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Characterizing the effects of N/NRTIs on human telomerase activity in vitro and telomere maintenance… Hukezalie, Kyle Reid 2011

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    CHARACTERIZING THE EFFECTS OF N/NRTIs ON HUMAN TELOMERASE ACTIVITY IN VITRO AND TELOMERE MAINTENANCE IN A TRANSFORMED HUMAN CELL MODEL   by   Kyle Reid Hukezalie   BHSc, The University of Western Ontario, 2007   A THESIS SUBMITTED IN PARTIAL FULLFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF   MASTER OF SCIENCE   in   The Faculty of Graduate Studies   (Genetics)   THE UNIVERSITY OF BRITISH COLUMBIA   (Vancouver)   December 2011   © Kyle Reid Hukezalie, 2011   ii ABSTRACT Telomeres are nucleoprotein structures found at the ends of most linear chromosomes. Telomeric DNA shortens with each cell division, effectively restricting the proliferative capacity of most human cells.  Telomerase, a specialized reverse transcriptase (RT), is responsible for de novo synthesis of telomeric DNA, and is the only physiological mechanism through which some human cells extend their telomere length.  Disruption in telomerase activity results in accelerated telomere attrition, which manifests as a loss in tissue regenerative capacity.  In individuals infected with the human immunodeficiency virus (HIV), current clinical treatment guidelines prescribe the use of a long-term, combination drug therapy known as highly active anti-retroviral therapy (HAART).  Nucleoside and non-nucleoside reverse transcriptase inhibitors (N/NRTIs) inhibit HIV RT and are integral components of HAART.  There are both reported structural and mechanistic similarities between telomerase RT and HIV RT.  Based on these observations, we hypothesized that N/NRTIs will inhibit telomerase in the same ways that they inhibit HIV RT, and that long-term exposure to these agents will limit telomere maintenance in telomerase-dependent cells.  We tested our hypothesis using two approaches.  First, N/NRTIs were tested against telomerase activity in vitro using a primer extension assay.  All NRTIs tested in this assay inhibited human telomerase, and their relative potencies were compared to their respective dideoxynucleotide analog counterparts.  The NNRTIs, which are non- competitive inhibitors of HIV RT, did not inhibit telomerase.  In our second approach, we tested the effects of long-term, continuous treatment with N/NRTIs on telomere length maintenance in a transformed human cell model with constitutive telomerase activity.  The rates of telomere length attrition in the presence of high doses of several NRTIs were consistent with maximal telomerase inhibition. In contrast, I observed minimal effects on telomere maintenance in cells treated with NNRTIs.  My primer extension assay data corroborate conclusions from previous studies on telomerase biochemistry and support mechanistic conservation between telomerase RT and HIV RT.  Collectively, my biochemical and cell culture studies demonstrated that   iii telomerase inhibition by NRTIs could potentially lead to treatment complications in current antiretroviral therapies and encourage large-scale clinical and epidemiological studies on the effects of telomerase inhibition by these drugs.   iv TABLE OF CONTENTS Abstract           ii Table of contents          iv List of tables           vii List of figures          viii List of abbreviations         x Acknowledgements          xiii 1.  Introduction          1 1.1.  Telomere structure and function       1 1.1.1.  Disguising the ends        1 1.1.2.  Buffering DNA loss        4 1.1.3.  Additional roles        5 1.2.  Telomerase          5  1.2.1.  Holoenzyme structure        5  TERT        6  TER and H/ACA proteins      10  1.2.2.  Catalysis         11  Intrinsic RAP factors       14  Extrinsic RAP factors      15  1.2.3.  Regulation and biogenesis       16 1.3.  Telomere dynamics: relevance to human physiology and tissue integrity 18 1.3.1.  Limiting replicative capacity through telomere length    18 1.3.2. Consequences of dysfunctional telomeres and telomerase deficiency 18  Genetic diseases of telomere/telomerase biology   18  Epidemiological studies of telomere length in aging  20    v 1.4.  HIV infection and AIDS        24  1.4.1.  Biology of HIV infection       24  1.4.2.  Pathology of HIV infection: CD4+ T lymphocytes    24 1.4.3.  HAART          25  Drug classes and mechanisms of action    25  Adverse effects of HAART      27  1.4.4.  Accelerated aging in HIV infection with HAART    30 1.5.  HIV and telomere/telomerase biology      31  1.5.1.  Telomere/telomerase biology in HIV infection with HAART   31  1.5.2.  In vitro effect of NRTIs on telomere/telomerase biology   32  1.5.3.  Similarities between TERT and HIV RT     34  2.  Hypothesis and goals of study        37 2.1.  Hypothesis          37 2.2.  Specific Aim 1         37 2.3.  Specific Aim 2         37  3.  Methods           40  4.  In vitro telomerase activity        48 4.1.  Introduction          48 4.2.  Results and discussion        49 4.2.1.  Methods development        49 4.2.2.  Primer extension assay with N/NRTIs     59     vi 5.  Telomere maintenance in human cells       74 5.1.  Introduction          74 5.2.  Results and discussion I        79 5.3.  Results and discussion II        89  6.  General discussion         103 6.1.  Brief summary         103 6.2.  NRTI inhibition of telomerase, HIV RT, and other cellular polymerases 103 6.3.  Significance of NRTI-mediated telomere shortening    104 6.4.  Comparison of in vitro and cell culture results     108 6.5.  Future studies with N/NRTIs and telomerase     110  References           113  Appendix           134 A.1.  Methods          134  A.1.1.  Estimation of IP efficiency with competitive RT-PCR    134  A.1.2.  Primer extension assay testing NNRTIs     135   vii LIST OF TABLES  Table 1.  Details of N/NRTIs tested        27  Table 2.  Primers used in primer extension assay      55  Table 3.  Variability of primer extension assay      58  Table 4.  Summary of dTTP analog data       66  Table 5.  Summary of dATP analog data       69  Table 6.  Summary of dGTP analog data       72  Table 7.  Summary of telomerase activity in the presence of NNRTIs   73  Table 8.  Rank of NRTIs by potency from in vitro data     112  Table 9.  Magnitude of effect of NRTIs on telomere maintenance in HT29 cells  112   viii LIST OF FIGURES  Figure 1: Structure and domain organization of TERT and TER    7  Figure 2: Telomerase catalytic cycle        13  Figure 3: Telomere dynamics and tissue integrity      21  Figure 4: Structures of N/NRTIs tested       27  Figure 5: Hypothesis          38  Figure 6: Optimization of primer extension assay for telomerase activity   54  Figure 7: Prediction of DNA products by telomerase using different primers  55  Figure 8: Confirmation of telomerase-specific primer extension assay   56  Figure 9: Optimization of primer extension assay for NRTIs    57  Figure 10: Variability of the primer extension assay for testing nucleotide analogs 58  Figure 11: Telomerase inhibition by dTTP analogs      64-66  Figure 12: Telomerase inhibition by dATP analogs      67-69  Figure 13: Telomerase inhibition by dGTP analogs      70-72  Figure 14: Telomerase activity in the presence of NNRTIs     73  Figure 15: Telomere length in untreated and vehicle treated HT29 cells (Experiment 1) 83  Figure 16: Telomere length in AZT-treated HT29 cells (Experiment 1)   84  Figure 17: Telomere length in d4T-treated HT29 cells (Experiment 1)   85  Figure 18: Telomere length in TDF-treated HT29 cells (Experiment 1)   86  Figure 19: Telomere length in ddI-treated HT29 cells (Experiment 1)   87  Figure 20: Telomere length in ABC-treated HT29 cells (Experiment 1)   88  Figure 21: Telomere length in untreated and vehicle treated HT29 cells (Experiment 2) 96  Figure 22: Telomere length in 3TC-treated HT29 cells (Experiment 2)   97  Figure 23: Telomere length in AZT-treated HT29 cells (Experiment 2)   98  Figure 24: Telomere length in d4T-treated HT29 cells (Experiment 2)   99  Figure 25: Telomere length in ABC-treated HT29 cells (Experiment 2)   100   ix Figure 26: Telomere length in NVP-treated HT29 cells (Experiment 2)   101  Figure 27: Telomere length in EFV-treated HT29 cells (Experiment 2)   102  Appendix Figure 1: Estimation of IP efficiency of telomerase    134  Appendix Figure 2: Dose-response experiments for NNRTIs    135                                               x LIST OF ABBREVIATIONS 3TC: Lamivudine  AA: Aplastic anemia  ABC: Abacavir  AIDS: Acquired immune deficiency syndrome  ARV: Anti-retroviral  AZT: Azidothymidine  AZT-TP: Azidothymidine triphosphate  CCR5: Chemokine receptor type 5  CBV: Carbovir  CBV-TP: Carbovir-triphosphate  CR4/5: Conserved regions 4 and 5  CTE: C-terminal extension  CVD: Cardiovascular disease  CXCR4: Chemokine receptor type 4  d4T: Stavudine  d4T-TP: Stavudine triphosphate  DAT: Dissociates activities of telomerase  DC: Dyskeratosis congenita  dNTP: deoxynucleotide triphosphate  ddNTP: dideoxynucleotide triphosphate  ddI: Didanosine  DMEM: Dulbecco’s Modified Eagle’s Medium  DMSO: Dimethyl sulfoxide  EFV: Efavirenz  FISH: Fluorescence in situ hybridization   xi  H/ACA: Hinge ACA domain  HAART: Highly active anti-retroviral therapy  HEK: Human embryonic kidney  HIV: Human immunodeficiency virus  HIV RT: Human immunodeficiency virus reverse transcriptase  hTER: Human telomerase RNA  hTERT: Human telomerase reverse transcriptase  IC50: Concentration of drug required for 50% enzyme inhibition  IFD: Insertion in fingers domain  IP: Immunopurified  Km: Michaelis constant  MI: Myocardial infarction  NNRTI: Non-nucleoside reverse transcriptase inhibitor  NRTI: Nucleoside reverse transcriptase inhibitor  nt: nucleotide(s)  NVP: Nevirapine  PBMC: Peripheral blood mononuclear cell  PBS: Phosphate buffered saline  PDL: Population doubling level  POT1: Protection of telomeres 1  RRL: Rabbit reticulocyte lysate  RAP: Repeat addition processivity  RAP1: Human ortholog of the yeast repressor/activator protein 1  RNP: Ribonucleoprotein  ROS: Reactive oxygen species    xii RPA: Replication protein A  RT: Reverse transcriptase  scaRNA: small Cajal-body RNA  snoRNA: Small nucleolar RNA  STELA: Single telomere length analysis  t-loop: Telomere loop  TCAB1: Telomerase Cajal body protein 1  TDF: Tenofovir disoproxil fumarate  TEN: Telomerase essential N-terminus  TER: Telomerase RNA  TERT: Telomerase reverse transcriptase  TFV: Tenofovir  TFV-DP: Tenofovir diphosphate  TIN2: TRF2- and TRF1-interacting nuclear protein 2  TRBD: Telomerase RNA binding domain  TRF1: Telomere Repeat Binding Factor 1  TRF2: Telomere Repeat Binding Factor 2  TRF: Terminal restriction fragment  TRFH: TRF homology  WCL: Whole cell lysate    xiii ACKNOWLEDGEMENTS  I offer my sincere thanks to the faculty, staff, and students in both The Faculty of Pharmaceutical Sciences and The Genetics Graduate Program at The University of British Columbia, who have provided support, encouragement, and inspiration throughout my time as a graduate student.  I am especially grateful to my research supervisor, Dr. Judy Wong, for her continuous guidance, mentoring, and unwavering effort to push me beyond what I thought my academic capabilities were.  I must also express thanks to Dr. Helen Fleisig, who helped keep me grounded during my time as a graduate student and provided helpful insight as I transitioned from student to professional life.  I would also like to thank Xi-Lei Zeng, Dr. Naresh Thumati, and Matthew Trudeau, for scientific and experimental insight, and for light-hearted conversation when things got too serious around the lab.  Finally, I thank my family for providing moral support during difficult times and for keeping things in perspective.  My parents, Judy Whitenect and Robert Hukezalie, have sacrificed a great deal for my education—this endeavor would not have been possible without their unwavering support.   1 1.  INTRODUCTION 1.1.  Telomere structure and function 1.1.1.  Disguising the ends Telomeres are the natural ends of linear chromosomes.  Functional telomeres are composed of both protein and DNA.  In humans, telomeric DNA is composed of short, tandem repeats of the sequence 5’-TTAGGG-3’ that normally range from 5 – 15 kb in length (de Lange, Shiue et al., 1990; Harley, Futcher et al., 1990).  While the majority of the length of telomeres is duplex DNA, the 3’ end of the G-rich strand terminates as a single-stranded overhang, which is typically 50 – 100 nt, but can be up to 400 nt (McElligott and Wellinger, 1997; Wright, Tesmer et al., 1997). The 3’ overhang is thought to participate in the formation of a higher order lariat structure called a telomere loop (t-loop).  T-loops have been observed at the ends of telomeres in humans (Griffith, Comeau et al., 1999; Stansel, de Lange et al., 2001), as well as in several other model organisms (Murti and Prescott, 1999; Munoz-Jordan, Cross et al., 2001; Nikitina and Woodcock, 2004).  The 3’ overhang is thought to participate in the formation of the t-loop through strand invasion of the more proximal, duplex telomeric DNA, base-pairing with the C-rich strand and causing a displacement loop (D loop).  The t-loop structure is integral in helping cells discriminate between natural chromosomal ends and ds DNA breaks.  Through this discrimination, chromosomal ends are able to avoid the normal responses to DNA damage which would otherwise lead to chromosomal end-to-end fusions, genomic instability, and subsequent cell cycle arrest or cell death (de Lange, 2009). An integral structural component of the mammalian telomere is the six-protein complex called shelterin (Palm and de Lange, 2008; Martinez and Blasco, 2011).  Shelterin is composed of six telomere-specific proteins: Telomere Repeat Factor 1 and 2 (TRF1 and TRF2), Protection Of Telomeres 1 (POT1), TRF2- and TRF1-Interacting Nuclear protein 2 (TIN2), the human ortholog of the yeast Repressor/Activator Protein 1 (Rap1) and TPP1 (its name given in   2 consideration of its previous names TINT1, PTOP, PIP1).  As a complex, the shelterin proteins play a critical role in maintaining the architecture of the chromosome end. TRF1 and TRF2 bind duplex telomeric DNA independently as either homodimers or oligomers.  DNA binding is accomplished through a SANT/Myb domain, which is nearly identical between TRF1 and TRF2 and directs both proteins to bind telomeric DNA sequence specifically. Homotypic interactions occur through the TRF homology (TRFH) domain, which is also important in recruiting other shelterin components and accessory factors to telomeric DNA. Although the exact mechanism of t-loop formation is not known, TRF2, but not TRF1, has been implicated as a participant through in vitro experiments. TRF2 binds preferentially to the 3’ end of a telomere repeat array when it contains a 3’ overhang, promotes strand invasion by introducing supercoils into DNA, and can form t-loop structures in vitro.  TRF1 and TRF2 both contribute to telomere length regulation.  In human cells, overexpression of either TRF1 or TRF2 leads to telomere shortening over time (van Steensel and de Lange, 1997; Smogorzewska, van Steensel et al., 2000; Karlseder, Smogorzewska et al., 2002).  In contrast, expression of a dominant negative form of TRF1 in human cells leads to an increase in telomere length (van Steensel and de Lange, 1997).  TRF1 and TRF2-mediated telomere length regulation is independent of telomerase activity. In contrast to TRF1 and TRF2, which bind duplex telomeric DNA, POT1 binds specifically to single-stranded telomeric DNA.  Human POT1 was first discovered as a telomeric protein by its sequence identity to chromosome end binding proteins in unicellular organisms and demonstrated ability to specifically bind single stranded human telomeric DNA in biochemical experiments (Baumann and Cech, 2001).  As such, much of the work on human POT1 has focused on characterizing its role in telomere-end binding.  In cell culture, reducing the amount of POT1 bound to single stranded telomeric DNA, either through POT1-directed RNA interference or mutagenesis of its DNA-binding domain, led to telomerase-dependent telomere elongation (Loayza and De Lange, 2003; Ye, Hockemeyer et al., 2004).  Subsequent   3 biochemical analyses identified POT1 and telomerase as direct competitors for the 3’ end of a single stranded telomeric substrate (Kelleher, Kurth et al., 2005; Lei, Zaug et al., 2005). Collectively, these data provide evidence that POT1 is an important cis-inhibitory factor of telomerase at the 3’ end of a single-stranded telomeric substrate.  The crystal structure of POT1 bound to single stranded telomeric DNA corroborates its role in sequestering the 3’ end of telomeric DNA (Lei, Podell et al., 2004).  POT1 normally binds telomeric DNA as a heterodimer with its binding partner, TPP1 (Liu, Safari et al., 2004).  TPP1 recruits POT1 to, and increases its binding affinity for single- stranded telomeric DNA (Liu, Safari et al., 2004; Ye, Hockemeyer et al., 2004; Xin, Liu et al., 2007).  Consistent with TPP1/POT1 functioning as a complex at telomeres, the two proteins are found at a 1:1 stoichiometric ratio in vivo (Takai, Hooper et al., 2010).  Similar to TRF1, TPP1 contributes to telomere length regulation both negatively (telomere shortening) and positively (telomere lengthening).  The negative regulatory role of TPP1 occurs through its interaction with POT1.  TPP1-dependent recruitment of POT1 to mammalian telomeric DNA appears to be essential to the ability of POT1 to prevent telomerase-dependent telomere elongation (Liu, Safari et al., 2004; Ye, Hockemeyer et al., 2004; Hockemeyer, Palm et al., 2007; Xin, Liu et al., 2007).  The positive influence that TPP1 has on telomere length regulation occurs through its interaction with TIN2.  In human cells, TPP1 bound to TIN2 can recruit telomerase to telomeres through a physical interaction within its oligonucleotide/oligosaccharide-binding (OB) fold (Xin, Liu et al., 2007; Abreu, Aritonovska et al., 2010).  Interestingly, TPP1-dependent recruitment of telomerase does not depend on POT1.  TIN2 has the ability to interact with TRF1, TRF2, and TPP1, thereby connecting the components of shelterin that bind ss- and dsDNA.  TIN2 binds TRF1 and TRF2 through different domains and their binding can occur simultaneously (Ye, Donigian et al., 2004).  TIN2 interacts with TPP1 through a domain separate from those involved in binding TRF1 and TRF2 (O'Connor, Safari et al., 2006).  Depletion of TIN2 or the expression of mutant forms of the   4 protein causes substantial destabilization of shelterin, supporting its role as a central component in shelterin (Kim, Beausejour et al., 2004; Ye and de Lange, 2004; Ye, Donigian et al., 2004). Rap1 forms a 1:1 complex with TRF2 in human cells (Takai, Hooper et al., 2010), and is dependent on TRF2 for its localization to telomeric DNA (Li, Oestreich et al., 2000; Li and de Lange, 2003).  Consistent with these data, most of Rap1 is lost from telomeric DNA when TRF2 is deleted (Celli and de Lange, 2005).  Similar to other shelterin components, Rap1 participates in telomere length homeostasis.  Overexpression of Rap1 leads to telomere shortening in human cells, while expression of dominant negative mutants causes telomeres to lengthen (Li and de Lange, 2003).  1.1.2.  Buffering DNA loss Synthesis of DNA requires the use of a short RNA primer.  As a consequence, the most distal portion of the lagging strand template is not copied after the removal of the last RNA primer. This phenomenon is generally referred to as the end-replication problem.  Adding to the end- replication problem, resolution of the T-loop at the DNA synthesis stage of the cell cycle, which allows polymerase access, also contributes to telomeric sequence loss.  On average, between 50-200 bp of telomeric DNA is lost with each cell division (Harley, Futcher et al., 1990; Counter, Avilion et al., 1992).  In this context, telomeres act as a buffer to prevent the loss of more proximal coding DNA.  Consequently, with continuous proliferation, telomeres will eventually become too short and the short-telomere checkpoint will be activated (d'Adda di Fagagna, Reaper et al., 2003).  Cellular surveillance mechanisms ensure the short telomere checkpoint leads to proliferative arrest, which can result in either a metabolically active, non-dividing state (senescence) (Vaziri and Benchimol, 1998), or in some cell types, apoptosis (Counter, Avilion et al., 1992; Mondello and Scovassi, 2004; Artandi and Attardi, 2005).  Telomere-length dependent proliferative arrest thus serves to limit the number of times cells can divide, and is recognized as an important anti-cancer mechanism (Zhang, Mar et al., 1999).   5 1.1.3.  Additional roles of telomeres Telomeres participate in other processes in cells, including replication of terminal chromosomal DNA (Gilson and Geli, 2007), meiosis (Price, 1999), and regulation of gene expression (Baur, Zou et al., 2001).  The role of telomeres in the replication of terminal chromosomal DNA appears to be through the modulation of secondary structures by TRF1, TRF2, and Pot1 at the telomere by interacting with components of the replication machinery.  Telomeres participate in meiosis in Schizosaccharomyces pombe.  During meiotic prophase in S. Pombe, the chromosomes take on a unique ‘horsetail’ shape, where the telomeres cluster near the spindle- pole body and the centromeres become dispersed in the nucleus (Chikashige, Ding et al., 1997). The nucleus elongates during this process and moves back and forth in the cell, with the telomeres and spindle-pole body directing the motion.  This phenomenon was shown to mediate homolog alignment (Cooper, Watanabe et al., 1998; Nimmo, Pidoux et al., 1998).  Telomere- related regulation of gene expression is known as the telomere position effect, and has been observed in Saccharomyces cerevisiae and humans (Gottschling, Aparicio et al., 1990; Kyrion, Liu et al., 1993; Baur, Zou et al., 2001). The heterochromatin structure at the telomere represses the transcription of neighbor genes, and this inhibitory effect on gene transcription has been observed to correlate with the relative position of the gene loci to the telomere heterochromatin, and the length of the telomere.  1.2.  Telomerase 1.2.1.  Holoenzyme structure Telomerase is a specialized reverse transcriptase (RT) that functions primarily to maintain telomeric DNA.  In humans, telomerase maintains telomeres by adding the hexanucleotide repeat TTAGGG to the 3’ ends of chromosomes.  The catalytic core telomerase enzyme is a ribonucleoprotein (RNP) composed of telomerase reverse transcriptase (TERT), the catalytic subunit (Nakamura, Morin et al., 1997), and telomerase RNA (TER) (Feng, Funk et al., 1995).   6 Telomerase uses a region of its integral RNA as a template for nucleotide addition.  Together, TERT and TER are the minimal requirements for telomerase activity in vitro (Weinrich, Pruzan et al., 1997).  In vivo, the composition of the telomerase holoenzyme is more complex.  In addition to TERT and TER, at least five other proteins contribute to the mature, active telomerase RNP in human cells (Egan and Collins, 2010).  Four of the five proteins belong to the H/ACA family of proteins, including dyskerin, Nhp2, Nop10, and Gar1. The fifth component of the telomerase holoenzyme is known as TCAB1.  Other factors, including 14-3-3, pontin, reptin, Hsp90, p23, and hEST1A and hnRNPs associate with telomerase in a cell cycle- and developmental stage-specific manner. These factors play transient roles in the biogenesis, correct intracellular trafficking and localization, chaperone, and general regulatory roles on the enzyme’s activity in the cell.  TERT TERT was identified as an RT-like polypeptide through sequence analysis shortly after its discovery in S. cerevisiae and Euplotes aediculatus (Lingner and Cech, 1996; Lingner, Hughes et al., 1997).  Since the initial discovery of these two TERTs, subsequent work has identified and characterized over 40 TERTs or TERT-like proteins in eukaryotes that, with few exceptions, share a common domain organization (Autexier and Lue, 2006; Wyatt, West et al., 2010). There are three distinct domains within TERT: i) an N-terminal extension ii) the RT domain and iii) a C-terminal extension (CTE) (Fig. 1A). The N-terminus of TERT is relatively long at approximately 400 amino acids, and can be divided into two functionally important domains: the telomerase essential N-terminal (TEN) domain and the telomerase RNA binding domain (TRBD).  As its name suggests, the TRBD interacts with TER, and does so via its cognate RNA Recognition Motif (RRM) (Bryan, Goodrich et al., 2000b; Bosoy and Lue, 2001; Lai, Mitchell et al., 2001; Lai, Miller et al., 2003; O'Connor, Lai et al., 2005).  In humans, regions within the TRBD of human TERT play an important   7 Figure 1.  TERT and TER.  A.  Functional domain organization of human TERT.  B.  Domain organization and secondary structure of human TER.  C.  Enlarged template region of TER, delineating the alignment and template domains. 5’ 3’ UTR !"#$%&'()*+$,#$(-'.( +/0+1.&)'( 2"#$%&'()*+$,#$(-'.( UTR GQ CP QFP T 12 A B’ C D E E-I E-II E-III E-IV 34 0$&5*)#$+%$6'.(78 38 !!!!!!!!!!"##$"""##$" ! 0$&5*)#$ 1.&)'( 9*'6(&$(# 1.&)'( 78 38 0$&5*)#$ %$6'.( :-$;1.<(.#+1.&)'( 2/=>2/3+1.&)'( ?>929 1.&)'( 9 2@ 29@+A., BCDE.#'F+7   8 catalytic role in the enzyme that is independent of its RNA binding function (Beattie, Zhou et al., 2000).  