Curr Infect Dis Rep (2014) 16:401 DOI 10.1007/s11908-014-0401-5

HIV/AIDS (R MACARTHUR, SECTION EDITOR)

Next-Generation Sequencing to Help Monitor Patients Infected with HIV: Ready for Clinical Use? Richard M. Gibson & Christine L. Schmotzer & Miguel E. Quiñones-Mateu

# Springer Science+Business Media New York 2014

Abstract Given the extreme variability of the human immunodeficiency virus (HIV) and its ability to replicate as complex viral populations, HIV variants with reduced susceptibility to antiretroviral drugs or with specific coreceptor tropism (CCR5 and/or CXCR4) may be present as minority members of the viral quasispecies. The sensitivity of current HIV genotypic or phenotypic assays is limited, and thus, these tests usually fail to detect low-abundance viral variants. Next-generation (deep) sequencing (NGS) produces an enormous amount of information that allows the detection of minority HIV variants at levels unimaginable using standard Sanger sequencing. NGS technologies continue to evolve, opening new and more affordable opportunities to implement this methodology in clinical laboratories, and HIV is not an exception. The ample use of a battery of more effective antiretroviral drugs, together with careful patient monitoring based on HIV resistance testing, has resulted in HIV-infected patients whose disease is usually well-controlled. The vast majority of adherent patients without detectable resistance become virologically suppressed; however, a subset of these patients with undetectable resistance by standard methods may fail antiretroviral therapy, perhaps due to the presence of minority HIV-resistant variants. Novel NGSbased HIV assays with increased sensitivity for identifying This article is part of the Topical Collection on HIV/AIDS R. M. Gibson : C. L. Schmotzer : M. E. Quiñones-Mateu University Hospital Translational Laboratory, University Hospitals Case Medical Center, Cleveland, OH, USA C. L. Schmotzer : M. E. Quiñones-Mateu Department of Pathology, Case Western Reserve University, Cleveland, OH, USA M. E. Quiñones-Mateu (*) Department of Pathology, Case Western Reserve University / University Hospitals Case Medical Center, 10900 Euclid Avenue, Cleveland, OH 44106-7288, USA e-mail: [email protected]

low-level drug resistance and/or coreceptor tropism may play an important role in the success of antiretroviral treatments. Keywords Human immunodeficiency virus (HIV) . Next-generation sequencing (NGS) . Drug resistance . Coreceptor tropism . Minority variants

Introduction Immediately following the first identification of human immunodeficiency virus (HIV) strains resistant to AZT, it became clear that patients would need to be monitored for the presence of viruses with reduced drug susceptibility [1]. During the last 25 years, the methodologies used to detect and characterize antiretroviral drug resistance—and later, HIV coreceptor tropism—have evolved considerably, to the point that detecting and quantifying drug resistance has become the standard of care prior to designing new antiretroviral regimens following treatment failure [2–6]. HIV drug resistance or coreceptor tropism can be analyzed using two approaches: (1) sequencing-based methods (genotypic) that detect mutations previously associated with resistance to specific antiretroviral drugs or nucleotide sequences associated with a particular coreceptor tropism or (2) cell-based methodologies (phenotypic) that test the ability of a patient-derived virus to replicate in the presence of antiretroviral drugs or to use a determined coreceptor (e.g., CCR5 and/or CXCR4) to enter susceptible cells [2, 4–6]. As was expected, both genotypic and phenotypic approaches have advantages and disadvantages; however, reduced costs and faster turnaround times have led to the use—almost exclusively—of sequencingbased assays in the clinical setting. Worldwide, current commercial genotypic HIV drug resistance assays are based on Sanger (population) sequencing [7–9], while in Europe genotypic HIV tropism tests are largely used [10, 11]. Nonetheless,

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the sensitivity of genotypic assays based on Sanger sequencing are limited to only detecting minority HIV variants present in 20 % of the viral population [8, 12–15]. Ultrasensitive HIV genotypic assays based on next-generation sequencing allow the detection of these minority variants to levels unthinkable with Sanger sequencing [5, 16]. Next-generation sequencing (NGS), also called “second-generation,” “massive parallel,” or “deep” sequencing, has replaced Sanger sequencing as the primary methodology used in research laboratories to identify and characterize genes in a multitude of organisms [17–19]. Deep sequencing technologies are able to generate three to four orders of magnitude more information than Sanger sequencing and are considerably less expensive (i.e., cost per nucleotide sequenced) [20•, 21]. Several NGS systems have been developed during the last 10 years, all of them with intrinsic characteristics such as number of reads obtained, read length, accuracy, time to run, cost, and so forth [21, 22]. More important, the use of deep-sequencing-based assays continues to expand in clinical laboratory practice [23, 24]. HIV basic and clinical research laboratories are not the exception; thus, numerous studies have used deep sequencing to detect drug-resistant HIV minority variants [25•, 26–33, 34••], to determine HIV coreceptor tropism [16, 34••, 35, 36•, 37, 38, 39•, 40•, 41–47], or to better understand HIV pathogenesis [48, 49]. This review summarizes the different NGS technologies used in HIV studies and addresses the challenges encountered in implementing HIV genotyping and/or HIV coreceptor assays based on deep sequencing in clinical laboratories.

Current HIV Genotypic and Phenotypic Assays As was described above, a multitude of genotypic and phenotypic assays have been developed to determine and quantify HIV drug resistance and HIV coreceptor tropism [2, 4–6, 10, 50]. Many of these in-house assays are used in research settings, while fewer are available in clinical laboratories (Fig. 1). HIV Drug Resistance Original phenotypic drug susceptibility assays used HIV isolates [51] until the arrival of replication-competent recombinant viruses [52–55]. Using clinical HIV isolates was timeconsuming and usually modified the actual proportion of viral variants found in vivo [56]; thus, the use of recombinant viruses carrying patient-derived HIV genomic fragments proved to be a more reliable and faster method for determining HIV susceptibility to antiretroviral drugs [52, 54, 55]. Commercial HIV phenotyping assays include: Antivirogram® (Virco BVBA; discontinued from the routine HIV clinical market) [52], the family of PhenoSense® assays (PhenoSense®, PhenoSense® Integrase, PhenoSense® Entry,

