Development of a Next-Generation Sequencing Protocol for Assessing Lenacapavir Resistance in HIV-1 Capsid

Development of a Next-Generation Sequencing Protocol for Assessing Lenacapavir Resistance in HIV-1 Capsid | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL Journal of Medical Virology This is a preprint and has not been peer reviewed. Data may be preliminary. 13 June 2025 V1 Latest version Share on Development of a Next-Generation Sequencing Protocol for Assessing Lenacapavir Resistance in HIV-1 Capsid Authors : Omar El Khalili , Collins Ambe Chenwi , Daniele Spalletta 0009-0009-4932-5344 , Greta Marchegiani , Luca Carioti 0000-0003-1713-8682 , Hossein Eizadi Moghadam , Ada Bertoli , Vincenzo Spagnuolo , M. Santoro , F. Ceccherini-Silberstein , and Maria Concetta Bellocchi 0000-0001-7717-2343 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.174981969.90487577/v1 Published Journal of Medical Virology Version of record Peer review timeline 426 views 169 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Lenacapavir (LEN) is a first-in-class capsid inhibitor (CAI) that targets multiple stages of the HIV-1 lifecycle, showing efficacy in heavily treatment-experienced (HTE) individuals with multidrug-resistance (MDR) and in pre-exposure prophylaxis (PrEP). This study aimed to characterize a novel home-made next-generation sequencing (NGS) protocol targeting HIV-1 capsid (CA) region using both HIV-1 RNA from plasma and HIV-1 DNA from peripheral-blood-mononuclear-cells (PBMCs). Accordingly, 60 samples (41 HIV-1 RNA, 19 HIV-1 DNA) with various HIV-1 subtypes and viremia levels were tested. Molecular amplification was successful in 83.3% of cases (75.6% HIV-1 RNA and 100% HIV-1 DNA), with sequencing achieved in 92.0% of amplified samples (87.1% HIV-1 RNA and 100% HIV-1 DNA). The protocol showed high NGS performance with HIV-1 RNA samples with viremia >500 copies/mL (92.6%) and a slight impact of subtype-associated variability (subtype B: amplification and sequencing 86.0% and 91.9%; non-B: 76.5% and 92.3%, respectively). Reproducibility was fully confirmed by pairwise similarity analyses at 10% and 20% frequency cutoff, upon reprocessing 13 HIV-1 RNA samples. This protocol provides an important tool for personalized HIV-1 treatment with CAI-based strategies, enabling efficient characterization of LEN resistance mutations in the CA region across different HIV-1 subtypes, using both DNA and RNA samples. Development of a Next-Generation Sequencing Protocol for Assessing Lenacapavir Resistance in HIV-1 Capsid Omar El Khalili 1,2§ , Collins Ambe Chenwi 1,2,3§ , Daniele Spalletta 1,2 , Greta Marchegiani 1,2 , Luca Carioti 1 , Hossein Eizadi Moghadam 1 , Ada Bertoli 1,4 , Vincenzo Spagnuolo 5 , Maria Mercedes Santoro 1 , Francesca Ceccherini-Silberstein 1# , Maria Concetta Bellocchi 1#* Affiliations 1 Department of Experimental Medicine, University of Rome Tor Vergata, Rome, Italy 2 Ph.D. Course in Microbiology, Immunology, Infectious Diseases, and Transplants (MIMIT), University of Rome Tor Vergata, Rome, Italy 3 Chantal Biya International Reference Centre for Research on HIV and AIDS Prevention and Management (CIRCB) 4 Virology Unit, Tor Vergata University Hospital, Rome, Italy 5 Infectious Diseases Unit, San Raffaele Scientific Institute, Milan, Italy § Equally contribution to this work as first author # Equally contribution to this work as last author Email addresses : Omar El Khalili ( [email protected] ), Collins Ambe Chenwi ( [email protected] ), Daniele Spalletta ( [email protected] ), Greta Marchegiani ( [email protected] ), Luca Carioti ( [email protected] ), Hossein Eizadi Moghadam ( [email protected] ), Ada Bertoli ( [email protected] ), Vincenzo Spagnuolo ( [email protected] ), Maria Mercedes Santoro ( [email protected] ) Francesca Ceccherini-Silberstein ( [email protected] ), *Corresponding author: Maria Concetta Bellocchi ( [email protected] ) Ethical considerations For this study, we used residual anonymized specimens from routine clinical practice and/or research activities within two cohorts of PWH living in Italy: the PRESTIGIO Registry (https://trials-ice2.advicepharma.com/PRESTIGIO/) and the ICONA foundation (https://www.fondazioneicona.org/). Approval by the Ethics Committee was deemed unnecessary under Italian law for residual anonymous samples evaluated for diagnostic purposes since this was not considered a clinical trial of medicinal products for clinical use (Art. 6 and Art. 9, Law Decree 211/2003). For residual samples obtained from research activities, approval was obtained by the Ethic Committee of all the participating centers involved in the above-mentioned Italian cohorts. Short title NGS Protocol for LEN Resistance in HIV-1 Development of a Next-Generation Sequencing Protocol for Assessing Lenacapavir Resistance in HIV-1 Capsid ABSTRACT Lenacapavir (LEN) is a first-in-class capsid inhibitor (CAI) that targets multiple stages of the HIV-1 lifecycle, showing efficacy in heavily treatment-experienced (HTE) individuals with multidrug-resistance (MDR) and in pre-exposure prophylaxis (PrEP). This study aimed to characterize a novel home-made next-generation sequencing (NGS) protocol targeting HIV-1 capsid (CA) region using both HIV-1 RNA from plasma and HIV-1 DNA from peripheral-blood-mononuclear-cells (PBMCs). Accordingly, 60 samples (41 HIV-1 RNA, 19 HIV-1 DNA) with various HIV-1 subtypes and viremia levels were tested. Molecular amplification was successful in 83.3% of cases (75.6% HIV-1 RNA and 100% HIV-1 DNA), with sequencing achieved in 92.0% of amplified samples (87.1% HIV-1 RNA and 100% HIV-1 DNA). The protocol showed high NGS performance with HIV-1 RNA samples with viremia subtype-associated variability (subtype B: amplification and sequencing 86.0% and 91.9%; non-B: 76.5% and 92.3%, respectively). Reproducibility was fully confirmed by pairwise similarity analyses at 10% and 20% frequency cutoff , upon reprocessing 13 HIV-1 RNA samples. This protocol provides an important tool for personalized HIV-1 treatment with CAI-based strategies, enabling efficient characterization of LEN resistance mutations in the CA region across different HIV-1 subtypes, using both DNA and RNA samples. Keywords (max 6) Capsid| HIV-1| lenacapavir| resistance| next-generation sequencing 1 | Introduction Despite the progress made in improving the efficacy and safety of antiretroviral therapy (ART), HIV-1 cure is not feasible and therefore continues to be a major global public health issue 1 . HIV-1 infection remains a serious concern in a proportion of heavily treatment experienced (HTE) people with HIV-1 (PWH) who harbor a multidrug-resistance (MDR) virus, often as a result of exposure to suboptimal treatment and multiple treatment failures 2 . For this fragile population ART options can also be limited. In this context, strategies for prevention of new infections and treatment are fundamental for reducing the individual and societal burden of HIV-1. In this light, a continuous development of new agents active against resistant variants of HIV-1 and targeting novel mechanisms of action is required, in order to provide simpler and more efficacious treatment options to all PWH, irrespective of their prior treatment history. Among new antiretrovirals, lenacapavir (LEN) is a novel injectable first-in-class HIV-1 capsid inhibitor (CAI). It inhibits selectively multiple stages of capsid function, by directly binding to the interface between the capsid protein subunits, preventing the nuclear import of proviral DNA, hindering virus assembly and release by interfering with the function of Gag/Gag-pol genes, and thereby generating malformed capsids 3 . LEN use is indicated, in combination with other antiretrovirals, for the treatment of HTE individuals with MDR and has recently shown high efficacy for prevention (more than 99%) when used as pre-exposure prophylaxis (PrEP) in diverse populations (cisgender women, cisgender gay, bisexual, and other men, transgender women, transgender men, and gender-nonbinary persons) 4–6 . Integrating into clinical routine new pharmacological targets, such as the capsid, is crucial for optimizing treatment strategies and improving clinical outcomes. Due to the novelty of this target, a method for characterizing the resistance associated mutations in the capsid is mandatory. Margot et al. in a recent study used the Sanger sequencing method to evaluate the capsid resistance mutations in HIV-1 RNA plasma samples 7 . However, there are limitations of Sanger sequencing in detecting low-frequency variants and providing adequate resistance profiles 8 . This has led to the need for the implementation of the genotypic test for the capsid, by using next-generation sequencing (NGS) technologies, which offers greater sensitivity and accuracy in identifying resistance-associated mutations. The advent of NGS has redefined genome sequencing techniques. This technology sequences millions of fragments simultaneously per run, enabling the detection of minority quasispecies with mutations occurring at frequencies below 20%, with an accuracy greater than 99%. Evidence suggests that some mutations present in HIV-1 resistant minority variants may be clinically relevant 9,10 . The aim of this study was to develop a novel NGS protocol to sequence HIV-1 capsid region for assessing resistance to LEN by using both HIV-1 RNA from plasma samples and HIV-1 DNA from peripheral blood mononuclear cells (PBMCs) matrices, with diverse subtypes and viremia levels. 2 | Materials and Methods 2.1 | Clinical samples For the protocol development, residual anonymized specimens were used, originating from routine clinical practice and/or research activities within two cohorts of PWH living in Italy: the PRESTIGIO Registry (https://trials-ice2.advicepharma.com/PRESTIGIO/) and the ICONA Foundation (https://www.fondazioneicona.org/). Ethic Committee approval was deemed unnecessary under Italian law for residual anonymized samples used for diagnostic purposes since this was not considered a clinical trial of medicinal products for clinical use (Art. 6 and Art. 9, Law Decree 211/2003). For residual anonymized samples obtained from research activities, approval was obtained by the Ethic Committee of each participating center involved in the above-mentioned Italian cohorts. 2.2 | HIV‐1 extraction and amplification Viral RNA was extracted from 1 mL of plasma using the QIAamp Viral RNA Mini Kit (Qiagen GmbH, Hilden, Germany), after ultracentrifugation at 23,000 g for 2 hours at 4°C, following the manufacturer’s instructions, while DNA was extracted from a pellet of 2–5 × 10⁶ PBMCs using the High Pure PCR Template Preparation Kit (Roche Diagnostics, Basel, Switzerland). HIV-1 RNA from plasma and HIV-1 DNA from PBMCs were subjected to reverse transcription/amplification and amplification, respectively, using the SuperScript III One-Step RT-PCR system for long templates (Invitrogen, Carlsbad, CA, USA). In detail, each 50 µL reaction contained: 10 µL of extracted viral genome, 25 µL of 2x reaction mix, 8 µL of MgSO₄ (5 mmol/L), 3 µL of DNase/RNase-free water, 0.75 µL each of forward and reverse primers (10 