1 Hepatitis C virus NS3 sequence diversity and antiviral resistance

35 Pages·2014·2.19 MB·English

AAC Accepts, published online ahead of print on 4 August 2014
Antimicrob. Agents Chemother. doi:10.1128/AAC.03466-14
Copyright © 2014, American Society for Microbiology. All Rights Reserved.

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2 Hepatitis C virus NS3 sequence diversity and antiviral resistance-associated variant
3 frequency in HCV/HIV coinfection
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5 Cassandra B. Jabaraa,b*†, Fengyu Hub,c*§, Katie Mollanb,d, Sara E. Willifordb,c,
6 Prema Menezesb,c, Yan Yangb,c, Joseph J. Eronb,c, Michael W. Friede, Michael Hudgensb,f, D
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7 Corbin D. Jonesa,b,d,g, Ronald Swanstromb,d,h, and Stanley M. Lemonb,c,d#
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9 Running title: Hepatitis C NS3 sequence diversity and RAV frequency e
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11 Department of Biologya, UNC Center for AIDS Researchb, Division of Infectious Diseases,

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12 Department of Medicinec, Lineberger Comprehensive Cancer Centerd, Division of tt
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13 Gastroenterology and Hepatology, Department of Medicinee, Department of Biostatisticsf, //a
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14 Carolina Center for Genome Sciencesg, Department of Biochemistry and Biophysicsh, The c
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15 University of North Carolina at Chapel Hill, Chapel Hill, NC, USA s
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18 Corresponding author:
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19 Stanley M. Lemon, M.D. p
20 8.034 Burnett-Womack CB #7292 ril
21 The University of North Carolina at Chapel Hill 1
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22 Chapel Hill, NC 27599-7292 USA ,

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24 Tel: [phone]; Fax: [phone]
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25 e-mail: [email protected] b
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29 *These authors contributed equally to this work.
30 †Current address: Abbott Molecular, Inc., 1300 E Touhy Ave., Des Plaines, IL 60018-3315
31 §Current address: Institute for Infectious Diseases, Guangzhou No.8 People’s Hospital,
32 Guangzhou, China
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34
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35 Abstract
36 HIV coinfection accelerates disease progression in chronic hepatitis C and reduces sustained
37 antiviral responses (SVR) to interferon-based therapy. New direct-acting antivirals (DAAs)
38 promise higher SVR rates, but the selection of pre-existing resistance-associated variants
39 (RAVs) may lead to virologic breakthrough or relapse. Pre-treatment frequencies of RAVs are
40 thus likely determinants of treatment outcome, but are typically below levels at which viral
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41 sequence can be accurately resolved. Moreover, it is not known how HIV coinfection o
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42 influences RAV frequency. We adopted an accurate high-throughput sequencing strategy to n
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43 compare nucleotide diversity in HCV NS3 protease-coding sequence in 20 monoinfected and
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44 20 coinfected subjects with well-controlled HIV infection. Differences in mean pair-wise d

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45 nucleotide diversity (π), Tajima’s D statistic, and Shannon entropy index suggested that the o
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46 genetic diversity of HCV is reduced in coinfection. Among coinfected subjects, diversity h
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47 correlated positively with increases in CD4+ T cells on anti-retroviral therapy, suggesting T cell p
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48 responses are important determinants of diversity. At a median sequencing depth of 0.084%, a
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49 pre-existing RAVs were readily identified. Q80K, which negatively impacts clinical responses .a
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50 to simiprevir, was encoded by more than 99% of viral RNAs in 17 of the 40 subjects. RAVs m
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51 other than Q80K were identified in 39 of 40 subjects, mostly at frequencies near 0.1%. RAV r
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52 frequency did not differ significantly between monoinfected and coinfected subjects. We o
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53 conclude that HCV genetic diversity is reduced in patients with well-controlled HIV infection, A
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54 likely reflecting impaired T cell immunity. However, RAV frequency is not increased and ril
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55 should not adversely influence the outcome of DAA therapy. 4
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58 Introduction
59 Coinfection with hepatitis C virus (HCV) is an important cause of morbidity and mortality
60 among persons infected with human immunodeficiency virus 1 (HIV) (1, 2). Disease
61 progression is accelerated, and coinfected patients respond poorly to treatment with pegylated
62 interferon-alfa and ribavirin (Peg-IFN/RBV) compared to those infected only with HCV
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63 (monoinfection). The rate of sustained antiviral response (SVR) with Peg-IFN/RBV was only
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64 19-22% in a large, international multi-center study of coinfected patients (3), less than half that n
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65 observed in monoinfected patients. The addition of direct-acting antiviral (DAA) therapies to a
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66 Peg-IFN/RBV significantly enhances SVR rates in monoinfected patients (4, 5). Four DAAs e
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67 have thus far been approved for use within the United States, three of which (boceprevir, r
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68 teleprevir, and simeprevir) target the viral NS3/4A protease (6, 7). Protease inhibitors show