More specifically, the T domain of human TRBD participates in the rate of template copying during catalysis in vitro, and is only moderately related to TER binding (Drosopoulos and Prasad, 2010).  The high-resolution structure of the Tetrahymena thermophilia TRBD corroborates the functional studies, indicating its importance in TER binding and telomerase activity (Rouda and Skordalakes, 2007). The TEN domain has been characterized through in vitro and cell-based work in yeast, ciliates and human.  Deletion of the TEN domain in human TERT abolished telomerase activity in vitro (Bachand and Autexier, 2001).  Subsequent analysis of the crystal structure of the N- terminal domain of Tetrahymena TERT demonstrated DNA-binding motifs in the TEN region (Jacobs, Podell et al., 2006).  Indeed, the TEN domain of Tetrahymena and humans binds single stranded telomeric DNA in vitro (Wyatt, Lobb et al., 2007; Finger and Bryan, 2008; Sealey, Zheng et al., 2010), and is suggested to remain associated with ss DNA during catalysis (Romi, Baran et al., 2007).  Interestingly, the human TEN domain also contains amino acid residues that, while essential for telomerase activity and telomere maintenance in human cells, are not important for DNA binding (Wyatt, Tsang et al., 2009; Sealey, Zheng et al., 2010).  In vitro studies using Tetrahymena TERT support the dual-function of the TEN domain in both enzyme activity and DNA binding (Zaug, Podell et al., 2008).  In addition, a region within the TEN domain known as the ‘dissociates activities of telomerase’ (DAT) has been implicated in directing telomerase to the telomeric substrate in human cells (Armbruster, Banik et al., 2001; Armbruster, Etheridge et al., 2003), a function which could be important in the localization of the enzyme and/or the correct positioning of the catalytic site on telomeric DNA (Lee, Wong et al., 2003).  In summary, the N-terminus of TERT is important in both substrate recognition and catalysis. The RT domain of TERT is the catalytic centre of telomerase, and contains the seven universally conserved RT motifs 1, 2, A, B’, C, D, and E (Xiong and Eickbush, 1990; Lingner,   9 Hughes et al., 1997; Nakamura, Morin et al., 1997)(Fig 1A).  Given the significance of the RT domain in telomerase activity, it has been thoroughly investigated and characterized through functional mutagenesis studies.  Mutation of conserved residues in the RT domain of TERTs from yeast (both S. cerevisiae and S. pombe), Tetrahymena, and humans cause either complete loss or substantial decrease in telomerase activity in vitro compared to WT TERT (Counter, Meyerson et al., 1997; Harrington, Zhou et al., 1997; Nakayama, Tahara et al., 1998; Bryan, Goodrich et al., 2000a; Haering, Nakamura et al., 2000).  The RT domain can be organized into two putative subdomains, the ‘fingers’ and ‘palm’ domains, composed of motifs 1- A and B’-E, respectively (Lingner, Hughes et al., 1997).  The fingers and palm nomenclature allude to the right hand structure of many nucleic acid polymerases (Joyce and Steitz, 1994; Steitz, 1999).  Typically, the fingers domain interacts with the nucleic acid substrate while the palm domain contains the catalytic site.  The fingers and palm domains of TERT are connected by a ‘primer grip’ region, which is implicated in ss DNA binding (Peng, Mian et al., 2001; Wyatt, Lobb et al., 2007; Gillis, Schuller et al., 2008; Mitchell, Gillis et al., 2010).  The RT domain also contains a large ‘insertion in fingers’ domain (IFD), which is typically found in TERTs, but not other RTs.  The IFD is implicated in stabilizing protein-protein interactions in TERT (Lue, Lin et al., 2003; Gillis, Schuller et al., 2008). An integral feature of the RT domain of TERTs is the triad of aspartic acid residues located in motifs A and C, which are critical to telomerase catalysis in vitro (Counter, Meyerson et al., 1997; Nakayama, Tahara et al., 1998; Haering, Nakamura et al., 2000).  The necessity of these aspartic acid residues in catalysis strongly suggests TERT uses a chemical mechanism for polymerization that is similar to nearly all nucleic acid polymerases (Steitz, 1999; Autexier and Lue, 2006). While the putative fingers and palm domain are found in the RT domain of TERT, the putative thumb domain is located within the CTE (Gillis, Schuller et al., 2008).  There is weak sequence conservation in this region among TERTs, which suggests it may have a species-   10 specific function. Mutations in the C-terminus of human TERT affect enzyme activity (Hossain, Singh et al., 2002; Huard, Moriarty et al., 2003), telomere length maintenance (Banik, Guo et al., 2002) and subcellular localization (Seimiya, Sawada et al., 2000).  Telomere maintenance and enzyme activity is also affected by mutagenesis of the C-terminus in S. cerevisiae (Peng, Mian et al., 2001).  Comparison of the crystal structure of Tribolium castaneum TERT with HIV RT (Gillis, Schuller et al., 2008) supports the functional studies that suggest its role as the ‘thumb’ domain of telomerase (Hossain, Singh et al., 2002; Finger and Bryan, 2008).  Further evidence of this function comes from the structural analysis of T. castaneum TERT bound to a DNA-RNA hybrid, which identified secondary structures within the C-terminus implicated in stabilization of the RNA-DNA heteroduplex (Mitchell, Gillis et al., 2010).  TER and H/ACA proteins Full-length, mature TER is a small, non-coding RNA of 451 nt(Feng, Funk et al., 1995). Telomerase holoenzyme function is critically dependent on several important conserved primary and secondary structures within TER (Zhang, Kim et al., 2011).  The major functional structures of TER include the core domain, conserved regions 4 and 5 (CR4/CR5), and the box H/ACA domain (Fig. 1B).  Located in the 5’ portion of TER, the core domain contains the template region and a pseudoknot domain.  The template region, which is copied to generate the hexanucleotide telomeric repeat, consists of an 11 nt sequence and can be further divided into the 5 nt alignment domain and the 6 nt template domain (Fig. 1C).  The pseudoknot contains several relevant structural features which when altered through mutagenesis severely impairs telomerase activity (Ly, Blackburn et al., 2003).  TER makes two independent contacts with TERT, one through the core domain (Mitchell and Collins, 2000), and the other through the CR4/CR5 domain (Chen, Opperman et al., 2002).  Together with TERT, the core domain of TER and the CR4/CR5 domain, when reconstituted in vitro, are the minimal requirements for in vitro telomerase activity (Autexier, Pruzan et al., 1996; Mitchell and Collins, 2000).  Thus, both   11 the core and CR4/CR5 domains are catalytically essential and can reconstitute telomerase activity when provided in trans (Tesmer, Ford et al., 1999). The box H/ACA domain structure is not unique to TER.  In fact, it is a defining characteristic of ~100 H/ACA small nucleolar RNAs (snoRNAs) and small Cajal body RNAs (scaRNAs) which help guide the sequence specific pseudouridylation of pre-rRNAs and snRNAs (Meier, 2005; Kiss, Fayet-Lebaron et al., 2010).  Essential to the function of snoRNAs is their assembly into catalytically active RNPs, which is dependent on their stable association with the H/ACA proteins dyskerin, Nhp2, Nop10, and Gar1.  The four H/ACA proteins are necessary for proper biogenesis and targeting of a mature, catalytically active H/ACA RNP to the nucleolus and/or the Cajal bodies (in the case of scaRNPs).  Similar to other scaRNAs, in addition to the box H/ACA motif, TER also contains a Cajal body localization sequence (the CAB box). The newly identified WD repeat domain 79 protein, now commonly known as TCAB1, binds sequence-specifically to the CAB box and is required for successful transport of TER to Cajal bodies.  In addition, TCAB1 retains the telomerase holoenzyme at chromosome ends following the DNA replication phase of the cell cycle.  In summary, the known composition of the telomerase holoenzyme is apparently rooted in its identity as a scaRNP.  As a member of the scaRNP family, it is subjected to the same complex level of biogenesis, assembly and trafficking as other endogenous scaRNPs.  Despite these similarities, the function of telomerase as a DNA repair enzyme brought on different sets of biological regulation of the enzyme’s activity following this common scaRNP biogenesis pathway.  1.2.2.  Catalysis According to the current model of telomerase catalysis, there are essentially three catalysis steps in telomerase-mediated DNA synthesis: DNA binding and positioning, synthesis of the telomeric sequence to the end of the TER template, and translocation and realignment of the   12 catalytic site with the 3’ end of the substrate (Fig. 2).  In vitro, telomerase reverse transcribes the 6 nt template region of TER through the incorporation of deoxynucleotide triphosphates (dNTPs) to the free 3’hydroxyl (OH) group of a ss DNA primer.  The incorporation of individual dNTPs by telomerase is known as nucleotide addition processivity (NAP, also known as type I processivity).  Reverse transcription of the 6 nt template domain is a tightly regulated process and is known in human telomerase to be mediated by regions in the N-terminus of TERT and the P1b helix within the pseudoknot domain of TER (Huard and Autexier, 2004).  After first- repeat synthesis, telomerase can either translocate on the DNA substrate and realign TER in preparation for the synthesis of a second 6 nt repeat, or dissociate from the substrate completely.  The propensity of telomerase to successively synthesize 6 nt repeats is referred to as repeat addition processivity (RAP, also known as type II processivity) and is a unique feature of telomerase amongst reverse transcriptases (Lue, 2004). Telomerase catalysis in human cells appears to be more complex than in vitro, specifically with respect to its mechanism of action at the ends of human telomeres. Telomerase can act both as a processive or distributive enzyme in vivo.  As a processive enzyme, a single molecule of telomerase remains bound to a single DNA substrate and using RAP, synthesizes the necessary number of telomeric repeats.  The distributive mode of action on the other hand, requires multiple molecules of telomerase to act sequentially on a single substrate.  Whether telomerase functions as a distributive or processive enzyme in vivo has been a long-standing question in the field and recent studies have shed some light on the topic. In human cancer cells, telomerase acts processively under homeostatic conditions when telomere length maintenance is required (Zhao, Abreu et al., 2011).  Under non-homeostatic conditions however, when telomeres are being actively extended, telomerase acts distributively. It is not clear whether this is the case in all human cell types, but provides interesting insight into telomerase function in vivo.  In addition to using multiple modes of catalysis, telomerase RAP is also influenced by several intrinsic and extrinsic factors in vivo.   13 Figure 2.  Telomerase catalytic cycle.  Telomerase must recognize and bind its substrate, telomeric DNA (green).  Alignment of the enzyme on the substrate is accomplished through the alignment domain within TER (red). Telomerase adds nucleotides to the 3’ end of its substrate using the template domain in TER.  This activity is referred to as nucleotide addition processivity (NAP).  After copying the 6 nt template domain in TER, the enzyme can translocate on the substrate and participate in another round of copying of the 6 nt template.  The propensity of telomerase to synthesize DNA in blocks of 6 nt is called repeat addition processivity (RAP). !"#$%&'%()&(*+,-.%.+-)'-/) #.-/.-, 012)$3-%4($.$ !""#!!!""#! $%%"& 5’ 3’ 5’ !""#!!!""#! $%%"&&&%%" 5’ 3’ & 5’ $$$$$!""#!!!""#! %%"&&&%%"& 5’ 3’ 5’ 5&'-$6+*'%.+-)'-/) &('6.,-7(-%   14  Intrinsic RAP Factors Five regions within eukaryotic TERTs are known to contribute to RAP: the anchor site (within the N-terminus), the IFD, motif C, motif 3, and the CTE.  The telomerase anchor site, which is found in the TEN domain of TERT, is thought to contribute to RAP by facilitation of template- primer translocation.  The anchor site physically interacts with the primer substrate, thereby preventing a complete enzyme-substrate dissociation during the translocation step.  In addition, at least one amino acid residue in the Tetrahymena anchor site important in RAP plays a role outside of its function in DNA binding (Zaug, Podell et al., 2008). In S. cerevisiae, four conserved amino acid residues within the IFD are also important in template-primer translocation, possibly by stabilizing the RNA-DNA hybrid between the telomerase RNA and DNA primer (Lue, Lin et al., 2003).  In Tetrahymena, an amino residue in motif C of TERT, which contains the catalytic centre of the enzyme, helps facilitate RAP through its role in protein-DNA interaction (Bryan, Goodrich et al., 2000a).  Motif 3, also in the catalytic domain of TERT, is suggested in humans to participate in RAP by affecting RNA-DNA strand separation and realignment after repeat synthesis (Xie, Podlevsky et al., 2010).  Additionally, a region in the C-terminal extension (CTE) domain of human TERT is a determinant of RAP, although its mechanistic contribution is not understood (Huard, Moriarty et al., 2003). With respect to telomerase RNA, both template length and conserved structural elements contribute to RAP.  In human telomerase, the length of the telomerase RNA template region contributes to RAP by affecting RNA-DNA base-pairing interactions during translocation (Gavory, Farrow et al., 2002; Chen and Greider, 2003).  There are other structural elements of the telomerase RNA in human and T. thermophilia telomerase that contribute to RAP by affecting RNA/TERT protein interactions (Lai, Miller et al., 2003; Moriarty, Marie-Egyptienne et al., 2004).     15  Extrinsic RAP Factors The POT1-TPP1 complex, which is an integral component of shelterin, was first identified as an extrinsic RAP factor for human telomerase through biochemical experiments demonstrating a substantial increase in RAP in the presence of POT1-TPP1 compared to telomerase alone or telomerase in the presence of either POT1 or TPP1 alone (Wang, Podell et al., 2007). Subsequent biochemical work has confirmed these data and further characterized the mechanism by which POT1-TPP1 contributes to RAP.  POT1-TPP1 requires only one binding site on a single-stranded telomeric substrate to cause an increase in RAP, and kinetic data indicate that POT1-TPP1 bound to a single-stranded telomeric substrate decreases primer dissociation from telomerase and increases the rate and efficiency of template-primer translocation (Latrick and Cech, 2010).  The POT1-TPP1-dependent increase in RAP requires a sequence-specific interaction between TPP1 and TERT (Zaug, Podell et al., 2010), which occurs between a conserved glycine residue in TERT, Gly100, in the DAT region of the TEN domain. However, the functionality of this increase in processivity has yet to be proven significant in the normal homeostatic maintenance of telomere length. There has also been interest in replication protein A (RPA) as an extrinsic telomerase RAP factor.  Human RPA can inhibit RAP in human and Tetrahymena telomerase at high concentrations, but at low concentrations can stimulate human RAP (Cohen, Jacob et al., 2004; Rubtsova, Skvortsov et al., 2009).  In Tetrahymena, a RPA-like protein, p82 (also called Teb1), stimulates RAP through its C-terminal and DNA-binding domains (Min and Collins, 2009). Interestingly, a different RPA-like protein complex in S. cerevisiae, called CST, participates in telomere protection and mediates the cell-cycle phase specific extension of the  telomeres by telomerase (Li, Makovets et al., 2009; Miyake, Nakamura et al., 2009).      16 1.2.3.  Regulation and Biogenesis Several steps are required for the generation of an active and fully functional telomerase holoenzyme.  Transcription of TERT from its genetic locus is regulated at multiple levels by a vast network of transcription factors. TERT transcription during embryonic development is subjected to alternative splicing mechanisms which can generate multiple, non-functional isoforms of TERT (Yi, White et al., 2000).  These alternate isoforms of TERT are suggested to participate in the regulation of telomerase activity during development and differentiation.  Once translated, the TERT polypeptide associates with chaperone proteins Hsp90 and p23 (Holt, Aisner et al., 1999), which are both important in the assembly of a functional telomerase holoenzyme and its transport to the nucleus (Forsythe, Jarvis et al., 2001; Woo, An et al., 2009; Lee and Chung, 2010). Nuclear retention of TERT is accomplished by its association with the 14-3-3 proteins, which are postulated to mask the nuclear export signal on TERT resulting in its nuclear retention (Seimiya, Sawada et al., 2000), and nucleolin, a phosphoprotein residing in the nucleolus with functions in ribosome biogenesis (Khurts, Masutomi et al., 2004). As with most proteins, TERT is subject to post-translational modifications that ultimately influence its function.  TERT is a substrate for both protein kinase Cα and protein kinase B (Akt). Phosphorylation by protein kinase Cα is required for active telomerase in human T cells (Li, Zhao et al., 1998), and phosphorylation by Akt enhances telomerase activity (Kang, Kwon et al., 1999).  In contrast, telomerase activity is inhibited by protein phosphatase 2A and protein kinase c-Abl (Kharbanda, Kumar et al., 2000).  Rapid downregulation of TERT can be brought on by protein degradation by the proteosome following ubiquitination by the E3 ubiquitin ligase MKRN1 (Kim, Park et al., 2005). Telomerase activity is additionally regulated at the level of holoenzyme assembly.  The biogenesis of the holoenzyme requires a concerted process of scaRNP assembly of TER with H/ACA proteins dyskerin, NHP2, NOP10, and Gar1 (Darzacq, Kittur et al., 2006) and the association of TERT with this RNP complex.  The association of TERT with the scaRNP is   17 known to involve the ATPases pontin and reptin (Venteicher, Meng et al., 2008).  Intracellular trafficking is another important level of regulation of the telomerase holoenzyme.  TCAB1 was recently identified as a telomerase holoenzyme component and is required for localization of telomerase to Cajal bodies (Venteicher, Abreu et al., 2009).  TCAB1-mediated Cajal-body localization has important functional implications for telomere maintenance in human cells (Venteicher, Abreu et al., 2009; Batista, Pech et al., 2011; Zhong, Savage et al., 2011).  The final level of regulation of the functional telomerase holoenzyme is its delivery and access to telomere ends.  Shuttling of telomerase to telomeres occurs during S phase of the cell cycle in a Cajal-body dependent manner (Zhu, Tomlinson et al., 2004; Jady, Richard et al., 2006; Tomlinson, Abreu et al., 2008).  For the remainder of the cell cycle, TERT localizes to subnuclear TERT foci (Tomlinson, Ziegler et al., 2006) in transformed cells and to the nucleolus in primary (non-transformed) human cells (Wong and Collins, 2006). Telomerase activity is detectable in human germline cells from early development through to adulthood (Wright, Piatyszek et al., 1996; Ulaner and Giudice, 1997; Ulaner, Hu et al., 1998).  However, most somatic cells lose telomerase activity after the first 16-20 weeks of development (Wright, Piatyszek et al., 1996), a phenomenon that is primarily due to transcriptional repression of TERT (Collins and Mitchell, 2002).  Some types of adult cells transiently activate telomerase throughout adulthood.  Such cells include activated lymphocytes and several types of adult stem cells (Hiyama and Hiyama, 2007).  An interesting and relevant example of developmental and context-dependent telomerase activity occurs in T- and B- lymphocytes, cells that are integral components of acquired immunity in humans.  T- and B- lymphocytes transiently activate telomerase in response to antigenic activation (Weng, Levine et al., 1995; Weng, Granger et al., 1997).  This strategy allows lymphocytes to compensate for telomere loss that occurs with massive clonal expansion and proliferation that follows positive selection and antigenic activation (Weng, Hathcock et al., 1998), allowing them to extend their   18 replicative capacity—an important trait, given the significance of these cells and their progeny in primary and long-term immune responses.  1.3.  Telomere dynamics: relevance to human physiology and tissue integrity 1.3.1.  Limiting replicative capacity through a telomere counting mechanism A consequence of limiting cell division capacity is the restriction of the regenerative potential of tissues.  Some tissues, especially those with high cellular turnover (e.g., epithelium) and/or high regenerative potential (e.g., liver), depend on the ability of specific subtypes of cells to maintain the capacity to proliferate over time (Conboy and Rando, 2005; Rando, 2006).  With increasing cell divisions, cells in these regenerative reservoirs lose the capacity to further proliferate, which effectively reduces the regenerative capacity of the respective tissue.  Loss of regenerative potential can lead to deterioration of tissues and thus is indirectly responsible for organismal aging (Djojosubroto, Choi et al., 2003; Conboy and Rando, 2005).  Taken together, it is suggested that telomere-length dependent proliferative arrest contributes to the loss of tissue regenerative capacity, providing an indirect link between aging and telomere integrity (Fig. 3).  1.3.2.  Consequences of dysfunctional telomeres and telomerase deficiency Genetic diseases of telomere/telomerase biology The importance of telomerase activity and telomere length in human aging is evident from human diseases of telomerase  dysfunction.  In the inherited degenerative disorder dyskeratosis congenita (DC), patients typically present with phenotypes consistent with deficiencies in highly proliferative tissues (Garcia, Wright et al., 2007; Kirwan and Dokal, 2009).  The classical triad of DC features consists of nail dystrophy, oral leukoplakia, and abnormal skin pigmentation and are present in 80 – 90% patients.  Bone marrow failure is also commonly observed and is responsible for the majority of mortality observed in patients affected by DC.  There are many other features observed in DC patients, overlapping with degenerations commonly seen in the   19 elderly including dental loss, greying of hair, osteoporosis, liver disease, and, interestingly, a predisposition to cancer (de la Fuente and Dokal, 2007).  As such, DC is generally accepted as a premature aging syndrome. The common underlying cause of these tissue abnormalities is short telomeres, which are observed in all cases of DC (Vulliamy, Marrone et al., 2006; Alter, Baerlocher et al., 2007).  In support of this notion is the fact that autosomal dominant DC shows anticipation.  Successive generations of patients affected by DC are observed with increasing severity of the disease and earlier onset, proportionate to the progressive shortening telomeres inherited from the previous generation (Vulliamy, Marrone et al., 2004).  It is now known that DC is caused by inherited mutations in either TERT, TER, Nhp2, Nop10, Gar1, dyskerin, TCAB1 (the known telomerase holoenzyme components) or TIN2 (part of the shelterin complex) (Zhong, Savage et al.; Heiss, Knight et al., 1998; Vulliamy, Marrone et al., 2001; Armanios, Chen et al., 2005; Vulliamy, Walne et al., 2005; Fu and Collins, 2007; Marrone, Walne et al., 2007; Savage, Giri et al., 2008). Other genetic diseases of telomere maintenance include Hoyeraal-Hreidersson syndrome, aplastic anemia and idiopathic pulmonary fibrosis. Hoyeraal-Hreidersson syndrome is considered to be a more severe form of DC (Borggraefe, Koletzko et al., 2009).  It shares clinical phenotypes with DC but exhibits earlier onset of symptoms and additional clinical abnormalities, including cerebellar hypoplasia, microcephaly, immunodeficiency and growth retardation (Knight, Heiss et al., 1999).  Mutations in both dyskerin and TERT have been identified in patients with Hoyeraal-Hreidersson syndrome. Aplastic anemia is a disease of defective bone marrow and is characterized by an overall reduction in blood cells from all lineages.  Telomere length has found to be reduced in sub-populations of familial aplastic anemia patients compared to healthy controls (Ball, Gibson et al., 1998; Vulliamy, Marrone et al., 2002), and mutations in either TERT or TER have been found in 5-10% of aplastic anemia patients (Vulliamy, Marrone et al., 2002).  Patients with idiopathic pulmonary fibrosis have shorter-than-normal telomeres, and their telomere length corresponds to disease state   20 (Cronkhite, Xing et al., 2008).  Mutations in both TERT and TER have been identified in some patients with idiopathic pulmonary fibrosis (Armanios, Chen et al., 2007) and predispose individuals to shorter telomeres than those individuals with idiopathic pulmonary fibrosis but without underlying mutations in TERT or TER (Cronkhite, Xing et al., 2008).  These human diseases are now being viewed as a spectrum of telomere dysfunction disorders.  The variations in clinical presentations highlight the complex relationship between tissue renewal capacity and telomere maintenance biology in the context of lifestyle and other disease predisposition factors.  