pmol/µL), 1 µL of RNase Out (40 U/µL; replaced with 1 µL of water for HIV-1 DNA samples) and 1.5 µL of RT/Taq enzyme. Thermal cycler conditions were 50°C for 30 minutes, 94°C for 2 minutes, followed by 45 cycles of 95°C for 30 seconds, 53°C for 30 seconds, and 72°C for 2 minutes; final extension at 72°C for 10 minutes. When necessary, a nested PCR was performed using AmpliTaq Gold DNA polymerase (Life Technologies, Carlsbad CA, USA) with a 50 µL reaction mix containing: 5 µL of first-round PCR product, 33 µL of DNase/RNase-free water, 5 µL of PCR buffer (10x), 3.5 µL of MgCl 2 (25 mM), 1 µL of dNTPs (10 mmol/L), 0.9 µL each of forward and reverse primers (10 pmol/µL) and 0.7 µL of Taq polymerase. Thermal cycler conditions were 93°C for 12 minutes, 40 cycles of 95°C for 30 seconds, 56°C for 30 seconds, and 72°C for 2 minutes, with a final extension at 72°C for 10 minutes. Amplicons were analyzed by agarose gel electrophoresis to confirm band sizes (See Figure 1). Gag specific primers and thermal profiles were adapted from Soria et al. 11 (See Table 1). FIGURE 1 | Mapping of HIV-1 Capsid Amplification Regions TABLE 1| Primer sequence and thermal profiles for amplification Gag Gag FW1 GCCTCAATAAAGCTTGCCTT 522-541 1 cycle 50°C, 30 min c 1 cycle to 94° C for 2 min 45 cycles (95°C 30 sec, 53°C 30 sec, 72 °C 2 min) 1 cycle at 72° C 10 min I RT/PCR Gag REV1 CCAATTCCCCCTATCATTTTT 2384–2404 Gag FW1 GCCTCAATAAAGCTTGCCTT 522-541 1 cycle to 93° C for 12 min 40 cycles (95°C 30 sec, 56°C 30 sec, 72 °C 2 min) 1 cycle at 72° C 10 min II PCR Nested Gag REV2 CCCTAAAAAATTAGCCTGTCT 2074-2094 a FW: Sense primer, REV: Antisense primer. b Positions according to HXB2 (Accession number: K03455.1) Numbering System. c Removed in case of HIV-1 DNA specimens. Min: minutes; sec: seconds. 2.3 | HIV-1 next generation sequencing Each amplified sample was purified using (0.8x ratio) Ampure XP Beads (Beckman Coulter, Pasadena, CA, USA), then quantified using Qubit dsDNA HS Assay Kit (Invitrogen, Carlsbad, CA, USA) with Qubit 2.0 Fluorometer (Life Technologies, Carlsbad, CA, USA). For each sample, 1 ng of amplicon was involved in a tagmentation reaction by Nextera XT DNA Library Kit (Illumina Inc., San Diego, CA, USA) and uniquely indexed with Nextera XT Index Kit v2 (Illumina Inc., San Diego, CA, USA) following the manufacturer’s instructions. After a second purification (0.6x ratio) and second quantification, the libraries were diluted at 4 nM and pooled. Finally, 15 pM of the denatured pool was sequenced paired-end with MiSeq Reagent Kits v2 (2x 250) (Illumina Inc., San Diego, CA, USA) with 6–10% of PhiX Control V3 library to monitor sequencing quality 12 . 2.4 | Bioinformatics analyses, mutational pattern and subtype assignment NGS data obtained as FASTQ files were analyzed using HIVdb Stanford algorithm (version 9.8; https://hivdb.stanford.edu/) to determine the mutational pattern of each sample. Sequences were considered valid with at least 100 coverage reads per position. The consensus sequences for all samples were generated with prevalence cutoffs of 5%, 10%, and 20% mutation detection threshold (MDT) as defined by the Stanford HIDVB website (https://hivdb.stanford.edu/hivdb-capsid/by-reads/). The HIV-1 subtype was assessed using two automated tools, COMET (https://comet.lih.lu/) and Stanford (https://hivdb.stanford.edu/) and the results for each sample were compared with those obtained from a previous subtyping analysis on protease/reverse transcriptase. In addition, a quality control of the raw data obtained in the FASTQ format was performed with Trimmomatic 13 software in order to remove adapters, PCR primers and poor-quality reads. FASTQ files were analyzed with VirVarSeq software version 1 14 using (Accession number K03455.1) reference. 2.5 | Efficiency assessment The efficiency assessment of the protocol was conducted, considering the main variables that could influence the success rate: the different compartment (HIV-1 RNA from plasma and HIV-1 DNA from PBMCs), the HIV-1 subtype (B vs. non-B), and viremia levels for the HIV-1 RNA samples. In particular, viremia levels were stratified according to the following strata: >50-500; >500-1,000; of the two main steps of the process (molecular amplification and sequencing on the Miseq platform) were considered separately. 2.6 | Reproducibility assessment For both precision and reproducibility testing, the variability in the result is determined based on nucleotide sequence similarity by comparison with the consensus sequences derived from the replicates (at 5%, 10%, and 20% cutoffs, as described before.) Briefly, sequences were aligned with the HXB2 reference for Gag and CA regions using MAFFT v7.475. The CA region (positions 397–1089 of Gag or 1186–1878 relative to HXB2, resulting in 693 nucleotides and 231 residues) was manually extracted with BioEdit v7.7. Pairwise sequence similarity for each sample across two runs was assessed using the Needleman-Wunsch algorithm implemented in EMBOSS Needle 15 . Acceptance criteria was more than 90% of pairwise comparisons with at least 98% identical (with non-matching mixtures counted as a difference) 16 . 2.7 | Statistical analysis Descriptive statistics were expressed as median values and the interquartile range (IQR) for continuous variables and the number (percentage) for categorical variables. 