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

The SARS-CoV-2 epidemic in southern Africa has been characterized by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, while the second and third waves were driven by the Beta (B.1.351) and Delta (B.1.617.2) 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, B.1.1.529) 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, which are 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.

Genome Detective Coronavirus Typing Tool for rapid identification and characterization of novel coronavirus genomes.

SUMMARY: Genome detective is a web-based, user-friendly software application to quickly and accurately assemble all known virus genomes from next-generation sequencing datasets. This application allows the identification of phylogenetic clusters and genotypes from assembled genomes in FASTA format. Since its release in 2019, we have produced a number of typing tools for emergent viruses that have caused large outbreaks, such as Zika and Yellow Fever Virus in Brazil. Here, we present the Genome Detective Coronavirus Typing Tool that can accurately identify the novel severe acute respiratory syndrome (SARS)-related coronavirus (SARS-CoV-2) sequences isolated in China and around the world. The tool can accept up to 2000 sequences per submission and the analysis of a new whole-genome sequence will take approximately 1 min. The tool has been tested and validated with hundreds of whole genomes from 10 coronavirus species, and correctly classified all of the SARS-related coronavirus (SARSr-CoV) and all of the available public data for SARS-CoV-2. The tool also allows tracking of new viral mutations as the outbreak expands globally, which may help to accelerate the development of novel diagnostics, drugs and vaccines to stop the COVID-19 disease. AVAILABILITY AND IMPLEMENTATION: https://www.genomedetective.com/app/typingtool/cov. CONTACT: koen@emweb.be or deoliveira@ukzn.ac.za. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Behavioral changes before lockdown and decreased retail and recreation mobility during lockdown contributed most to controlling COVID-19 in Western countries.

BACKGROUND: The COVID-19 pandemic has prompted a lockdown in many countries to control the exponential spread of the SARS-CoV-2 virus, hereby reducing the time-varying basic reproduction number (Rt) to below one. Governments are looking for evidence to balance the demand of their citizens to ease some of the restriction, against the fear of a new peak in infections. In this study, we wanted to quantify the relative contribution of mobility restrictions, and that of behavioral changes that occurred already before the lockdowns, on the reduction of transmission during lockdowns in Western countries in early 2020. METHODS: Incidence data of cases and deaths from the first wave of infections for 35 Western countries (32 European, plus Israel, USA and Canada) were analyzed using epidemiological compartment models in a Bayesian framework. Mobility data was used to estimate the timing of changes associated with a lockdown, and was correlated with estimated reductions of Rt. RESULTS: Across all countries, the initial median estimate for Rt was 3.6 (95% IQR 2.4-5.2), and it was reduced to 0.78 (95% IQR 0.58-1.01) during lockdown. 48% (18-65%) of the reduction occurred already in the week before lockdown, with lockdown itself causing the remaining drop in transmission. A lower Rt during lockdown was independently associated with an increased time spent at home (0.21 per 10% more time, p < 0.007), and decreased mobility related to retail and recreation (0.07 per 10% less mobility, p < 0.008). CONCLUSIONS: In a Western population unaware of the risk, SARS-CoV-2 can be highly contagious with a reproduction number R0 > 5. Our results are consistent with evidence that recreational activities (including restaurant and bar visits) enable super-spreading events. Exiting from lockdown therefore requires continued physical distancing and tight control on this kind of activities.

VIRULIGN: fast codon-correct alignment and annotation of viral genomes.

SUMMARY: Virus sequence data are an essential resource for reconstructing spatiotemporal dynamics of viral spread as well as to inform treatment and prevention strategies. However, the potential benefit of these applications critically depends on accurate and correctly annotated alignments of genetically heterogeneous data. VIRULIGN was built for fast codon-correct alignments of large datasets, with standardized and formalized genome annotation and various alignment export formats. AVAILABILITY AND IMPLEMENTATION: VIRULIGN is freely available at https://github.com/rega-cev/virulign as an open source software project. SUPPLEMENTARY INFORMATION: Supplementary data is available at Bioinformatics online.

Genome Detective: an automated system for virus identification from high-throughput sequencing data.

