Phylogenetic Relatedness of Circulating HIV-1C Variants in Mochudi, Botswana

Background: Determining patterns of HIV transmission is increasingly important for the most efficient use of modern prevention interventions. HIV phylogeny can provide a better understanding of the mechanisms underlying HIV transmission networks in communities. Methods: To reconstruct the structure and dynamics of a local HIV/AIDS epidemic, the phylogenetic relatedness of HIV-1 subtype C env sequences obtained from 785 HIV-infected community residents in the northeastern sector of Mochudi, Botswana, during 2010–2013 was estimated. The genotyping coverage was estimated at 44%. Clusters were defined based on relatedness of HIV-1C env sequences and bootstrap support of splits. Results: The overall proportion of clustered HIV-1C env sequences was 19.1% (95% CI 17.5% to 20.8%). The proportion of clustered sequences from Mochudi was significantly higher than the proportion of non-Mochudi sequences that clustered, 27.0% vs. 14.7% (p = 5.8E-12; Fisher exact test). The majority of clustered Mochudi sequences (90.1%; 95% CI 85.1% to 93.6%) were found in the Mochudi-unique clusters. None of the sequences from Mochudi clustered with any of the 1,244 non-Botswana HIV-1C sequences. At least 83 distinct HIV-1C variants, or chains of HIV transmission, in Mochudi were enumerated, and their sequence signatures were reconstructed. Seven of 20 genotyped seroconverters were found in 7 distinct clusters. Conclusions: The study provides essential characteristics of the HIV transmission network in a community in Botswana, suggests the importance of high sampling coverage, and highlights the need for broad HIV genotyping to determine the spread of community-unique and community-mixed viral variants circulating in local epidemics. The proposed methodology of cluster analysis enumerates circulating HIV variants and can work well for surveillance of HIV transmission networks. HIV genotyping at the community level can help to optimize and balance HIV prevention strategies in trials and combined intervention packages

Timing Constraints of In Vivo Gag Mutations during Primary HIV-1 Subtype C Infection

Background: Aiming to answer the broad question “When does mutation occur?” this study examined the time of appearance, dominance, and completeness of in vivo Gag mutations in primary HIV-1 subtype C infection. Methods: A primary HIV-1C infection cohort comprised of 8 acutely and 34 recently infected subjects were followed frequently up to 500 days post-seroconversion (p/s). Gag mutations were analyzed by employing single-genome amplification and direct sequencing. Gag mutations were determined in relation to the estimated time of seroconversion. Time of appearance, dominance, and completeness was compared for different types of in vivo Gag mutations. Results: Reverse mutations to the wild type appeared at a median (IQR) of 62 (44;139) days p/s, while escape mutations from the wild type appeared at 234 (169;326) days p/s (p<0.001). Within the subset of mutations that became dominant, reverse and escape mutations appeared at 54 (30;78) days p/s and 104 (47;198) days p/s, respectively (p<0.001). Among the mutations that reached completeness, reverse and escape mutations appeared at 54 (30;78) days p/s and 90 (44;196) days p/s, respectively (p = 0.006). Time of dominance for reverse mutations to and escape mutations from the wild type was 58 (44;105) days p/s and 219 (90;326) days p/s, respectively (p<0.001). Time of completeness for reverse and escape mutations was 152 (100;176) days p/s and 243 (101;370) days p/s, respectively (p = 0.001). Fitting a Cox proportional hazards model with frailties confirmed a significantly earlier time of appearance (hazard ratio (HR): 2.6; 95% CI: 2.3–3.0), dominance (4.8 (3.4–6.8)), and completeness (3.6 (2.3–5.5)) of reverse mutations to the wild type Gag than escape mutations from the wild type. Some complex mutational pathways in Gag included sequential series of reversions and escapes. Conclusions: The study identified the timing of different types of in vivo Gag mutations in primary HIV-1 subtype C infection in relation to the estimated time of seroconversion. Overall, the in vivo reverse mutations to the wild type occurred significantly earlier than escape mutations from the wild type. This shorter time to incidence of reverse mutations remained in the subsets of in vivo Gag mutations that reached dominance or completeness