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Fig. 1 Commercially available phenotypic and/or genotypic assays for determining HIV-1 drug resistance and/or HIV-1 coreceptor tropism. The PhenoSense GT (Monogram Biosciences) and VIRALARTS™HIV (University Hospitals Case Medical Center) assays provide drug susceptibility information based on both phenotypic and genotypic data. DEEPGEN™HIV (University Hospitals Case Medical Center) is the only all-inclusive HIV-1 genotyping and coreceptor tropism currently available. HIV assays based on next-generation sequencing are indicated in italics—that is, HIV CCR5 Tropism Test V3 (British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada) [36•], HIV Coreceptor Tropism with Reflex to Ultradeep Sequencing (Quest Diagnostics) [39•], and DEEPGEN™HIV (University Hospitals Case Medical Center) [34••]. Antivirogram® (Virco BVBA) [52], PhenoSense®, PhenoSense® Integrase, PhenoSense® Entry, and PhenoSense® GT (Monogram Biosciences) [54], Phenoscript™ (Eurofins-Viralliance) [57], ViroSeq® (Abbott), TRUGENE® (Siemens Healthcare), HIV Genotype (Quest Diagnostics), GenoSure® MG and GenoSure PRIme® (Monogram Biosciences), vircoTYPE™ HIV (Janssen Diagnostics) [106], Trofile (Monogram Biosciences) [67, 76], Trocai (Hospital Universitario Virgen del Rocio) [107], Toulouse Tropism Test (Universitie Toulouse III PaulSabatier)[68], and VERITROP™ (University Hospitals Case Medical Center) [71]

PhenoSense® GT; Monogram Biosciences) [54], Phenoscript™ (Eurofins-Viralliance) [57], and the allinclusive VIRALARTS™HIV (University Hospitals Case Medical Center) [55] (Fig. 1). Despite longer turn-around time and higher cost, phenotypic assays can assess susceptibility to any antiretroviral drug without any prior knowledge of HIV sequence from the patient. On the other hand, the massive amount of information accumulated during the last 20 years— that is, (1) the identification and correlation of single or multiple mutations associated with reduced susceptibility to all current antiretroviral drugs and (2) the development of complex algorithms to analyze these amino acid changes— has made indispensable the use of HIV genotyping tests in the management of HIV-infected patients [58, 59]. As with the phenotypic assays, multiple Sanger-sequencing-based HIV genotypic assays have been developed, but just a few are commercially available: ViroSeq® (Abbott), TRUGENE® (Siemens Healthcare), HIV Genotype (Quest Diagnostics), GenoSure® MG and GenoSure PRIme® (Monogram

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Biosciences), and vircoTYPE™ HIV (Janssen Diagnostics; no longer offered) (Fig. 1). Novel and more sophisticated databases and algorithms have resulted in more easily interpretable genotypic results; however, monitoring patients with complex antiretroviral regimens still requires considerable expertise. HIV Coreceptor Tropism The discovery that HIV requires a coreceptor to enter target cells—mainly, the chemokine receptors CCR5 and CXCR4 [60–62]—prompted the development of novel anti-HIV molecules targeting these receptors, better represented by the first CCR5-receptor antagonist approved for clinical use (maraviroc; Selzentry/Celsentri, Pfizer, NY) [63]. Given their mechanism of action, treatment with CCR5 antagonists requires the prior knowledge of the HIV coreceptor tropism in the patient, which led to the development of numerous phenotypic and genotypic approaches to determining HIV coreceptor usage or tropism [4, 64, 65] (Fig. 1). Similar to HIV drug resistance assays, phenotypic tests for determining HIV coreceptor tropism usually involve the infection of reporter cell lines expressing HIV receptors and coreceptors with patient-derived env-recombinant viruses [66–68], while others are based on the quantification of cell-tocell fusion events [69–71]. These phenotypic assays have the advantage of assessing the impact of multiple regions within the HIVenv gene on coreceptor tropism. Genotypic assays use the V3 region in the HIVenv gene as the determinant of CCR5 or CXCR4 tropism to infer HIV coreceptor tropism based on a series of bioinformatic tools [72–75]. A phenotypic assay, a Trofile (Monogram Biosciences) [67, 76], is currently the gold standard method used to determine HIV-1 coreceptor tropism in the U.S., while in-house genotypic HIV-1 tropism tests are largely used in Europe [10, 11]. Both approaches have advantages and disadvantages; however, the lack of sensitivity of Sanger-sequencing-based assays has led to the use of deep sequencing to increase the ability of genotypic assays to detect minority CXCR4-tropic variants [16, 34••, 35, 36•, 37, 38, 39•, 40•, 41–47].

Deep Sequencing: Multiple Platforms, One Goal Next-generation sequencing enables the rapid and costeffective production of high-quality sequence data, which is revolutionizing a multitude of disciplines, such as clinical diagnostics, drug and biomarker discovery, and personalized medicine [77]. Indeed, high demand for low-cost deep sequencing has led to the development of several NGS technologies that are transforming the way molecular diagnostic tests are designed and performed in clinical laboratories. Currently, four NGS platforms dominate the deep sequencing field: 454™ (454 Life Sciences/Roche, Branford, CT) [78],

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Illumina® (Illumina, Inc., San Diego, CA) [79], Ion Torrent™ (Ion Torrent/Life Technologies, South San Francisco, CA) [80], and PacBio® (Pacific Biosciences, Menlo Park, CA) [81]. A fifth deep sequencing platform based on nanopores is being developed by Oxford Nanopore Technologies® (Oxford, U.K.), although it is not currently available for clinical applications [82]. All these NGS technologies share and/or differ in the methods used in template preparation, sequencing, and data analysis. In general, all NGS platforms are able to generate valuable sequence information; however, there are key significant differences between the amount and quality of the data and the applications that each system may support. Table 1 summarizes the main characteristics of the four most used deep sequencing platforms. Additional and more detailed information, beyond the scope of this article, can be found in these comprehensive reviews [21, 77]. Choosing a NGS platform usually depends on the potential application(s) and resources available, including cost of the instrument and reagents, existing infrastructure, and personal experience. In the case of HIV, most of the published studies using deep sequencing have used the 454™ system, perhaps due to the fact that it was one of the first NGS systems available providing relatively longer reads (Table 1). However, all deep sequencing platforms have continued to work on improving their sequencing chemistries, simplifying sample preparation, decreasing sequencing time, and reducing cost per nucleotide sequenced, which has led HIV research and clinical laboratories to evaluate and adopt deep sequencing as part of their testing processes.

