The purpose of this study is to determine if African American Women (AAW) with low fitness levels have low fitness related to a lifestyle choice of decreased physical activity (PA) or the cardiovascular disadvantage of greater proportion of Type II (FT) muscle fibers. Forty-eight apparently healthy AAW participated in the study. The women had no known risk factors for CVD; were sedentary (no structured fitness training program within last six months) or minimally fit (PA ≤ 3 x week for 20 minutes); and were not taking any prescription medications for blood pressure, diabetes, or lipid control. On the first visit the following measurements were taken: 1.) height and weight (electronic scale and stadiometer); 2.) body fat percentage (dual energy x-ray absorptiometry (DXA % body fat); and 3.) CRF (submaximal treadmill exercise test). On the second visit additional measurements included: 1.) blood pressure (stethoscope and sphygmomanometer); 2.) lipid profile and high sensitivity-C reactive protein (hs-CRP) (Cholestech LDX analyzer); 3.) thigh anthropometric measurements; 4.) isokinetic power and fatigue testing (KIN-COM dynamometer). Pearson product correlation coefficient (r) was used to analyze the relationship between the variables. The results indicated that gross oxygen consumption at 85% maximal heart rate (VO2) was not significantly related to PA (r = -.06, p = .67) or FT fibers (r = 0.14, p = 0.34). VO2 was negatively correlated with hs-CRP (r = -.31, p < 0.05), systolic blood pressure (r = -0.47, p < 0.01), diastolic blood pressure (r = -0.42, p < 0.01), and DXA % body fat (r = -0.64, p < 0.01). There were no significant relationships between PA and any of the variables. FT fibers were negatively correlated with low density lipoprotein (r = -0.30, p < 0.05) and DXA % body fat (r = -0.46, p < 0.01). In conclusion, low cardiorespiratory fitness in AAW does not seem to be a related to reported levels of PA or proportion of FT fibers. This suggests that there may be other factors that are contributing to the low levels of cardiorespiratory fitness observed in this sample of AAW.

<p>These studies are based on the isolation of ë replication defective mutants that had acquired multiple point mutations within ë replication initiation genes O and P in a cryptic prophage (Hayes et al., 1998). Each mutant cell arose after shifting wild type cells with a cI[Ts] cryptic ë prophage deleted for int-kil, and from ren into E. coli, from 30oC to 42oC. Derepression of the trapped cryptic prophage kills the host cells (designated as RK+). Rare colony forming units survive and were designated as RK- mutants. This led to a hypothesis that ë replication-triggered cell stress provokes mutator activity, i.e., increases the frequency of replication errors within the simultaneously replicating chromosome of the host E. coli cells. We tested this hypothesis by asking three questions: (1) Do unselected, untargeted (with no link to ë fragment) auxotrophic mutations appear within the RK- mutant population selected from RK+ culture cells? (2) Is replication initiation from the cryptic ë fragment, or, alternatively, just expression of one or more ë genes required for the appearance of the unselected auxotrophic mutations? (3) Do E. coli functions participate in the appearance of unselected auxotrophic mutations within the RK- mutant population? Our results indicate that auxotrophic mutations unlinked to the ë fragment appeared at high frequency within RK- mutants. RK- auxotrophs arising on rich medium were identified by screening the survivor clones for growth on minimal medium. The appearance of RK- auxotrophic colonies at high frequency (>1 per 100 RK- mutants) leads us to conclude that auxotrophic mutations arise during the independent selection for RK- mutants. Conditions that inhibited ë fragment induction fully suppressed the mutator phenotype. Mutation of host dnaB such that the helicase does not support replication initiation from the induced ë fragment completely suppressed host cell killing, but not the appearance of auxotrophic mutations. We asked if E. coli error-prone polymerases IV and V, or gene functions regulated as part of the host SOS response contributed to the provoked mutator phenotype and observed no close correlation. We demonstrated that the RK+ starting cells did not have a distinct intrinsic mutator activity in several ways, including moving the cryptic ë fragment to different E. coli host cells, blocking ë fragment induction by the addition of a cI+ plasmid to eliminate ë gene expression at high temperatures, and independent assays for spontaneous rifampicin resistance. We found that the induced mutator phenotype associated with the appearance of untargeted auxotrophs was linked to the expression of lambda gene P, and did not require replication initiation from the cryptic ë prophage. We also found that the mutator phenotype of the induced cryptic ë fragment increased the frequency of rifampicin resistant colonies among the RK- mutant population. </p>