HIV-1 pol Diversity among Female Bar and Hotel Workers in Northern Tanzania

A national ART program was launched in Tanzania in October 2004. Due to the existence of multiple HIV-1 subtypes and recombinant viruses co-circulating in Tanzania, it is important to monitor rates of drug resistance. The present study determined the prevalence of HIV-1 drug resistance mutations among ART-naive female bar and hotel workers, a high-risk population for HIV-1 infection in Moshi, Tanzania. A partial HIV-1 pol gene was analyzed by single-genome amplification and sequencing in 45 subjects (622 pol sequences total; median number of sequences per subject, 13; IQR 5–20) in samples collected in 2005. The prevalence of HIV-1 subtypes A1, C, and D, and inter-subtype recombinant viruses, was 36%, 29%, 9% and 27%, respectively. Thirteen different recombination patterns included D/A1/D, C/A1, A1/C/A1, A1/U/A1, C/U/A1, C/A1, U/D/U, D/A1/D, A1/C, A1/C, A2/C/A2, CRF10_CD/C/CRF10_CD and CRF35_AD/A1/CRF35_AD. CRF35_AD was identified in Tanzania for the first time. All recombinant viruses in this study were unique, suggesting ongoing recombination processes among circulating HIV-1 variants. The prevalence of multiple infections in this population was 16% (n = 7). Primary HIV-1 drug resistance mutations to RT inhibitors were identified in three (7%) subjects (K65R plus Y181C; N60D; and V106M). In some subjects, polymorphisms were observed at the RT positions 41, 69, 75, 98, 101, 179, 190, and 215. Secondary mutations associated with NNRTIs were observed at the RT positions 90 (7%) and 138 (6%). In the protease gene, three subjects (7%) had M46I/L mutations. All subjects in this study had HIV-1 subtype-specific natural polymorphisms at positions 36, 69, 89 and 93 that are associated with drug resistance in HIV-1 subtype B. These results suggested that HIV-1 drug resistance mutations and natural polymorphisms existed in this population before the initiation of the national ART program. With increasing use of ARV, these results highlight the importance of drug resistance monitoring in Tanzania

Transmission of single and multiple viral variants in primary HIV-1 subtype C infection.

To address whether sequences of viral gag and env quasispecies collected during the early post-acute period can be utilized to determine multiplicity of transmitted HIV's, recently developed approaches for analysis of viral evolution in acute HIV-1 infection [1,2] were applied. Specifically, phylogenetic reconstruction, inter- and intra-patient distribution of maximum and mean genetic distances, analysis of Poisson fitness, shape of highlighter plots, recombination analysis, and estimation of time to the most recent common ancestor (tMRCA) were utilized for resolving multiplicity of HIV-1 transmission in a set of viral quasispecies collected within 50 days post-seroconversion (p/s) in 25 HIV-infected individuals with estimated time of seroconversion. The decision on multiplicity of HIV infection was made based on the model's fit with, or failure to explain, the observed extent of viral sequence heterogeneity. The initial analysis was based on phylogeny, inter-patient distribution of maximum and mean distances, and Poisson fitness, and was able to resolve multiplicity of HIV transmission in 20 of 25 (80%) cases. Additional analysis involved distribution of individual viral distances, highlighter plots, recombination analysis, and estimation of tMRCA, and resolved 4 of the 5 remaining cases. Overall, transmission of a single viral variant was identified in 16 of 25 (64%) cases, and transmission of multiple variants was evident in 8 of 25 (32%) cases. In one case multiplicity of HIV-1 transmission could not be determined. In primary HIV-1 subtype C infection, samples collected within 50 days p/s and analyzed by a single-genome amplification/sequencing technique can provide reliable identification of transmission multiplicity in 24 of 25 (96%) cases. Observed transmission frequency of a single viral variant and multiple viral variants were within the ranges of 64% to 68%, and 32% to 36%, respectively

Transmission of Single and Multiple Viral Variants in Primary HIV-1 Subtype C Infection

To address whether sequences of viral gag and env quasispecies collected during the early post-acute period can be utilized to determine multiplicity of transmitted HIV’s, recently developed approaches for analysis of viral evolution in acute HIV-1 infection [1,2] were applied. Specifically, phylogenetic reconstruction, inter- and intra-patient distribution of maximum and mean genetic distances, analysis of Poisson fitness, shape of highlighter plots, recombination analysis, and estimation of time to the most recent common ancestor (tMRCA) were utilized for resolving multiplicity of HIV-1 transmission in a set of viral quasispecies collected within 50 days post-seroconversion (p/s) in 25 HIV-infected individuals with estimated time of seroconversion. The decision on multiplicity of HIV infection was made based on the model’s fit with, or failure to explain, the observed extent of viral sequence heterogeneity. The initial analysis was based on phylogeny, inter-patient distribution of maximum and mean distances, and Poisson fitness, and was able to resolve multiplicity of HIV transmission in 20 of 25 (80%) cases. Additional analysis involved distribution of individual viral distances, highlighter plots, recombination analysis, and estimation of tMRCA, and resolved 4 of the 5 remaining cases. Overall, transmission of a single viral variant was identified in 16 of 25 (64%) cases, and transmission of multiple variants was evident in 8 of 25 (32%) cases. In one case multiplicity of HIV-1 transmission could not be determined. In primary HIV-1 subtype C infection, samples collected within 50 days p/s and analyzed by a single-genome amplification/sequencing technique can provide reliable identification o

