Medicine, Faculty of
Medicine, Department of
DSpace
UBCV
Zhang, Wendy W.
Master of Science - MSc
University of British Columbia
Antiretroviral drugs are basis of the treatment of human immunodeficiency virus (HIV) infections. Combined antiretroviral therapy (ART) uses a combination of three antiretroviral drugs to inhibit viral replication and to prevent disease progression and has become a global standard for HIV treatment. Integrase strand transfer inhibitors (INSTIs) are the most recent class of antiretroviral drugs to reach the market. INSTIs function by inhibiting the 3’-processing ability of HIV integrase and preventing the incorporation of the HIV genome into the host’s deoxyribonucleic acid (DNA). The use of raltegravir (RAL), elvitegravir (EVG) and dolutegravir (DTG) in clinical settings has increased since their approval, however there is a risk that the development of drug resistance would impact the treatment of the individual as well as the general population in the event of transmitted drug resistance. New integrase inhibitors, bictegravir (BIC) and cabotegravir (CAB), has been recently approve and has reached late phases of development, respectively. Due to the novelty of INSTIs, less is known about INSTI resistance than other drug classes that pre-date INSTIs. The main objectives discussed in this thesis are 1) the direct comparison of the effect of DTG, BIC and CAB on viruses harbouring known major INSTI mutations and 2) the development of a panel of patient-derived recombinant viruses with INSTI resistance with matched genotypes and phenotypes and the assessment of resistance to new INSTIs using recombinant viruses from the database. The resistance profiles of a set of patient-derived recombinant viruses harbouring the major mutations G140S/Q148H on its own and in combination with additional amino acid substitutions was determined for DTG, BIC and CAB. As a follow-up, a larger panel of recombinant viruses with unique permutations of amino acid substitutions in the integrase gene were generated using a limiting dilution PCR procedure. The resulting panel was assessed for INSTI resistance using a phenotypic assay in order to populate a database of matched genotype-phenotype data. High levels of resistance to the new INSTIs, BIC and CAB, were detected and BIC and CAB resistance was found to be highly correlated with DTG resistance, highlighting the similarity between the new and current INSTIs.
HIV-1 INTEGRASE STRAND TRANSFER INHIBITOR RESISTANCE TO DOLUTEGRAVIR, BICTEGRAVIR AND CABOTEGRAVIR by Wendy W. Zhang BSc. The University of British Columbia, 2014 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE In THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Experimental Medicine) THE UNIVERISTY OF BRITISH COLUMBIA (Vancouver) December 2022 ã Wendy W. Zhang, 2022 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis entitled: HIV-1 integrase strand transfer inhibitor resistance to dolutegravir, bictegravir and cabotegravir submitted by Wendy Wenyu Zhang in partial fulfillment of the requirements for the degree of Master of Science in Experimental Medicine Examining Committee: Dr. P. Richard Harrigan, Professor, Medicine, UBC Supervisor Dr. Jeffery Joy, Assistant Professor, Medicine, UBC Supervisory Committee Member Dr. Helene Côté, Professor, Pathology and Laboratory Medicine, UBC Supervisory Committee Member Muhammad Morshed, Clinical Professor, Pathology, UBC Additional Examiner iii Abstract Antiretroviral drugs are basis of the treatment of human immunodeficiency virus (HIV) infections. Combined antiretroviral therapy (ART) uses a combination of three antiretroviral drugs to inhibit viral replication and to prevent disease progression and has become a global standard for HIV treatment. Integrase strand transfer inhibitors (INSTIs) are the most recent class of antiretroviral drugs to reach the market. INSTIs function by inhibiting the 3’-processing ability of HIV integrase and preventing the incorporation of the HIV genome into the host’s deoxyribonucleic acid (DNA). The use of raltegravir (RAL), elvitegravir (EVG) and dolutegravir (DTG) in clinical settings has increased since their approval, however there is a risk that the development of drug resistance would impact the treatment of the individual as well as the general population in the event of transmitted drug resistance. New integrase inhibitors, bictegravir (BIC) and cabotegravir (CAB), has been recently approve and has reached late phases of development, respectively. Due to the novelty of INSTIs, less is known about INSTI resistance than other drug classes that pre-date INSTIs. The main objectives discussed in this thesis are 1) the direct comparison of the effect of DTG, BIC and CAB on viruses harbouring known major INSTI mutations and 2) the development of a panel of patient-derived recombinant viruses with INSTI resistance with matched genotypes and phenotypes and the assessment of resistance to new INSTIs using recombinant viruses from the database. The resistance profiles of a set of patient-derived recombinant viruses harbouring the major mutations G140S/Q148H on its own and in combination with additional amino acid iv substitutions was determined for DTG, BIC and CAB. As a follow-up, a larger panel of recombinant viruses with unique permutations of amino acid substitutions in the integrase gene were generated using a limiting dilution PCR procedure. The resulting panel was assessed for INSTI resistance using a phenotypic assay in order to populate a database of matched genotype-phenotype data. High levels of resistance to the new INSTIs, BIC and CAB, were detected and BIC and CAB resistance was found to be highly correlated with DTG resistance, highlighting the similarity between the new and current INSTIs. v Lay Summary A combination of antiretroviral drugs which act upon different parts of the human immunodeficiency virus (HIV) lifecycle is the basis of HIV treatment. Integrase strand-transfer inhibitors (INSTIs) are the newest class of antiretroviral drugs developed and are increasingly used in clinical settings. The newest INSTIs, dolutegravir, bictegravir and cabotegravir are thought to be effective and less likely for HIV to become resistant to, than their predecessors, raltegravir and elivtegravir. Though promising, the efficacy and longevity of these newer INSTIs can still be affected by the development of drug resistance. Knowledge about the mutations which would confer the virus resistance to INSTIs is still relatively limited. The main objectives are 1) the comparison of the effect of DTG, BIC and CAB on viruses harbouring known major INSTI mutations and 2) developing a panel of patient-derived recombinant viruses with INSTI resistance with matched genotypes and phenotypes and assessing resistance to new INSTIs using recombinant viruses. vi Preface The main body of this thesis contains one peer-reviewed article (Chapter Two) of which I, Wendy W. Zhang, was primary author and one article that has been submitted for publication (Chapter 3), which I have revised for this thesis. The work done in these studies was conducted at the British Columbia Centre for Excellence in HIV/AIDS (BC-CfE), a laboratory affiliated with the University of British Columbia in Vancouver BC, Canada. Chapter Two was previously published in The Journal of Infectious Diseases by Oxford University Press and reprinted here with permission from Oxford University Press, license number 4630891168946. Zhang WW, Cheung PK, Oliveira N, Robbins MA, Harrigan PR, Shahid A. Accumulation of Multiple Mutations In Vivo Confers Cross-Resistance to New and Existing Integrase Inhibitors. J Infect Dis. 2018 Oct 20;218(11):1773-1776. I was the primary author of this publication, responsible for conducting experimental procedure, data analysis and the writing of the manuscript. Peter K Cheung and Aniqa Shahid were responsible for conducting experimental procedures. Natalia Oliveira and Aniqa Shahid and conducted data analysis. P Richard Harrigan, Peter K Cheung and Aniqa Shahid provided feedback and editing. P Richard Harrigan and Marjorie A Robbins conceived the original study design. The University of British Columbia Providence Health Care Research Ethics Board granted ethical approval for the study presented in Chapter Two (H14-03423). vii A version of Chapter Three has been submitted for publication. I contributed to the design of the experimental procedures, conducting experiments and the analysis of the data, I made the figures and wrote for the version included in this thesis. Aniqa Shahid was the primary author of the submitted publication. The study was conceived by P. Richard Harrigan and the experimental procedures were designed and conducted by Marjorie A. Robbins, Peter K. Cheung, Aniqa Shahid, Wendy W. Zhang and Manraj S. Sidhu. Data analysis was done by Aniqa Shahid, Wendy W. Zhang, Vincent Montoya, Natalia Oliveira, and Conan K. Woods. The manuscript was written by Aniqa Shahid. Advising and editing was provided by Chanson J. Brumme and P. Richard Harrigan. Ethical approval was provided by the University of British Columbia Providence Health Care Research Ethics Board for the study presented in Chapter Three (H14-03423). viii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ................................................................................................................................ v Preface ........................................................................................................................................... vi List of Tables ................................................................................................................................ xi List of Figures .............................................................................................................................. xii List of Abbreviations ................................................................................................................. xiii Acknowledgements ..................................................................................................................... xv Dedication ................................................................................................................................... xvi Chapter 1: Introduction ............................................................................................................... 1 1.1 An Overview of HIV/AIDS ....................................................................................................... 1 1.2 Discovery of HIV ....................................................................................................................... 2 1.3 HIV genetic diversity ................................................................................................................. 2 1.4 Antiretroviral drugs .................................................................................................................. 3 1.4.1 Nucleoside/nucleotide and Non-nucleoside Reverse Transcriptase Inhibitors ....................... 5 1.4.2 Protease Inhibitors ................................................................................................................... 5 1.4.3 Fusion Inhibitors and Entry Inhibitors .................................................................................... 6 1.4.4 Integrase Strand Transfer Inhibitors ........................................................................................ 6 1.5 INSTI resistance ........................................................................................................................ 8 1.6 Assessing HIV drug resistance ............................................................................................... 10 1.6.1 Drug resistance testing .......................................................................................................... 10 1.6.2 Genotypic assays ................................................................................................................... 11 1.6.3 Phenotypic assays .................................................................................................................. 12 1.6.4 Genotype-Phenotype Databases ............................................................................................ 13 1.7 Thesis Objectives and Organization ...................................................................................... 14 1.7.1 Thesis Objectives and Aims .................................................................................................. 14 1.7.2 Thesis organization ............................................................................................................... 15 ix Chapter 2: Accumulation of Multiple Mutations In Vivo Confers Cross-Resistance to New and Existing Integrase Inhibitors .............................................................................................. 17 2.1 Background .............................................................................................................................. 17 2.2 Methods .................................................................................................................................... 18 2.2.1 Cells, viruses, and integrase inhibitors .................................................................................. 18 2.2.2 Recombinant virus construction ............................................................................................ 18 2.2.3 Phenotypic susceptibility assay and data analysis ................................................................. 20 2.2.4 Data analysis ......................................................................................................................... 20 2.3 Results ....................................................................................................................................... 20 2.4 Discussion and Conclusion ...................................................................................................... 23 Chapter 3: Systematic determination of in vitro phenotypic resistance to HIV-1 Integrase Strand Transfer Inhibitors from clinical samples ................................................................... 26 3.1 Background .............................................................................................................................. 26 3.2 Methods .................................................................................................................................... 27 3.2.1 Cells, virus vectors and drugs ............................................................................................... 27 3.2.2 Selection of amino acid positions .......................................................................................... 27 3.2.3 Samples ................................................................................................................................. 29 3.2.4 Oligo clonal PCR .................................................................................................................. 30 3.2.5 Recombinant virus construction ............................................................................................ 31 3.2.6 Phenotype assay .................................................................................................................... 31 3.2.7 Data analysis ......................................................................................................................... 31 3.3 Results ....................................................................................................................................... 32 3.3.1 Identification of positions of interest in the integrase gene .................................................. 32 3.3.2 Oligo-genome amplification and recombinant virus generation ........................................... 32 3.3.3 Subtype and amino acid diversity among recombinant viruses ............................................ 33 3.3.4 Phenotype Assay ................................................................................................................... 37 3.3.5 Extensive cross-resistance between DTG, BIC and CAB ..................................................... 42 3.4 Discussion and Conclusion ...................................................................................................... 45 Chapter 4: General Discussion and Conclusion ....................................................................... 48 4.1 Thesis Summary ...................................................................................................................... 48 x 4.2 Limitations ............................................................................................................................... 49 4.3 Overall impact and future directions ..................................................................................... 50 Bibliography ................................................................................................................................ 52 Appendices ................................................................................................................................... 66 Appendix I. Amino acid sequence of 12 recombinant viruses at 27 amino acid positions of interest. .................................................................................................................................................. 66 Appendix II. Permutations of 27 amino acids in integrase observed in clinical samples. ............. 68 Appendix III. Amino acid sequences at 27 positions of interest of the panel of 162 recombinant viruses. .................................................................................................................................................. 77 Appendix IV. Phenotypic susceptibility to INSTIs of the panel of recombinant viruses. .............. 83 Appendix V. Distribution of phenotypic susceptibilities to raltegravir and elivitegravir. ............ 87 Appendix VI. The cumulative percent of variation of clinical samples without mixtures covered by the number of virus variants tested. .............................................................................................. 88 xi List of Tables Table 2.1 Median Fold-Change Resistance of Viruses to five INSTIs. ........................................ 22 Table 3.1 Log prevalence ratios of integrase amino acid substitutions. ....................................... 