Recent advances in DNA sequencing technology have enabled entire genomes to be sequenced quickly and accurately, resulting in an exponential increase in the number of organisms whose genome sequences have been elucidated. While the genome sequence of a given organism represents an important starting point in understanding its physiology, the functions of the protein products of many genes are still unknown; as such, computational methods for studying protein function are becoming increasingly important. In addition, this wealth of genomic information has created an unprecedented opportunity to compare the protein content of different organisms; among other applications, this can enable us to improve taxonomic classifications, to develop more accurate diagnostic tests for identifying particular bacteria, and to better understand protein content relationships in both closely-related and distantly-related organisms.<p> This thesis describes the design, evaluation, and use of a program called Proteome Subtraction and Intersection (PSI) that uses an idea called genome subtraction for discovering protein-phenotype relationships and for characterizing differences in protein content in groups of organisms. PSI takes as input a set of proteomes, as well as a partitioning of that set into a subset of "included" proteomes and a subset of "excluded" proteomes. Using reciprocal BLAST hits, PSI finds orthologous relationships among all the proteins in the proteomes from the original set, and then finds groups of orthologous proteins containing at least one orthologue from each of the proteomes in the "included" subset, and none from any of the proteomes in the "excluded" subset.<p> PSI is first applied to finding protein-phenotype relationships. By identifying proteins that are present in all sequenced isolates of the genus <i>Lactobacillus</i>, but not in the related bacterium <i>Pediococcus pentosaceus</i>, proteins are discovered that are likely to be responsible for the difference in cell shape between the lactobacilli and <i>P. pentosaceus</i>. In addition, proteins are identified that may be responsible for resistance to the antibiotic gatifloxacin in some lactic acid bacteria.<p> This thesis also explores the use of PSI for comparing protein content in groups of organisms. Based on the idea of genome subtraction, a novel metric is proposed for comparing the difference in protein content between two organisms. This metric is then used to create a phylogenetic tree for a large set of bacteria, which to the author's knowledge represents the largest phylogenetic tree created to date using protein content. In addition, PSI is used to find the proteomic cohesiveness of isolates of several bacterial species in order to support or refute their current taxonomic classifications.<p> Overall, PSI is a versatile tool with many interesting applications, and should become more and more valuable as additional genomic information becomes available.

Arteries possess the ability to grow and remodel in response to sustained alterations in biomechanical loading, likely via mechanisms that are similarly involved in diverse arterial pathologies and responses to treatment. In particular, myriad experminental observations suggest that cell and matrix turnover within vasoaltered states enable arteries to adapt to sustained changes in mechanical stimuli. The goal herein is to show explicitly how altered smooth muscle contractility and matrix growth and remodeling work together to adapt the geometry, structure, stiffness, and function of a representative basilar artery. This work seeks to illustrate the importance of complementary vasoactivity and matrix remodeling for basilar arteries in response to sustained alterations in mechanical stimuli. Toward this end, an extended constrained mixture model of the arterial wall is employed whereby the mass fractions, material properties, and natural configurations of individual constituents can evolve separately and thereby dictate overall growth and remodeling. This approach accounts for fundamentally important behaviors. Simulations provide important intuition and insight regarding constitutive functional forms and model parameters.

Thesis (Ph. D.)--University of Missouri-Columbia, 2000. / Typescript. Vita. Includes bibliographical references. Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 2000. / Typescript. Vita. Includes bibliographical references. Also available on the Internet.