Using Deep Sequencing to Study HIV Next-generation sequencing has started to make a significant contribution to the HIV field, including a better understanding of (1) viral diversity and pathogenesis, (2) drug resistance selection and evolution, and (3) prediction of virus coreceptor usage or tropism. As was described above, deep sequencing allows the cost-effective study of a greater number of HIV variants from complex viral populations and—equally important for clinical laboratories—multiplexing and analyzing a number of patient-derived viruses in a single assay. Viral Diversity and Pathogenesis The extraordinary number of sequences (depth) that are generated by deep sequencing are ideal for studying intra- and interpatient HIV diversity. Long gone are the days of having to generate and Sanger sequence a multitude of individual molecular clones to reconstruct HIV quasispecies populations [83]. Now it is possible to sequence the complete HIV genome at variable depth—for example, ~40,000 nucleotides per position [84]—depending on the application. This massive

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Table 1 Summary of current next-generation technologiesa 454™ (GS Jr.) Amplification method Principle (chemistry) Average read length (bp) Average yield/run (Gb) Primary error (error rate) HIV-related scientific publicationsb Main advantage(s) Main disadvantage(s)

Illumina® (MiSeq)

Ion Torrent™ (PGM)

PacBio® (RS II)

Emulsion PCR on beads Bridge PCR in situ Emulsion PCR on beads Linear Synthesis (pyrosequencing) Synthesis (reversible termination) Synthesis (H+ detection) Single molecule, real-time synthesis 400–700 ~150 ~400 4,200–8,500 0.05 1 1.2–2 0.02–0.08 Indel ~1 % 116 Long read length, maturity Homopolymer misreads, high cost per Mb

Substitution ~0.1 % 77 Easy work flow, maturity Shortest reads

Indel ~1 % 3 Low cost, fast run Homopolymer misreads

Indel ~13 % 1 Longest reads High error rate, expensive

a

454™, Illumina®, and Ion Torrent™ technologies are available on different platforms, but here we describe their compact systems (GS Jr., MiSeq, and PGM, respectively), since these are the instruments that most likely will be used in clinical laboratories. PacBio® offers only one platform, the RS II, at the moment

b Based on information obtained from the respective companies (personal communications and/or Web sites) and PubMed search as of November 30, 2013

amount of information allows the detection of different HIV mutational patterns under selective antiretroviral pressures [85] and, in general, provides a greater understanding of the natural evolution of the virus [84–86] and the importance of viral escape from the host immune response early after transmission [49] and even helps with the characterization of HIV superinfection events [87]. HIV Drug Resistance Most deep-sequencing-based studies whose aim has been to detect and characterize mutations associated with resistance to antiretroviral drugs have been performed in the research setting. These studies have been instrumental in the evaluation of different NGS platforms and their ability to detect minority HIV drug-resistant variants at levels ranging from 0.1 % to 1 % of the virus population [27, 31, 33, 34••, 88, 89]. Most have used the 454™ platform [25•, 27, 33, 88, 90], but recently, other NGS technologies such as Illumina® [84] and Ion Torrent™ [26, 34••] have proved to be useful in the identification of low-level drug-resistant HIV variants. Dudley et al. [27] described the utility of a 454™-based method for the surveillance of HIV drug resistance, where they were able to multiplex 48 samples in a single assay with a conservative sensitivity of 5 %. A similar assay has been developed by 454 Life Sciences/Roche, which was able to detect all the mutations identified by the standard HIV genotyping assay TRUGENE® and 50 additional low-abundance drug resistance mutations [25•]. Many of the studies using deep sequencing have tried to determine the importance of detecting low-level HIV drug-resistant variants—that is, below the ~20 % detection level of Sanger sequencing [8, 12–15]. Minority HIV variants carrying single or multiple mutations associated with resistance to one or several classes of antiretroviral drugs

have been identified in both treatment-naïve and experienced patients [28, 29, 31, 32, 88, 91–94], although the actual clinical relevance of these minority members of the viral quasispecies is still under debate [31, 95••, 96–100]. Nevertheless, it makes sense that minority drug-resistant HIV-1 variants could eventually be selected under antiretroviral pressure, leading to therapy failure. For example, detection of drug resistance mutations by deep, but not population, sequencing has been associated with a higher risk of virologic failure in antiretroviral treatment-naïve patients [31, 101]. To date, only one NGS-based HIV genotyping assay is commercially available—that is, DEEPGEN™HIV (University Hospitals Case Medical Center) [34••] (Fig. 1). This assay is capable of accurately providing drug resistance information for all protease, reverse transcriptase, integrase, and maturation inhibitors, as well as HIV coreceptor tropism (see below), by multiplexing up to 96 samples in a single sequencing run [34••]. The analysis of longitudinal samples from large cohorts of patients with a reliable and ultrasensitive HIV genotyping assay based on deep sequencing, such as DEEPGEN™HIV, may provide the information needed for a better understanding of the role of low-level drug-resistant HIV variants in the clinical outcome of HIV-infected individuals. HIV Coreceptor Tropism Similar to HIV drug resistance, a multitude of studies have evaluated the use of deep sequencing to detect minority nonR5 (using coreceptor other than CCR5) HIV variants [34••, 35, 36•, 38, 40•, 41, 43–46]. Using deep sequencing, researchers have been able to detect CXCR4-tropic viruses during early HIV infection [46], study the mutational pathway of the V3 region in HIV during the transition from CCR5 to CXCR4 usage [102], and identify low levels of CXCR4-tropic provirus

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[103]. In the clinical setting, prediction of HIV coreceptor tropism by deep sequencing is highly concordant with phenotypic assays (82 %–87 %) [34••, 35, 36•, 37, 38, 39•, 47], has improved sensitivity for detecting non-R5 variants over population sequencing [34••, 36•, 38, 39•, 41, 42, 46, 104], and predicts the success of maraviroc-based antiretroviral regimens [35, 36•]. Most of these studies have used the 454™ platform [35, 36•, 37, 41–44, 46, 102, 105]; however, Archer et al. [40•] compared four NGS technologies (454™, Illumina®, Ion Torrent™, and PacBio®) used to detect low-level non-R5 viruses in HIVinfected individuals and found that all NGS platforms were able to identify these minority variants at similar frequencies, suggesting that any NGS-based method can be used to predict HIV coreceptor tropism. As was described above, the adoption of genotypic HIV tropism assays in the clinical setting has been hampered by the limited sensitivity of Sanger-based sequencing assays for detecting minor non-R5 variants, as compared with standard phenotypic assays capable of detecting non-R5 variants down to 0.3 % [67, 76]. Therefore, more sensitive genotypic HIV tropism assays based on deep sequencing have been developed to detect non-R5 variants below 20 % of the population, which have been shown to correlate well with other HIV-1 tropism tests [34••, 35, 36•, 39•]. To date, three deep-sequencing-based HIV tropism assays are available in clinical laboratories: HIV CCR5 Tropism Test V3 (British Columbia Centre for Excellence in HIV/AIDS, Vancouver, Canada) [36•], HIV Coreceptor Tropism with Reflex to Ultradeep Sequencing (Quest Diagnostics) [39•], and DEEPGEN™HIV (University Hospitals Case Medical Center) [34••] (Fig. 1). These tests have technical sensitivities between 0.5 % and 1 %, have a quick turnaround time, and are cost effective by having the ability to include multiple clinical samples in a single sequencing run. Thus, deep-sequencingbased HIV tropism assays may promote the development of new HIV coreceptor (CCR5 or CXCR4) antagonists and help in the treatment and management of HIV-infected individuals prior to treatment with this class of drugs.