SUMMARY: Genome Detective is an easy to use web-based software application that assembles the genomes of viruses quickly and accurately. The application uses a novel alignment method that constructs genomes by reference-based linking of de novo contigs by combining amino-acids and nucleotide scores. The software was optimized using synthetic datasets to represent the great diversity of virus genomes. The application was then validated with next generation sequencing data of hundreds of viruses. User time is minimal and it is limited to the time required to upload the data. AVAILABILITY AND IMPLEMENTATION: Available online: http://www.genomedetective.com/app/typingtool/virus/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Possible footprints of APOBEC3F and/or other APOBEC3 deaminases, but not APOBEC3G, on HIV-1 from patients with acute/early and chronic infections.

UNLABELLED: Members of the apolipoprotein B mRNA-editing enzyme-catalytic polypeptide-like-3 (APOBEC3) innate cellular cytidine deaminase family, particularly APOBEC3F and APOBEC3G, can cause extensive and lethal G-to-A mutations in HIV-1 plus-strand DNA (termed hypermutation). It is unclear if APOBEC3-induced mutations in vivo are always lethal or can occur at sublethal levels that increase HIV-1 diversification and viral adaptation to the host. The viral accessory protein Vif counteracts APOBEC3 activity by binding to APOBEC3 and promoting proteasome degradation; however, the efficiency of this interaction varies, since a range of hypermutation frequencies are observed in HIV-1 patient DNA. Therefore, we examined "footprints" of APOBEC3G and APOBEC3F activity in longitudinal HIV-1 RNA pol sequences from approximately 3,000 chronically infected patients by determining whether G-to-A mutations occurred in motifs that were favored or disfavored by these deaminases. G-to-A mutations were more frequent in APOBEC3G-disfavored than in APOBEC3G-favored contexts. In contrast, mutations in APOBEC3F-disfavored contexts were relatively rare, whereas mutations in contexts favoring APOBEC3F (and possibly other deaminases) occurred 16% more often than average G-to-A mutations. These results were supported by analyses of >500 HIV-1 env sequences from acute/early infection. IMPORTANCE: Collectively, our results suggest that APOBEC3G-induced mutagenesis is lethal to HIV-1, whereas mutagenesis caused by APOBEC3F and/or other deaminases may result in sublethal mutations that might facilitate viral diversification. Therefore, Vif-specific cytotoxic T lymphocyte (CTL) responses and drugs that manipulate the interplay between Vif and APOBEC3 may have beneficial or detrimental clinical effects depending on how they affect the binding of Vif to various members of the APOBEC3 family.

APOBEC3G-induced hypermutation of human immunodeficiency virus type-1 is typically a discrete "all or nothing" phenomenon.

The rapid evolution of Human Immunodeficiency Virus (HIV-1) allows studies of ongoing host-pathogen interactions. One key selective host factor is APOBEC3G (hA3G) that can cause extensive and inactivating Guanosine-to-Adenosine (G-to-A) mutation on HIV plus-strand DNA (termed hypermutation). HIV can inhibit this innate anti-viral defense through binding of the viral protein Vif to hA3G, but binding efficiency varies and hypermutation frequencies fluctuate in patients. A pivotal question is whether hA3G-induced G-to-A mutation is always lethal to the virus or if it may occur at sub-lethal frequencies that could increase viral diversification. We show in vitro that limiting-levels of hA3G-activity (i.e. when only a single hA3G-unit is likely to act on HIV) produce hypermutation frequencies similar to those in patients and demonstrate in silico that potentially non-lethal G-to-A mutation rates are ∼10-fold lower than the lowest observed hypermutation levels in vitro and in vivo. Our results suggest that even a single incorporated hA3G-unit is likely to cause extensive and inactivating levels of HIV hypermutation and that hypermutation therefore is typically a discrete "all or nothing" phenomenon. Thus, therapeutic measures that inhibit the interaction between Vif and hA3G will likely not increase virus diversification but expand the fraction of hypermutated proviruses within the infected host.

RegaDB: community-driven data management and analysis for infectious diseases.