The important role of telomere maintenance in human physiology , and the overlapping clinical symptoms between telomere maintenance deficiency syndromes provides strong evidence in support of a role for telomere length in normal human tissue aging. Epidemiological studies on telomere length and age-related diseases The correlation of short telomere length to human age-related diseases has been investigated in numerous clinical epidemiological studies.  Much of the data currently address whether or not telomere length is associated with cardiovascular disease (CVD), but there are a few interesting studies investigating telomere length and its possible relationship to psychological stress and human longevity.  The data described in this section provide insight into the complex interplay of hereditary, environmental, and lifestyle factors and their potential roles in telomere length maintenance in aging and age-related diseases. In a study examining centenarians and their offspring, significantly shorter telomere lengths were found in people with age-related diseases, including hypertension, diabetes, and the metabolic syndrome (Atzmon, Cho et al., 2010).  Centenarians with impaired cognitive function had shorter telomeres than those with normal cognitive function and longer telomeres were associated with lipid profiles of healthy aging.  Similarly, in a study of patients with premature myocardial infarction (MI), age- and sex-adjusted mean peripheral blood mononuclear cell (PBMC) telomere restriction fragment (TRF) length was significantly shorter in   21 Figure 3.  Telomere dynamics and proliferative capacity.  A. Most somatic cells (solid blue line) lose telomeric DNA with each cell division until the short telomere checkpoint is reached (red dotted line), setting an upper limit to their replicative lifespan.  Some cell types (e.g., germline and embryonic stem cells; solid green line) are able to maintain telomere length, and thus their replicative capacity, indefinitely.  In cells with transient telomerase activity (solid orange line) telomeres are extended periodically, but not sufficiently enough to counteract the overall loss that occurs with time.  These cells have a higher proliferative capacity than somatic cells, but eventually reach a point of proliferative arrest.  B. Implications of dysfunctional telomere/telomerase biology on maintenance of tissue integrity. Within a given tissue, the demand for cellular renewal is assumed to remain relatively constant over time (blue line).  However, the fraction of dividing cells within the tissue decreases over time as cells undergo proliferative arrest due to the short-telomere checkpoint.  When the fraction of dividing cells can no longer meet the demand for cellular renewal (red arrows), tissue integrity cannot be optimally maintained, leading to tissue aging. An underlying disruption in telomere or telomerase function can lead to accelerated tissue aging. !"# $%&'() *++, -*.#+&/*('*++,0(,%*#('*++, !1".%(%*+"#*.* '1*'23"&/% 4 * +" # * .* (+ * / 5 %1 )*++(6&7&,&"/, )*++,(8&%1(%.$/,&*/%( %*+"#*.$,*($'%&7&%9 ! "# $ %& ' ( )' *) + &, &+ &( - )$ . // 0 1. 2 # ( + )*' " $ . //3 /# ")". ( . 4 # / 5&2. 6'"2#/ 7&%8) 696:5;0 < =   22 patients with premature MI compared to controls, a difference that was not accounted for by other cardiovascular risk factors (Brouilette, Singh et al., 2003). When compared to individuals in the highest quartile for TRF length, the risk of MI was increased significantly (approximately three-fold) in individuals with shorter-than-average telomeres.  In a subsequent study of normal individuals aged 60 and over, individuals with shorter telomeres in PBMCs had an approximately two-fold higher overall mortality rate compared to those with longer telomeres (Cawthon, Smith et al., 2003).  The increase in overall mortality was mainly due to an approximately three-fold higher mortality rate from heart disease and an approximately eight-fold higher mortality rate due to infectious disease. Mean PBMC TRF length was also found to be significantly shorter in hypertensive males with atherosclerosis compared to hypertensive males without atherosclerosis. Multivariate analysis identified telomere length as a significant predictor of atherosclerosis (Benetos, Gardner et al., 2004).  Telomere length was also indicated as an important factor in CVD in a study of individuals aged 65 and older (Fitzpatrick, Kronmal et al., 2007).  Short PBMC TRF length was significantly associated with an increased risk of MI and stroke in the younger half of the study population (individuals aged 73 or younger).  The increased risk was approximately three-fold for both MI and stroke.  The authors also found a significant or borderline inverse association between TRF length and several CVD risk factors, including diabetes, glucose, insulin, diastolic blood pressure, and interleukin-6.  In a more comprehensive study, aimed at investigating whether telomere biology was associated with physiological signs of stress and CVD biomarkers, telomere length and telomerase activity were measured in PBMCs from 62 healthy women aged 20-50 (Epel, Lin et al., 2006).  Low telomerase activity was found to be associated with increased excretion of stress hormones and well-established risk factors for CVD.  However, telomere length was not found to be associated with CVD risk factors.  The authors interpreted these data as suggesting that low telomerase activity in PBMCs might precipitate shorter telomeres later in life, and that   23 low telomerase activity in PBMCs of younger, healthy women might be a preclinical marker of disease. However, the heterogeneity of PBMC complicates this simple interpretation, as a different proportion of naive, mature and memory immune cell types are known to differ in their mean telomere length, even within an individual. Psychological stress has also been found associated with shorter telomeres (Epel, Blackburn et al., 2004).  Both telomere length and telomerase activity in PBMCs were found to negatively correlate with perceived psychological stress in a study of 58 healthy women. Chronicity of perceived stress was also negatively correlated with telomere length in this population.  Interestingly, oxidative stress was positively correlated with perceived stress in this population of women.  The authors suggest that increased perceived stress might lead to increased oxidative stress, which, based on data observed in vitro (von Zglinicki, 2002), might lead to accelerated telomere attrition. The epidemiological studies addressed here provide evidence for a link between telomere length and biomarkers of healthy human aging.  While these observations did not provide direct biological mechanisms as that described for DC and other diseases of telomerase dysfunction, it provides further insight into the complexity of telomere biology. In humans, genetic inheritance, gene-environment interactions, controllable, as well as uncontrollable lifestyle factors all act in concert to determine the final telomere length maintenance level. Accordingly, depending on the confounding disease state and/or health status, tissue compartments that bear the highest burden of renewal demand or harbor the lowest capacity for telomere maintenance are predicted to show the highest level of telomere dysfunction and the first to manifest clinical symptoms.       24 1.4.  HIV infection and AIDS 1.4.1.  Biology of HIV infection The human immunodeficiency virus (HIV) is a lentivirus belonging to the retrovirus family and is the pathogen that causes the acquired immunodeficiency syndrome (AIDS).  HIV preferentially infects cells of the human immune system that express CD4, including T lymphocytes, macrophages, and dendritic cells (Chinen and Shearer, 2002).  To gain entry, proteins in the viral envelope dock on the CD4 cell surface molecule.  Either chemokine receptor type 5 (CCR5) or chemokine receptor type 4 (CXCR4), which are expressed on the plasma membranes of CD4+ T lymphocytes, are used as co-receptors in the process of viral entry. After viral entry, viral capsids release the RNA genome and the accompanying viral proteins, including the HIV reverse transcriptase. HIV RT copies the RNA genome into cDNA, which is subsequently transported to the nucleus.  Once in the nucleus, viral cDNA is randomly integrated into the host genome through viral integrase activity.  Production of progeny viruses depends upon the transcription of viral cDNA via host transcriptional machinery.  During new virion assembly, multigenic viral transcripts are translated into long polypeptides and require the function of viral proteases for processing.  The maturation process of these viral proteins within the budding virion is crucial for the next round of HIV infectivity. HIV is spread through either lysis of an infected cell which releases newly assembled virions or by the fusion of an infected cell with an uninfected cell (Sigal, Kim et al., 2011).  1.4.2.  Pathology of HIV infection: CD4+ T lymphocytes A defining characteristic of HIV infection is CD4 T+ lymphocyte depletion.  While the process is not completely understood, it is known is that HIV infection can cause CD4+ T-cell death.  CD4+ T cell death primarily occurs because of virus-induced apoptosis (Wan and Chen, 2010), but also through killing by cytotoxic (CD8+) T cells (Mehandru, Poles et al., 2007).  HIV can induce cell death in T lymphocytes by inducing apoptosis through both the intrinsic and   25 extrinsic pathways (Chinen and Shearer, 2002; Wan and Chen, 2010).  In untreated HIV infection, the most dramatic decrease in T cell numbers occurs acutely within the first few weeks of infection (Douek, Picker et al., 2003).  Infected CD4+ T cells that survive often harbour latent HIV, and this is the basis for chronic infection, another trademark of HIV infection.  Chronic HIV infection is, on average, a 10-year endeavour and is characterized by progressive T cell depletion and increased viral load.  In most untreated individuals, chronic infection eventually causes the CD4+ T lymphocyte concentration to drop below 200 cells per microlitre of peripheral blood, which is half of the normal concentration.  If left untreated, the immunodeficiency caused by chronic HIV infection will leave individuals susceptible to the opportunistic infections and cancers typical of AIDS, with a high rate of mortality.  1.4.3.  HAART While gene therapy- and vaccine-based strategies targeting HIV are currently being explored (Mitsuyasu, Merigan et al., 2009; Holt, Wang et al., 2010; Chhatbar, Mishra et al., 2011; Korber and Gnanakaran, 2011; Lopalco and Bomsel, 2011), the current standard of therapy in HIV infection is a drug therapy known as highly active antiretroviral therapy, or HAART. HAART involves the regular intake of drugs that hinder the ability of HIV to successfully propagate in host cells.  The purpose of HAART is to increase disease-free survival through suppression of viral replication and preservation of immunologic function; HAART cannot eliminate the HIV infection.  Drug classes and mechanisms of action There are currently six unique drug classes used in HAART: entry inhibitors, fusion inhibitors, integrase inhibitors, protease inhibitors (PIs), nucleoside reverse transcriptase inhibitors (NRTIs), and non-nucleoside reverse transcriptase inhibitors (NNRTIs) (Table 1).  The first three classes of ARVs are relatively new agents and are rarely used in first-line anti-retroviral therapy.   26 There is only one FDA-approved entry inhibitor used in HAART, maraviroc.  HIV uses chemokine receptors CXCR4 and CCR5 as co-receptors to the CD4+ molecule to enter host cells.  Maraviroc acts as a CCR5 antagonist, preventing the binding of HIV and thereby its entry into host cells.  Like the entry inhibitor class, only one FDA-approved fusion inhibitor, enfuvirtide is available for current HAART.  Enfuvirtide binds glycopeptide 41, a viral coat protein found in the HIV envelope, which prevents the viral envelope from fusing with the cell membrane and thereby stopping the virus from entering the host cell. Integrase inhibitors inhibit HIV integrase, the enzyme responsible for inserting the HIV genome into the host’s chromosomal DNA. The absence of host genome integration can help to prevent the establishment of chronic infection. PIs inhibit HIV protease, which is needed for the post-translational processing of HIV peptides.  As new virions are budding from the infected host, long polypeptide chains must be proteolytically processed.  The inhibition of this process prevents the budding virion from establishing a new infection in a naive host.  Lastly, NRTIs and NNRTIs (N/NRTIs) both target HIV reverse transcriptase, the enzyme responsible for copying the virus’s RNA genome into dsDNA. NRTIs structurally mimic nucleosides endogenous to human cells, but lack the three- prime hydroxyl group necessary for incorporation into a growing nucleotide chain.  After intracellular phosphorylation to their triphosphate form, NRTIs inhibit HIV RT by competing with endogenous dNTPs (deoxynucleotide triphosphates).  NNRTIs inhibit HIV RT in a non- competitive manner.  These agents bind HIV RT in a hydrophobic pocket and restrict its movement, effectively inhibiting further nucleotide polymerization (Ivetac and McCammon, 2009).  Typical first-line HAART involves two NRTIs in combination with either an NNRTI or a PI (Hammer, Eron et al., 2008).  Newer classes of drugs, such as fusion/entry inhibitors are generally only used in treatment-experienced patients.   27  Figure 4.  Structure of N/NRTIs used in this work.  NRTIs are shown as their prodrug form.  TDF and ABC must both undergo additional metabolic steps before phosphorylation can occur.  The metabolized forms (TFV and CBV) of both drugs are shown below their respective prodrugs.  NNRTIs are shown as their active forms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dverse effects of HAART HIV infection with accompanying HAART is associated with numerous pathophysiological symptoms, some of which are due to the viral infection and some of which are due to the xenobiotic agents used in HAART.  As HAART usage becomes better tailored and more effective, HIV-infected individuals are living longer and more productive lives (Luther and Wilkin, 2007).  But longer lifespan in this population means an increased exposure to antiretroviral drugs, as HAART is life-long once started.  It is important to understand the adverse effects of the individual agent and the combinatorial drug regimens used in HAART in the context of onset.  Most adverse drug-effect studies focus on the short-term, immediate toxicity of a drug therapy, which is not adequate in the cases of anti-HIV therapies.  As in the context of HAART, adverse effects that require a longer incubation time/drug exposure time could be clinically significant but are under-investigated. As fusion/entry inhibitors are the ARVs most recently approved, there are few data available on their post-market adverse drug effects.  Maraviroc appears to be well tolerated in humans, with upper respiratory tract infections, cough, fever, and rash among the most frequent adverse effects (Yost, Pasquale et al., 2009).  Enfuvirtide also appears to be well tolerated, with injection site reactions as the most common adverse effect (Joly, Jidar et al., 2010).  As these drugs continue to be used and studied as part of HAART, longer-term adverse side effect data will become available. Much more data is available for PIs, NRTIs, and NNRTIs, as these drugs have been used clinically for longer period of time than entry/fusion inhibitors in HIV therapy.  The main treatment-limiting factor for PIs is gastrointestinal toxicity (Ortiz, Dejesus et al., 2008), which might be due to disruption of the intestinal epithelial barrier through sustained endoplasmic reticular (ER) stress via an unidentified mechanism (Wu, Sun et al., 2010).  Some PIs can lead to jaundice through inhibition of the UGT1A1 enzyme (Rayner, Esch et al., 2001), and are also known to cause kidney stones (Saltel, Angel et al., 2000; Chan-Tack, Truffa et al., 2007).   29 Furthermore, PIs are known to be associated with longer-term adverse effects including increased risk of myocardial infarction (MI) (Lang, Mary-Krause et al., 2010; Worm, Sabin et al., 2010). Another major long-term concern with PI treatment is lipodystrophy.  Lipodystrophy is generally defined as defective fat metabolism and can be considered both a cosmetic concern and a serious long-term health concern for individuals actively taking PIs.  In HIV positive individuals on PI-containing HAART, lipodystrophy usually involves body composition changes, including apparent fat redistribution with a relative increase in abdominal fat and peripheral lipoatrophy, and underlying metabolic alterations leading to insulin resistance and hyperlipidemia (Flint, Noor et al., 2009).  At the biochemical level, many of the changes associated with PI therapy resemble changes observed in normal individuals with the metabolic syndrome, including hypertriglyceridemia, low HDL cholesterol levels, and insulin resistance (Grunfeld and Tien, 2003).  There is relatively little known about the biological mechanism underlying PI-induced dyslipidemia, and it has been difficult to tease apart the virus-specific effects from the HAART-induced effects, a problem further complicated by the fact that NRTI use can also lead to dyslipidemia.  However, both in vivo and in vitro studies have led to a better understanding of the underlying mechanism of this phenomenon (Hruz, Murata et al., 2002; Murata, Hruz et al., 2002; Noor, Seneviratne et al., 2002; Hertel, Struthers et al., 2004; Lee, Rao et al., 2007; Flint, Noor et al., 2009). NNRTIs can be considered relatively benign drugs with respect to adverse effects amongst the anti-HIV agents.  There are however a few important caveats.  The most prominent adverse effect of NNRTI use is the development of a rash, which has been observed in 10-17% of individuals taking NNRTIs (Carr and Cooper, 2000).  Most rashes occurring with NNRTI are mild to moderate in severity and can often be treated.  In severe cases, patients would be switched to another antiretroviral drug.  Hypersensitivity reaction is known to occur with both NVP and EFV treatment.  An NNRTI-induced hypersensitivity reaction is characterized by fever,   30 rash, myalgia, abdominal pain, lethargy, respiratory distress, and/or renal or hepatic failure, and can lead to a serious and possibly fatal anaphylactic reaction if not treated properly.  The underlying mechanism of NVP-induced hypersensitivity reaction is suggested to be related to a specific metabolite of the drug that can form a reactive compound in the skin (Popovic, Shenton et al., 2010), but unequivocal evidence of this phenomenon is lacking.  The mechanism of EFV- induced hypersensitivity reaction is not known. NRTIs are some of the worst offenders in HAART-induced toxicity, primarily because they are structural analogs of endogenous nucleosides/nucleotides and thus have the ability to inhibit endogenous polymerases.  The majority of NRTI-induced toxicity has been attributed to mitochondrial damage and dysfunction, as a consequence of inhibition of the mitochondrial (mt) DNA polymerase (DNA polymerase γ) (Koczor and Lewis, 2010).  The generally accepted theory of NRTI-induced mt toxicity is that inhibition of pol γ leads to an increase in mtDNA depletion and damage, which can cause dysfunction of the electron transport chain leading to enhanced production of reactive oxygen species (ROS) and further mtDNA damage.  The consequences of NRTI-induced mt dysfunction include lactic acidosis, which can in some cases be life threatening, muscle myopathy, renal dysfunction (especially in the case of TFV), peripheral neuropathy, and, similar to PIs, lipodystrophy and fat redistribution.  1.4.4.  Accelerated aging in HIV infection with HAART Despite the fact that the effects of HAART agents are relatively well understood, it can be difficult to separate the HAART- and HIV-specific effects, and even more difficult to separate those effects from natural human aging and age-related disease due to underlying risk factors. This difficulty is compounded further by the fact that the HIV-positive population is living much longer with the advent of successful antiviral therapy (Effros, Fletcher et al., 2008; Simone and Appelbaum, 2008).  Indeed, many of the adverse HAART treatment effects outlined above, including dyslipidemia, cardiovascular disease, neurological dysfunction, and hepatic and renal   31 disorders can occur during the course of natural human aging, and HIV infection with HAART appears to cause these problems to occur earlier than in normal, healthy individuals (Patel and Crane, 2011; Zhao and Goetz, 2011).  Thus, HIV infection with accompanying HAART appears to accelerate aging.  Anecdotal evidence indicates that accelerated aging in HIV infection with HAART can also be observed phenotypically in tissue compartments such as skin and hair, which depend on high cellular turnover for adequate tissue maintenance.  These interesting correlative observations seem to indicate the presence of regenerative deficiencies in tissues with high cellular turnover, suggesting that proliferative capacity of cells in these tissues may be diminished.  1.5.  HIV and telomere/telomerase biology 1.5.1.  Telomere/telomerase biology in HIV infection with HAART Relatively little research has been undertaken to investigate the possible effects of HIV and HAART on telomere maintenance in vivo.  The conclusions drawn from clinically based research are conflicting.  In comparing peripheral T lymphocytes between long-term HIV- infected survivors and age-matched controls, no difference in either telomere length or telomerase activity was found (Tucker, Jenkins et al., 2000).  Similarly, no difference in the telomere length from peripheral, lymph node, or bone marrow T lymphocytes was observed between HIV-infected and uninfected patients (Wolthers, Otto et al., 1999).  Conversely, telomeres in peripheral-blood mononuclear cells (PBMCs) were shorter in HIV-infected patients compared to uninfected controls (Bestilny, Gill et al., 2000), and in separate studies, telomerase activity was decreased in both peripheral lymphocytes (Ballon, Ometto et al., 2001) and lymphocyte progenitors (Vignoli, Stecca et al., 1998) in HIV-infected patients compared to uninfected controls. There are two studies published to date investigating whether HAART affects telomere maintenance. HIV-infected patients being treated with DDI, AZT, or DDC (dideoxycytidine) in   32 combination or alone have decreased telomerase activity in peripheral T lymphocytes relative to uninfected controls (Wolthers, Otto et al., 1999).  After two years of aggressive anti-retroviral (ARV) drug treatment, HIV-infected individuals demonstrated accelerated telomere attrition compared to non-drug treated, uninfected controls (Hotchkiss, Pehrson et al., 1999).  In an animal study, offspring of pregnant mice that were given AZT during the last third of their gestational period showed telomere shortening in liver and brain tissues compared to untreated controls (Olivero, Anderson et al., 1997).  In vitro studies have been in agreement with respect to the inhibitory effect of HIV on telomerase.  Either an HIV transcription factor (Franzese, Comandini et al., 2004) or the whole HIV virus are able to downregulate telomerase activity (Reynoso, Minces et al., 2006; Franzese, Adamo et al., 2007).  Given the well-documented, natural inter-individual variations of TRF in human populations, the lack of correlation of HIV infection (either with or without HAART) with TRF size is likely due to inadequately powered studies,  1.5.2.  In vitro studies on the effect of NRTIs on telomere/telomerase biology The question of whether NRTIs might interact with and inhibit telomerase was first posed as a result of simple logic: NRTIs are chain-terminating drugs, NRTIs can inhibit DNA synthesis by HIV RT and other nucleic acid polymerases, so NRTIs might also inhibit telomerase.  Telomere shortening caused by treatment with the dTTP analogs azidothymidine (AZT) and stavudine (d4T) was first observed in Tetrahymena (Strahl and Blackburn, 1994).  In the same study, AZT- triphosphate (AZT-TP), the active form of AZT, inhibited Tetrahymena telomerase in vitro.  This study established the potential for NRTIs to impact telomere and telomerase biology, and sparked several more studies on the topic. In immortalized, telomerase-expressing Chinese hamster ovary cells, [3H]-labeled AZT was incorporated into telomeric DNA (Gomez, Kassim et al., 1995).  Incorporation of [3H]- labeled AZT was suggested to be telomerase specific, as incorporation of the [3H]-AZT was   33 substantially less in telomeric DNA of non-telomerase-expressing cells.  In mouse embryonic fibroblasts, both AZT and the dGTP analog carbovir (CBV, the partial active form of abacavir) inhibited telomerase (Yegorov, Chernov et al., 1996).  AZT completely inhibited telomerase activity in a mouse mammary carcinoma cell line, but telomere length was not affected (Tejera, Alonso et al., 2001).  These studies demonstrate the inhibitory effect of both AZT and CBV on telomerase.  However, it is important to note that they were performed in the mouse, and that telomerase expression, regulation and functions are all very different between rodents and humans.  AZT and CBV have also been investigated for their effects on human telomerase and telomere length maintenance.  As the importance of telomerase activity in human cancers became clear, there was increasing interest in discovering agents that inhibited the enzyme. Indeed, all of the work investigating NRTIs and human telomerase was done in human lines of transformed or cancerous cells.  