Using dried blood spots collected under field condition to determine HIV-1 diversity and drug resistance mutations in resource limited Tanzania

Introduction: A dried blood spot (DBS) on filter paper has been used for different tests globally and has gained popularities in resource limited settings especially during HIV/AIDS epidemic. We assessed the efficiency of molecular characterization of HIV-1 subtypes using DBS collected under field conditions in northern Tanzania. Materials and Methods In 2011 and 2012, 60 DBS samples were collected under field conditions from exposed and newly diagnosed HIV-1 infected children from Kilimanjaro (n=20), Arusha (n=20), Tanga (n=10) and Manyara (n=10). Results and discussion Of 60 DBS analyzed at both Protease (PR) and Reverse Transcriptase (RT) regions, 45 (75%) were analyzed, including 17 (85%) from Kilimanjaro, 15 (75%) from Arusha, 8 (80%) from Tanga, and 5 (50%) from Manyara region. All 45 DBS characterized had viral load above 1000 copies/mL with mean log10 viral loads of 3.87 copies/mL (SD 0.995). The phylogenetic results indicated presence of subtype and circulating recombinant form (CRF). In which, 24 were subtype A1 (53.33%), 16 were subtype C (35.55%), 3 were subtype D (6.67%) and 2 were CRF10_CD (4.35%). All major mutations were detected in the RT region, none from protease (PR) region. The mutations detected were Y181C (n=8), K103 (n=4) and G190A (n=1), conferring resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs), and M184V (n=1), conferring resistance to lamivudine and emtricitabine. Conclusions: Our results indicate that DBS collected from field conditions in resource scarcity areas can be used to determine the phylogeny of the virus and drug resistance mutations in areas with diverse HIV-1 group M subtypes

High prevalence of pre-treatment and acquired HIV-1 drug resistance mutations among non-citizens living with HIV in Botswana

DATA AVAILABITY STATEMENT: The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found at: https://www.ncbi.nlm.nih.gov/genbank/, OR548006–OR548042.BACKGROUND: Approximately 30,000 non-citizens are living with HIV in Botswana, all of whom as of 2020 are eligible to receive free antiretroviral treatment (ART) within the country. We assessed the prevalence of HIV-1 mutational profiles [pre-treatment drug resistance (PDR) and acquired drug resistance (ADR)] among treatment-experienced (TE) and treatment-naïve (TN) non-citizens living with HIV in Botswana. METHODS: A total of 152 non-citizens living with HIV were enrolled from a migrant HIV clinic at Independence Surgery, a private practice in Botswana from 2019–2021. Viral RNA isolated from plasma samples were genotyped for HIV drug resistance (HIVDR) using Sanger sequencing. Major known HIV drug resistance mutations (DRMs) in the pol region were determined using the Stanford HIV Drug Resistance Database. The proportions of HIV DRMs amongst TE and TN non-citizens were estimated with 95% confidence intervals (95% CI) and compared between the two groups. RESULTS: A total of 60/152 (39.5%) participants had a detectable viral load (VL) >40 copies/mL and these were included in the subsequent analyses. The median age at enrollment was 43  years (Q1, Q3: 38–48). Among individuals with VL  >  40 copies/mL, 60% (36/60) were treatment-experienced with 53% (19/36) of them on Atripla. Genotyping had a 62% (37/60) success rate – 24 were TE, and 13 were TN. A total of 29 participants (78.4, 95% CI: 0.12–0.35) had major HIV DRMs, including at least one non-nucleoside reverse transcriptase inhibitor (NNRTI) associated DRM. In TE individuals, ADR to any antiretroviral drug was 83.3% (20/24), while for PDR was 69.2% (9/13). The most frequent DRMs were nucleoside reverse transcriptase inhibitors (NRTIs) M184V (62.1%, 18/29), NNRTIs V106M (41.4%, 12/29), and K103N (34.4%, 10/29). No integrase strand transfer inhibitor-associated DRMs were reported. CONCLUSION: We report high rates of PDR and ADR in ART-experienced and ARTnaïve non-citizens, respectively, in Botswana. Given the uncertainty of time of HIV acquisition and treatment adherence levels in this population, routine HIV1C VL monitoring coupled with HIVDR genotyping is crucial for long-term ART success.The Fogarty International Center at the US National Institutes of Health, the Fogarty International Center at the US National Institutes of Health, the NIH Fogarty International Centre, the European Union, the Sub-Saharan African Network for TB/HIV Research Excellence (SANTHE 2.0) from the Bill and Melinda Gates Foundation.https://www.frontiersin.org/journals/microbiologySchool of Health Systems and Public Health (SHSPH)SDG-03:Good heatlh and well-bein