SUMMARY: RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB provides researchers with a mechanism to collect data in a uniform format and offers them a canvas to make newly developed bioinformatics tools available to clinicians and virologists through a user friendly interface. AVAILABILITY AND IMPLEMENTATION: Source code, binaries and documentation are available on http://rega.kuleuven.be/cev/regadb. RegaDB is written in the Java programming language, using a web-service-oriented architecture.

Treatment-associated polymorphisms in protease are significantly associated with higher viral load and lower CD4 count in newly diagnosed drug-naive HIV-1 infected patients.

BACKGROUND: The effect of drug resistance transmission on disease progression in the newly infected patient is not well understood. Major drug resistance mutations severely impair viral fitness in a drug free environment, and therefore are expected to revert quickly. Compensatory mutations, often already polymorphic in wild-type viruses, do not tend to revert after transmission. While compensatory mutations increase fitness during treatment, their presence may also modulate viral fitness and virulence in absence of therapy and major resistance mutations. We previously designed a modeling technique that quantifies genotypic footprints of in vivo treatment selective pressure, including both drug resistance mutations and polymorphic compensatory mutations, through the quantitative description of a fitness landscape from virus genetic sequences. RESULTS: Genotypic correlates of viral load and CD4 cell count were evaluated in subtype B sequences from recently diagnosed treatment-naive patients enrolled in the SPREAD programme. The association of surveillance drug resistance mutations, reported compensatory mutations and fitness estimated from drug selective pressure fitness landscapes with baseline viral load and CD4 cell count was evaluated using regression techniques. Protease genotypic variability estimated to increase fitness during treatment was associated with higher viral load and lower CD4 cell counts also in treatment-naive patients, which could primarily be attributed to well-known compensatory mutations at highly polymorphic positions. By contrast, treatment-related mutations in reverse transcriptase could not explain viral load or CD4 cell count variability. CONCLUSIONS: These results suggest that polymorphic compensatory mutations in protease, reported to be selected during treatment, may improve the replicative capacity of HIV-1 even in absence of drug selective pressure or major resistance mutations. The presence of this polymorphic variation may either reflect a history of drug selective pressure, i.e. transmission from a treated patient, or merely be a result of diversity in wild-type virus. Our findings suggest that transmitted drug resistance has the potential to contribute to faster disease progression in the newly infected host and to shape the HIV-1 epidemic at a population level.

A standardized framework for accurate, high-throughput genotyping of recombinant and non-recombinant viral sequences.

Human immunodeficiency virus type-1 (HIV-1), hepatitis B and C and other rapidly evolving viruses are characterized by extremely high levels of genetic diversity. To facilitate diagnosis and the development of prevention and treatment strategies that efficiently target the diversity of these viruses, and other pathogens such as human T-lymphotropic virus type-1 (HTLV-1), human herpes virus type-8 (HHV8) and human papillomavirus (HPV), we developed a rapid high-throughput-genotyping system. The method involves the alignment of a query sequence with a carefully selected set of pre-defined reference strains, followed by phylogenetic analysis of multiple overlapping segments of the alignment using a sliding window. Each segment of the query sequence is assigned the genotype and sub-genotype of the reference strain with the highest bootstrap (>70%) and bootscanning (>90%) scores. Results from all windows are combined and displayed graphically using color-coded genotypes. The new Virus-Genotyping Tools provide accurate classification of recombinant and non-recombinant viruses and are currently being assessed for their diagnostic utility. They have incorporated into several HIV drug resistance algorithms including the Stanford (http://hivdb.stanford.edu) and two European databases (http://www.umcutrecht.nl/subsite/spread-programme/ and http://www.hivrdb.org.uk/) and have been successfully used to genotype a large number of sequences in these and other databases. The tools are a PHP/JAVA web application and are freely accessible on a number of servers including: http://bioafrica.mrc.ac.za/rega-genotype/html/, http://lasp.cpqgm.fiocruz.br/virus-genotype/html/, http://jose.med.kuleuven.be/genotypetool/html/.

Estimating the individualized HIV-1 genetic barrier to resistance using a nelfinavir fitness landscape.

