Whole Genome Deep Sequencing of HIV-1 Reveals the Impact of Early Minor Variants Upon Immune Recognition During Acute Infection

Deep sequencing technologies have the potential to transform the study of highly variable viral pathogens by providing a rapid and cost-effective approach to sensitively characterize rapidly evolving viral quasispecies. Here, we report on a high-throughput whole HIV-1 genome deep sequencing platform that combines 454 pyrosequencing with novel assembly and variant detection algorithms. In one subject we combined these genetic data with detailed immunological analyses to comprehensively evaluate viral evolution and immune escape during the acute phase of HIV-1 infection. The majority of early, low frequency mutations represented viral adaptation to host CD8+ T cell responses, evidence of strong immune selection pressure occurring during the early decline from peak viremia. CD8+ T cell responses capable of recognizing these low frequency escape variants coincided with the selection and evolution of more effective secondary HLA-anchor escape mutations. Frequent, and in some cases rapid, reversion of transmitted mutations was also observed across the viral genome. When located within restricted CD8 epitopes these low frequency reverting mutations were sufficient to prime de novo responses to these epitopes, again illustrating the capacity of the immune response to recognize and respond to low frequency variants. More importantly, rapid viral escape from the most immunodominant CD8+ T cell responses coincided with plateauing of the initial viral load decline in this subject, suggestive of a potential link between maintenance of effective, dominant CD8 responses and the degree of early viremia reduction. We conclude that the early control of HIV-1 replication by immunodominant CD8+ T cell responses may be substantially influenced by rapid, low frequency viral adaptations not detected by conventional sequencing approaches, which warrants further investigation. These data support the critical need for vaccine-induced CD8+ T cell responses to target more highly constrained regions of the virus in order to ensure the maintenance of immunodominant CD8 responses and the sustained decline of early viremia

Highly Sensitive and Specific Detection of Rare Variants in Mixed Viral Populations from Massively Parallel Sequence Data

Viruses diversify over time within hosts, often undercutting the effectiveness of host defenses and therapeutic interventions. To design successful vaccines and therapeutics, it is critical to better understand viral diversification, including comprehensively characterizing the genetic variants in viral intra-host populations and modeling changes from transmission through the course of infection. Massively parallel sequencing technologies can overcome the cost constraints of older sequencing methods and obtain the high sequence coverage needed to detect rare genetic variants (<1%) within an infected host, and to assay variants without prior knowledge. Critical to interpreting deep sequence data sets is the ability to distinguish biological variants from process errors with high sensitivity and specificity. To address this challenge, we describe V-Phaser, an algorithm able to recognize rare biological variants in mixed populations. V-Phaser uses covariation (i.e. phasing) between observed variants to increase sensitivity and an expectation maximization algorithm that iteratively recalibrates base quality scores to increase specificity. Overall, V-Phaser achieved >97% sensitivity and >97% specificity on control read sets. On data derived from a patient after four years of HIV-1 infection, V-Phaser detected 2,015 variants across the ∼10 kb genome, including 603 rare variants (<1% frequency) detected only using phase information. V-Phaser identified variants at frequencies down to 0.2%, comparable to the detection threshold of allele-specific PCR, a method that requires prior knowledge of the variants. The high sensitivity and specificity of V-Phaser enables identifying and tracking changes in low frequency variants in mixed populations such as RNA viruses

Reduced Viral Replication Capacity of Human Immunodeficiency Virus Type 1 Subtype C Caused by Cytotoxic-T-Lymphocyte Escape Mutations in HLA-B57 Epitopes of Capsid Protein▿

Cytotoxic-T-lymphocyte (CTL) escape mutations in human immunodeficiency viruses encode amino acid substitutions in positions that disrupt CTL targeting, thereby increasing virus survival and conferring a relative fitness benefit. However, it is now clear that CTL escape mutations can also confer a fitness cost, and there is increasing evidence to suggest that in some cases, e.g., escape from HLA-B*57/B*5801-restricted responses, the costs to the escape virus may affect the clinical course of infection. To quantify the magnitude of the costs of HLA-B*57/B*5801 escape, a highly sensitive dual-infection assay that uses synonymous nucleotide sequence tags to quantify viral relative replication capacity (RRC) was developed. We then asked whether such CTL escape mutations had an impact equivalent to that seen for a benchmark mutation, the M184V antiretroviral drug resistance mutation of reverse transcriptase (RRCV184 = 0.86). To answer the question, the RRCs were quantified for escape mutations in three immunodominant HLA-B*57/B*5801 epitopes in capsid: A146P in IW9 (RRCP146 = 0.91), A163G in KF11 (RRCG163 = 0.89), and T242N in TW10 (RRCN242 = 0.86). Individually, the impact of the escape mutations on RRC was comparable to that of M184V, while coexpression of the mutations resulted in substantial further reductions, with the maximum impact observed for the triple mutant (RRCP146-G163-N242 = 0.62). By comparison to M184V, the magnitude of the reductions in RRC caused by the escape mutations, particularly when coexpressed, suggests that the costs of escape are sufficient to affect in vivo viral dynamics and may thus play a role in the protective effect associated with HLA-B*57/B*5801

Ultrasensitive Detection of Minor Drug-Resistant Variants for HIV After Nevirapine Exposure Using Allele-Specific PCR: Clinical Significance