In immortalized human T- and B-lymphocyte cell lines, AZT but not d4T caused telomere shortening, and AZT-TP inhibited human telomerase in vitro (Strahl and Blackburn, 1996).  The lack of observable effects of d4T on telomere length might have been due to the inherently large variability in telomere length in the T- and B-lymphocyte cell lines.  AZT also inhibited telomerase and caused telomere shortening in human breast cancer cells (Olivero, Anderson et al., 1997; Ji, Rha et al., 2005), colon cancer cells (Brown, Sigurdson et al., 2003), and leukemia cells (Liu, Takahashi et al., 2007).  In addition, AZT-mediated telomerase inhibition was measured in a human hepatoma cell line (Fang and Beland, 2009), and telomere shortening was observed in cervical cancer cells (Gomez, Tejera et al., 1998). The only other NRTI studied to date, Abacavir (ABC), inhibited telomerase in human medulloblastoma cells (Tendian and Parker, 2000; Rossi, Russo et al., 2009).  The active form of ABC, CBV-TP, also inhibited human telomerase in vitro.  These studies demonstrate the ability of both AZT and ABC to inhibit telomerase activity in human cells.  Direct evidence of telomerase inhibition is apparent from the in vitro telomerase   34 activity assays using the active forms of these drugs (i.e., AZT-TP and CBV-TP).  It is clear that AZT has a negative effect on telomere maintenance in human cells with constitutive telomerase activity.  Although there are key differences between rodent and human telomerase, the animal work lends further support to the telomerase-inhibitory effect of both AZT and CBV. The effects of other NRTIs on telomere length maintenance by telomerase are less certain. Only one study investigated the effects of d4T on telomere maintenance, and none on the effects of d4T-TP on telomerase activity in vitro.  It is not known whether ABC affects telomere maintenance. Furthermore, the effects of the newer generations of NRTIs, such as tenofovir (TFV) and didanosine (ddI), and the NNRTIs nevirapine (NVP) and efavirenz (EFV) on telomere maintenance and telomerase activity have yet to be investigated.  1.5.3.  Similarities between HIV RT and TERT Based on the competitive mechanism of action of the NRTI class of drugs, it is likely that all NRTIs used in HAART, aside from the dCTP analogs, will inhibit telomerase.  However, it is much less clear whether NNRTIs will affect telomere synthesis by telomerase, in a manner that is consistent with their actions on the HIV RT.  Previous studies on the mechanistic and structural comparisons between TERT and HIV RT provide predictions and molecular insights into whether this could be possible. HIV-1 RT is required for successful viral infection (Castro, Loureiro et al., 2006). Functional HIV-RT is a heterodimer composed of a 66 kDa and a 51 kDa polypeptide, called p66 and p51, respectively (Jacobo-Molina and Arnold, 1991).  p66 is responsible for the HIV RT catalytic activity, including nucleotide polymerization and RNAse H activity (Le Grice, Naas et al., 1991).  p51 is derived from p66 through proteolytic cleavage, and in the process its RNAseH activity is lost and it maintains no catalytic function.  Instead, p51 plays a structural role within the active enzyme providing a base for p66 (Chattopadhyay, Evans et al., 1992).  There are three functionally important domains in p66: thumb, fingers, and palm.  Both the thumb and   35 the fingers domain are important in enzyme fidelity and efficiency.  The palm domain contains the catalytic site (Castro, Loureiro et al., 2006). There is biochemical data describing both mechanistic and structural similarities between HIV RT and TERT.  To date, the only crystal structure of the TERT molecule in its entirety is that from the flour beetle T. Castaneum (Gillis, Schuller et al., 2008).  Similar to HIV RT p66, T. Castaneum TERT was sub-divided into a thumb, fingers, and a palm domain. Furthermore, T. Castaneum TERT and HIV RT share high structural similarity with respect to the spatial arrangement of the fingers and thumb domains.  The location of the active site down to the structure of the nucleotide binding pocket when bound to a substrate are also highly conserved between the two structures (Gillis, Schuller et al., 2008).  Subsequent biochemical work solving the structure of T. Castaneum TERT bound to a DNA:RNA hybrid as a model of telomerase RNA bound to telomeric DNA, elucidated that TERT-RNA and TERT-DNA associations resemble those observed with HIV RT as well (Mitchell, Gillis et al., 2010). Catalytic mechanism similarities between both TERT and viral RTs in general, and TERT and HIV RT specifically, are evident from biochemical studies (Bryan, Goodrich et al., 2000a; Bosoy and Lue, 2001; Peng, Mian et al., 2001).  In retroviral RTs, mutation of a tyrosine residue in motif C, which lies at the interface of the fingers and thumb domains, abolishes enzymatic activity.  When the analogous, highly conserved residue in Tetrahymena TERT was mutated from leucine to the conserved tyrosine residue, an increase in enzyme processivity was measured (Bryan, Goodrich et al., 2000a).  The predicted function of this tyrosine in retroviral RTs is to precisely position template-primer duplex in the active site, and thereby increase enzyme efficiency. Mutations of amino acid residues in S. cerevisiae TERT at positions analogous to residues implicated in nucleotide and template binding in HIV RT caused defects in S. cerevisiae telomerase similar to what has been observed in mutagenesis studies of HIV RT (Bosoy and Lue, 2001).  Specifically, using the HIV RT structure-activity analysis as a guide,   36 when the analogous amino acid residues important in nucleotide contacts in HIV RT were similarly mutated to alanine in TERT, severe defects in DNA synthesis and enzyme processivity were observed.  Specific amino acids within the primer grip region (motif E), palm (motif c), and thumb domains of HIV RT are important in enzyme processivity (Ding, Das et al., 1998; Huang, Chopra et al., 1998).  Mutation in conserved amino acid residues in S. cerevisiae TERT analogs to residues important for enzyme processivity in these regions altered S. cerevisiae telomerase activity exactly as predicted based on previous mutational analysis of HIV RT (Peng, Mian et al., 2001).  Collectively, these studies support a high degree of sequence and catalytic mechanism conservations between TERT and HIV RT and strongly support the possibility that inhibitors of HIV RT could affect telomerase catalysis in a similar fashion.   37 2.  HYPOTHESIS AND SPECIFIC AIMS 2.1. Hypothesis I hypothesize that N/NRTIs will inhibit human telomerase with the same mechanisms by which they are known to inhibit HIV RT.  Continuous exposure of telomerase-positive human cells with N/NRTIs will cause telomere length maintenance deficiencies through the inhibition of telomerase by these agents.  2.2.  Specific Aim 1 Determine whether selected members of the N/NRTI family of ARVs inhibit human telomerase with an optimized, telomerase-specific primer extension assay.  2.3.  Specific Aim 2 Test whether long-term, continuous treatment with selected members of the N/NRTI family of ARVs causes telomere length maintenance defects in a transformed human cell line with constitutive telomerase activity.   38 Figure 5.  Hypothesis.  An underlying disruption in telomere biology can lead to an accelerated loss of regenerative capacity in human tissues.  Over the course of normal tissue aging, cells naturally reach a point of proliferative arrest when their telomeres become too short.  Telomerase activity in several types of adult cells helps maintain replicative capacity in human tissues.  If there are any underlying disruptions in telomere biology or telomerase activity caused by treatment with N/NRTIs, the rate of telomere attrition can be accelerated, causing proliferative arrest to occur earlier in time.   39 3.  METHODS  HT29 Cell culture Maintenance The human colon cancer cell line HT29 (ATCC, Manassas, VA) was cultured in T25 flasks in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 5% FBS and 100U each penicillin and streptomycin.  Cells were maintained at 37°C in 5% CO2.  Media was renewed three times per week and cells were sub-cultured upon reaching 90-95% confluency.  Harvesting Cells were harvested at 90-95% confluency (about once per week) by treating cells with 0.5% trypsin-ethylenediaminetetraacetic acid (EDTA).  Detached cells were transferred to a 15 mL conical tube, centrifuged for 5 mins at 378 g, washed once with 1 X phosphate-buffered saline (PBS), aliquoted in 1.5 mL microcentrifuge tubes, then stored at -80°C for further analysis.  Drug treatment All drugs for cell culture were obtained through The National Institutes of Health (NIH) AIDS Reagent Program (Germantown, MD).  Drugs were dissolved in either PBS or dimethyl sulfoxide (DMSO) and stored at -20°C.  Diluted working aliquots were prepared for cell culture experiments, and drugs were added as 0.1% (d4T, ddI, NVP, EFV, 3TC), 0.17% (AZT), or 0.5% (TDF) of the final volume.  As controls, PBS and DMSO were added to media as 0.5% and 0.1% of the final volume, respectively.  Cell viability Cell viability was determined using the trypan blue exclusion test. Trypsinized cells were mixed 1:1 with 0.4% trypan blue solution, and 10 µL was pipetted onto a hemocytometer.  This dilution   40 will yield between 50 and 150 cells 100 mm2.  Five different fields of view were counted (between 250 and 750 cells total).  Viability was calculated by dividing the number of unstained cells by total cells counted.  Transient transfection of 293 Human Embryonic Kidney (HEK) cells Transient transfection of 293 HEK cells (ATCC, Manassas, VA) was performed using the calcium phosphate mediated transfection method.  293 HEK cells were maintained in T175 flasks in DMEM supplemented with 5% FBS and 100U each penicillin and streptomycin at 37°C in 5% CO2.  Upon reaching 60% confluency, cells were harvested and seeded on 150 mm plates at a density of 1x107 cells/plate.  Transfection was performed 24 h after seeding as follows. 3X FLAG hTERT in pCDNA and U3 hTR in pBS (both plasmids obtained with permission from Kathleen Collins laboratory at UC Berkeley) were diluted in sterile water such that each 150 mm plate received 25 µg of each plasmid.  Calcium chloride (final 250 mM) was mixed with the plasmid DNA, followed by the drop-wise addition of 2X HBS buffer (25 mM HEPES, 5 mM KCl, 6 mM glucose, 140 mM NaCl, 0.75 mM Na2HPO4).  Media was aspirated from each 150 mm plate, and fresh media containing the DNA/CaCl2/HBS solution was added. Media was changed 24 h after transfection, and cells were harvested 48 h after transfection. Harvested cells were washed once with 1X PBS (1 mL) and then stored -80°C for subsequent whole cell lysate preparation.  Whole cell lysate (WCL) preparation Harvested cells were washed once in 1 X PBS (1 mL) and centrifuged at 2,300 g for 1 min at 4°C in 1.5 mL microcentrifuge tubes.  After washing, cell pellets were resuspended in 1 mL of hypotonic cell lysis buffer [20 mM HEPES pH 8, 2 mM MgCl2, 0.2 mM ethylene glycol tetraacetic acid (EGTA) 1 mM dithiothreitol (DTT), 0.1 mM phenylmethylsulfonyl fluoride (PMSF), 10% glycerol] and immediately snap frozen in liquid nitrogen.  Subsequently, pellets were thawed at   41 37°C, vortexed, and frozen again in liquid nitrogen.  The freeze-thaw-vortex process was repeated a total of three times, after which 5 M NaCl was added to each microcentrifuge tube in two parts for a final NaCl concentration of 400 mM.  To separate the soluble whole cell extract fraction, reactions were left on ice for 5 mins and then centrifuged at 16,200 g for 15 mins.  After centrifugation, the supernatant was stored at -80°C until use in an immunopurification reaction.  Determination of protein concentration of WCL Protein concentration of WCL was determined using the Bradford Protein Assay (Bio-Rad Laboratories Inc., Hercules, CA).  Dye reagent concentrate was diluted five fold with deionized water and 200 µL were added to each well in a 96-well plate.  Bovine serum albumin (BSA) was used to generate the standard curve, which ranged from 0.1 to 0.5 mg/mL.  WCL was diluted 20- and 40-fold using hypotonic cell lysis buffer.  WCL or BSA standard (10 µL) was added to each well, and the dye-protein mix was incubated at room temperature for 5 min.  Protein concentration was determined by reading the 96-well plate at 595 nm.  Protein concentration of extract was determined using the linear equation generated from the sample standards.  Immunopurification of FLAG-tagged hTERT WCL prepared from HEK 293 cells transiently transfected with hTERT and hTER was used in immunopurification (IP) reactions.  WCL equivalent to 2 mg of protein was mixed with IP dilution buffer, then with IP wash buffer (same composition as IP dilution buffer except contains no NaCl) was added to each IP reaction to bring the total volume to 1 mL.  Ten microlitres of a 50% slurry of anti-FLAG M2 agarose beads (Sigma-Aldrich, Oakville, ON) was added to each IP reaction, and reactions were then rotated end on end for 2 h at 4°C.  After 2 h, reactions were centrifuged at 2,300 g for 30 s at 4°C.  The supernatant was removed, 1 mL of fresh IP wash buffer was added, and reactions were again rotated for 10 min at 4°C; this washing procedure was repeated three times.  After the third wash, reactions were centrifuged at 2,300 g for 30 s at   42 4°C and beads were resuspended in 130 µL IP wash buffer and stored at -80°C until use in the conventional assay.  Primer extension assay (conventional assay) A typical reaction consisted of immunopurified telomerase (20 µL of an IP reaction), dATP, dTTP, dGTP, either [α-32P]-labelled dGTP or dTTP, an 18 nt primer (2.5 µM), and 10X assay buffer (50 mM Tris-acetate pH  8.3, 1 mM MgCl2, 50 mM Potassium acetate, 1 mM spermidine, 5 mM β-mercaptoethanol).  Radiolabelled nucleotide selection, final nucleotide concentration, and primer permutation varied depending on the experiment.  For reactions using WCL, a volume equivalent to 100 µg total protein was used for activity.  NaCl concentration was diluted down from 400 mM down to 200 mM using an equal volume of hypotonic cell lysis buffer.  The volume of the salt-corrected WCL was brought up to 20 µL by adding the necessary volume of hypotonic cell lysis buffer containing 200 mM NaCl.  The experimental set ups for the activity optimization experiments and the primer permutation experiment were identical.  Each reaction contained 20 µL salt-corrected WCL or 20 µL IP, 1 mM dATP, 1 mM dTTP, 10 µM dGTP, 200 nM [α-32P]dGTP (3000 Ci/mmol 10 mCi/mL, 3.3 µM, Perkin Elmer), an 18 nt primer (2.5 µM), and 10X assay buffer.  The primer used in the activity optimization experiments was 5’- TTAGGGTTAGGGTTAGGG-3’.  Primers used in the primer permutation experiments are listed in Table 2.  For the dTTP and dATP titration experiments, each reaction contained 20 µL IP from 293 HEK cells transiently transfected with hTER/hTERT, 10 µM dGTP, [α-32P]dGTP, the 18 nt primer 5’-GGGTTAGGGTTAGGGTTA-3’ (2.5 µM), and 10X assay buffer.  Each reaction in the dTTP titration experiments contained 1 mM dATP, and dTTP was used at 20 µM, 10 µM, or 5 µM. Each reaction in the dATP titration experiments contained 1 mM dTTP, and dATP was used at 20 µM, 10 µM, or 5 µM.  Optimization experiments for labelled [α-32P]dTTP  were done using 20 µL IP from 293 HEK cells transiently transfected with hTER/hTERT in the presence of 1 mM   43 dATP, 20 µM dGTP, 200 nM [α-32P]dTTP (3000 Ci/mmol 10 mCi/mL, 3.3 µM, Perkin Elmer), primer 5’-GTTAGGGTTAGGGTTAGG-3’ (2.5 µM), and 10X assay buffer, while the dTTP concentration was titrated from 40 µM down to 10 µM.  For dTTP analog experiments, [α-32P]dGTP (3000 Ci/mmol 10 mCi/mL, 3.3 µM, Perkin Elmer) was used, final nucleotide concentrations were 1 mM dATP, 10 µM dTTP, and 10 µM dGTP, and the primer used was 5’-GGGTTAGGGTTAGGGTTA-3’.  The setup for dATP analog experiments was identical except for the final dATP and dTTP concentrations, which were 10 µM and 1 mM, respectively.  For dGTP analog experiments, [α-32P]dTTP (3000 Ci/mmol 10 mCi/mL, 3.3 µM, Perkin Elmer) was used, final nucleotide concentrations were 1 mM dTTP, and 20 µM dGTP (dATP was withheld from the reaction) and the primer used was 5’- GTTAGGGTTAGGGTTAGG-3’.  With respect to the experiments testing the NNRTIs, [α- 32P]dGTP (3000 Ci/mmol 10 mCi/mL, 3.3 µM, Perkin Elmer) was used, final nucleotide concentrations were as follows: 1 mM dATP, 1 mM dTTP, and 10 µM dGTP, and the primer used was 5’-TTAGGGTTAGGGTTAGGG-3’.  Reactions were incubated at 30°C for 2 h and stopped by 15 min incubation with Stop Solution A [10 mM tris(hydroxymethyl)aminomethane (Tris)-HCl pH  7.5, 10 mM EDTA, 0.1 mg/mL RNAse A], followed by 15 min incubation with Stop Solution B [10 mM Tris-HCl pH  7.5, 0.4% sodium dodecyl sulfate (SDS), 0.2 mg/mL proteinase K]. After the addition of a 250 nt [γ- 32P]ATP (3000 Ci/mmol, 5 mCi/mL, Perkin Elmer, Boston, MA, USA) end-labelled recovery control (RC), DNA products were purified by adding an equal volume of phenol/chloroform/isoamyl alcohol (25:24:1), then precipitated overnight at -20°C in 1/10 volume 3 M sodium acetate (pH  5.4) and 3 volumes of absolute ethanol, with 50 µg linear polyacrylamide (LPA) as a carrier.  Following precipitation, products were recovered by centrifugation at 16,200 g for 30 mins at room temperature, resuspended in equal volumes of Tris-EDTA (TE) buffer (pH  8) and 2X formamide loading dye.  Products were resolved on 17.5% denaturing gel [17.5% acrylamide/bis (19:1), 0.5 X Tris-boric acid-EDTA (TBE), 7 M urea]   44 for 4 hours at 650 V.  Gels were dried for 5 hours (3.5 hours at 80°C, 1.5 hours cooling), then exposed to a phosphor screen overnight. Images (100 µm resolution) were obtained using the Typhoon Trio Imager (GE Healthcare Life Sciences).  Drug treatment For the conventional assay, aqueous solutions of d4T-triphosphate (TP) and AZT-TP were obtained from ChemCyte Inc. (San Diego, CA, USA).  Aqueous solutions of CBV-TP and TFV- DP were obtained from Moravek Biochemicals Inc. (Brea, CA, USA).  Dideoxynucleotide analogs were obtained from MJS Biolynx (Brockville, ON, CA).  EFV and NVP (from NIH AIDS reagent program) were dissolved in DMSO.  Stock nucleotide analog concentrations were determined prior to every experiment through UV/Visual spectrophotometry.  The absorbance of each drug stock was measured at its lambda max (λmax) and concentration was calculated using the molar extinction coefficient for each drug.  Extinction coefficient and λmax for each drug are as follows: AZT-TP and d4T-TP 9650 L mol-1 cm-1 at 267 nM, CBV-TP 13,260 L mol-1 cm-1 at 253 nm, TFV-DP 12,800 L mol-1 cm-1 at 262 nm.  All nucleotide analogs were added into the reaction as 20% of the final volume, while NVP and EFV were added as either 5% or 10% of the final volume.  Quantification of primer extension assay gel images  Quantification was done using ImageQuant (v. 5.2, GE Healthcare Life Sciences) and was performed as follows.  For experiments investigating dTTP analogs and ddATP, total enzyme activity for each reaction was determined by quantifying the signal of all bands between the primer +1 nt product and the RC.  The total activity value was then normalized for activity by dividing total activity by the primer +1 nt product for the respective lane.  The activity-normalized values were then normalized to the untreated reaction and plotted against the logarithm of the drug concentration to generate a dose-response curve for each experiment.  TFV-DP was   45 quantified in a similar manner except the data were not normalized to the primer +1 nt band. For the experiments testing dGTP analogs, total activity was quantified and normalized to the RC, then normalized to the untreated reaction for each experiment.  For NNRTIs, whole-lane activity was used for quantification of data.  Analysis of primer extension assay data GraphPad Prism (v. 4.0b, GraphPad Software, Inc.) was used to fit the activity data from the primer extension assay data.  For nucleotide analogs, after the necessary data normalizations were completed (as outlined above), activity data were plotted against the logarithm of drug concentration, and an IC50 was determined for each nucleotide analog.  Student’s t-test for independent samples was used to compare means between each synthetic nucleotide analog its corresponding dideoxy counterpart (e.g., TFV-DP was compared to ddATP).  For NNRTIs, data were plotted as activity relative to control and are represented as histograms only.   A Student’s t-test for independent samples was used to compare means between each NNRTI and the DMSO control.  The difference between means was considered statistically significant if the probability of making a type I error was less than 5% (i.e., p < 0.05).  Genomic DNA preparation Cell pellets containing approximately 3x106 cells, previously stored at -80°C, were thawed and resuspended in 200 µL 1X PBS.  Genomic DNA was isolated using the QIAamp DNA Blood Mini Kit (Qiagen) and resuspended in 200 µL Elution Buffer (Qiagen).  Terminal Restriction Fragment (TRF) digestion of genomic DNA Half (90 µL) of the genomic DNA preparation (20-30 µg) was digested overnight at 37°C with 2 units each of HinfI and RsaI.  Digested DNA was precipitated by adding 1/10 volume 3 M sodium acetate (pH  5.4), 50 µg linear polyacrylamide (LPA), and three volumes of absolute   46 ethanol for 1 h at -80°C.  Digested DNA was recovered by centrifugation at 16,200 g at 4°C for 30 min.  DNA pellets were resuspended in 35 µL of TE buffer (pH  8) and stored at -20°C until use.  QuantIT PicoGreen assay The fluorescent QuantIT PicoGreen assay (Sigma-Aldrich, Oakville, ON) was used to determine the concentration of ds DNA after TRF digestion.  On the day of use, the PicoGreen reagent was thawed and diluted 1:200 using TE buffer (pH  8).  The 1 kb DNA ladder (New England Biolabs, Ipswich, MA) was diluted in TE buffer (pH  8), and a two-fold dilution series was performed to provide a dsDNA standard in the range of 0.625 to 10 µg/mL.  TRF samples were diluted 1:100 with TE buffer (pH  8).  The diluted PicoGreen reagent was added to each well (57 µL per well) and 3 µL of either sample or standard were added to the diluted PicoGreen reagent.  The plate was protected from light, and reagent was given 5 min incubation time with the samples and standards.  Samples were analyzed using either the Typhoon Trio Imager (GE Healthcare Lifesciences) or the SynergyMX plate reader (BioTek) fitted with the appropriate laser and filters.  TRF assay Digested DNA (2 µg) was resolved on 0.5% agarose overnight (approximately 14 h).  DNA markers 1 kb DNA ladder (New England Biolabs, Ipswich, MA) and GeneRuler High Range DNA ladder (Fermentas, Burlington, ON) were end labelled with [γ-32P]ATP (3000 Ci/mmol, 5 mCi/mL, Perkin Elmer, Boston, MA) and resolved in parallel with digested DNA.  Agarose gels were dried for 2.5 hrs at 60°C, denatured for 20 min in 0.5 M NaOH/1.5 M NaCl,  and neutralized for 20 min in 0.5 M Tris, pH  7.4/1.5 M NaCl.  Gels were prehybridized in Church’s Hybridization Solution (1 mM EDTA, 500 mM Na2HPO4, 7% SDS, 10 mg/mL BSA) for 1 h at 42°C followed by overnight hybridization with a telomeric probe (5’-   47 TTAGGGTTAGGGTTAGGG-3’) end labelled with [γ-32P]ATP ([γ-32P]ATP (3000 Ci/mmol, 5 mCi/mL, Perkin Elmer, Boston, MA).  Blots were washed three times (30 min per wash) in 0.5X SSC (sodium chloride-sodium citrate buffer)/0.1% SDS), and exposed to a Phosphor screen (GE Healthcare Lifesciences).  Images were obtained at 200 µm resolution using the Typhoon Trio Imager.  Quantification was performed using ImageQuant (v. 5.2).  TRF length was determined as a weighted average.  The gel image was divided into horizontal segments corresponding to the size markers.  For each TRF smear, the optical density (OD) of each horizontal segment was multiplied by the length corresponding to the respective segment, summed, and divided by the sum of the OD of all segments [i.e., TRF=Σ(ODi*Li)/ΣOdi, where ODi is optical density at interval i, and Li is average length at interval i].  TRF lengths are reported as kb to one decimal place (Vaziri, Schachter et al., 1993).                 48 4.  IN VITRO TELOMERASE ACTIVITY 4.1.  Introduction Published work testing the potential of NRTIs to inhibit telomerase in vitro has focused exclusively on older NRTIs such as AZT and ABC.  I wanted to expand this body of work to include all NRTIs currently used in anti-HIV therapy that have the potential to inhibit telomerase, as predicted by their mechanisms of action.  In addition, the effect of NNRTIs on telomerase activity has not yet been investigated.  There were two primary objectives of these experiments. First, I wanted to know whether anti-retrovirals (ARVs) from the N/NRTI categories inhibited telomerase.  To answer this question, I set up in vitro dose-response experiments to determine IC50 values for each drug.  The IC50 values would allow us to comment on the relative potency of each N/NRTIs in their inhibitory activities against telomerase.  With NRTIs, I wanted to compare the potency of NRTIs to the dideoxy forms of the natural substrates (deoxynucleotides) of telomerase, so I performed positive control experiments testing the potencies of ddTTP, ddATP, and ddGTP against telomerase. The second objective of these experiments was to determine whether N/NRTIs mechanistically inhibit telomerase in the same manner that they inhibit HIV RT.  