Barriers to the Adoption of Deep-Sequencing-based HIV Assays The clinical utility provided by deep sequencing is increasingly established; however, there remain a number of barriers to widespread integration into routine management of HIVinfected patients. Current FDA-approved HIV-1 genotypic assays, such as ViroSeq® and TRUGENE®, are widely available and priced such that they are accessible to molecular pathology laboratories of various sizes. On the contrary, the start-up costs for NGS instrumentation paired with data analysis and storage solutions are high and likely prohibitive for widespread integration to lower volume laboratories. Clinical laboratories may justify this purchase by adding multiple tests

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to the system; for example, NGS testing for cancer genomics and inherited disorders can be developed in the same platform, in addition to other infectious disease assays. Beyond the costs, implementation and maintenance of clinical quality NGS testing require considerable technical expertise. Any NGS-based HIV assay is considered a laboratory-developed test (LDT)—a test that has not received IVD approval from the Food and Drug Administration (FDA)—requiring a more rigorous validation of the methodology within an individual laboratory than would be needed to verify the performance of an FDA-approved assay. These methods must be implemented in a CLIA-certified environment familiar with the regulatory requirements for laboratorydeveloped testing in general and NGS in particular. Specifically, new NGS-based HIV LDTs must be scrutinized for their ability to differentiate low-level mutant populations from sequencing or amplification errors [34••, 39•]. Perhaps a larger challenge is in the bioinformatics expertise required to analyze high-throughput data. While an increasing number of “out-of-the-box” bioinformatics solutions are becoming available for genomic analysis of cancers or human inherited genetic abnormalities, such ready solutions are limited and/ or in development for HIV drug resistance and coreceptor tropism analysis. Therefore, it remains that sophisticated bioinformatics expertise paired with high-complexity computing systems are essential for effective implementation of NGSbased HIVassays in the clinical setting, and this expertise may need to be maintained within an individual laboratory. With these requirements, performance of NGS assays is likely to be limited to large commercial laboratories or sophisticated academic centers with resources to develop and maintain the platforms. The availability of NGS assays in clinical laboratories is a recent development, and thus, clinical barriers to widespread adoption of HIV assays based on deep sequencing remain. As was discussed above, evidence of the importance of highly sensitive assays in the detection of low-level CXCR4-tropic HIV variants, monitoring for HIV superinfection, and addressing early emergence of drug resistance from the viral quasispecies continues to grow [34••, 36•, 40•, 87]. However, larger scale studies and clinical trials are needed to fully evaluate the utility of NGS-based HIV testing and the clinical impact of using these newly detectable minority HIV variants to alter drug regimens for clinical care. Current drug susceptibility evidence based on HIV genotyping is derived from studies using Sanger sequencing. Similar drug susceptibility information relating the spectrum of minority HIV variants detected by deep sequencing is not yet mature enough to make confident associations. As HIV genotypic and/or tropism assays based on deep sequencing are becoming available [34••, 36•, 39•], such clinical trials are now feasible, and undertaking them should be a priority. Lastly, as with Sanger sequencing, current NGS methods have limited success in obtaining

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accurate drug resistance and/or coreceptor tropism data in plasma samples with low HIV RNA levels [34••, 36•, 39•]. The success of antiretroviral therapy in suppressing HIV replication and the use of sensitive real-time PCR assays for monitoring plasma viral loads have resulted in the identification of an increased number of patients with low-level detectable virus [3, 6]. HIV genotypic assays based on deep sequencing are well positioned to study the mutation spectrum in these viral populations and identify potential emergence of resistance that could result in virologic failure.

Conclusions Next-generation sequencing technology is poised to revolutionize the monitoring of HIV therapy. As clinical trials and/or multi-institutional studies get underway, the clinical impact of this methodology will be established. Larger scale collaborations with key leaders in the application of NGS to HIV are ongoing to discuss how to overcome these barriers, utilize this technology to advance the field, and provide additional benefit to HIV patients. Compliance with Ethics Guidelines Conflict of Interest Richard M. Gibson, Christine L. Schmotzer, and Miguel E. Quiñones-Mateu have developed the novel HIV-1 genotyping and coreceptor tropism assay, DEEPGEN™HIV.

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Human and Animal Rights and Informed Consent This article does not contain any studies with human or animal subjects performed by any of the authors.

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References

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Papers of particular interest, published recently, have been highlighted as: • Of importance •• Of major importance

20.•

21. 1. 2.

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5. 6.

Marx JL. Drug-resistant strains of AIDS virus found. Science. 1989;243:1551–2. MacArthur RD. Understanding HIV, phenotypic resistance testing: usefulness in managing treatment-experienced patients. AIDS Rev. 2009;11:223–30. Zolopa AR. The evolution of HIV treatment guidelines: current state-of-the-art of ART. Antiviral Res. 2010;85:241–4. Rose JD, Rhea AM, Weber J, Quinones-Mateu ME. Current tests to evaluate HIV-1 coreceptor tropism. Curr Opin HIV AIDS. 2009;4:136–42. Dunn DT, Coughlin K, Cane PA. Genotypic resistance testing in routine clinical care. Curr Opin HIV AIDS. 2011;6:251–7. Grant PM, Zolopa AR. The use of resistance testing in the management of HIV-1-infected patients. Curr Opin HIV AIDS. 2009;4:474–80.

22.

23.

24.