28 Table 3.2 HIV subtypes of oligo-clonal amplicons and recombinant viruses. ............................. 34 xii List of Figures Figure 2.1 Correlations between dolutegravir, bictegravir and cabotegravir resistance. .............. 23 Figure 3.1The number of recombinant viruses with amino acid substitutions. ............................ 35 Figure 3.2 Amino acid variation. .................................................................................................. 36 Figure 3.3 Distribution of log fold-changes. ................................................................................. 38 Figure 3.4 Average fold-change in resistance grouped by the number of substitutions. .............. 39 Figure 3.5 Effect of single amino acid substitutions ..................................................................... 41 Figure 3.6 Average log fold-change in resistance grouped by amino acid substitution. .............. 42 Figure 3.7 Correlations between dolutegravir, bictegravir, cabotegravir, raltegravir and elvitegravir resistance. .................................................................................................................. 44 xiii List of Abbreviations AIDS – acquired immune deficiency syndrome ART – antiretroviral therapy BCCfE – British Columbia Centre for Excellence in HIV/AIDS BIC – bictegravir CRFs - circulating recombinant forms CAB – cabotegravir CCR5 – C-C Motif Receptor 5 CD4 – Cluster of Differentiation 4 CDC - Center for Disease Control CXCR4 – C-X-C-Motif Receptor 4 DNA – deoxyribonucleic acid DTG – dolutegravir EVG – elvitegravir EC50 – 50% effective concentration FC – fold-change HAART – highly active antiretroviral treatment HIV – Human Immunodeficiency Virus HTLV-III – human T-lymphotropic virus type III INSTI – integrase strand transfer inhibitor LAV - lymphadenopathy associated virus LTR – long terminal repeat NGS – next-generation sequencing nNRTI – non-nucleoside reverse transcriptase inhibitor xiv NRTI - nucleotide reverse transcriptase inhibitors PCR – polymerase chain reaction PI – protease inhibitor RAL – raltegravir RNA – ribonucleic acid RT-PCR – reverse-transcription polymerase chain reaction USA – United States of America WHO – World Health Organization xv Acknowledgements I would like to thank my supervisor Richard Harrigan, for whom I am incredibly grateful. I feel very fortunate to have had you as a supervisor because of the endless support, encouragement and patience you have given me. You’ve taught me many important lessons on science and on life that I will not forget. I would like to thank the other members of my graduate supervisory committee, Jeffrey B. Joy and Hélène Côté for your valuable support and guidance. I would like to acknowledge the co-authors and collaborators that have made these studies possible. In particular I would like to thank Marjorie A. Robbins, Aniqa Shahid and Peter K. Cheung for their tireless work and for their willingness to help me along this journey. I am grateful to the laboratory staff at the BC Centre for Excellence in HIV/AIDS for supporting me and for teaching me. Thank you to all the participants who have provided samples for the studies; without you, none of our work would be possible. Finally, I would like to thank my family, my Mom and my Dad, for their years of sacrifice and support. xvi Dedication To my family and to my friends who have stuck with me through the thick and the thin. 1 Chapter 1: Introduction 1.1 An Overview of HIV/AIDS The human immunodeficiency virus (HIV) is the causative agent of acquired immune-deficiency syndrome (AIDS) responsible for 35 million deaths since the start of the epidemic.1 In 2017, approximately 37 million people worldwide were estimated to be living with HIV/AIDS with the majority of infected individuals living in Sub-Saharan Africa. 2 With the implementation of various strategies around the world to detect infection in the earlier stages, to combat the spread of the virus and to treat infected persons, there have been marked reductions in the number of new infections and AIDS-related deaths worldwide. HIV is a retrovirus which infects CD4 positive immune cells such as T helper cells, macrophages and dendritic cells. The primary modes of transmission are through the exchange of bodily fluids (ex. blood, semen) or contact between mucosal membranes (ex. anal or vaginal intercourse). Once in the body, HIV invades CD4 positive immune cells by binding to the CD4 receptor and either co-receptor CCR5 or CXCR4 on the cell membrane surface. 3 Upon entry into the cell, HIV evades the host’s immune system, inserts itself into the host genome and can remain latent for long periods of times. The onset of infection is characterized by a rapid immune response followed by an overall decrease in the amount of CD4 positive cells in the body once the infection establishes. The viral load increases dramatically and the further decline of CD4 cell counts contribute to the susceptibility of the infected individual to opportunistic infections, which if untreated, lead to death. 2 1.2 Discovery of HIV In 1981, doctors and scientists in the United States of America (USA) became aware of an unusual pattern of illness in gay men who had developed rare and severe diseases such as Kaposi’s sarcomas and Pneumocystis carinii pneumonia despite having been previously healthy individuals. 4, 5 By the following year, more cases were reported in the USA, Haiti, Spain, France and various countries around the world. The United States Center for Disease Control (CDC) termed the disease “acquired immune deficiency syndrome” due to the disease’s apparent effect on the immune system and its transmissible nature.6 By 1984, the retrovirus responsible for causing AIDS, then called the lymphadenopathy associated virus (LAV) or human T-lymphotropic virus type III (HTLV-III), had been isolated from a number of patients with AIDS or exhibiting AIDS-like symptoms.7, 8 It was agreed upon by the International Committee on Taxonomy of Viruses in 1986 that LAV/HTLV-III should be renamed the human immunodeficiency virus.9 1.3 HIV genetic diversity The Human immunodeficiency virus is a phylogenetically diverse group of viruses. HIV can be divided into two broad types, HIV-1 and HIV-2. The majority of the HIV infections worldwide are attributed to HIV-1 though HIV-2 infections represent 1-2 million of all the infections globally.10 Further distinctions are made within the types: HIV-1 is divided into groups M and N and HIV-2, into groups O, and P. Group M accounts for most of the infections and is further divided into 9 major subtypes A, B, C, D, F, G, H, J, K and various circulating recombinant forms (CRFs). 11, 12 These classifications are determined by phylogenetic analysis of the nucleotide sequences of individual HIV genes or entire HIV genomes.13 Sequence variation 3 of HIV can be as great as 50% between HIV-1 and HIV-2 and can vary nearly 15% between the subtypes, demonstrating the great diversity for which HIV testing and treatment must account.14 The high level of diversity of HIV is the combined result of a high mutation rate due to an error-prone reverse transcriptase and various selection pressures applied by the immune system, various host factors, antiretroviral therapies and the long period of infection. Within an infected individual, the overall effect of the various factors that influence HIV evolution is an increasingly heterogenous population of circulating virus as the infection progresses.15 Within a single infected individual, variants of the virus in the plasma can differ from each other by up to 2%.15 This diversity can be clinically relevant. The rapidity of evolution of the HIV population within an individual may mean a rapid disease progression while the heterogeneity of the population could mean that minority variants bearing drug-resistance mutations could have negative implications on treatment outcome. 16, 17 1.4 Antiretroviral drugs The first antiretroviral drug approved for the treatment of HIV was approved in 1987 by the FDA. 18 While the drug was able to improve the patients’ conditions and CD4 counts for a short time, HIV drug resistance developed with prolonged use rendering single drugs or entire drug classes ineffective.19, 20 The subsequent implementation of dual and then triple drug therapy was able to produce sustained positive patient outcomes provided that treatment interruptions did not occur.21 These new regimens were able to reduce the circulating virus count, boost CD4 counts, and delay the onset of AIDS. 22, 23 Newer drugs belonging to different drug classes have 4 since been developed but highly active antiretroviral treatment (HAART) that was implemented in 1995 still remains the basis of modern HIV treatment. Antiretroviral drugs work by inhibiting processes in the HIV replication cycle that are crucial to the maturation of the virus and its ability to produce infectious virions. Reverse transcriptase inhibitors, protease inhibitors, fusion inhibitors, entry inhibitors and integrase inhibitors each interrupt different enzymes and processes in the HIV life cycle. By combining different drugs which act upon different stages of the HIV lifecycle, the replication and spread of HIV is effectively halted. Modern HIV treatment has led to the decline of HIV infections and AIDS-related deaths over the years. Current HIV drug regimens are capable of decreasing the amount of circulating virus in the blood to virtually undetectable levels thereby eliminating the risk of HIV transmission between sexual partners and between mother and child. 24 As a result of HAART, HIV infected individuals can expect to live a normal life span with the proper medical attention. However, HIV drugs cannot affect viruses which have already integrated with the body’s cells and entered a latency period where no active replication occurs. 25 Currently, HAART is able to achieve sustained suppression of viral replication but cannot fully eliminate HIV from the body. 5 1.4.1 Nucleoside/nucleotide and Non-nucleoside Reverse Transcriptase Inhibitors Nucleoside and nucleotide reverse transcriptase inhibitors (NRTIs) and non-nucleoside reverse transcriptase inhibitors (nNRTIs) were among the first antiretroviral drugs discovered. 26 These drugs act upon the reverse transcriptase enzyme which is responsible for the reverse transcription of viral RNA into DNA prior to integration into the host genome. Following fusion of the viral envelope to the cell membrane, reverse transcriptase catalyzes the synthesis of viral DNA. Nucleoside and nucleotide reverse transcriptase inhibitors mimic the structure of the nucleoside or nucleotide substrates used by reverse transcriptase enzyme and prevent reverse transcriptase activity and further DNA synthesis once incorporated into the reverse transcribed DNA. 27 nNRTIs inhibit reverse transcriptase activity by interfering with non-catalytic allosteric sites.27 Three-drug combinations of NRTIs and nNRTI are recommended as first-line antiretroviral therapy (ART) in resource limited settings. 1.4.2 Protease Inhibitors Following transcription and translation of the HIV genome, the viral protease is required to cleave the resulting precursor polyprotein into active proteins. Protease inhibitors (PIs) inhibit this crucial step in HIV maturation by binding to the active sites of the protease enzyme. 28 Protease inhibitors were routinely incorporated into combined ART since the development of the first PI in 1995. 29 Wide-spread and common PI resistance has remained an issue in the use and development of PIs. 29 Protease inhibitors can cause a range of mild to severe adverse drug reactions and have a variety of interactions with other drugs. 30 6 1.4.3 Fusion Inhibitors and Entry Inhibitors Fusion inhibitors and entry inhibitors are other alternatives to the main classes of antiretrovirals for the treatment of HIV. Fusion inhibitors are peptide analogues of a region of the gp-41 surface protein which is required for the margining of the viral envelope and the host cell membrane. Fusion inhibitors work by binding to the viral protein gp-41 to inhibit fusion of the host and viral membranes.31 Entry inhibitors such as the CCR5 antagonist, maraviroc, target the CCR5 host cell receptor which mediates HIV entry into the cell. By binding to CCR5, these drugs allosterically inhibit the interaction between the viral gp120 protein and the host receptor. 32 However, maraviroc can only be used in patients infected with HIV which use the CCR5 receptor for cell entry. 1.4.4 Integrase Strand Transfer Inhibitors Integrase Strand Transfer inhibitors (INSTIs) are the most recently introduced class of antiretroviral drugs to be approved for clinical use. INSTIs are currently recommended as possible alternatives to first and second-line antiretroviral drugs for HIV treatment. 33 Expanding INSTI research has led to broadened approved and recommended uses of INSTIs to include use in children, pregnant women and as the recommended first-line ART. 34 Integrase Strand Transfer Inhibitors act during the integration of reverse-transcribed viral DNA it into the host genome. During the integration of HIV DNA into the host genome, the viral integrase protein catalyzes two main reactions: 3’-processing and strand transfer. In the host cell cytoplasm, the integrase protein first binds to the ends of the long terminal repeat (LTR) sequences in the viral DNA and cleaves the two 3’ ends. 35 The strand transfer of the 3’- 7 processed DNA into the host genome requires the viral integrase to form a tetramer and to bind to both the target host DNA and the viral DNA. The 3’ hydroxyl-groups of the viral DNA attack the host DNA backbone in a process that requires Mg2+ ions to bind to the active site of the integrase protein. 36 The strand transfer step is the target of current INSTIs. The INSTIs bind to the viral integrase to prevent binding of Mg2+ ions, processed viral DNA and the formation of the active tetramer, thus preventing strand transfer from occurring.37 The first generation INSTIs raltegravir (RAL) and elvitegravir (EVG) were first approved in 2007 and in 2012, respectively. 38, 39 Raltegravir and EVG (pharmacologically boosted with cobicistat) were both found to be highly effective and generally well tolerated in patients. In clinical trials, both RAL and EVG were found to as efficacious as the standard-of-care of the time, efavirenz/emtricitabine/tenofovir disoproxil fumarate, and were associated with fewer adverse events during treatment. 40-43 Despite having good efficacy and tolerability, resistance to RAL and EVG these drugs come with the caveat that emergent drug resistance mutations have been observed in treated clinical populations.44, 45 Dolutegravir (DTG), approved in 2014, bictegravir (BIC), approved in 2018 and cabotegravir (CAB), in late phase clinical trials, are described as “second generation” INSTIs. Like their precursors, RAL and EVG, these drugs are well tolerated and efficacious in both treatment-naïve and treatment experienced patients.46-48 Importantly, both DTG and BIC are able to suppress the growth of viruses carrying some resistance mutations which would render RAL and EVG ineffective. 46-48 Furthermore, patients on, as well as HIV grown in vitro in, DTG and BIC are less likely to develop resistance mutations, suggesting a higher barrier to resistance.49 8 However, if pre-existing RAL and EVG mutations are compounded with additional resistance mutations, DTG and BIC can become less effective. Dolutegravir, in particular, is currently part of the recommendations for first-line ART by some countries. Cabotegravir is being investigated for its potential to be used as a long-acting injectable form of ART.50 Though DTG, BIC and CAB are promising options for HIV treatment with INSTIs, the risk of developing drug resistance remain. 1.5 INSTI resistance As with all antiretroviral drugs, there is a risk of patient viruses developing mutations which reduce the susceptibility of the virus to one or more of the INSTIs. Transcriptional errors in the HIV replication process can accumulate due to drug selection pressures when the virus is not being optimally inhibited. In the case of suboptimal drug adherence, concentrations of INSTIs in the body may not be high enough to fully inhibit HIV replication and ultimately resulting in acquired drug resistance. A meta-analysis of clinical trials for RAL, EVG and DTG has found that the rate of developing resistance mutations to INSTIs in clinical populations is lower than the rate of developing mutations to other classes of drugs such as PIs and NRTIs.51 Resistance to RAL is the most common, followed by EVG and DTG. Although amino acid substitutions that confer INSTI resistance are mainly located within the integrase gene, a recent report suggests that sites outside of integrase, in the nef region, may have an impact on RAL, EVG and DTG. 52 Amino acid substitutions at positions Q148, N155 and Y143 in integrase are the most commonly observed mutations among patients failing RAL and EVG.53, 54 The three major 9 substitutions Q148, N155 and Y143 are represent different pathways of resistance though more than one pathway may exist within a patient.49 Various additional amino acid substitutions such as T66, L74, E92, E138, G140 and G163, can also play a role in the accumulation of further amino acid substitutions and decreasing susceptibility of the virus to INSTIs.55, 56 Furthermore, the high levels of cross-resistance between RAL and EVG make switching between the two drugs impossible once resistance to just one of them develops. 56 Dolutegravir and Bictegravir have high barriers to resistance meaning that it takes much more time for resistance to develop, if at all. The acquisition of resistance mutations to DTG in patients on DTG-based regimens is uncommon.47, 48 Major substitutions at Q148, N155 and Y143 alone have little effect on DTG susceptibility.57 Only when combined with other additional substitutions, do these RAL and EVG-associated substitutions show a considerable effect on DTG susceptibility.57 In clinical populations, the substitution R263K has been found, though rarely, in patients failing DTG-containing regimens. On its own, R263K can decrease DTG susceptibility by 2-fold.47, 48 Due to the novelty of BIC, less is known about BIC resistance, however, BIC and DTG appear to share similar resistance profiles due to similar chemical structures. 