I wanted to know whether NRTIs act as competitive inhibitors of telomerase, and whether NNRTIs act as non-competitive inhibitors.  More specifically, I wanted to know whether NRTIs inhibit telomerase by acting as chain terminators, in a manner that they were expected to as predicted by their inhibitory profiles against HIV RT, and whether NNRTIs inhibit telomerase processivity as they do with the HIV RT. There are several different assays available to measure telomerase activity, but none offer the combined flexibility and resolution of the telomerase primer extension assay.  Since I am investigating drugs originally designed to target HIV RT, I wanted as much information as possible about how and if these drugs interact with telomerase.  The primer extension assay allows us to determine whether NRTIs behave as chain-terminating agents in telomerase-   49 mediated DNA synthesis reactions.  It was also important to confirm whether the NRTIs cause chain termination at the expected position within the DNA synthesis sequence.  That is, I wanted to confirm that AZT-TP and d4T-TP were incorporated in place of dTTP, that TFV-DP is incorporated in place of dATP, and that CBV-TP is incorporate in place of dGTP.  The nucleotide-level resolution radioactive primer extension assay, combined with flexibility in nucleotide concentrations and primer permutations, permitted us to determine those details.  4.2.  Results and discussion 4.2.1.  Methods development Before experimenting with N/NRTIs, I needed to optimize the primer extension assay.  I first used whole cell lysate (WCL) prepared from 293 HEK cells stably transfected with hTERT and hTER as a source of telomerase activity.  The phosphorimages of primer extension product gels from this approach had high background and did not provide a good signal-to-noise ratio for accurate quantification of my gel images (Fig. 6, lane 1).  To increase the radioactive primer extension signals for product visualization and quantification, I over-expressed telomerase activity by performing transient transfections of 293 HEK cells with hTER under the heterogenous human U3 snoRNA promoter and FLAG tagged hTERT, under the viral cytomegalovirus promoter.  In mammalian cells, transient transfections were repeatedly shown to be superior over using WCL prepared from the hTERT/hTER expressing stable cell line as a source of telomerase activity and proved successful at increasing my signals relative to background (Fig. 6, lane 2).  However, my gel images still revealed a marked level of non- specific, nuclease-mediated DNA degradation in my reactions. As illustrated in Figure 2, since telomerase adds nucleotides in blocks of six (repeat addition processivity), I expected a distinct separation of DNA products in intervals of six nt. Instead, I observed intermediary DNA products between the six nt intervals.  This is particularly true for small molecular weight DNA molecules (Fig. 6, lane 2, brackets), which were especially   50 important for accurate analysis of my NRTI experiments.  As stated, I suspected that this degradation was caused by non-specific endogenous nucleases from the unpurified whole cell lysate and reasoned that immunopurifying the recombinantly tagged telomerase from the WCL should alleviate this issue.  Indeed, immunopurification of recombinant telomerase using anti- FLAG antibodies (immunopurifying flag-hTERT) resulted in a much cleaner banding pattern in the resultant primer extension assay products (Fig. 6, lane 3). The IP efficiency was determined by measuring the co-purified TER in the complex, as a quantitative read-out for the copy number of holoenzyme (both TERT and TER) purified by my immunopurification protocol. Using competitive RT-PCR, I measured the total TER copy number in the transiently transfected 293 HEK WCL before immunopurification, and compared it with the TER copy number following immunopurification.  With this method, I determined that the average efficiency of my IP reaction was 21% (Appendix Fig. 1).  The efficiency of my IP procedure was determined using two biological repeats from two independent transient transfections.  Based on these measurements, I calculated the input of telomerase holoenzyme in my primer extension assay to be 8 x 1010 copy/40ul reaction. To confirm that my assay was telomerase specific, I used the telomere template sequence to predict the outcome of the nucleotide addition using my primer extension assay.  I used six possible permutations of the telomeric repeat as the ending nucleotide on synthetic primers (Table 2), and performed the same primer extension protocol in separate reactions.  If my primer extension assay faithfully measures telomerase catalysis, then the product profiles from these reactions should satisfy my prediction based on the specific primer’s interaction with the TER template region (Fig. 1).  I should be able to predict the number of nucleotides added to each primer permutation during first-repeat synthesis, based on each primer’s last nucleotide positioning within the TER template (Fig. 7).  After first repeat synthesis for each primer, dark bands signaling terminal products should appear in intervals of six nt, equivalent to the length of a single telomeric DNA repeat.   The DNA banding patterns from my primer permutation   51 experiment (Fig. 8) matched my predictions perfectly, confirming that my assay is telomerase specific. Once my assay was demonstrated to be telomerase specific, I had to optimize the nucleotide concentrations and primer permutations for testing different NRTIs.  I wanted to identify the minimal deoxynucleotide concentrations that would still provide sufficient telomerase activity for accurate quantification.  This approach allowed us to prepare for a scenario where one might require large quantities of NRTIs to completely inhibit telomerase activity.  I performed experiments in which dTTP or dATP were titrated from 20 µM down to 5 µM, while the other deoxynucleotides were being supplied in excess (Fig. 9A and B, respectively).  From these titration experiments, I determined by visual inspection the minimal concentration of each nucleotide that would support telomerase catalysis without the appearance of truncated products indicative of substrate (free deoxynucleotides) depletion.  Using this approach, I determined that the optimal concentration of dTTP was 10 µM (Fig. 9A, red arrowhead), while the optimal concentration for dATP was 20 µM (Fig. 9B, red arrowhead). For experiments testing dGTP analogs against telomerase, I had to address two separate issues.  First, I needed to optimize my activity assay using a radiolabeled nucleotide other than dGTP, as I needed to be able to measure accurately the stock concentration of my competitor nucleotide for each experiment.  Radioactively labeled nucleotides are supplied based on their specific activity.  Variation in factors such as date of manufacturing, storage conditions, as well as labeling efficiency, which are all beyond my control, complicates and in some cases prevents the calculation of nucleotide input accurately.  Second, telomerase exhibits both nucleotide addition and repeat addition processivities.  Since the last nucleotide on the TER template is a guanine, competition from a G-analog that causes chain termination at this nucleotide position would be indistinguishable from that of a natural stop at the end of the template.  As such, I needed to develop a strategy that would allow us to differentiate the effects of dGTP analogs on nucleotide addition processivity compared to repeat addition processivity.   52 To address the first issue, I optimized my assay to incorporate radiolabeled dTTP instead of radiolabeled dGTP.  The radiolabeled nucleotide was supplied in high specific activities, and the equivalent of 200 nM was added to each reaction.  To bring the free nucleotide level over and beyond the Km of telomerase for these substrates, my reactions included the use of a mix of a radiolabeled nucleotide and its non-radioactive counterpart.  I had to titrate non-radioactive dTTP in the presence of [α-32P]dTTP to determine the amount of non- radioactive dTTP that would provide normal telomerase catalysis pattern (Fig. 9C). I determined that the ratio of 48:1 (moles dTTP:moles [α-32P]dTTP) resulted in an optimal signal (Fig. 9C, red arrowhead). To address the second issue, I had to re-design my primer-extension quantification method.  In this new method, I used primer 18AGG and withheld dATP from the reaction.  This allowed us to measure incorporation of a mid-template guanine, at a position unrelated to repeat addition processivity.  Withholding dATP from the reaction blocked the completion of first repeat synthesis and predicted the addition of only three nt to the primer (i.e., primer +3) before telomerase was forced to terminate synthesis.  The result of my modifications was that, in the presence of a dGTP analog, I would look for the loss of the primer +3 nt signal.  I observed minimal but reproducible telomerase activity past the primer +3 position (Fig. 9D, bracket), which I attributed to endogenous dATP nucleotides co-immunopurified during the telomerase immunopurification procedure.  Once my assay was established for the competition dose-response experiments, I wanted to test the variability of my assay.  I performed three sets of dose-response experiments, one set for each of the three nucleotides I will be testing in my NRTI competition experiment.  Each set of experiments consisted of three replicates of the primer extension assay testing the potency of the most-closely related congeners of the natural nucleotides: their dideoxy counterparts (ddTTP, ddATP, or ddGTP) (Fig. 10).  Since there is no cytidine in telomere repeats, this nucleotide was omitted from my experimental scheme.  I obtained a   53 coefficient of variation (CV) of 1.48% for the measurement of competition with thymidine analogs. The variability was very low for experimental set up testing the dTTP analogs. Variability was substantially higher with dATP and dGTP analogs, which had CVs of 23% and 26%, respectively. Using the optimized primer extension assay, immunopurified telomerase activity was tested in the presence and absence of N/NRTIs.  Given that NRTIs must be phosphorylated in cells to become active, I had to use the fully activated form of each NRTI tested in my cell-free assay system.  Within the NRTI category, I tested the dTTP analogs AZT-TP and d4T-TP, the dATP analog tenofovir-diphosphate (TFV-DP), and the dGTP analog CBV-TP (Table 1, Fig. 4). Since the telomeric repeat only contains the nucleobases adenine, guanine, and thymidine, only NRTIs that are analogs of these nucleobases should have the potential to inhibit telomerase NAP.  As such, I did not include any cytosine analogs in my in vitro experiments. I tested the NRTIs in dose-response experiments using either four- or five-fold dilution series.  In parallel, I tested two NNRTIs, NVP and EFV and the NNRTIs were tested at single concentrations in the low millimolar range.  Three replicates were performed for each experiment for both NRTIs and NNRTIs.  I used four unique experimental setups: one for dTTP analogs, one for dATP analogs, one for dGTP analogs, and one for the NNRTIs (standard primer extension assay).  Using different setups permitted us to answer my questions precisely, based on the pattern of telomerase-specific DNA products observed after denaturing gel electrophoresis.  Each gel image was quantified for whole lane activity, and the data were analyzed using GraphPad Prism.  The NRTI data were plotted, and GraphPad Prism was used to estimate dose-response relationships.  The NNRTI data were plotted as histograms and compared at the single concentrations tested.   54  Figure 6.  Optimization of the telomerase primer extension assay for telomerase activity.  Initially, I used WCL from 293 HEK cells stably transfected with recombinant flag- tagged TERT and U3-TER (lane 1), which did not provide a sufficient signal on my gel.  WCL from the same cells transiently transfected with TERT and TER provided a better signal, but smaller DNA products showed additional terminal products, possibly from non-specific degradation (lane 2 brackets).  Optimal signal and banding patterns were obtained after recombinant telomerase was immunopurified (IP) from 293 HEK cells stably transfected with TERT and TER.  Primer +n (where n represents nt) denotes the main products synthesized by telomerase.  Note that the darker bands are separated by 6 nt.   55 Figure 7.  Prediction of DNA products after first-repeat synthesis using six different primer permutations.  Based on each primer’s last nucleotide positioning within the TER template, I predicted the number of nt added to six different primers during first-repeat synthesis (A-F).  The primer short form name is shown on the left, schematic of telomerase on ss DNA primers shown in the middle (only TERT and TER shown for simplicity), and predicted DNA molecule shown at the right. Table 2.  Primers used in the primer extension assay.  Each ss 18 nt primer is denoted by a short form, 18XXX, where the Xs represent the last three nt of the primer sequence.  !"#$%&#'(')%&)**"%"+, TERT !!!!!!!!!!!"##$"""##$"!%&'''((#'''((#'''((#!)'!*& !" #" $%&'(%)*'+,-&./0 -#".'# 12//3 -#'*"/%'*&012&(#+*3/%& )4%'#&4"#$%&#+3,*&+4& $5,%6'$"$ TERT !!!!!!!!!!!!"##$"""##$"!%&#'''((#'''((#'''((!)#'!*& !" #" 12.// 0$'4,$-56 #'''((#'''((#'''((#' 0$'4,$-51 '''((#'''((#'''((#' TERT !!!!!!!!!!!!!"##$"""##$"!%&(#'''((#'''((#'''(!)(#'!*& !" #" 12../ 0$'4,$-5! (#'''((#'''((#'''((#' TERT !!!!!!!!!!!!!!"##$"""##$"!%&((#'''((#'''((#'''!)((#'!*& !" #" 12... 0$'4,$-57 ((#'''((#'''((#'''((#' TERT !!!!!!!!!!!!!!!"##$"""##$"!%&'((#'''((#'''((#''!)'((#'!*& !" #" 123.. 0$'4,$-5# '((#'''((#'''((#'''('((#' TERT !!!!!!!!!!!!!!!!"##$"""##$"!%&''((#'''((#'''((#'!)''((#'!*& !" #" 12/3. 0$'4,$-58 ''((#'''((#'''((#'''(''((#' 2 7 8 0 9 !   56  Figure 8.  My primer extension assay is telomerase specific.  Immunopurified telomerase holoenzymes from 293 HEK cells transiently expressing flag-TERT and U3-TER were used to test telomerase activity in the presence of six different ss DNA primers.  DNA size after first repeat synthesis is delineated at the bottom of the gel image.  The banding patterns after first repeat synthesis agree with my predictions from Fig. 6, confirming that my assay is telomerase specific.   57 Figure 9.  Optimization of the primer extension assay for testing NRTIs.  A.  dTTP titration experiment to determine optimal dTTP concentration for experiments testing dTTP analogs using primer 18TTA.  The red arrowhead indicates dTTP concentration selected for experiments.  B. dATP titration experiment to determine optimal dATP concentration for experiments testing dATP analogs using primer 18TTA.  The red arrowhead indicates dATP concentration selected for experiments.  C.  Optimization of the primer extension assay using [α-32P]dTTP instead of [α-32P]dGTP.  The optimal ratio of dTTP:[α-32P]dTTP is identified by the red arrowhead.  D.  Optimization of the primer extension assay to test dGTP analogs using primer 18AGG and withholding dATP from the reaction.  Excessive activity refers to activity as a result of endogenous dATP in my IP reactions.   58  Figure 10.  Variability of the primer extension assay testing ddNTPs.  Immunopurified telomerase from 293 HEK cells transiently expressing TERT and TER was used to test telomerase activity in the presence of ddTTP, ddATP, and ddGTP.  Three technical replicates for each ddNTP were performed.  Gels were quantified using ImageQuant and IC50 values were determined using GraphPad Prism.  The mean of three IC50 values was plotted on a histogram.  Error bars are standard deviation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rimer extension assay with N/NRTIs I used primer 18TTA (Table 2) to test the dTTP analogs ddTTP, AZT-TP, and d4T-TP.  With primer 18TTA, I anticipated that each lane within an experiment, regardless of drug concentration, would have the primer +1 band (Fig. 7A), since incorporation of the first G nucleotide will bring the primer extension product to the end of the template, and no competition is expected at this nucleotide position.  The signals of the first G incorporation from each reaction lane were use to normalize for activity.  I also predicted that as the concentration of the dTTP analogs increased, I would observe an increasing accumulation of DNA molecules at the primer +4 and primer +5 positions, the positions corresponding to where dTTP is normally incorporated during DNA synthesis using primer 18TTA (Fig. 11A). The dTTP analogs were tested in four-fold dilution series ranging from 8 – 2500 µM, and both of the above predictions were realized (Figs. 11B-D).  After quantification, dose-response relationships were estimated using GraphPad Prism (Fig. 11E).  The dose-response curves for ddTTP (black) and d4T-TP (purple) overlapped, indicating similar potencies against telomerase. The dose-response curve for AZT-TP (turquoise) was right-shifted compared to both ddTTP and d4T-TP, indicating its lower potency.  Although d4T-TP had a lower apparent IC50 when compared with the value obtained with ddTTP (24.12 ± 14.54 µM versus 30.64 ± 2.36 µM, respectively), the difference was not statistically significant (P=0.5234) (Fig. 11F, Table 4). Similarly, AZT-TP had a higher IC50 than that of ddTTP, but the result was not statistically significant (44.08 ± 5.05 µM and 30.64 ± 2.361 µM, respectively, P=0.0528) (Table 4). I tested the dATP analogs ddATP and TFV-DP using the same primer that I used in the experiments testing dTTP analogs (18TTA). It should be noted that the NRTI didanosine (ddI) is metabolized in human cells to ddATP.  Thus, the data obtained for ddATP should be considered applicable to the active form of ddI.  In regards to the DNA banding pattern on my gels from these experiments, I anticipated that each lane within an experiment would have the primer +1 band, regardless of drug concentration.  In contrast to the dTTP experiments, I expected that,   60 with increasing concentration of the dATP analogs I would see the accumulation of DNA molecules at the primer +6 position (Fig. 12A). The dATP analogs ddATP and TFV-DP were tested in a five-fold dilution series ranging from 4 – 2300 µM (Fig. 12B-C).  I observed a consistent level of primer +1 band in each lane for the ddATP experiments, but not so for the TFV-DP experiments.  The primer +1 band was reproducibly less intense in the reactions containing 2300 µM TFV-DP (Fig. 12C, last lane).  I reasoned that the loss of intensity of the primer +1 band in the presence of a high dose of TFV- DP might be due to its ability to compete against dGTP incorporation at this position.  In other words, TFV-DP is showing non-specific nucleotide inhibition properties at 2300 µM.  I suspect inhibition is non-specific since dGTP was provided in a lower concentration than dATP for each reaction (10 µM compared to 20 µM, respectively).  If indeed TFV-DP is acting as a dGTP competitor, one would expect the disappearance of the first dGTP incorporation should occur with much lower concentration of the drug.  In comparing the dose-response curves of ddATP and TFV-DP, it appears that TFV-DP is much less potent as a telomerase inhibitor than ddATP (Fig. 12D), as the TFV-DP curve (turquoise) is shifted far to the right of that of the ddATP curve (black).  This shift is reflected in the IC50 values for each analog, as the IC50 for ddATP was 12.57 ± 1.87 µM, compared to that of TFV-DP, which was 109.7 ± 52.33 µM (Fig. 12E and Table 5).  The difference between the dATP analog IC50s was not statistically significant, with P=0.0925 (Table 5). As outlined in the methods development section, I used a slightly different set up to measure telomerase inhibition by dGTP analogs (Figs. 9D and 13A).  I used this unique set up because I wanted to specifically measure the effect of dGTP analogs as competitors for dGTP and, wanted to ensure that this measurement would not be influenced by template-primer dissociation.  With this assay, I predicted that testing telomerase in the presence of a dGTP analog in my modified assay would result in a decrease of the primer +3 signal at competitive concentrations.  As predicted, exposure of telomerase to either ddGTP or CBV-TP resulted in a   61 decrease of the primer +3 signal in a dose-dependent manner (Fig. 13B-C).  Both dGTP analogs were tested in five-fold dose-response series over a range of 3 – 2000 µM.  The data were quantified as whole-lane activity and dose-response relationships were estimated (Fig. 13D).  Similar to what was observed with the dATP analogs, it appears that CBV-TP was substantially less potent than ddGTP, as the dose response-curve of CBV-TP (turquoise) is notably right-shifted when compared to that of ddGTP (black).  The IC50 of CBV-TP (357.7 ± 182.0 µM) is higher than that of ddGTP (17.17 ± 8.478 µM), but the difference was not statistically significant (P = 0.0849) (Fig. 13E and Table 6). I also used the primer extension assay set up to test the NNRTIs. Nucleotides were not in limiting concentrations in this case, and I used the primer 18GGG for all NNRTI experiments. Initial dose-response experiments with NNRTIs NVP and EFV were performed in my primer extension assay prior to complete optimization (Appendix Fig. 2).  Since I observed no indication of telomerase inhibition, I decided to test each NNRTI in a series of experiments testing each at 1 mM (Fig. 14A).  There was some variation in mean whole-lane activity when comparing NVP and EFV to DMSO control, but neither NNRTI was significantly different compared to control (P=0.79 for NVP and P=0.98 for EFV) (Fig. 14B, Table 7).  To confirm lack of NNRTI-mediated telomerase inhibition, a single experiment was performed, maximizing each NNRTI concentration to 4 mM (Fig. 14C).  Again, there was no observable inhibitory effect with either NVP or EFV compared to control. In order to compare my data to published work, I had to interpret my data as the fold concentration of NRTI above the relevant competitor required for 50% telomerase inhibition. This was required because experimental set ups within the literature vary, rendering the reported IC50s incomparable at face value.  In my assay, 44 µM AZT-TP was required to inhibit telomerase activity by 50% in the presence of 10 µM dTTP.  That is, the concentration of AZT- TP required to achieve 50% telomerase inhibition was 4.4-fold above that of its competitor, dTTP.  When AZT-TP was tested against Tetrahymena telomerase in a primer extension assay,   62 the AZT-TP concentration necessary to achieve 50% inhibition was 2.4-fold higher than TTP (Strahl and Blackburn, 1994).  The slightly lower value could be due to the fact that Tetrahymena telomerase has several biological differences compared to human telomerase. When tested in a primer extension assay, telomerase from immortalized human T- and B- lymphocytes required a 3 – 4-fold higher concentration of AZT-TP relative to TTP, which is similar to my results (Strahl and Blackburn, 1996).  Similarly, measuring telomerase activity from HeLa cells in a primer extension assay required a 5-fold higher concentration of AZT-TP relative to dTTP for 50% telomerase inhibition (Liu, Takahashi et al., 2007).  It appears that my data, at least with respect to AZT-TP, agree with data from previous experiments for human telomerase. For the dGTP analog CBV-TP, a concentration of CBV-TP 18-fold higher than dGTP, was required for 50% telomerase inhibition in my assay.  In the only published study of telomerase inhibition by CBV-TP, a CBV-TP concentration 6-fold higher than dGTP was necessary to achieve 50% inhibition of HeLa telomerase in a primer extension assay (Tendian and Parker, 2000).  However, telomerase inhibition in that study was determined by eye, which is clearly subjective and likely involves a large amount of error.  The differences in data quantification between these experiments may explain the discrepancy in the IC50 values.  To date there have not been any data published on either d4T-TP or TFV-DP with respect to in vitro telomerase inhibition.  In my experiments, however, I observed that d4T-TP was required at 2.4-fold that of the dTTP concentration for 50% telomerase inhibition, and that TFV-DP was required at 5.5-fold the dATP concentration for 50% telomerase inhibition. I did not observe telomerase inhibition with either of the NNRTIs tested in my in vitro assays, even at concentrations as high as 4 mM.  NNRTIs interact and inhibit HIV RT by binding the enzyme in a hydrophobic pocket within the enzyme.  Based on the existence of a small molecule, NNRTI-like telomerase inhibitor called BIBR 1532 (Pascolo, Wenz et al., 2002), I speculated that a similar binding site might exist in TERT.  In my experiments, I used telomerase immunopurified from whole cell lysate (WCL).  My immunopurified telomerase likely   63 contains components additional to TERT and TER, including the holoenzyme proteins dyskerin, Nhp2, Nop10, Gar1, and TCAB1, as well as other potential telomerase-interacting proteins.  I suspect that these non-catalytic holoenzyme proteins could provide steric hindrance obstructing the NNRTI binding sites on TERT.  If this hypothesis is true, then using a minimal reconstituted telomerase enzyme composed only of TERT and TER expressed using the rabbit reticulocyte (RRL) system should reveal whether NNRTIs inhibit telomerase in vitro.  