# HIV-1 genotypic resistance testing using single molecule real-time sequencing

Stéphanie Raymond, Nicolas Jeanne, Camille Vellas, Florence Nicot, Karine Saune, Noémie Ranger, Justine Latour, Romain Carcenac, Agnès Harter, Pierre Delobel, et al.

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Stéphanie Raymond, Nicolas Jeanne, Camille Vellas, Florence Nicot, Karine Saune, et al. HIV-1 genotypic resistance testing using single molecule real-time sequencing. Journal of Clinical Virology, 2024, 174, pp.105717. 10.1016/j.jcv.2024.105717. hal-05038121

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Full Length Article

# HIV-1 genotypic resistance testing using single molecule real-time sequencing

Stéphanie Raymond<sup>a,b,*</sup>, Nicolas Jeanne<sup>b</sup>, Camille Vellas<sup>a,b</sup>, Florence Nicot<sup>b</sup>, Karine Saune<sup>b</sup>, Noémie Ranger<sup>b</sup>, Justine Latour<sup>b</sup>, Romain Carcenac<sup>b</sup>, Agnès Harter<sup>b</sup>, Pierre Delobel<sup>a,c</sup>, Jacques Izopet<sup>a,b</sup>

<figure><img src="image_3.png" /></figure>

## ARTICLE INFO

### Keywords:

Next-generation sequencing

HIV-1 polymerase

Long reads

Haplotypes

## ABSTRACT

**Background:** HIV-1 resistance testing is recommended in clinical management and next-generation sequencing (NGS) methods are now available in many virology laboratories.

**Objectives:** To evaluate the diagnostic performance of Long-Read Single Molecule Real-time (SMRT) sequencing (Sequel, PacBio) for HIV-1 polymerase genotyping.

**Study design:** 111 prospective clinical samples (83 plasma and 28 leukocyte-enriched blood fraction) were analyzed for routine HIV-1 resistance genotyping using Sanger sequencing, Vela NGS, and SMRT sequencing. We developed a SMRT sequencing protocol and a bio-informatics pipeline to infer antiretroviral resistance on both haplotype and variant calling approaches.

**Results:** The polymerase was successfully sequenced by the three platforms in 98 % of plasma RNA samples for viral loads above 4 log copies/mL. The success rate decreased to 83 % using Sanger or Vela sequencing and to 67 % using SMRT sequencing for viral loads of 3 to 4 log copies/mL. Sensitivities of 50 %, 54 % and 61 % were obtained using SMRT, Vela, and Sanger sequencing, respectively, in cellular DNA from patients with prolonged undetectable plasma HIV-1 RNA. Ninety-eight percent of resistance-associated mutations (RAMs) identified with Sanger sequencing were detected using SMRT sequencing. Furthermore, 91 % of RAMs (> 5 % threshold) identified with Vela NGS were detected using SMRT sequencing. RAM quantification using Vela and SMRT sequencing was well correlated (Spearman correlation ρ = 0.82; P < 0.0001).

**Conclusions:** SMRT sequencing of the full-length HIV-1 polymerase appeared performant for characterizing HIV-1 genotypic resistance on both RNA and DNA clinical samples. Long-read sequencing is a new tool for mutation haplotyping and resistance analysis.

## 1. Background

HIV-1 infection is now controlled by drugs with a viral suppression rate reaching 90 % in countries where antiretroviral therapy is widely accessible (UNAIDS 2021). This is accompanied by the risk of emerging resistance that would rapidly occur if viral load suppression was not achieved and maintained through therapy. Characterization of HIV-1 resistance relies on sequencing the virus polymerase targeted by antiretroviral drugs. The high capacity for HIV mutation and adaptation is also evident in intra-individual variability, as illustrated in the quasispecies infecting individuals. In this context, HIV genotyping would

benefit from next-generation sequencing (NGS) techniques allowing resistance-associated mutations (RAMs) to be identified and also quantified with improved sensitivity for detecting variants accounting for less than 15–20 % of the virus quasispecies compared to Sanger sequencing [1–3]. Many studies have shown that minority variants may emerge under drug selection pressure [4] and impair the virological response to combination therapy with non-nucleoside reverse transcriptase inhibitors (NNRTI) [5–7]. Previous studies have shown that resistant variants are also frequent in treatment-naïve individuals [8,9]. NGS platforms developed for genotyping HIV reverse transcriptase, protease and integrase are mainly second-generation platforms [10,11]. As