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69 promise when used in combination with Peg-IFN for treatment of persons coinfected with HIV tp
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70 (8-10), and are likely to be key components of all oral, interferon-sparing therapies for hepatitis /a
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71 C in the future. Nonetheless, experience with the use of DAAs in coinfected patients remains c
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72 limited. m
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73 In monoinfected patients, HCV variants resistant to NS3/4A protease inhibitors emerge r
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74 rapidly unless the drugs are used in combination with other inhibitors of HCV replication such o
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75 as Peg-IFN/RBV (11, 12). Even with concomitant Peg-IFN/RBV, however, virologic A
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76 breakthrough or relapse occurred in as many as 11-14% of coinfected patients treated in phase ril
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77 IIa trials of HCV protease inhibitors (8, 13). Resistant HCV variants emerging during DAA 4
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78 therapy likely represent pre-existing minor quasispecies that become predominant due to the 0
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79 selective pressure of the drugs (14). In part this reflects the highly replicative nature of HCV 9

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80 infection, with large numbers of new virions produced each day (~5 x 1012) in the typical y

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81 infected individual (15), coupled with error-prone genome replication. The response to DAA e
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82 therapy and the risk of emergence of resistant HCV variants may thus be influenced by the t
83 frequency and fitness of pre-existing resistance-associated variants (RAVs) (16, 17). Pre-
84 existing RAVs are likely to be particularly important with interferon-sparing treatment
85 regimens consisting solely of combinations of DAAs.
86 An important question is whether the frequency of RAVs is increased in HCV treatment-
87 naïve, coinfected persons. This might be expected if the genetic diversity of HCV is enhanced
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88 in coinfection by impaired host responses with attendant reductions in clearance of the virus.
89 Indeed, some previous studies suggest increased diversity within the envelope-coding region of
90 the HCV genome in coinfected versus monoinfected subjects (18-20). However, HIV diversity
91 decreases with advancing immunosuppression (21) and other studies suggest that the genetic
92 diversity of HCV may be reduced in coinfected persons (22-24). Still other studies have simply
93 failed to demonstrate a difference (25, 26). These conflicting results are likely related to
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94 variations in cohort size, sampling depth, the region of the HCV genome examined, and/or
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95 technical errors related to the sequencing strategy. n
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96 Efforts to define the population diversity of RNA viruses by high-throughput sequencing
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97 are potentially confounded by multiple sources of error (27, 28). Artifactual increases in d

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98 sequence diversity may be imparted by misincorporation of nucleotides during reverse o
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99 transcription of RNA to cDNA, or during cDNA amplification by PCR. Skewed views of viral h
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100 population structure can also result from recombination during multiple rounds of PCR, non- p
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101 uniform amplification of sequences, or oversampling of small numbers of genomes in the a
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102 starting population. Each of these types of error may obscure the true frequency of minor .a
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103 variants within a viral population. However, by incorporating a random 8-nucleotide tag within m
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104 the primer used for initial reverse transcription of a population of viral RNAs while r
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105 purposefully under-sampling that population with the number of tagging combinations, it is o
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106 possible to identify PCR amplicons derived from a single RNA template (29). This allows a A
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107 consensus sequence to be determined for a cluster of sequencing reads originating from that ril
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108 one template, and largely overcomes PCR-related errors in defining viral population diversity 4
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109 by high-throughput sequencing. We exploited this ‘primer ID’ strategy to accurately sequence 0
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110 HCV quasispecies at an unprecedented depth. 9