25.•

Cunningham S, Ank B, Lewis D, Lu W, Wantman M, Dileanis JA, et al. Performance of the applied biosystems ViroSeq human immunodeficiency virus type 1 (HIV-1) genotyping system for sequence-based analysis of HIV-1 in pediatric plasma samples. J Clin Microbiol. 2001;39:1254–7. Grant RM, Kuritzkes DR, Johnson VA, Mellors JW, Sullivan JL, Swanstrom R, et al. Accuracy of the TRUGENE HIV-1 genotyping kit. J Clin Microbiol. 2003;41:1586–93. Paar C, Palmetshofer C, Flieger K, Geit M, Kaiser R, Stekel H, et al. Genotypic antiretroviral resistance testing for human immunodeficiency virus type 1 integrase inhibitors by use of the TruGene sequencing system. J Clin Microbiol. 2008;46:4087–90. Obermeier M, Symons J, Wensing AM. HIV population genotypic tropism testing and its clinical significance. Curr Opin HIV AIDS. 2012;7:470–7. Poveda E, Alcami J, Paredes R, Cordoba J, Gutierrez F, Llibre JM, et al. Genotypic determination of HIV tropism - clinical and methodological recommendations to guide the therapeutic use of CCR5 antagonists. AIDS Rev. 2010;12:135–48. Larder BA, Kohli A, Kellam P, Kemp SD, Kronick M, Henfrey RD. Quantitative detection of HIV-1 drug resistance mutations by automated DNA sequencing. Nature. 1993;365:671–3. Church JD, Jones D, Flys T, Hoover D, Marlowe N, Chen S, et al. Sensitivity of the ViroSeq HIV-1 genotyping system for detection of the K103N resistance mutation in HIV-1 subtypes A, C, and D. J Mol Diagn: JMD. 2006;8:430–2. quiz 527. Halvas EK, Aldrovandi GM, Balfe P, Beck IA, Boltz VF, Coffin JM, et al. Blinded, multicenter comparison of methods to detect a drug-resistant mutant of human immunodeficiency virus type 1 at low frequency. J Clin Microbiol. 2006;44:2612–4. Leitner T, Halapi E, Scarlatti G, Rossi P, Albert J, Fenyo EM, et al. Analysis of heterogeneous viral populations by direct DNA sequencing. Biotechniques. 1993;15:120–7. Swenson LC, Daumer M, Paredes R. Next-generation sequencing to assess HIV tropism. Curr Opin HIV AIDS. 2012;7:478–85. Scally A, Dutheil JY, Hillier LW, Jordan GE, Goodhead I, Herrero J, et al. Insights into hominid evolution from the gorilla genome sequence. Nature. 2012;483:169–75. Howden BP, McEvoy CR, Allen DL, Chua K, Gao W, Harrison PF, et al. Evolution of multidrug resistance during Staphylococcus aureus infection involves mutation of the essential two component regulator WalKR. PLoS Pathog. 2011;7:e1002359. Quan PL, Firth C, Conte JM, Williams SH, Zambrana-Torrelio CM, Anthony SJ, et al. Bats are a major natural reservoir for hepaciviruses and pegiviruses. Proc Natl Acad Sci U S A. 2013;110:8194–9. Loman NJ, Misra RV, Dallman TJ, Constantinidou C, Gharbia SE, Wain J, et al. Performance comparison of benchtop high-throughput sequencing platforms. Nat Biotechnol. 2012. An excellent study comparing 454’s GS jr., Illumina’s MiSeq, and Ion Torrent’s PGM. Liu L, Li Y, Li S, Hu N, He Y, Pong R, et al. Comparison of nextgeneration sequencing systems. J Biomed Biotechnol. 2012;2012: 251364. Quail MA, Smith M, Coupland P, Otto TD, Harris SR, Connor TR, et al. A tale of three next generation sequencing platforms: comparison of Ion Torrent, Pacific Biosciences and Illumina MiSeq sequencers. BMC Genom. 2012;13:341. Wong LJ. Challenges of bringing next generation sequencing technologies to clinical molecular diagnostic laboratories. Neurother: J Am Soc Exp Neurother. 2013;10:262–72. Gullapalli RR, Lyons-Weiler M, Petrosko P, Dhir R, Becich MJ, LaFramboise WA. Clinical integration of next-generation sequencing technology. Clin Lab Med. 2012;32:585–99. Avidor B, Girshengorn S, Matus N, Talio H, Achsanov S, Zeldis I, et al. Evaluation of a benchtop HIV ultradeep pyrosequencing drug resistance assay in the clinical laboratory. J Clin Microbiol.

