Phylogenetic measures of indel rate variation among the HIV-1 group M subtypes

Please Mind the Gap: Indel-Aware Parsimony for Fast and Accurate Ancestral Sequence Reconstruction and Multiple Sequence Alignment Including Long Indels

Despite having important biological implications, insertion, and deletion (indel) events are often disregarded or mishandled during phylogenetic inference. In multiple sequence alignment, indels are represented as gaps and are estimated without considering the distinct evolutionary history of insertions and deletions. Consequently, indels are usually excluded from subsequent inference steps, such as ancestral sequence reconstruction and phylogenetic tree search. Here, we introduce indel-aware parsimony (indelMaP), a novel way to treat gaps under the parsimony criterion by considering insertions and deletions as separate evolutionary events and accounting for long indels. By identifying the precise location of an evolutionary event on the tree, we can separate overlapping indel events and use affine gap penalties for long indel modeling. Our indel-aware approach harnesses the phylogenetic signal from indels, including them into all inference stages. Validation and comparison to state-of-the-art inference tools on simulated data show that indelMaP is most suitable for densely sampled datasets with closely to moderately related sequences, where it can reach alignment quality comparable to probabilistic methods and accurately infer ancestral sequences, including indel patterns. Due to its remarkable speed, our method is well suited for epidemiological datasets, eliminating the need for downsampling and enabling the exploitation of the additional information provided by dense taxonomic sampling. Moreover, indelMaP offers new insights into the indel patterns of biologically significant sequences and advances our understanding of genetic variability by considering gaps as crucial evolutionary signals rather than mere artefacts.

Insertions and Deletions (Indels): A Missing Piece of the Protein Engineering Jigsaw

Over the years, protein engineers have studied nature and borrowed its tricks to accelerate protein evolution in the test tube. While there have been considerable advances, our ability to generate new proteins in the laboratory is seemingly limited. One explanation for these shortcomings may be that insertions and deletions (indels), which frequently arise in nature, are largely overlooked during protein engineering campaigns. The profound effect of indels on protein structures, by way of drastic backbone alterations, could be perceived as "saltation" events that bring about significant phenotypic changes in a single mutational step. Should we leverage these effects to accelerate protein engineering and gain access to unexplored regions of adaptive landscapes? In this Perspective, we describe the role played by indels in the functional diversification of proteins in nature and discuss their untapped potential for protein engineering, despite their often-destabilizing nature. We hope to spark a renewed interest in indels, emphasizing that their wider study and use may prove insightful and shape the future of protein engineering by unlocking unique functional changes that substitutions alone could never achieve.

New antiretroviral inhibitors and HIV-1 drug resistance: more focus on 90% HIV-1 isolates?

Combined HIV antiretroviral therapy (cART) has been effective except if drug resistance emerges. As cART has been rolled out in low-income countries, drug resistance has emerged at higher rates than observed in high income countries due to factors including initial use of these less tolerated cART regimens, intermittent disruptions in drug supply, and insufficient treatment monitoring. These socioeconomic factors impacting drug resistance are compounded by viral mechanistic differences by divergent HIV-1 non-B subtypes compared to HIV-1 subtype B that largely infects the high-income countries (just 10% of 37 million infected). This review compares the inhibition and resistance of diverse HIV-1 subtypes and strains to the various approved drugs as well as novel inhibitors in clinical trials. Initial sequence variations and differences in replicative fitness between HIV-1 subtypes pushes strains through different fitness landscapes to escape from drug selective pressure. The discussions here provide insight to patient care givers and policy makers on how best to use currently approved ART options and reduce the emergence of drug resistance in ∼33 million individuals infected with HIV-1 subtype A, C, D, G, and recombinants forms. Unfortunately, over 98% of the literature on cART resistance relates to HIV-1 subtype B.

Increased Frequency of Indels in Hypervariable Regions of SARS-CoV-2 Proteins—A Possible Signature of Adaptive Selection

Most attention in the surveillance of evolving SARS-CoV-2 genome has been centered on nucleotide substitutions in the spike glycoprotein. We show that, as the pandemic extends into its second year, the numbers and ratio of genomes with in-frame insertions and deletions (indels) increases significantly, especially among the variants of concern (VOCs). Monitoring of the SARS-CoV-2 genome evolution shows that co-occurrence (i.e., highly correlated presence) of indels, especially deletions on spike N-terminal domain and non-structural protein 6 (NSP6) is a shared feature in several VOCs such as Alpha, Beta, Delta, and Omicron. Indels distribution is correlated with spike mutations associated with immune escape and growth in the number of genomes with indels coincides with the increasing population resistance due to vaccination and previous infections. Indels occur most frequently in the spike, but also in other proteins, especially those involved in interactions with the host immune system. We also showed that indels concentrate in regions of individual SARS-CoV-2 proteins known as hypervariable regions (HVRs) that are mostly located in specific loop regions. Structural analysis suggests that indels remodel viral proteins’ surfaces at common epitopes and interaction interfaces, affecting the virus’ interactions with host proteins. We hypothesize that the increased frequency of indels, the non-random distribution of them and their independent co-occurrence in several VOCs is another mechanism of response to elevated global population immunity.