3 | Results 3.1 | Sample characteristics Sixty samples were analyzed, of which 41 (68.3%) were of HIV-1 RNA, obtained from plasma samples, and 19 (31.7%) were of HIV-1 DNA, extracted from PBMCs. All plasma samples had detectable viremia, with a median [IQR] value of 2,014 [183-12,070] HIV-1 RNA copies/mL. Among plasma samples, 18 (43.9%) had HIV-1 RNA levels in the range samples; >500–1,000 copies/mL: 4 samples), 13 (31.7%) had HIV-1 RNA levels in the range >1,000-10,000 copies/mL, and 10 (24.4%) presented HIV-1 RNA levels > 10,000 copies/mL (See Table 2). Overall, HIV-1 subtype B was detected in 43 samples (71.7%), of which 25 were HIV-1 RNA samples and 18 were HIV-1 DNA samples. Non-B subtypes were identified in the remaining 17 samples (28.3%), predominantly among HIV-1 RNA (n=16) and in only one HIV-1 DNA sample (see Table 2). The non-B subtypes included 4 samples with CRF02_AG (6.7%), 3 with subtype F1 (5.0%), 2 with the DF recombinant form (3.3%, one in the HIV-1 DNA sample), 2 with subtype C (3.3%), and 1 with subtype G (1.7%). The remaining 5 samples (8.3%) harbored other recombinant forms: CRF09_cpx (n=1), CRF12_BF (n=1), CRF41_CD (n=1), CRF42_BF (n=1), and CRF60_BC (n=1). TABLE 2 | Sample characteristics Sample, N (%) 41 (68.3) 19 (31.7) HIV-1 RNA, copies/mL, Median (IQR) 2,014 (183–12,070) / HIV-1 RNA, copies/mL, Minimum 52 / HIV-1 RNA, copies/mL, Maximum 9,4 x 10 6 / Subtype B, N (%) b 25 (61.0) 18 (94.7) HIV-1 RNA ranges, N (%) b >50–1,000 copies/mL 18 (43.9) / a. >50 – 500 copies/mL 14 (34.1) / b. >500 – 1,000 copies/mL 4 (9.8) / >1,000–10,000 copies/mL 13 (31.7) / >10,000 copies/mL 10 (24.4) / a HIV-1 DNA from PBMCs were obtained by individuals with suppressed viremia. b Percentages refer to subgroup (41 HIV-1 RNA and 19 HIV-1 DNA). IQR: interquartile range; PBMCs: peripheral-blood-mononuclear-cells 3.2 | Efficiency of the developed NGS protocol The main factors potentially affecting the success rate of the developed NGS protocol for CA region characterization were carefully evaluated. These included the viral genome specimen (HIV-1 RNA vs. HIV-1 DNA), the HIV-1 subtype, and the level of viremia in HIV-1 RNA samples. The analysis was performed by evaluating both the amplification efficiency of the CA region and the sequencing efficiency in samples with successful amplification, as summarized in Table 3. TABLE 3 | Amplification and sequencing performance on HIV-1 RNA and HIV-1 DNA HIV-1 RNA (N=41) Overall, N (%) 31 (75.6) 27/31 (87.1) By HIV-1 subtype B, N=25 19 (76.0) 16/19 (84.2) Non-B, N=16 12 (75.0) 11/12 (91.7) By HIV-1 RNA ranges >50–1,000 copies/ml, N=18 9 (50.0) 5/9 (55.6) a. >50 – 500 copies/mL, N=14 6 (42.9) 2/6 (33.3) b. >500–1,000 copies/mL, N=4 3 (75.0) 3/3 (100) >1,000–10,000 copies/mL N=13 12 (92.3) 12/12 (100) >10,000 copies/mL, N=10 10 (100) 10/10 (100) HIV-1 DNA (N=19) Overall, N (%) 19 (100) 19/19 (100) By HIV-1 subtype B, N=18 18 (100) 18/18 (100) Non-B, N=1 1 (100) 1/1 (100) NGS: next generation sequencing 3.2.1 | Efficiency by sample compartment: HIV-1 RNA and HIV-1 DNA Samples The first variable evaluated to assess the efficiency of the developed NGS protocol was the viral genome compartment, considering different sample types: HIV-1 RNA from plasma sample and HIV-1 DNA extracted from PBMCs. Overall, CA region amplification was successfully achieved for 50 of the 60 samples, with a success rate of 83.3%. In detail, 31 out of 41 (75.6%) HIV-1 RNA samples were amplified, while 100% efficiency was obtained with HIV-1 DNA samples, with all 19 cases successfully amplified. Regarding sequencing efficiency, 46 out 50 samples (92.0%) with positive amplification were successfully sequenced. The remaining 4 samples (8.0%) failed to produce an analyzable sequence due to low coverage of the CA region (<100 reads), all of which were HIV-1 RNA samples. Notably, all amplified HIV-1 DNA samples were successfully sequenced and analyzed, achieving 100% success in both amplification and sequencing. 3.2.2| Efficiency by HIV-1 subtype-associated variability: B subtype vs. non-B subtypes The second variable analyzed was the impact of HIV-1 subtype-associated viral variability on the success rate. Specifically, samples with different non-B subtypes were merged, and efficiency was evaluated by comparing the B subtype vs. non-B subtypes (N=43 vs . N=17). For B subtype plasma samples, the median [IQR] viremia was 1,726 [171–14,415] copies/mL, while for non-B subtype samples, the median viral load was 2,788 [185–15,030] copies/mL. Among the 43 samples with HIV-1 B subtype, amplification was successful in 37 (86.0%), including 19 HIV-1 RNA and 18 HIV-1 DNA samples. In comparison, among the 17 samples with non-B subtypes, 13 (76.5%) were successfully amplified, comprising 12 HIV-1 RNA and 1 HIV-1 DNA sample. Regarding sequencing success, 34 out of the 37 amplified samples with HIV-1 subtype B (91.9%) yielded valid sequences: 16 (47.1%) from HIV-1 RNA and 18 (52.9%) from HIV-1 DNA. Among the 13 amplified samples with HIV-1 non-B subtypes, 12 (92.3%) produced valid sequences: 11 (91.7%) from HIV-1 RNA and 1 (8.3%) from HIV-1 DNA. Overall, HIV-1 subtype variability did not appear to affect the performance of the protocol, either in terms of amplification (86.0% for B subtype vs. 76.5% for non-B subtypes) or sequencing success (91.9% vs. 92.3%, respectively). Figure 2 summarizes amplification and sequencing performance among HIV-1 non-B subtypes. FIGURE 2|Amplification and sequencing performance among HIV-1 non-B subtypes (N=17). The figure shows the amplification success rates (yellow bars) calculated as the percentage of successfully amplified samples out of the total number of samples. Green bars represent the sequencing success rates, calculated as the percentage of successfully sequenced samples on the total of successfully amplified samples. Overall, four non-B subtype samples failed amplification: two CRF02_AG samples (HIV-1 RNA, 192 copies/mL and 222 copies/mL, respectively), one 09_cpx (HIV-1 RNA, 183 copies/mL) and one subtype C (HIV-1 RNA, 101 copies/mL). Only one successfully amplified sample did not yield a valid sequence after sequencing (42_BF; HIV-1 RNA, 81 copies/mL). The only non-B HIV-1 DNA sample (DF) was successfully amplified and sequenced. 