BACKGROUND: Failure on Highly Active Anti-Retroviral Treatment is often accompanied with development of antiviral resistance to one or more drugs included in the treatment. In general, the virus is more likely to develop resistance to drugs with a lower genetic barrier. Previously, we developed a method to reverse engineer, from clinical sequence data, a fitness landscape experienced by HIV-1 under nelfinavir (NFV) treatment. By simulation of evolution over this landscape, the individualized genetic barrier to NFV resistance may be estimated for an isolate. RESULTS: We investigated the association of estimated genetic barrier with risk of development of NFV resistance at virological failure, in 201 patients that were predicted fully susceptible to NFV at baseline, and found that a higher estimated genetic barrier was indeed associated with lower odds for development of resistance at failure (OR 0.62 (0.45 - 0.94), per additional mutation needed, p = .02). CONCLUSIONS: Thus, variation in individualized genetic barrier to NFV resistance may impact effective treatment options available after treatment failure. If similar results apply for other drugs, then estimated genetic barrier may be a new clinical tool for choice of treatment regimen, which allows consideration of available treatment options after virological failure.

Genome Detective Coronavirus Typing Tool for rapid identification and characterization of novel coronavirus genomes.

Genome Detective is a web-based, user-friendly software application to quickly and accurately assemble all known virus genomes from next generation sequencing datasets. This application allows the identification of phylogenetic clusters and genotypes from assembled genomes in FASTA format. Since its release in 2019, we have produced a number of typing tools for emergent viruses that have caused large outbreaks, such as Zika and Yellow Fever Virus in Brazil. Here, we present The Genome Detective Coronavirus Typing Tool that can accurately identify novel coronavirus (2019-nCoV) sequences isolated in China and around the world. The tool can accept up to 2,000 sequences per submission and the analysis of a new whole genome sequence will take approximately one minute. The tool has been tested and validated with hundreds of whole genomes from ten coronavirus species, and correctly classified all of the SARS-related coronavirus (SARSr-CoV) and all of the available public data for 2019-nCoV. The tool also allows tracking of new viral mutations as the outbreak expands globally, which may help to accelerate the development of novel diagnostics, drugs and vaccines.

SANTA-SIM: simulating viral sequence evolution dynamics under selection and recombination.

Simulations are widely used to provide expectations and predictive distributions under known conditions against which to compare empirical data. Such simulations are also invaluable for testing and comparing the behaviour and power of inference methods. We describe SANTA-SIM, a software package to simulate the evolution of a population of gene sequences forwards through time. It models the underlying biological processes as discrete components: replication, recombination, point mutations, insertion-deletions, and selection under various fitness models and population size dynamics. The software is designed to be intuitive to work with for a wide range of users and executable in a cross-platform manner.

A computational method for the identification of Dengue, Zika and Chikungunya virus species and genotypes.

In recent years, an increasing number of outbreaks of Dengue, Chikungunya and Zika viruses have been reported in Asia and the Americas. Monitoring virus genotype diversity is crucial to understand the emergence and spread of outbreaks, both aspects that are vital to develop effective prevention and treatment strategies. Hence, we developed an efficient method to classify virus sequences with respect to their species and sub-species (i.e. serotype and/or genotype). This tool provides an easy-to-use software implementation of this new method and was validated on a large dataset assessing the classification performance with respect to whole-genome sequences and partial-genome sequences. Available online: http://krisp.org.za/tools.php.

The incidence of multidrug and full class resistance in HIV-1 infected patients is decreasing over time (2001-2006) in Portugal.

Despite improvements in HIV treatment, the prevalence of multidrug resistance and full class resistance is still reported to be increasing. However, to investigate whether current treatment strategies are still selecting for multidrug and full class resistance, the incidence, instead of the prevalence, is more informative. Temporal trends in multidrug resistance (MDR defined as at most 1 drug fully susceptible) and full class resistance (FCR defined as no drug in this class fully susceptible) in Portugal based on 3394 viral isolates genotyped from 2000 to 2006 were examined using the Rega 6.4.1 interpretation system. From July 2001 to July 2006 there was a significant decreasing trend of MDR with 5.7%, 5.2%, 3.8%, 3.4% and 2.7% for the consecutive years (P = 0.003). Multivariate analysis showed that for every consecutive year the odds of having a new MDR case decreased with 20% (P = 0.003). Furthermore, a decline was observed for NRTI- and PI-FCR (both P < 0.001), whereas for NNRTI-FCR a parabolic trend over time was seen (P < 0.001), with a maximum incidence in 2003-'04. Similar trends were obtained when scoring resistance for only one drug within a class or by using another interpretation system. In conclusion, the incidence of multidrug and full class resistance is decreasing over time in Portugal, with the exception of NNRTI full class resistance which showed an initial rise, but subsequently also a decline. This is most probably reflecting the changing drug prescription, the increasing efficiency of HAART and the improved management of HIV drug resistance. This work was presented in part at the Eighth International Congress on Drug Therapy in HIV Infection, Glasgow (UK), 12-16 November 2006 (PL5.5); and at the Fifth European HIV Drug Resistance Workshop, Cascais (Portugal), 28-30 March 2007 (Abstract 1).