Large Evolutionary Rate Heterogeneity among and within HIV-1 Subtypes and CRFs

HIV-1 is a fast-evolving, genetically diverse virus presently classified into several groups and subtypes. The virus evolves rapidly because of an error-prone polymerase, high rates of recombination, and selection in response to the host immune system and clinical management of the infection. The rate of evolution is also influenced by the rate of virus spread in a population and nature of the outbreak, among other factors. HIV-1 evolution is thus driven by a range of complex genetic, social, and epidemiological factors that complicates disease management and prevention. Here, we quantify the evolutionary (substitution) rate heterogeneity among major HIV-1 subtypes and recombinants by analyzing the largest collection of HIV-1 genetic data spanning the widest possible geographical (100 countries) and temporal (1981–2019) spread. We show that HIV-1 substitution rates vary substantially, sometimes by several folds, both across the virus genome and between major subtypes and recombinants, but also within a subtype. Across subtypes, rates ranged 3.5-fold from 1.34 × 10⁻³ to 4.72 × 10⁻³ in env and 2.3-fold from 0.95 × 10⁻³ to 2.18 × 10⁻³ substitutions site⁻¹ year⁻¹ in pol. Within the subtype, 3-fold rate variation was observed in env in different human populations. It is possible that HIV-1 lineages in different parts of the world are operating under different selection pressures leading to substantial rate heterogeneity within and between subtypes. We further highlight how such rate heterogeneity can complicate HIV-1 phylodynamic studies, specifically, inferences on epidemiological linkage of transmission clusters based on genetic distance or phylogenetic data, and can mislead estimates about the timing of HIV-1 lineages.

Forecasting future HIV infection cases: evidence from Indonesia

Countries throughout the world, including Indonesia, are facing a complex problem with regards to HIV infection incidences and its prevalence. This is despite some local governments in some provinces of Indonesia working together with the Social Ministry of Indonesia to eradicate prostitution. There are high numbers of HIV sub-types in Indonesia such as HIV-1 (CRF01_AE and B). The forecast was conducted with the Autoregressive Integrated Moving Average model. The ARMA (1,1) was observed to be the best model for forecasting the number of HIV patients in Indonesia. This forecasting has been done since March 2019. Based on its dynamic forecasting with ARMA (1,1), this study proved the number of HIV-positive patients, from 2019 to 2030, had increased from 22,679 to 36,255, by almost 37% within 12 years. Indonesia is facing a growing trend in the number of new HIV cases, until 2030 which caused by stopped their follow-up treatments or they have ceased in consuming the Antiretroviral drugs even though the Indonesian government was provided national health insurance which covers the Antiretroviral drug and a limited number of health-care services providing the Antiretroviral therapy. Therefore, investigations focusing on estimate the number of HIV patients in Indonesia is an important finding. The information can be used as a resource for policy and decision making for plans and programs.

On the stability of sequences inserted into viral genomes

Viruses are widely used as vectors for heterologous gene expression in cultured cells or natural hosts, and therefore a large number of viruses with exogenous sequences inserted into their genomes have been engineered. Many of these engineered viruses are viable and express heterologous proteins at high levels, but the inserted sequences often prove to be unstable over time and are rapidly lost, limiting heterologous protein expression. Although virologists are aware that inserted sequences can be unstable, processes leading to insert instability are rarely considered from an evolutionary perspective. Here, we review experimental work on the stability of inserted sequences over a broad range of viruses, and we present some theoretical considerations concerning insert stability. Different virus genome organizations strongly impact insert stability, and factors such as the position of insertion can have a strong effect. In addition, we argue that insert stability not only depends on the characteristics of a particular genome, but that it will also depend on the host environment and the demography of a virus population. The interplay between all factors affecting stability is complex, which makes it challenging to develop a general model to predict the stability of genomic insertions. We highlight key questions and future directions, finding that insert stability is a surprisingly complex problem and that there is need for mechanism-based, predictive models. Combining theoretical models with experimental tests for stability under varying conditions can lead to improved engineering of viral modified genomes, which is a valuable tool for understanding genome evolution as well as for biotechnological applications, such as gene therapy.