3.2.3 | Efficiency by viremia levels of HIV-1 RNA samples Efficiency was additionally assessed by categorizing the 41 HIV-1 RNA plasma samples according to viral load ranges. The molecular amplification success rate was 100% (10/10) in the >10,000 copies/mL range, 92.3% (12/13) in the the >50 – 1,000 copies/mL range. Considering the sub-analysis of the lower viremia interval, the amplification success rate was 42.9% (6/14) in the >50 – 500 copies/mL range and 75.0% (3/4) in the >500 – 1,000 copies/mL range (see Table 3). The sequencing success rate was 100% in both the >10,000 copies/mL (10/10) and >1,000 – 10,000 copies/mL ranges (12/12). For the >50 – 1,000 copies/mL interval, the sequencing success rate was 55.6%, with 5 samples yielding analyzable sequences out of 9 amplified samples. In the sub-analysis, the sequencing success rate was 100% (3/3) for samples in the >500 – 1,000 copies/mL range and 33.3% (2/6) for samples in the >50 – 500 copies/mL range. Overall, a high success rate was achieved (92.6%, 25/27) in processing samples with viremia above 500 copies/mL (see Figure 3). FIGURE 3|Amplification and sequencing performance by HIV-1 RNA viremia ranges. The figure shows the relationship between viremia levels and performance (amplification and sequencing success). Each dot represents an individual, yellow dots indicate successful amplification, green dots indicate successful amplification and sequencing. Failures are shown in white dots. The dashed line indicates the HIV-1 RNA threshold of 500 copies/mL. Only two amplification failures occurred in samples with viremia above 500 copies/mL (512 and 3,564 copies/mL), both with subtype B. 3.3 | Evaluation of NGS reproducibility To evaluate the reproducibility of the developed protocol, 13 representative HIV-1 RNA samples with successful amplification and analyzable sequences were reprocessed, starting from the same extraction sample. All reprocessed samples showed consistent performance, with successful amplification and sequencing achieved in every case. Using the pairwise similarity sequence test with EMBOSS Needle, nucleotide sequences obtained from the two processes were compared for each sample at NGS cut-offs of 5%, 10%, and 20% (see Table 4). TABLE 4 |Capsid NGS reproducibility performance on 13 repeated HIV-1 RNA samples NGS-CA_R01 B 48,700 684 98.7% 688 99.3% 693 100% none NGS-CA_R02 B 468,1314 688 99.3% 691 99.7% 692 99.9% none NGS-CA_R03 B 38,084 688 99.3% 691 99.7% 692 99.9% none NGS-CA_R04 60_BC 3,900 691 99.7% 691 99.7% 691 99.7% one accessory NGS-CA_R05 B 4,239 692 99.9% 692 99.9% 692 99.9% none NGS-CA_R06 41_CD 6,151 683 98.6% 689 99.4% 692 99.9% none NGS-CA_R07 B 5,276 670 96.7% 679 98.0% 689 99.4% none NGS-CA_R08 B 1,726 691 99.7% 691 99.7% 693 100% none NGS-CA_R09 12_BF 3,561 677 97.7% 681 98.3% 686 99.0% none NGS-CA_R10 B 4,021 690 99.6% 690 99.6% 690 99.6% none NGS-CA_R11 02_AG 2,014 691 99.4% 692 99.9% 692 99.9% none NGS-CA_R12 B 884 691 99.7% 690 99.6% 690 99.6% none NGS-CA_R13 B 642 676 97.5% 682 98.4% 688 99.3% none Pairwise nucleotide similarity across runs for each sample was evaluated in the CA region of the gag gene (693 nt) at 5%, 10%, and 20% NGS thresholds, as defined by the Stanford HIVdb (https://hivdb.stanford.edu/). Results are shown as percentages. *CAI mutations: amino acid changes associated with resistance to LEN were assessed according to the major and accessory mutations listed in Stanford Algorithm v9.8. Only one accessory mutation (A105T) was found at 5% cutoff. All samples demonstrated very high similarity values. Reproducibility acceptance criteria were met at all NGS analysis cut-offs, excluding the most stringent 5% threshold. The proportion of samples with at least 98% pairwise similarity was 100% (13/13) at both the 20% and 10% cut-offs. The lowest pairwise similarity observed was 96.7% at the 5% cut-off. The specific amino acid changes identified at the three NGS cut-offs (5%, 10%, and 20%) for each of the 13 sample pairs are detailed in Supplementary Table S1. 3.4 | LEN Resistance Profile Overall, within the 46 CA sequences obtained, no major mutations associated with resistance to LEN were detected, except for two sequences derived from a single individual with a virological failure during LEN-based therapy. In this case, the resistance-associated mutation K70H (97.8%) and Q67K (98.5%) were identified in the HIV-1 RNA sequence, and were also confirmed in the corresponding proviral HIV-1 DNA at frequencies of 75.6% and 75.7%, respectively. Furthermore, the accessory mutation T107A was observed in three sequences from three distinct individuals, with variant frequencies of 98.2% and 66.9% in two HIV-1 RNA sequences, and 5.9% in a HIV-1 DNA sequence, respectively. Finally, the accessory mutation A105T, at a frequency of 6.0%, was detected in only one sequence of the replicated HIV-1 RNA samples used to assess protocol reproducibility at 5% cutoff (see Table S1). 