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.

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 (R) 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.

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.

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.

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.

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.

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.

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.

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.

Automated subtyping of HIV-1 genetic sequences for clinical and surveillance purposes: performance evaluation of the new REGA version 3 and seven other tools.

Background: To investigate differences in pathogenesis, diagnosis and resistance pathways between HIV-1 subtypes, an accurate subtyping tool for large datasets is needed. We aimed to evaluate the performance of automated subtyping tools to classify the different subtypes and circulating recombinant forms using pol, the most sequenced region in clinical practice. We also present the upgraded version 3 of the Rega HIV subtyping tool (REGAv3).

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.

HIV-1 fitness landscape models for indinavir treatment pressure using observed evolution in longitudinal sequence data are predictive for treatment failure.

We previously modeled the in vivo evolution of human immunodeficiency virus-1 (HIV-1) under drug selective pressure from cross-sectional viral sequences. These fitness landscapes (FLs) were made by using first a Bayesian network (BN) to map epistatic substitutions, followed by scaling the fitness landscape based on an HIV evolution simulator trying to evolve the sequences from treatment naïve patients into sequences from patients failing treatment. In this study, we compared four FLs trained with different sequence populations.

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.

A public HTLV-1 molecular epidemiology database for sequence management and data mining.

Background: It is estimated that 15 to 20 million people are infected with the human T-cell lymphotropic virus type 1 (HTLV-1). At present, there are more than 2,000 unique HTLV-1 isolate sequences published. A central database to aggregate sequence information from a range of epidemiological aspects including HTLV-1 infections, pathogenesis, origins, and evolutionary dynamics would be useful to scientists and physicians worldwide.

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.

An automated genotyping tool for enteroviruses and noroviruses.

Background: Molecular techniques are established as routine in virological laboratories and virus typing through (partial) sequence analysis is increasingly common. Quality assurance for the use of typing data requires harmonization of genotype nomenclature, and agreement on target genes, depending on the level of resolution required, and robustness of methods.

Objective: To develop and validate web-based open-access typing-tools for enteroviruses and noroviruses.

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.

Resistance pathways of human immunodeficiency virus type 1 against the combination of zidovudine and lamivudine.

A better understanding of human immunodeficiency virus type 1 drug-resistance evolution under the selective pressure of combination treatment is important for the design of long-term effective treatment strategies. We applied Bayesian network learning to sequences from patients treated with the reverse transcriptase inhibitor combination of zidovudine (AZT) and lamivudine (3TC) to identify the role of many treatment-selected mutations in the development of resistance. Based on the Bayesian network structure, an in vivo fitness landscape was built, reflecting the necessary selective pressure under treatment, to evolve naive sequences to sequences obtained from patients treated with the combination.

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.

The rise and fall of K65R in a Portuguese HIV-1 Drug Resistance database, despite continuously increasing use of tenofovir.

Objective: The overall prevalence of the K65R mutation in HIV-1 reverse transcriptase has increased in treatment-experienced patients, mostly attributed to the increasing use of tenofovir (TDF). A number of TDF-based regimens are associated with high rate of early virological failure. In this study, we evaluated the impact of these combinations on K65R selection over time.

Bayesian network analyses of resistance pathways against efavirenz and nevirapine.

Objective: To clarify the role of novel mutations selected by treatment with efavirenz or nevirapine, and investigate the influence of HIV-1 subtype on nonnucleoside reverse transcriptase inhibitor (nNRTI) resistance pathways.

Design: By finding direct dependencies between treatment-selected mutations, the involvement of these mutations as minor or major resistance mutations against efavirenz, nevirapine, or coadministrated nucleoside analogue reverse transcriptase inhibitors (NRTIs) is hypothesized. In addition, direct dependencies were investigated between treatment-selected mutations and polymorphisms, some of which are linked with subtype, and between NRTI and nNRTI resistance pathways.

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.

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).