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Michael Bittner

Publications and source records attributed to Michael Bittner.

11 recordsLinked to original sources
PubMed2005

Multiplexed DNA sequencing-by-synthesis.

We report a new DNA sequencing-by-synthesis method in which the sequences of DNA templates, hybridized to a surface-immobilized array of DNA primers, are determined by sensing the number of nucleotides by which the primers in each array spot are extended in sequential DNA polymerase-catalyzed nucleotide incorporation reactions, each with a single fluorescein-labeled deoxyribonucleoside triphosphate (dNTP) species. The fluorescein label is destroyed after each readout by a photostimulated reaction with diphenyliodonium chloride. A DNA polymerase with enhanced ability to incorporate, and to extend beyond, modified nucleotides is used. Self-quenching of adjacent fluorescein labels, which impedes readout of homopolymeric runs, is avoided by diluting the labeled dNTP with unlabeled reagent. Misincorporation effects have been quantified and are small; however, low-level contamination of dNTPs with other nucleotides mimics misincorporation and can produce significant false-positive signals. These impurities are removed by polymerase-catalyzed incorporation into complementary "cleaning duplexes." Here, we demonstrate the accurate sequence readout for a small array of known DNA templates, the ability to quantify homopolymeric runs, and a short sequencing example of sections of the wild-type and mutant BRCA1 gene. For a 20,000-spot array, readout rates in excess of 6000 bases per minute are projected.

Amino Acid Sequence↗
PubMed2004

A Bayesian connectivity-based approach to constructing probabilistic gene regulatory networks.

MOTIVATION: We have hypothesized that the construction of transcriptional regulatory networks using a method that optimizes connectivity would lead to regulation consistent with biological expectations. A key expectation is that the hypothetical networks should produce a few, very strong attractors, highly similar to the original observations, mimicking biological state stability and determinism. Another central expectation is that, since it is expected that the biological control is distributed and mutually reinforcing, interpretation of the observations should lead to a very small number of connection schemes. RESULTS: We propose a fully Bayesian approach to constructing probabilistic gene regulatory networks (PGRNs) that emphasizes network topology. The method computes the possible parent sets of each gene, the corresponding predictors and the associated probabilities based on a nonlinear perceptron model, using a reversible jump Markov chain Monte Carlo (MCMC) technique, and an MCMC method is employed to search the network configurations to find those with the highest Bayesian scores to construct the PGRN. The Bayesian method has been used to construct a PGRN based on the observed behavior of a set of genes whose expression patterns vary across a set of melanoma samples exhibiting two very different phenotypes with respect to cell motility and invasiveness. Key biological features have been faithfully reflected in the model. Its steady-state distribution contains attractors that are either identical or very similar to the states observed in the data, and many of the attractors are singletons, which mimics the biological propensity to stably occupy a given state. Most interestingly, the connectivity rules for the most optimal generated networks constituting the PGRN are remarkably similar, as would be expected for a network operating on a distributed basis, with strong interactions between the components.

Algorithms↗
PubMed2004

Generation and analysis of melanoma SAGE libraries: SAGE advice on the melanoma transcriptome.

In this study, we generated three SAGE libraries from melanoma tissues. Using bioinformatics tools usually applied to microarray data, we identified several genes, including novel transcripts, which are preferentially expressed in melanoma. SAGE results converged with previous microarray analysis on the importance of intracellular calcium and G-protein signaling, and the Wnt/Frizzled family. We also examined the expression of CD74, which was specifically, albeit not abundantly, expressed in the melanoma libraries using a melanoma progression tissue microarray, and demonstrate that this protein is expressed by melanoma cells but not by benign melanocytes. Many genes involved in intracellular calcium and G-protein signaling were highly expressed in melanoma, results we had observed earlier from microarray studies (Bittner et al., 2000). One of the genes most highly expressed in our melanoma SAGE libraries was a calcium-regulated gene, calpain 3 (p94). Immunohistochemical analysis demonstrated that calpain 3 moves from the nuclei of non-neoplastic cells to the cytoplasm of malignant cells, suggesting activation of this intracellular proteinase. Our SAGE results and the clinical validation data demonstrate how SAGE profiles can highlight specific links between signaling pathways as well as associations with tumor progression. This may provide insights into new genes that may be useful for the diagnosis and therapy of melanoma.