This experiment, of course, would be interesting strictly for mechanism-based studies, as telomerase in vivo is not minimally composed of TERT and TER in human cells. An important caveat with respect to the NRTI data is that I set up my experiments based on previous knowledge of the mechanisms of NRTIs with the studies on HIV RT, and based on their structural similarities to the natural deoxy-nucleotides.   In my experiments testing AZT-TP and d4T-TP against telomerase, the dTTP concentration was 100-fold lower than that of dATP. Under these conditions, I would not have been able to determine whether either AZT-TP or d4T- TP could act as competitor against dATP.  The same reasoning applies to experiments testing TFV-DP, since the dTTP concentration provided was substantially above the dATP concentration.  This caveat is especially true for the CBV-TP experiments, for which I restricted telomerase activity to the addition of only three nt to the primer, excluding dATP.  This issue could be resolved through more detailed kinetic studies or by testing each NRTI in all three of my experimental set ups.   64  Figure 11. A.  Telomerase catalytic activity in the presence or absence of dTTP analogs using primer 18TTA. Telomerase incorporates one dGTP molecule during first repeat synthesis.  The enzyme translocates on the substrate DNA in order to synthesize the next telomeric repeat.  In the absence of dTTP analogs (no drug, top), telomerase successfully synthesizes a complete telomeric repeat of 6 nt.  DNA products expected after a second round of repeat synthesis are noted at right of figure (Primer +n nt).  In the presence of increasing concentrations of either ddTTP, d4T-TP, or AZT-TP (illustrated as purple T), telomerase cannot synthesize past either the primer +4 (middle) or primer +5 (bottom) position and cannot translocate in order to synthesize further repeats.   65 Figure 11 continued.  Representative gel images of the conventional assay testing telomerase in the presence dTTP analogs.  dTTP analogs tested were ddTTP (B), AZT-TP (C), and d4T-TP (D).  Telomerase-specific DNA products are labeled at left and right of each gel.  Free, end-labeled primer is shown for reference.  Primer +4 and +5 products are identified to demonstrate competitive inhibition by the dTTP analogs.   66 Figure 11 continued. Quantification of telomerase inhibition by dTTP analogs.  E. Dose-response curves showing differential telomerase inhibition by ddTTP (black curve), AZT-TP (turquoise curve), and d4T-TP (purple curve).  F.  Histogram showing mean IC50 (µM) of each dTTP analog (n=3 for each analog). Error bars are SD.  IC50 values of AZT-TP and d4T-TP were compared to that of ddTTP using a Student’s T-test for independent samples.  Statistical significance was reached when two-tailed P values of less than 0.05 were observed.  Asterisk (*) denotes P < 0.05.  Dose-response curves were generated in GraphPad Prism. !"#!$ "%! "%& "%$ "%' "%( !%! ))**+ ,-*#*+ ).*#*+ !"" !"! !"/ !"& !". !"#$%&&'()*)!"#+,-./ ! " #$ % $# & '( ) *! #$ % ) '# + ', - # 01 ./ 0 1 (, - . / ))**+ ,-*#*+ ).*#*+ $ !$ /$ &$ .$ $$ )**+2343567 ))**+ ,-*#*+ ).*#*+ ! # "%"$/8 "%$/&. &"%9. ..%"8 /.%!/ :; $"2 !"#$ 2!3*)' 4%2 2 <=>>3?@2 6A2 )**+2 3435672BCDB?E>B4FG%   67 Figure 12. A.  Schematic illustrating telomerase catalytic activity in either the presence or absence of dATP analogs using primer 18TTA.  Telomerase incorporates one dGTP molecule during first repeat synthesis.  The enzyme translocates on the substrate DNA in order to synthesize the next telomeric repeat.  In the absence of dATP analogs (no drug, top), telomerase successfully synthesizes a complete telomeric repeat of 6 nt.  DNA products expected after second repeat synthesis are noted at right of figure (Primer +n nt).  In the presence of increasing concentrations of either ddATP or TFV-DP (illustrated as orange A), telomerase cannot synthesize past the primer +6 position and cannot translocate in order to synthesize further repeats. TERT !!!!!!!!!!!"##$"""##$" !%&'''((#'''((#'''((#!)'!*& !"#$%"&'(") *+, -. /. !"#$%&'(#!)'$* #$+*%,$!-.%)% /)"%!*".0.#!*#++)!)'$ 1")2."*34*$! $' *+" 56 3++78198/:;<1 &'01$'2!13")0456 =.('$+*".0.#!*#++)!)'$ !!!!!!!!!!!!!!"##$"""##$" '''((#'''((#'''((#'''((# !!!!!!!!!!!!!!"##$"""##$" '''((#'''((#'''((#'''((#' 1")2."*3>*$! 1")2."*3?*$! )$('"0'"#!)'$*'@*+781*#$#&'6%* (#5%.%*(-#)$*!."2)$#!)'$*#!* 0")2."*3*>*$! ,   68 Figure 12 continued.  Representative gel images of the conventional assay testing telomerase in the presence dATP analogs. B-C.  Representative gel images of the conventional assay testing telomerase in the presence of ddATP (B) and TFV- DP (C).  Telomerase-specific DNA products are labeled to the left and right of each gel.  Free, end-labeled primer is shown for reference.  Primer +6 products are identified to demonstrate competitive inhibition by the dATP analogs.   69  Figure 12 continued. Quantification of telomerase inhibition by dATP analogs. D.  Dose-response curves showing differential telomerase inhibition by ddATP (black curve) and TFV-DP (turquoise curve).  E.  Histogram showing mean IC50 (µM) of each dATP analog (n=3 for both ddATP and TFV-DP).  Error bars are SD.  Data were analyzed using a Student’s T-test for independent samples with Welch’s correction.  Differences were considered statistically significant when P < 0.05. !" !"#$%&'()*+*!"#,-./0 ! " #$ % $# & '( ) *! #$ % ) '# + ', - # ./ 0 1 )- . / 0 ##$%& %'()"& * +, ,* -, .** .+, .,* .-, .*)., */. */0 */, */- */1 ./. ##$%& %'()"& .** .*. .*+ .*0 .*2 #$%&3454678 ##$%& %'()"& ! ) */*1+, .+/,- .*1/- 9: ,*3 !"#$ 2!3*)' 0/3 3 ;<==4>?3 7@3 #$%&3 4546783ABCA>D=A5EF/   70 Figure 13. A. Schematic illustrating the DNA products expected either in the absence (left panel) or presence (right panel) of dGTP analogs.  At high concentrations of a dGTP analog, the intensity of the primer +3 band should be dramatically diminished or disappear completely.  Telomerase catalysis is restricted to only one round of synthesis with this experimental set up.   71 Figure 13 continued.  Representative gel images of the conventional assay testing telomerase in the presence dGTP analogs. Representative gel images of the conventional assay testing telomerase in the presence of ddGTP (B) or CBV-TP (C). Telomerase-specific DNA products are labeled at left of each gel as primer +3.  Free, end-labeled primer is shown for reference.   72 Figure 13 continued. Quantification of telomerase inhibition by dGTP analogs. D.  Dose-response curves showing differential telomerase inhibition by ddGTP (black curve) and CBV-TP (turquoise curve).  E.  Histogram showing mean IC50 (µM) of each dGTP analog (n=3 for both ddGTP and CBV-TP).  Error bars are mean ± SD.  Data were analyzed using a Student’s T- test for independent samples.  Statistical significance was reached when P < 0.05. !"#$%&'()*+*!"#,-./0 ! " #$ % $# & '( ) *! #$ % ) '# + ', - # !" #$%#& $'# $'( $'& $') $'* #'# #'( ++,-. /01%-. #$$ #$# #$2 #$( #$3 ++,-. /01%-. $ #$$ 2$$ ($$ 3$$ &$$ +,-.454678 ++,-. /01%-. ! % $'$93* (2'*9 (&)') :/ &$; !"#$ .!/*)' 0'; ; <=>>4?@; 7A; +,-.; 454678;BCDB?E>B5FG' 12 3 4 )- . / 0   73 Fig. 14.  The NNRTIs NVP and EFV do not inhibit telomerase in vitro.  A.  Representative gel image showing the result of the conventional assay testing NVP and EFV at 1 mM against telomerase.  B.  Histogram showing the mean raw activity of telomerase in the presence of 5% DMSO, 1 mM NVP, and 1 mM EFV (n=3 for all treatments).  Error bars are mean ± SD. Statistical significance was reached when P < 0.05.  C.  Gel image of the conventional assay testing NVP and EFV at 4 mM (n=1). Note: NVP and EFV were 10% of the final reaction volume, hence the control of 10% DMSO.  An untreated reaction (i.e., no DMSO or drug) is shown for comparison.  !"#$%&' ()* +,) - ./-0.- 1 2/-0.- 1 3/-0.- 1 ! " # $" % &' ( '& ) 4567896:8 !"#$%&' ()* +,) ! ; -/<= -/=1 ./1>#0#.-1 2/-.#0#.-1 ./1<#0#.-1 ?@A/#B7C# 7D8E@E8F .#9% + , ) ! " #$ % & ' G5E965 H.- H.> H22 H21 G5E965#HI BJ ( ) * ? K I#9% + , ) . - " #$ % & ' ( ) * L : 85 6 7 86 M J G5E965 H.- H.> H22 H21 G5E965#HI BJ *"+,-.$ //# # &N9975F# OP# ((B4Q# 60G65E96:8R   74 5.  TELOMERE MAINTENANCE IN HUMAN CELLS 5.1.  Introduction My second approach to studying the effects of N/NRTI treatment on telomere/telomerase biology involved asking whether longer-term exposure of human telomerase-positive cells with N/NRTIs would affect the dynamics of telomere length maintenance.  I used the human colorectal carcinoma cell line HT29 as a cell culture model.  Similar to most human cancer cell lines, HT29 cells depend on constitutive telomerase activity to maintain their telomeres for immortal growth in culture (Naasani, Seimiya et al., 1998; de Souza Nascimento, Alves et al., 2006).  Given that in vitro and epidemiological studies indicate that HIV itself may interfere with telomere maintenance, possibly through telomerase inhibition, it was important for us to use a cell culture model that did not include any HIV components.  I designed my cell culture model such that any perturbation in telomere length maintenance measured in N/NRTI-treated cells was due to drug treatment and no other factor. There are, in general, four different assays available to measure telomere length in human cells i) the terminal restriction fragment length (TRF) assay, ii) single telomere length analysis (STELA), iii) quantitative PCR, and iv) telomere-fluorescent in situ hybridization (telomere-FISH or Q-FISH) (Aubert, Hills et al., 2011).  The TRF assay is the first and oldest method used in measuring telomere length, and is the gold standard in telomere length measurement (Moyzis, Buckingham et al., 1988; Allsopp, Chang et al., 1995).  In the TRF assay, genomic DNA is digested with frequent cutting restriction endonucleases that do not recognize telomeric DNA.  The digested DNA is resolved through agarose gel electrophoresis, and TRFs are visualized by in-gel hybridization with an end-labeled radioactive telomeric DNA probe.  TRF size is normally quantified as a weighted average by using molecular mass markers resolved in parallel with digested DNA.  The main advantage of the TRF assay is that one can directly measure and visualize telomere length.  A disadvantage of the assay is that genomic DNA at the subtelomeric region is polymorphic.  Depending on the restriction   75 endonuclease recognition sequences, this polymorphism could affect final TRF quantification as a result of counting a substantial part portion of the subtelomeric region as telomeric sequences. This disadvantage is particularly concerning when measuring TRF in genetically diverse samples, such as the general population.  Moreover, the TRF assay requires a substantial amount of starting material (at least 1 µg of genomic DNA), which could be difficult to obtain for clinical research. STELA is a PCR-based method for measuring telomeric regions on individual chromosome ends, usually the well defined XpYp, 2p, 11q, and 17p (Britt-Compton, Rowson et al., 2006).  Using a chromosome specific primer from the subtelomeric region and a non-specific tagged primer that recognizes the telomeric sequence, STELA uses PCR to amplify the region between the subtelomeric primer-binding site and the end of the chromosome.  The PCR product thus contains information on regional telomeric length for that particular chromosome. Although STELA offers the advantage of very accurate telomere-length measurements with little starting material, its analysis can be labor intensive as telomere length, even for the same chromosome, varies between cells, and the PCR products of each STELA reaction can be highly variable in size. Secondly, the analysis of only a few telomere ends may not be representative of all telomeres in a sample.  In addition, by virtue of the limitation of long-range PCR, STELA sets an upper limit on telomere-length measurement; therefore it is not amenable to measuring telomeres greater than 20 kb in length.  Another method of telomere measurement is the quantitative PCR-based method (Cawthon, 2002).  The basis of the qPCR assay is that primers are used to amplify telomeric repeats, thereby avoiding the more variable subtelomeric regions. Primers anneal to both the G- and C-rich strands of the telomeres but contain mismatches to avoid dimerization. The amplification of telomeric DNA is measured quantitatively and compared to that of a single copy gene in order to generate a ratio between telomeric and single gene amplification (the T/S ratio). The telomere qPCR assay has been widely adopted in epidemiological research as it requires   76 no special equipment, is a relatively quick assay to perform, and requires very little starting material. However, there are definite drawbacks to this method.  Firstly, there is no direct readout of telomere length information.  A correlation analysis can be performed with a known standard, containing a DNA sample with measured telomere length to estimate telomere length of a sample, however scale compression can nonetheless occur for the extremely short or extremely long telomere lengths.  Secondly, there is variability in methodology between research centres, making it difficult to compare the T/S ratio between studies (Aubert, Hills et al., 2011).  Finally, it is necessary to confirm whether the single copy gene used is actually present in a single copy in the genome.  Aside from copy number polymorphisms with normal human populations, it may be of particular concern in genetically unstable, transformed cell lines or tumor specimens where aneuploidy is a common occurrence.  Lastly, telomere FISH (also called Q-FISH) measures telomere length by hybridizing a fluorescent telomere-specific peptide nucleic acid probe to denatured telomeric DNA in metaphase spreads of human cells (Lansdorp, Verwoerd et al., 1996).  The fluorescent signal is detected and measured relative to a standard of known telomere length using image quantification software.  Telomere FISH has been optimized to study telomere biology in broad settings and may be useful in measuring telomere length in rare cells, such as hematopoietic stem cells (Goldman, Aubert et al., 2008).  The disadvantage of telomere FISH is that it requires cells that are able to divide and additionally cannot detect telomeres in terminally senescent cells, as metaphase spreads cannot be prepared from non-dividing cell samples.  A variation of telomere FISH is flow-FISH, which makes use of flow cytometry to measure median telomere length in suspension cells.  An obvious advantage of this method is that cells at any phase of the cell cycle could be measured and thereby negating the need for the generation of a metaphase spread.  The ability to co-sort for various cell types by using antibodies for cell-type specific surface biomarkers is also highly useful for studies of hematopoietic cell types.   77 Although a useful technique, the flow-FISH technique still requires optimization to allow adoption by more laboratories. I decided to use the TRF assay to measure telomere length in my samples.  The TRF assay allows us to quantify telomere length directly, whereas all other methods (except STELA) provide only a relative measurement to a known standard.  Furthermore, since I am using cancer cells as a model, biological material is not limiting in my experiments.  Differences in TRF measurements will be compared within a single cell line, therefore polymorphism and variability in the subtelomeric region is not a consideration in my final analysis. If N/NRTIs inhibit telomerase, a decrease in TRF size over the course of the experiment should be evident.  The dynamics of this TRF loss over time should also be captured if I measured TRF at regular intervals over the course of my cell culture experiments, instead of just performing endpoint measurements.  In normal somatic cells without telomerase activity, an average loss of 100bp of telomeric DNA is expected in every cell division.  Population doubling level (PDL) is a cumulative measure of the number of cell divisions a population of cells has gone through over the course of an experiment.  In my case, the start of an experiment is defined to have a PDL of 0.  When the entire population of cells has gone through one cell division, such that the number of cells doubles, then the PDL increases by 1. In a cell line with constitutive telomerase activity such as HT29, complete telomerase inhibition is expected to decrease telomere length at a rate similar to that observed in normal human somatic cells (i.e., 100 bp/PDL).  The average TRF length in HT29 cells is between 7 – 9 kb.  In this size range of DNA molecular weight, my TRF assay can clearly resolve the DNA ladder in 1 kb intervals.  I assume that in the case where maximal telomerase inhibition occurred in HT29 cells, analyzing TRF at intervals of 10 PDL would allow us to measure a 1 kb change in TRF size (10 PDL x 100 bp TRF lost/PDL = 1000 bp) between each time point.  I subsequently determined empirically that on average, I am able to detect TRF changes of 0.3 kb in the median range of TRF length in HT29 cells run on a   78 single gel (intra-assay variability).  This number was calculated by measuring the variability in average TRF size of the same sample run multiple times in a single gel.  I also determined that, on average, I could expect variability of up to 0.6 kb when comparing the same sample on different gels (inter-assay variability). For drug dosage, my approach in treating HT29 cells was to test N/NRTIs in the range of their maximum plasma concentrations (plasma Cmax) as measured in humans (Table 1).  I reasoned that testing N/NRTIs at concentrations in that range would allow us to infer what impact constant exposure might have on human cells in vivo with respect to telomere biology. In addition, the constant exposure to N/NRTIs over a relatively long period of time (at least 30 days in most cases) reflects the use of these drugs in humans, given that HAART is life-long. Normal human cells generally undergo a maximum of 50 PDL in culture (Smith and Hayflick, 1974), and I plan to culture HT29 cells for at least 20 PDL.  Thus, the duration of my cell culture experiments should represent approximately half of the normal lifespan of a normal human cell.  When I observed a trend of decreasing TRF with a given drug treatment, I discussed my data in terms of a rate of TRF loss.  The rate of loss was calculated by dividing the cumulative TRF lost by total PDL, resulting in TRF lost (kb)/PDL, assuming a linear relationship of TRF loss from day 1.  This is in most cases a theoretical representation of my data, as I learned that telomere loss dynamics could be variable as treatment length increased.  Presenting the data this way gives us insight into telomeric DNA loss with NRTI treatment per cell division within the experimental window, and allows us to comment on whether telomerase inhibition is the only mechanism behind TRF loss observed.  The maximum expected decrease in TRF per cell division, due to the inhibition of telomerase in human cells is 200 bp.  Anything beyond this rate is likely due to factors other than telomerase inhibition, such as direct telomeric DNA degradation or chromosome loss/fusion.     79 5.2.  Results and discussion I In the first HT29 cell culture experiment, I tested only the NRTIs.  Untreated HT29 cells, and cells treated with PBS or DMSO as vehicle controls were cultured in parallel with the NRTI treatments (Fig. 15A).  As expected, the growth curves of the vehicle-treated cells deviated very little from that of the untreated HT29 cells (Fig. 15B).  I observed very little TRF change in untreated and PBS-treated cells with no apparent trend (Figs. 15A left, 1C).  In DMSO-treated cells, however, there was a trend in TRF change over the course of the experiment, with TRF size consistently decreasing (Figs. 15A right, 1C).  The rate of TRF loss in DMSO-treated cells was 31 bp/PDL, and must be taken into account in the interpretation of DMSO-soluble drugs (ABC, ddI). I tested two dTTP analogs, AZT and d4T, in the first HT29 cell culture experiment. Based on data from my laboratory and from published work (Brown, Sigurdson et al., 2003), I tested AZT at 62.5 and 125 µM (Fig. 16A, right).  These concentrations are well above the plasma Cmax for AZT, which is approximately 5 µM.  AZT caused HT29 cells to double at a slower rate compared to untreated cells, especially before 5 PDL (Fig. 16B).  The effect on growth was similar in magnitude between the two AZT concentrations.  I observed a substantial decrease in TRF size in HT29 cells treated with both concentrations of AZT.  With continuous exposure to AZT at 62.5 µM I measured a TRF decrease of 158 bp/PDL (Figs. 16A and C).  In HT29 cells treated with 125 µM AZT, I observed a more exaggerated TRF decrease of 192 bp/PDL. Thus, AZT led to a substantial and dose-dependent decrease in TRF that correlated with a slowed growth rate compared to untreated HT29 cells.  Furthermore, the rates of loss measured with AZT treatment are consistent with complete telomerase inhibition. I tested d4T at three concentrations ranging from 5 to 40 µM, which is slightly higher than its plasma Cmax of between 2-3 µM (Fig. 17).  There was a very small but noticeable dose-dependent effect on the doubling rate of HT29 cells treated with d4T, with d4T-treated cells having a slightly slower growth rate compared to untreated cells (Fig. 17B).  In HT29 cells   80 treated with d4T at 5, 20 or 40 µM, TRF decreased at 47, 52, and 50 bp/PDL, respectively (Figs. 17A and C).  The fact that the rate of TRF decrease is similar over this range of d4T concentrations suggests that there could be a threshold beyond which I might observe more substantial TRF loss.  I addressed this possibility in my second cell culture experiment. There are currently two dATP analogs used in HAART—TDF and ddI—and I tested both in my HT29 cell culture system.  I tested TDF at 50 and 100 µM in HT29 cells, which is substantially higher than its plasma Cmax of 1 µM (Fig. 18A).  Compared to the rest of the NRTIs tested in this cell culture experiment, TDF showed the greatest toxicity in HT29 cells. Cells treated with 50 µM TDF survived in culture to 8 PDL, while cells treated with 100 µM survived only to 3 PDL (Fig. 18B).  TDF caused a slight decrease in HT29 TRF size at both concentrations tested.  With constant exposure to 50 µM TDF, TRF in HT29 cells lost 62 bp/PDL (Figs. 18A and C).  At 100 µM TDF, a TRF decrease of 200 bp/PDL.  The rate of TRF decrease measured in the HT29 cells treated with 100 µM TDF is approximately three-fold higher than that observed in cells treated with 50 µM.  Thus, the effects of TDF on cell growth and on TRF size appear to be dose-dependent.  I tested the second dATP analog, ddI, at 30, 60 and 120 µM (Fig. 19A).  Similar to TDF, I observed a dose-dependent effect on the growth of ddI-treated HT29 cells in culture (Fig. 19B). In contrast to TDF, however, HT29 cells treated with the highest concentration of ddI, 120 µM, were robust in culture over the entire course of the experiment.  In terms of TRF dynamics, TRF decreases in HT29 cells treated with 30, 60 and 120 µM ddI were 33, 44, and 67 bp/PDL, respectively (Figs 19A and C right).  Since ddI is a DMSO-soluble drug, I subtracted the background rate of TRF loss in DMSO-treated HT29 cells.  The revised rates of TRF loss were 2, 13, and 36 bp/PDL in cells treated with 30, 60 and 120 µM ddI, respectively.  The rates of loss for the 30 and 60 µM ddI were hardly above the background rate, indicating that these concentrations do not substantially affect telomere maintenance.  Nonetheless, the effects of ddI on HT29 cell growth and TRF dynamics appear to be dose-dependent.   81  Finally, I tested one dGTP analog, ABC, in the first HT29 cell culture experiment.  I tested ABC at 5, 10, and 20 µM (Fig. 20A), which is in the range of its reported plasma Cmax of 10-15 µM.  Interestingly, the effect of ABC on the growth of HT29 was opposite to that of drugs like ddI and d4T.  Whereas ddI and d4T slowed HT29 growth rate, with the most severe effect occurring at the highest concentration of each drug, the slowest growing HT29 cells treated with ABC were those treated with the lowest concentration (Fig. 20B).  I measured TRF decreases of 47, 53, and 63 bp/PDL for 5, 10, and 20 µM ABC, respectively (Fig. 20A and C).  Similar to ddI, ABC is a DMSO-soluble drug, so the revised estimates of TRF loss were 16, 21, and 32 bp/PDL.  The trend in the rate of TRF loss agrees with what was measured with ddI and TDF, which is increasing rate of TRF loss with increasing drug concentration.  However, the trend in rate of TRF loss is exactly opposite of the trend observed with the effect of ABC on the growth of HT29 cells, arguing that the rate of cell growth in the presence of NRTIs does not necessarily predict their effects on telomere dynamics.  In this series of cell culture experiments, I measured TRF loss with all NRTIs tested. AZT and TDF had the greatest impact on telomere maintenance in HT29 cells, d4T had an intermediate effect, and ddI and ABC had the least impact.  I might have expected to be able to group the NRTIs and their impact on telomere maintenance by their analog type.  That is, I might have expected the two dATP analogs, ddI and TDF, to have a similar impact on telomere maintenance, and the two dTTP analogs, AZT and d4T, to be similar to each other.  The discrepancy in the rates of TRF loss between AZT and d4T can be explained by the concentrations used.  