58 10 1.6 Assessing HIV drug resistance 1.6.1 Drug resistance testing Drug resistance testing is part of a global strategy to monitor global HIV drug resistance trends and to inform patient care and national HIV treatment strategies. 59, 60 In recent years, the World Health Organization has focused the recommendations on the monitoring of drug resistance among populations initiating ART as part of a coordinated global approach to addressing HIV drug resistance, particularly in resource-limited settings. 61 Continued drug resistance testing can aid the continued effectiveness of ART on an individual and on a population level. Two methods of drug resistance testing exist: genotypic resistance testing and phenotypic resistance testing. Genotypic resistance testing detects known resistance mutations in the viral genome of the virus population within an infected individual. Phenotypic resistance testing asses the ability of the virus harboured by an individual to grow, in vitro, in the presence of varying concentrations of drugs. For the purposes of patient care, genotypic resistance testing is generally recommended for patients starting ART and patients experiencing virologic failure or sustained detectable viral loads. 59, 60 Baseline drug resistance testing for PIs, nNRTIs and NRTIs resistance can detect pre-existing or transmitted drug resistance which is associated with higher odds of treatment failure though baseline INSTI resistance testing may not have an impact on treatment outcome and is not currently part of drug resistance testing guidelines. 59-64 Studies looking at the effect of implementing drug resistance testing as per guidelines suggestions have found more favourable 11 virologic outcomes in patients who received drug resistance testing at treatment failure. 65, 66 Further phenotypic resistance testing may be warranted and beneficial if it is suspected that a patient’s virus carries complex mutation patterns. 59, 67 1.6.2 Genotypic assays Genotypic resistance testing utilizes automated DNA sequencing technology to obtain the nucleic acid sections of the HIV genome isolated from patients. This method is time-efficient and can be completed within days, making it possible to assess drug resistance in a large number of patients in a clinically relevant time frame. In genotypic resistance testing, typically plasma is collected from the patient and put through the process of RNA extraction. Resulting RNA is amplified by reverse-transcription polymerase chain reaction (RT-PCR) in a one or two-step nested reaction and the final PCR product is sequenced via Sanger sequencing or next-generation sequencing (NGS). A consensus sequence of all the HIV variants harboured by the patient is created from the sequencing reads. The sequences are translated into protein sequences and compared to known wildtype HIV standards. Known drug resistance mutations are flagged and a cumulative score of drug resistance is assigned to the sample ranging from susceptible to highly resistant. Clinicians use this information to decide whether or not a patient requires regime switches particularly in context of apparent treatment failure. The identification and interpretation of drug resistance mutations relies upon the algorithm for interpretation. Several interpretation algorithms exist, including the Stanford University HIV Drug Resistance Database, which compile data from clinical and in vitro studies 12 and use them to provide resistance predictions that range from susceptible to a complete loss of susceptibility. 68-70 Drug resistance predictions are not without uncertainty as results can vary between different algorithms; clinicians have been found to benefit from expert opinions in addition to resistance predictions based on genotype. 71 1.6.3 Phenotypic assays Phenotypic assays that measure drug resistance are in vitro assays in which a virus, either isolated from an infected patient or a lab-grown strain, is grown in the presence of increasing concentrations of antiretroviral drugs in order to determine its susceptibility to the drug. In order to investigate the effect of specific amino acid substitutions within a particular HIV gene on drug susceptibility, viruses containing the substitutions of interest generated in one of three ways: site-directed mutagenesis, in vitro drug selection, or recombination which incorporates the gene of interest from a patient-derived virus into a wild-type HIV backbone. 72-74 The viruses are used to infect cell lines susceptible to HIV infection and increasing doses of the antiretroviral drug are added in order to inhibit viral growth. The level of resistance is measured by the amount of growth and virus spread in the cell line in the presence of increasing drug doses and is reported as the 50% effective concentration (EC50), the concentration of drug effective at inhibiting 50% of the viral growth and spread. A relative measure of the level of resistance is determined by comparing the growth of the virus being tested with that of a wildtype lab strain known to be susceptible to the drug in question. This measure of susceptibility, known as fold-change (FC), is the ratio of the concentration of drug required to inhibit 50% of the patient-derived virus to the concentration of drug required to inhibit 50% of the wild-type control virus. Phenotypic assays 13 are used to investigate the effect of observed amino acid substitutions on drug susceptibility regardless of whether or not the substitution is a known resistance mutation. The interpretation of the phenotypic assay data depends upon having a reference point for what range of FCs qualify as “resistant” and “susceptible”. Many different phenotypic assay protocols exist utilizing a variety of cell lines and reporter systems and the variations in the assay may affect the magnitude of the reported EC50s and FCs. Technical cut-offs describe the limit which a particular phenotypic assay can reliably reproduce results but do not provide information on the clinical relevance of the resistance results. A ‘biological cut-off’ may be determined by observing the variation in FC of treatment-naive patient viruses and defining the cut-off as two standard deviations from the mean. 75 This type of cut-off can be used to determine if a virus is outside the range of normal susceptibility. Clinical cut-offs are the most appropriate cut-off to use when interpreting phenotypic assay data for clinical consideration. Clinical cut-offs are determined using large sets of phenotypic assay data associated with the response to treatment and are therefore less common. Commercially available phenotypic assays tend to have varied clinical cut-offs. 76 1.6.4 Genotype-Phenotype Databases Genotypic resistance assays can be performed quickly but rely upon prior knowledge of resistance-associated mutations while phenotypic assays can detect resistance in patient-derived viruses with complex mutation patterns but at the expense of time. Databases of paired HIV genotypes and drug resistance phenotypes provide the basis for the various resistance interpretation algorithms and represent a compromise between the two drug resistance testing 14 methods. Using a large sample of viruses with paired DNA sequences and in vitro resistance data, regression models and machine learning methods are implemented to predict the degree of resistance of a patient’s virus based on its genetic sequence. 77, 78 Ideally, the data sets that resistance prediction algorithms are based on are large and capture as much diversity (i.e. different subtypes, different drug exposure) as possible in order to be applicable to a broad range of HIV. There are currently commercially and publicly available algorithms for predicting phenotype based on genotype which are commonly used in clinical and research settings. 77-79 There can some discrepancy in the resistance interpretations given by various algorithms depending on the sample in question. 80-82 As commercial prediction algorithms and some public algorithms do not make publicly accessible the datasets from which they form their prediction algorithms, it can be difficult to determine the whether the differences in results are due to computational differences or due to differing underlying databases. Prediction algorithms that draw upon publicly available published data face the limitations of the amount of published data available and the variability between different phenotype assays. 1.7 Thesis Objectives and Organization 1.7.1 Thesis Objectives and Aims The objective of this thesis is to assess INSTI resistance , particularly to the newest INSTIs, DTG, BIC and CAB, in a large panel of recombinant HIV harbouring naturally selected amino acid substitutions in the integrase gene. Information on INSTI resistance is still relatively sparse and therefor the aims of this thesis are to 1) examine resistance to the newest INSTIs, 15 DTG, BIC and CAB in HIV with known major INSTI resistance mutations 2) develop and use a large panel of patient-derived recombinant viruses to investigate INSTI resistance. 1.7.2 Thesis organization This thesis is divided into four chapters. Figures and tables are placed after their first mention and supplementary data is provided in the appendices. Chapter One provides a general overview of HIV/AIDS as a disease, provides background information on virus diversity and INSTI resistance and introduces the techniques used to assess drug resistance. Chapters Two and Three contain the research conducted for this thesis and answer the main objectives. Chapter Two consists of an exploratory study into INSTI resistance to DTG, BIC and CAB. The phenotypic susceptibility profiles of a panel of 12 HIV-1 carrying known major INSTI resistance mutations. Recombinant viruses containing the major mutations G140S and Q148H, either alone or with additional amino acid substitutions, were generated from patient-derived samples and assayed for phenotypic susceptibility to DTG, BIC and CAB. Cross-resistance between the three INSTIs was also examined. Chapter Three expands upon the work in Chapter 2 and examines the phenotypic susceptibilities of a large panel of patient-derived HIV-1 integrase recombinant viruses to INSTIs. A systematic approach was used to identify the amino acid positions of interest in integrase and to generate the recombinant viruses required to represent the variability observed in the clinical population. The phenotypic susceptibility profiles of 162 recombinant viruses to five INSTIs, RAL, EVG, DTG, BIC and CAB, was examined and differential resistance was 16 analyzed based on the number of amino acid substitutions and the presence of individual amino acids. Finally, the cross-resistance between DTG and the other four INSTIs was analyzed. Chapter Four summarizes the findings of Chapter Two and Three and expands upon the limitations, implications and future applications of the main findings. A bibliography of the reference materials is provided at the end of Chapter Four. 17 Chapter 2: Accumulation of Multiple Mutations In Vivo Confers Cross-Resistance to New and Existing Integrase Inhibitors 2.1 Background Integrase inhibitors are the most recent class of antiretroviral drugs approved for treatment of Human Immunodeficiency Virus (HIV) infections. Raltegravir (RAL), approved for use in Canada in 2009, elvitegravir (EVG), approved in 2012 and dolutegravir (DTG), approved in 2014, are the three integrase inhibitors currently most widely in clinical use. New integrase inhibitors bictegravir (BIC) and cabotegravir (CAB), recently approved in Canada and in late-phase clinical trials respectively, have shown good efficacy and tolerability. 50, 83 Resistance to these integrase inhibitors could present a potential barrier to effective treatment. Mutations in integrase that confer resistance to RAL and EVG have been well documented, with many of the combinations of mutations having a lesser effect on phenotypic resistance to DTG than either RAL or EVG. 55 In the VIKING trials, integrase resistance mutations in RAL and EVG-experienced patients failing treatment lead to decreases in DTG efficacy. In particular, the combination of Q148 substitutions and two additional substitutions were common in patients failing RAL and EVG and led to a decreased response to DTG. 47, 48 Recent in vitro studies have shown that the combination G140S/Q148H with or without additional substitutions can affect BIC and CAB in addition to DTG efficacy, BIC tends to exhibit smaller fold-change phenotypic resistance and CAB exhibits higher fold-changes than DTG, although BIC, CAB and DTG were not directly compared in these studies. 58, 84 Currently, 18 little is known about the extent to which known integrase inhibitor resistance mutations compromise the effect of BIC and CAB and the amount of cross-resistance between the new and existing integrase inhibitors. To study the impact of G140S/Q148H with one or more additional substitutions on integrase inhibitor susceptibility, we assayed the in vitro phenotypic susceptibility of patient-derived recombinant viruses to RAL, EVG, DTG, BIC, and CAB. We also assessed cross-resistance between DTG and these integrase inhibitors. 2.2 Methods 2.2.1 Cells, viruses, and integrase inhibitors CEM-GXR cells and the HIV-1 pNL4.3 plasmid with integrase gene deleted (Δint) were kindly provided by Dr. Mark Brockman (Simon Fraser University, Burnaby, Canada). 85 MT4-LTR-EGFP cells were kindly provided by Dr. Theresa Pattery (Janssen Diagnostics, Beerse, Belgium). The drugs RAL, EVG, DTG, and CAB were purchased from Selleck Chemicals (Houston, USA). Bictegravir was synthesized by the Centre for Organic Synthesis, University of British Columbia (Vancouver, Canada). 2.2.2 Recombinant virus construction The British Columbia Centre for Excellence in HIV/AIDS (BCCfE) collected patient plasma samples as part of routine clinical testing. Patient samples that were tested for integrase genotype containing a variety of combinations of major, minor, and accessory mutations based on current Stanford HIVdb defined mutations were selected for recombinant virus construction. 19 86 Ethical approval was granted by the University of British Columbia Providence Health Care Research Ethics Board (protocol H14-03423). Samples were extracted using the NucliSens easyMag Extractor (bioMérieux, Saint-Laurent, Canada). “Oligo-genome” amplification was performed on viral extracts by dilution in diethyl pyrocarbonate-treated water to approximately 500 viral copies/mL in order to achieve primarily single-copy amplification. Diluted extracts were PCR amplified in 12 parallel reactions using the Transcriptor One-step RT-PCR kit (Roche, Basel, Switzerland) for reverse-transcription and first-round PCR. A second round of PCR amplification was performed on each reaction using integrase-specific primers IN4155F (5’-GTACCAGCACACAAAGGAATTGGAG) and IN5219R (5’-CCTAGTGGGATGTGTACTTCTGAAC) creating an amplicon covering amino acids 1-288 of integrase. PCR amplicons were sequenced on an ABI 3730xl sequencer (Thermo Fisher Scientific, Waltham, USA) and analyzed using the in-house base-calling software ReCall (University of British Columbia, Vancouver, Canada). 87 Amplicons that contained no inferred amino acid mixtures at 27 codons associated with HIV integrase exposure upon sequence analysis (see reference 7 and Appendix I) were chosen for recombinant virus construction. Where multiple amplicons met the criteria, one was chosen arbitrarily. Recombinant viruses were generated by co-transfecting amplicons with linearized Δint-pNL4.3 plasmid into CEM-GXR cells via electroporation using the Bio Rad Gene Pulser II using a previously described method. 85 Recombinant viruses, generated as previously described, were grown in RPMI-1640 media plus 20% fetal Bovine serum (R20+ media) and harvested at approximately 30% GFP. The virus sequences were confirmed to be identical to the amplicon sequences at 27 codons associated with HIV integrase exposure. 20 2.2.3 Phenotypic susceptibility assay and data analysis Recombinant virus titres were determined by infecting MT4-LTR-EGFP cells in a three-day assay and infectivity data collected using a Spectramax i3 Minimax 300 microplate reader (Molecular Devices, San Jose, USA). This microplate reader and cytometer captures images of each individual well of a 96-well plate and counts the number of infected fluorescent GFP-positive cells and non-infected GFP-negative cells. Titered volumes of recombinant viruses (such that 15% - 30% GFP+ is reached on the third or fourth day post-infection) and MT4-LTR-EGFP cells were plated in triplicate with eight concentrations ranging from no drug to 1000nM (10-fold dilutions from 0.1nM to 1000nM with 3nM and 45nM included) of drug of RAL, EVG, DTG, BIC and CAB. Percent infection was measured using the Spectramax microplate reader. 2.2.4 Data analysis The 50% effective concentrations (EC50s) were calculated by fitting to a four-parameter EC50 model using R with in-house scripts. Fold-changes (FC) in EC50 of the virus relative to a NL4.3 control virus were calculated from the average FCs (performed in triplicate) of one or more independent experiments. Medians, ranges and graphs were calculated and generated using R (version 3.2.3). 2.3 Results Eleven patient samples containing G140S/Q148H substitutions were identified from the BCCfE genotype database and 12 recombinant viruses with patient-derived integrase gene were constructed from clonal PCR products. The majority of the viruses tested were subtype B viruses (11/12) with one subtype C virus also included. Recombinant viruses were assayed for 21 phenotypic susceptibility to integrase inhibitors (Table 2.1). Of the 12 viruses examined, seven had only G140S/Q148H, two had the combination G140S/Q148H + T97A and three viruses had G140S/Q148H + T97A + L74M. Viruses with G140S/Q148H were highly resistant to RAL and EVG with FC >100 but had relatively small changes in susceptibility to DTG, BIC and CAB (median 2.5 to 3.7 FC) (Table 2.1). Viruses with an additional T97A substitution or additional T97A + L74M substitutions maintained high FC to RAL and EVG (>100 FC) but were increasingly resistant to DTG, BIC, and CAB. Resistance to DTG, BIC, and CAB increased 3 to 20-fold with each additional substitution. Resistance to DTG increased to 28 (range 23 - 33) with T97A and to 345 (range 263 - 514) with the further addition of L74M. Similar increasing trends were observed with BIC and CAB: 9 (range 5.6 - 12) to 67 (range 55 - 88) for BIC and 74 (range 30 - 117) to 586 (range 249 - 866) for CAB. Fold-change resistance to BIC was slightly lower than for DTG and CAB. Correlation coefficients of log FC values for DTG and the other four integrase inhibitors were calculated. Dolutegravir log fold-change resistance values were very strongly correlated with BIC and CAB with correlation coefficients of 0.97 (slope 0.69) and 0.96 (slope 1.1), respectively (Figure 2.1A, Figure 2.1B). DTG resistance, however, was poorly correlated with RAL and EVG resistance (data not shown). 