Decision thresholds for transmission of single and multiple HIV-1 variants

<p>Note: The following decision strategy was applied for each analysis of subject's maximum and mean distances within <i>gag</i> and <i>env</i>: A sample with value exceeding the “Multi” threshold was associated with transmission of <i>multiple</i> HIV-1 variants. A sample with value smaller than the “Single” threshold was associated with transmission of a <i>single</i> HIV-1 variant. A sample with value exceeding the “Single” threshold but less than the “Multi” threshold was considered <i>undetermined</i> in relation to multiplicity of HIV-1 transmission.</p

Estimated tMRCA, days.

1<p>Days post-seroconversion.</p>2<p>HPD is the highest posterior density interval, which represents the most compact interval on the selected parameter that contains 95% of the posterior probability. It is a Bayesian analog to a confidence interval.</p>3<p>ESS: Effective Sample Size – should be higher than 100, and characterizes the posterior distribution.</p

Summary table of second-step analysis for transmission of multiple HIV-1 variants in five subjects.

<p>The table includes the following sections: study subjects with corresponding Fiebig stage and time of sampling in days p/s; cumulative results of distribution of pairwise distances based on six analyses per gene (ML-corrected distances, K2P-corrected distances, Hamming distances, ML-corrected distances to MRCA, K2P-corrected distances to consensus sequence, and Hamming distances to consensus sequence); analysis of highlighter plots; cumulative results of recombination analysis; tMRCA; number of methods suggesting transmission of single and multiple viral variants; and conclusion regarding multiplicity of HIV-1 transmission. Numeric coding: 0 – transmission of single viral variant; 1 – undetermined; 2 – transmission of multiple viral variants. Numeric coding of “1” and “2” are further enhanced by blue and light red colors.</p

Patient characteristics, time of sampling, and number of analyzed <i>gag</i> and <i>env</i> sequences

1<p>Years at the time of sampling.</p>2<p>log₁₀ copies/ml.</p>3<p>log₁₀ copies/10⁶ PBMC.</p>4<p>Date of sampling (first sampling for patients with dual dates of sampling).</p>5<p>Seroconversion.</p>6<p>Fiebig EW, Wright DJ, Rawal BD, Garrett PE, Schumacher RT, et al. (2003) Dynamics of HIV viremia and antibody seroconversion in plasma donors: implications for diagnosis and staging of primary HIV infection. AIDS 17: 1871-1879.</p>7<p>Subjects A and B had viral sequences available at two time points within 50 days p/s. Both sets were included in analysis.</p

Summary Table of initial assessment for multiplicity of HIV-1C transmission.

<p>The Table includes the following sections: Study subjects with corresponding Fiebig stage and time of sampling in days p/s; Results of phylogenetic analysis, Maximum distances, Mean distances, Results of the Poisson-Fitter analysis, and Conclusion regarding multiplicity of HIV-1 transmission. Color coding of background: columns with <i>gag</i> results have light blue background, and columns with <i>env</i> results have light yellow background. Numeric coding: 0 – transmission of single viral variant; 1 – undetermined; 2 – transmission of multiple viral variants. Numeric coding of “1” and “2” are further enhanced by blue and light red colors. Each subsection of maximum and mean distance for both <i>gag</i> and <i>env</i> includes 6 columns with ML-corrected pairwise distances, K2P-corrected pairwise distances, Hamming distances, ML-corrected distances to MRCA, K2P-corrected distances to consensus sequence, and Hamming distances to consensus sequence. The last column “Multiplicity of infection” represents summary of initial analysis per subject indicating transmission of “Single” or “Multiple” viral variants in successfully resolved cases. The uncertain and non-congruent results are interpreted as “Undetermined” cases, and are subjects for detailed analysis by additional methods.</p