Taken at face value, AZT had a higher rate of TRF loss when compared to d4T, but the concentrations of AZT tested were higher than those of d4T.  The same line of reasoning cannot be applied to the dATP analogs.  Furthermore, I anticipated the dGTP analog ABC would have the greatest impact on telomere maintenance, since dGTP is the most abundant nucleotide in the telomeric repeat TTAGGG.   82 An important caveat to take into consideration in interpreting these cell culture data is that I did not measure senescence or apoptosis.  However, preliminary experiments done with the NRTIs used in this experiment in HT29 cells demonstrated a lack of an affect on cell viability with the trypan blue assay.  PDL is supposed to represent the number of cell divisions the population has gone through over the course of the experiment.  Since I cannot completely account for cells in proliferative arrest due to senescence or apoptosis, I cannot directly infer that 20 PDL is 20 cell divisions, since cells maintaining proliferative capacity within the population would have had to divide more to compensate for proliferative deficiencies as a result of non-dividing cells.  However, since HT29 cells have constitutive telomerase activity and maintain a constant telomere length over time, an increased proliferative demand should not impact telomere length maintenance.  In conclusion, this suggests that the rates of loss reported might, under some circumstances, be an overestimate, i.e. the population of cells being measured for their TRF have undergone a higher number of cell divisions.   83 Figure 15.  A.  TRF blots of untreated and vehicle treated (PBS and DMSO) HT29 cells. Time points used for analysis (PDL) are shown at the top of the gel image, above each lane. The phosphorimage quantified, weighted average of TRF size (kb) is shown at the bottom of the gel, below each TRF smear. B.  Growth curves of untreated and vehicle-treated HT29 cells.  C.  Graphical representation of telomere dynamics in untreated and vehicle treated HT29 cells.  Note the relatively constant TRF size over the course of the experiment.    84 Figure 16. A.  TRF blot of untreated and AZT-treated HT29 cells. Time points used for analysis are identified at the top of the gel, above each lane.  The weighted average of TRF size (kb) is shown at the bottom of the gel, below each TRF smear.  Note the continuous and dose-dependent TRF length decrease in the AZT-treated HT29 cells with time.  B.  Growth curves of HT29 cells treated continuously with AZT.  The growth curve of untreated HT29 cells is plotted in parallel with both AZT for comparison.  Note the decreased growth rate in AZT-treated HT29 cells.  C.  Graphical representation of telomere dynamics in untreated and AZT-treated HT29 cells.     85 Figure 17.  A.  TRF blots of untreated and d4T-treated HT29 cells. TRF blot of untreated HT29 cells is shown for comparison.  Time points used for analysis are identified at the top of the gel, above each lane.  The weighted average of TRF size (kb) is shown at the bottom of the gel, below each TRF smear.  Continuous treatment with d4T appears to cause a small decrease in TRF size over time.  B.  Growth curves of HT29 cells treated continuously with d4T.  The growth curve of untreated HT29 cells is plotted together with that for d4T treated cells for comparison.   C.  Graphical representation of telomere dynamics in untreated and d4T-treated HT29 cells.     86 Figure 18. A.  TRF blots of HT29 cells from untreated and TDF-treated HT29 cells.  Time points used for analysis are identified at the top of the gel, above each lane.  The weighted average of TRF size (kb) is shown at the bottom of the gel, below each lane.  B.  Growth curves of HT29 cells treated continuously with TDF.  The growth curve of untreated HT29 cells is plotted together for comparison.  Note the dose-dependent decrease in doubling rate and viability in TDF-treated HT29 cells. C.  Graphical representation of telomere dynamics in untreated and TDF-treated HT29 cells.    87 Figure 19. A.  TRF blots of HT29 cells from untreated and ddI-treated HT29 cells.  Time points used for analysis are identified at the top of the gel, above each lane.  The weighted average of TRF size (kb) is shown at the bottom of the gel, below each lane. B.  Growth curves of HT29 cells treated continuously with ddI.  The growth curve of untreated HT29 cells is plotted on the same graph for comparison.  ddI caused a decrease in doubling rate, with the highest concentration having the most dramatic effect.  C.  Graphical representation of telomere dynamics in untreated and ddI-treated HT29 cells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igure 20. A.  TRF blots of HT29 cells that were either untreated (left) or continuously treated with ABC.  Time points used for analysis (PDL) are shown at the top of the gel image, above each lane.  The weighted average of TRF size (kb) is shown at the bottom of the gel, below each lane.  At the concentrations tested, ABC appeared to cause slight, dose- dependent loss of telomeric DNA over time compared to untreated HT29 cells.  B.  Growth curves of untreated and ABC-treated HT29 cells.  Note the differences in doubling rate among the different ABC concentrations compared to untreated cells.  C.  Graphical representation of telomere dynamics in ABC-treated HT29 cells compared to untreated HT29 cells.    89 5.3.  Results and discussion II In the second HT29 experiment, I tested both NRTIs and the two NNRTIs currently used in clinical therapy, NVP and EFV.  In addition to re-testing some of the NRTIs from the first HT29 cell culture experiment, I included the dCTP analog lamivudine (3TC) as an additional control. Since the telomeric repeat TTAGGG does not include cytosine, I did not expect 3TC to have any impact on telomere maintenance, but wanted to control for the presence of an NRTI that might cause proliferation defects in HT29 cells through other mechanisms, such as inhibition of other DNA polymerases.  I re-tested both d4T and ABC, and included AZT as a positive control for telomere shortening.  Since I observed a similar rate of TRF loss (average of 50 bp/PDL) with d4T when tested in the range of 5 – 40 µM, I wanted to determine whether higher concentrations would cause a higher rate of TRF loss.  When I tested ABC in HT29 cells in the range of 5-20 µM, the rates of TRF loss were similar between the concentrations tested and were not substantially above the background rate of loss.  Similar to the reasoning applied to d4T, I wondered whether higher ABC concentrations would lead to increased rates of TRF loss. I treated HT29 cells with either PBS or DMSO as vehicle controls, and kept a continuous culture of untreated HT29 cells throughout the entire experiment (Fig. 21A).  There were no major deviations in the growth curves of the vehicle-treated cells compared to untreated cells (Fig. 21B).  Surprisingly, in the untreated HT29 cells, I observed a consistent decrease in TRF size over the course of the experiment (Figs. 21A left panel, 21C).  TRF loss in untreated HT29 cells was especially apparent after 9 PDL. In the vehicle control treatments, a less pronounced effect was seen, perhaps due to the lack of data extending beyond 30 days (Figs. 21A right panel, 21C).  I reasoned that even though an apparent TRF loss in control cells will complicate my analysis, my comparison between treatment groups should still be valid if the cell cycle time for HT29 did not change between groups; and that I always compared the TRF profiles from N/NRTI treated cells to that of the vehicle control treated cells. The plasma Cmax of 3TC is 6-7 µM, and I exposed HT29 cells to 80 µM.  Similar to the vehicle controls, I observed little   90 deviation of 3TC-treated cells with respect to TRF dynamics and growth characteristics (Figs. 22A and B).  I measured a trend of decreasing TRF in 3TC-treated cells (Fig. 22A), but when TRF loss was plotted against time, it paralleled that of the untreated HT29 cells (Fig. 22C). Given that I included AZT only as a positive control in this experiment, I used a single concentration of the drug (125 µM) (Fig. 23A).  AZT slowed the growth rate of HT29 cells compared to untreated cells, and led to a marked decrease in TRF size, both of which are in agreement with observations from experiment one (Figs. 16 and 23).  The magnitude of the effect of AZT on the growth of HT29 cells was similar to that observed in the first experiment and the rate of TRF decrease measured in this experiment was slightly less than that observed in the first experiment (142 bp/PDL versus 192 bp/PDL, respectively).  I cannot rule out whether the discrepancy in the rate of TRF loss is biological, chemical, or due to a natural variation in my cell culture system. I exposed cells to 40, 80, and 160 µM d4T continuously, a range which is substantially higher than the plasma Cmax for d4T (2-3 µM) (Fig. 24A).  I observed dose-dependent effects on both cell growth and telomere maintenance, with the highest d4T concentration of 160 µM having the most impact on both (Fig. 24B and C).  At relatively high concentrations (80 and 160 µM), d4T treatment caused a considerable drop in TRF size.  The drop in TRF size, however, seems to happen abruptly at the last PDL measured (PDL 21 for 80 µM, PDL 18 for 160 µM) rather than continuously as I would expect in the case of a consistent level of telomerase inhibition.  In considering only the last two PDL analyzed for 80 and 160 µM d4T, the rate of TRF loss is 30 and 330 bp/PDL, respectively.  The loss measured in HT29 cells treated with 80 µM is within a physiologically plausible range due to telomerase inhibition.  The loss measured in HT29 cells treated with 160 µM, in contrast, is well beyond physiological range for the rate of TRF loss due to telomerase inhibition alone. Abrupt induction of cellular apoptosis at this stage is unlikely, as I would have expected apoptosis-related genome disturbances to occur earlier rather than late in the experiment.  Other explanations for the additional telomere shortening   91 include: 1) the accumulation of oxidative stress or 2) the inhibition of other nuclear polymerases in addition to telomerase inhibition observed at this high dose of d4T.  Alternatively, as the culture is quite sickly after the continuous exposure to d4T for over 65 days, a rare selective event might have occurred that allowed a survivor HT29 clone, with undetermined genetic changes to tolerate high d4T drug concentration to emerge.  This genomic instability event could be fueled by short telomere- induced genome-wide instability or could be a passenger attribute of the selected HT29 clone.  I tested ABC at 12.5, 50 and 100 µM in HT29 cells  (Fig. 25A right panel).  The plasma Cmax for ABC is 10 – 15 µM.  In the first cell culture experiment, the lowest concentration of ABC (5 µM) had the most pronounced effect on the growth of HT29 cell growth and the highest concentration (20 µM) the least (Fig. 20B).  In the second experiment I observed the opposite, with the lowest concentration of ABC (12.5 µM) having no effect on cell growth and the highest concentration (100 µM) having the most pronounced effect (Fig. 25B). I currently cannot find any physiological explanation for this bell-shaped dose-viability effect for ABC in the literature. Increasing the concentrations of ABC proved to be a worthwhile experiment, as I uncovered a dose-dependent size decrease in TRF with these treatment doses (Figs. 25A and C). The rate of TRF loss in untreated cells cultured in parallel with the ABC-treated cells was 67 bp/PDL.  TRF in HT29 cells treated with 12.5 µM ABC actually decreased at a slower rate than untreated cells, at 42 bp/PDL.  Cells treated with 50 µM ABC lost telomeric DNA at a rate over 1.5-fold that of the untreated cells, at 110 bp/PDL.  I measured a rate of TRF decrease in cells treated with 100 µM ABC of 350 bp/PDL, which is beyond physiological possibility when considering only telomerase inhibition as a cause of TRF decrease.  When the background rate of loss of 67 bp/PDL is subtracted from the rate of loss measured in cells treated with 100 µM ABC, the rate of loss of 283 bp/PDL in this treatment is still beyond what is physiologically possible as a result of telomerase inhibition alone.  In contrast to d4T at 160 µM, it is possible that apoptosis occurred at the time point used to measure TRF in cells treated with 100 µM ABC   92 since these cells only survived to PDL 3.  I may have been measuring the effect of apoptosis- induced nuclear DNA fragmentation in the remaining cell population, right before the formation of the apoptotic bodies. Lastly, I tested both NNRTIs NVP and EFV in my cell culture system (Figs. 26 and 27). The plasma Cmax for NVP is 20 µM.  Based on previous experiments in my lab indicating that NVP is well tolerated at high concentrations, I exposed HT29 cells to 100 and 200 µM NVP (Fig. 26A).  Neither 100 nor 200 µM NVP had an effect on HT29 cell growth when compared to untreated cells (Fig. 26B).  The background rate of TRF loss in untreated HT29 cells for the duration of the NNRTI experiment was 33 bp/PDL (Figs. 26A and C).  In HT29 cells treated with NVP at 100 and 200 µM, the rates of TRF loss were 74 and 28 bp/PDL.  Taking the background rate of TRF loss into consideration, it seems that the lower concentration of 100 µM affected telomere maintenance while the higher concentration did not, and could be interpreted as a technical or biological variation in the system. I tested EFV at 6 and 12 µM, which is close to its plasma Cmax of 13 µM (Fig. 27A). Treatment of HT29 cells with 6 µM EFV did not substantially affect growth, while treatment with 12 µM caused a dramatic decrease in the growth rate (Fig. 27B).  EFV at 12 µM was toxic to HT29 cells, as they remained viable in culture only up to 10 PDL.  The effect on cell growth and viability at 12 µM EFV is surprising since it is so close to the plasma Cmax of this drug.  EFV did not cause TRF loss above background at either concentration tested (Fig. 27A and C). In my second cell culture experiment, I measured TRF loss with all NRTIs tested except for 3TC.  In addition to telomerase inhibition, I suspected that NRTIs might also cause telomere shortening through alternate mechanisms such as increased oxidative stress due to mitochondrial toxicity or the general inhibition of DNA synthesis by other nuclear polymerases, not just at the telomeres. The dCTP analog 3TC was used to control for the presence of a chain-terminating nucleotide analog in HT29 cells to measure the contribution of these non- specific mechanisms to telomere maintenance dynamics.  At 80 µM, which is over 10-fold above   93 the plasma Cmax for 3TC, I did not measure any TRF loss above background.  In contrast, I did measure TRF loss in HT29 cells treated with all other NRTIs.  This comparison suggests that TRF loss phenotypes were most likely contributed by telomerase inhibition in my experiments. Increasing the concentrations of d4T and ABC, compared to the concentrations tested for these drugs in the first cell culture experiment, resulted in an increase in the rate of TRF loss.  In terms of telomere maintenance, it appears that HT29 cells are able to tolerate d4T when exposed to concentrations below 40 µM, but not at or above 80 µM.  Similarly, HT29 cells were able to maintain telomere length in the presence of up to 20 µM ABC, but not at or above 50 µM.  Given that I did not test all NRTIs over a low and high range of concentrations, I cannot comment on whether all other NRTIs tested in my experiments (AZT, ddI, TDF) might have shown the same trend of tolerance.  As NRTIs act as competitive inhibitors of telomerase, the endogenous concentrations of the natural nucleotides present intracellularly will have a profound effect on the potencies of these agents.  HT29 cells, by virtue of their oncogenic transformation, are likely to contain high endogenous levels of dNTPs and/or process high production capabilities for deoxynucleotides.  This translates to a higher threshold concentration for NRTIs, below which telomere maintenance would be unaffected.  These threshold levels are likely to be much lower in primary human cells that divide intermittently.  Additionally, cellular variations in processes such as drug influx or efflux, or intracellular kinase activity levels, or possibly a combination of all these biological processes might have contributed to the sensitivity levels of different cell types to the NRTIs. EFV did not cause substantial loss in TRF size in HT29 cells.  NVP, however, affected telomere maintenance at the lower but not the higher concentration tested. The lack of toxicity in HT29 cells treated with 100 µM NVP suggests that telomere shortening was most likely due to telomerase inhibition.  However, the fact that I did not observe a dose-dependent effect on telomere maintenance with NVP argues against telomerase inhibition the cause of telomere shortening.   94 The magnitude of telomere shortening observed in HT29 cells treated with 160 µM d4T and 100 µM ABC suggests biological mechanisms in addition to telomerase inhibition as a cause of telomere shortening.  The growth curve for the HT29 cells treated with these drugs indicates cytotoxicity, especially in the case of cells treated with ABC at 100 µM, which survived in culture only to PDL 3.  However, I also observed loss of cell viability indicative of cytotoxicity in HT29 cells treated with EFV at 12 µM and TDF at 100 µM (exp 1 Fig. 4), yet neither exhibited telomere shortening beyond what is physiologically possible due to telomerase inhibition.  This suggests that the additional causes of telomere shortening in HT29 cells treated with high concentrations of d4T and ABC may be specific to these drugs at the indicated concentrations. AZT and d4T are the only two NRTIs that have been studied in the context of telomere maintenance in human cell lines.  In immortalized T- and B-lymphocytes, continuous treatment with 100 µM AZT caused telomere shortening at rates of 50 and 20 bp/PDL, respectively, while treatment with d4T did not affect telomere maintenance in either cell line (Strahl and Blackburn, 1996).  I measured a much higher rate of TRF loss in HT29 cells treated with a similar concentration of AZT.  The differences in rates of loss could be due to the inherently high variability of TRF length in the T- and B-lymphocyte cell lines used in that study, in addition to the variations in sensitivity to these agents due to inherent metabolic differences between the cell culture systems.  The lack of effect of d4T at 50 µM on telomere maintenance is consistent with my findings. TRF loss was measured in HT29 cells grown in the presence of 125 µM AZT at a rate of 60 bp/PDL (Brown, Sigurdson et al., 2003), which is substantially less than that measured in my experiments.  It is difficult to explain the discrepancy in TRF loss given that the experiments were done in the same cell line.  Careful examination of their assay conditions revealed that the total treatment length was 91 days, a period substantially longer than my experimental set up.  It is conceivable that during the latter part of the long-term drug treatment, outgrowth of resistant clones to the effect of AZT may have reduced the overall effect of telomere length attrition in the   95 reported study.  In MCF7 (human breast cancer) cells, AZT was tested at both 20 and 70 µM for 53 PDL, resulting in rates of TRF loss of 7 and 13 bp/PDL, respectively.  I measured a 11.5-fold higher rate of TRF loss in HT29 cells treated with 62.5 µM AZT (Ji, Rha et al., 2005).  Treatment of HeLa (cervical cancer) cells with 800 µM AZT caused telomere shortening at a rate of approximately 50 bp/PDL (Gomez, Tejera et al., 1998).  However, the TRF methodology used in these particular experiments was modified when compared to most studies, and the method of quantification was not reported in detailed, so it is not clear whether the modified TRF measurements were as robust as the standard assay.  Taken at face value, it would appear that HeLa cells are much more tolerant to the effects of AZT than the HT29 cells used in my experiments.  TRF shortening with 50 µM AZT was also demonstrated in HL60 (promyelocytic leukemia) cells (Liu, Takahashi et al., 2007).  TRF size, however, was not quantified in this study.   96 Figure 21. A.  TRF blots of untreated and vehicle-treated (PBS and DMSO) HT29 cells. Time points used for analysis (PDL) are shown at the top of the gel image, above each lane. The weighted average of TRF size (kb) is shown at the bottom of the gel below each lane. B. Growth curves of untreated and vehicle treated HT29 cells.  Note the minimal deviation of the growth curves of vehicle-treated cells compared to untreated cells.  C.  Graphical representation of data obtained from TRF images in panel A.  TRF size was plotted against time in culture.  Note the gradual decrease in TRF size in the untreated HT29 cells, at a rate of approx. 26 bp/PDL over the course of the experiment.   97 Figure 22.  The dCTP analog 3TC does not cause telomere shortening in HT29 cells. A. TRF blots of untreated and 3TC-treated HT29 cells.  Time points used for analysis (PDL) are shown at the top of the gel image, above each lane.  The weighted average of TRF size (kb) is shown at the bottom of the gel, below each lane. B.  Growth curves of untreated and vehicle treated HT29 cells.  The growth curves of untreated and 3TC-treated HT29 cells overlap with very little deviation.  C.  Graphical representation of data obtained from TRF images in panel A.    98 Figure 23.  A.  TRF blots of AZT-treated HT29 cells. TRF blot of untreated HT29 cells is shown for comparison.  PDLs used for analysis are shown at the top of the gel image, above each lane.  The weighted average of TRF size (kb) is shown at the bottom of the gel, below each lane.  Note the continuous TRF decrease in the AZT-treated HT29 cells with time. B. Growth curves of HT29 cells treated continuously with AZT at 125 µM.  The growth curve of untreated HT29 cells is plotted together with AZT for comparison.  Note the decreased growth rate in AZT-treated HT29 cells compared to untreated cells.  C.  Graphical representation of telomere dynamics in untreated and AZT-treated HT29 cells.  TRF size was obtained from images in panel A.    99 Figure 24.  A. The dTTP analogs AZT and d4T cause telomere shortening in HT29 cells.  A. TRF blots of d4T-treated HT29 cells. TRF blot of untreated HT29 cells is shown for comparison.  PDLs used for analysis are shown at the top of the gel image, above each lane. The weighted average of TRF size (kb) is shown at the bottom of the gel, below each lane. Continuous treatment with d4T at 80 and 160 µM led to an abrupt decrease in TRF.  B. Growth curves of HT29 cells treated continuously with d4T at 40, 80 and 160 µM.  The growth curve of untreated HT29 cells is plotted together with both AZT and d4T for comparison.  Note the decreased growth rate in HT29 cells treated with either 80 or 160 µM d4T compared to untreated cells.  C.  Graphical representation of telomere dynamics in untreated and d4T-treated HT29 cells.  TRF size was obtained from images in panel A.    100 Figure 25. The dGTP analog ABC causes telomere shortening in HT29 cells.  A.  TRF blots of HT29 cells that were either untreated (left) or continuously treated with ABC.  PDLs used for analysis are shown at the top of the gel image, above each lane.  The weighted average of TRF size (kb) is shown at the bottom of the gel, below each lane.  Continuous treatment of HT29 cells with ABC led to a noticeable and dose-dependent TRF decrease over time.  B. Growth curves of untreated and ABC-treated HT29 cells.  Note the decrease in growth rate in HT29 cells treated with 50 (green line) and 100 µM (purple line) ABC.  C.  Graphical representation of telomere dynamics in ABC-treated HT29 cells compared to untreated HT29 cells.  TRF size was obtained from images in panel A.    101 Figure 26.  A.  TRF blots of untreated HT29 cells HT29 cells that were continuously treated with either 100 µM NVP or 200 µM NVP.  Time points used for analysis (PDL) are shown at the top of the gel image, above each lane.  The weighted average of TRF size (kb) is shown at the bottom of the gel, below each lane.  B.  Growth curves of HT29 cells treated continuously with NVP.  The growth curve of untreated HT29 cells is plotted together for comparison.  C.  Graphical representation of telomere dynamics in untreated and NVP- treated HT29 cells.  TRF size was obtained from images in panel A.    102 Figure 27.  A.  TRF blots of untreated HT29 cells and HT29 cells that were continuously treated with 6 µM EFV or 12 µM EFV.  Time points used for analysis (PDL) are shown at the top of the gel image, above each lane.  The weighted average of TRF size (kb) is shown at the bottom of the gel, below each lane. B.  Growth curves of HT29 cells treated continuously with EFV.  The growth curve of untreated HT29 cells is plotted in parallel for comparison. Note the slowed growth of the HT29 cells treated with 12 µM EFV. C.  Graphical representation of telomere dynamics in untreated and EFV-treated HT29 cells.  TRF size was obtained from images in panel A.  Note that continuous treatment with EFV at 12 µM decreased the population doubling rate of HT29 cells (B) yet had no effect on telomere maintenance (A and C).    103 6.  GENERAL DISCUSSION 6.1.  Brief summary Telomerase-mediated telomere maintenance is an important factor in maintaining the replicative capacity of human cells.  