Aged↗
PubMed2003

Functional genomics as a window on radiation stress signaling.

Exposure to ionizing radiation, as well as other stresses, results in the activation of complex signal transduction pathways, which eventually shape the response of cells and organisms. Some of the important pathways responding to radiation include the ATM/P53 pathway, MAPK cascades and NF-kappaB activation, as well as signaling events initiated at the cell membrane and within the cytoplasm. Alterations in gene expression play roles both as intermediaries in signaling and as downstream effector genes. Differences in cell type, interindividual genetic differences and crosstalk occurring between signaling pathways may help to channel radiation stress signals between cell cycle delay, enhanced DNA repair, and apoptosis. These differences may in turn help determine the likelihood of late effects of radiation exposure, including carcinogenesis and fibrosis. The tools of the postgenomic era enable high-throughput studies of the multiple changes resulting from the interplay of radiation signaling pathways. Gene expression profiling, in particular shows great promise, both in terms of insight into basic molecular mechanisms and for the future hope of biomarker development and individual tailoring of cancer therapy.

Animals↗
PubMed2003

Gene-expression profiling in human cutaneous melanoma.

Genomic technology presents new and exciting opportunities to study complex human diseases. Several types of genomic analysis are helping to elucidate the biology of important human cancers. One of these, gene expression profiling, provides a more comprehensive view of the consequences of the genetic changes in cancer cells than was previously available. In addition to detailing the expression patterns of thousands of genes simultaneously, this exploding field of research has begun to build a new 'molecular taxonomy' of cancer and to identify novel disease genes for many human cancers, including cutaneous melanoma. Whether this new information will lead to improved treatments and prolonged survival for cancer patients remains to be determined. Here, we review the use of complementary DNA microarray technology to study gene expression patterns in cutaneous melanoma and highlight recent advances concerning the identification of novel melanoma disease-related genes. The fundamentals of microarray technology and analysis have been extensively discussed, and readers are referred to several recent reviews in this area.

Antineoplastic Agents↗
PubMed2002

Mutation of melanosome protein RAB38 in chocolate mice.

Mutations of genes needed for melanocyte function can result in oculocutaneous albinism. Examination of similarities in human gene expression patterns by using microarray analysis reveals that RAB38, a small GTP binding protein, demonstrates a similar expression profile to melanocytic genes. Comparative genomic analysis localizes human RAB38 to the mouse chocolate (cht) locus. A G146T mutation occurs in the conserved GTP binding domain of RAB38 in cht mice. Rab38(cht)/Rab38(cht) mice exhibit a brown coat similar in color to mice with a mutation in tyrosinase-related protein 1 (Tyrp1), a mouse model for oculocutaneous albinism. The targeting of TYRP1 protein to the melanosome is impaired in Rab38(cht)/Rab38(cht) melanocytes. These observations, and the fact that green fluorescent protein-tagged RAB38 colocalizes with end-stage melanosomes in wild-type melanocytes, suggest that RAB38 plays a role in the sorting of TYRP1. This study demonstrates the utility of expression profile analysis to identify mammalian disease genes.

Animals↗
PubMed2002

Wnt5a signaling directly affects cell motility and invasion of metastatic melanoma.

Gene expression profiling identified human melanoma cells demonstrating increased cell motility and invasiveness. The gene WNT5A best determined in vitro invasive behavior. Melanoma cells were transfected with vectors constitutively overexpressing Wnt5a. Consistent changes included actin reorganization and increased cell adhesion. No increase in beta-catenin expression or nuclear translocation was observed. There was, however, a dramatic increase in activated PKC. In direct correlation with Wnt5a expression and PKC activation, there was an increase in melanoma cell invasion. Blocking this pathway using antibodies to Frizzled-5, the receptor for Wnt5a, inhibited PKC activity and cellular invasion. Furthermore, Wnt5a expression in human melanoma biopsies directly correlated to increasing tumor grade. These observations support a role for Wnt5a in human melanoma progression.

