This PhD dissertation is focused on short tandemly repeated nucleotide patterns which occur extremely often across DNA sequences, called microsatellites. The main characteristic of microsatellites, and probably the reason why they are so abundant across genomes, is the extremely high frequency of specific replication errors occurring within their sequences, which usually cause addition or deletion of one or more complete tandem repeat units. Due to these errors, frequent fluctuations in the number of repetitive units can be observed among cellular and organismal generations. The molecular mechanisms as well as the consequences of these microsatellite mutations, both, on a generational as well as on an evolutionary scale, have sparked debate and controversy among the scientific community. Furthermore, the bioinformatic approaches used to study microsatellites and the ways microsatellites are referred to in the general literature are often not rigurous, leading to misinterpretations and inconsistencies among studies. As an introduction to this complex topic, in Chapter I I present a review of the knowledge accumulated on microsatellites during the past two decades. A major part of this chapter has been published in the Encyclopedia of Life Sciences in a Chapter about microsatellite evolution (see Publication 1 in Appendix II). The ongoing controversy about the rates and patterns of microsatellite mutation was evident to me since before starting this PhD thesis. However, the subtler problems inherent to the computational analyses of microsatellites within genomes only became apparent when retrieving information on microsatellite distribution and abundance for the design of comparative genomic analyses. There are numerous publications analyzing the microsatellite content of genomes but, in most cases, the results presented can neither be reliably compared nor reproduced, mainly due to the lack of details on the microsatellite search process (particularly the program’s algorithm and the search parameters used) and because the results are expressed in terms that are relative to the search process (i.e. measures based on the absolute number of microsatellites). Therefore, in Chapter II I present a critical review of all available software tools designed to scan DNA sequences for microsatellites. My aim in undertaking this review was to assess the comparability of search results among microsatellite programs, and to identify the programs most suitable for the generation of microsatellite datasets for a thorough and reproducible comparative analysis of microsatellite content among genomic sequences. Using sequence data where the number and types of microsatellites were empirical know I compared the ability of 19 programs to accurately identify and report microsatellites. I then chose the two programs which, based on the algorithm and its parameters as well as the output informativity, offered the information most suitable for biological interpretation, while also reflecting as close as possible the microsatellite content of the test files. From the analysis of microsatellite search results generated by the various programs available, it became apparent that the program’s search parameters, which are specified by the user in order to define the microsatellite characteristics to the program, influence dramatically the resulting datasets. This is especially true for programs suited to allow imperfections within tandem repeats, because imperfect repetitions can not be defined accurately as is the case for perfect ones, and because several different algorithms have been proposed to address this problem. The detection of approximate microsatellites is, however, essential for the study of microsatellite evolution and for comparative analyses based on microsatellites. It is now well accepted that small deviations from perfect tandem repeat structure are common within microsatellites and larger repeats, and a number of different algorithms have been developed to confront the challenge of finding and registering microsatellites with all expectable kinds of imperfection. However, biologists have still to apply these tools to their full potential. In biological analyses single tandem repeat hits are consistently interpreted as isolated and independent repeats. This interpretation also depends on the search strategy used to report the microsatellites in DNA sequences and, therefore, I was particularly interested in the capacity of repeat finding programs to report imperfect microsatellites allowing interpretations that are useful in a biological sense. After analzying a series of tandem repeat finding programs I optimized my microsatellite searches to yield the best possible datasets for assessing and comparing the degree of imperfection of microsatellites among different genomes (Chapter III) During the program comparisons performed in Chapter II, I show that the most critical search parameter influencing microsatellite search results is the minimum length threshold. Biologically speaking, there is no consensus with respect to the minimum length, beyond which a short tandem repeat is expected to become prone to microsatellite-like mutations. Usually, a single absolute value of ~12 nucleotides is assigned irrespective of motif length.. In other cases thresholds are assigned in terms of number of repeat units (i.e. 3 to 5 repeats or more), which are better applied individually for each motif. The variation in these thresholds is considerable and not always justifiable. In addition, any current minimum length measures are likely naïve because it is clear that different microsatellite motifs undergo replication slippage at different length thresholds. Therefore, in Chapter III, I apply two probabilistic models to predict the minimum length at which microsatellites of varying motif types become overrepresented in different genomes based on the individual oligonucleotide frequency data of these genomes. Finally, after a range of optimizations and critical analyses, I performed a preliminary analysis of microsatellite abundance among 24 high quality complete eukaryotic genomes, including also 8 prokaryotic and 5 archaeal genomes for contrast. The availability of the methodologies and the microsatellite datasets generated in this project will allow informed formulation of questions for more specific genome research, either about microsatellites, or about other genomic features microsatellites could influence. These datasets are what I would have needed at the beginning of my PhD to support my experimental design, and are essential for the adequate data interpretation of microsatellite data in the context of the major evolutionary units; chromosomes and genomes.