4 | Discussion In this study, a novel and highly effective NGS protocol was developed for sequencing the HIV-1 CA region to assess resistance to LEN, a recently approved CA inhibitor for antiviral treatment, with significant potential applicability to both current and future antiretroviral drugs targeting this protein. The previously published protocol based on Sanger sequencing (Soria et al., 2016) was modified and optimized for the Illumina NGS platform to enable efficient amplification and deep sequencing of the HIV-1 CA region across various sample matrices (HIV-1 DNA and HIV-1 RNA), different subtypes, and viremia levels. The method is versatile and robust and can be implemented in both diagnostic and research settings, particularly for assessing LEN resistance in HTE PWH with MDR, either at baseline before initiating LEN therapy or in cases of virological failure 17 . To date, the novelty of this protocol lies in its ability to detect low-frequency variants through the implementation of an NGS-based approach, and to efficiently analyze both HIV-1 RNA samples and HIV-1 DNA derived from PBMCs. The protocol achieved a 100% success rate with HIV-1 DNA samples and a 76.5% success rate with HIV-1 RNA samples. Among the 41 HIV-1 RNA samples, most amplification failures occurred in those with viremia levels below 500 copies/mL. A marked decrease in amplification and sequencing success was observed in samples >50–500 copies/mL. Specifically, only 2 out of 14 samples were successfully amplified and sequenced, while 3 out of 4 samples in the >500–1,000 copies/mL range yielded successful results. With viremia levels above 500 copies/mL, amplification and sequencing were successful in 92.6% of cases, demonstrating robust performance, especially considering that commercial kits generally have a higher detection threshold of 1,000 copies/mL. The higher success rate observed with HIV-1 DNA samples can likely be attributed to the type of starting material. In the study, proviral DNA was extracted from PBMCs, resulting in higher nucleic acid yield and purity compared to whole blood. This excellent performance will enable genotypic resistance testing (GRT) even in virologically suppressed individuals with undetectable plasma HIV-1 RNA or in individuals with low level viremia ( particularly below 500 copies/mL , where the success rate was not optimal). Regarding the subtype issue, similar success rate was observed for both HIV-1 B and non-B subtypes (approximately 92% each), likely due to the consistent efficiency of the primers in binding to the viral gag region. The subtype-related molecular variability did not appear to affect the amplification success rate, thus demonstrating the broad applicability of the protocol across diverse viral strains. Regarding the resistance, the population included also samples from individuals treated with LEN. One of them, who experienced a virologic failure, showed the major resistance mutation K70H with the Q67K at high prevalence (>75%), in both HIV-1 RNA and HIV-1 DNA matrices. Furthermore, the accessory mutation T107A was identified in three distinct individuals: two in HIV-1 RNA samples (at 98.2 and 66.9% prevalence, respectively) and one in a HIV-1 DNA sample (5.9% prevalence). These results show that the protocol can effectively detect resistance-associated mutations, highlighting its relevance for monitoring the effectiveness of LEN and other future CA inhibitors. It was possible to effectively detect resistance-associated mutations even at a lower level, although their role and clinical significance need to be investigated. Finally, to evaluate the reproducibility and sensitivity of the protocol, 13 representative HIV-1 RNA samples with different subtypes and viral loads were reprocessed. The amplification and sequencing results were confirmed. Using pairwise similarity comparison, all sequences at 10% and 20% frequency cutoff achieved the 100% criteria of reproducibility (≥98% similarity) 15 . While 76.9% reproducibility was achieved at the 5% threshold (with only 10 out of 13 pairs showing ≥98% similarity). This result is likely due to technical limitations, and is in line with other NGS protocols, as a 10% frequency threshold is currently recommended for NGS-based GRT analyses 18 . A limitation of this study is the relatively small sample size (60 samples). Although 28.3% of the population carried non-B subtypes, only one HIV-1 DNA sample with a non-B subtype was analyzed. Moreover, the kind of subtypes analyzed were limited to the more common circulating in Italy 19 . Most amplification failures occurred in HIV-1 RNA samples with viremia levels below 500 copies/mL. Finally, regarding the HIV-1 DNA analysis, the use of PBMCs instead of whole blood could potentially limit the adoption of the protocol in diagnostic routine, as Ficoll separation involves additional steps, increased costs, and longer processing times. Further optimization (on HIV-1 RNA samples with low level viremia, using whole blood samples and more different non-B subtypes) could be implemented. 