression of CD133 in primary human GBM cultures. CD133-LV selectively transduces CD133-expressing cells in intracranial human GBM xenografts in NOD.SCID mice, but spares normal mouse brain tissue, neurons derived from human embryonic stem cells and primary human astrocytes. Our findings indicate that CD133-LV represents a novel tool for the selective genetic manipulation of CD133-expressing GSCs, and can be used to answer important questions about how these cells contribute to tumor biology and therapy resistance.

Cultured primary neurons are a well-established model for the study of neuronal function. Conventional stable isotope labeling with amino acids in cell culture (SILAC) requires nearly complete metabolic labeling of proteins and therefore is difficult to apply to cultured primary neurons, which do not divide in culture. Here we describe a protocol that utilizes a multiplex SILAC labeling strategy for primary cultured neurons. In this strategy, two different sets of heavy amino acids are used for labeling cells for the different experimental conditions. This allows for a straightforward SILAC quantitation using partially labeled cells because the two cell populations are always equally labeled.

The progranulin (PGRN) is known to protect regulatory T cells (Tregs) from a negative regulation by TNF-alpha, and its levels are elevated in various kinds of autoimmune diseases. Whether PGRN directly regulates the conversion of CD4+CD25-T cells into Foxp3-expressing regulatory T cells (iTreg), and whether PGRN affects the immunosuppressive function of Tregs, however, remain unknown. In this study we provide evidences demonstrating that PGRN is able to stimulate the conversion of CD4+CD25-T cells into iTreg in a dose-dependent manner in vitro. In addition, PGRN showed synergistic effects with TGF-beta1 on the induction of iTreg. PGRN was required for the immunosuppressive function of Tregs, since PGRN-deficient Tregs have a significant decreased ability to suppress the proliferation of effector T cells (Teff). In addition, PGRN deficiency caused a marked reduction in Tregs number in the course of inflammatory arthritis, although no significant difference was observed in the numbers of Tregs between wild type and PGRN deficient mice during development. Furthermore, PGRN deficiency led to significant upregulation of the Wnt receptor gene Fzd2. Collectively, this study reveals that PGRN directly regulates the numbers and function of Tregs under inflammatory conditions, and provides new insight into the immune regulatory mechanism of PGRN in the pathogenesis of inflammatory and immune-related diseases.

Presenilin 1 (PSEN1) encodes the catalytic subunit of gamma-secretase, and PSEN1 mutations are the most common cause of early onset familial Alzheimer's disease (FAD). In order to elucidate pathways downstream of PSEN1, we characterized neural progenitor cells (NPCs) derived from FAD mutant PSEN1 subjects. Thus, we generated induced pluripotent stem cells (iPSCs) from affected and unaffected individuals from two families carrying PSEN1 mutations. PSEN1 mutant fibroblasts, and NPCs produced greater ratios of Abeta42 to Abeta40 relative to their control counterparts, with the elevated ratio even more apparent in PSEN1 NPCs than in fibroblasts. Molecular profiling identified 14 genes differentially-regulated in PSEN1 NPCs relative to control NPCs. Five of these targets showed differential expression in late onset AD/Intermediate AD pathology brains. Therefore, in our PSEN1 iPSC model, we have reconstituted an essential feature in the molecular pathogenesis of FAD, increased generation of Abeta42/40, and have characterized novel expression changes.

Telomeres protect and cap linear chromosome ends, yet these genomic buffers erode over an organism's lifespan. Short telomeres have been associated with many age-related conditions in humans, and genetic mutations resulting in short telomeres in humans manifest as syndromes of precocious aging. In women, telomere length limits a fertilized egg's capacity to develop into a healthy embryo. Thus, telomere length must be reset with each subsequent generation. Although telomerase is purportedly responsible for restoring telomere DNA, recent studies have elucidated the role of alternative telomeres lengthening mechanisms in the reprogramming of early embryos and stem cells, which we review here.

A central problem in genetic epidemiology is to identify and rank genetic markers involved in a disease. Complex diseases, such as cancer, hypertension, diabetes, are thought to be caused by an interaction of a panel of genetic factors, that can be identified by markers, which modulate environmental factors. Moreover, the effect of each genetic marker may be small. Hence, the association signal may be missed unless a large sample is considered, or a priori biomedical data are used. Recent advances generated a vast variety of a priori information, including linkage maps and information about gene regulatory dependence assembled into curated pathway databases. We propose a genotype-based approach that takes into account linkage disequilibrium (LD) information between genetic markers that are in moderate LD while modeling gene-gene and gene-environment interactions. A major advantage of our method is that the observed genetic information enters a model directly thus eliminating the need to estimate haplotype-phase. Our approach results in an algorithm that is inexpensive computationally and does not suffer from bias induced by haplotype-phase ambiguity. We investigated our model in a series of simulation experiments and demonstrated that the proposed approach results in estimates that are nearly unbiased and have small variability. We applied our method to the analysis of data from a melanoma case-control study and investigated interaction between a set of pigmentation genes and environmental factors defined by age and gender. Furthermore, an application of our method is demonstrated using a study of Alcohol Dependence.