<footnote><sup>a</sup> INSERM UMR1291 – CNRS UMR 5051 – Université Toulouse III, Toulouse Institute for Infectious and Inflammatory Diseases, Toulouse, France</footnote>

<footnote><sup>b</sup> CHU de Toulouse, Hôpital Purpan, Laboratoire de Virologie, Toulouse, France</footnote>

<footnote><sup>c</sup> CHU de Toulouse, Service des Maladies Infectieuses et Tropicales, Toulouse, France</footnote>

<footnote>* Corresponding author at: CHU de Toulouse, Laboratoire de Virologie, Toulouse, 31300, France.</footnote>

<footnote>E-mail address: raymond.s@chu-toulouse.fr (S. Raymond).</footnote>
clinical management requires robust methods, we previously validated the automated Sentosa NGS platform (Vela Diagnostics, Hamburg, Germany) [9,12,13]. However, the short reads produced by second generation technology do not facilitate analysis of linkage between mutations. Long-read sequencing can reveal the mutations present on each haplotype with a potential impact on the susceptibility to antiretroviral drugs. The use of long-read Single Molecule Real-Time (SMRT) sequencing (Pacific Biosciences, California) for HIV-1 polymerase sequencing and resistance analysis is still limited [14–16].

## 2. Objectives

To address the performance of long-read SMRT sequencing of the HIV-1 polymerase with reference to Sanger sequencing and the Vela Diagnostics platform.

## 3. Study design

### 3.1. Patients and samples

A total of 111 blood samples collected prospectively from December 2020 to February 2021 and forwarded to Toulouse University Hospital for HIV-1 resistance genotyping were analyzed using three methods, namely Sanger sequencing, Vela NGS and SMRT sequencing. Polymerase sequencing was performed on plasma HIV-1 RNA for 83 samples (mean viral load: 3.8 log copies/mL; range 1.5 to 6.8 log copies/mL) and on cell HIV-1 DNA for 28 samples with undetectable plasma viral loads.

### 3.2. Nucleic acid extraction from blood plasma and leukocyte-enriched blood fraction

HIV-1 RNA was extracted from 500 µL of plasma using the Viral NA Large Volume kit on the MagNA Pure 96 instrument (Roche) after adding 50 µL of Carrier RNA (Qiagen). The 50 µL eluate was used for both Sanger and SMRT sequencing. The SX101 instrument extracted HIV RNA from 700 µL of plasma using with the Sentosa SX Virus Total Nucleic Acid Plus II Kit (Vela Diagnostics, Hamburg, Germany).

HIV-1 DNA was extracted from 250 µL of the leukocyte-enriched blood fraction using the MagNA Pure 96 DNA and Viral NA Small Volume Kit (Roche Diagnostics, Meylan, France) and was eluted in 100 µL. The three sequencing methods used this eluate for HIV-1 DNA amplification.

### 3.3. HIV-1 genotyping by Sanger sequencing

The protease (PR) and reverse transcriptase (RT) regions of the pol gene were amplified and sequenced on an ABI 3500 Genetic Analyzer (Applied Biosystems) using primers available in supplementary material. The integrase (IN) region was not analyzed.

### 3.4. HIV-1 polymerase sequencing using the Sentosa NGS platform

The Sentosa NGS platform (Vela Diagnostics, Hamburg, Germany) is a semi-automated platform for RNA extraction, amplification, sequencing, and analysis of HIV-1 polymerase in two assembled amplicons - one for the PR-RT region and one for the integrase region (IN). HIV sequencing was performed from plasma RNA and cellular DNA as previously described [12,13]. Vela software provided contiguous sequences and a list of mutations with a detection threshold of 3 % for each sample that we re-analyzed with the DeepChek-HIV v.3.27 software (Advanced Biological Laboratories, TherapyEdge).