Curr Infect Dis Rep (2014) 16:401 2013;51:880–6. Description of an HIV-1 genotyping assay based on the 454 GS Jr. platform. 26. Chang MW, Oliveira G, Yuan J, Okulicz JF, Levy S, Torbett BE. Rapid deep sequencing of patient-derived HIV with ion semiconductor technology. J Virol Methods. 2013;189:232–4. 27. Dudley DM, Chin EN, Bimber BN, Sanabani SS, Tarosso LF, Costa PR, et al. Low-cost ultra-wide genotyping using Roche/454 pyrosequencing for surveillance of HIV drug resistance. PloS One. 2012;7:e36494. 28. Messiaen P, Verhofstede C, Vandenbroucke I, Dinakis S, Van Eygen V, Thys K, et al. Ultra-deep sequencing of HIV-1 reverse transcriptase before start of an NNRTI-based regimen in treatment-naive patients. Virology. 2012;426:7–11. 29. Armenia D, Vandenbroucke I, Fabeni L, Van Marck H, Cento V, D’Arrigo R, et al. Study of genotypic and phenotypic HIV-1 dynamics of integrase mutations during raltegravir treatment: a refined analysis by ultra-deep 454 pyrosequencing. J Infect Dis. 2012;205:557–67. 30. Mukherjee R, Jensen ST, Male F, Bittinger K, Hodinka RL, Miller MD, et al. Switching between raltegravir resistance pathways analyzed by deep sequencing. AIDS. 1951–1959;2011:25. 31. Simen BB, Simons JF, Hullsiek KH, Novak RM, Macarthur RD, Baxter JD, et al. Low-abundance drug-resistant viral variants in chronically HIV-infected, antiretroviral treatment-naive patients significantly impact treatment outcomes. J Infect Dis. 2009;199:693–701. 32. Liu J, Miller MD, Danovich RM, Vandergrift N, Cai F, Hicks CB, et al. Analysis of low-frequency mutations associated with drug resistance to raltegravir before antiretroviral treatment. Antimicrob Agents Chemother. 2011;55:1114–9. 33. Shao W, Boltz VF, Spindler JE, Kearney MF, Maldarelli F, Mellors JW, et al. Analysis of 454 sequencing error rate, error sources, and artifact recombination for detection of Low-frequency drug resistance mutations in HIV-1 DNA. Retrovirology. 2013;10:18. 34.•• Gibson RM, Meyer AM, Winner D, Archer J, Feyertag F, Robertson DL, et al. Characterization and validation of a deep sequencing-based HIV-1 genotypic and coreceptor tropism assay to simultaneously monitor susceptibility to maturation, protease, reverse transcriptase, and integrase inhibitors, and CCR5 antagonists. Antivir Ther. 2013;18:A43. Original description of the first all-inclusive HIV-1 genotyping and coreceptor tropism assay based on deep sequencing. 35. Swenson LC, Mo T, Dong WW, Zhong X, Woods CK, Thielen A, et al. Deep V3 sequencing for HIV type 1 tropism in treatmentnaive patients: a reanalysis of the MERIT trial of maraviroc. Clin Infect Dis: Off Publ Infect Dis Soc Am. 2011;53:732–42. 36.• Swenson LC, Mo T, Dong WW, Zhong X, Woods CK, Jensen MA, et al. Deep sequencing to infer HIV-1 co-receptor usage: application to three clinical trials of maraviroc in treatmentexperienced patients. J Infect Dis. 2011;203:237–45. Excellent study describing the use of an deep sequencing-based HIV-1 coreceptor tropism test in the clinical setting. 37. Saliou A, Delobel P, Dubois M, Nicot F, Raymond S, Calvez V, et al. Concordance between two phenotypic assays and ultradeep pyrosequencing for determining HIV-1 tropism. Antimicrob Agents Chemother. 2011;55:2831–6. 38. Kagan RM, Johnson EP, Siaw MF, Van Baelen B, Ogden R, Platt JL, et al. Comparison of genotypic and phenotypic HIV Type 1 tropism assay: results from the screening samples of cenicriviroc study 202, a randomized phase II trial in treatment-naive subjects. AIDS Res Hum Retrovir. 2013;29. 39.• Kagan RM, Johnson EP, Siaw M, Biswas P, Chapman DS, Su Z, et al. A genotypic test for HIV-1 tropism combining Sanger sequencing with ultradeep sequencing predicts virologic response in treatment-experienced patients. PloS One. 2012;7:e46334. Description of a commercial HIV-1 coreceptor tropism assay based on deep sequencing. 40.• Archer J, Weber J, Henry K, Winner D, Gibson R, Lee L, et al. Use of Four Next-Generation Sequencing Platforms to Determine HIV-1

Page 7 of 9, 401

41.

42.

43.

44.

45.

46.

47.

48.

49.

50.

51.

52.

53.

54.

55.

Coreceptor Tropism. PloS One. 2012;7:e49602. First study comparing all fourdeep sequencing technologies (454, Illumina, Ion Torrent, and Pacific Biosciences) to quantify HIV-1 coreceptor tropism. Swenson LC, Moores A, Low AJ, Thielen A, Dong W, Woods C, et al. Improved detection of CXCR4-using HIV by V3 genotyping: application of population-based and “deep” sequencing to plasma RNA and proviral DNA. J Acquir Immune Defic Syndr. 2010;54:506–10. Archer J, Braverman MS, Taillon BE, Desany B, James I, Harrigan PR, et al. Detection of low-frequency pretherapy chemokine (CXC motif) receptor 4 (CXCR4)-using HIV-1 with ultradeep pyrosequencing. AIDS. 2009;23:1209–18. Vandenbroucke I, Van Marck H, Mostmans W, Van Eygen V, Rondelez E, Thys K, et al. HIV-1 V3 envelope deep sequencing for clinical plasma specimens failing in phenotypic tropism assays. AIDS Res Ther. 2010;7:4. Archer J, Rambaut A, Taillon BE, Harrigan PR, Lewis M, Robertson DL. The evolutionary analysis of emerging low frequency HIV-1 CXCR4 using variants through time–an ultra-deep approach. PLoS Comput Biol. 2010;6:e1001022. Raymond S, Saliou A, Nicot F, Delobel P, Dubois M, Cazabat M, et al. Frequency of CXCR4-using viruses in primary HIV-1 infections using ultra-deep pyrosequencing. AIDS. 2011;25:1668–70. Abbate I, Vlassi C, Rozera G, Bruselles A, Bartolini B, Giombini E, et al. Detection of quasispecies variants predicted to use CXCR4 by ultra-deep pyrosequencing during early HIV infection. AIDS. 2011;25:611–7. Lee GQ, Harrigan PR, Dong W, Poon AF, Heera J, Demarest J, et al. Comparison of population and 454 “deep” sequence analysis for HIV type 1 tropism versus the original trofile assay in non-B subtypes. AIDS Res Hum Retrovir. 2013;29:979–84. Wu X, Zhou T, Zhu J, Zhang B, Georgiev I, Wang C, et al. Focused evolution of HIV-1 neutralizing antibodies revealed by structures and deep sequencing. Science. 2011;333:1593–602. Henn MR, Boutwell CL, Charlebois P, Lennon NJ, Power KA, Macalalad AR, et al. Whole genome deep sequencing of HIV-1 reveals the impact of early minor variants upon immune recognition during acute infection. PLoS Pathog. 2012;8:e1002529. Raymond S, Delobel P, Izopet J. Phenotyping methods for determining HIV tropism and applications in clinical settings. Curr Opin HIV AIDS. 2012;7:463–9. Japour AJ, Mayers DL, Johnson VA, Kuritzkes DR, Beckett LA, Arduino JM, et al. Standardized peripheral blood mononuclear cell culture assay for determination of drug susceptibilities of clinical human immunodeficiency virus type 1 isolates. The RV43 Study Group, the AIDS Clinical Trials Group Virology Committee Resistance Working Group. Antimicrob Agents Chemother. 1993;37:1095–101. Hertogs K, de Bethune MP, Miller V, Ivens T, Schel P, Van Cauwenberge A, et al. A rapid method for simultaneous detection of phenotypic resistance to inhibitors of protease and reverse transcriptase in recombinant human immunodeficiency virus type 1 isolates from patients treated with antiretroviral drugs. Antimicrob Agents Chemother. 1998;42:269–76. Kellam P, Larder BA. Recombinant virus assay: a rapid, phenotypic assay for assessment of drug susceptibility of human immunodeficiency virus type 1 isolates. Antimicrob Agents Chemother. 1994;38:23–30. Petropoulos CJ, Parkin NT, Limoli KL, Lie YS, Wrin T, Huang W, et al. A novel phenotypic drug susceptibility assay for human immunodeficiency virus type 1. Antimicrob Agents Chemother. 2000;44:920–8. Weber J, Vazquez AC, Winner D, Rose JD, Wylie D, Rhea AM, et al. Novel method for simultaneous quantification of phenotypic resistance to maturation, protease, reverse transcriptase, and integrase HIV inhibitors based on 3′Gag(p2/p7/p1/p6)/PR/RT/ INT-recombinant viruses: a useful tool in the multitarget era of

