The role of metal metabolism and heat shock protein genes on replicative lifespan of the budding yeast, Saccharomyces cerevisiae

A variety of genes that influence aging have been identified in a broad selection of organisms including Saccharomyces cerevisiae (yeast), Caenorhabditis elegans (worms), Drosophila (fruit flies), Macaca Mulatta (rhesus monkeys), and even Homo sapiens. Many of these genes, such the TOR’s, FOXO’s, AKT’s, and S6K’s are conserved across different organisms. All of these genes participate in nutrient sensing networks. Other conserved genetic networks may similarly affect lifespan. In this thesis, I explored genes from an iron metabolism family and a heat shock protein (HSP) gene family that have been identified, but not confirmed, to influence lifespan. Yeast is a reliable model for mitotic (replicative) aging. Using yeast, I tested whether the FET-genes, encoding a family of iron importer-related genes, are required for mitotic lifespan. I also tested whether another family of genes, the yeast SSA HSP70- encoding genes, related to mammalian HSP70s, influence mitotic aging. I primarily used the replicative lifespan (RLS) assay, in which I measured the mitotic capacity of multiple FET and SSA yeast mutants. I hypothesize that aging occurs when iron transport is misregulated, which may lead to an over-reliance on HSPs for lifespan maintenance. The results presented in this thesis support the hypothesis. First, FET3 was primarily involved in lifespan maintenance under normal conditions (2% glucose), while FET5 was primarily involved in the cellular lifespan extension characteristic of caloric restriction (0.01% glucose), a known anti-aging intervention. In addition, SSA2 appeared to facilitate lifespan maintenance in the absence of FET4, while the presence of SSA1 limited lifespan length. That the aging genes identified in this study are involved in iron metabolism or heat stress suggests that protein aggregation or reactive oxidative species production are common processes through which these genes interact

Metabolic Reprogramming By DNA Tumour Viruses

Viruses are the etiological agents of approximately 12% of human cancers. However, only a subset of viral infections eventually progress to cancer. As obligate intracellular parasites, viruses create a host-cell environment that is amenable to virus replication. These changes to host-cell processes during infection are enacted by virally-encoded proteins that act as molecular hubs. When these processes intersect with pathways that encourage the development of cancer, such as the p53 tumour suppressor pathway, these virally-encoded molecular hub proteins function as viral oncoproteins. One major requirement of both virus infected cells and rapidly growing cancer cells is an altered metabolism that provides the rapid production of energy and macromolecules required for either viral or cellular replication. Typically, this metabolic phenotype involves an increased rate of glycolysis and a decreased rate of cellular respiration despite the presence of ample oxygen that would otherwise encourage respiration. The purpose of this thesis is to investigate how viruses belonging to a subset viruses known as DNA tumour viruses can reprogram cellular metabolism. We hypothesize that DNA tumour viruses cause a cancer-like metabolic phenotype in the infected cell or cancerous tissue, which is similar to, but still distinct from, the metabolic phenotype in corresponding non-virally induced cancers. First, we determined that the 13S isoform of the E1A oncoprotein found in human adenovirus is responsible for causing an increase in glycolysis both as an endogenously expressed protein and in HAdV infected cells. Next, we utilized The Cancer Genome Atlas, a repository of patient tumour data, to determine that human papillomavirus-positive (HPV+) head and neck squamous cell carcinoma (HNSCC) have a distinct metabolism-related transcriptome when compared to HPV- HNSCC, and that some of these metabolic genes are associated with patient survival. Finally, we confirm that DNA tumour virus-induced cancers do have a distinct metabolism-related transcriptome in the context of another cancer, Epstein-Barr virus associated gastric cancer. These findings highlight that the metabolic phenotypes of virally infected cells and cancer cells, while superficially similar, are distinct enough to represent potential novel druggable targets or biomarkers

Metabolic Reprogramming of the Host Cell by Human Adenovirus Infection

Viruses are obligate intracellular parasites that alter many cellular processes to create an environment optimal for viral replication. Reprogramming of cellular metabolism is an important, yet underappreciated feature of many viral infections, as this ensures that the energy and substrates required for viral replication are available in abundance. Human adenovirus (HAdV), which is the focus of this review, is a small DNA tumor virus that reprograms cellular metabolism in a variety of ways. It is well known that HAdV infection increases glucose uptake and fermentation to lactate in a manner resembling the Warburg effect observed in many cancer cells. However, HAdV infection induces many other metabolic changes. In this review, we integrate the findings from a variety of proteomic and transcriptomic studies to understand the subtleties of metabolite and metabolic pathway control during HAdV infection. We review how the E4ORF1 protein of HAdV enacts some of these changes and summarize evidence for reprogramming of cellular metabolism by the viral E1A protein. Therapies targeting altered metabolism are emerging as cancer treatments, and similar targeting of aberrant components of virally reprogrammed metabolism could have clinical antiviral applications