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111 Our goals in this study were three-fold: (i), to adapt this high throughput primer ID g
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112 sequencing strategy to the study of HCV quasispeices; (ii) to compare the degree of genetic e
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113 diversity of NS3 sequences in monoinfected, treatment-naive patients with that in coinfected
114 patients, also HCV treatment-naïve but on stable anti-retroviral therapy (ART); and (iii), to
115 conduct an unbiased and accurate assessment of the frequency of protease inhibitor RAVs in
116 HCV treatment-naïve subjects and ascertain whether RAV frequencies are altered by HIV
117 coinfection. Our results show that HCV diversity is decreased in coinfected subjects, but that
118 protease-inhibitor RAVs are present at similar frequencies in these two groups.
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119 Methods
120 Patient samples. Archived plasma or serum samples were collected between 2000-2011
121 from 20 monoinfected and 20 coinfected HCV treatment-naïve subjects at the University of
122 North Carolina Hospitals (Table 1). All were infected with genotype 1a HCV with
123 serum/plasma HCV RNA levels 1 x105 IU/mL. Coinfected subjects were on stable anti-
124 retroviral therapy (ART) with serum/plasma HIV RNA <50 copies/mL and a median CD4+ T
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125 cell count of 430 cells/mm3 (IQR: 284-665 cells/mm3). The study was approved by the o
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126 Institutional Review Board of The University of North Carolina at Chapel Hill. All study
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127 subjects provided written informed consent prior to enrollment. d
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128 Viral RNA extraction and cDNA synthesis. Viral RNA was extracted using the QIAamp f
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129 Viral RNA Mini Kit (Qiagen, Valencia, CA). Approximately 10,000 RNA copies were used as m

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130 template for reverse transcription with SuperScript III Reverse Transcriptase (Invitrogen, t
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131 Carlsbad, CA) and a tagging primer with the consensus sequence, 5’- :/
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132 ACCTTGCAAGCACGCTCTGGCCTTGAA-NNNNNNNN-CT-(BARCODE)- a
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133 GAACACCGGGGACCTCATGGTTGTCTC -3’, in which an 8 nt degenerate primer ID tag
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134 (NNNNNNNN) was followed by a CT linker and a 3-4 nt barcode for sample identification. .
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135 The 3’ end of the tagging primer (underlined sequence) was customized to provide an exact g
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136 reverse complement of the HCV sequence downstream of codon 173 of NS3 in each subject n

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137 (nts 3945-3971 in H77 virus, GenBank AF011751) as determined by prior population p
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138 sequencing. Primer sequences are shown in Table S1. Oligonucleotides were purchased from il
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139 Integrated DNA Technologies (IDT, Coralville, IA) and purified by standard desalting. ,

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140 Amplification of tagged cDNA. Single-stranded cDNA was column purified using the 1
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141 PureLink PCR Purification Kit (Invitrogen, Carlsbad, CA), washing 3 times with Binding
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142 Buffer HC (high cut-off) to remove the cDNA primer. Primer removal was verified on a subset u
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143 of samples by electropherogram analysis using an Experion HighSense RNA microfluidic chip s
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144 (Bio-Rad Laboratories, Hercules, CA). Purified cDNA was amplified by nested PCR using the
145 primer 5’-TAYTGCTYGGRCCRGCYGA-3’ (H77c nts 3370-3388) for first-round PCR, and
146 patient-matched primers with the consensus sequence 5’- AGTGGAGGGTGAGGTCCAGAT-
147 3’ (H77c nts 3503-3523) for second-round PCR. Downstream primers for nested PCR targeted
148 the 5’ end of the tagging primer: 5’-ACCTTGCAAGCACGCTCTGGC-3’ (first round), and 5’-
149 CAAGCACGCTCTGGCCTTGAA-3’ (second round). Amplification was carried out in HS
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150 Buffer Premix (PrimerSTARTM HS kit (TaKaRa, Japan). For first round PCR, purified cDNA
151 was divided between two 50 l reaction mixes, each subjected to 20 amplification cycles at
152 98C for 10 seconds followed by 68C for 45 seconds. One l of the combined first-round
153 reaction products was subjected to the second round of PCR that involved amplification for 20
154 cycles at 98C for 10 seconds, and 68C for 45 seconds. Reaction products were gel purified
155 using a 1.5% agarose gel and the MinElute gel extraction kit (Qiagen) with incubation of the
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156 solubilization buffer at room temperature. PCR amplicons were quantified using the PicoGreen o
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157 dsDNA assay (Life Technologies, Grand Island, NY). n
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158 454 Junior pyrosequencing and bioinformatic processing of raw sequences. d
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159 Amplicons from 4 patient samples, each with a unique barcode, were pooled in equal molar
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160 ratios. Library adaptors were added by blunt-end ligation using the Rapid Library Preparation m