Modelled in vivo HIV fitness under drug selective pressure and estimated genetic barrier towards resistance are predictive for virological response.

BACKGROUND: A method has been developed to estimate a fitness landscape experienced by HIV-1 under treatment selective pressure as a function of the genotypic sequence thereby also estimating the genetic barrier to resistance. METHODS: We evaluated the performance of two estimated fitness landscapes (nelfinavir [NFV] and zidovudine [AZT] plus lamivudine [3TC]) to predict week 12 viral load (VL) change for 176 treatment change episodes (TCEs) and probability of week 48 virological failure for 90 TCEs, in treatment experienced patients starting these drugs in combination. RESULTS: A higher genetic barrier for AZT plus 3TC, (quantified per additional mutation required to develop resistance against these drugs) was associated with a 0.54 (95% confidence interval [CI] 0.30-0.77) larger log10 VL reduction at 12 weeks (P < 0.0001) and a 0.39 (95%/ CI 0.23-0.66) lower odds of virological failure at 48 weeks (P = 0.0005), in analyses adjusting for the pre-TCE VL and the exact time-lag between the TCE and the date of determining response VL. The strength of these associations was comparable with those seen with expert interpretation systems (Rega, ANRS and HIVDB). A higher genetic barrier to NFV resistance was the only genotypic predictor that tended to be associated with a 0.19 (95% CI 0-0.39) higher log10 VL reduction at 12 weeks (P = 0.05) and a 0.63 (95% CI 0.36-1.09) lower odds of virological failure at 48 weeks ( P = 0.10) per additional mutation. CONCLUSIONS: These results suggest that an estimated genetic barrier derived from fitness landscapes may contribute to an improvement of predicted treatment outcome for NFV and this approach should be explored for other drugs.

Impact of HIV-1 protease mutations A71V/T and T74S on M89I/V-mediated protease inhibitor resistance in subtype G isolates.

OBJECTIVES: Non-B human immunodeficiency virus (HIV)-1 subtypes possess several amino acid signatures in the viral protease that distinguish them from subtype B, some of which are reported as secondary drug-related mutations. We have previously shown a strong statistical interdependency of residues 71, 89 and 90 in subtype G, but the impact of substitutions on protease inhibitor (PI) resistance is unknown. PATIENTS AND METHODS: We selected subtype G viruses from patients with diverse amino acid combinations at codons 71 (A/T), 74 (T/S), 89 (I/L/M/V) and 90 (L/M). Viral protease genes were inserted into an HIV molecular clone (HXB2). PI drug susceptibilities of chimeric viruses were determined. RESULTS: In isolates displaying 89I/V in combination with A71 or T74, a reversal to subtype G wild-type 89M was observed after growth in the absence of PI. The presence of 71T in one isolate and 74S in another allowed the persistence of 89I. Mutation 90M conferred intermediate but significant degrees of drug resistance to ritonavir and nelfinavir in subtype G viruses. The combination of 71T or 74S, 89I and 90M resulted in higher levels of resistance to those PIs. CONCLUSIONS: Our results point to the hypothesis that 71T or 74S stabilizes 89I in the protease of subtype G, whose association was previously seen by Bayesian network analyses. The association of 89I with 90M may further increase the PI resistance of subtype G viruses when compared with 90M alone, highlighting novel mutational profiles for drug resistance in this non-B subtype.

