Comparing Gold-Standard Sanger Sequencing with Two Next-Generation Sequencing Platforms of HIV-1 gp160 Single Genome Amplicons.

Our goal was to assess the accuracy of next generation sequencing (NGS) compared with Sanger. We performed single genome amplification (SGA) of HIV-1 gp160 on extracted tissue DNA from two HIV+ individuals. Amplicons (n = 30) were sequenced with Sanger or reamplified with barcoded primers and pooled before sequencing using Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PB). For each amplicon, a consensus sequence for NGS reads was obtained by (1) mapping reads to the Sanger sequence when available ("reference-based") or (2) mapping reads to a "pseudo-reference" sequence, i.e., a consensus sequence of a subset of NGS reads ("reference-free"). PB reads were clustered based on genetic similarity. A Sanger consensus sequence was obtained for 23/30 amplicons, for which all NGS consensus sequences were identical (n = 9) or nearly identical (n = 14) compared with Sanger. For the nine mismatches between Sanger/NGS, the nucleotide in the NGS sequence matched all other sequences from that patient. Of the 7/30 amplicons without a Sanger sequence, NGS sequences had ≥35 ambiguous calls in five amplicons and 0 ambiguities in two amplicons. Analysis of the electropherograms showed failure of a single sequencing primer for the latter two amplicons (consistent with a single template) and overlapping peaks for the other five (consistent with multiple templates). Clustering results closely followed the Sanger/NGS consensus results, where amplicons derived from a single template also had a single cluster and vice versa (with one exception, which could be the result of barcode misidentification). Representative sequences from the clusters contained 2-13 differences compared with Sanger/NGS. In summary, we show that both ONT and PB can produce amplicon consensus sequences with similar or higher accuracy compared with Sanger and, importantly, without the need for a known reference sequence. Clustering could be useful in some circumstances to predict or confirm the presence of multiple starting templates.

A bioinformatic analysis of T-cell epitope diversity in SARS-CoV-2 variants: association with COVID-19 clinical severity in the United States population.

Long-term immunity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires the identification of T-cell epitopes affecting host immunogenicity. In this computational study, we explored the CD8+ epitope diversity estimated in 27 of the most common HLA-A and HLA-B alleles, representing most of the United States population. Analysis of 16 SARS-CoV-2 variants [B.1, Alpha (B.1.1.7), five Delta (AY.100, AY.25, AY.3, AY.3.1, AY.44), and nine Omicron (BA.1, BA.1.1, BA.2, BA.4, BA.5, BQ.1, BQ.1.1, XBB.1, XBB.1.5)] in analyzed MHC class I alleles revealed that SARS-CoV-2 CD8+ epitope conservation was estimated at 87.6%-96.5% in spike (S), 92.5%-99.6% in membrane (M), and 94.6%-99% in nucleocapsid (N). As the virus mutated, an increasing proportion of S epitopes experienced reduced predicted binding affinity: 70% of Omicron BQ.1-XBB.1.5 S epitopes experienced decreased predicted binding, as compared with ~3% and ~15% in the earlier strains Delta AY.100-AY.44 and Omicron BA.1-BA.5, respectively. Additionally, we identified several novel candidate HLA alleles that may be more susceptible to severe disease, notably HLA-A*32:01, HLA-A*26:01, and HLA-B*53:01, and relatively protected from disease, such as HLA-A*31:01, HLA-B*40:01, HLA-B*44:03, and HLA-B*57:01. Our findings support the hypothesis that viral genetic variation affecting CD8 T-cell epitope immunogenicity contributes to determining the clinical severity of acute COVID-19. Achieving long-term COVID-19 immunity will require an understanding of the relationship between T cells, SARS-CoV-2 variants, and host MHC class I genetics. This project is one of the first to explore the SARS-CoV-2 CD8+ epitope diversity that putatively impacts much of the United States population.

Temporary increase in circulating replication-competent latent HIV-infected resting CD4+ T cells after switch to an integrase inhibitor based antiretroviral regimen.

BACKGROUND: The principal barrier to an HIV cure is the presence of the latent viral reservoir (LVR), which has been understudied in African populations. From 2018 to 2019, Uganda instituted a nationwide rollout of ART consisting of Dolutegravir (DTG) with two NRTI, which replaced the previous regimen of one NNRTI and the same two NRTI. METHODS: Changes in the inducible replication-competent LVR (RC-LVR) of ART-suppressed Ugandans with HIV (n = 88) from 2015 to 2020 were examined using the quantitative viral outgrowth assay. Outgrowth viruses were examined for viral evolution. Changes in the RC-LVR were analyzed using three versions of a Bayesian model that estimated the decay rate over time as a single, linear rate (model A), or allowing for a change at time of DTG initiation (model B&C). FINDINGS: Model A estimated the slope of RC-LVR change as a non-significant positive increase, which was due to a temporary spike in the RC-LVR that occurred 0-12 months post-DTG initiation (p < 0.005). This was confirmed with models B and C; for instance, model B estimated a significant decay pre-DTG initiation with a half-life of 6.9 years, and an ∼1.7-fold increase in the size of the RC-LVR post-DTG initiation. There was no evidence of viral failure or consistent evolution in the cohort. INTERPRETATION: These data suggest that the change from NNRTI- to DTG-based ART is associated with a significant temporary increase in the circulating RC-LVR. FUNDING: Supported by the NIH (grant 1-UM1AI164565); Gilead HIV Cure Grants Program (90072171); Canadian Institutes of Health Research (PJT-155990); and Ontario Genomics-Canadian Statistical Sciences Institute.

Evaluating real-world emissions from in-use buses and taxis using on-road remote sensing.

Assessing real-world emissions from buses and taxis is vital to comprehend their impact on urban air quality. Such vehicles differ significantly from the majority of the fleet owing to their higher mileage rates. However, few studies have focused on specifically assessing the emissions from this segment of the vehicle fleet. In this context, this study evaluated the real-world emissions of nitrogen oxides (NOx) from in-use buses and taxis in Dublin, Ireland, using crossroad remote sensing technology. The remote sensing system was deployed at strategic locations throughout the city to capture on-road emissions from passing vehicles. The collected data included vehicle related information such as emission standard, make, and mileage, and pollutants including NOx. Based on this data, analysis was aimed to understand the impact of Euro emission standard, ambient temperature, mileage, and make of the vehicle on NOx emissions. The results reveal that the average emissions from taxis reduce by 37% from Euro 5 to Euro 6b, and average emissions from Euro 6 buses are 87% lower compared to Euro 5. The trends in emission factors (EFs) of buses and taxis were similar during summer and winter sampling. Moreover, on comparing the emissions from the top five taxi manufacturers, different trends in the emission factors were observed. Finally, the study found that the effect of vehicle mileage on emissions was unclear for both buses and taxis. In any case, these findings provide valuable insights into the real-world emission performance of the existing fleet of buses and taxis in Dublin and highlight the need for targeted measures to reduce emissions from these vehicles. The results can assist policymakers and urban planners in formulating evidence-based strategies to improve air quality in Dublin and other cities facing similar challenges.