I showed that NRTIs, which are an integral class of agents in anti-HIV drug therapy, inhibit telomerase activity in vitro.  In addition, I showed that continuous treatment of telomerase-positive transformed human cells with selected members of NRTIs caused telomere shortening over time.  My experiments were the first to test the full panel of clinically relevant NRTIs against telomerase activity in vitro and on telomere length maintenance in human cells.  In addition, my experiments were the first to test the non-nucleoside RT inhibitors, nevirapine and efavirenz, against telomerase activity and telomere maintenance.  My data support the need for further biochemical, as well as clinical and epidemiology studies to investigate the long-term effects of NRTI toxicity against telomere biology.  6.2.  NRTI inhibition of telomerase, HIV RT, and other cellular polymerases Using the in vitro primer extension assay for telomerase activity, I demonstrated that all NRTIs approved in HAART (excluding dCTP analogs) inhibit human telomerase with different potencies.  AZT-TP and d4T-TP appeared to be the most potent inhibitors of telomerase relative to their ddNTP counterpart (Table 8).  CBV-TP was the least potent telomerase inhibitor relative to its ddNTP counterpart and TFV-DP had intermediate inhibitory potency.  In my primer extension assay, d4T-TP was similar in potency to ddTTP, and both d4T-TP and ddTTP were more potent than AZT-TP.  These findings are corroborated by data from kinetic experiments showing that HIV RT incorporates d4T-TP as efficiently as dTTP, and that AZT-TP is incorporated less efficiently than both d4T-TP and dTTP by HIV RT (Painter, Almond et al., 2004). Similar to d4T-TP, HIV RT does not have a high level of discrimination against TFV-DP (dATP analog) in vitro (Brown, Pack et al., 2011), nor does it have a high level of discrimination against CBV-TP (dGTP analog) (Vince, Hua et al., 1988).  In contrast, most other cellular   104 polymerases preferentially select for the natural substrates dATP and dGTP when compared to TFV-DP and CBV-TP, respectively.  Although I did not perform detailed kinetic analyses of telomerase in the presence of NRTIs, my data, in combination with data from kinetic studies of HIV RT mentioned above, support the notion that the NRTIs TFV-DP and CBV-TP may be preferentially incorporated into telomeric sequence by telomerase.  This is an important consideration when determining the off-target effects of these agents in human cells. Unlike other nuclear polymerases, neither HIV RT nor telomerase have built-in proofreading functions, which is perhaps a consequence of their common ancestral origin.  In the case of HIV RT, the lack of proofreading activities is advantageous as it allows the rapid evolution of diversity through sequence divergence, an important mechanism of drug resistance. In contrast, telomerase catalysis is confined to the copying of a 6 nt integral template sequence within the holoenzyme complex.  Following the synthesis of the 6 nt repeat to the end of the template, telomerase has to go through a series of conformational changes in preparation for translocation.  These conformational changes are followed by dissociation/sliding of the catalytic site to the newly synthesized 3’ DNA end and proper alignment and repositioning of the template-DNA product for the next round of catalysis. The absence of proofreading activity is perhaps a trade-off for the efficient progression of these concerted steps of repeat addition processivity.  Of course this trade-off is not without a price. Even though the telomeric sequence is non-coding, sequence-specific binding of the shelterin complex could be disrupted even with a single mismatched telomeric sequence (Prescott and Blackburn, 2000).  Uncapped or poorly capped telomeres are recognized as DNA damage signals, leading to the temporary halt of cell proliferation or cell death.  6.3.  Significance of NRTI-mediated telomere shortening One significant problem with my long-term treatment approach is a profound treatment toxicity issue with high concentrations of certain NRTIs.  In my cell culture system, the effects of   105 telomerase inhibition manifest as a gradual loss of telomere length, which is only evident after sufficient time lapse (10-20 PDL when telomerase is inhibited completely) with cell proliferation. With agents such ABC and TDF, there are no surviving cells past PDL 2 and 3, respectively.  In these cases, even if telomerase were inhibited completely, the lack of cell survival beyond the necessary time/PDL will not have been enough to see the full effect of telomere length attrition due to enzyme inhibition.  Additionally, under extreme selective pressure, transformed cells with unstable genomes can be forced to induce genetic changes much more readily. Pharmacokinetic changes brought on by genetic changes that increase tolerance to the toxicity of NRTIs could effectively reduce the intracellular concentration of the active form of these drugs.  Even though telomerase itself may still maintain its sensitivity to the NRTI, the changes in the effective intracellular concentration of the active drug could cause a particular NRTI to appear less potent than others with regards to its magnitude of effect on telomere-length maintenance.  Together, these two factors could complicate my long-term TRF analysis. In human colorectal cancer cells that have constitutive telomerase activity, all dTTP, dATP, and dGTP analogs used in HAART cause time- and dose-dependent telomere shortening.  Substantial telomere shortening was observed in HT29 cells treated with high concentrations of AZT, d4T, ABC, and TDF.  Although the concentrations at which complete telomerase inhibition observed with these NRTIs were substantially above that measured in clinical situations (plasma Cmax), it does provide plausible cause for conducting further investigations in humans.  It is possible that some NRTIs could accumulate in tissues rather than blood, at concentrations higher than that reported as the plasma Cmax.  Although pharmacokinetics of NRTIs are well characterized in humans, it is often difficult to determine the tissue reservoirs in which these drugs are absorbed and stored, since access to many tissues (e.g., brain) for measurement is not feasible or safe.  Thus, animal models of drug disposition have provided the best insight into tissue disposition.  In a mouse model of chronic retrovirus infection, AZT and AZT metabolites (mono-, di-, and tri-phosphate) were shown to accumulate   106 in the bone marrow, spleen, kidneys, and muscle to a greater extent than in plasma (Chow, Li et al., 1997).  Chronic infection with a retrovirus increased the amount of AZT and AZT metabolites in the spleen.  As well, the competitive nature of the NRTIs against their natural analogs argues that the intracellular concentration of dNTPs determines the potency of NRTIs.  Additionally, these reservoirs and the enzymatic activation capacities could vary within different tissue compartments, even within the same individual. Long-term inhibition of telomerase by NRTIs could have implications on tissue integrity in humans.  In DC, the haploinsufficient mode of telomerase deficiency in autosomal dominant inheritance cases argues that clinical symptoms could precipitate when telomerase activity is reduced by 50%.  In this scenario, deficiencies in highly proliferative tissues are normally observed within the first decade of life.  Given that the rates of telomere loss in my cell culture experiments for AZT, d4T, ABC, and TDF at high concentrations were consistent with complete telomerase inhibition, I would expect to, at least theoretically, find shorter telomeres in individuals undergoing long-term HAART.  This simple correlation, is complicated by the fact that telomerase deficiency at early embryonic development will have a much stronger effect on telomere homeostasis than telomerase inhibition in later life.  In this context, it is important to note that babies born to HIV positive mothers are exposed to ARVs in utero as preventive measures against vertical transmission of the disease, and provide a unique clinical situation where the effects of ARV drug exposure without concurrent HIV positive status could be measured. The current data on telomere length in adult HIV positive populations undergoing ARV therapies do not show a consistent trend toward telomere shortening (Vignoli, Stecca et al., 1998; Hotchkiss, Pehrson et al., 1999; Wolthers, Otto et al., 1999; Bestilny, Gill et al., 2000; Tucker, Jenkins et al., 2000).  The lack of a discernable trend could be due to a lack of telomere shortening, or to the inability of the existing methodologies to discern small changes in telomere length over time, given the inherently high variability in lymphocyte telomere length.  The   107 limitation in population size and/or suitable controls might also explain the lack of a consistent trend toward telomere shortening.  Another significant difference between genetic diseases of telomere shortening, such as DC, and the clinical effects of NRTI treatments is that the magnitude of the effects of genetic disorders on telomerase activity are consistent over the lifetime of the affected individual. Additionally, the genetic lesion(s) in DC and its effects are ubiquitous in the tissues of an affected individual.  In the case of NRTIs, even with life-long exposure, the magnitude of effect on telomerase activity would likely vary over time due to factors like fluctuations of intra- and extracellular drug concentrations, alterations of drug regimes (e.g., switching to another NRTI), and the potential of increased drug tolerance due to metabolic changes.  Indeed, functional alteration of lymphocytes and reduced antiviral activities of NRTIs in these cells has been shown with long-term treatment with some NRTIs (Fletcher, Acosta et al., 1998; Sommadossi, 1998).  Thus, even if NRTIs reach concentrations in human tissues high enough to inhibit telomerase, inhibition may not be maintained at a consistent level.  Furthermore, to exert maximal effects on proliferative tissues, NRTIs must be consistently present in cells where telomerase activity is required most, i.e., stem and progenitor cells. However, due to the sensitivity of stem and progenitor cell compartments to perturbations in telomere length maintenance, continual exposure to NRTIs and their potential effects on telomere length maintenance warrants further investigations.  While there is no consistent trend in telomere length maintenance defects in HIV positive adults receiving HAART, it remains possible that the perturbations in telomerase and telomere biology will be manifested in a different context.  For example, defects in telomere length maintenance in germ line cells may only be seen in the next generation after NRTI exposure, or even in many generations after a relative has been exposed to NRTIs.  To answer these questions, carefully planned and skillfully designed complementary laboratory studies and longitudinal epidemiological studies would be needed.   108 6.4.  Comparison of in vitro and cell culture results My in vitro primer extension assay predicted that the magnitude of inhibitory effects on telomerase activity should decrease in the following order: d4T>AZT>TFV>ABC (Table 8).  This rank did not agree with the results obtained in my cell culture experiments (Table 9). Continuous exposure to 100 µM ABC in HT29 cells appeared to result in telomere shortening at a rate beyond that of AZT and d4T, which were more potent in vitro relative to their respective ddNTP counterparts.  The rate of telomere shortening in HT29 cells was similar even at lower doses of ABC (50 µM) compared to that of d4T (80 µM).  A similar phenomenon was observed for HT29 cells continuously treated with TDF at 100 µM.  TDF at 100 µM caused a rate of TRF loss beyond that measured in cells treated with the highest concentration of AZT, while TFV-DP was substantially less potent against telomerase in vitro compared to AZT-TP.  There are likely a few key factors that explain these seemingly counterintuitive findings. Kinetic studies on the effects of NRTIs with mammalian DNA polymerases (pols) provide insight into my findings.  Inhibition of DNA pols other than telomerase may have contributed to an increased rate of telomere shortening in addition to that caused by telomerase inhibition. Indeed, DNA pols are variable in their sensitivities to different NRTIs.  DNA pol α, which is an important replicative DNA pol, incorporates CBV-TP more efficiently than ddGTP (Parker, White et al., 1991).  Given that I measured a rate of TRF loss in HT29 cells treated with 100 µM ABC beyond what is possible due to telomerase inhibition alone, I suspect that there were additional mechanisms of telomere shortening.  Inhibition of DNA pol α by CBV-TP in addition to telomerase may have contributed to additional telomere shortening.  In support of this hypothesis, DNA pol α incorporates ddTTP more efficiently relative to both AZT-TP and d4T-TP (Parker, White et al., 1991; Martin, Brown et al., 1994).  Thus, incorporation of CBV-TP by DNA pol α more frequently than other NRTIs during telomere replication or replication elsewhere in   109 the genome may also explain the additional telomere shortening and cytotoxicity observed with ABC treatment. A recent study on the kinetics of the X and Y family DNA pols indicates that some mammalian DNA pols are less discriminatory than others when comparing TFV-DP to dATP (Brown, Pack et al., 2011).  DNA pols β and λ were shown to have substantially lower discrimination for dATP relative to TFV-DP.  DNA pols β and λ are involved in base-excision repair and non-homologous end joining, respectively.  Similar to ABC, the inhibition of these DNA pols in addition to telomerase could explain the additional telomere shortening and toxicity observed with TDF.  Kinetic data showing that DNA pol β also has a similar affinity for AZT-TP compared to ddTTP suggests that a similar phenomenon could have played a role in telomere shortening measured with AZT treatment (White, Parker et al., 1989).  In addition, NRTIs have differential effects on mitochondrial integrity through inhibition of DNA pol γ (Bienstock and Copeland, 2004; Koczor and Lewis, 2010).  Mitochondrial toxicity and the development of resistance against a particular NRTI could also help explain the discrepancy between my in vitro and cell culture data.  In addition to the these kinetic studies, differences between my in vitro telomerase activity assay and the cell culture system used in my experiments may help to explain the discrepancies observed in my two sets of data.  For my in vitro telomerase assay, I provided definitive concentrations of dNTP analogs and their active (phosphorylated) competitors, so the resulting data were relatively clear and easy to interpret.  This is not the case in human cells. Successful incorporation of NRTIs into a nucleic acid chain within human cells depends on several factors.  NRTIs must reach the cytoplasm, which requires transport across the plasma membrane.  Transmembrane transport of NRTIs in itself is a complicated, multi-factorial process involving several different transmembrane proteins (Pastor-Anglada, Cano-Soldado et al., 2005).  NRTI uptake by cells requires their recognition by these transmembrane proteins, which depends on chemical structure and charge, and more importantly, on whether the necessary   110 transport proteins are expressed by a given cell type.  Different transporter proteins recognize different NRTIs, suggesting that some NRTIs may be taken up more readily than others.  This could also be a cell-type specific process. Once in the cytoplasm, NRTIs must be mono-, di-, and tri-phosphorylated (except for TFV, which requires only di- and tri-phosphorylation), with each step requiring the activity of a different cellular kinase.  Complicating these processes are findings that continuous treatment with some NRTIs can downregulate intracellular kinase activity (Magnani, Brandi et al., 1995; Antonelli, Turriziani et al., 1996; Turriziani, Scagnolari et al., 2002), which can lead to cellular resistance to these drugs in vitro.  Finally, once tri-phosphorylation has occurred, NRTIs can exert their inhibitory effects on nucleic acid polymerases.  However, drug efflux also plays an important role in the effectiveness of NRTIs (Turriziani, Scagnolari et al., 2003; Pastor-Anglada, Cano-Soldado et al., 2005).  The multidrug resistance proteins, including multidrug resistance proteins 4, 5, and 8, mediate drug efflux of several NRTIs. Finally, even though recombinant TERT immunopurification schemes were successful in identifying holoenzyme components (Fu and Collins, 2007), I cannot rule out the possibility that the composition of the holoenzyme complex could vary.  Conceivably, the loss of trans-acting factors during the immunopurification process could potentially affect the binding characteristics of the ARVs with telomerase and their inhibitory activities on enzyme catalysis.  6.5.  Future studies on telomerase inhibition and telomere maintenance with N/NRTIs My study provides the impetus for conducting additional investigations on the effects of N/NRTIs on telomerase activity and telomere maintenance both in vitro and in vivo.  Future in vitro studies on the impact of NRTIs on telomere maintenance in human cells should focus on primary human cells forced to express telomerase constitutively.  Relevant cell types, such as human stem cells would provide an ideal model for these experiments, but their maintenance in culture for extended periods of time may pose a significant challenge.  Combinational   111 chemotherapeutic treatments could be designed based on their current clinical usage combinations to observe the extent of their synergistic effects on telomere length maintenance. Additionally, experiments should be performed to better estimate the intracellular levels of NRTIs and their respective metabolites, as well as endogenous dNTPs in parallel.  These experiments would provide better insight into the concentrations of NRTIs relative to endogenous dNTPs required for telomerase inhibition, and would also allow comparison to NRTI potency against telomerase in vitro.  To generate a more comprehensive pattern of NRTI activity across a spectrum of tissue types, such as a panel of human cells comprising different tissues and cell types, could be used in a screen for telomerase inhibition.  Future clinical work should focus on larger-scale studies of telomere length measurement in PBMCs and other cell types.  Despite their common use in epidemiological studies of telomere effects, hematopoietic cell compartments are subjected to complex telomerase regulation and activation based on one’s immune status.  While PBMCs are arguably the most available tissue for epidemiology collection, the highly variable telomere length phenotype could mask otherwise significant observations of changes in TRF length. Indeed, other cell types such as buccal mucosal cells are currently being explored to replace PBMC for telomere length measurement in epidemiological studies.  Given the high variability in HAART treatment guidelines and the fact that most HAART agents are subjected to genetic variability in pharmacokinetic determinants, perhaps multi-centre studies (if protocols were standardized) will be necessary to fully appreciate the interactions between the genes, environment/disease state and drug therapy.  Clinical studies should categorize patients by NRTI as well as by estimating the duration of exposure to gain better insight into whether or not NRTIs inhibit telomerase and lead to telomere maintenance defects in appropriate cell types in vivo.   112 !"#$%&'(!!"#$%!&'!(")*+!#$,!,,()-+!.#+/,!&$!0&1/$23!#4#5$+1!1/6&7/8#+/! #2159513!5$!9518&: );&6,!2&$2/$18#15&$!&'!(")*!#.&9/!8/+0/2159/!,()-!8/<=58/,!'&8!>?@!1/6&7A /8#+/!5$B5.515&$: *+!,-& ..*!/-& 0123& /45%678)& ..*!/& /45%678)& ,C)A)-! D:C! ,,E)-! ?:FG! EH)A)-! C:C! ,,I)-! J:F! );KAL-! >:>! ,,))-! G:?! MNKA)-! 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Zhu Y, Tomlinson RL, Lukowiak AA, Terns RM & Terns MP (2004). Telomerase RNA accumulates in Cajal bodies in human cancer cells. Mol Biol Cell 15, 81-90.     132 APPENDIX A.1.  Methods A.1.1.  Estimating the Efficiency of Immunopurification of telomerase from WCL Competitive RT-PCR was performed by Naresh Thumati, who is a post-doctoral fellow in my laboratory.  I used competitive RT-PCR to determine the efficiency of my immunopurification (IP) scheme for human telomerase from WCL.  Total RNA was prepared from WCL and IP samples using Trizol (Invitrogen) and subsequent extraction with 1/2 volume of chloroform. RNA was precipitated overnight at -20°C in isopropanol with 50 µg LPA as a carrier.  RNA was recovered by centrifugation at 16,200 g for 15 minutes at 4°C and the dried RNA pellet resuspended in 500 µL DEPC H2O.  In separate reactions, 10 µL of each RNA sample together with the calculated number of copies of synthetic input competitor RNA molecules were denatured by incubation at 70°C for 10 min.  The denatured RNA pool was then added into a 20 µL RT reaction containing 1 mM DTT, 1X M-MuLV buffer (NEB), 1 mM dNTP, 1.25 µM reverse primer (5'-GCC TGG GAG GGG TGG TG-3'), 1.2 U RNAse inhibitor, 20 U of M-MuLV RTase in DEPC H2O.  RT reactions were incubated at room temperature for 10 min, followed by incubation at 42°C for 1 h and were subsequently heat inactivated by incubation at 95°C for 3 min.  For PCR, 10 µL of the RT reaction was added to the 50 µL reaction mix containing 1 X ThermoPol buffer (NEB), 0.5 µM forward primer (5'-Cy5-GCC TGG GAG GGG TGG TG-3'), 0.5 µM reverse primer (same primer as RT reaction), 200 µM dNTP and 2.5 U of Pfu polymerase. The PCR program was as follows: 30 cycles of 95°C for 30 sec (denaturing), 55°C for 30 sec (annealing) and 72°C (extension), followed by a single extension step of 72°C for 5 min. PCR amplicons were resolved through non-denaturing polyacrylamide gel electrophoresis (10%) and visualized by laser scanning at 650 nm using the Typhoon Trio (GE Healthcare Sciences).  Bands corresponding to the endogenous TER amplicons (122bp) and the competitor amplicon (142 bp, with a 20-nt non-specific DNA insertion internally into the endogenous TER amplicon) competitive PCR product signals were quantified using   133 ImageQuant (v. 5.2, GE Healthcare Life Sciences).  A ratio of endogenous amplicon:competitor amplicon was calculated based on the intensity of these bands within each lane.  The endogenous amplicon:competitor amplicon ratio was plotted against input competitor RNA copy number and linear regression was performed.  The linear equation was used to determine the copy number of competitor RNA required to generate an endogenous amplicon:competitor amplicon ratio of 1.  The TER copy numbers found in the WCL and IP samples for each independent transient transfection experiment were then used to determine the IP efficiency. An example calculation is shown in Supp. Fig. 1.  A.1.2.  Primer extension assay for NNRTI dose-response experiments The methodology for the primer extension assay is essentially the same as that described in the methods section, except activity was provided by telomerase immunopurified from 293 HEK cells stably transfected with hTER under the heterogenous U3 snoRNA promoter and FLAG tagged hTERT under the viral cytomegalovirus promoter instead of transiently transfected. Each 40 µL reaction contained 200 nM [α-32P]dGTP (3000 Ci/mmol 10 mCi/mL, 3.3 µM, Perkin Elmer) 1 mM dATP, 1 mM dTTP, and 10 µM dGTP, and the primer used was 5’- TTAGGGTTAGGGTTAGGG-3’.  Both NNRTIs were solubilized in DMSO and were added into the reactions at 5% final volume.  Product separation by denaturing polyacrylamide gel electrophoresis and the phosphorimaging of the product signals were identical to that described in previously in the methodology section.   134 Supplementary Figure 1.  Competitive PCR for determination of IP efficiency.  Top: Gel image of competitive PCR products.  Competitor and endogenous, at right, refer to competitor and endogenous RNA, respectively.  Numbers above each lane indicate the amount of competitor input in the corresponding reaction.  Arrows at bottom of gel indicate approximately where the competitor amplicon:endogenous amplicon signals is 1.  Bottom: a representative example of linear regression used to calculate the copy number for WCL 2 (top) and IP 2 (bottom).  The calculation done to determine the IP efficiency for IP 2 is shown at right.  Credit for the competitive PCR work goes to Naresh Thumati. !"#$%&'&"( %)*"+%)",- !"#$%&'&"( ')$,& ./ 01 2. 3 4 0/ 12 .3 4 12 .3 4 .2 .3 5 02 .3 5 ./ 01 2. 3 4 0/ 12 .3 4 12 .3 4 .2 .3 5 02 .3 5 62 .3 5 0/ 12 .3 4 12 .3 4 .2 .3 5 02 .3 5 ./ 01 2. 3 4 0/ 12 .3 4 12 .3 4 .2 .3 5 7/ 01 2. 3 7 !"#$% !"#$& '($% '($&   135  !"#$%&'()*+,-. / 0 *1 - 2 3 ! "# # $# ! # ! ! # ! ! ! # ! $! ! ! 4'$%&#5%('*+,-. / 0 *1 - 2 3 ! "# # $# ! # ! ! # ! ! ! # ! $! ! ! Supplementary Figure 2.  NNRTI dose-response experiments.  I tested both EFV (left) and NVP (right) in 10-fold dose- response experiments to determine whether either NNRTI inhibited telomerase.  Due to the high background on these gel images, I was not able to accurately quantify these data.   Neither NNRTI appears to inhibit telomerase by visual inspections, even when tested at 10 mM (last lane on each gel).


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