### 3.5. SMRT sequencing of the HIV-1 polymerase (Pacific Biosciences)

RT-PCR amplification was performed using the aforementioned primers [17] and followed by a nested-PCR using barcoded primers to

obtain a 3359 base-paired amplicon (Supplementary Table 1). The DNA size and concentration of the nested PCR product was assessed by automated capillary electrophoresis. DNA was purified using AMPure PacBio beads (PacBio, California, USA) and then quantified with the Quantifluor DSDNA system operating on a Roche LC480 instrument. The barcoded samples were then pooled and the library was prepared using the SMRTbell Express Template Prep 2.0 (PacBio, California, USA) according to the manufacturer's instructions for sequencing on a Sequel IIe instrument (PacBio, California, USA). HiFi reads were generated on the instrument using the PacBio circular consensus sequencing (CCS) mode.

Bioinformatic analysis was carried out with a Snakemake workflow. The demultiplexing of HiFi reads with lima (v.2.2.0, https://github.com/PacificBiosciences/barcoding) was performed on reads with a quality threshold > Q30. The VCF file was then created from pbAA haplotypes (PacBio tool, v.0.1.3 https://github.com/PacificBioscience/s/pbAA). Variant calling was performed with Juliet (v1.12.0, PacBio, California, USA, https://github.com/PacificBiosciences/minorseq) listing the differences between each variant and the reference HIV-1 sequence HXB2. The minimum coverage depth was 200 reads to analyze the results. Haplotypes with a read count exceeding 2 % of the total number of reads were submitted to (i) perform a phylogenetic analysis for HIV-1 subtype determination; (ii) analyze the genotypic resistance of each haplotype prior to compilation using LoReHR (Long Read Haplotype Resistance, v2.3.2, homemade script); (iii) verify the absence of inter-sample contamination using UBIK software (v1.3.1, homemade script).

### 3.6. HIV-1 subtype determination and interpretation of genotypic susceptibility to antiretroviral drugs

HIV-1 subtypes were determined after phylogenetic analysis of the RT and PR sequences obtained with the Sanger method and the phylogeny of the polymerase sequence of the majority haplotypes obtained with SMRT sequencing. We used the reference sequence database from Los Alamos National Laboratory HIV (http://www.hiv.lanl.gov). The HIV-1 subtype obtained with Vela sequences was determined automatically using the software provided by Vela Diagnostics (SQ Reporter).

The resistance mutations list was the 2023 ANRS algorithm list (http://www.hivfrenchresistance.org/table.html). We also checked the International AIDS Society mutation list (https://www.iasusa.org/resources/hiv-drug-resistance-mutations/).

## 4. Results

### 4.1. Coverage and reproducibility of SMRT sequencing

HIV-1 polymerase SMRT sequencing was successfully performed for 67 plasma and cellular virus samples with a median coverage of 2277 (IQR, 1324-3872) reads. Clustering generated a median of 10 haplotypes (IQR, 2-16). The mean error rate of amplification and sequencing of the 8E5 clonal cell line polymerase was $1.095 \times 10^{-5}$ nucleotides. RAM detection reproducibility was measured on a virus culture supernatant harboring one mutation (L741 100 %) which was found with the same 100 % frequency in ten consecutive runs (see supplementary Table 2).

### 4.2. Analytical sensitivity

Fifty-five out of 83 plasma samples (66 %) were successfully sequenced using Sanger sequencing, while sequencing failures occurred with 21 samples in the RT region and 25 samples in the PR region (Table 1). Fifty-seven out of 83 plasma samples (69 %) were successfully sequenced using Vela NGS, while sequencing failures occurred with 19 PR-RT amplicons and 18 IN amplicons. Fifty-three out of 83 plasma samples (64 %) were successfully sequenced using SMRT sequencing.