Systems biology studies the complex interactions between components of biological systems. One major goal of systems biology is to reconstruct the network of interactions between genes in response to normal and perturbed conditions. In order to accomplish this goal, large-scale data are needed. Accordingly, diverse powerful and high-throughput methods must be developed for this purpose. We have developed novel high-throughput technologies focusing on cellular phenotype profiling and now provide additional genome-scale analysis of gene and protein function. Few high-throughput methods can perform large-scale and high-throughput cellular phenotype profiling. However, analyzing gene expression patterns and protein behaviors in their cellular context will provide insights into important aspects of gene function. To complement current genomic approaches, we developed two technologies, the spotted cell microarray (cell chip) and the yeast spheroplast microarray, which allow high-throughput and highly-parallel cellular phenotype profiling including cell morphology and protein localization. These methods are based on printing collections of cells, combined with automated high-throughput microscopy, allowing systematic cellular phenotypic characterization. We used spotted cell microarrays to identify 15 new genes involved in the response of yeast to mating pheromone, 80 proteins associated with shmoo-tip 'localizome' upon pheromone stimulation and 5 genes involved in regulating the localization pattern of a group II intron encoded reverse transcriptase, LtrA, in Escherichia coli. Furthermore, in addition to morphology assays, yeast spheroplast microarrays were built for high-throughput immunofluorescence microscopy, allowing large-scale protein and RNA localization studies. In order to identify additional cell cycle genes, especially those difficult to identify in loss-of-function studies, we performed a genome-scale screen to identify yeast genes with overexpression-induced defects in cell cycle progression. After measuring the fraction of cells in G1 and G2/M phases of the cell cycle via high-throughput flow cytometry for each of ~5,800 ORFs and performing the validation and secondary assays, we observed that overexpression of 108 genes leads to reproducible and significant delay in the G1 or G2/M phase. Of 108 genes, 82 are newly implicated in the cell cycle and are likely to affect cell cycle progression via a gain-of-function mechanism. The G2/M category consists of 87 genes that showed dramatic enrichment in the regulation of mitotic cell cycle and related biological processes. YPR015C and SHE1 in the G2/M category were further characterized for their roles in cell cycle progression. We found that the G2/M delay caused by the overexpression of YPR015C and SHE1 likely results from the malfunction of spindle and chromosome segregation, which was supported by the observations of highly elevated population of large-budded cells in the pre-M phase, super-sensitivity to nocodazole, and high chromosome loss rates in these two overexpression strains. While the genes in the G2/M category were strongly enriched for cell cycle associated functions, no pathway was significantly enriched in the G1 category that is composed of 21 genes. However, the strongest enrichment for the G1 category consists of the genes involved in negative regulation of transcription. For instance, the overexpression of SKO1, a transcription repressor, resulted in strong cell cycle delay at G1 phase. Moreover, we found that the overexpression of SKO1 results in cell morphology changes that resembles mating yeast cells (shmoos) and activates the mating pheromone response pathway, thus explaining the G1 cell cycle arrest phenotype of SKO1 ORF strains.

Mutation is a fundamental process in evolution because affects the amount of genetic variation in evolving populations. Molecular-structure models offer significant advantages over traditional population-genetics models for studying mutation, mainly because such models incorporate simple, tractable genotype-to-phenotype maps. Here, I use RNA secondary structure models to study four basic properties of mutation. The first section of this thesis studies the statistical properties of beneficial mutations. According to population genetics theory, the fitness effects of new beneficial mutations will be exponentially distributed. I show that in RNA there is sufficient correlation between a genotype and its point mutant neighbors to produce non-exponential distributions of fitness effects of beneficial mutations. These results suggest that more sophisticated statistical models may be necessary to adequately describe the distribution of fitness effects of new beneficial mutations. The second section of this thesis addresses the dynamics of deleterious mutations in evolving populations. There is a vast body of theoretical work addressing deleterious mutations that almost universally assumes that the fitness effects of deleterious mutations are static. I use an RNA simulation model to show that, at moderately high mutation rates, initially deleterious mutations may ultimately confer beneficial effects to the individuals harboring them. This result suggests that deleterious mutations may play a more important role in evolution than previously thought. The third section of this thesis studies the global patterns of mutations connecting phenotypes in fitness landscapes. I developed a network model to describe global characteristics of the relationship between sequence and structure in RNA fitness landscapes. I show that phenotype abundance varies in a predictable manner and critically influences evolutionary dynamics. A study of naturally occurring functional RNA molecules using a new structural statistic suggests that these molecules are biased towards abundant phenotypes. These results are consistent with an "ascent of the abundant" hypothesis, in which evolution yields abundant phenotypes even when they are not the most fit. The final section of this thesis addresses the evolution of mutation rates infinite asexual populations. I developed an RNA-based simulation model in which each individual's mutation rate is controlled by a neutral modifier locus. Using this model, I show that smaller populations maintain higher mutation rates than larger populations. I also show that genome length and shape of the fitness function do not significantly determine the evolved mutation rate. Lastly, I show that intermediate rates of environmental change favor evolution of the largest mutation rates. / text