22 Table 2.1 Median Fold-Change Resistance of Viruses to five INSTIs. Median (range) Fold-Change (FC) in the 50% effective concentrations (EC50) of recombinant viruses with G140S and Q148H mutations and additional mutations for raltegravir (RAL), elvitegravir (EVG), dolutegravir (DTG), bictegravir (BIC) and cabotegravir (CAB). Mutations G140S + Q148H G140S + Q148H + T97A G140S + Q148H + T97A + L74M N (patients) 6 2 3 n (viruses) 7 2 3 RAL >100 (>50 - >100) >100 (>50 - >100) >100 (>50 - >100) EVG >100 (>100 - >100) >100 (>100 - >100) >100 (>100 - >100) DTG 3.0 (1.9 - 8.2) 28 (23 - 33) 345 (263 - 514) BIC 2.5 (1.6 - 3.2) 9 (5.6 - 12) 67 (55 - 88) CAB 3.7 (1.8 - 5.8) 74 (30 - 117) 586 (249 - 866) 23 Figure 2.1 Correlations between dolutegravir, bictegravir and cabotegravir resistance. Correlation between log bictegravir (BIC), cabotegravir (CAB) and Dolutegravir (DTG) fold-change (FC) values for the same sample. A) Log BIC FC versus Log DTG FC. Correlation (r-value) was 0.97 and slope was 0.69. B) Log CAB FC versus Log DTG FC. Correlation (r-value) was 0.96 and slope was 1.1. 2.4 Discussion and Conclusion In this study, we compared the phenotypic profiles of HIV integrase inhibitors on a panel of patient-derived viruses containing G140S/Q148H substitutions, particularly in combination with additional minor or accessory substitutions. The Q148 pathway of resistance is one of the major pathways to developing high-level integrase inhibitor resistance. Q148 substitutions are commonly seen in patients failing RAL and EVG and have even been observed in a case of CAB failure. 50 Similar to reporting elsewhere, we observed that these variants had greatly reduced RAL and EVG susceptibility, exceeding the limits of our analysis. 88 Viruses containing only 24 G140S/G148H had relatively low (two to four-fold) shifts in resistance to DTG, BIC and CAB. However, small shifts in FC may have important clinical effects for these “next-generation integrase inhibitors” as seen in the VIKING-2 and VIKING-3 studies where even two-fold to ten-fold changes in susceptibility had an impact on clinical outcomes. 47, 48 We observed very substantial decreases in susceptibility to DTG, BIC, and CAB when the substitutions T97A and L74M were combined with the major substitutions G140S/Q148H. With at least two additional substitutions, Q148 substitutions can confer clinically relevant resistance to DTG and can decrease in vitro susceptibility to BIC. 47, 48, 58 The substitution T97A has been observed in patients on RAL and, in combination with G140S/Q148H, has been associated with 13-fold and >100-fold decreases in susceptibility to DTG and RAL respectively. 49, 89 The substitution L74M is a polymorphic substitution found in up to 10% of patients and confers further increased resistance to RAL and EVG when combined with the N155H but combined alone with G140S/G148H does not affect DTG susceptibility. 90 Phenotypic resistance data have not been previously reported for the pattern G140S/Q148H + T97A + L74M with RAL, EVG, BIC or CAB. 45 There is broad cross-resistance between RAL and EVG as they share some of the same resistance pathways and similar mechanisms of interaction with HIV integrase. 91 This study is one of the only in vitro studies so far to directly compare DTG, BIC and CAB resistance. The highly RAL and EVG - resistant virus variants in this study had greater slightly greater susceptibility to BIC than to DTG or CAB. However, the nearly co-linear relationship between log FC of DTG and BIC and CAB, and the similarity of trough drug levels of the three drugs 25 (1.1-2.6 µg/mL) suggests that it would not be feasible to use of any of these agents as “salvage” therapy after high-level integrase resistance develops. In summary, the accumulation of substitutions T97A and L74M greatly decreases susceptibility to DTG, BIC, and CAB, leading to high-level resistance to all five integrase inhibitors. Additionally, there is extensive cross-resistance between DTG, BIC, and CAB. Considering the limited scope of this study, further studies to assess the effect of other reported integrase substitutions in various permutations on DTG, BIC, and CAB susceptibility will be needed. 26 Chapter 3: Systematic determination of in vitro phenotypic resistance to HIV-1 Integrase Strand Transfer Inhibitors from clinical samples 3.1 Background The development and implementation of the combined antiretroviral regimens consisting of three drugs has led to a decrease in the rates of HIV transmission and deaths due to acquired immune deficiency syndrome – related illnesses around the world. 23, 92 The introduction of integrase strand-transfer inhibitors (INSTIs), raltegravir (RAL), elvitegravir (EVG), dolutegravir (DTG), bictegravir (BIC) and cabotegravir (CAB), has provided more options for the treatment of HIV with improved tolerability and favourable potency. 46, 50 In particular, DTG, BIC and CAB show great promise in providing a higher barrier to resistance. 93 However, emerging HIV drug resistance to INSTIs remains an important impediment to the efficacy of treatment and must be monitored. HIV drug resistance is primary detected using genotypic assays which look for known resistance-associated mutations in the patient virus genome. While time-efficient, genotypic assays rely on prior knowledge of mutations which confer drug resistance and may be less able to assess resistance in viruses with complex patterns of mutations. Phenotypic assays are used to measure resistance using in vitro culturing of patient-derived viruses and is able to provide a more specific and in-depth profile of drug resistance of each virus. As phenotypic assays are often costly and require long turnover times, it has limited uses in routine clinical monitoring. 59 However, large datasets of resistance data generated using phenotypic assays paired with genotypic data can provide the basis for inferring resistance from genotypes. While genotype- 27 phenotype correlations are currently used for inferring resistance to many existing drugs, the relative novelty of integrase inhibitors, particularly BIC and CAB, and the low rates of integrase inhibitor failure and acquired resistance limit the amount of the data available from which predictions about integrase inhibitor resistance may be drawn. In the previous chapter, as a proof-of-concept study, a limited sample of patient-derived viruses harbouring known INSTI resistance mutations were assayed for resistance to existing INSTIs. In order to represent the large diversity of viral sequences found in vivo, we generated a panel of patient-derived recombinant viruses with a broad range of amino acid permutations at 27 key amino acid positions of interest. We assessed the phenotypic susceptibility of a large panel of clinically-derived HIV variants to all five current INSTIs. 3.2 Methods 3.2.1 Cells, virus vectors and drugs The CEM-GXR cells and the HIV-1 pNL4.3 plasmid with integrase gene deleted (Δint) were provided by Dr. Mark Brockman (Simon Fraser University, Burnaby, Canada). The MT4-LTR-EGFP cells were provided by Dr. Theresa Pattery (Janssen Diagnostics, Beerse, Belgium). The integrase inhibitors, RAL, EVG, DTG, and CAB were purchased from Selleck Chemicals (Houston, USA). Bictegravir was synthesized by the Centre for Organic Synthesis, University of British Columbia (Vancouver, Canada). 3.2.2 Selection of amino acid positions A set of amino acid positions in the integrase gene were decided upon as positions associated with potential resistance. These positions of interest were based on current Stanford 28 HIV Database defined mutations and an analysis of amino acid substitutions selected for by INSTI treatment (Table 3.1). In an attempt to observe and identify yet unknown substitutions associated with INSTI treatment, 6,738 integrase sequences were accessed from the Stanford HIV Database, 1,003 of which were from INSTI-experienced patients (14.9%). Prevalence ratios, defined as the frequency of a mutation in the treated population relative to the frequency of that mutation in the non-treated population, were calculated for all amino acids in all amino acid positions in the integrase gene. Substitutions, insertions, deletions and mixtures (resolved to the mutation with the highest prevalence ratio) were included in the analysis. Two amino acid positions, V79 and D232 were selected from a list of 37 of the mutations with the highest log prevalence ratios to be considered as positions of interest (Table 3.1). Table 3.1 Log prevalence ratios of integrase amino acid substitutions. The ratio of the prevalence of each mutation in INSTI-experienced patients to INSTI-naïve patients was calculated and a log-transformation was applied. The log prevalence ratios were calculated using publicly available integrase sequence data from INSTI-experienced and INSTI-naïve patients. Log prevalence ratios >1 are shown. “X” represents amino acid substitutions that have been previously reported to be associated with INSTI resistance. Mutation Log Prevalence Ratio Associated with INSTI resistance Q148H 3.07 X N155H 2.83 X G140S 2.79 X Y143R 2.53 X Q148R 2.51 X E92Q 2.28 X Y143C 2.16 X 29 Mutation Log Prevalence Ratio Associated with INSTI resistance E138A 1.98 X G140A 1.92 X S230R 1.85 X S147G 1.73 X Y143H 1.59 X G140C 1.53 X Q95K 1.51 X G163R 1.35 X Y143G 1.35 X T97A 1.31 X E138K 1.27 X K160S 1.21 L158I 1.21 L74M 1.15 X V79I* 1.13 D232N* 1.08 T66I 1.04 X E170A 1.04 L63V 1.04 V180I 1.03 D229N 1.03 I161T 1.03 A169S 1.03 P142A 1.03 G70R 1.03 K273Q 1.03 R263K 1.03 X V260L 1.03 T218L 1.03 * Amino acid positions selected to be observed for this study. 3.2.3 Samples Patient plasma samples collected by the British Columbia Centre for Excellence in HIV/AIDS (BCCfE) up to the date of July 31st, 2017 as part of clinical testing were used. Ethical approval was granted by the University of British Columbia Providence Health Care Research 30 Ethics Board (protocol H14-03423). Upon physician request, INSTI resistance testing was performed on selected patient plasma samples as previously reported. In brief, HIV RNA from plasma samples were extracted using the NucliSens easyMag Extractor (bioMérieux, Saint-Laurent, Canada) followed by a ‘nested’ PCR amplification of the integrase gene which converted viral RNA into DNA. The integrase amplicons were then sequenced on an ABI 3730xl sequencer (Thermo Fisher Scientific, Waltham, USA). Sequence chromatograms were analyzed, and consensus sequences were generated using the in-house base-calling software ReCall. 87 Excluding amino acid mixtures at the 27 amino acid positions of interest, 12109 clinical samples were ultimately identified for potential recombinant virus generation. Additional samples were added, increasing the total number of samples to 15285 for the purposes of a coverage analysis (Appendix II) 3.2.4 Oligo clonal PCR Oligo clonal PCR amplification was performed on viral extracts that were diluted in diethyl pyrocarbonate-treated water to between 250 - 500 viral copies/mL. Diluted extracts were PCR amplified in 12 parallel reactions using the Transcriptor One-step RT-PCR kit (Roche, Basel, Switzerland) for reverse-transcription and first-round PCR. Integrase-specific primers IN4155F (5’-GTACCAGCACACAAAGGAATTGGAG) and IN5219R (5’-CCTAGTGGGATGTGTACTTCTGAAC) specifically for recombination were used in the second round of PCR creating an amplicon covering amino acids 1-288 of integrase. PCR amplicons were sequenced and analyzed as described above. Resulting amplicons which had no inferred amino acid mixtures at the 27 positions of interest were selected for recombinant virus construction. 31 3.2.5 Recombinant virus construction Recombinant viruses were generated by co-transfecting amplicons with linearized Δint-pNL4.3 plasmid into CEM-GXR cells via electroporation using the Bio Rad Gene Pulser II using a previously described method [9]. Recombinant viruses, generated as previously described, were grown in RPMI-1640 media plus 20% fetal Bovine serum (R20+ media) and harvested at approximately 30% GFP. The recombinant viruses were extracted and sequenced to confirm that resulting viruses were identical at the amino acid level at the 27 positions of interest to the amplicon sequences. 3.2.6 Phenotype assay Recombinant viruses with a unique permutation of amino acids at the 27 positions of interest were assayed for drug resistance using the phenotype assay described in Chapter 2. For viruses which were identical at the 27 positions of interest, only a single virus, chosen arbitrarily, was assayed. Dolutegravir, BIC and CAB resistance was assessed in 162 recombinant viruses and RAL and EVG resistance was assessed in 78 viruses. 3.2.7 Data analysis A four-parameter model was used to fit the data to calculate the 50% effective concentrations (EC50s) using R with in-house scripts. Fold-changes (FC) in EC50 of the virus relative to a NL4.3 control virus were calculated from the mean FCs (performed in triplicate) of one or more independent experiments. Log prevalence ratios, linear regressions, medians and graphs were calculated and generated using R (version 3.2.3). 32 3.3 Results 3.3.1 Identification of positions of interest in the integrase gene Prevalence ratios were calculated for each of the amino acid substitutions observed at each amino acid positions for which there was publicly available integrase sequences from INSTI-naïve and INSTI-experienced patients (Stanford HIV Database ver 8.4). Thirty-seven amino acid substitutions were found to be more prevalent in the INSTI-experienced group (log prevalence ratios >1) (Table 3.1). Twenty of these high prevalence substitutions were at 13 amino acid positions known to be associated with INSTI resistance (T66, E92, L74, Q95, T97, E138, G140, Y143, S147, Q148, N155, G163, S230 and R263). Amino acid positions V79 and D232 (with log prevalence ratios of 1.13 and 1.08, respectively for V79I and D232N), were selected at random from among the substitutions with prevalence ratios >1 to be considered as a position of interest for sample selection and downstream analyses. 3.3.2 Oligo-genome amplification and recombinant virus generation In order to generate a panel of recombinant viruses representative of the clinical population, approximately 290 amino acid permutations based on the 27 positions of interest were identified (Appendix II). Sample extracts were diluted to approximately 250 -500 copies/mL and PCR amplified in 12 parallel reactions to generate near clonal amplicon sequences. In total, 1644 amplicon sequences with no mixtures at the 27 amino acid positions of interest were collected from a total of 3985 PCR reactions, representing an average PCR success rate of 41%. Ultimately, 162 recombinant viruses were generated and assayed for resistance to all five INSTIs (Appendix III, Appendix IV). These recombinant viruses phenotyped represented a majority (90%) of the variation in clinical samples at the 27 positions of interest. 33 3.3.3 Subtype and amino acid diversity among recombinant viruses The oligo genome PCR procedure was designed to be able to amplify INT from all HIV subtypes. Both subtype B and non-subtype B extract samples from were chosen for dilution PCR amplification (Table 3.2). Of the resulting amplicons (excluding amplicons with mixtures), 75% (1233) were subtype B, 11% (188) were subtype C, 3.7% (61) were subtype A, 2.6% (42) were subtype CRF02_AG, 2.1% (35) were subtype G and less than 2% were of the subtypes D, F, J, CRF03_AB and CRF01_AE. The recombinant viruses generated and from the amplicons and phenotyped had a similar composition of subtypes: 70% (115) subtype B, 11% (18) subtype C, 8.0% (13) were subtype A, 3.1% (5) were subtype CRF02_AG, 2.5% (4) were subtype CRF01_AE, and less than 2% (1 to 3 viruses each) were of the subtypes D, F, G and CRF03_AB. No subtype J viruses were successfully generated. Recombinant viruses were generated containing amino acid substitutions that differed from the reference virus NL4-3 at all 27 amino acid positions of interest aside from P145 and Q146 (Figure 3.1). Of the 162 viruses assayed, most contained amino acid substitutions at positions G163 (N = 50), L74 (N = 35), Q148 (N = 34) and T97 (N = 33) (Figure 3.1). Substitutions at positions V79, H114, F121, V151, D232 and R263 were observed only in subtype B viruses while substitutions at positions H51 and G118 were observed only in non-subtype B viruses (Figure 3.1). Between one and eight different amino acids were observed at each of the 27 positions of interest among 162 recombinant viruses. The diversity of the amino acid substitutions at each of the 27 positions of interest observed is shown in Figure 3.2. The Positions G163 and L68 were the sites of the greatest amino acid diversity with eleven (A, E, G, 34 H, K, N, Q, R, S, T and V) and eight (A, H, K, P, Q, R, S, T) different amino acids observed respectively. Table 3.2 HIV subtypes of oligo-clonal amplicons and recombinant viruses. Subtype Amplicons (%) n = 1644 Virus (%) n = 162 A 61 (3.7) 13 (8.0) B 1233 (75) 115 (70) C 188 (11) 18 (11) D 31 (1.9) 2 (1.2) F 17 (1.0) 1 (>1) G 35 (2.1) 3 (1.9) J 1 (>1) 0 CRF01_AE 18 (1.1) 4 (2.5) CRF02_AG 42 (2.6) 5 (3.1) CRF03_AB 18 (1.1) 1 (>1) 35 Figure 3.1 The number of recombinant viruses with amino acid substitutions. The number of recombinant viruses with different amino acid substitutions observed at each amino acid position of interest in subtype B (N=115, dark grey) and non-B recombinant viruses (N=47, light grey). 36 Figure 3.2 Amino acid variation. The variability of different amino acid substitutions observed at each amino acid position of interest in A) subtype B and B) non-B viruses. B A 37 3.3.4 Phenotype Assay The majority of the recombinant viruses phenotyped exhibited log fold-changes (FC) in the 50% effective concentrations (EC50) that were comparable to the wildtype NL4-3 control viruses (Figure 3.3). The median log FC in resistance was highest for CAB (median: 0.19; Q1-Q3: 0.029 – 0.47) followed by DTG (median: 0.037; Q1-Q3: -0.080 – 0.29), and BIC (median: 0.023; Q1-Q3: -0.11 – 0.20). The range of log FC in resistance was greater for CAB (range -0.51 – 3.7) than for DTG (range: 0.54 – 2.9) or BIC was -0.59 – 2.8 such that the maximum fold-change for CAB was approximately 10 times greater than the maximum fold-change for DTG and BIC. Median FC in resistance to RAL (median: 0.22; Q1-Q3: 0.017 – 3.0) and EVG (median: 0.55; Q1-Q3: 0.082 – 3.6) were greater than median FC for DTG and BIC but similar to CAB (Appendix V). 