The polymerase region was successfully sequenced by the three platforms in 98 % of plasma RNA samples when the viral load was above
<table><caption>**Table 1**
Sequencing detection rate on three platforms according to HIV-1 viral load.</caption><thead><tr><th rowspan="2"></th><th colspan="3">HIV-1 plasma RNA according to viral load</th><th rowspan="2">HIV-1<br>cellular<br>DNA N = 28</th></tr><tr><th>1.5 to &lt; 3<br>log copies/<br>mL N = 30</th><th>3 to &lt; 4 log<br>copies/mL<br>N = 12</th><th>≥ 4 log<br>copies/mL<br>N = 41</th></tr></thead><tbody><tr><td>Sanger<br>sequencing –<br>detection rate<sup>a</sup></td><td>12/30 (40<br>%)</td><td>12/12 (100<br>%)</td><td>41/41 (100<br>%)</td><td>21/28 (75<br>%)</td></tr><tr><td>Full PR-RT ( %<br>success)</td><td>5/30 (17 %)</td><td>10/12 (83<br>%)</td><td>40/41 (98<br>%)</td><td>17/28 (61<br>%)</td></tr><tr><td>PR region</td><td>8/30 (27 %)</td><td>10/12 (83<br>%)</td><td>40/41 (98<br>%)</td><td>20/28 (71<br>%)</td></tr><tr><td>RT region</td><td>9/30 (30 %)</td><td>12/12 (100<br>%)</td><td>41/41 (100<br>%)</td><td>18/28 (64<br>%)</td></tr><tr><td>Vela sequencing<br>– detection<br>rate<sup>a</sup></td><td>17/30 (57<br>%)</td><td>12 (100 %)</td><td>41/41 (100<br>%)</td><td>21/28 (75<br>%)</td></tr><tr><td>Full<br>polymerase ( %<br>success)</td><td>7/30 (23 %)</td><td>10/12 (83<br>%)</td><td>40/41 (98<br>%)</td><td>15/28 (54<br>%)</td></tr><tr><td>PR-RT region</td><td>12/30 (40<br>%)</td><td>11/12 (92<br>%)</td><td>41/41 (100<br>%)</td><td>18/28 (64<br>%)</td></tr><tr><td>IN region</td><td>12/30 (40<br>%)</td><td>11/12 (92<br>%)</td><td>40/41 (98<br>%)</td><td>18/28 (64<br>%)</td></tr><tr><td>SMRT<br>sequencing ( %<br>success)</td><td>5/30 (17 %)</td><td>8/12 (67 %)</td><td>40/41 (98<br>%)</td><td>14/28 (50<br>%)</td></tr></tbody></table>

4 log copies/mL (Table 1). The specimen PI04047 which failed to amplify could not undergo further analysis due to lack of stock. The success rate decreased to 83 % using Sanger or Vela sequencing and to 67 % using SMRT sequencing when the viral load was between 3 and 4 log copies/mL. The polymerase region was obtained in 17 % of the 30 plasma samples with a viral load below 3 log copies/mL when using Sanger or SMRT sequencing and in 23 % of the same samples using Vela NGS.

Seventeen out of 28 DNA samples (61 %) were successfully sequenced using Sanger when HIV-1 RNA was below 1.5 log copies/mL. Fifteen and fourteen out of 28 DNA samples (54 % and 50 %) were successfully sequenced using Vela and SMRT sequencing, respectively.

### 4.3. Determination of HIV-1 subtypes

We compared HIV-1 subtype determination obtained by the three sequencing platforms for the 41 plasma RNA samples with a viral load above 4 log copies/mL. SMRT sequencing and phylogeny identified 20 B subtypes, 12 CRF02, 2 C, 2 CRF01, 1 A1, 1 A6, 1 D and 1 CRF36; one amplification failed (Table 2). The agreement between SMRT and Sanger sequencing methods for HIV-1 subtyping was 98 % (39/40). One sample determined CRF36 with SMRT was subtyped CRF02 with Sanger. The agreement between SMRT sequencing and SQ Reporter (Vela Diagnostics) was 95 % (38/40). Two virus samples, one CRF01 and one CRF36 with SMRT, were both subtyped CRF02 with SQ Reporter.

### 4.4. Detection and quantification of RAMs

A total of 110 RAMs were identified using Sanger sequencing (59 in PR and 51 in RT regions; the IN region was not analyzed), 168 RAMs were identified using Vela NGS (71, 83 and 14 RAMs in PR, RT and IN regions, respectively) and 164 RAMs were identified using SMRT sequencing (67, 83 and 14 RAMs in PR, RT and IN regions, respectively) (Fig. 1).