HIV-1 drug resistance mutations have been detected at low frequencies after single-dose nevirapine (sdNVP) for prevention of mother-to-child transmission (PMTCT). We investigated the relationship between these “minor variant” NVP-resistant viruses and clinical outcome with NVP-containing antiretroviral therapy (ART). An allele-specific quantitative PCR (ASPCR) assay was used to quantify the pre-ART frequency of K103N and Y181C in 26 women who had received sdNVP. The cohort was composed of 7 patients who experienced virologic failure and 19 control patients who maintained virologic suppression on NVP-containing ART; all were negative for resistance by standard genotyping. NVP resistance mutations were found in 17 of 26 (65%) patients using ASPCR. The frequency of NVP-resistant viruses ranged from 0.1% to 4.11%. Receiver operating characteristics (ROC) analysis identified a clinical threshold frequency of 0.19% for the ASPCR assay. Application of this threshold demonstrated minor variant resistance in 6 of 7 patients (86%) who failed treatment compared to 6 of 19 patients (32%) who were successful (OR = 13; 95% CI 1.27–133). ASPCR provides a means of detecting minor variant drug-resistant viruses that may impact subsequent treatment response. These data suggest a clinical role for highly sensitive assays to detect and quantify resistant viruses at low frequencies

Efficient Ablation of Genes in Human Hematopoietic Stem and Effector Cells using CRISPR/Cas9.

Genome editing via CRISPR/Cas9 has rapidly become the tool of choice by virtue of its efficacy and ease of use. However, CRISPR/Cas9-mediated genome editing in clinically relevant human somatic cells remains untested. Here, we report CRISPR/Cas9 targeting of two clinically relevant genes, B2M and CCR5, in primary human CD4(+) T cells and CD34(+) hematopoietic stem and progenitor cells (HSPCs). Use of single RNA guides led to highly efficient mutagenesis in HSPCs but not in T cells. A dual guide approach improved gene deletion efficacy in both cell types. HSPCs that had undergone genome editing with CRISPR/Cas9 retained multilineage potential. We examined predicted on- and off-target mutations via target capture sequencing in HSPCs and observed low levels of off-target mutagenesis at only one site. These results demonstrate that CRISPR/Cas9 can efficiently ablate genes in HSPCs with minimal off-target mutagenesis, which could have broad applicability for hematopoietic cell-based therapy

Rapid evolution of HIV-1 to functional CD8⁺ T cell responses in humanized BLT mice.

The development of mouse/human chimeras through the engraftment of human immune cells and tissues into immunodeficient mice, including the recently described humanized BLT (bone marrow, liver, thymus) mouse model, holds great promise to facilitate the in vivo study of human immune responses. However, little data exist regarding the extent to which cellular immune responses in humanized mice accurately reflect those seen in humans. We infected humanized BLT mice with HIV-1 as a model pathogen and characterized HIV-1-specific immune responses and viral evolution during the acute phase of infection. HIV-1-specific CD8(+) T cell responses in these mice were found to closely resemble those in humans in terms of their specificity, kinetics, and immunodominance. Viral sequence evolution also revealed rapid and highly reproducible escape from these responses, mirroring the adaptations to host immune pressures observed during natural HIV-1 infection. Moreover, mice expressing the protective HLA-B*57 allele exhibited enhanced control of viral replication and restricted the same CD8(+) T cell responses to conserved regions of HIV-1 Gag that are critical to its control of HIV-1 in humans. These data reveal that the humanized BLT mouse model appears to accurately recapitulate human pathogen-specific cellular immunity and the fundamental immunological mechanisms required to control a model human pathogen, aspects critical to the use of a small-animal model for human pathogens

Phase information increased sensitivity, and base quality scores increased specificity.

<p>We compared <i>V-Phaser</i> to alternate versions of <i>V-Phaser</i> with specific components disabled. In the No Phase version, <i>V-Phaser</i> called variants without phase information. In the Uniform Errors version, <i>V-Phaser</i> estimated uniform error rates within homopolymer and nonhomopolymer regions without regard to assigned base qualities. In the No Filtering version, <i>V-Phaser</i> did not filter out low quality bases. (<b>A</b>) Phase information increased sensitivity. The version without phase information attained a sensitivity of 90%, but all other versions of <i>V-Phaser</i> used phase information and attained a sensitivity of 97% or more. We calculated sensitivity as the percentage of known variants correctly identified. Data are from WNV mixed population control dataset. (<b>B</b>) Individual base quality scores increased specificity. Among loci with mismatches, the Uniform Errors version had only 91% specificity, but all other versions incorporated base quality scores in their probability model and attained 97% specificity or more. We calculated specificity as the percentage of loci in the control sample correctly identified as having no variants among loci that had at least one candidate variant. Data are from infectious clone (HIV NL4-3) control dataset.</p

Error rates were not uniformly distributed.

<p>Error rates varied by (<b>A</b>) read position, (<b>B</b>) base transition, and (<b>C</b>) base quality score. We counted as errors any mismatches to the consensus assembly for each of the two runs in the control read set under the assumption that the NL-43 infectious clone had no diversity. We defined the read position relative to the beginning or end of the read, whichever was closer. We defined a base transition as a dinucleotide representing the transition from the preceding base to the current base, and we scored a transition as an error if the current base was a mismatch. Base quality scores came from the sequencing process.</p