Prevalence and epidemiology of HIV type 1 drug resistance among newly diagnosed therapy-naive patients in Belgium from 2003 to 2006.

This study is the first prospective study to assess the prevalence, epidemiology, and risk factors of HIV-1 drug resistance in newly diagnosed HIV-infected patients in Belgium. In January 2003 it was initiated as part of the pan-European SPREAD program, and continued thereafter for four inclusion rounds until December 2006. Epidemiological, clinical, and behavioral data were collected using a standardized questionnaire and genotypic resistance testing was done on a sample taken within 6 months of diagnosis. Two hundred and eighty-five patients were included. The overall prevalence of transmitted HIV-1 drug resistance in Belgium was 9.5% (27/285, 95% CI: 6.6-13.4). Being infected in Belgium, which largely coincided with harboring a subtype B virus, was found to be significantly associated with transmission of drug resistance. The relatively high rate of baseline resistance might jeopardize the success of first line treatment as more than 1 out of 10 (30/285, 10.5%) viruses did not score as fully susceptible to one of the recommended first-line regimens, i.e., zidovudine, lamivudine, and efavirenz. Our results support the implementation of genotypic resistance testing as a standard of care in all treatment-naive patients in Belgium.

HIV-1 gp120 N-linked glycosylation differs between plasma and leukocyte compartments.

BACKGROUND: N-linked glycosylation is a major mechanism for minimizing virus neutralizing antibody response and is present on the Human Immunodeficiency Virus (HIV) envelope glycoprotein. Although it is known that glycosylation changes can dramatically influence virus recognition by the host antibody, the actual contribution of compartmental differences in N-linked glycosylation patterns remains unclear. METHODOLOGY AND PRINCIPAL FINDINGS: We amplified the env gp120 C2-V5 region and analyzed 305 clones derived from plasma and other compartments from 15 HIV-1 patients. Bioinformatics and Bayesian network analyses were used to examine N-linked glycosylation differences between compartments. We found evidence for cellspecific single amino acid changes particular to monocytes, and significant variation was found in the total number of N-linked glycosylation sites between patients. Further, significant differences in the number of glycosylation sites were observed between plasma and cellular compartments. Bayesian network analyses showed an interdependency between N-linked glycosylation sites found in our study, which may have immense functional relevance. CONCLUSION: Our analyses have identified single cell/compartment-specific amino acid changes and differences in N-linked glycosylation patterns between plasma and diverse blood leukocytes. Bayesian network analyses showed associations inferring alternative glycosylation pathways. We believe that these studies will provide crucial insights into the host immune response and its ability in controlling HIV replication in vivo. These findings could also have relevance in shielding and evasion of HIV-1 from neutralizing antibodies.

Estimating the relative contribution of dNTP pool imbalance and APOBEC3G/3F editing to HIV evolution in vivo.

The human immunodeficiency virus (HIV) has a genome that is rich in adenine, and its rapid evolution shows an observed bias of guanine (G) to adenine (A) mutations. Two mechanisms have been proposed to explain these properties: (1) an imbalance in dNTP pool concentrations which drives the misincorporation process during reverse transcription, and (2) cytidine deamination by the APOBEC3G/3F restriction factor, causing G to A mutations most notably in specific dinucleotide contexts. Although crucial to understanding HIV evolution, current estimates on misincorporation bias during the replication cycle are based on scarce in vitro measurements. In this work, HIV partial pol sequences obtained for drug resistance testing purposes are analyzed using likelihood methods to estimate various models of HIV misincorporation bias in vivo. The technique is robust to selection on the amino acid sequence and selection against CpG dinucleotides. A model where misincorporations are explained only by an imbalance in dNTP pool concentrations, together with a preference for transitions versus transversions, explained 98% (95% confidence interval [C.I.] 93-100) of the observed variation in freely estimated misincorporation rates. Although dinucleotide context was responsible for variation in misincorporation probabilities, this variation was not specific for G to A mutations implying that the footprint of APOBEC3G/3F editing could not be detected. These results indicate that an imbalance in dNTP pool concentrations explains most of the bias in HIV nucleotide misincorporations, while the effect of editing by APOBEC3G/3F on HIV evolution, based on its dinucleotide specificity, could not be observed in this study.