All of the 96 plasma RNA mutations identified by Sanger sequencing were detected using Vela NGS with frequencies ranging from 5 % to 100 % (7 minority resistant variants and 89 RAMs with frequencies greater than 20 %). Similarly, SMRT sequencing (variant calling analysis)

detected all but one RAM (RT K101R 13 % according to Vela NGS) with frequencies ranging from 5 % to 100 % (9 minority resistant variants and 86 RAMs with frequencies greater than 20 %).

Eleven out of the 13 cellular DNA mutations identified by Sanger sequencing were detected using Vela NGS with frequencies ranging from 44 % to 99 %, while two RAMs (RT M184I and M230I with frequencies of 100 % according to SMRT sequencing) were missed. SMRT sequencing detected all but one (PR L63P 44 % according to Vela) of the 13 RAMs with frequencies ranging from 24 % to 100 %. Conversely, Sanger sequencing missed 12/127 RAMs (9.4 %) detected in Vela and SMRT sequences at the 5 % threshold (according to Vela), 8/121 RAMs (6.6 %) at the 10 % threshold and 7/116 RAMs (6 %) at the 20 % threshold.

We then compared SMRT sequencing and Vela NGS for complete polymerase sequencing at sensitivity thresholds of 5 %, 10 % and 20 % (Table 3). SMRT sequencing (variant calling analysis) detected 109 of the 120 RAMs detected using Vela NGS at the 5 % threshold (concordance 91 %), 106/115 at the 10 % threshold (concordance 92 %) and 102/108 at the 20 % threshold (concordance 94 %). Among the eleven RAMs missed by SMRT sequencing at the 5 % threshold, five had frequencies below 20 % and six had frequencies over 20 % including three RAMs detected by Sanger sequencing (RT M184V 100 %, IN T66I 100 % and L74M 21 %) and three were not detected (RT V179I 31 %, PR A71T 38 % and PR V11I 65 %). Eight more RAMs were detected using only SMRT sequencing at the sensitivity threshold of 5 % (Table 3), seven RAMs were detected with frequencies below 20 % and one RT T215N at 20 %.

SMRT sequencing (variant calling analysis) detected 29 of the 33 cellular DNA RAMs identified using Vela NGS at the 5 % threshold (concordance 88 %). Four RAMs were missed by SMRT sequencing: three with frequencies below 20 % and one PR L63P at 44 %. Six more RAMs were detected using only SMRT sequencing at the 5 % threshold: one with a frequency of 18 % and five mutations with frequencies over 20 % (RT E44D 58 %, M184I 100 %, G190A 100 %, T215I 100 % and M230I 100 %).

The frequencies of the 143 RAMs determined by both NGS platforms in the quasispecies were well correlated (Spearman correlation $\rho$= 0.82; $P$ < 0.0001) (Fig. 2).

### 4.5. Comparison of variant calling and haplotyping analyses using SMRT sequencing

The haplotyping method identified 148 of the 170 RAMs identified by variant calling analysis (frequencies 2-100 %) in the SMRT sequencing dataset. The 22 RAMs missing in the haplotypes had frequencies ranging from 2 to 9 %. Only six mutations were missing at the 5 % threshold for RAM analysis - two in the PR region (L63P 14.6 % and V11I 6.3 %) and four in the RT region (D67N 7.1 %, T69N 12.2 %, V106I 5.8 % and V179I 9 %), with no systematic error being highlighted.

## 5. Discussion

Long-read SMRT sequencing combined with variant calling analysis and haplotype-resolved analysis have been developed for HIV-1 resistance genotyping. This NGS method was suitable for characterizing polymerase mutations in RNA and DNA matrices.

Comparison with Sanger sequencing and Vela NGS showed that the HIV-1 subtype did not induce amplification bias and that subtyping correlated well with all three methods (95 % agreement). We also found that the amplification success rate was dependent on the viral load for the three sequencing methods with a cut-off at 3 log copies/mL to achieve sensitivity above 90 % (94 % using Sanger and Vela sequencing and 91 % using SMRT sequencing). Similarly, the HIV-1 DNA genotyping success rate was lower (50 % to 65 %) than that obtained with plasma HIV-1 RNA, probably due to the low quantity of virus DNA in patients with prolonged undetectable HIV-1 RNA. The difficulties for