161 kit (Roche Diagnostics, Indianapolis, IN). Products were analyzed with a Bioanalyzer using a h
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162 high sensitivity DNA chip (Agilent Technologies, Santa Clara, CA). The resulting library (2 x :
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163 107 copies) was subjected to emulsion-based clonal amplification with the Lib L emPCR a
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164 Amplification Kit (454 Life Sciences, Branford, CT), and sequenced on the 454 GS Junior a
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165 platform using Titanium chemistry (454 Life Sciences). Raw sequencing reads were processed
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166 through the native amplicon pipeline using default settings. A custom bioinformatics pipeline rg
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167 was used to filter and parse raw 454 primer ID sequencing reads as previously described (29). o
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168 In short, individual full-length reads were evaluated for the barcode and primer ID tag derived
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169 from the tagging primer used for cDNA synthesis. When 3 or more full-length reads from a il
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170 single patient sample (identical barcode) contained identical primer IDs, a consensus sequence ,

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171 was constructed by majority rule. 0
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172 Viral population diversity. Diversity measures were computed for populations of non- b
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173 ambiguous consensus sequences derived from 3 or more individual full-length reads as above. g
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174 The use of tagging primers containing numerically greater numbers of random tag sequences s
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175 (in theory, 65,536) than viral RNA copies (~10,000) in the reverse transcription reaction
176 ensures that the large majority of consensus sequences are derived from a single RNA template
177 molecule (29). Three different measures of genetic diversity were used to compare virus
178 populations from different subjects: average pairwise nucleotide diversity () (30), Tajima’s
179 statistic (D) (31), and the Shannon index (32, 33). Nucleotide diversity was computed for the
180 entire read length using a customized script according to the formula,
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181 xx
i j ij
ij
182 in which x and x are the frequency of ith and jth sequences respectively and  is the number
i j ij
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183 of differences between them (30). Tajima’s D and sliding window analysis of  (100 nt window
184 with 10 nt step size ) were computed by DnaSP v.5.10.01 (34). The Shannon index was
185 calculated using the VEGAN package of functions for R (35). Haplotypes (defined as unique
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186 combinations of sequence polymorphisms within a consensus sequence) and RAV occurrence
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187 at specific codons were enumerated with customized bioinformatics scripts in which consensus lo
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188 sequences in each population were first sorted by diversity, binned by unique variant, then d
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189 tallied to obtain variant frequencies. The RAVs that we searched for were V36A, V36L, or
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190 V36M; Q41R; F43S or F43I; T54A or T54S; V55A or V55I; Q80K or Q80R; V107I; R109K; m

191 S138T; R155G, R155K, R155M, or R155T; A156S, A156V, or A156D; D168E, D168N, or h
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192 D168G; and V170T. :
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193 Statistical analysis. Differences in diversity indices from monoinfected versus coinfected c
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194 subjects were tested for statistical significance by a t-test with Welch’s adjustment for unequal s
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195 variances; an exact Wilcoxon rank-sum (WRS) test was used as a sensitivity analysis. .
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196 Multivariable associations between covariates and each diversity index were analyzed with
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197 linear regression. Correlations between diversity indices and clinical parameters were n

