Searching for virus phylotypes

Insights into SARS-CoV-2 in Angola during the COVID-19 peak: Molecular epidemiology and genome surveillance

Background

In Angola, COVID-19 cases have been reported in all provinces, resulting in >105,000 cases and >1900 deaths. However, no detailed genomic surveillance into the introduction and spread of the SARS-CoV-2 virus has been conducted in Angola. We aimed to investigate the emergence and epidemic progression during the peak of the COVID-19 pandemic in Angola.

Methods

We generated 1210 whole-genome SARS-CoV-2 sequences, contributing West African data to the global context, that were phylogenetically compared against global strains. Virus movement events were inferred using ancestral state reconstruction.

Results

The epidemic in Angola was marked by four distinct waves of infection, dominated by 12 virus lineages, including VOCs, VOIs, and the VUM C.16, which was unique to South-Western Africa and circulated for an extended period within the region. Virus exchanges occurred between Angola and its neighboring countries, and strong links with Brazil and Portugal reflected the historical and cultural ties shared between these countries. The first case likely originated from southern Africa.

Conclusion

A lack of a robust genome surveillance network and strong dependence on out-of-country sequencing limit real-time data generation to achieve timely disease outbreak responses, which remains of the utmost importance to mitigate future disease outbreaks in Angola.

Exploration of Computational Aids for Effective Drug Designing and Management of Viral Diseases: A Comprehensive Review

BACKGROUND

Microbial diseases, specifically originating from viruses are the major cause of human mortality all over the world. The current COVID-19 pandemic is a case in point, where the dynamics of the viral-human interactions are still not completely understood, making its treatment a case of trial and error. Scientists are struggling to devise a strategy to contain the pandemic for over a year and this brings to light the lack of understanding of how the virus grows and multiplies in the human body.

METHODS

This paper presents the perspective of the authors on the applicability of computational tools for deep learning and understanding of host-microbe interaction, disease progression and management, drug resistance and immune modulation through in silico methodologies which can aid in effective and selective drug development. The paper has summarized advances in the last five years. The studies published and indexed in leading databases have been included in the review.

RESULTS

Computational systems biology works on an interface of biology and mathematics and intends to unravel the complex mechanisms between the biological systems and the inter and intra species dynamics using computational tools, and high-throughput technologies developed on algorithms, networks and complex connections to simulate cellular biological processes.

CONCLUSION

Computational strategies and modelling integrate and prioritize microbial-host interactions and may predict the conditions in which the fine-tuning attenuates. These microbial-host interactions and working mechanisms are important from the aspect of effective drug designing and fine- tuning the therapeutic interventions.

EvoLaps: a web interface to visualize continuous phylogeographic reconstructions

BACKGROUND

Phylogeographic reconstructions serve as a basis to understand the spread and evolution of pathogens. Visualization of these reconstructions often lead to complex graphical representations which are difficult to interpret.

RESULT

We present EvoLaps, a user-friendly web interface to visualize phylogeographic reconstructions based on the analysis of latitude/longitude coordinates with various clustering levels. EvoLaps also produces transition diagrams that provide concise and easy to interpret summaries of phylogeographic reconstructions.

CONCLUSION

The main contribution of EvoLaps is to assemble known numerical and graphical methods/tools into a user-friendly interface dedicated to the visualization and edition of evolutionary scenarios based on continuous phylogeographic reconstructions. EvoLaps is freely usable at www.evolaps.org .

Kinship networks of seed exchange shape spatial patterns of plant virus diversity

By structuring farmers’ informal networks of seed exchange, kinship systems play a key role in the dynamics of crop genetic diversity in smallholder farming systems. However, because many crop diseases are propagated through infected germplasm, local seed systems can also facilitate the dissemination of seedborne pathogens. Here, we investigate how the interplay of kinship systems and local networks of germplasm exchange influences the metapopulation dynamics of viruses responsible for the cassava mosaic disease (CMD), a major threat to food security in Africa. Combining anthropological, genetic and plant epidemiological data, we analyzed the genetic structure of local populations of the African cassava mosaic virus (ACMV), one of the main causal agents of CMD. Results reveal contrasted patterns of viral diversity in patrilineal and matrilineal communities, consistent with local modes of seed exchange. Our results demonstrate that plant virus ecosystems have also a cultural component and that social factors that shape regional seed exchange networks influence the genetic structure of plant virus populations.

