A cellular cleavage pathway for the Moloney murine leukemia virus precursor protein, Pr65$\rm\sp{gag}$: Identification of a new viral protein containing CAp30 and NCp10 sequences

The origin and structure of P55$\sp{\rm gag},$ a gag encoded polyprotein lacking the nucleocapsid protein, NCp10, have been explored. Evidence shows that P55$\sp{\rm gag}$ is formed by non-viral proteolytic cleavage of the Moloney murine leukemia virus (MoMuLV)gag precursor protein, Pr65$\sp{\rm gag}.$ P55$\sp{\rm gag}$ is produced in cells infected by a viral protease deletion mutant and by a recombinant murine sarcoma virus known to lack the protease gene, implying that a cellular protease is responsible for the cleavage. Structural and immunological studies show that the protein cleavage site is upstream of the CAp30-NCp10 viral proteolytic junction, implying that P55$\sp{\rm gag}$ lacks the carboxy-terminal residues of CAp30. During the course of studying P55$\sp{\rm gag},$ another protein was discovered, which I named nucleocapsid-related protein(NCRP). NCRP possesses the portion of CAp30 that is lacking in P55$\sp{\rm gag}.$ NCRP possesses antigenic epitopes present in CAp30 and NCp10. NCRP was observed in virus lysates and in nuclear lysates of MoMuLV infected cells; it was not detected in the cytoplasmic fractions of MoMuLV infected cells. Our results indicated that NCRP originates from Pr65$\sp{\rm gag},$ resulting from the same cellular proteolytic cleavage event that produces the viral cellular protein P55$\sp{\rm gag}.$ P55$\sp{\rm gag}$- and NCRP-like proteins also were observed in AKV murine leukemia virus (AKV MuLV) and feline leukemia virus (FeLV) infected cells and in their respective virus particles. The site of cleavage that yields P55$\sp{\rm gag}$ and NCRP is within the carboxy terminus of CAp30, likely within a motif highly conserved among mammalian type C retroviruses. This new motif, called the capsid conserved motif (CCM), overlaps a region containing both a possible bipartite nuclear targeting sequence and a region homologous with the U1 small nuclear ribonucleoprotein 70-kD protein. This domain, when intact, may act as a nuclear targeting sequence for the gag precursor proteins Pr65$\sp{\rm gag}$ and CAp30. Nuclei of cells infected with MoMuLV were examined for the presence of gag proteins. Both Pr65$\sp{\rm gag}$ and CAp30 were detected in the nuclear fraction of MoMuLV, AKV MuLV and FeLV infected cells. P55$\sp{\rm gag}$ was never detected in the nucleus of MoMuLV, AKV MuLV and FeLV infected cells or in their respective virus particles. I propose that NCRP may be involved in sequestering viral genomic RNA for the purposes of encapsidation and intracellular viral genomic RNA dimerization. ^

Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^

HUMAN PROPHASE CHROMOSOME UNIQUE BAND SEQUENCES; DEFINITION, CHARACTERIZATION, AND APPLICATION (CYTOGENETICS, IMAGE PROCESSING)

Extensive experience with the analysis of human prophase chromosomes and studies into the complexity of prophase GTG-banding patterns have suggested that at least some prophase chromosomal segments can be accurately identified and characterized independently of the morphology of the chromosome as a whole. In this dissertation the feasibility of identifying and analyzing specified prophase chromosome segments was thus investigated as an alternative approach to prophase chromosome analysis based on whole chromosome recognition. Through the use of prophase idiograms at the 850-band-stage (FRANCKE, 1981) and a comparison system based on the calculation of cross-correlation coefficients between idiogram profiles, we have demonstrated that it is possible to divide the 24 human prophase idiograms into a set of 94 unique band sequences. Each unique band sequence has a banding pattern that is recognizable and distinct from any other non-homologous chromosome portion.^ Using chromosomes 11p and 16 thru 22 to demonstrate unique band sequence integrity at the chromosome level, we found that prophase chromosome banding pattern variation can be compensated for and that a set of unique band sequences very similar to those at the idiogram level can be identified on actual chromosomes.^ The use of a unique band sequence approach in prophase chromosome analysis is expected to increase efficiency and sensitivity through more effective use of available banding information. The use of a unique band sequence approach to prophase chromosome analysis is discussed both at the routine level by cytogeneticists and at an image processing level with a semi-automated approach to prophase chromosome analysis. ^

Non B-DNA structures and genomic instability associated with myotonic dystrophy type 2 (CCTG).(CAGG) repeats

There are many diseases associated with the expansion of DNA repeats in humans. Myotonic dystrophy type 2 is one of such diseases, characterized by expansions of a (CCTG)•(CAGG) repeat tract in intron 1 of zinc finger protein 9 (ZNF9) in chromosome 3q21.3. The DM2 repeat tract contains a flanking region 5' to the tract that consists of a polymorphic repetitive sequence (TG)14-25(TCTG)4-11(CCTG) n. The (CCTG)•(CAGG) repeat is typically 11-26 repeats in persons without the disease, but can expand up to 11,000 repeats in affected individuals, which is the largest expansion seen in DNA repeat diseases to date. This DNA tract remains one of the least characterized disease-associated DNA repeats, and mechanisms causing the repeat expansion in humans have yet to be elucidated. Alternative, non B-DNA structures formed by the expanded repeats are typical in DNA repeat expansion diseases. These sequences may promote instability of the repeat tracts. I determined that slipped strand structure formation occurs for (CCTG)•(CAGG) repeats at a length of 42 or more. In addition, Z-DNA structure forms in the flanking human sequence adjacent to the (CCTG)•(CAGG) repeat tract. I have also performed genetic assays in E. coli cells and results indicate that the (CCTG)•(CAGG) repeats are more similar to the highly unstable (CTG)•(CAG) repeat tracts seen in Huntington's disease and myotonic dystrophy type 1, than to those of the more stable (ATTCT)•(AGAAT) repeat tracts of spinocerebellar ataxia type 10. This instability, however, is RecA-independent in the (CCTG)•(CAGG) and (ATTCT)•(AGAAT) repeats, whereas the instability is RecA-dependent in the (CTG)•(CAG) repeats. Structural studies of the (CCTG)•(CAGG) repeat tract and the flanking sequence, as well as genetic selection assays may reveal the mechanisms responsible for the repeat instability in E. coli, and this may lead to a better understanding of the mechanisms contributing to the human disease state. ^

An exploratory analysis of variance and volatility in epileptic electroencephalograms

The electroencephalogram (EEG) is a physiological time series that measures electrical activity at different locations in the brain, and plays an important role in epilepsy research. Exploring the variance and/or volatility may yield insights for seizure prediction, seizure detection and seizure propagation/dynamics.^ Maximal Overlap Discrete Wavelet Transforms (MODWTs) and ARMA-GARCH models were used to determine variance and volatility characteristics of 66 channels for different states of an epileptic EEG – sleep, awake, sleep-to-awake and seizure. The wavelet variances, changes in wavelet variances and volatility half-lives for the four states were compared for possible differences between seizure and non-seizure channels.^ The half-lives of two of the three seizure channels were found to be shorter than all of the non-seizure channels, based on 95% CIs for the pre-seizure and awake signals. No discernible patterns were found the wavelet variances of the change points for the different signals. ^