401, Page 8 of 9 antiretroviral therapy. Antimicrob Agents Chemother. 2011;55: 3729–42. 56. Meyerhans A, Cheynler R, Albert J, Seth M, Kwok S, Sninsky J, et al. Temporal Fluctuations in HIV Quasispecies In Vivo Are Not Reflected by Sequential HIV Isolations. Cell. 1989;58:901–10. 57. Race E, Dam E, Obry V, Paulous S, Clavel F. Analysis of HIV cross-resistance to protease inhibitors using a rapid single-cycle recombinant virus assay for patients failing on combination therapies. AIDS. 1999;13:2061–8. 58. Paredes R, Clotet B. Clinical management of HIV-1 resistance. Antiviral Res. 2010;85:245–65. 59. Shafer RW. Rationale and uses of a public HIV drug-resistance database. J Infect Dis. 2006;194 Suppl 1:S51–58. 60. Dragic T, Litwin V, Allaway GP, Martin SR, Huang Y, Nagashima KA, et al. HIV-1 entry into CD4+ cells is mediated by the chemokine receptor CC- CKR-5. Nature. 1996;381:667–73. 61. Feng Y, Broder CC, Kennedy PE, Berger EA. HIV-1 entry cofactor: functional cDNA cloning of a seven-transmembrane, G protein-coupled receptor. Science. 1996;272:872–7. 62. Deng H, Liu R, Ellmeier W, Choe S, Unutmaz D, Burkhart M, et al. Identification of a major co-receptor for primary isolates of HIV-1. Nature. 1996;381:661–6. 63. 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;49:4721–32. 64. Poveda E, Briz V, Quinones-Mateu M, Soriano V. HIV tropism: diagnostic tools and implications for disease progression and treatment with entry inhibitors. AIDS. 2006;20:1359–67. 65. Weber J, Piontkivska H, Quinones-Mateu ME. HIV type 1 tropism and inhibitors of viral entry: clinical implications. AIDS Rev. 2006;8:60–77. 66. Trouplin V, Salvatori F, Cappello F, Obry V, Brelot A, Heveker N, et al. Determination of coreceptor usage of human immunodeficiency virus type 1 from patient plasma samples by using a recombinant phenotypic assay. J Virol. 2001;75:251–9. 67. Whitcomb JM, Huang W, Fransen S, Limoli K, Toma J, Wrin T, et al. Development and characterization of a novel single-cycle recombinantvirus assay to determine human immunodeficiency virus type 1 coreceptor tropism. Antimicrob Agents Chemother. 2007;51:566–75. 68. Raymond S, Delobel P, Mavigner M, Cazabat M, Souyris C, Encinas S, et al. Development and performance of a new recombinant virus phenotypic entry assay to determine HIV-1 coreceptor usage. J Clin Virol: Off Publ Pan Am Soc Clin Virol. 2010;47:126–30. 69. Holland AU, Munk C, Lucero GR, Nguyen LD, Landau NR. Alpha-complementation assay for HIV envelope glycoproteinmediated fusion. Virology. 2004;319:343–52. 70. Grund S, Klein A, Adams O. Expression plasmids are only useful for the investigation of co-receptor tropism and fusion capacity of short HIV-1 envelope domains. J Virol Methods. 2010;166:106–9. 71. Weber J, Vazquez AC, Winner D, Gibson RM, Rhea AM, Rose JD, et al. Sensitive Cell-based Assay to Determine Human Immunodeficiency Virus Type 1 Coreceptor Tropism. J Clin Microbiol. 2013;51:1517–27. 72. Sing T, Low AJ, Beerenwinkel N, Sander O, Cheung PK, Domingues FS, et al. Predicting HIV coreceptor usage on the basis of genetic and clinical covariates. Antivir Ther. 2007;12:1097–106. 73. Jensen MA, Li FS, van’t Wout AB, Nickle DC, Shriner D, He HX, et al. Improved coreceptor usage prediction and genotypic monitoring of R5-to-X4 transition by motif analysis of human immunodeficiency virus type 1 env V3 loop sequences. J Virol. 2003;77:13376–88. 74. Cardozo T, Kimura T, Philpott S, Weiser B, Burger H, ZollaPazner S. Structural basis for coreceptor selectivity by the HIV type 1 V3 loop. AIDS Res Hum Retrovir. 2007;23:415–26.

Curr Infect Dis Rep (2014) 16:401 75.

76.

77. 78.

79. 80.

81.

82.

83.

84.

85.

86.

87. 88.

89.

90.

91.

92.

93.