This study combines ethnobotanical and epidemiological data to understand how social networks of seed exchange influence the genetic structure of the African cassava mosaic virus in Gabon. Results reveal contrasted patterns of viral diversity in patrilineal and matrilineal communities, consistent with cultural differences in modes of seed exchange.

Origin, evolution and global spread of SARS-CoV-2

SARS-CoV-2 is the virus responsible for the global COVID19 pandemic. We review what is known about the origin of this virus, detected in China at the end of December 2019. The genome of this virus mainly evolves under the effect of point mutations. These are generally neutral and have no impact on virulence and severity, but some appear to influence infectivity, notably the D614G mutation of the Spike protein. To date (30/09/2020) no recombination of the virus has been documented in the human host, and very few insertions and deletions. The worldwide spread of the virus was the subject of controversies that we summarize, before proposing a new approach free from the limitations of previous methods. The results show a complex scenario with, for example, numerous introductions to the USA and returns of the virus from the USA to certain countries including France.

A Fast Likelihood Method to Reconstruct and Visualize Ancestral Scenarios

The reconstruction of ancestral scenarios is widely used to study the evolution of characters along phylogenetic trees. One commonly uses the marginal posterior probabilities of the character states, or the joint reconstruction of the most likely scenario. However, marginal reconstructions provide users with state probabilities, which are difficult to interpret and visualize, whereas joint reconstructions select a unique state for every tree node and thus do not reflect the uncertainty of inferences. We propose a simple and fast approach, which is in between these two extremes. We use decision-theory concepts (namely, the Brier score) to associate each node in the tree to a set of likely states. A unique state is predicted in tree regions with low uncertainty, whereas several states are predicted in uncertain regions, typically around the tree root. To visualize the results, we cluster the neighboring nodes associated with the same states and use graph visualization tools. The method is implemented in the PastML program and web server. The results on simulated data demonstrate the accuracy and robustness of the approach. PastML was applied to the phylogeography of Dengue serotype 2 (DENV2), and the evolution of drug resistances in a large HIV data set. These analyses took a few minutes and provided convincing results. PastML retrieved the main transmission routes of human DENV2 and showed the uncertainty of the human-sylvatic DENV2 geographic origin. With HIV, the results show that resistance mutations mostly emerge independently under treatment pressure, but resistance clusters are found, corresponding to transmissions among untreated patients.

PastView: a user-friendly interface to explore ancestral scenarios

BACKGROUND

Ancestral character states computed from the combination of phylogenetic trees with extrinsic traits are used to decipher evolutionary scenarios in various research fields such as phylogeography, epidemiology, and ecology. Despite the existence of powerful methods and software in ancestral character state inference, difficulties may arise when interpreting the outputs of such inferences. The growing complexity of data (trees, annotations), the diversity of optimization criteria for computing trees and ancestral character states, the combinatorial explosion of potential evolutionary scenarios if some ancestral characters states do not stand out clearly from others, requires the design of new methods to explore associations of phylogenetic trees with extrinsic traits, to ease the visualization and interpretation of evolutionary scenarios.

RESULT

We developed PastView, a user-friendly interface that includes numerical and graphical features to help users to import and/or compute ancestral character states from discrete variables and extract ancestral scenarios as sets of successive transitions of character states from the tree root to its leaves. PastView provides summarized views such as transition maps and integrates comparative tools to highlight agreements or discrepancies between methods of ancestral annotations inference.

CONCLUSION

The main contribution of PastView is to assemble known numerical and graphical methods into a multi-maps graphical user interface dedicated to the computing, searching and viewing of evolutionary scenarios based on phylogenetic trees and ancestral character states. PastView is available publicly as a standalone software on www.pastview.org .