<footnote>a Amplification and sequencing of at least one region (PR and/or RT and/or IN)</footnote>
<table><caption>**Table 2**

Characteristics of 41 plasma samples and HIV-1 subtyping using three sequencing methods.</caption><thead><tr><th>Sample Identification</th><th>Viral load (log copies/mL) or DNA</th><th>SMRT read count</th><th>SMRT haplotypes</th><th>SMRT subtype</th><th>Sanger subtype</th><th>Vela subtype</th></tr></thead><tbody><tr><td>RO02240</td><td>6.8</td><td>5345</td><td>14</td><td>CRF02</td><td>NON B</td><td>NON B</td></tr><tr><td>TA36437</td><td>6.57</td><td>557</td><td>19</td><td>CRF36</td><td>CRF02</td><td>CRF02</td></tr><tr><td>DE00732</td><td>6.2</td><td>558</td><td>16</td><td>A1</td><td>A1</td><td>A1</td></tr><tr><td>KA35524</td><td>6.18</td><td>1287</td><td>20</td><td>B</td><td>B</td><td>B</td></tr><tr><td>VO06602</td><td>6.17</td><td>2956</td><td>12</td><td>D</td><td>D</td><td>D</td></tr><tr><td>DO01307</td><td>6.02</td><td>1751</td><td>7</td><td>CRF02</td><td>CRF02</td><td>CRF02</td></tr><tr><td>VI33040</td><td>5.83</td><td>7122</td><td>18</td><td>B</td><td>B</td><td>B</td></tr><tr><td>CA36332</td><td>5.8</td><td>1361</td><td>19</td><td>B</td><td>B</td><td>B</td></tr><tr><td>ST02905</td><td>5.74</td><td>2277</td><td>15</td><td>C</td><td>C</td><td>C</td></tr><tr><td>HO35641</td><td>5.72</td><td>1970</td><td>12</td><td>CRF02</td><td>CRF02</td><td>CRF02</td></tr><tr><td>CA04831</td><td>5.48</td><td>3714</td><td>14</td><td>CRF02</td><td>NON B</td><td>NON B</td></tr><tr><td>CH02549</td><td>5.47</td><td>2917</td><td>13</td><td>B</td><td>B</td><td>B</td></tr><tr><td>LU33921</td><td>5.37</td><td>1102</td><td>13</td><td>A6</td><td>NONB</td><td>NONB</td></tr><tr><td>MA32936</td><td>5.32</td><td>1847</td><td>12</td><td>B</td><td>B</td><td>B</td></tr><tr><td>AG00435</td><td>5.29</td><td>282</td><td>26</td><td>CRF02</td><td>CRF02</td><td>CRF02</td></tr><tr><td>MA33131</td><td>5.26</td><td>3692</td><td>3</td><td>CRF02</td><td>CRF02</td><td>CRF02</td></tr><tr><td>BA00519</td><td>5.18</td><td>608</td><td>19</td><td>B</td><td>B</td><td>B</td></tr><tr><td>BI06331</td><td>5.14</td><td>2725</td><td>21</td><td>B</td><td>B</td><td>B</td></tr><tr><td>N 02946</td><td>5.13</td><td>320</td><td>11</td><td>CRF02</td><td>CRF02</td><td>CRF02</td></tr><tr><td>CA35136</td><td>5.06</td><td>1114</td><td>20</td><td>B</td><td>B</td><td>B</td></tr><tr><td>VI02039</td><td>5</td><td>3320</td><td>18</td><td>B</td><td>B</td><td>B</td></tr><tr><td>ES01124</td><td>5</td><td>4911</td><td>24</td><td>CRF02</td><td>CRF02</td><td>CRF02</td></tr><tr><td>BE02956</td><td>4.98</td><td>1209</td><td>4</td><td>B</td><td>B</td><td>B</td></tr><tr><td>MU034631</td><td>4.84</td><td>1233</td><td>18</td><td>B</td><td>B</td><td>B</td></tr><tr><td>PI04047</td><td>4.83</td><td>NA<sup>a</sup></td><td>NA</td><td>NA</td><td>NON B</td><td>CRF02</td></tr><tr><td>BO06441</td><td>4.8</td><td>3354</td><td>1</td><td>CRF01</td><td>CRF01</td><td>CRF01</td></tr><tr><td>CH04746</td><td>4.65</td><td>3015</td><td>9</td><td>CRF02</td><td>NON B</td><td>CRF02</td></tr><tr><td>MA01149</td><td>4.6</td><td>1269</td><td>10</td><td>B</td><td>B</td><td>B</td></tr><tr><td>DO35035</td><td>4.56</td><td>860</td><td>9</td><td>B</td><td>B</td><td>B</td></tr><tr><td>NT02151</td><td>4.5</td><td>5485</td><td>19</td><td>B</td><td>B</td><td>B</td></tr><tr><td>SO03532</td><td>4.4</td><td>10710</td><td>8</td><td>B</td><td>B</td><td>B</td></tr><tr><td>KA03522</td><td>4.38</td><td>4805</td><td>1</td><td>CRF02</td><td>NON B</td><td>CRF02</td></tr><tr><td>TR33551</td><td>4.35</td><td>14223</td><td>18</td><td>B</td><td>B</td><td>B</td></tr><tr><td>AL01233</td><td>4.32</td><td>875</td><td>5</td><td>B</td><td>B</td><td>B</td></tr><tr><td>SO02142</td><td>4.3</td><td>6864</td><td>18</td><td>CRF02</td><td>CRF02</td><td>CRF02</td></tr><tr><td>DE06033</td><td>4.13</td><td>13052</td><td>14</td><td>CRF01</td><td>NON B</td><td>CRF02</td></tr><tr><td>SK02535</td><td>4.1</td><td>8993</td><td>14</td><td>CRF02</td><td>NON B</td><td>CRF02</td></tr><tr><td>CH02729</td><td>4.07</td><td>2756</td><td>10</td><td>B</td><td>B</td><td>B</td></tr><tr><td>MA04135</td><td>4.04</td><td>6707</td><td>19</td><td>B</td><td>B</td><td>B</td></tr><tr><td>DU33932</td><td>4.01</td><td>1464</td><td>12</td><td>B</td><td>B</td><td>B</td></tr><tr><td>SA33024</td><td>4.01</td><td>1082</td><td>1</td><td>C</td><td>C</td><td>C</td></tr></tbody></table>