5 | Conclusions The study presents a novel highly effective NGS protocol for analyzing the HIV-1 CA region, viral target of LEN and other future CA inhibitors. The protocol achieved high success rates for both HIV-1 DNA and RNA samples with viremia levels >500 copies/ml. High amplification and sequencing success rates were achieved regardless of viral subtype. The overall reproducibility and robustness of the protocol remained very high, supporting its reliability and implementation in both clinical and research applications particularly for the management of PWH receiving LEN, or future CA inhibitors, for treatment or HIV-1 prevention. AUTHOR CONTRIBUTIONS: Maria Concetta Bellocchi, Francesca Ceccherini-Silberstein, and Maria Mercedes Santoro conceived the project; Greta Marchegiani, Ada Bertoli, Vincenzo Spagnuolo and Daniele Spalletta collected the samples and clinical and virological information; Greta Marchegiani, Daniele Spalletta and Omar El Khalili performed sequencing; Greta Marchegiani, Luca Carioti, Daniele Spalletta and Hossein Eizadi performed bioinformatic and statistical analyses; Omar El Khalili, Collins Ambes Chenwi, and Maria Concetta Bellocchi wrote the manuscript; Maria Mercedes Santoro and Francesca Ceccherini-Silberstein revised the manuscript. All authors read, revised and approved the final version of the manuscript. ACKNOWLEDGMENTS: Thanks are extended to all clinicians, virologists, statisticians, data managers, and the biological bank of the ICONA Foundation and the PRESTIGIO Registry. Additionally, gratitude is expressed to Ilaria Maugliani for data management of this study, and to Flavia Funari, Livia Benedetti, and Giulia Torre for their assistance in the laboratory experiments. ICONA Foundation Study Group. Board of directors: A d’Arminio Monforte (President), A Antinori (Vice-President), S Antinori, A Castagna, R Cauda, G Di Perri, E Girardi, R Iardino, A Lazzarin, GC Marchetti, C Mussini, E Quiros-Roldan, L Sarmati, B Suligoi, F von Schloesser, P Viale. Scientific secretary: A d’Arminio Monforte, A Antinori, A Castagna, F Ceccherini-Silberstein, A Cingolani, A Cozzi-Lepri, E Girardi, A Gori, S Lo Caputo, G Marchetti, F Maggiolo, C Mussini, M Puoti, CF Perno. Steering committee: C Agrati, A Antinori, F Bai, A Bandera, S Bonora, A Calcagno, D Canetti, A Castagna, F Ceccherini-Silberstein, A Cervo, S Cicalini, A Cingolani, P Cinque, A Cozzi-Lepri, A d’Arminio Monforte, A Di Biagio, R Gagliardini, A Giacomelli, E Girardi, N Gianotti, A Gori, G Guaraldi, S Lanini, G Lapadula, M Lichtner, A Lai, S Lo Caputo, G Madeddu, F Maggiolo, V Malagnino, G Marchetti, C Mussini, S Nozza, CF Perno, S Piconi, C Pinnetti, M Puoti, E Quiros Roldan, R Rossotti, S Rusconi, MM Santoro, A Saracino, L Sarmati, V Spagnuolo, N Squillace, V Svicher, L Taramasso, A Vergori. Statistical and monitoring team: F Bovis, A Cozzi-Lepri, I Fanti, A Rodanò, M Ponzano, A Tavelli. Community advisory board: A Bove, M Cernuschi, L Cosmaro, M Errico, A Perziano, V Calvino. Biological bank INMI and San Paolo: S Carrara, S Graziano, G Prota, S Truffa, D Vincenti, Y D’Errico. Participating physicians and centres: Italy A Giacometti, A Costantini, V Barocci (Ancona); A Saracino, C Santoro, E Milano (Bari); F Maggiolo, C Suardi (Bergamo); P Viale, L Badia, S Cretella (Bologna); E Quiros Roldan, E Focà, C Minardi (Brescia); B Menzaghi, C Abeli (Busto Arsizio); L Chessa, F Pes (Cagliari); P Maggi, L Alessio (Caserta); B Cacopardo, B Celesia (Catania); J Vecchiet, K Falasca (Chieti); A Pan, S Dal Zoppo (Cremona); D Segala (Ferrara); F Vichi, MA Di Pietro (Firenze); T Santantonio, S Ferrara (Foggia); M Bassetti, E Pontali, S Blanchi, N Bobbio, G Mazzarello (Genova); M Lichtner, L Fondaco (Latina); S Piconi, C Molteni (Lecco); S Rusconi, G Canavesi (Legnano) A Chiodera, P Milini (Macerata); G Nunnari, G Pellicanò (Messina); A d’Arminio Monforte, S Antinori, A Lazzarin, G Rizzardini, M Puoti, A Gori, A Castagna, A Bandera, V Bono, MV Cossu, A Giacomelli, R Lolatto, MC Moioli, L Pezzati, C Tincati (Milano); C Mussini, C Puzzolante (Modena); P Bonfanti, G Lapadula (Monza); V Sangiovanni, I Gentile, V Esposito, FM Fusco, G Di Filippo, V Rizzo, N Sangiovanni (Napoli); AM Cattelan, S Marinello (Padova); A Cascio, C Colomba (Palermo); D Francisci, E Schiaroli (Perugia); G Parruti, F Sozio (Pescara); P Blanc, A Vivarelli (Pistoia); C Lazzaretti, R Corsini (Reggio Emilia); M Andreoni, A Antinori, R Cauda, C Mastroianni, A Cingolani, V Mazzotta, S Lamonica, M Capozzi, A Mondi, M Rivano Capparuccia, G Iaiani, C Stingone, L Gianserra, J Paulicelli, MM Plazzi, G d’Ettore, M Fusto (Roma); M Cecchetto, F Viviani (Rovigo); G Madeddu, A De Vito (Sassari); M Fabbiani, F Montagnani (Siena); A Franco, R Fontana Del Vecchio (Siracusa); BM Pasticci, C Di Giuli (Terni); GC Orofino, G Calleri, G Di Perri, S Bonora, G Accardo (Torino); C Tascini, A Londero (Udine); V Manfrin, G Battagin (Vicenza); G Starnini, A Ialungo (Viterbo). PRESTIGIO Study Group STEERING COMMITTEE: Antonella Castagna (Coordinator), Vincenzo Spagnuolo (Operative Coordinator), Daniele Armenia, Stefano Bonora, Leonardo Calza, Anna Maria Cattelan, Giovanni Cenderello, Adriana Cervo, Laura Comi, Antonio Di Biagio, Emanuele Focà, Roberta Gagliardini, Andrea Giacomelli, Filippo Lagi, Giulia Marchetti, Stefano Rusconi, Francesco Saladini, Maria Santoro, Maurizio Zazzi. VIROLOGY TEAM AND BIOLOGICAL BANK: Andrea Galli, Daniele Armenia, Francesco Saladini, Maria Santoro, Maurizio Zazzi, BioRep SRL. STUDY COORDINATORS: Elisabetta Carini, Sabrina Bagaglio, Girolamo Piromalli. STATISTICAL AND MONITORING TEAM: Riccardo Lolatto, Nicolò Capra. ENROLLING CENTERS: ANCONA: Marcello Tavio, Alessandra Mataloni Paggi; AOSTA: Silvia Magnani, Manuela Colafigli AVIANO: Ornella Schioppa, Stefania Zanussi, Valentina Da Ros, Silvia Rossetto; BARI: Annalisa Saracino, Flavia Balena; BERGAMO: Laura Comi, Daniela Valenti; BOLOGNA: Pierluigi Viale, Leonardo Calza, Federica Malerba, Silvia Cretella, Riccardo Riccardi; BRESCIA: Francesco Castelli, Emanuele Focà, Davide Minisci; BUSTO ARSIZIO: Barbara Menzaghi, Maddalena Farinazzo, Chiara Abeli; CATANIA: Bruno Cacopardo, Maurizio Celesia, Michele Salvatore Paternò Raddusa, Carmen Giarratana; CATANZARO: Paolo Fusco, Vincenzo Olivadese, Simona