38 Figure 3.3 Distribution of log fold-changes. Distribution of log fold-changes (FC) in the 50% effective concentrations (EC50) to dolutegravir (DTG), bictegravir (BIC) and cabotegravir (CAB) of 162 recombinant viruses. Each of the 162 recombinant viruses carried between zero and six amino acid substitutions (relative to NL4-3) at the 27 positions of interest. Fold-change (FC) in resistance to DTG, BIC, and CAB are relatively similar across viruses with zero to three amino acid substitutions (Figure 3.4). Resistance to CAB was higher than resistance to DTG or BIC across viruses with three to six substitutions with a nearly 2-fold higher median FC in viruses with six substitutions. A wider range of FC shifts were observed for subtype B viruses compared to non-subtype B viruses (Figure 3.4). 39 Figure 3.4 Average fold-change in resistance grouped by the number of substitutions. Average (median) Fold-change (FC) in resistance to dolutegravir (DTG), bictegravir (BIC) and cabotegravir (CAB) for viruses with zero to six amino acid substitutions at the 27 amino acid positions of interest. The FC cut-off for DTG, reported in the literature, is shown with a dotted line A) Average FC for all 162 viruses. B) Average FC for subtype B viruses (N = 115) and for non-subtype B viruses (N = 47). A B 40 Substitutions at R263 (N = 2) were the only single amino acid substitutions to result in a median FC elevated above 3-FC for DTG, BIC and CAB (3.9, 3.2 and 4-fold, respectively) (Figure 3.5). Single amino substitutions N155H, E157Q and Y143R had >3-FC for RAL and EVG. Among the double mutants observed, T66I/G118R had >3-FC for DTG, BIC and CAB. G140S/Q148R showed consistently >3-FC for all five drugs. N155H/G163E had >3-FC for CAB (and RAL and EVG) but was susceptible to DTG and BIC. R263K/G163E had consistently higher FC (>3-FC) as a double mutant as well. E138K/Q148R had >10 and >200-FC for RAL and EVG, respectively. Among triple mutants, E138A/G140S/Q148H showed >5-FC for CAB, however it was susceptible to BIC and DTG (2 and 2.8-fold, respectively). As shown previously, eight viruses carried G140S/Q148H, two had the combination G140S/Q148H + T97A and three viruses had G140S/Q148H + T97A + L74M. Viruses with G140S/Q148H were highly resistant to RAL and EVG with >100-FC but had relatively small changes in susceptibility to DTG, BIC and CAB (median 2.9 to 4.7 FC). Viruses with an additional T97A substitution or additional T97A + L74M substitutions maintained high FC to RAL and EVG (>100-FC) but were increasingly resistant to DTG, BIC, and CAB (see Chapter 2). Among quadruple mutants, V79I/E138K/G140A/Q148R had >10-FC for DTG, BIC and CAB. A virus carrying six amino acid substitutions (L74I/V79I/G140A/Q148R/V151I/ E157Q) showed high FC to DTG, BIC and CAB (>500-FC). One additional virus carrying six amino acid substitutions (L74I/T97M/F121C/V151I/E157Q/G163K) showed >50-FC for CAB, however it was susceptible to DTG and BIC. The greatest exceptions were variants with N155H/G163E or L74I/T97M/F121C/V151I/E157Q/G163K, where both had >75-FC for CAB, while <3-FC for DTG and BIC (Figure 3.6). 41 Figure 3.5 Effect of single amino acid substitutions Average log fold-change (FC) in resistance to dolutegravir (DTG), bictegravir (BIC) and cabotegravir (CAB) of recombinant viruses with single amino acid substitutions in one of the 27 amino acid positions of interest. The dashed horizontal line shows a previously published resistance cut-off for DTG. 42 Figure 3.6 Average log fold-change in resistance grouped by amino acid substitution. Average log fold-change (FC) of each individual single amino acid substitution in subtype B and non-B viruses. 3.3.5 Extensive cross-resistance between DTG, BIC and CAB The correlation coefficients of log FC values for BIC, CAB, RAL and EVG versus DTG were calculated. The log FC resistance values for DTG were strongly correlated with BIC and CAB with correlation coefficients of 0.93 (slope 0.81) and 0.87 (slope 1.1), respectively (Figure 43 3.7A, Figure 3.7B). Small shifts in DTG resistance was associated with large increases in RAL and EVG resistance (Figure 3.7C, Figure 3.7D). Since RAL and EVG FCs reached maximum levels (at or beyond the level of detection of the phenotype assay) while DTG FC remained relatively low (<1-FC), DTG resistance was poorly correlated with RAL and EVG resistance. 44 Figure 3.7 Correlations between dolutegravir, bictegravir, cabotegravir, raltegravir and elvitegravir resistance. Correlation between log bictegravir (BIC), cabotegravir (CAB), raltegravir (RAL), elvitegravir (EVG) and dolutegravir (DTG) fold-change (FC) values for the same viruses. A) Log BIC FC versus Log DTG FC for 162 viruses. Correlation (r-value) was 0.93 and slope was 0.81. B) Log CAB FC versus Log DTG FC for 162 viruses. Correlation (r-value) was 0.87 and slope was 1.1. C) Log RAL FC versus Log DTG FC for 78 viruses. D) Log EVG FC versus Log DTG FC for 78 viruses. 45 3.4 Discussion and Conclusion Integrase-strand transfer inhibitors are being rolled out across the world as effective complements to the other well-established drug classes as a part of highly active antiretroviral treatment (HAART). To date, relatively few cases INSTI resistance have been reported in clinical settings, with most reported cases of resistance being associated with RAL or EVG use. 54, 94, 95 Resistance to second generation integrase inhibitors, DTG, BIC and CAB, is uncommon likely as a result of the drugs’ high barrier for resistance. While the low rate of resistance is a highly desirable characteristic of an ARV, it limits our knowledge of resistance mutations which may compromise the use of INSTIs. Characterizing the INSTI resistance profiles of large panels of clinically-derived viruses can provide the data necessary to inferring INSTI resistance based on genotypes using genotype-phenotype algorithms. This study is among the first and largest studies that characterizes the phenotypic susceptibility profiles of a large panel of patient-derived HIV-1 recombinant viruses to all five INSTIs, RAL, EVG, DTG, BIC and CAB. Published in vitro phenotypic susceptibility data is relatively sparse for RAL, EVG and DTG with under 40 amino acid permutations matched with phenotypic susceptibility values while data for BIC and CAB are nearly absent. 96-99 In order to capture the diversity of our clinical database of over 15000 samples and 288 amino acid permutations, we selected samples which would cover as many of the 288 permutations as possible. While certain permutations were omitted due to the scarcity of samples, we found that the relatively few samples we used in this analysis (N = 141) represented about 99% of the variation in the clinical samples (Appendix VI). Furthermore, the inclusion of non-subtype B recombinant viruses gives a preliminary glimpse into the differences in amino acid substitutions 46 and resistance profiles between subtype B and non-subtype B HIV in an area of research that is still predominantly focused on subtype B HIV. Previous clinical study observations and in vitro selection assays have found DTG failure to be linked to the substitution R263K which can reduce DTG susceptibility by two to 20-fold. Similarly, we found that the single substitution R263K was the only single substitution to reduce DTG, BIC and CAB susceptibility beyond the resistance cut-off for DTG of 1.58 that has been reported elsewhere. In contrast, reports on laboratory-adapted strains that carry Q148R/N155H with DTG FC of around 5 could not be replicated as we did not observe any instances of N155H co-existing with a Q148R alone in over 15,000 clinical isolates. When found in combination N155H and Q148 substitutions existed as G140S/Q148K/N155H. This suggests that using site-directed mutagenesis to generate INSTI-resistant viruses may not be sufficient to represent the in vivo sequence variation of clinically populations. In line with our findings in Chapter 2, log-FC resistance to RAL and EVG was higher than log-FC resistance to the second generation INSTIs, DTG, BIC and CAB. Due to the similarities between RAL and EVG resistance, developing resistance to either RAL or EVG would preclude the use of the other. As we previous found, DTG, BIC and CAB resistance was well correlated with 162 recombinant viruses. This study is limited firstly in that only 27 amino acid positions were considered in our analysis. Other amino acid substitutions within integrase or outside integrase which may confer some level of INSTI resistance were not part of this study which limits our ability to directly 47 infer phenotypes from genotypes. Secondly, this study lacks clinically defined cut-off values which would have allowed us to comment on the clinical impacts of the in vitro resistance observed. Lastly, the patient population from which we drew our samples was exposed mostly to RAL/EVG or naïve to INSTIs altogether. Viruses with substitutions selected for by DTG or other second-generation INSTIs are likely under-represented. 48 Chapter 4: General Discussion and Conclusion 4.1 Thesis Summary As new INSTIs become available, the need for studies that assess the resistance profiles to these new drugs becomes apparent. Of particular interest is the effectiveness of the newer INSTIs, DTG, BIC and CAB on RAL and EVG-resistant viruses. Chapter Two provides a preliminary assessment of the effect of select known INSTI resistance mutations upon DTG, BIC and CAB in a direct comparison. While there appeared to be very little cross-resistance between the three newer INSTIs and RAL and EVG in the context of the major INSTI resistance pattern G140S and Q148H, additional substitutions L74M and T97A elevated the level of resistance observed greatly to all INSTIs. In clinical trials looking at the efficacy of DTG in INSTI-experienced patients, successful viral suppression was limited particularly in patients with substitutions at Q148 and two or more additional substitutions. Additionally, this study found a high level of cross-resistance between DTG, BIC and CAB, highlighting the similarity between these drugs. The findings in this chapter further confirm that compounded substitutions have a profound effect on resistance and suggest that the effectiveness of DTG, BIC or CAB as salvage therapy in heavily INSTI treatment-experienced patients may be ineffective. This study was very limited in scope with a small sample size, looking at only the well-established INSTI resistance pathway with G140S and Q148H. While the very large decreases in susceptibility and the strength of the correlation between DTG, BIC and CAB suggest that these results are convincing. Further experiments with more samples and a greater variety of patterns of amino acid substitutions required to expands this study are discussed in Chapter Three. 49 In Chapter Three, a large panel of viruses (N = 162) harbouring various permutations of amino acid substitutions in integrase were assayed for INSTI resistance. We use a systematic and relatively time-efficient method to identify permutations of substitutions observed in clinical populations and to generate near-clonal recombinant viruses using patient-derived isolates. A high level of cross-resistance was found between DTG, BIC and CAB, confirming a similar finding in the study discussed in Chapter Two. 4.2 Limitations The findings in this thesis contribute to a body of knowledge of INSTI resistance and has implications for INSTI use, however these results are not intended for making clinical judgements and decisions. These studies were conducted using an in vitro system without defined clinical cut-offs and were meant to observe the magnitude of resistance to various INSTIs. Furthermore, the diversity of the viruses used in these studies represents only a small proportion of the diversity of all the viruses harboured by patients on INSTIs worldwide. The majority of the viruses used in this study were subtype B, as is representative of the HIV epidemic in North America, however, the majority of the subtypes around the world are non-B subtypes. Future studies should focus on expanding to the variety of viruses in this panel and coupling these results with clinical observations in order to provide information for clinical assessments. 50 4.3 Overall impact and future directions Integrase strand-transfer inhibitors are a class of HIV antiretrovirals that has seen many advancements in recent years. With the increased uptake by countries around the world, the inclusion by various HIV treatment guidelines in first-line regimens and the development of new drug, INSTIs are becoming a prominent part of the treatment of HIV infections. As with other drugs classes that came before, a major barrier to the effectiveness of INSTIs is drug resistance. Currently, the collective knowledge of INSTI resistance is centered around the INSTIs that have been available the longest, RAL and EVG. Information on DTG resistance is still fairly sparse and information on BIC and CAB resistance is less prevalent still. Collectively, Chapters Two and Three presents one of the largest sets of directly compared DTG, BIC and CAB resistance data publicly available. This data has been incorporated into the public Stanford HIV resistance database along with other published resistance data to provide resistance information on INSTIs accessible to researchers and the public. Dolutegravir and, recently, BIC, have been said to have a high barrier to developing resistance mutations and could potentially be used for “salvage therapy” when other INSTIs become ineffective due to resistance. Resistance to DTG and BIC (and to some extent CAB) has been found to be lesser in magnitude and in frequency compared to RAL and EVG. However, in clinical trials, DTG has been found to have limited efficacy in INSTI-treated patients with viruses harbouring multiple resistance-associated substitutions. The results in Chapter Three support the finding that complex patterns of multiple substitutions, particularly at G140 and Q148, render all five INSTIs ineffective. Furthermore, the high level of cross-resistance between 51 DTG, BIC and CAB suggests that the use of these drugs as “salvage therapy” once resistance develops to any one of the INSTIs may be inappropriate. While the findings in this thesis provide a substantial amount of information about DTG, BIC and CAB resistance to an area of study that is as recent as the drugs themselves, continued efforts to understand the pathways to resistance and other amino acid substitutions or polymorphisms which may impact INSTI susceptibility will be needed. The methods of “oligo-clonal” amplification described in Chapter Three can be used create large panels of patient-derived viruses for future drug resistance studies. Furthermore, the current panel of viruses can be a starting point for investigating new INSTIs which may be developed. Expanding upon this panel to include new amino acid permutations as clinical INSTI resistance continues to be observed and viruses of non-B subtypes would provide a larger dataset and broaden our understanding of INSTI resistance. It will be important to continue the monitoring of INSTI resistance and the genetic variation of HIV both within and outside integrase. 52 Bibliography 1. UNAIDS. Global HIV & AIDS statistics – 2018 fact sheet. 2018 Available from: http://www.unaids.org/en/resources/fact-sheet 2. World Health Organization. Number of people (all ages) living with HIV.https://www.who.int/gho/hiv/epidemic_status/cases_all/en/. Published August 29, 2018. Accessed May 16, 2019. 3. Wyatt R, Sodroski J. The HIV-1 Envelope Glycoproteins: Fusogens, Antigens, and Immunogens. Science. 1998; 280:1884-1888. 4. Hymes KB, Cheung T, Greene JB, Prose NS, Marcus A, Ballard H et al. Kaposi's sarcoma in homosexual men: A report of eight cases. Lancet. 1981;2(8247):598-600 5. Centers for Disease Control (CDC). Kaposi's Sarcoma and Pneumocystis Pneumonia among Homosexual Men- New York City and California. Morbidity and Mortality Weekly Report. 1981;30(25):305-308 6. Centers for Disease Control (CDC). Current Trends Update on Acquired Immune Deficiency Syndrome (AIDS) - United States. Morbidity and Mortality Weekly Report.1982; 31(37):507-508 7. Popovic M, Sarin PS, Robert-Gurroff M, Kalyanaraman VS, Mann D, Minowada J et al. Isolation and Transmission of Human Retrovirus (Human T-Cell Leukemia Virus). Source Sci. New Ser. 1983;219, 856–859. 8. Barré-Sinoussi F, Chermann JC, Rey F, Nugeyre MT, Chamaret S, Gruest J, et al. Isolation of a T-lymphotropic retrovirus from a patient at risk for acquired immune deficiency syndrome (AIDS). Science.1983;220(4599):868-871 53 9. Case K. Nomenclature: Human Immunodeficiency Virus' Annals of Internal Medicine. 1986;105(1):133 10. Gottlieb GS, Raugi DN, Smith RA. 90-90-90 for HIV-2? Ending the HIV-2 epidemic by enhancing care and clinical management of patients infected with HIV-2. The Lancet HIV. 2018; 5(7):e390-e399 11. Kuiken CL, Foley B, Hahn B, Marx PA, McCutchan F, Mellors JW, et al. Human Retroviruses and AIDS 1999: A Compilation and Analysis of Nucleic Acid and Amino Acid Sequences. Eds Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, Los Alamos, NM. 12. Hemelaar J. The origin and diversity of the HIV-1 pandemic. Trends Mol Med. 2012;18(3):182-92. 13. Buonaguro L, Tornesello ML, Buonaguro FM. Human Immunodeficiency Virus Type 1 Subtype Distribution in the Worldwide Epidemic: Pathogenetic and Therapeutic Implications. Journal of Virology. 2007;81(19):10209-10219 14. Li G, Piampongsant S, Faria NR, Voet A, Pineda-Peña A, Khouri R, Lemey P, et al. An integrated map of HIV genome-wide variation from a population perspective. Retrovirology. 2015;12:18. 15. Maldarelli F, Kearney M, Palmer S, Stephens R, Mican J, Polis MA, et al. HIV populations are large and accumulate high genetic diversity in a nonlinear fashion. J Virol. 2013;87(18):10313-23. 16. Cuevas JM, Geller R, Garijo R, López-Aldeguer J, Sanjuán R. Extremely High Mutation Rate of HIV-1 In Vivo. PLOS Biology 2015;13(9): e1002251. 