Consolidated bioprocessing, a process in which cellulase production, substrate hydrolysis, and fermentation occur simultaneously, offers the potential for lower biofuel production costs than traditional approaches and is an economically attractive near-term goal for fermentative production of ethanol and/or hydrogen (H2) as biofuels. Current yields fall short of theoretical maxima, vary considerably between species, and are influenced by the highly branched metabolic pathways utilized by fermentative organisms. For fermentative ethanol/ H2 production to become practical, yields must be increased either through intelligent species selection, a manipulation of culture conditions, or via the implementation of rational metabolic engineering strategies. A comparative genomics approach amoungst select members of the Firmicutes, Euryarchaeota, and Thermotogae was used to identify genes relevent to ethanol and H2 production. Growth, end-product synthesis, enzyme activities and the associated transcription of select genes were studied in the cellulolytic anaerobe, Clostridium thermocellum ATCC 27405, during batch fermentation of cellobiose to determine the effect of elevated N2 and H2 sparging on end-product distribution. The absence of genes encoding acetaldehyde dehydrogenase and bifunctional acetaldehyde/alcohol dehydrogenase (AdhE) correlates with elevated H2 yields and low ethanol production. The type(s) of encoded hydrogenases appear to have minimal impact on H2 production in organisms that do not encode ethanologenic pathways, however, they do influence reduced end-product yields in those that do. We also find that while gas sparging can be used to effectively shift carbon and electron flow, the observed shifts at the pyruvate branch-point are likely principally influenced by the availability of reduced electron carriers (NAD, NADP, ferredoxin) and thermodynamic considerations. Finally, both electrotransformation and conjugative plasmid protocols were developed and evaluated for thermophilic species C. thermocellum and Thermoanaerobacter pseudethanolicus 39E, and the mesophilic bacterium, Clostridium termitidis CT1112. The efficiency of transformation for C. thermocellum strain ATCC 27405 is consistently low whereas transformation frequencies were ~100-fold higher in C. termitidis. Observed frequencies of plasmid transfer, via conjugation, were similar in both C. thermocellum and C. termitidis suggesting the transfer of single stranded DNA may circumvent aggressive restriction methylation systems.

Chemotherapeutic agents act by targeting rapidly dividing cancer cells. The full extent of their cellular mechanisms, which is essential to balance efficacy and toxicity, is often unclear. In addition, the use of many anticancer drugs is limited by dose-limiting toxicities as well as the development of drug resistance. The work presented in this thesis aims to address the basic biology that underlies these issues through the development and application of chemical genomic tools to probe mechanisms of current and novel anticancer compounds. Chemical genomic screens in the yeast Saccharomyces cerevisiae have been used to successfully identify targets and pathways related to a compound’s mode of action. I applied these screens to examine the mode of action of potential anticancer drugs: a class of platinum-acridine compounds and the apoptosis-inducing compound elesclomol. By analogy to the yeast screens, I developed an RNAi-mediated chemical genomic screen in human cells which has the potential to reveal novel targets and drug mechanisms. This screen was applied to further understand doxorubicin’s mode of action. In parallel with the loss-of-function assays, our lab developed a human ORF overexpression screen in human cells. I applied this gain-of-function screen to identify those genes that, when overexpressed, are toxic to cells. Characterization of such genes that cause toxicity can provide insight into human diseases where gene amplification is prevalent.

Over the past two decades, high-throughput (HTP) technologies such as microarrays and mass spectrometry have fundamentally changed the landscape of aging and disease biology. They have revealed novel molecular markers of aging, disease state, and drug response. Some have been translated into the clinic as tools for early disease diagnosis, prognosis, and individualized treatment and response monitoring. Despite these successes, many challenges remain: HTP platforms are often noisy and suffer from false positives and false negatives; optimal analysis and successful validation require complex workflows; and the underlying biology of aging and disease is heterogeneous and complex. Methods from integrative computational biology can help diminish these challenges by creating new analytical methods and software tools that leverage the large and diverse quantity of publicly available HTP data. In this thesis I report on four projects that develop and apply strategies from integrative computational biology to identify improved biomarkers and therapeutics for aging and disease. In Chapter 2, I proposed a new network analysis method to identify gene expression biomarkers of aging, and applied it to study the pathway-level effects of aging and infer the functions of poorly-characterized longevity genes. In Chapter 4, I adapted gene-level HTP chemogenomic data to study drug response at the systems level; I connected drugs to pathways, phenotypes and networks, and built the NetwoRx web portal to make these data publicly available. And in Chapters 3 and 5, I developed a novel meta-analysis pipeline to identify new drugs that mimic the beneficial gene expression changes seen with calorie restriction (Chapter 3), or that reverse the pathological gene changes associated with lung cancer (Chapter 5). The projects described in this thesis will help provide a systems-level understanding of the causes and consequences of aging and disease, as well as new tools for diagnosis (biomarkers) and treatment (therapeutics).