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198 determined by Spearman’s rank correlation. RAV frequency was modeled using negative p
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199 binomial regression with coinfection status and codon nucleotide as predictor variables. This il 1
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200 model was fit using generalized estimating equations (GEE) with an exchangeable working ,
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201 correlation structure to account for multiple codon nucleotide observations within-subject. The 1
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202 outcome variable was number of occurrences of a given RAV, and log-transformed number of b
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203 consensus sequences was included as the offset term; associations were tested using a modified g
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204 F-statistic. A binary sensitivity outcome, RAV frequency >0%, was evaluated using a logistic s
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205 GEE model adjusted for sequencing depth. Analyses were conducted two-sided without
206 adjustment for multiplicity, using Prism 5 for Mac OS X software (GraphPad Software, Inc.) or
207 SAS version 9.3 (SAS Institute, Cary, NC).
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208 Results
209 Primer ID sequencing of HCV RNA. We characterized sequence diversity within the
210 segment of the HCV genome encoding the protease domain of NS3 (codons 36-173) isolated
211 from serum or plasma from 40 HCV-treatment naïve subjects, 20 who were infected solely
212 with HCV, and 20 who were coinfected with HIV (Table 1). All coinfected subjects were on
213 stable ART with HIV RNA levels <50 copies/ml. The use of tagged primers for cDNA
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214 synthesis eliminated several common sources of error in high-throughput sequencing
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215 populations of viral genomes (29). A random 8 nt sequence (“primer ID”) embedded in each
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216 primer labeled cDNA products derived from individual viral RNA molecules, allowing these a
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217 molecules to be tracked through subsequent PCR amplification and high-throughput e
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218 sequencing on the 454 Junior platform. Sequencing reads sharing a common primer ID were fr
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219 clustered, and a consensus sequence developed for each cluster of 3 or more reads. Non-

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220 ambiguous consensus sequences are likely to represent the authentic sequence of a single RNA t
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221 molecule given the ratio of possible primer ID sequences and starting RNA templates (see /a
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222 Methods). c
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223 We used this primer ID strategy to sequence circulating HCV RNAs in all 40 study s
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224 subjects. To illustrate the nature of the data obtained and how they were processed through the o
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225 bioinformatics pipeline, we show in detail representative results obtained with 2 monoinfected /

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226 (M1, M2) and 2 coinfected (C1, C2) study subjects (Fig. 1). Between 14,461 and 37,864
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227 sequence reads from each of these samples passed initial filtering, with the maximum number
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228 of reads sharing the same primer ID varying from 19 to 77 (Table 2). This allowed the 1
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229 construction of between 1,492 and 2,798 consensus sequences per sample (Fig. 1A-D, left), 2
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230 most of which (94.3-99.7%) were non-ambiguous by majority call. Consistent with substantial 1
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231 diversity among virions circulating in individual subjects, numerous unique haplotypes
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232 (defined as described in Methods) were present within each population (Fig. 1A-D, right). The u
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233 most frequent haplotype present comprised only 12.5-20.0% of all consensus sequences in any s
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234 one subject. The number of unique haplotypes representing >1% of the consensus sequences
235 ranged from 5 to 14. The most frequent 12 to 20 haplotypes comprised 50% of all sequences in
236 the coinfected subjects. This compared with 36 to 80 haplotypes in the two monoinfected
237 subjects, suggesting greater haplotype diversity in the absence of HIV coinfection.
238 To ascertain reproducibility, we carried out replicate, independent cDNA syntheses and
239 sequencing runs on these 4 subjects. The two pyrosequencing runs yielded similar numbers of
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240 consensus sequences from each subject (Table 2). Excluding several notable exceptions (all
241 cytosine-rich primer ID tags, Table S2), the most frequent primer IDs observed were unique to
242 each run. The most prevalent primer IDs in reads from subject C1 were reproducibly enriched
243 for cytosine (Table S2), suggesting either poor randomization of the degenerate region in the
244 tagging primer during synthesis, or more efficient priming for cDNA synthesis. This was not
245 observed with subsequent samples using different tagging primers for cDNA synthesis.
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246 Importantly, there was strong reproducibility in the frequency of individual haplotypes resolved
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247 in the two independent runs (Fig. 2). Overall, between 1,411 and 3,577 nonambiguous n
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248 consensus sequences were resolved per sample, resulting in population depths between 0.07% - a
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249 0.03%. Because the probability of sampling a low-abundance haplotype approximates the e
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250 Poisson distribution, this depth of sampling would be expected to identify variants with r
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251 frequencies as low as 0.2%-0.08%. Collectively, these data show that primer ID sequencing is

