To investigate the extent to which drug resistance mutations are missed by standard genotyping methods, we analyzed the same plasma samples from 26 patients with suspected multidrug-resistant human immunodeficiency virus type 1 by using a newly developed single-genome sequencing technique and compared it to standard genotype analysis. Plasma samples were obtained from patients with prior exposure to at least two antiretroviral drug classes and who were on a failing antiretroviral regimen. Standard genotypes were obtained by reverse transcriptase (RT)-PCR and sequencing of the bulk PCR product. For single-genome sequencing, cDNA derived from plasma RNA was serially diluted to 1 copy per reaction, and a region encompassing p6, protease, and a portion of RT was amplified and sequenced. Sequences from 15 to 46 single viral genomes were obtained from each plasma sample. Drug resistance mutations identified by single-genome sequencing were not detected by standard genotype analysis in 24 of the 26 patients studied. Mutations present in less than 10% of single genomes were almost never detected in standard genotypes (1 of 86). Similarly, mutations present in 10 to 35% of single genomes were detected only 25% of the time in standard genotypes. For example, in one patient, 10 mutations identified by single-genome sequencing and conferring resistance to protease inhibitors (PIs), nucleoside analog reverse transcriptase inhibitors, and nonnucleoside reverse transcriptase inhibitors (NNRTIs) were not detected by standard genotyping methods. Each of these mutations was present in 5 to 20% of the 20 genomes analyzed; 15% of the genomes in this sample contained linked PI mutations, none of which were present in the standard genotype. In another patient sample, 33% of genomes contained five linked NNRTI resistance mutations, none of which were detected by standard genotype analysis. These findings illustrate the inadequacy of the standard genotype for detecting low-frequency drug resistance mutations. In addition to having greater sensitivity, single-genome sequencing identifies linked mutations that confer high-level drug resistance. Such linkage cannot be detected by standard genotype analysis.

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Background The Centers for Disease Control and Prevention contracted with laboratories to sequence the SARS-CoV-2 genome from positive samples across the United States to enable public health officials to investigate the impact of variants on disease severity as well as the effectiveness of vaccines and treatment. Herein we present the initial results correlating RT-PCR quality control metrics with sample collection and sequencing methods from full SARS-CoV-2 viral genomic sequencing of 24,441 positive patient samples between April and June 2021. Methods RT-PCR confirmed (N Gene Ct value < 30) positive patient samples, with nucleic acid extracted from saliva, nasopharyngeal and oropharyngeal swabs were selected for viral whole genome SARS-CoV-2 sequencing. Sequencing was performed using Illumina COVIDSeq™ protocol on either the NextSeq550 or NovaSeq6000 systems. Informatic variant calling, and lineage analysis were performed using DRAGEN COVID Lineage applications on Illumina’s Basespace cloud analytical system. All sequence data and variant calls were uploaded to NCBI and GISAID. Results An association was observed between higher sequencing coverage, quality, and samples with a lower Ct value, with < 27 being optimal, across both sequencing platforms and sample collection methods. Both nasopharyngeal swabs and saliva samples were found to be optimal samples of choice for SARS-CoV-2 surveillance sequencing studies, both in terms of strain identification and sequencing depth of coverage, with NovaSeq 6000 providing higher coverage than the NextSeq 550. The most frequent variants identified were the B.1.617.2 Delta (India) and P.1 Gamma (Brazil) variants in the samples sequenced between April 2021 and June 2021. At the time of submission, the most common variant > 99% of positives sequenced was Omicron. Conclusion These initial analyses highlight the importance of sequencing platform, sample collection methods, and RT-PCR Ct values in guiding surveillance efforts. These surveillance studies evaluating genetic changes of SARS-CoV-2 have been identified as critical by the CDC that can affect many aspects of public health including transmission, disease severity, diagnostics, therapeutics, and vaccines.

A 16-week STI before optimized ART did not improve virologic response. Genetic analyses strongly suggest that virologic failure resulted from the reemergence of virus present before STI that encoded 3-drug class resistance on the same genome.

Background The rapid failure of initial therapy with combinations of nucleoside/nucleotide reverse transcriptase inhibitors (NRTI) that exclude zidovudine has not been fully explained by standard virus population analyses of HIV-1 drug resistance. We therefore investigated HIV-1 genotype and phenotype at the single genome level in samples from patients on a failing regimen of tenofovir (TNV), didanosine (ddI), and lamivudine (3TC). Methods Single genome sequencing was performed on nine failure samples containing both K65R and M184V mutations by standard genotype, either as wild-type/mutant mixtures (6/9) or as mutant only (3/9). Recombinant clones with different combinations of observed mutations were generated and tested for NRTI susceptibility. Results Of the 204 single genome sequences analyzed, 50% were K65R/M184V double-mutants, 38% were M184V single-mutants, 10% were M184I single-mutants, and only 1% (2 sequences) were K65R single-mutants. Phenotypic testing of recombinant clones showed a significant increase in resistance for double-mutants: mean fold-resistance to ABC, ddI, and TNV was 6.5, 4.3, and 1.6 for K65R/M184V double-mutants versus 2.5, 1.9, and 0.6 for M184V single-mutants, respectively (p<0.001). Conclusions Mutants with K65R and M184V linked on the same genome were the most common HIV-1 variants in samples analyzed from patients failing TNV, ddI, and 3TC with both mutations detected by standard genotype. The double-mutant exhibited reduced susceptibility to all three NRTI in the regimen. This resistant phenotype, resulting from just two linked point mutations, likely contributes to rapid failure of NRTI combinations that exclude zidovudine.