The effect of interventions on the transmission and spread of HIV in South Africa: a phylodynamic analysis

The epidemic in South Africa is characterized by high genetic diversity driven by multiple independent introductions. The bulk of these introductions occurred between 1985-2000 during which time HIV prevalence increased exponentially. Epidemic growth has stabilized in recent years with the implementation of several interventions. Here we identified distinct HIV clades from a large sequence dataset of southern African HIV sequences (n = 15,332). Each clade was characterized using phylodynamic and phylogeographic methods to infer their growth through time and space. The estimated date of origin for the 18 clades that were found, fell between 1979-1992 with strong growth during the 1990's. Phylogeographic reconstruction revealed wide dispersal of clades throughout the country with the city of Johannesburg as the focal point of viral dispersal. We found clear signs of decreasing growth rate in four of the clades since the advent of interventions, while other clades have continued to growth and expand. Our results demonstrate that interventions do not affect the HIV epidemic universally with major difference between different clades over time and space. Here we demonstrate the utility and flexibility of molecular epidemiological methods and demonstrate how they can potentially be a powerful tool in HIV epidemic monitoring in South Africa.

Bioinformatics Applications in Advancing Animal Virus Research

Viruses serve as infectious agents for all living entities. There have been various research groups that focus on understanding the viruses in terms of their host-viral relationships, pathogenesis and immune evasion. However, with the current advances in the field of science, now the research field has widened up at the ‘omics’ level. Apparently, generation of viral sequence data has been increasing. There are numerous bioinformatics tools available that not only aid in analysing such sequence data but also aid in deducing useful information that can be exploited in developing preventive and therapeutic measures. This chapter elaborates on bioinformatics tools that are specifically designed for animal viruses as well as other generic tools that can be exploited to study animal viruses. The chapter further provides information on the tools that can be used to study viral epidemiology, phylogenetic analysis, structural modelling of proteins, epitope recognition and open reading frame (ORF) recognition and tools that enable to analyse host-viral interactions, gene prediction in the viral genome, etc. Various databases that organize information on animal and human viruses have also been described. The chapter will converse on overview of the current advances, online and downloadable tools and databases in the field of bioinformatics that will enable the researchers to study animal viruses at gene level.

Recent advances in computational phylodynamics

Time-stamped, trait-annotated phylogenetic trees built from virus genome data are increasingly used for outbreak investigation and monitoring ongoing epidemics. This routinely involves reconstructing the spatial and demographic processes from large data sets to help unveil the patterns and drivers of virus spread. Such phylodynamic inferences can however become quite time-consuming as the dimensions of the data increase, which has led to a myriad of approaches that aim to tackle this complexity. To elucidate the current state of the art in the field of phylodynamics, we discuss recent developments in Bayesian inference and accompanying software, highlight methods for improving computational efficiency and relevant visualisation tools. As an alternative to fully Bayesian approaches, we touch upon conditional software pipelines that compromise between statistical coherence and turn-around-time, and we highlight the available software packages. Finally, we outline future directions that may facilitate the large-scale tracking of epidemics in near real time.

Geographically-stratified HIV-1 group M pol subtype and circulating recombinant form sequences

Accurate classification of HIV-1 group M lineages, henceforth referred to as subtyping, is essential for understanding global HIV-1 molecular epidemiology. Because most HIV-1 sequencing is done for genotypic resistance testing pol gene, we sought to develop a set of geographically-stratified pol sequences that represent HIV-1 group M sequence diversity. Representative pol sequences differ from representative complete genome sequences because not all CRFs have pol recombination points and because complete genome sequences may not faithfully reflect HIV-1 pol diversity. We developed a software pipeline that compiled 6,034 one-per-person complete HIV-1 pol sequences annotated by country and year belonging to 11 pure subtypes and 70 CRFs and selected a set of sequences whose average distance to the remaining sequences is minimized for each subtype/CRF and country to generate a Geographically-Stratified set of 716 Pol Subtype/CRF (GSPS) reference sequences. We provide extensive data on pol diversity within each subtype/CRF and country combination. The GSPS reference set will also be useful for HIV-1 pol subtyping.

The Role of Phylogenetics as a Tool to Predict the Spread of Resistance

Drug resistance mutations emerge in genetic sequences of HIV through drug-selective pressure. Drug resistance can be transmitted. In this review we discuss phylogenetic methods used to study the emergence of drug resistance and the spread of resistant viruses.

Genome-Wide Association Study of HIV Whole Genome Sequences Validated using Drug Resistance

Background

Genome-wide association studies (GWAS) have considerably advanced our understanding of human traits and diseases. With the increasing availability of whole genome sequences (WGS) for pathogens, it is important to establish whether GWAS of viral genomes could reveal important biological insights. Here we perform the first proof of concept viral GWAS examining drug resistance (DR), a phenotype with well understood genetics.