<figure><img src="image_4.png" /><figcaption>Fig. 1. Positions and number of resistance-associated mutations identified in the HIV-1 polymerase region from 111 clinical samples using Sanger, Vela, and SMRT sequencing.</figcaption></figure>

Each bar represents the total number of mutations at one position of the PR, RT or IN region identified by the indicated sequencing method from 83 plasma samples and 28 cellular samples. Sanger sequencing was performed on PR and RT regions while Vela and SMRT sequencing were performed on PR, RT and IN regions.

<footnote>a NA: not amplified</footnote>
<table><caption>**Table 3**
Concordance between SMRT and Vela sequencing methods for detecting RAMs.</caption><thead><tr><th></th><th>RAM<sup>a</sup><br>frequency 5 to<br>&lt; 10 %</th><th>RAM<br>frequency 10<br>to &lt; 20 %</th><th>RAM<br>frequency<br>≥ 20 %</th><th>Concordance</th></tr></thead><tbody><tr><td colspan="5">Mutations detected by Vela sequencing</td></tr><tr><td>Mutations<br>detected using<br>SMRT-Juliet<sup>b</sup></td><td>3/5</td><td>4/7</td><td>102/108</td><td>91 %</td></tr><tr><td>Mutations<br>detected using<br>SMRT-<br>LoReHR<sup>c</sup></td><td>1/5</td><td>2/7</td><td>102/108</td><td>87 %</td></tr><tr><td colspan="5">Mutations detected by SMRT sequencing<br>(variant calling)</td></tr><tr><td>Mutations<br>detected using<br>Vela</td><td>5/9</td><td>7/10</td><td>98/99</td><td>93 %</td></tr></tbody></table>

<sup>a</sup> RAMs: Resistance Associated Mutations

<sup>b</sup> Juliet: variant calling software

<sup>c</sup> LoReHR: Long Read Haplotyping resistance software

DNA sequencing using Vela NGS have been previously described with a complete or partial sequencing failure rate of 42 % [18].