54 17. Li JZ, Paredes R, Ribaudo HJ, Svarovskaia ES, Metzner KJ, Kozal MJ, et al. Low-frequency HIV-1 drug resistance mutations and risk of NNRTI-based antiretroviral treatment failure: a systematic review and pooled analysis. JAMA. 2011;305(13):1327-35. 18. U.S. Food & Drug Administration. HIV/AIDS Historical Time Line 1981-1990. 2018. Accessed: 2019, Mar 3. Available from: https://www.fda.gov/patients/hiv-timeline-and-history-approvals/hivaids-historical-time-line-1981-1990 19. Stambuk D, Hawkins D, Gazzard BG. Zidovudine treatment of patients with acquired immune deficiency syndrome and acquired immune deficiency syndrome-related complex: St Stephen's Hospital experience. J Infect. 1989; Suppl 1:41-51. 20. Larder BA, Darby G, Richman DD. HIV with reduced sensitivity to Zidovudine (AZT) isolated during prolonged therapy. Science. 1989;234, 1731–1734. 21. Harrigan PR, Hogg RS, Dong WW, Yip B, Wynhoven B, Woodward J, et al. Predictors of HIV drug-resistance mutations in a large antiretroviral-naive cohort initiating triple antiretroviral therapy. J Infect Dis. 2005;191(3):339-47. 22. Mathez D, Bagnarelli P, Gorin I, Katlama C, Pialoux G, Saimot G, et al. Reductions in viral load and increases in T lymphocyte numbers in treatment-naive patients with advanced HIV-1 infection treated with ritonavir, zidovudine and zalcitabine triple therapy. Antivir Ther. 1997;2(3):175-83. 23. Henry K, Erice A, Tierney C, Balfour HH, Fischl MA, Kmack A, et al. A randomized, controlled, double-blind study comparing the survival benefit of four different reverse transcriptase inhibitor therapies (three-drug, two-drug, and alternating drug) for the treatment of advanced AIDS. AIDS Clinical Trial Group 193A Study Team. J Acquir Immune Defic Syndr Hum Retrovirol. 1998;19(4):339-49. 55 24. Anema A, Lima VD, Johnston K, Levy A, Montaner JS. Expanded Highly Active Antiretroviral Therapy Coverage - A Powerful Strategy to Curb Progression to AIDS, Death and New Infections. Eur Infect Dis. 2009;3(1):41-43. 25. Romani B, Allahbakhshi E. Underlying mechanisms of HIV-1 latency. Virus Genes. 2017;53(3):329-339. 26. De Clercq E, Li G. Approved Antiviral Drugs over the Past 50 Years. Clinical microbiology reviews. 2016;29(3): 695-747. 27. Arts EJ, Hazuda DJ. HIV-1 antiretroviral drug therapy. Cold Spring Harb Perspect Med. 2012;2(4):a007161. 28. Lv Z, Chu Y, Wang Y. HIV protease inhibitors: a review of molecular selectivity and toxicity. HIV. AIDS. 2015;7, 95–104. 29. Ghosh AK, Osswald HL, Prato G. Recent Progress in the Development of HIV-1 Protease Inhibitors for the Treatment of HIV/AIDS. J Med Chem. 2016;59(11):5172-208. 30. Montessori V, Press N, Harris M, Akagi L, Montaner JS. Adverse effects of antiretroviral therapy for HIV infection. CMAJ. 2004;170(2): 229-38. 31. Yi HA, Fochtman BC, Rizzo RC, Jacobs A. Inhibition of HIV Entry by Targeting the Envelope Transmembrane Subunit gp41. Curr HIV Res. 2016;14(3):283-94. 32. Dorr P, Westby M, Dobbs S, Griffin P, Irvine B, Macartney M, et al. Maraviroc (UK-427,857), a potent, orally bioavailable, and selective small-molecule inhibitor of chemokine receptor CCR5 with broad-spectrum anti-human immunodeficiency virus type 1 activity. Antimicrob Agents Chemother. 2005;49(11):4721-32. 56 33. WHO. Consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection Recommendations for a public health approach - Second edition. World Health Organization June 2016 34. Günthard HF, Saag MS, Benson CA, del Rio C, Eron JJ, Gallant JE, et al. Antiretroviral Drugs for Treatment and Prevention of HIV Infection in Adults 2016 Recommendations of the International Antiviral Society–USA Panel. JAMA. 2016;316(2):191–210. 35. Mouscadet JF, Tchertanov L. Raltegravir: molecular basis of its mechanism of action. Eur J Med Res. 2009;14 (Suppl 3):5-16. 36. Di Santo R. Inhibiting the HIV integration process: past, present, and the future. J Med Chem. 2013;57(3):539-66. 37. Hare S, Gupta SS, Valkov E, Engelman A, Cherepanov P. Retroviral intasome assembly and inhibition of DNA strand transfer. Nature. 2010;464(7286):232-6.) 38. U.S. Department of Health and Human Services. Drug Approval Package Drug Name: Isentress (raltegravir) 400mg Tablets. U.S. Food & Drug website. https://www.accessdata.fda.gov/drugsatfda_docs/nda/2007/022145_Isentress.cfm. February 22, 2008. Accessed June 7, 2017.) 39. (U.S. Department of Health and Human Services. Drug Approval Package Stribild (elvitegravir, cobicistat, emtricitabine, tenofovir disoproxil fumarate) Fixed Dose Combination Tablets. U.S. Food & Drug website. https://www.accessdata.fda.gov/drugsatfda_docs/nda/2012/203100Orig1s000TOC.cfm. October 10, 2012. Accessed June 7, 2017) 40. Lennox JL, Dejesus E, Berger DS, Lazzarin A, Pollard RB, Ramalho Madruga JV, et al. Raltegravir versus Efavirenz regimens in treatment-naive HIV-1-infected patients: 96-week 57 efficacy, durability, subgroup, safety, and metabolic analyses. J Acquir Immune Defic Syndr. 2010;55(1):39-48. 41. Teppler H, Brown DD, Leavitt RY, Sklar P, Wan H, Xu X, et al. Long-term safety from the raltegravir clinical development program. Curr HIV Res. 2011;9(1):40-53. 42. Sax PE, DeJesus E, Mills A, Zolopa A, Cohen C, Wohl D, et al. Co-formulated elvitegravir, cobicistat, emtricitabine, and tenofovir versus co-formulated efavirenz, emtricitabine, and tenofovir for initial treatment of HIV-1 infection: a randomised, double-blind, phase 3 trial, analysis of results after 48 weeks. Lancet. 2012;379(9835):2439-2448. 43. Cohen C, Elion R, Ruane P, Shamblaw D, DeJesus E, Rashbaum B, et al. Randomized, phase 2 evaluation of two single-tablet regimens elvitegravir/cobicistat/emtricitabine/tenofovir disoproxil fumarate versus efavirenz/emtricitabine/tenofovir disoproxil fumarate for the initial treatment of HIV infection. AIDS. 2011;25(6):F7-12. 44. Winters MA, Lloyd RM, Shafer RW, Kozal MJ, Miller MD, Holodniy M. Development of elvitegravir resistance and linkage of integrase inhibitor mutations with protease and reverse transcriptase resistance mutations. PLoS One. 2012;7(7):e40514. 45. Eron JJ, Cooper DA, Steigbigel RT, Clotet B, Gatell JM, Kumar PN et al. Efficacy and safety of raltegravir for treatment of HIV for 5 years in the BENCHMRK studies: final results of two randomised, placebo-controlled trials. Lancet Infect Dis. 2013;13(7):587-96. 46. Sax PE, Dejesus E, Crofoot G, Ward D, Benson P, Wei L, et al. A Randomized Trial of Bictegravir or Dolutegravir with Emtricitabine and Tenofovir Alafenamide (F/TAF) Followed by Open Label Switch to Bictegravir/F/TAF Fixed Dose Combination. Open Forum Infect Dis. 2017;4(Suppl 1):S426–S427. 58 47. Eron JJ, Clotet B, Durant J, Katlama C, Kumar P, Lazzarin A, Poizot-Martin I, et al. Safety and efficacy of dolutegravir in treatment-experienced subjects with raltegravir-resistant HIV type 1 infection: 24-week results of the VIKING Study. The Journal of Infectious Diseases. 2013;207(5):740–748. 48. Castagna A, Maggiolo F, Penco G, Wright D, Mills A, Grossberg R, et al.Dolutegravir in Antiretroviral-Experienced Patients With Raltegravir- and/or Elvitegravir-Resistant HIV-1: 24-Week Results of the Phase III VIKING-3 Study. The Journal of Infectious Diseases. 2014;210(3):354-362. 49. Seki T, Suyama-Kagitani A, Kawauchi-Miki S, Wakasa-Morimoto C, Akihisa E, Nakahara K, et al. Effects of raltegravir or elvitegravir resistance signature mutations on the barrier to dolutegravir resistance in vitro. Antimicrob Agents Chemother. 2015;59(5):2596-606. 50. Margolis DA, Gonzalez-Garcia J, Stellbrink HJ, Eron JJ, Yazdanpanah Y, Podzamczer D, et al. Long-acting intramuscular cabotegravir and rilpivirine in adults with HIV-1 infection (LATTE-2): 96-week results of a randomised, open-label, phase 2b, non-inferiority trial. Lancet. 2017;390(10101):1499-1510. 51. You J, Wang H, Huang X, Qin Z, Deng Z, Luo J, et al. Therapy-Emergent Drug Resistance to Integrase Strand Transfer Inhibitors in HIV-1 Patients: A Subgroup Meta-Analysis of Clinical Trials. PLoS One. 2016;11(8):e0160087. 52. Malet I, Subra F, Charpentier C, Collin G, Descamps D, Calvez V, Marcelin AG, Delelis O. Mutations Located outside the Integrase Gene Can Confer Resistance to HIV-1 Integrase Strand Transfer Inhibitors. MBio. 2017;8(5). pii:e00922-17. 59 53. Cooper DA, Steigbigel RT, Gatell JM, Rockstroh JK, Katlama C, Yeni P, et al. Subgroup and resistance analyses of raltegravir for resistant HIV-1 infection. N Engl J Med. 2008;359(4):355-65. 54. Hurt CB, Sebastian J, Hicks CB, Eron JJ. Resistance to HIV integrase strand transfer inhibitors among clinical specimens in the United States, 2009-2012. Clin Infect Dis. 2013;58(3):423-31. 55. Anstett K, Brenner B, Mesplede T, Wainberg MA. HIV drug resistance against strand transfer integrase inhibitors. Retrovirology. 2017;14(1):36. 56. Garrido C, Villacian J, Zahonero N, Pattery T, Garcia F, Gutierrez F, et al. Broad phenotypic cross-resistance to elvitegravir in HIV-infected patients failing on raltegravir-containing regimens. Antimicrob Agents Chemother. 2012;56(6):2873-8. 57. Kobayashi M, Yoshinaga T, Seki T, Wakasa-Morimoto C, Brown KW, Ferris R, et al. In Vitro antiretroviral properties of S/GSK1349572, a next-generation HIV integrase inhibitor. Antimicrob Agents Chemother. 2010;55(2):813-21. 58. Tsiang M, Jones GS, Goldsmith J, Mulato A, Hansen D, Kan E, Tsai L, et al. Antiviral Activity of Bictegravir (GS-9883), a Novel Potent HIV-1 Integrase Strand Transfer Inhibitor with an Improved Resistance Profile. Antimicrobial Agents and Chemotherapy. 2016;60(12):7086-7097. 59. Günthard HF, Calvez V, Paredes R, Pillay D, Shafer RW, Wensing AM, et al. Human Immunodeficiency Virus Drug Resistance: 2018 Recommendations of the International Antiviral Society–USA Panel. Clinical Infectious Diseases.2019;68(2):177–187. 60. WHO. HIV Drug Resistance Surveillance Guidance: 2015 Update. World Health Organization, December 2015 60 61. Clutter DS, Jordan MR, Bertagnolio S, Shafer RW. HIV-1 drug resistance and resistance testing. Infect Genet Evol. 2016;46:292-307. 62. Naeger LK, Struble KA. Effect of baseline protease genotype and phenotype on HIV response to atazanavir/ritonavir in treatment-experienced patients. AIDS. 2006;20(6):847-853. 63. Ávila-Ríos S, García-Morales C, Matías-Florentino M, Romero-Mora KA, Tapia-Trejo D, Quiroz-Morales VS, et al. Pretreatment HIV-drug resistance in Mexico and its impact on the effectiveness of first-line antiretroviral therapy: a nationally representative 2015 WHO survey. Lancet HIV. 2016;3(12):e579-e591. 64. Koullias Y, Sax PE, Fields NF, Walensky RP, Hyle EP. Should We Be Testing for Baseline Integrase Resistance in Patients Newly Diagnosed With Human Immunodeficiency Virus? Clin Infect Dis. 2017;65(8):1274-1281. 65. Cingolani A, Antinori A, Rizzo MG, Murri R, Ammassari A, Baldini F, et al. Usefulness of monitoring HIV drug resistance and adherence in individuals failing highly active antiretroviral therapy: a randomized study (ARGENTA). AIDS. 2002;16(3):369-379. 66. Baxter JD, Mayers DL, Wentworth DN, Neaton JD, Hoover ML, Winters MA, et al. A randomized study of antiretroviral management based on plasma genotypic antiretroviral resistance testing in patients failing therapy. CPCRA 046 Study Team for the Terry Beirn Community Programs for Clinical Research on AIDS. AIDS. 2000;14(9):F83-93. 67. Cohen CJ, Hunt S, Sension M, Farthing C, Conant M, Jacobson S, et al. A randomized trial assessing the impact of phenotypic resistance testing on antiretroviral therapy. AIDS. 2002;16(4):579-588. 61 68. Vercauteren J, Vandamme AM. Algorithms for the interpretation of HIV-1 genotypic drug resistance information. Antiviral Res. 2006;71(2-3):335-342. 69. Paredes R, Tzou PL, van Zyl G, Barrow G, Camacho R, Carmona S, et al. Collaborative update of a rule-based expert system for HIV-1 genotypic resistance test interpretation. PLoS One. 2017;12(7):e0181357. 70. Obermeier M, Pironti A, Berg T, Braun P, Däumer M, Eberle J, et al. HIV-GRADE: a publicly available, rules-based drug resistance interpretation algorithm integrating bioinformatic knowledge. Intervirology. 2012;55(2):102-7. 71. Tural C, Ruiz L, Holtzer C, Schapiro J, Viciana P, González J, et al. Clinical utility of HIV-1 genotyping and expert advice: the Havana trial. AIDS. 2002;16(2):209-218. 72. Munir S, Thierry E, Malet I, Subra F, Calvez V, Marcelin AG, et al. G118R and F121Y mutations identified in patients failing raltegravir treatmentconfer dolutegravir resistance. J Antimicrob Chemother. 2015;70(3):739-49. 73. Quashie PK, Mesplède T, Han YS, Oliveira M, Singhroy DN, Fujiwara T, et al. Characterization of the R263K mutation in HIV-1 integrase that confers low-level resistance to the second-generation integrase strand transfer inhibitor dolutegravir. J Virol. 2012;86(5):2696-705 74. Heger E, Theis AA, Remmel K, Walter H, Pironti A, Knops E, et al. Development of a phenotypic susceptibility assay for HIV-1 integrase inhibitors. J Virol Methods. 2016;238:29-37. 75. Harrigan PR, Montaner JS, Wegener SA, Verbiest W, Miller V, Wood R, et al. World-wide variation in HIV-1 phenotypic susceptibility in untreated individuals: biologically relevant values for resistance testing. AIDS. 2001;15:1671–1677. 62 76. Perno CF, Bertoli A. Clinical cut-offs in the interpretation of phenotypic resistance. In: Geretti AM, editor. Antiretroviral Resistance in Clinical Practice. London: Mediscript. 2006; Chapter 7. Available from: https://www.ncbi.nlm.nih.gov/books/NBK2254/ 77. Pattery T, Verlinden Y, De Wolf H, Nauwelaers D, Van Baelen K, Van Houtte M, et al. Development and Performance of Conventional HIV-1 Phenotyping (Antivirogram®) and Genotype-Based Calculated Phenotyping Assay (virco®TYPE HIV-1) on Protease and Reverse Transcriptase Genes to Evaluate Drug Resistance. Intervirology 2012;55:138-146. 78. Beerenwinkel N, Däumer M, Oette M, Korn K, Hoffmann D, Kaiser R, et al. Geno2pheno: Estimating phenotypic drug resistance from HIV-1 genotypes. Nucleic Acids Res. 2003;31(13):3850-5. 79. Petropoulos CJ, Parkin NT, Limoli KL, Lie YS, Huang W, Tian H, et al. A novel phenotypic drug susceptibility assay for human immunodeficiency virus type 1. Antimicrob Agents Chemother. 2000;44(4):920–928. 80. Zhang J, Rhee SY, Taylor J, Shafer RW. Comparison of the precision and sensitivity of the Antivirogram and PhenoSense HIV drug susceptibility assays. J Acquir Immune Defic Syndr. 2005;38(4):439–444. 81. Wang K, Samudrala R, Mittler J. Weak agreement between Antivirogram and Phenosense assays in predicting reduced susceptibility to antiretroviral drugs. J Clin Microbiol. 2004;42(5):2353–2354. 82. Qari SH, Respess R, Weinstock H, Beltrami EM, Hertogs K, Larder BA, et al. Comparative analysis of two commercial phenotypic assays for drug susceptibility testing of human immunodeficiency virus type 1. J Clin Microbiol. 2002;40(1):31–35. 63 83. Gallant J, Lazzarin A, Mills A, Orkin C, Podzamczer D, Tebas P, et al. Bictegravir, emtricitabine, and tenofovir alafenamide versus dolutegravir, abacavir, and lamivudine for initial treatment of HIV-1 infection (GS-US-380-1489): a double-blind, multicentre, phase 3, randomised controlled non-inferiority trial. The Lancet 2017;390(10107):2063 - 2072. 84. Yoshinaga T, Kobayashi M, Seki T, Miki S, Wakasa-Morimoto C, Suyama-Kagitani A, et al. . Antiviral Characteristics of GSK1265744, an HIV Integrase Inhibitor Dosed Orally or by Long-Acting Injection. Antimicrobial Agents and Chemotherapy. 2015;59(1):397-406. 85. Brockman MA, Chopera DR, Olvera A, Brumme CJ, Sela J, Markle TJ, et al. Uncommon Pathways of Immune Escape Attenuate HIV-1 Integrase Replication Capacity. Journal of Virology. 2012;86(12):6913-6923. 86. Stanford University HIV Drug Resistance Database. INSTI resistance notes. Available at: https://hivdb.stanford.edu/dr-summary/resistance-notes/INSTI/ Accessed: January 12, 2018. 87. Lee GQ, Swenson LC, Poon AF, Martin JN, Hatano H, Deeks SG, et al. Prolonged and Substantial Discordance in Prevalence of Raltegravir-Resistant HIV-1 in Plasma versus PBMC Samples Revealed by 454 “Deep” Sequencing. PLoS ONE. 2012;7(9):e46181. 88. Fransen S, Gupta S, Frantzell A, Petropoulos CJ, Huang W. Substitutions at Amino Acid Positions 143, 148, and 155 of HIV-1 Integrase Define Distinct Genetic Barriers to Raltegravir Resistance In Vivo. Journal of Virology. 2012;86(13):7249-7255. 89. Malet I, Delelis O, Valantin MA, Montes B, Soulie C, Wirden M, et al. Mutations Associated with Failure of Raltegravir Treatment Affect Integrase Sensitivity to the Inhibitor In Vitro. Antimicrobial Agents and Chemotherapy. 2008;52(4):1351-1358. 64 90. Hachiya A, Kirby KA, Ido Y, Shigemi U, Matsuda M, Okazaki R, et al. . Impact of HIV-1 Integrase L74F and V75I Mutations in a Clinical Isolate on Resistance to Second-Generation Integrase Strand Transfer Inhibitors. Antimicrob. Agents Chemother. 2017;61(8): e00315-17 91. Xue W, Jin X, Ning L, Wang M, Liu H, Yao X. Exploring the Molecular Mechanism of Cross-Resistance to HIV-1 Integrase Strand Transfer Inhibitors by Molecular Dynamics Simulation and Residue Interaction Network Analysis. Journal of Chemical Information and Modeling. 2013;53(1): 210-222. 92. Granich R, Gupta S, Hersh B, Williams B, Montaner J, Young B et al. Trends in AIDS Deaths, New Infections and ART Coverage in the Top 30 Countries with the Highest AIDS Mortality Burden; 1990-2013. PloS one. 2015;10(7): e0131353. 93. Oliveira M, Ibanescu RI, Anstett K, Mésplède T, Routy JP, Robbins MA, et al. Selective resistance profiles emerging in patient-derived clinical isolates with cabotegravir, bictegravir, dolutegravir, and elvitegravir. Retrovirology. 2018;15(1): 56. 94. Kamelian K, Lepik KJ, Chau W, Yip B, Zhang WW, Lima VD, et al. Prevalence of Human Immunodeficiency Virus-1 Integrase Strand Transfer Inhibitor Resistance in British Columbia, Canada between 2009 and 2016: A longitudinal analysis. Open Forum Infect Dis. 2019;6(3):ofz060. 95. .Lepik KJ, Harrigan PR, Yip B, Wang L, Robbins MA, Zhang WW, et al. Emergent drug resistance with integrase strand transfer inhibitor-based regimens. AIDS. 2017; 31:1425–34. 96. Saladini F, Boccuto A, Dragoni F, Appendino A, Albanesi E, Vicenti I, Zazzi M, in vitro activity of DTG/BIC/E/CAB on first-generation INSTI-resistant HIV-1, in Conference of Retroviruses and Opportunistic infections (CROI). 2019, CROI: Seattle, USA. 65 97. 20. Orkin C, Hernández-Mora MG, Pokrovsky V, Overton ET, Girard P, Oka S, et al. Long-acting cabotegravir + rilpivirine for hiv maintenance: FLAIR week 48 results in Conference on Opportunistic infections and Retroviruses (CROI). 