Mongiardi; CREMONA: Angelo Pan, Chiara Fornabaio, Paola Brambilla; FIRENZE: Alessandro Bartoloni, Filippo Lagi, Paola Corsi, Trevisan Sasha, Gasparro Giuseppe, Cecilia Costa, Alessio Bellucci, Elisa Mariabelli; FOGGIA: Teresa Santantonio, Sergio Lo Caputo, Sergio Ferrara, Arianna Narducci; GENOVA: Emanuele Pontali, Marcello Feasi, Antonio Sarà, Matteo Bassetti, Antonio Di Biagio, Sabrina Blanchi; LECCO: Stefania Piconi, Martina Bottanelli, Silvia Pontiggia, Valsecchi Giada; LEGNANO: Stefano Rusconi, Cinzia Roberta Bassoli, Francesco Bassani, Liana Bevilacqua; MILANO: Antonella Castagna, Vincenzo Spagnuolo, Camilla Muccini, Elisabetta Carini, Sabrina Bagaglio, Riccardo Lolatto, Nicolò Capra, Andrea Galli, Rebecka Papaioannu, Tommaso Clemente, Golnaz Torkjazi, Girolamo Piromalli, Spinello Antinori, Andrea Giacomelli, Tiziana Formenti, Giulia Marchetti, Lidia Gazzola, Fabiana Trionfo Fineo, Massimo Puoti, Cristina Moioli, Federico D’Amico, Simoncini Elena, Sassi Serena; MODENA: Cristina Mussini, Adriana Cervo, Giulia Nardini; NAPOLI: Elio Manzillo, Antonella Gallicchio; PADOVA: Anna Maria Cattelan, Maria Mazzitelli; PALERMO: Antonio Cascio, Marcello Trizzino; PARMA: Elisa Fronti, Diletta Laccabue, Federica Carli; PAVIA: Roberto Gulminetti, Layla Pagnucco, Mattia Demitri, Alessandra Ferrari; PERUGIA: Daniela Francisci, Giuseppe De Socio, Elisabetta Schiaroli; REGGIO EMILIA: Elisa Garlassi, Romina Corsini; ROMA: Roberta Gagliardini, Marisa Fusto, Loredana Sarmati, Vincenzo Malagnino, Tiziana Mulas, Mirko Compagno, Carlo Torti, Simona Di Giambenedetto, Silvia Lamonica, Pierluigi Salvo; SANREMO: Giovanni Cenderello, Rachele Pincino, Davide Laurenda; SASSARI: Giordano Madeddu, Andrea De Vito; SIENA: Mario Tumbarello, Massimiliano Fabbiani, Francesca Panza, Ilaria Rancan; TORINO: Giovanni Di Perri, Stefano Bonora, Micol Ferrara, Andrea Calcagno, Silvia Fantino, Giancarlo Orofino, Guido Calleri, Guastavigna Marta; VERONA: Stefano Nardi, Marta Fiscon. SUPPORTED BY: ViiV Healthcare, Gilead Sciences, MSD, Janssen-Cilag. FUNDING STATEMENT: Funding for this publication was partially provided by an unconditional grant by Gilead Sciences. CONFLICT OF INTEREST STATEMENT: The authors declare no conflict of interest. DATA AVAILABILITY STATEMENT: The data that support the findings of this study are available from the corresponding author upon reasonable request. Sequences obtained from this study are available in GenBank, sequences accession numbers PV054267-PV054325. REFERENCES 1. Joint United Nations Programme on HIV/AIDS (UNAIDS) 2024. The Urgency of Now: AIDS at a Crossroads. Geneva: Joint United Nations Programme on HIV/AIDS; 2024. Licence: CC BY-NC-SA 3.0 IGO. 2. Brizzi MB, Cable TL, Patel DC, Williams K, Adjei Z, Fichtenbaum CJ. Heavily treatment-experienced patients with HIV: are new mechanisms of action enough? Journal of International Medical Research . 2024;52(12). doi:10.1177/03000605241301883 3. 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Journal of Antimicrobial Chemotherapy . 2024;79(9):2152-2162. doi:10.1093/jac/dkae189 Supplementary Material File (figures.zip) Download 8.98 MB File (tables.zip) Download 56.93 KB Information & Authors Information Version history V1 Version 1 13 June 2025 Peer review timeline Published Journal of Medical Virology Version of Record 24 Dec 2025 Published Copyright This work is licensed under a Non Exclusive No Reuse License. Collection Journal of Medical Virology Keywords anti-retrovirus drug antiviral agents human immunodeficiency virus infection resistance virus classification Authors Affiliations Omar El Khalili Universita degli Studi di Roma Tor Vergata Dipartimento di Medicina Sperimentale View all articles by this author Collins Ambe Chenwi Universita degli Studi di Roma Tor Vergata Dipartimento di Medicina Sperimentale View all articles by this author Daniele Spalletta 0009-0009-4932-5344 Universita degli Studi di Roma Tor Vergata Dipartimento di Medicina Sperimentale View all articles by this author Greta Marchegiani Universita degli Studi di Roma Tor Vergata Dipartimento di Medicina Sperimentale View all articles by this author Luca Carioti 0000-0003-1713-8682 Universita degli Studi di Roma Tor Vergata Dipartimento di Medicina Sperimentale View all articles by this author Hossein Eizadi Moghadam Universita degli Studi di Roma Tor Vergata Dipartimento di Medicina Sperimentale View all articles by this author Ada Bertoli Universita degli Studi di Roma Tor Vergata Dipartimento di Medicina Sperimentale View all articles by this author Vincenzo Spagnuolo IRCCS Ospedale San Raffaele Division of Immunology Transplantation and Infectious Diseases View all articles by this author M. Santoro Universita degli Studi di Roma Tor Vergata Dipartimento di Medicina Sperimentale View all articles by this author F. Ceccherini-Silberstein Universita degli Studi di Roma Tor Vergata Dipartimento di Medicina Sperimentale View all articles by this author Maria Concetta Bellocchi 0000-0001-7717-2343 [email protected] Universita degli Studi di Roma Tor Vergata Dipartimento di Medicina Sperimentale View all articles by this author Metrics & Citations Metrics Article Usage 426 views 169 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Omar El Khalili, Collins Ambe Chenwi, Daniele Spalletta, et al. Development of a Next-Generation Sequencing Protocol for Assessing Lenacapavir Resistance in HIV-1 Capsid. Authorea . 13 June 2025. DOI: https://doi.org/10.22541/au.174981969.90487577/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. 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