Vela NGS and SMRT sequencing were 98 % concordant with Sanger sequencing for identifying mutations isolated from plasma or cellular samples, as previously highlighted in a study evaluating SMRT sequencing for detecting Sanger mutations in the HIV-1 polymerase [16]. Sanger sequencing detected majority mutations above the 20 % threshold but also 7 or 9 minority resistant variants, according to Vela NGS or SMRT sequencing, respectively. This result illustrates the difficulty in defining a threshold for resistance interpretation. Indeed, a 20 % threshold analysis would exclude minority variants detected by Sanger sequencing. Therefore, the 5 % threshold showing the best concordance with Sanger sequencing and an increased sensitivity without overestimation of resistance has been proposed [19,20].

The Vela sequencing method for PR, RT and IN regions was previously validated in our laboratory [9,12,13]. At the 20 % threshold, the agreement between Vela and SMRT sequencing was 94 % (102 RAMs detected by both platforms, 7 RAMs detected by only one platform). Three of the seven RAMs were also missed with Sanger sequencing and three others were in samples with a viral load below 3 log copies/mL. Discrepancies were observed mainly when RAM frequencies were below 20 %: 7 RAMs accounting for 5 % to 20 % of the quasispecies were detected only by SMRT sequencing (37 %) and 5 others were detected

only by Vela sequencing (42 %). Nevertheless, the mutation frequencies in the quasispecies determined by both sequencing methods were correlated (Spearman correlation $\rho$ = 0.82; $P$ < 0.0001). A previous study also found a good correlation between the mutation frequencies measured using SMRT sequencing and Illumina [16]. In this context we showed that the genotypic monitoring of HIV-1 resistance using short-read sequencing can be switched to long-read SMRT sequencing while maintaining consistency in terms of RAM characterization.

Haplotype-resolved sequencing is an approach specific to long-read third-generation sequencing, available only with SMRT sequencing [21]. We used a clustering method to generate haplotypes with reads accounting for more than 2 % of the total read count. This approach correlated well with the variant-calling method. Only six mutations were missing after haplotyping. Long-read sequencing combined with haplotyping analysis may be helpful to resolve resistance analysis when the quasispecies harbour mutations that must be combined to confer drug resistance. This concerns both transmitted resistance and treatment failures and provides additional information to Sanger or short-read sequencing to select drug therapies. In addition, long-read sequencing on the Sequel Ile instrument is adequate for testing a large number of samples. Further studies are needed to analyze the impact on the virological response.

We developed an in-house method for HIV-1 resistance genotyping using SMRT sequencing on a Sequel Ile instrument. The full-length polymerase can be characterized in various HIV-1 subtypes on RNA and DNA matrices. Expanded access to antiretroviral treatments implies that HIV-1 genotyping is crucial for characterizing HIV resistance epidemiology and for choosing an active drug combination for the individuals.

## Funding

This study was supported by INFINITY (INSERM UMR1291).

## CRediT authorship contribution statement

**Stéphanie Raymond:** Writing – original draft, Validation, Investigation, Formal analysis, Data curation. **Nicolas Jeanne:** Writing – review & editing, Software, Methodology. **Camille Vellas:** Conceptualization. **Florence Nicot:** Writing – review & editing, Methodology, Conceptualization. **Karine Saune:** Validation, Methodology. **Noémie Ranger:** Methodology, Formal analysis, Data curation. **Justine Latour:** Methodology, Formal analysis. **Romain Carcenac:** Validation, Formal analysis. **Agnès Harter:** Validation, Methodology, Formal

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Comparison of Vela NGS and SMRT sequencing for the quantifying mutated variants. Each point represents one of the 143 mutated variants quantified by both NGS platforms. The Spearman correlation was $\rho$= 0.8212 [0.7572 - 0.8695]; $P$ < 0.0001.</figcaption></figure>
**analysis. Pierre Delobel:** Supervision, Conceptualization. **Jacques Izopet:** Writing – review & editing, Supervision, Funding acquisition, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Supplementary materials

Supplementary material associated with this article can be found, in
the online version, at doi:10.1016/j.jcv.2024.105717.

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