Method

We performed a GWAS of DR in a sample of 343 HIV subtype C patients failing 1^st line antiretroviral treatment in rural KwaZulu-Natal, South Africa. The majority and minority variants within each sequence were called using PILON, and GWAS was performed within PLINK. HIV WGS from patients failing on different antiretroviral treatments were compared to sequences derived from individuals naïve to the respective treatment.

Results

GWAS methodology was validated by identifying five associations on a genetic level that led to amino acid changes known to cause DR. Further, we highlighted the ability of GWAS to identify epistatic effects, identifying two replicable variants within amino acid 68 of the reverse transcriptase protein previously described as potential fitness compensatory mutations. A possible additional DR variant within amino acid 91 of the matrix region of the Gag protein was associated with tenofovir failure, highlighting GWAS’s ability to identify variants outside classical candidate genes. Our results also suggest a polygenic component to DR.

Conclusions

These results validate the applicability of GWAS to HIV WGS data even in relative small samples, and emphasise how high throughput sequencing can provide novel and clinically relevant insights. Further they suggested that for viruses like HIV, population structure was only minor concern compared to that seen in bacteria or parasite GWAS. Given the small genome length and reduced burden for multiple testing, this makes HIV an ideal candidate for GWAS.

History and origin of the HIV-1 subtype C epidemic in South Africa and the greater southern African region

HIV has spread at an alarming rate in South Africa, making it the country with the highest number of HIV infections. Several studies have investigated the histories of HIV-1 subtype C epidemics but none have done so in the context of social and political transformation in southern Africa. There is a need to understand how these processes affects epidemics, as socio-political transformation is a common and on-going process in Africa. Here, we genotyped strains from the start of the epidemic and applied phylodynamic techniques to determine the history of the southern Africa and South African epidemic from longitudinal sampled data. The southern African epidemic's estimated dates of origin was placed around 1960 (95% HPD 1956-64), while dynamic reconstruction revealed strong growth during the 1970s and 80s. The South African epidemic has a similar origin, caused by multiple introductions from neighbouring countries, and grew exponentially during the 1980s and 90s, coinciding with socio-political changes in South Africa. These findings provide an indication as to when the epidemic started and how it has grown, while the inclusion of sequence data from the start of the epidemic provided better estimates. The epidemic have stabilized in recent years with the expansion of antiretroviral therapy.

A phylotype-based analysis highlights the role of drug-naive HIV-positive individuals in the transmission of antiretroviral resistance in the UK

OBJECTIVE

Antiretroviral-naive HIV-positive individuals contribute to the transmission of drug-resistant viruses, compromising first-line therapy. Using phylogenetic inference, we quantified the proportion of transmitted drug-resistance originating from a treatment-naive source.

METHODS

Using a novel phylotype-based approach, 24 550 HIV-1 subtype B partial pol gene sequences from the UK HIV Drug Resistance database were analysed. Ongoing transmission of drug resistance amongst HIV-positive individuals was identified as phylotypes of at least three sequences with at least one shared drug resistance mutation, a maximum intra-clade genetic distance of 4.0% and a basal branch support at least 90%. The time of persistence of the transmission chains was estimated using a fast least-squares molecular clock inference approach.

RESULTS

Around 70% of transmitted drug-resistance had a treatment-naive source. The most commonly transmitted mutations were L90M in the protease gene and K103N, T215D and T215S in reverse transcriptase. Reversion to wild type occurred at a low frequency and drug-independent reservoirs of resistance have persisted for up to 13 years.

CONCLUSION

These results illustrate the impact of viral fitness on the establishment of resistance reservoirs and support the notion that earlier diagnoses and treatment of HIV infections are warranted for counteracting the spread of antiretroviral resistance. Phylotype-based phylogenetic inference is an attractive approach for the routine surveillance of transmitted drug resistance in HIV as well as in other pathogens for which genotypic resistance data are available.