Metabolic Control by DNA Tumor Virus-Encoded Proteins

Viruses co-opt a multitude of host cell metabolic processes in order to meet the energy and substrate requirements for successful viral replication. However, due to their limited coding capacity, viruses must enact most, if not all, of these metabolic changes by influencing the function of available host cell regulatory proteins. Typically, certain viral proteins, some of which can function as viral oncoproteins, interact with these cellular regulatory proteins directly in order to effect changes in downstream metabolic pathways. This review highlights recent research into how four different DNA tumor viruses, namely human adenovirus, human papillomavirus, Epstein–Barr virus and Kaposi’s associated-sarcoma herpesvirus, can influence host cell metabolism through their interactions with either MYC, p53 or the pRb/E2F complex. Interestingly, some of these host cell regulators can be activated or inhibited by the same virus, depending on which viral oncoprotein is interacting with the regulatory protein. This review highlights how MYC, p53 and pRb/E2F regulate host cell metabolism, followed by an outline of how each of these DNA tumor viruses control their activities. Understanding how DNA tumor viruses regulate metabolism through viral oncoproteins could assist in the discovery or repurposing of metabolic inhibitors for antiviral therapy or treatment of virus-dependent cancers

Viral Appropriation: Laying Claim to Host Nuclear Transport Machinery

Protein nuclear transport is an integral process to many cellular pathways and often plays a critical role during viral infection. To overcome the barrier presented by the nuclear membrane and gain access to the nucleus, virally encoded proteins have evolved ways to appropriate components of the nuclear transport machinery. By binding karyopherins, or the nuclear pore complex, viral proteins influence their own transport as well as the transport of key cellular regulatory proteins. This review covers how viral proteins can interact with different components of the nuclear import machinery and how this influences viral replicative cycles. We also highlight the effects that viral perturbation of nuclear transport has on the infected host and how we can exploit viruses as tools to study novel mechanisms of protein nuclear import. Finally, we discuss the possibility that drugs targeting these transport pathways could be repurposed for treating viral infections

Tumor-Infiltrating T Cells in EBV-Associated Gastric Carcinomas Exhibit High Levels of Multiple Markers of Activation, Effector Gene Expression, and Exhaustion

Epstein–Barr virus (EBV) is a gamma-herpesvirus associated with 10% of all gastric cancers (GCs) and 1.5% of all human cancers. EBV-associated GCs (EBVaGCs) are pathologically and clinically distinct entities from EBV-negative GCs (EBVnGCs), with EBVaGCs exhibiting differential molecular pathology, treatment response, and patient prognosis. However, the tumor immune landscape of EBVaGC has not been well explored. In this study, a systemic and comprehensive analysis of gene expression and immune landscape features was performed for both EBVaGC and EBVnGC. EBVaGCs exhibited many aspects of a T cell-inflamed phenotype, with greater T and NK cell infiltration, increased expression of immune checkpoint markers (BTLA, CD96, CTLA4, LAG3, PD1, TIGIT, and TIM3), and multiple T cell effector molecules in comparison with EBVnGCs. EBVaGCs also displayed a higher expression of anti-tumor immunity factors (PDL1, CD155, CEACAM1, galectin-9, and IDO1). Six EBV-encoded miRNAs (miR-BARTs 8-3p, 9-5p, 10-3p, 22, 5-5p, and 14-3p) were strongly negatively correlated with the expression of immune checkpoint receptors and multiple markers of anti-tumor immunity. These profound differences in the tumor immune landscape between EBVaGCs and EBVnGCs may help explain some of the observed differences in pathological and clinical outcomes, with an EBV-positive status possibly being a potential biomarker for the application of immunotherapy in GC

Abstract Modeling and visualization of leaf venation patterns

We introduce a class of biologically-motivated algorithms for generating leaf venation patterns. These algorithms simulate the interplay between three processes: (1) development of veins towards hormone (auxin) sources embedded in the leaf blade; (2) modification of the hormone source distribution by the proximity of veins; and (3) modification of both the vein pattern and source distribution by leaf growth. These processes are formulated in terms of iterative geometric operations on sets of points that represent vein nodes and auxin sources. In addition, a vein connection graph is maintained to determine vein widths. The effective implementation of the algorithms relies on the use of space subdivision (Voronoi diagrams) and time coherence between iteration steps. Depending on the specification details and parameters used, the algorithms can simulate many types of venation patterns, both open (tree-like) and closed (with loops). Applications of the presented algorithms include texture and detailed structure generation for image synthesis purposes, and modeling of morphogenetic processes in support of biological research