Actins↗
PubMed2002

Inference from clustering with application to gene-expression microarrays.

There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different underlying classes, whereas those in the same cluster come from the same class. Stochastically, the underlying classes represent different random processes. The inference is that clusters represent a partition of the sample points according to which process they belong. This paper discusses a model-based clustering toolbox that evaluates cluster accuracy. Each random process is modeled as its mean plus independent noise, sample points are generated, the points are clustered, and the clustering error is the number of points clustered incorrectly according to the generating random processes. Various clustering algorithms are evaluated based on process variance and the key issue of the rate at which algorithmic performance improves with increasing numbers of experimental replications. The model means can be selected by hand to test the separability of expected types of biological expression patterns. Alternatively, the model can be seeded by real data to test the expected precision of that output or the extent of improvement in precision that replication could provide. In the latter case, a clustering algorithm is used to form clusters, and the model is seeded with the means and variances of these clusters. Other algorithms are then tested relative to the seeding algorithm. Results are averaged over various seeds. Output includes error tables and graphs, confusion matrices, principal-component plots, and validation measures. Five algorithms are studied in detail: K-means, fuzzy C-means, self-organizing maps, hierarchical Euclidean-distance-based and correlation-based clustering. The toolbox is applied to gene-expression clustering based on cDNA microarrays using real data. Expression profile graphics are generated and error analysis is displayed within the context of these profile graphics. A large amount of generated output is available over the web.

Computational Biology↗
PubMed2002

Stress-gene induction by low-dose gamma irradiation.

Using a human myeloid tumor cell line (ML-1), we detected induction of mRNA expression of several stress-responsive genes by doses of gamma rays as low as 2 cGy. For instance, the dose response for induction of CIP1/WAF1 and GADD45 appears to be linear over the range of 2 to 50 cGy and shows no evidence of a threshold for induction. Although 2 and 5 cGy exposures did not result in any detectable reduction in cloning efficiency nor in increased apoptosis in ML-1 cells, these exposures did produce a brief cell-cycle delay. We also used fluorescent cDNA microarray hybridization to investigate transcriptional stress responses following low doses of gamma rays and to identify additional radiation-responsive genes for inclusion in a stress-specific microarray we are developing. These studies provide insight into the molecular responses to physiologically relevant doses, which cannot necessarily be extrapolated from high-dose studies. The use of high throughput arrays will allow the identification of multiple stress-responsive genes that are radiation inducible in a variety of cell types and tissues. The expectation is that transcriptional stress responses will provide a molecular approach to monitoring for radiation exposure and detecting interindividual differences.

Gamma Rays↗
PubMedDate not supplied

Effects of HIV-1 Nef on cellular gene expression profiles.

The early human immunodeficiency virus (HIV) accessory protein Nef makes an important contribution to virulence, but the mechanisms by which Nef influences pathogenesis remain unclear. Many well-studied effects of Nef, like CD4 and class I MHC downregulation, occur posttranslationally. However, Nef has the potential to affect gene expression by interfering with cell signaling pathways and by virtue of structural features such as the Pro-X-X-Pro motif, which may interact with src homology region-3 domains of src-like kinases. We used a cDNA microarray screening strategy to identify cellular genes whose steady state transcriptional levels may be affected by Nef. We generated HeLa cell lines expressing wild-type or mutant HIV-1 nef protein sequences. Using cDNA microarray technology, we compared the patterns of cellular gene expression in the various cell lines to the pattern in non-Nef-expressing HeLa cells. By matching the patterns of cellular gene expression in HeLa cell lines expressing various Nefs with that of parental HeLa cells, we identified several cellular genes whose expression was modulated differentially by Nef and its mutants. We confirmed the differential expression of selected genes by RNA filter blotting. Genes expressed at higher levels included proteases, transcription factors, protein kinases, nuclear import/export proteins, adaptor molecules and cyclins, some of which have previously been implicated as being important for HIV replication and pathogenesis. The results indicate that Nef expression can alter the expression of cellular genes and suggest that this alteration in cellular gene expression may serve to optimize the cell to support the subsequent stages of viral replication.

Gene Expression↗