Evidence of long-lived founder virus in mother-to-child HIV transmission

Exposure of the infant’s gut to cell-associated and cell-free HIV-1 trafficking in breast milk (BM) remains a primary cause of mother-to-child transmission (MTCT). The mammary gland represents a unique environment for HIV-1 replication and host-virus interplay. We aimed to explore the origin of the virus transmitted during breastfeeding, and the link with quasi-species found in acellular and cellular fractions of breast-milk (BM) and in maternal plasma. The C2–V5 region of the env gene was amplified, cloned and sequenced from the RNA and DNA of BM, the RNA from the mother’s plasma (PLA) and the DNA from infant’s dried blood spot (DBS) in 11 post-natal mother-infant pairs. Sequences were assembled in Geneious, aligned in ClustalX, manually edited in SeAL and phylogenetic reconstruction was undertaken in PhyML and MrBayes. We estimated the timing of transmission (ETT) and reconstructed the time for the most recent common ancestor (TMRCA) of the infant in BEAST. Transmission of single quasi-species was observed in 9 of 11 cases. Phylogenetic analysis illustrated a BM transmission event by cell-free virus in 4 cases, and by cell-associated virus in 2 cases but could not be identified in the remaining 5 cases. Molecular clock estimates, of the infant ETT and TMRCA, corresponded well with the timing of transmission estimated by sequential infant DNA PCR in 10 of 11 children. The TMRCA of BM variants were estimated to emerge during gestation in 8 cases. We hypothesize that in the remaining cases, the breast was seeded with a long-lived lineage latently infecting resting T-cells. Our analysis illustrated the role of DNA and RNA virus in MTCT. We postulate that DNA archived viruses stem from latently infected quiescent T-cells within breast tissue and MTCT can be expected to continue, albeit at low levels, should interventions not effectively target these cells.

Unraveling the web of viroinformatics: computational tools and databases in virus research

The beginning of the second century of research in the field of virology (the first virus was discovered in 1898) was marked by its amalgamation with bioinformatics, resulting in the birth of a new domain--viroinformatics. The availability of more than 100 Web servers and databases embracing all or specific viruses (for example, dengue virus, influenza virus, hepatitis virus, human immunodeficiency virus [HIV], hemorrhagic fever virus [HFV], human papillomavirus [HPV], West Nile virus, etc.) as well as distinct applications (comparative/diversity analysis, viral recombination, small interfering RNA [siRNA]/short hairpin RNA [shRNA]/microRNA [miRNA] studies, RNA folding, protein-protein interaction, structural analysis, and phylotyping and genotyping) will definitely aid the development of effective drugs and vaccines. However, information about their access and utility is not available at any single source or on any single platform. Therefore, a compendium of various computational tools and resources dedicated specifically to virology is presented in this article.

Detection of transmission clusters of HIV-1 subtype C over a 21-year period in Cape Town, South Africa

Introduction

Despite recent breakthroughs in the fight against the HIV/AIDS epidemic within South Africa, the transmission of the virus continues at alarmingly high rates. It is possible, with the use of phylogenetic methods, to uncover transmission events of HIV amongst local communities in order to identify factors that may contribute to the sustained transmission of the virus. The aim of this study was to uncover transmission events of HIV amongst the infected population of Cape Town.

Methods and Results

We analysed gag p24 and RT-pol sequences which were generated from samples spanning over 21-years with advanced phylogenetic techniques. We identified two transmission clusters over a 21-year period amongst randomly sampled patients from Cape Town and the surrounding areas. We also estimated the origin of each of the identified transmission clusters with the oldest cluster dating back, on average, 30 years and the youngest dating back roughly 20 years.

Discussion and Conclusion

These transmission clusters represent the first identified transmission events among the heterosexual population in Cape Town. By increasing the number of randomly sampled specimens within a dataset over time, it is possible to start to uncover transmission events of HIV amongst local communities in generalized epidemics. This information can be used to produce targeted interventions to decrease transmission of HIV in Africa.

Phylogenetic studies of transmission dynamics in generalized HIV epidemics: an essential tool where the burden is greatest?

Efficient and effective HIV prevention measures for generalized epidemics in sub-Saharan Africa have not yet been validated at the population level. Design and impact evaluation of such measures requires fine-scale understanding of local HIV transmission dynamics. The novel tools of HIV phylogenetics and molecular epidemiology may elucidate these transmission dynamics. Such methods have been incorporated into studies of concentrated HIV epidemics to identify proximate and determinant traits associated with ongoing transmission. However, applying similar phylogenetic analyses to generalized epidemics, including the design and evaluation of prevention trials, presents additional challenges. Here we review the scope of these methods and present examples of their use in concentrated epidemics in the context of prevention. Next, we describe the current uses for phylogenetics in generalized epidemics and discuss their promise for elucidating transmission patterns and informing prevention trials. Finally, we review logistic and technical challenges inherent to large-scale molecular epidemiological studies of generalized epidemics and suggest potential solutions.