Low prevalence of archived integrase strand transfer inhibitors resistance associated mutations in Botswana before the roll out of dolutegravir based first line antiretroviral therapy

DATA AVAILABITY STATEMENT: Publicly available datasets were analyzed in this study. This data can be found here: HIV-1 sequences are available on request through the PANGEA consortium (www.pangea-hiv.org). BCPP data are available at https://data.cdc.gov/Global-Health/BotswanaCombination-Prevention-Project-BCPP-Publi/qcw5-4m9q.BACKGROUND: We evaluated the prevalence of archived proviral drug resistance mutations (DRMs) associated with resistance to integrase strand transfer inhibitors (INSTIs) shortly before Botswana transitioned in 2016 to using dolutegravir (DTG)-based antiretroviral treatment in first-line regimens. METHODS: We used the Stanford University HIV drug resistance database to analyze INSTI-resistance associated mutations (RAMs) in a large representative population-based cohort of adults recruited in 30 geographically dispersed communities as part of the Botswana Combination Prevention Project (BCPP) cohort from 2013 to 2018. A total of 5,144 HIV-1 proviral DNA sequences were included in our analysis; 1,281 sequences were from antiretroviral therapy (ART)-naïve individuals and 3,863 sequences were from non-nucleoside reverse transcriptase inhibitor (NNRTI) ART-experienced individuals. None of the sequences were from DTG-ART experienced participants. RESULTS: The overall prevalence of major INSTIs DRMs was 1.11% (95% CI 0.82–1.39%). The prevalence of INSTI DRMs in ART-naïve individuals was 1.64% (21/1,281) and 0.93% (36/3,863) in ART-experienced individuals. Major INSTI-RAMs detected in ART-naïve individuals were E138K (2/1,281; 0.16%), G140R (8/1,281;0.62%), E92G (2/1,281;0.16%), R263K (5/1,281; 0.4%), N155H (1/1,281; 0.08%), P145S (1/1,281;0.008%). Among the ART-experienced individuals, major INSTI RAMs detected were E138K (4/3,863; 0.10%), G140R (25/3,863;0.65%), G118R (2/3,863, 0.05%), R263K (4/3,863, 0.10%), T66I (1/3,863;0.03%), E138K + G140R (1/3,863, 0.03%|), G140R + R263K (1/3,863, 0.03%). High-level resistance to cabotegravir (CAB), elvitegravir (EVG), and raltegravir (RAL) was detected in 0.70, 0.16 and 0.06% of the individuals, respectively. Notably, bictegravir (BIC) and dolutegravir (DTG) showed no high-level resistance. CONCLUSION: The overall prevalence of archived INSTI RAMs in Botswana was low prior to transitioning to first-line DTG-based ART regimens, and did not differ between ART-naïve and ART-experienced individuals. Ongoing surveillance of INSTI DRMs in Botswana will allow for re-assessment of INSTI resistance risk following nationwide DTG rollout.The President’s Emergency Plan for AIDS Relief, the Sub-Saharan African Network for TB/HIV Research Excellence from the Bill & Melinda Gates Foundation, the Fogarty International Center at the US National Institutes of Health Award, the Fogarty International Center at the US National Institutes of Health Award, the European Union, the Trials of Excellence in Southern Africa, Africa Research Excellence Fund Research Development Fellowship.https://www.frontiersin.org/journals/microbiologySchool of Health Systems and Public Health (SHSPH)SDG-03:Good heatlh and well-bein