2019, CROI: Seattle, Washington. 98. 21. Swindells S, Richmond GJ, Rizzardini G, Baumgarten A, Del Mar Masia M, Latiff G, et al. Long-acting cabotegravir + rilpivirine as maintenance therapy: ATLAS week 48 results in Conference of Retroviruses and Opportunistic infections (CROI). 2019, CROI: Seattle, Washington. 99. Stanford University HIV Drug Resistance Database. INI Mutation Pattern & Susceptibility. Available at: https://hivdb.stanford.edu/pages/phenoSummary/Pheno.INI.Simple.html Accessed: March 29, 2019. 66 Appendices Appendix I. Amino acid sequence of 12 recombinant viruses at 27 amino acid positions of interest. Amino acids at 27 amino acid positions of interest and median fold-change (FC) of 12 recombinant viruses for raltegravir (RAL), elvitegravir (EVG), dolutegravir (DTG), cabotegravir (CAB) and bictegravir (BIC). The FC values are summarized for each virus using data from one or more individual experiments. Virus 1 2 3 4 5 6 7 8 9 10 11 12 Subtype B B B B B B B B B B B C Integrase amino acid positions H51 . . . . . . . . . . . . T66 . . . . . . . . . . . . L68 . . . . . . . . . . . . L74 . . . . . . . M M M . . V79 . . . . . . . . . . . . E92 . . . . . . . . . . . . Q95 . . . . . . . . . . . . T97 . . . . . . . A A A A A H114 . . . . . . . . . . . . G118 . . . . . . . . . . . . F121 . . . . . . . . . . . . A128 . . . . . . . . . . . . E138 . . . . . . . . . . . . G140 S S S S S S S S S S S S Y143 . . . . . . . . . . . . P145 . . . . . . . . . . . . Q146 . . . . . . . . . . . . S147 . . . . . . . . . . . . Q148 H H H H H H H H H H H H V151 . . . . . . . . . . . . S153 . . . . . . . . . . . . N155 . . . . . . . . . . . . E157 . . . . . . . . . . . . G163 . . . . . . . . . . . . S230 . . . . . . . . . . . . D232 . . . . . . . . . . . . 67 Virus 1 2 3 4 5 6 7 8 9 10 11 12 Subtype B B B B B B B B B B B C R263 . . . . . . . . . . . . Median FC RAL >100 >50 >50 >100 NA >100 >100 NA >100 >100 >100 >100 EVG >100 >100 >100 >100 NA >100 >100 NA >100 >100 >100 >100 DTG 8.2 5.6 2.6 1.9 3.1 3.0 2.7 345 263 515 23 33 CAB 4.8 3.7 2.3 3.3 1.8 5.8 3.8 249 866 586 30 117 BIC 3.0 2.5 3.1 2.5 1.6 3.2 2.1 55 67 88 5.6 12 68 Appendix II. Permutations of 27 amino acids in integrase observed in clinical samples. 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Clinical samples (number) 8514 . . . . . . . . . . . . . . . . . . . . . . . . . . . 768 . . . . . . . . . . . . . . . . . . . . . . . . N . . 429 . . . . . . . . . . . . . . . . . . . . . . . E . . . 332 . . . . . . . . . . . . . . . . . . . I . . . . . . . 321 . . . I . . . . . . . . . . . . . . . . . . . . . . . 275 . . . . . . . . . . . . . . . . . . . . . . . . . E . 119 . . . . . . . . . . . . . . . . . . . . . . Q . . . . 91 . . . . . . . A . . . . . . . . . . . . . . . . . . . 63 . . . . . . . . . . . . . . . . . . . . . . . . N E . 52 . . . . . . . . . . . . . . . . . . . . . . . E N . . 47 . . . I . . . . . . . . . . . . . . . . . . . E . . . 40 . . . . . . . . . . . . . . . . . . . . . . . A . . . 38 . . . . . . . . . . . . . . . . . . . . . . . T . . . 34 . . . . . . . . . . . . . . . . . . . . . H . . . . . 30 . . . . . . . . . . . . Q . . . . . . . . . . . . . . 29 . . . M . . . . . . . . . . . . . . . . . . . . . . . 29 . . . . . . . . . . . . D . . . . . . . . . . . . . . 28 . . . . . Q . . . . . . . . . . . . . . . . . . . . . 25 . . . . . . H . . . . . . . . . . . . . . . . . . . . 25 . . . . . . . . . . . . . S . . . . H . . . . . . . . 23 . . . . . . . . . . . . . . . . . . . . . . . Q . . . 22 . . . . . . . . . . . . . . . . . . . I . H . . . N . 22 . . . . . . . . . . . . . . . . . . . . . . . V . . . 19 . . . V . . . . . . . . . . . . . . . . . . . . . . . 19 . . . I . . . A . . . . . . . . . . . . . . . . . . . 19 . . . V . . . . . . . . . . . . . . . . . . . E . . . 18 . . . . . . . . . . . . . . . . . . . . . . . . G . . 17 . . . . . . . . . . . . . . . . . . . . A . . . . . . 17 . . . . . . P . . . . . . . . . . . . . . . . . . . . 16 . . . . I . . . . . . . . . . . . . . . . . . . . . . 16 . . . . I . . . . . . . K . . . . G R . . . . E . . . 15 . . M . . . . . . . . . . . . . . . . . . . . . . . . 69 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Clinical samples (number) 15 . . . . . . . . . . . . K . . . . . R . . . . . . . . 15 . . V . . . . . . . . . . . . . . . . . . . . . . . . 15 . . . . . . . . . . . . . . . . . . . . . . . N . . . 14 . . . . . . . . . . . . . . . . . . . I . . . . . E . 13 . . . I . . . . . . . . . . . . . . . . . . . . N . . 10 . . . . . . . . . . . T . . . . . . . . . . . . . . . 10 . . . I . . . . . . . . . . . . . . . . . . Q . . . . 9 . . . . A . . . . . . . . . . . . . . . . . . . . . . 9 . . . . . . S . . . . . . . . . . . . . . . . . . . . 8 . . . . . . . . . . . . K . . . . . . . . . . . . . . 8 . . . . . . A . . . . . . . . . . . . . . . . . . . . 8 . . . . . . . . . . . . . . . . . . . . . . D . . . . 8 . . . . . . . A . . . . . . . . . . . . . H . . . . . 8 . . . . . . . . . . . . . . . . . . . . . . . R . . . 7 . . . . . . . . . . . . . . . . . . . . . . Q . N . . 7 . . . . . . . A . . . . . . R . . . . . . . . . . . . 7 . . . I . . . . . . . . . S . . . . H . . . . . . E . 7 . . . . . . . . . . . . . S . . . . H I . . . . . . . 7 . . . . . . . . . . . . . . . . . . . . . . K . . . . 6 . . . . . . . . . . . . . . . . . . . . . . . D . . . 6 . A . . . . . . . . . . . . . . . . . . . . . . N . . 6 . . . I . . . . . . . . . . . . . . . . . . . . . E . 6 . . . . . . . A . . . . . . . . . . . . . . . . . E . 6 . . . . . . . S . . . . . . . . . . . . . . . . . . . 6 . . . . . . . . . . . . . . . . . . . . . . . E . E . 5 . . I . . . . . . . . . . . . . . . . . . . . . . . . 5 . . . . . . . . . . . . . . . . . . . . . . . . . N . 5 . . . . . . . A . . . . . S . . . . H . . . . . . . . 5 . . . . . . . . . . . . . . . . . . . . . H . . R . . 5 . . . . . Q . . . . . . . . . . . . . . . . . E . . . 5 . . . . . . . . . . . . . . . . . . . . . . . M . . . 5 . . . M . . . A . . . . . . . . . . . . . . . . . . . 5 . . S . . . . . . . . . . . . . . . . . . . . . . . . 5 . . . . . . . . . . . . . . . . . G . . . . . . . . . 70 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Clinical samples (number) 4 . . . . . Q . A . . . . . . . . . . . . . . . . . . . 4 . . . . . Q . . . . . . . . . . . . . . . H . . . . . 4 . . . . . . T . . . . . . . . . . . . . . . . . . . . 4 . . . . . . K . . . . . . . . . . . . . . . . E . . . 4 . . . . I . . . . . . . . A . . . . R . . . . . . . . 4 . . . . . . . A . . . . . . . . . . . . . . Q . . . . 4 . . . . . . K . . . . . . . . . . . . . . . . . . . . 4 . . . . . . . . . . . . . . . . . . . . . . . Q N . . 4 . . . . . . . . . . . T . . . . . . . . . . . E . . . 4 . . . . . . . . . . . . . . . . . . . I . H . . . . . 3 . I . . . . . . . R . . . . . . . . . . . . Q . . . . 3 . . . . . . P . . . . . . . . . . . . . . . . E . . . 3 . S . . . . . . . . . . . . . . . . . . . . . . . . . 3 . . T . . . . . . . . . . . . . . . . . . . . . . . . 3 . . . . . . . . . . . . . S . . . . H . . . . . N . . 3 . . . . . . . . . . . . . . . . . . . . . . . . . . K 3 . . . . . . . . . . . . . S . . . . R . . . . . . . . 3 . . . . . . . . . . . . . . . . . . . . . . . K . . . 3 . . . . . . . A . . . . . . C . . . . . . . . . R . . 3 . . . I . . . . . . . . . . . . . . . . . . . Q . . . 3 . . . . . . . A . . . . . . . . . . . . . . . . N E . 3 . . . . . . . A . . . . . . . . . . . . . . . E . . . 3 . . . M . . . . . . Y . . . . . . . . I . . . R . N . 3 . . . . . . . . . . . . . . R . . . . . . . . . . . . 3 . . . . A . . . . . . . . . . . . . . . . . Q . . . . 3 . . . M . . . A . . . . . S . . . . H . . . . . . . . 3 . . . . . . . . . . . . K C . . . . K . . . . . . . . 3 . . . . . . . A . . . . . . . . . . . I . H . . . . . 3 . . . . . . . . . . . . . . . . . . . . . . . R N . . 3 . . . . . Q . . . . . . . . . . . . . . . . Q . . . . 3 . . . M . . . . . . . . . . . . . . . . . . . E . . . 2 . . . . . . . . . . . . . . . . . . . . . . Q . . E . 2 . . . . I . . . . . . . K A . . . . R . . . . . . . . 2 . . . . . . . . . . . . . . . . . . . . . . . H . E . 71 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Clinical samples (number) 2 . . . . . . . . . . . . . . . . . . . . . . . S . . . 2 . . . . . . H . . . . . . . . . . . . . . . . Q . . . 2 . . . . . . . . . . . . . . . . . . . . . . . . R . . 2 . . . M . L . A . . . . . . . . . . . . . . . . . . . 2 . . . I . . . . . . . . . . . . . . . I . . . . . . . 2 . . . . . . . . . . . . . . . . . . R . . . . . N . . 2 . . . . . . . A . . . . D . . . . . . . . . . . . . . 2 . . . . . . . . . . . . . . . . . . . . . H . . N . . 2 . . . . . . . . . . . . . . . . . . . I . H . R . . . 2 . . . . . . . . . . . . . . . . . . . . . . . T N . . 2 . . . . . . . . . . . . . . . . . . . . . . . A N . . 2 . . . . . . . . . . . . . . . . . . . . . . . V N . . 2 Q . . . . . . . . . . . . . . . . . . . . . . . . . . 2 . . . . A . . . . . . . . . . . . . . . . . . E . . . 2 . . . . . . . . . . . . . . . . . . . I . . . . N . . 2 . . . . . . . . . . . . T . . . . . . . . . . . . . . 2 . . E . . . . . . . . . . . . . . . . . . . . . . . . 2 . . . . . . . . . . . . . A . . . . R . . . . . . . . 2 . . F . . . . . . . . . . . . . . . . . . . . . . . . 2 . . . . . . . . . . . . . . . . . . . . . H Q . . . . 2 . . . I . . . . . . . . . . . . . . . . . . . . N E . 2 . . . . . . H . . . . . . . . . . . . . . . . E . . . 2 . I . . . . . A . . . . . . . . . . . . . . . . . N . 2 . . . . . . . . . . . . . . . . H . . . . . . . . . . 2 . . . I . . . . . . . . . . . . . . . . A . . . . . . 2 . . . I . . . A . . . . . . G . . . . . . . . . . . . 2 . . . I . . . . . . . . . . . . . . . . . H . . . . . 2 . . C . . . . . . . . . . . . . . . . . . . . . . . . 2 . . . . . . K . . . . . . . . . . . . I . H . . . . . 2 . . . . . . . . . . . . . . . . . . . I . H . . . E . 2 . . . . . . . . . . . . D . . . . . . . . . Q . . . . 2 . . . . . . . . . . . . . . . . . . . . . . Q A . . . 2 . . V . . Q . . . . . . . . . . . . . . . . . . . . . 2 . . . . . . . . . . . . . . . . . . R . . . . . . . . 72 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Clinical samples (number) 1 . . . M . . . . . . . . . . . . . . . . . . . E N . . 1 . . . I . . . . . . . . K . . . . G R . . . . E . . . 1 . . . . . . . . . . . . . . . . . . . I . . . E N . . 1 . . . . . . . . . . . . K . . . . . . . . . . . N . . 1 P . . I . . . . . . . . . . . . . . . . . . . . . . . 1 Y . . . . . . . . . . . . . . . . . . . . . . . . . . 1 . . . . . . H . . . . . . . . . . . . . . . . . . E . 1 . . . . . . E . . . . . . . . . . . . . . . K . . . . 1 . . . M . . . A . . . . . . . . . . . . . . . R . . . 1 . . . . . . . . . . . . . . . . . . . . . . K E . . . 1 . . . . . . . A . . . . . . . . . . . . . . . A . . . 1 . . . M . . . . . . . . . . . . . . . . . . . . N . . 1 . . . . . Q . A . . . . D . . . . . . . . . . . . . . 1 . . . . . . P . . . . . . . . . . . . . . . Q . . . . 1 . . . . . Q . . . . . . . . . . . . . . . . Q T . . . 1 . . . . . . . . . . . . . . . . . . . . . . K . N . . 1 . . . . . . . A . . . . . . . . . . . . . H . . . N . 1 . A . I I . . . . . . . K . . . . G R . . . . . . . . 1 . . . . . . . . . . . . . . . . . . . I . H Q T . . . 1 . . . . . . . A . . . . . . . . . . . . . . . V . E . 1 . . . . . . . . . . . . . . . . . . . I . H Q K . . . 1 . . Y . . . . . . . . . . . . . . . . . . . . . . . . 1 . I . . . . . . . R . . . . . . . . . . . . . . . . . 1 . . . . . . . . . . . . D . . . . . . . . . . V . . . 1 . . . . . . . I . . . . . . . . . . . . . . . . . E . 1 . . . M . . . . . . . . . . . . . . . . . . . . . E . 1 . . . . . . . . . . . . . . . . . . . . . H . . . N . 1 . . . . . . . . Q . . . . . . . . . . . . . . . . . . 1 . . . . . . . . . . . . . . . . . . . . . . . E G . . 1 . K . . . . . . . . . . . . . . . . . . . . . . . . . 1 . . . . . . . . . . C . . . . . . . . . . . . . . . . 1 . . . . . . . . . . . . . . . . . . . . . . D . N . . 1 . . . . . . . . . . . . . A . . . . R . . . . A . . . 1 . . . I . . . A . . . . . . . . . . . . . . . E . . . 73 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Clinical samples (number) 1 . . . . . . . . . . . . . . . . . . . . A . . E . . . 1 . . . . . . . . . . . . . R . . . . . . . . . . . . . 1 . I . . . . . . . . . . . . . . . . . . . . . A . . . 1 . . I . . . . . . . . . . . . . . . . . . . . E . . . 1 . . . . . . . . . . . . . . . . . . . . . . . E . N . 1 . . . . . A . A . . . . . . . . . . . . . . . . . . . 1 . . . I . . . A . . . . . . R . . . . . . . . . . . . 1 R . . . . . . . . . . . . . . . . . . . . . . . . . . 1 . . . . . . . . . . . . . . . S . . . . . . . . . . . 1 . . . M . . . . . . . . . . . . R . . . . . . . . . . 1 . . M . . . . . . . . . . . . . . . . . . . Q . . . . 1 . . . I . A . A . . . . . . . . . . . . . . . . . . . 1 . . . . . . P . . . . . . . . . . . . . . . . . N . . 1 . . . M . . . S . . . . . . . . . . . . . . . . . . . 1 . . . M . . . . . . . . . . C . . . . . . . . R R . . 1 . . . M . . . A . . . . . . R . . . . . . . . . . . . 1 . . . . . . . . . . . . . . . . . . . . . . . . . . G 1 . . . . . . . A . . . . . . . . . G . . . H . . . . . 1 . . Y . . . . A . . . . . . . . . . . I . H Q . . . . 1 . . . . . . . . . . . . . . . . . . . . . H . . . E . 1 . . . I . . . . . . . . . . . . . . . . . . . R . . . 1 . . . I . . P . . . . . . . . . . . . . . . . . . . . 1 . I . . . . . . . . . . . . . . . . . . . . . . . . . 1 . . . . . . S . . . . . . . . . . . . . . . . S . . . 1 . . . . . . . . . . . . . . . . . . . . . . Q T . . . 1 . A . . . . . . . . . . K . . . . G R . . . . . . . . 1 . . S I . . . . . . . . . . . . . . . . . . . E . . . 1 . . . I . . . . . . . . . . . . . . . . . . . D . . . 1 . . . . . . . . . . . . . C . . . . R . . . . . N . . 1 . . . I . . . . . . . . . . . . . . . . . . . A N . . 1 . . . . . . R . . . . . . . . . . . . . . H . . . . . 1 . . V . . Q . . . . . . . . . . . . . . A . . . . . . 1 . . . M . . . . . . . . . . . . . . . . . H . . . . . 1 . . . . . . . . . . . . . . . . . . . . . . Q . G . . 74 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Clinical samples (number) 1 . . . . . . . . . . . . . . . . . . . I . . Q . . . . 1 . A . . . . . . . . . . . . . . . . . . . . . . . . . 1 . . . . . . . . . . . . . . . . . . . . . . . . . Y . 1 . . . I . . . A . . . . . . . . . . . I . . . . . . . 1 . . . V . . . A . . . . . . R . . . . . . . . . . . . 1 . . . Q . . . . . . . . . . . . . G . I . H Q . . . . 1 . I . . . . - - . . . . . . . . . . . . . . . A . . . 1 . . . I I . . . . . . . . A . . . . R I . . Q . . . . 1 . . . . . . . . . . . . . . . . . . . I . . . V . . . 1 . . . . . . . . . . . . . S . . . . H . . . . . . E . 1 . . . . . . . . . . . . . S . . . . K . . . . . . . . 1 . . . I . . . . . . . . . . . . . . . . . . . E N . . 1 . . . . . . . . . . . . D . . . . . . . . . . T . . . 1 . . . . . . . A . . . . T . . . . . . . . . . . . . . 1 . . . . . . H . . . . . . . . . . . . . . . . E N . . 1 . . I M . . . A . . . . . . G . . . . . . . . . N . . 1 . . . I . . . A . . . . . . C . . . . . . . . . . . . 1 . . . . . . . . . . . D . . . . . . . . . . . . . . . 1 . . . . . . . . . . . . . S . . . . R . . . . . N . . 1 . . . I . . . M . . C . . . . . . . . I . . Q K . . . 1 . . . . . . . . . . . . . . . . . . . . . . Q R . . . 1 . . . . . . . . . . . . . . C . . . . . . . . R K . . 1 . . . . . . . . . . . . . . . . . . . . . . Q E . . . 1 . I . . . . . . . . . . . . . . . G . . . . . K N . . 1 . . V . . Q . . . . . . . . . . . . . . . . Q . . . . 1 . . I . . . . . . . . . . . . . . . . . . . . . . E . 1 . . . . . . . . . . . . . . . . . . . . . . K . . E . 1 . . A . . . K . . . . . . . . . . . . . . . . T . E . 1 . . . . . . . . . . . . . . . . . . . . C . . E . . . 1 . . . V . . . . . . . . . . . . . . . . . . . . N E . 1 . . . . . . . . . . . . . . . . . . . . . . . E . . K 1 . . . . . . . . . . . . . . . . . . . . . . . Q . E . 1 . . . . . . . . . . . . . . . . . . . . . . . D . E . 1 . . I M . . . A . . . . . . . . . . . . . . Q . . . . 75 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Clinical samples (number) 1 Y . . . . Q . . . . . . . . . . . . . . . . . . . . . 1 . . . . . . . . . . . . . . . . . . . A . . . E . . . 1 . . . . . . . . . . . V . . . . . . . . . . . . . . . 1 . . . . . . . . . . . . . . . . . G R . . . . . N . . 1 . . . . . . . . . . . . . . . . . . . . . H . V . . . 1 . . . . . . . . . . . . . . . . . . . . . . . R . E . 1 . . V M . Q . A . . . . . . . . . . . . . . . . . . . 1 . . . . . . . . . . . . . . . . . . . . . . . K N . . 1 . . . . . A . . . . . . . . . . . . . . . H . . . . . 1 . . I . . Q . . . . . . . . . . . . . . . . Q . . . . 1 . . . . . . . M . . C . . . . . . . . I . . Q K . . . 1 . . . M . Q . A . . . . . . . . . . . . . . . . . . . 1 . . . . . . . . . . . . . S . . . . H . . . . R . . . 1 . . . . . . . . . . . . . . . . . . . I . . . . G . . 1 . . . . . . . . . . . . K . . . . . . . . . . D . . . 1 . . . . . . . . . . . . D S . . . . H . . . . . . . . 1 . . . . . G . . . . . . . . . . . . . . . . Q . N . . 1 . . . . . . . A . . . . . . . . . . . . . . . . N . . 1 . . . . . . H . . . . . . . . . . . . I . . . . . . . 1 . I . . . . . . . . . . . . . . . . . . . . . . . E . 1 . . . M . . . A . . . . . . R . . . . . . H . . . . . 1 . . . . . . . . . . . . . . . . . . . . . S . . . N . 1 . . . . . . . . . . . . . . . . . . . I . . . M . . . 1 . . . . . . . . . . . . . . . . . . . . . H . E . N . 1 . A . . . A . . . . . . . . . . . . . . . . . . . . . 1 . . . . . . . . . . . . . . . . . . . . . . . D N . . 1 . . . . . . . . . . . T . . . . . . . . . H . . . . . 1 . . . . . . . . . . . . . . . . . . . . . . . V . E . 1 . . . . . . . . . . . . . . . . L . . . . . . . . . . 1 . . . . . . . . . . . . . A . . . . R . . . Q . . . . 1 . . . I . . . . . . . . . . . . . . . . . . . N . . . 1 . . . . . G . . . . . . . . . . . . . . . H . . . . . 1 . . . . . . . . . . . . . . C . . . . . . . . . N . . 1 . . . . I . . . . . . . . . . . . . . . . . . . N . . 76 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Clinical samples (number) 1 . . . I . . . A . . . . . . . . . . . . . . . D . . . 1 . . . I . . . . . . . . . . . . . . . . . . . T . . . 1 . . . . . . K A . . . . . . C . . . . . . . . . . N . 1 . . V . . . . . . . . . . . . . . . . . . . G . . . . 1 . K . I . . . . . . . . . . . . . . . . . . . E . . . 1 . . . . . . . . . . . V . . . . . . . . . . . . N E . 1 . . . . . . . . . . . . Q A . . . . . . . . . . . . . 1 . . . I . . . . . . . . . . . . . . . . . . . A . . . 1 . . . . . . . . . . . . . S . . . . R . . . . . . N . 