The ability to predict is one of the hallmarks of successful theories. Historically, the predictive power of biology has lagged behind disciplines like physics because the biological world is complex, challenging to quantify, and full of exceptions. However, in recent years the amount of available data has expanded exponentially and biological predictions based on this data become a possibility. The functional gene network is a quantitative way to integrate this data and a useful framework for making biological predictions. This study demonstrates that functional networks capture real biological insight and uses the network to predict both subcellular protein localization and the phenotypic outcome of gene knockouts. Furthermore, I use the functional network to evaluate genetic modules shared between diverse organisms that lead to orthologous phenotypes, many that are non-obvious. I show that the successful predictions of the functional network have broad applicability and implications that range from the design of large-scale biological experiments to the discovery of genes with potential roles in human disease. / text

Vasomotion is the spontaneous oscillation of vascular tone, occurring due to synchronization of internal calcium fluctuations between multiple vascular smooth muscle cells by gap junction and electrical communication. Although altered vasomotion has been observed in a variety of pathological situations, characterization of these alterations has been lacking. Using a novel method of spectral quantification, and two experimental models known to have altered vascular structure, the present thesis was designed to evaluate whether vasomotion characteristics could be correlated with altered vascular structure. Rats with perinatal iron deficiency (PID) have previously been shown to possess altered vascular structure. When phenylephrine-mediated contractile and acetylcholine-mediated dilatory responses were investigated in PID animals, they both displayed blunted relaxation as compared to control vessels. When vasomotion characteristics were quantified, vessels taken from PID animals exhibited a decreased power in the very low frequency window (VLF <0.2 Hz). Changing vessel oxygenation to 10% O2 from 95% O2 did not result in significant alterations of vasomotion characteristics. The primary frequency of oscillation was investigated with a peak finder, and found to be significantly different compared to control in both the aorta and renal arteries obtained from PID animals. To investigate the effect of antihypertensive treatment (enalapril and hydrochlorothiazide) on gap junction communication, spontaneously hypertensive rats (SHR) were subject to a 2-week intensive angiotensin converting enzyme inhibitor treatment. This treatment resulted in significant vascular structural regression. All vessels (aorta, renal, mesenteric) from treated animals had greater proportions of power in the VLF window, with both the mesenteric and renal vessels exhibiting a primary peak of oscillation around 0.2 Hz; whereas the aorta had a primary peak at 0.12 Hz. Investigating altered gap junction communication with the gap junction blocker 18-α glycyrrhetinic acid, revealed that vascular bed location was the determining factor of vasomotion response. Immunoblotting did not indicate differences in connexin 43, a major gap junction protein in the vascular smooth muscle. These studies suggest that vasomotion characteristics can be used as a method of vascular phenotype investigation; vasomotion characteristics were significantly different in vessels taken from PID and hypertensive animals as compared to control and antihypertensive-treated animals, respectively. / Thesis (Master, Pharmacology & Toxicology) -- Queen's University, 2008-09-26 11:39:44.043