Emergence of SARS-CoV-2 Omicron lineages BA.4 and BA.5 in South Africa

Three lineages (BA.1, BA.2 and BA.3) of the SARS-CoV-2 Omicron variant of concern predominantly drove South Africa's fourth COVID-19 wave. We have now identified two new lineages, BA.4 and BA.5, responsible for a fifth wave of infections. The spike proteins of BA.4 and BA.5 are identical, and comparable to BA.2 except for the addition of 69-70del (present in the Alpha variant and the BA.1 lineage), L452R (present in the Delta variant), F486V and the wild type amino acid at Q493.The two lineages only differ outside of the spike region. The 69-70 deletion in spike allows these lineages to be identified by the proxy marker of S-gene target failure, on the background of variants not possessing this feature . BA.4 and BA.5 have rapidly replaced BA.2, reaching more than 50% of sequenced cases in South Africa by the first week of April 2022. Using a multinomial logistic regression model, we estimate growth advantages for BA.4 and BA.5 of 0.08 (95% CI: 0.08 - 0.09) and 0.10 (95% CI: 0.09 - 0.11) per day respectively over BA.2 in South Africa. The continued discovery of genetically diverse Omicron lineages points to the hypothesis that a discrete reservoir, such as human chronic infections and/or animal hosts, is potentially contributing to further evolution and dispersal of the virus

Rapid dynamic changes of FL.2 variant : a case report of COVID-19 breakthrough infection

AVAILABILITY OF DATA AND MATERIALS : The figures and tables of the study are included in the manuscript. The FASTA files are deposited in the Global Initiative on Sharing All Influenza Data (GISAID) database https://doi.org/10.55876/gis8.230821xh : Day-08 is EPI_ISL_17601323[hCoV-19/Botswana/BHP_0123017470/2023], and Day-21 is EPI_ISL_17601322[hCoV-19/Botswana/BHP_1100219671/2023].We investigated intra-host genetic evolution using two SARS-CoV-2 isolates from a fully vaccinated (primary schedule x2 doses of AstraZeneca plus a booster of Pfizer), >70-year-old woman with a history of lymphoma and hypertension who presented a SARS-CoV-2 infection for 3 weeks prior to death due to COVID-19. Two full genome sequences were determined from samples taken 13 days apart with both belonging to Pango lineage FL.2: the first detection of this Omicron sub-variant in Botswana. FL.2 is a sub-lineage of XBB.1.9.1. The repertoire of mutations and minority variants in the Spike protein differed between the two time points. Notably, we also observed deletions within the ORF1a and Membrane proteins; both regions are associated with high T-cell epitope density. The internal milieu of immune-suppressed individuals may accelerate SARS-CoV-2 evolution; hence, close monitoring is warranted.Supported by the Sub-Saharan African Network for TB/HIV Research Excellence (SANTHE) which is funded by the Science for Africa Foundation to the Developing Excellence in Leadership, Training and Science in Africa (DELTAS Africa) programme [Del-22-007] with support from Wellcome Trust and the UK Foreign, Commonwealth & Development Office and is part of the EDCPT2 programme supported by the European Union; the Bill & Melinda Gates Foundation [INV-033558]; and Gilead Sciences Inc., [19275]. This work was also supported by the National Institutes of Health NIH Fogarty International Center K43 TW012350. Sequencing was supported by funding from the Foundation for Innovation in Diagnostics, the Bill and Melinda Gates Foundation, the National Institutes of Health Fogarty International Centre, the HHS/NIH/National Institute of Allergy and Infectious Diseases (NIAID) and the Africa Centers of Disease Control through the Pathogen Genomics Initiative.http://www.elsevier.com/locate/ijidhj2024School of Health Systems and Public Health (SHSPH)SDG-03:Good heatlh and well-bein