Rosen O, Sharon M, Quadt-Akabayov SR, Anglister J. Molecular switch for alternative conformations of the HIV-1 V3 region: implications for phenotype conversion. Proc Natl Acad Sci U S A. 2006;103:13950–5. Reeves JD, Coakley E, Petropoulos CJ, Whitcomb JM. An Enhanced-Sensitivity Trofile™ HIV Coreceptor Tropism Assay for Selecting Patients for Therapy with Entry Inhibitors Targeting CCR5: A Review of Analytical and Clinical Studies. J Viral Entry. 2009;3:94–102. Metzker ML. Sequencing technologies - the next generation. Nat Rev Genet. 2010;11:31–46. Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, Bemben LA, et al. Genome sequencing in microfabricated highdensity picolitre reactors. Nature. 2005;437:376–80. Bennett S. Solexa Ltd. Pharmacogenomics. 2004;5:433–8. Rothberg JM, Hinz W, Rearick TM, Schultz J, Mileski W, Davey M, et al. An integrated semiconductor device enabling non-optical genome sequencing. Nature. 2011;475:348–52. Eid J, Fehr A, Gray J, Luong K, Lyle J, Otto G, et al. Real-time DNA sequencing from single polymerase molecules. Science. 2009;323:133–8. Howorka S, Cheley S, Bayley H. Sequence-specific detection of individual DNA strands using engineered nanopores. Nat Biotechnol. 2001;19:636–9. Quinones-Mateu ME, Albright JL, Mas A, Soriano V, Arts EJ. Analysis of pol gene heterogeneity, viral quasispecies, and drug resistance in individuals infected with group O strains of human immunodeficiency virus type 1. J Virol. 1998;72:9002–15. Willerth SM, Pedro HA, Pachter L, Humeau LM, Arkin AP, Schaffer DV. Development of a low bias method for characterizing viral populations using next generation sequencing technology. PloS One. 2010;5:e13564. Eriksson N, Pachter L, Mitsuya Y, Rhee SY, Wang C, Gharizadeh B, et al. Viral population estimation using pyrosequencing. PLoS Comput Biol. 2008;4:e1000074. Poon AF, Swenson LC, Dong WW, Deng W, Kosakovsky Pond SL, Brumme ZL, et al. Phylogenetic analysis of population-based and deep sequencing data to identify coevolving sites in the nef gene of HIV-1. Mol Biol Evol. 2010;27:819–32. Redd AD, Quinn TC, Tobian AA. Frequency and implications of HIV superinfection. Lancet Infect Dis. 2013;13:622–8. Fisher R, van Zyl GU, Travers SA, Kosakovsky Pond SL, Engelbrech S, Murrell B, et al. Deep sequencing reveals minor protease resistance mutations in patients failing a protease inhibitor regimen. J Virol. 2012;86:6231–7. Wang C, Mitsuya Y, Gharizadeh B, Ronaghi M, Shafer RW. Characterization of mutation spectra with ultra-deep pyrosequencing: application to HIV-1 drug resistance. Genome Res. 2007;17:1195–201. Stelzl E, Proll J, Bizon B, Niklas N, Danzer M, Hackl C, et al. Human immunodeficiency virus type 1 drug resistance testing: Evaluation of a new ultra-deep sequencing-based protocol and comparison with the TRUGENE HIV-1 Genotyping Kit. J Virol Methods. 2011;178:94–7. Lataillade M, Chiarella J, Yang R, DeGrosky M, Uy J, Seekins D, et al. Virologic failures on initial boosted-PI regimen infrequently possess low-level variants with major PI resistance mutations by ultra-deep sequencing. PloS One. 2012;7:e30118. Nicot F, Saliou A, Raymond S, Saune K, Dubois M, Massip P, et al. Minority variants associated with resistance to HIV-1 nonnucleoside reverse transcriptase inhibitors during primary infection. J Clin Virol: Off Publ Pan Am Soc Clin Virol. 2012;55:107–13. D’Aquila RT, Geretti AM, Horton JH, Rouse E, Kheshti A, Raffanti S, et al. Tenofovir (TDF)-selected or abacavir (ABC)selected low-frequency HIV type 1 subpopulations during failure with persistent viremia as detected by ultradeep pyrosequencing. AIDS Res Hum Retrovir. 2011;27:201–9.

Curr Infect Dis Rep (2014) 16:401 94.

95.••

96.

97.

98.

99.

100.

Bellecave P, Recordon-Pinson P, Papuchon J, Vandenhende MA, Reigadas S, Tauzin B, et al. Detection of low-frequency HIV Type 1 reverse transcriptase drug resistance mutations by Ultradeep Sequencing in Naive HIV Type 1-Infected individuals. AIDS Res Hum Retrovir. 2013. Li JZ, Kuritzkes DR. Clinical implications of HIV-1 minority variants. Clin Infect Dis: Off Publ Infect Dis Soc Am. 2013;56: 1667–74. Excellent article that analyses the potential use of deep sequencing HIV-1 assays in the clinical setting. 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: J Am Med Assoc. 2011;305:1327–35. Stekler JD, Ellis GM, Carlsson J, Eilers B, Holte S, Maenza J, et al. Prevalence and impact of minority variant drug resistance mutations in primary HIV-1 infection. PloS One. 2011;6:e28952. Li JZ, Paredes R, Ribaudo HJ, Kozal MJ, Svarovskaia ES, Johnson JA, et al. Impact of minority nonnucleoside reverse transcriptase inhibitor resistance mutations on resistance genotype after virologic failure. J Infect Dis. 2013;207:893–7. Li JZ, Paredes R, Ribaudo HJ, Svarovskaia ES, Kozal MJ, Hullsiek KH, et al. Relationship between minority nonnucleoside reverse transcriptase inhibitor resistance mutations, adherence, and the risk of virologic failure. AIDS. 2012;26:185–92. Codoner FM, Pou C, Thielen A, Garcia F, Delgado R, Dalmau D, et al. Added value of deep sequencing relative to population sequencing in heavily pre-treated HIV-1-infected subjects. PloS One. 2011;6:e19461.

Page 9 of 9, 401 101.

Gonzalez S, Tully DC, Gondwe C, Wood C. Low-abundance resistant mutations in HIV-1 subtype C antiretroviral therapy-naive individuals as revealed by pyrosequencing. Curr HIV Res. 2013;11:43–9. 102. Bunnik EM, Swenson LC, Edo-Matas D, Huang W, Dong W, Frantzell A, et al. Detection of inferred CCR5- and CXCR4-using HIV-1 variants and evolutionary intermediates using ultra-deep pyrosequencing. PLoS Pathog. 2011;7:e1002106. 103. Rozera G, Abbate I, Bruselles A, Vlassi C, D’Offizi G, Narciso P, et al. Archived HIV-1 minority variants detected by ultra-deep pyrosequencing in provirus may be fully replication competent. AIDS. 2009;23:2541–3. 104. Gonzalez-Serna A, McGovern RA, Harrigan PR, Vidal F, Poon AF, Ferrando-Martinez S, et al. Correlation of the virological response to short-term maraviroc monotherapy with standard and deep-sequencing-based genotypic tropism prediction methods. Antimicrob Agents Chemother. 2012;56:1202–7. 105. Raymond S, Recordon-Pinson P, Saliou A, Delobel P, Nicot F, Descamps D, et al. Improved V3 genotyping with duplicate PCR amplification for determining HIV-1 tropism. J Antimicrob Chemother. 2011;66:1972–5. 106. Van HM, Picchio G, Van der Borght K, Pattery T, Lecocq P, Bacheler LT. A comparison of HIV-1 drug susceptibility as provided by conventional phenotyping and by a phenotype prediction tool based on viral genotype. J Med Virol. 2009;81:1702–9. 107. Gonzalez-Serna A, Leal M, Genebat M, Abad MA, GarciaPerganeda A, Ferrando-Martinez S, et al. TROCAI (tropism coreceptor assay information): a new phenotypic tropism test and its correlation with Trofile enhanced sensitivity and genotypic approaches. J Clin Microbiol. 2010;48:4453–8.