Chemotherapeutic agents act by targeting rapidly dividing cancer cells. The full extent of their cellular mechanisms, which is essential to balance efficacy and toxicity, is often unclear. In addition, the use of many anticancer drugs is limited by dose-limiting toxicities as well as the development of drug resistance. The work presented in this thesis aims to address the basic biology that underlies these issues through the development and application of chemical genomic tools to probe mechanisms of current and novel anticancer compounds. Chemical genomic screens in the yeast Saccharomyces cerevisiae have been used to successfully identify targets and pathways related to a compound’s mode of action. I applied these screens to examine the mode of action of potential anticancer drugs: a class of platinum-acridine compounds and the apoptosis-inducing compound elesclomol. By analogy to the yeast screens, I developed an RNAi-mediated chemical genomic screen in human cells which has the potential to reveal novel targets and drug mechanisms. This screen was applied to further understand doxorubicin’s mode of action. In parallel with the loss-of-function assays, our lab developed a human ORF overexpression screen in human cells. I applied this gain-of-function screen to identify those genes that, when overexpressed, are toxic to cells. Characterization of such genes that cause toxicity can provide insight into human diseases where gene amplification is prevalent.

Consolidated bioprocessing, a process in which cellulase production, substrate hydrolysis, and fermentation occur simultaneously, offers the potential for lower biofuel production costs than traditional approaches and is an economically attractive near-term goal for fermentative production of ethanol and/or hydrogen (H2) as biofuels. Current yields fall short of theoretical maxima, vary considerably between species, and are influenced by the highly branched metabolic pathways utilized by fermentative organisms. For fermentative ethanol/ H2 production to become practical, yields must be increased either through intelligent species selection, a manipulation of culture conditions, or via the implementation of rational metabolic engineering strategies. A comparative genomics approach amoungst select members of the Firmicutes, Euryarchaeota, and Thermotogae was used to identify genes relevent to ethanol and H2 production. Growth, end-product synthesis, enzyme activities and the associated transcription of select genes were studied in the cellulolytic anaerobe, Clostridium thermocellum ATCC 27405, during batch fermentation of cellobiose to determine the effect of elevated N2 and H2 sparging on end-product distribution. The absence of genes encoding acetaldehyde dehydrogenase and bifunctional acetaldehyde/alcohol dehydrogenase (AdhE) correlates with elevated H2 yields and low ethanol production. The type(s) of encoded hydrogenases appear to have minimal impact on H2 production in organisms that do not encode ethanologenic pathways, however, they do influence reduced end-product yields in those that do. We also find that while gas sparging can be used to effectively shift carbon and electron flow, the observed shifts at the pyruvate branch-point are likely principally influenced by the availability of reduced electron carriers (NAD, NADP, ferredoxin) and thermodynamic considerations. Finally, both electrotransformation and conjugative plasmid protocols were developed and evaluated for thermophilic species C. thermocellum and Thermoanaerobacter pseudethanolicus 39E, and the mesophilic bacterium, Clostridium termitidis CT1112. The efficiency of transformation for C. thermocellum strain ATCC 27405 is consistently low whereas transformation frequencies were ~100-fold higher in C. termitidis. Observed frequencies of plasmid transfer, via conjugation, were similar in both C. thermocellum and C. termitidis suggesting the transfer of single stranded DNA may circumvent aggressive restriction methylation systems.

Thesis (Ph. D.)--Case Western Reserve University, 2008. / [School of Medicine] Department of Bioethics. Includes bibliographical references.

Thesis (M.S.)--Rochester Institute of Technology, 2009. / Typescript. Includes bibliographical references (leaves 56-59).

Thesis (M.S.)--West Virginia University, 2008. / Title from document title page. Document formatted into pages; contains viii, 85 p. : col. ill. Includes abstract. Includes bibliographical references (p. 81-85).

Thesis (Ph.D.)--University of California, San Francisco, 2004. / Includes bibliographical references. Also available online.