Low prevalence of archived integrase strand transfer inhibitors resistance associated mutations in Botswana before the roll out of dolutegravir based first line antiretroviral therapy

BackgroundWe evaluated the prevalence of archived proviral drug resistance mutations (DRMs) associated with resistance to integrase strand transfer inhibitors (INSTIs) shortly before Botswana transitioned in 2016 to using dolutegravir (DTG)-based antiretroviral treatment in first-line regimens.MethodsWe used the Stanford University HIV drug resistance database to analyze INSTI-resistance associated mutations (RAMs) in a large representative population-based cohort of adults recruited in 30 geographically dispersed communities as part of the Botswana Combination Prevention Project (BCPP) cohort from 2013 to 2018. A total of 5,144 HIV-1 proviral DNA sequences were included in our analysis; 1,281 sequences were from antiretroviral therapy (ART)-naïve individuals and 3,863 sequences were from non-nucleoside reverse transcriptase inhibitor (NNRTI) ART-experienced individuals. None of the sequences were from DTG-ART experienced participants.ResultsThe overall prevalence of major INSTIs DRMs was 1.11% (95% CI 0.82–1.39%). The prevalence of INSTI DRMs in ART-naïve individuals was 1.64% (21/1,281) and 0.93% (36/3,863) in ART-experienced individuals. Major INSTI-RAMs detected in ART-naïve individuals were E138K (2/1,281; 0.16%), G140R (8/1,281;0.62%), E92G (2/1,281;0.16%), R263K (5/1,281; 0.4%), N155H (1/1,281; 0.08%), P145S (1/1,281;0.008%). Among the ART-experienced individuals, major INSTI RAMs detected were E138K (4/3,863; 0.10%), G140R (25/3,863;0.65%), G118R (2/3,863, 0.05%), R263K (4/3,863, 0.10%), T66I (1/3,863;0.03%), E138K + G140R (1/3,863, 0.03%|), G140R + R263K (1/3,863, 0.03%). High-level resistance to cabotegravir (CAB), elvitegravir (EVG), and raltegravir (RAL) was detected in 0.70, 0.16 and 0.06% of the individuals, respectively. Notably, bictegravir (BIC) and dolutegravir (DTG) showed no high-level resistance.ConclusionThe overall prevalence of archived INSTI RAMs in Botswana was low prior to transitioning to first-line DTG-based ART regimens, and did not differ between ART-naïve and ART-experienced individuals. Ongoing surveillance of INSTI DRMs in Botswana will allow for re-assessment of INSTI resistance risk following nationwide DTG rollout

Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in southern Africa has been characterised by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, whilst the second and third waves were driven by the Beta and Delta variants respectively1–3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng Province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, predicted to influence antibody neutralization and spike function4. Here, we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity.Temple University. College of Science and TechnologyBiolog

Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in southern Africa has been characterised by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, whilst the second and third waves were driven by the Beta and Delta variants, respectively1-3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng Province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, predicted to influence antibody neutralization and spike function4. Here, we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance.

Investment in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing in Africa over the past year has led to a major increase in the number of sequences that have been generated and used to track the pandemic on the continent, a number that now exceeds 100,000 genomes. Our results show an increase in the number of African countries that are able to sequence domestically and highlight that local sequencing enables faster turnaround times and more-regular routine surveillance. Despite limitations of low testing proportions, findings from this genomic surveillance study underscore the heterogeneous nature of the pandemic and illuminate the distinct dispersal dynamics of variants of concern-particularly Alpha, Beta, Delta, and Omicron-on the continent. Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve while the continent faces many emerging and reemerging infectious disease threats. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century