Changes in diversification patterns and signatures of selection during the evolution of murinae-associated hantaviruses

In the last 50 years, hantaviruses have significantly affected public health worldwide, but the exact extent of the distribution of hantavirus diseases, species and lineages and the risk of their emergence into new geographic areas are still poorly known. In particular, the determinants of molecular evolution of hantaviruses circulating in different geographical areas or different host species are poorly documented. Yet, this understanding is essential for the establishment of more accurate scenarios of hantavirus emergence under different climatic and environmental constraints. In this study, we focused on Murinae-associated hantaviruses (mainly Seoul Dobrava and Hantaan virus) using sequences available in GenBank and conducted several complementary phylogenetic inferences. We sought for signatures of selection and changes in patterns and rates of diversification in order to characterize hantaviruses’ molecular evolution at different geographical scales (global and local). We then investigated whether these events were localized in particular geographic areas. Our phylogenetic analyses supported the assumption that RNA virus molecular variations were under strong evolutionary constraints and revealed changes in patterns of diversification during the evolutionary history of hantaviruses. These analyses provide new knowledge on the molecular evolution of hantaviruses at different scales of time and space.

Automated analysis of phylogenetic clusters

BACKGROUND

As sequence data sets used for the investigation of pathogen transmission patterns increase in size, automated tools and standardized methods for cluster analysis have become necessary. We have developed an automated Cluster Picker which identifies monophyletic clades meeting user-input criteria for bootstrap support and maximum genetic distance within large phylogenetic trees. A second tool, the Cluster Matcher, automates the process of linking genetic data to epidemiological or clinical data, and matches clusters between runs of the Cluster Picker.

RESULTS

We explore the effect of different bootstrap and genetic distance thresholds on clusters identified in a data set of publicly available HIV sequences, and compare these results to those of a previously published tool for cluster identification. To demonstrate their utility, we then use the Cluster Picker and Cluster Matcher together to investigate how clusters in the data set changed over time. We find that clusters containing sequences from more than one UK location at the first time point (multiple origin) were significantly more likely to grow than those representing only a single location.

CONCLUSIONS

The Cluster Picker and Cluster Matcher can rapidly process phylogenetic trees containing tens of thousands of sequences. Together these tools will facilitate comparisons of pathogen transmission dynamics between studies and countries.

Is ecological speciation a major trend in aphids? Insights from a molecular phylogeny of the conifer-feeding genus Cinara

Introduction

In the past decade ecological speciation has been recognized as having an important role in the diversification of plant-feeding insects. Aphids are host-specialised phytophagous insects that mate on their host plants and, as such, they are prone to experience reproductive isolation linked with host plant association that could ultimately lead to species formation. The generality of such a scenario remains to be tested through macroevolutionary studies. To explore the prevalence of host-driven speciation in the diversification of the aphid genus Cinara and to investigate alternative modes of speciation, we reconstructed a phylogeny of this genus based on mitochondrial, nuclear and Buchnera aphidicola DNA sequence fragments and applied a DNA-based method of species delimitation. Using a recent software (PhyloType), we explored evolutionary transitions in host-plant genera, feeding sites and geographic distributions in the diversification of Cinara and investigated how transitions in these characters have accompanied speciation events.

Results

The diversification of Cinara has been constrained by host fidelity to conifer genera sometimes followed by sequential colonization onto different host species and by feeding-site specialisation. Nevertheless, our analyses suggest that, at the most, only half of the speciation events were accompanied by ecological niche shifts. The contribution of geographical isolation in the speciation process is clearly apparent in the occurrence of species from two continents in the same clades in relatively terminal positions in our phylogeny. Furthermore, in agreement with predictions from scenarios in which geographic isolation accounts for speciation events, geographic overlap between species increased significantly with time elapsed since their separation.

Conclusions

The history of Cinara offers a different perspective on the mode of speciation of aphids than that provided by classic models such as the pea aphid. In this genus of aphids, the role of climate and landscape history has probably been as important as host-plant specialisation in having shaped present-day diversity.