1 . . . . . . . . . . . . . . . . . . . . . . . K G . . 1 . . . M . . . . . . . . . . . . . . . . . . . . K . . 1 . . . M . . . A . . . . . . . . . . . . . . Q . . . . 1 . . . . . . . . . . . . . . . . . . . . . H . E . . . 1 . . . . . . E . . . . . . . . . . . . . . . . . . . . 1 . . . I . . . . . . . . . . . . . . . I . . . . N . . 1 . . . . I . . . . . . . K . . . . G R . . . . E N . . 1 . . . . . . . . . . . . . . . . . . . . . H . A N . . 1 . I . . . . . A . . . . . . . . . . . . . . . . . . . 77 Appendix III. Amino acid sequences at 27 positions of interest of the panel of 162 recombinant viruses. 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Virus ID 1 . . . . . . . . . . . . . . . . . . . . . . . . N . . 2 . . . . . . . . . . . . . . . . . . . . . . . T . . . 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 . . . . . . . . . . . . . . . . . . . . . . . . N . . 5 . . . . . . . . . . . . . . . . . . . I . . . . . . . 6 . . . . . . . . . . . . . . . . . . . . . . . H . E . 7 . . . . . . . A . . . . . S . . . . H . . . . . . . . 8 . . . M . L . A . . . . . . . . . . . . . . . . . . . 9 . . . . . . . . . . . . . S . . . . R . . . . . N . . 10 . . . M . Q . A . . . . . . . . . . . . . . . . . . . 11 . . . . . . . . . . . . . S . . . . H . . . . . . . . 12 . . . . . . . . . . . . . . . . . . . . . . . S . . . 13 . . . . . . . . . . . . . S . . . . R . . . . . . . . 14 . . . . . . . . . . . . . . . . . . . . . . Q . . . . 15 . . T . . . . . . . . . . . . . . . . . . . . . . . . 16 . . M . . . . . . . . . . . . . . . . . . . Q . . . . 17 . . M . . . . . . . . . . . . . . . . A . . Q . . . . 18 . . . . . . . . . . . . . S . . . . H . . . . . . . . 19 . . Y . . . . . . . . . . . . . . . . . . . . . . . . 20 . . . . . . . . . . . . . . . . . . . . . . Q T . . . 21 . . . . . . . . . . . . . . . . . . . . . . . E G . . 22 . . . I . . . M . . C . . . . . . . . I . . Q K . . . 23 . . . . . . . . . . . . . . R . . . . . . . . R . . . 24 . . . . . . . . . . . . . S . . . . H . . . . . . . . 25 . . . M . . . . . . . . . . C . . . . . . . . R R . . 26 . . . . . . . . . . . . . . . . . . . . . . . R . E . 27 . A . . . . . . . . . . . . . . . . . . . . . . . . . 28 . . . . . . . . . . . . A S . . . . H . . . . . . . . 29 . . . . . . . . . . . . . S . . . . H . . . . . . . . 30 . . . . I . . . . . . . K . . . . G R . . . . E . . . 78 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Virus ID 31 . . . . I Q . . . . . . . . . . . . . . . H . . . . . 32 . . . . . . . . . . . . . S . . . . R . . . . . . . . 33 . . . . . . . . . . . . K . . . . . R . . . . . . . . 34 . . . . . . . . . . . . K . . . . . R . . . . . . . . 35 . . . . . . . A . . . . . . R . . . . . . . . . . . . 36 . . . . . . . . . . . . . . . . . . . I . H . . . N . 37 . . . . . Q . . . . . . . . . . . . . . . H . . . . . 38 . . . M . Q . A . . . . . . . . . . . . . . . . . . . 39 . . . . . Q . A . . . . . . . . . . . . . . . . . . . 40 . . . . I . . . . . . . K A . . . . R . . . . . . . . 41 . . . . . . . . . . . . . . . . . . . . . . . A . . . 42 . . . . . . . . . . . . . . . . . . . . . . . H . E . 43 . . . M . . . . . . . . . . . . . . . . . . . . K . . 44 . . . I . . . . . . . . . . . . . . . I . H . R . . . 45 . . T . . . . . . . . . . . . . . . . . . . . . . . . 46 . . M . . . . . . . . . . . . . . . . . . . . . . . . 47 . . . . . . . A . . . . . . . . . . . . . . D . . . . 48 . . . I . . . . . . . . . . . . . . . . . . . . N . . 49 . . . . . . . . . . . . . . . . . . . I . H Q T . . . 50 . . . . . . . . . . . . . . . . . . . I . . . . . E . 51 . . . . . . H . . . . . . . . . . . . . . . . E N . . 52 . . . I . . . . . . . . . . . . . . R . . . . . . . . 53 . . . I . . . . . . . . . . . . . . . . . H . . . . . 54 . . . M . . . A . . . . . . . . . . . . . . . R . . . 55 . . . M . . . A . . . . . S . . . . H . . . . . . . . 56 . . . . . . . A . . . . . . . . . . . . . H . . . . . 57 . . . M . L . A . . . . . . . . . . . . . . . . . . . 58 . . . . . . . . . . . . . . . . . . . . . . . E . . . 59 . . . . . . . . . . . . K . . . . G K . . . . V . . . 60 . . . . . . . . L . . . . S . . . . K . . . . V . . . 61 . . . . . . . . . . . . A S . . . . H . . . . E . . . 62 . K . I . . . . . . . . . . . . . . . . . . . E . . . 63 . . . . . . . A . . . . . . R . . . . . . . . . . . . 79 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Virus ID 64 . . . . . . . . . . . . . . R . . . . . . . . . . . . 65 . . . M . . . A . . . . . S . . . . H . . . . . . . . 66 . . . . . . . . . . . . . . . . . . . . . . . E N . . 67 . . . . . . . A . . . . . . . . . . . . . . . E . . . 68 . . C . . . . . . . . . . . . . . . . . . . . . . . . 69 . . . . . . . . . . . . . S . . . . H . . . . . . . . 70 . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 . . A . . . K . . . . . . . . . . . . . . . . T . E . 72 . K . I . . . . . . . . . . . . . . . . . . . . . N . 73 . . . . . . . . . . . . . S . . . . H . . . . . . . . 74 . . . . . . P . . . . . . . . . . . . . . . . . . . . 75 . . I M . . . A . . . . . . . . . . . . . . Q . . . . 76 . . . I . . . . . . . . . . . . . . . . . . . E . . . 77 . . . M . . . . . . . . . . R . . . . . . . . . . . . 78 . . . . . Q . . . . . . . . . . . . . . . H . . . . . 79 . . F . . Q . . . . . . . . . . . . . . . H . . . . . 80 . . . . . . . . . . . T . . . . . . . . . . . E . . . 81 . . . . . . . . . . . T . . . . . . . . . . . E . . . 82 . . . . . . . . . . . . . . . . . . . . A . . . . . . 83 . . . I . . . A . . . . . . . . . . . I . . . . . . . 84 . . Y . . . . A . . . . . . . . . . . I . H Q . . . . 85 . . . I . . . . . . . . . . . . . . . . . . . E N . . 86 . . . . . . . . . . . . . . . . . . . . . H . . . . . 87 . . I . . Q . . . . . . . . . . . . . . . . . . . . . 88 . . . . . . . . . . . . . . . . . . . . . . . E . . K 89 . . . . . . . . . . . . . . . . . . . . . H . E . . . 90 . . . . . . . . . . . . . C . . . . R . . . . . N . . 91 . . . . . . . . . . . . . S . . . . H . . . . R . . . 92 . . . . . . . . . . . . . . . . . . . . . . . . . . K 93 . . . . . . . . . . . . K . . . . G R . . . . E N . . 94 . . . . I . . . . . . . K . . . . G R . . . . E N . . 95 . . . M . . . . . . . . . . . . . . . . . H . . . . . 96 . . . . . . . A . . . . . . . . . . . . . . . . . . . 80 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Virus ID 97 . . . . . . . . . . . . . . . . . . . . . . . . G . . 98 . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 . . . V . . . . . . . . . . . . . . . . . . . E . . . 100 . . . . . Q . . . . . . . . . . . . . . . . Q . . . . 101 . . . . . Q . . . . . . . . . . . . . . A . Q . . . . 102 . . . . . . . . . . . . . . . . . . . . . H . R . . . 103 . . . . . . . . . . . . D . . . . . . . . H . . . . . 104 . . . M . . . A . . . . . S . . . . H . . . . . . . . 105 . . . . . . . . . . . . . . . . . . R . . . . . N . . 106 . . . . . Q . A . . . . . . . . . . . . . . . . . . . 107 . . . . . . . . . . . . . . . . . . . I . H Q K . . . 108 . . . I I . . . . . . . . A . . . . R I . . Q . . . . 109 . . . . . . . . . . . . . . . . . . . . . H . . . . . 110 . . . . . . . . . . . . K . . . . . . . . . . . N . . 111 . . . . . . . A . . . . . . . . . . . . . . . . . . . 112 . . . . . . . . . . . . K . . . . . . . . . . . . . . 113 . . . M . . . A . . . . . . . . . . . . . H . . . . . 114 . . . . . . . . . . . . A S . . . . H . . . . . . . . 115 . . . . . . . . . . . . . S . . . . H . . . . . . . . 116 . . . . . . S . . . . . . . . . . . . . . . . . . . . 117 . . . . . . . . . . . T . . . . . . . . . . . E . . . 118 . . . . . . . . . . . . . . . . . . . . . . Q . . . . 119 Q . . . . . . . . . . . . . . . . . . . . . . . . . . 120 . . . . . . . . . . . . . . . . . . . . . . . S . . . 121 . . . . . . K . . . . . . . . . . . . . . . . E . . . 122 . . V . . . . . . . . . . . . . . . . . . . . . . . . 123 . . . . . . . . . . . . . . . . . . . . . . . A . . . 124 . . . . . . . . . . . . . . . . . . . . . . Q . . . . 125 . . . . . . . . . . . . D . . . . . . . . . . . . . . 126 . . . . . . . . . . . . . . . . . . . . . . . A . . . 127 . . . I . . . . . . . . . . . . . . . . . . . . . . . 128 . . . I . . . . . . . . . . . . . . . . . . . . . . . 129 . . . I . . . . . . . . K . . . . . R . . . . E . . . 81 27 codon positions in HIV-1 Integrase 51 66 68 74 79 92 95 97 114 118 121 128 138 140 143 145 146 147 148 151 153 155 157 163 232 232 263 H T L L V E Q T H G F A E G Y P Q S Q V S N E G S D R Virus ID 130 . . . . . . . A . . . . . . . . . . . . . . . . . . . 131 . . . . . . . A . . . T . . . . . . . . . . . . . . . 132 . . . . . . . . . . . . . . . . . . . . . . Q E . . . 133 . . . I . . . A . . . . . . . . . . . . . . . . . . . 134 . . . . . . . . . . . . . . R . . . . . . . . . . . . 135 . . . . . . . . . . . . . A . . . . R . . . Q . . . . 136 . . . . . . . A . . . . . S . . . . H . . . . . . . . 137 . . . . . . R . . . . . . . . . . . . . . H . . . . . 138 . . . . . . . . . . . . . . . . . . . . . . . K . . . 139 . . . . . . H . . . . . . . . . . . . . . . . . . . . 140 . . . M . . . A . . . . . . R . . . . . . H . . . . . 141 . . . I . . . . . . . . . . . . . . . . . . . E . . . 142 . . . . . . . . . . . . . . . . . . . . . . . V . . . 143 . . . . . . . . . . . . . . . . . . . . . H . . R . . 144 . . V . . . . . . . . . . . . . . . . . . H . . R . . 145 . . . I . . . A . . . . . . G . . . . . . . . . . . . 146 . . . . . . . . . . . . . . . . . . . . A . . E . . . 147 . . . . . . K . . . . . . . . . . . . . . . . . . . . 148 . . . . . . K . . . . . . . . . . . . . . . . E . . . 149 . . I . . . . . . . . . . . . . . . . . . . . . . . . 150 . . . . . . . . . . . . . . . . . . . . . . . Q . . . 151 . . . . . Q . . . . . . . . . . . . . . . . . . . . . 152 . . . . . . T . . . . . . . . . . . . . . . . . . . . 153 . . V . . Q . . . . . . . . . . . . . . . H . . . . . 154 Y . V . . Q . . . . . . . . . . . . . . . H . . . . . 155 Y . V . . Q . . . . . . . . . . . . . . . . . . . . . 156 . . . . . . . . . . . . . . . . . . . . . . . N . . . 157 . . . . . . A . . . . . . . . . . . . . . . . . . . . 158 . I . . . . . . . R . . . . . . . . . . . . . . . . . 159 . . . . . . . A . . . . . . . . . G . . . H . . . . . 160 . . . V . . . A . . . . . . R . . . . . . . . . . . . 161 . . . . . . . A . . . . . . R . . . . . . . . . . . . 162 . . . I . . . A . . . . . . R . . . . . . . . . . . . 82 83 Appendix IV. Phenotypic susceptibility to INSTIs of the panel of recombinant viruses. Virus ID Subtype INSTI mutation pattern Fold Change (FC) BIC CAB DTG RAL EVG 1 B S230N 0.60 0.92 1.12 0.84 1.21 2 B G163T 0.90 0.58 2.55 1.04 1.00 3 B None 1.40 1.19 0.79 0.39 0.82 4 B S230N 0.88 1.00 0.79 0.52 0.82 5 B V151I 1.22 0.77 0.59 0.32 0.39 6 B G163H, D232E 0.70 0.71 0.80 n/a n/a 7 B T97A, G140S, Q148H 5.81 23.91 20.70 380.71 2097.90 8 B L74M, E92L, T97A 0.83 1.58 0.96 n/a n/a 9 B G140S, Q148R, S230N 2.88 6.83 1.94 121.13 202.27 10 B L74M, E92Q, T97A 0.85 2.71 1.11 n/a n/a 11 B G140S, Q148H 1.57 3.20 2.49 39.72 100.00 12 B G163S 1.07 1.23 0.68 0.22 0.58 13 B G140S, Q148R 12.32 19.81 4.98 972.24 3137.31 14 B E157Q 1.28 1.10 0.76 n/a n/a 15 B L68T 0.82 0.54 0.89 n/a n/a 16 B L68M, E157Q 0.79 2.25 1.01 0.64 0.65 17 B L68M, V151A, E157Q 0.81 0.95 0.87 n/a n/a 18 B G140S, Q148H 3.66 6.32 7.63 561.47 3345.22 19 B L68Y 1.16 1.59 1.09 1.35 1.21 20 B E157Q, G163T 1.19 1.69 1.23 1.56 1.79 21 B G163E, S230G 1.28 1.38 1.13 0.85 1.56 22 B L74I, T97M, F121C, V151I, E157Q, G163K 1.20 77.03 2.17 488.40 2256.27 23 B Y143R, G163R 0.60 1.71 1.66 n/a n/a 24 B G140S, Q148H 2.95 7.01 2.34 392.54 2941.18 25 B L74M, Y143C, G163R, S230R 0.68 0.84 0.82 n/a n/a 26 B G163R, D232E 0.86 0.94 1.21 n/a n/a 27 B T66A 0.26 0.31 0.39 0.16 5.35 28 B E138A, G140S, Q148H 1.95 3.88 2.61 120.78 2040.82 29 B G140S, Q148H 3.53 3.51 2.97 146.81 3846.15 30 B V79I, E138K, S147G, Q148R, G163E 0.65 2.14 0.98 n/a n/a 31 B V79I, E92Q, N155H 0.53 1.54 0.94 n/a n/a 32 B G140S, Q148R 4.54 9.00 3.70 183.18 299.88 33 B E138K, Q148R 1.75 4.94 1.39 17.68 431.96 34 B E138K, Q148R 1.01 1.85 0.83 15.82 269.00 35 B T97A, Y143R 0.88 0.98 1.10 190.71 15.00 36 B V151I, N155H, D232N 0.34 1.09 0.51 n/a n/a 37 B E92Q, N155H 1.28 2.90 1.64 n/a n/a 38 B L74M, E92Q, T97A 0.83 2.43 1.16 n/a n/a 39 B E92Q, T97A 0.76 1.43 1.15 n/a n/a 40 B V79I, E138K, G140A, Q148R 13.14 90.45 19.35 n/a n/a 84 Virus ID Subtype INSTI mutation pattern Fold Change (FC) BIC CAB DTG RAL EVG 41 B G163A 1.04 1.04 1.07 n/a n/a 42 B G163H, D232E 0.79 1.31 1.29 n/a n/a 43 B L74M, S230K 1.19 1.61 1.00 n/a n/a 44 B L74I, V151I, N155H, G163R 0.89 1.81 1.00 n/a n/a 45 B L68T 0.69 0.76 0.90 1.08 2.84 46 B L68M 1.16 1.71 1.00 0.57 1.15 47 B T97A, E157D 1.00 1.19 1.26 n/a n/a 48 B L74I, S230N 0.77 1.53 0.92 1.26 1.49 49 B V151I, N155H, E157Q, G163T 2.06 1.96 1.83 14.08 80.85 50 B V151I, D232E 1.07 1.00 0.95 n/a n/a 51 B Q95H, G163E, S230N 0.80 1.18 0.92 1.04 1.06 52 B L74I, Q148R 0.32 1.48 0.29 n/a n/a 53 B L74I, N155H 0.78 1.71 1.11 n/a n/a 54 B L74M, T97A, G163R 0.71 1.00 0.67 n/a n/a 55 B L74M, T97A, G140S, Q148H 59.11 417.38 202.46 380.71 2097.90 56 B T97A, N155H 1.08 1.92 1.85 30.71 114.73 57 B L74M, E92L, T97A 1.04 3.06 1.50 n/a n/a 58 B G163E 1.19 1.19 1.59 2.97 4.64 59 B E138K, S147G, Q148K, G163V 1.77 9.78 2.98 n/a n/a 60 B H114L, G140S, Q148K, G163V 3.21 14.00 2.73 n/a n/a 61 B E138A, G140S, Q148H, G163E 0.74 6.48 0.84 n/a n/a 62 B T66K, L74I, G163E 0.47 1.67 0.85 n/a n/a 63 B T97A, Y143R 1.57 1.60 1.25 88.57 7.68 64 B Y143R 1.61 1.37 1.65 63.59 10.42 65 B L74M, T97A, G140S, Q148H 98.88 493.38 302.37 519.48 2941.18 66 B G163E, S230N 0.65 1.06 0.69 1.10 1.20 67 B T97A, G163E 1.08 1.18 0.69 1.10 2.75 68 B L68C 1.18 1.58 1.08 1.17 1.56 69 B G140S, Q148H 2.22 4.38 3.98 361.66 1620.50 70 B G140S, Q148H 3.06 3.95 2.44 277.99 2040.82 71 B L68A, Q95K, G163T, D232E 0.46 0.69 0.36 n/a n/a 72 B T66K, L74I, D232N 1.64 3.38 1.78 n/a n/a 73 B G140S, Q148H 2.96 6.34 2.88 100.00 2941.18 74 B Q95P 0.92 1.16 1.32 1.11 1.78 75 B L68I, L74M, T97A, E157Q 0.71 1.67 0.50 n/a n/a 76 B L74I, G163E 1.22 1.68 1.48 2.45 2.59 77 B L74M, Y143R 1.30 1.22 1.22 n/a n/a 78 B E92Q, N155H 1.22 3.00 2.34 21.45 138.88 79 B L68F, E92Q, N155H 1.36 3.00 2.34 n/a n/a 85 Virus ID Subtype INSTI mutation pattern Fold Change (FC) BIC CAB DTG RAL EVG 80 B A128T, G163E 0.59 1.53 0.96 0.98 0.88 81 B A128T, G163E 0.65 0.68 0.92 1.06 1.01 82 B S153A 1.02 1.33 1.14 0.81 3.09 83 B L74I, T97A, V151I 0.66 1.07 0.62 17.15 36.35 84 B L68Y, T97A, V151I, N155H, E157Q 1.10 1.75 2.10 131.93 409.40 85 B L74I, G163E, S230N 0.46 0.37 0.36 n/a n/a 86 B N155H 1.53 2.11 1.33 n/a n/a 87 B L68I, E92Q 0.74 1.28 1.07 n/a n/a 88 B G163E, R263K 4.60 3.94 3.49 n/a n/a 89 B N155H, G163E 2.34 100.00 1.09 9.25 21.75 90 B G140C, Q148R, S230N 2.63 8.81 0.96 19.34 1759.36 91 B G140S, Q148H, G163R 1.43 5.01 4.95 361.26 2097.90 92 B R263K 3.20 4.39 3.99 n/a n/a 93 B E138K, S147G, Q148R, G163E, S230N 0.33 0.63 0.40 n/a n/a 94 B V79I, E138K, S147G, Q148R, G163E, S230N 0.64 1.63 1.30 n/a n/a 95 B L74M, N155H 1.28 3.33 0.87 n/a n/a 96 B T97A 0.52 0.87 0.67 1.65 2.79 97 B S230G 1.20 1.13 1.21 0.96 0.68 98 B None 2.18 2.14 2.51 1.73 1.92 99 B L74V, G163E 0.67 0.81 0.83 2.20 4.89 100 B E92Q, E157Q 1.20 1.22 0.93 2.55 25.65 101 B E92Q, S153A, E157Q 1.16 2.50 2.31 n/a n/a 102 B N155H, G163R 1.40 2.31 2.14 n/a n/a 103 B E138D, N155H 1.25 2.16 3.02 27.93 112.29 104 B L74M, T97A, G140S, Q148H 89.60 493.45 258.98 515.46 2010.05 105 B Q148R, S230N 0.77 1.50 0.77 n/a n/a 106 B E92Q, T97A 1.46 1.83 1.24 n/a n/a 107 B V151I, N155H, E157Q, G163K 0.95 1.07 0.74 n/a n/a 108 B L74IV79I, G140A, Q148R, V151I, E157Q 564.75 5377.19 739.79 n/a n/a 109 B N155H 1.30 1.19 1.00 8.24 23.50 110 B E138K, S230N 1.44 1.19 0.87 0.40 0.74 111 B T97A 0.68 1.33 0.68 1.09 5.37 112 B E138K 1.23 1.07 1.00 0.76 0.88 113 B L74M, T97A, N155H 0.81 2.56 0.57 n/a n/a 114 B E138A, G140S, Q148H 2.14 26.09 3.16 n/a n/a 115 B G140S, Q148H 1.10 5.00 1.90 n/a n/a 116 A Q95S 1.26 0.92 0.70 0.13 0.64 117 A A128T, G163E 0.73 0.83 0.87 n/a n/a 118 A E157Q 0.86 0.62 1.66 5.55 3.99 119 C H51Q 0.81 0.89 0.93 n/a n/a 120 C G163S 0.95 0.77 1.26 1.09 1.21 86 Virus ID Subtype INSTI mutation pattern Fold Change (FC) BIC CAB DTG RAL EVG 121 C Q95K, G163E 0.99 0.92 0.98 0.68 2.12 122 F L68V 0.65 0.87 0.70 0.94 1.16 123 G G163A 0.85 1.27 1.13 n/a n/a 124 CRF02_AG E157Q 0.89 0.97 1.09 1.29 1.45 125 C E138D 1.09 1.35 0.98 1.36 1.45 126 G G163A 0.69 0.48 0.64 n/a n/a 127 A L74I 0.87 0.71 0.75 0.92 1.11 128 A L74I 1.02 1.82 0.87 1.12 1.11 129 C L74I, E138K, Q148R, G163E 1.61 15.83 2.20 n/a n/a 130 A T97A 1.61 2.73 1.96 n/a n/a 131 A T97A, A128T 0.68 1.07 0.80 n/a n/a 132 CRF 03_AB E157Q, G163E 0.77 1.32 0.81 1.00 1.69 133 CRF01_AE L74I, T97A 0.70 0.89 0.78 1.37 2.51 134 C Y143R 0.56 0.45 0.99 21.47 1.98 135 CRF02_AG G140A, Q148R, E157Q 1.28 5.06 1.58 8.37 357.12 136 C T97A, G140S, Q148H 15.00 172.78 41.64 990.47 3741.26 137 A Q95R, N155H 1.35 1.44 1.13 n/a n/a 138 G G163K 0.81 1.02 1.01 n/a n/a 139 C Q95H 0.85 2.07 0.64 1.08 1.21 140 C L74M, T97A, Y143R, N155H 1.60 2.62 2.25 1025.64 455.75 141 CRF01_AE L74I, G163E 2.13 2.98 2.45 n/a n/a 142 C G163V 0.95 1.13 0.79 1.04 0.74 143 CRF02_AG N155H, S230R 1.84 2.50 1.44 n/a n/a 144 CRF02_AG L68V, N155H, S230R 1.68 2.38 1.24 n/a n/a 145 C L74I, T97A, Y143G 0.88 0.68 0.99 69.74 5.57 146 C S153A, G163E 1.19 1.87 1.03 1.13 0.90 147 C Q95K 0.95 0.88 0.66 n/a n/a 148 D Q95K, G163E 0.76 1.13 0.50 0.41 0.98 149 CRF01_AE L68I 0.66 0.63 0.58 n/a n/a 150 CRF02_AG G163Q 0.59 0.50 0.58 n/a n/a 151 D E92Q 1.96 2.20 1.83 1.36 7.50 152 CRF01_AE Q95T 1.84 2.34 2.23 n/a n/a 153 C L68V, E92Q, N155H 0.88 1.50 1.51 n/a n/a 154 C H51Y, L68VE92Q, N155H 1.94 4.03 2.11 n/a n/a 155 C H51Y, L68VE92Q 1.03 1.75 1.06 n/a n/a 156 A G163N 0.42 1.46 0.95 n/a n/a 157 A Q95A 0.85 1.41 0.97 n/a n/a 158 C T66I, G118R 6.08 40.34 19.24 n/a n/a 159 C T97A, S147G, N155H 2.28 6.43 6.06 n/a n/a 160 A L74V, T97A, Y143R 0.59 0.78 0.82 n/a n/a 161 A T97A, Y143R 0.66 1.51 0.76 n/a n/a 162 A L74I, T97A, Y143R 0.56 1.07 0.68 n/a n/a 87 Appendix V. Distribution of phenotypic susceptibilities to raltegravir and elivitegravir. Distribution of log fold-changes (FC) in the 50% effective concentrations (EC50) to raltegravir (RAL) and elvitegravir (EVG) of 78 recombinant viruses. 88 Appendix VI. The cumulative percent of variation of clinical samples without mixtures covered by the number of virus variants tested.
Thesis/Dissertation
eng
Experimental Medicine
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Harrigan, Paul Richard
HIV-1 integrase strand transfer inhibitor resistance to dolutegravir, bictegravir and cabotegravir
Text