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252 capable of accurately resolving genetic diversity in populations of RNA viruses. tp
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253 Genetic diversity of HCV in monoinfection versus coinfection. A similar primer ID /a
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254 analysis of NS3-coding sequence was carried out with RNA extracted from serum or plasma c
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255 from each of the other study subjects, thereby providing data on a total of 40 subjects with m
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256 genotype 1a HCV infection, 20 of whom were coinfected with HIV but on stable ART with o
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257 non-detectable HIV load (<50 c/mL). These cohorts were of comparable age (monoinfected /
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258 median age = 54 years vs. coinfected median age = 51 years) and predominantly male, but
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259 coinfected subjects were more likely to be of African-American, rather than white, race (78% r
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260 vs. 30%, p=0.004) and had somewhat lower serum ALT (Table 1). The results of the replicate 1
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261 sequencing runs described above were pooled and included in this analysis. Median sampling 2
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262 depth was 0.07% for monoinfected subjects and 0.08% for coinfected subjects (Fig. 3A). Each
9

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263 viral population was rich in allelic diversity, including numerous low frequency haplotypes. y

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264 Average pairwise nucleotide diversity () across the NS3 region sequenced varied by subject, u
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265 but was higher overall in monoinfected (mean π = 0.0143 ± 0.0069 s.d.) compared with t
266 coinfected (0.00954 ± 0.0051 s.d.) subjects (p=0.02, WRS p=0.03) (Fig. 3B). A sliding window
267 analysis revealed localized regions of minimally increased or decreased mean nucleotide
268 diversity within the linear sequence of the protease-coding region that were conserved in both
269 patient cohorts (Fig. 4, top panel). This position dependence did not correlate with the location
270 of active-site residues in the protease. In contrast, regions of maximum and minimum
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271 nucleotide diversity varied widely between individual subjects, suggesting host-specific
272 differences in regional selective forces such as might be mediated by HLA-restricted T cell
273 responses (Fig. 4, middle and lower panels). Nucleotide diversity was not significantly
274 associated with sequencing depth, HCV RNA copy number, ALT, bilirubin, age, or sex in
275 univariate models (p>0.05).
276 Tajima’s D statistic reflects the deviation between the observed and expected distribution
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277 of allelic frequencies at mutation-drift equilibrium (31). Strongly negative values of D may
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278 reflect recent selective sweeps, population bottlenecks, and population expansion whereas n
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279 positive values can indicate balancing selection, migration, and population subdivision. a
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280 Tajima’s D was ≤ -2.0 in all but two subjects, indicating an excess of low frequency e
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281 polymorphisms. While the mean value of Tajima’s D for coinfected subjects (-2.45 ± 0.18 s.d.) r
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282 was lower than for monoinfected subjects (-2.33 ± 0.23 s.d.), this difference did not achieve

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283 statistical significance (p=0.08, WRS p=0.15) (Fig. 3C). We also computed the Shannon tp
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284 diversity index for each virus population. This measure captures both the number of variants /a
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285 and the "evenness" of their distribution (how similar their numbers are) within the population c
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286 (32, 33). An increase in the number of unique haplotypes and/or an increase in the evenness of m
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287 their distribution will result in an increased Shannon index. Consistent with other measures of o
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288 diversity, the Shannon index showed a trend toward higher values in virus populations from /
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289 monoinfected versus coinfected subjects (mean = 4.96 ± 1.07 s.d. versus 4.34 ± 1.03 s.d,
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290 p=0.07, WRS p=0.10) (Fig. 3D). r
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291 As significantly more coinfected subjects were African-American than monoinfected 1
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292 subjects, we explored the association between these measures of HCV diversity and race in a 2
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293 series of multivariable linear regression models. Nucleotide diversity (π) was numerically
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294 greater in monoinfected subjects among both African-Americans and whites (Fig. 5). y

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295 Moreover, in a model adjusted for sequencing depth and HCV RNA copy number but ignoring u
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296 race, coinfection was associated with lower nucleotide diversity (p=0.02), while in a s
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297 comparable model ignoring coinfection status no association was detected with race (p=0.12).
298 However, in a model that included coinfection, race, sequencing depth, and HCV RNA level,
299 neither coinfection (p=0.11) nor race (p=0.52) was statistically significant, but interpretation of
300 this model was limited by co-linearity of coinfection and race (Table S3). None of the
301 evaluated covariates were significantly associated with Tajima’s D in multivariable models