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Bats are the natural reservoir of Coronaviruses (CoVs). Human CoVs cause mild respiratory diseases worldwide, but, in the last decade, two Beta-CoVs [Middle East respiratory syndrome (MERS)-CoV and severe acute respiratory syndrome] caused thousands of deaths and cases worldwide. Phylogenetic analysis suggested the evolutionary origin of mammalian CoVs is derived from bats. In this study, we characterized three Alpha-CoVs and two Beta-CoVs demonstrating the circulation of bat strains in Italy. Isolates were sequenced using a next-generation sequencing approach and genomes reconstructed using the online tool Galaxy Aries. Phylogenetic analyses were conducted using MEGA7 and MrBayes. Similarity plots were generated using SSE v1.2. The structure of the receptor binding domain (RBD) in the S protein was predicted by sequence-homology method using the protein data bank. Bioinformatics analysis permitted the identification of 2 Beta-CoV complete genomes of 30 kb and three Alpha-CoV of 28 kb (named BatCoV-ITA1-5). BatCoV-ITA1 and 2 formed a monophyletic group with MERS-CoV sequences. The comparison of the concatenated domains within ORF1ab confirmed their classification into the MERS-CoV species. The 3D structure of RBD of Italian strains showed two amino acid deletions located in a region corresponding to the external subdomain of MERS-RBD. BatCoV-Ita3 and BatCoV-Ita4/5 were classified into two novel Alpha-CoV species by comparison of concatenated domains within ORF1ab. Due to the high divergence with the Alpha human spike protein strains, it was impossible to establish the protein structure and the potential affinity to human receptor. The Italian strains showed the typical organization of Alpha and Beta-CoVs. We reported two Beta-CoVs closely related to MERS-CoVs from bats belonging to common Italian species (Pipistrellus kuhlii and Hypsugo savii). The analysis of the RBD in the spike protein indicates significant differences from human RBD known to date. The three Alpha-CoV strains were classified into two novel species, confirming the high heterogeneity of CoV strains in bats. Although the studies conducted cannot confirm a risk for humans, surveillance studies are needed to investigate the genetic diversity of CoVs in bats. Because this exceeds what is known for other hosts, it is compatible with bats being the major reservoir of mammalian CoVs.

Next-generation sequencing (NGS) is a technique that can capture the variability of viral populations in transmission studies. The conventional sample preparation for NGS, based on amplicons, is a potential source of errors, derived from the variable affinity of specific primers for different viral variants and from irregular DNA polymerase efficiency. In this context, we propose a more reliable method for viral whole genome sample preparation, starting from nucleic acids obtained and stored with conventional procedures. Our goal was to obtain complete hepatitis C virus (HCV) genome sequences to subsequently perform extensive phylogenetic analyses. Additionally, we aimed to test the effectiveness of nuclease treatment used to remove contaminating host DNA. Nucleic acids were obtained from almost cell-free blood plasma of HCV-infected patients. As a source for Illumina library preparation, double-stranded cDNA was generated using random primers. The HCV genome was not amplified before library preparation, avoiding possible biases derived from unequal copying. To get rid of possible host contaminants in the samples, a DNase treatment step was added. Libraries were paired-end sequenced on the Illumina platform using MiSeq reagent kit v3. After conservative filtering of contaminant human reads by alignment with the human reference genome using Burrows-Wheeler Aligner (BWA), the remaining reads were mapped to the HCV reference genome using BWA. Primary maximum likelihood phylogenetic analyses were performed using ClustalW and IQTREE to infer the phylogenetic relationships of the sequenced samples in the context of complete genome sequences of the same genotype. NGS sample preparation method of HCV from blood plasma was established. Complete genome sequences of HCV could be obtained with variable coverage depending on the viral load of plasma samples. No significant reduction of host DNA proportion in DNase treated samples in comparison to the controls was observed. The new sequences clustered within the Los Alamos National Laboratory database-deposited HCV subtype 4d samples. The method can be used to obtain full-length sequences of HCV from nucleic acid samples not previously planned for NGS. No improvement was observed when DNase pre-treatment of nucleic acids extracted from blood plasma was performed.

Chikungunya virus (CHIKV) is a re-emerging, mosquito-borne alphavirus that causes chikungunya fever, a febrile illness characterized by severe acute and persistent arthralgia. At the end of 2013, autochthonous CHIKV transmission was detected for the first time in the Americas, on the Caribbean island of Saint Martin. Subsequently, CHIKV rapidly spread through the Caribbean Islands and onto the American mainland, causing millions of cases of chikungunya fever. During the outbreak, the Dutch National Institute of Health performed diagnostics on patient samples originating from the six Caribbean islands that belong to the Kingdom of the Netherlands. Using a subset of PCR-positive patient samples, we aimed to retrospectively analyze the 2013–5 CHIKV outbreak on the Dutch Caribbean islands using whole-genome sequences. Twenty-five CHIKV-positive sera were selected for next-generation sequencing based on viral load, location, and date of sampling. Sera were subjected to high speed centrifugation, filtration, and nuclease treatment to reduce the amount of background sequences from human and bacterial origin. Total RNA was extracted, primed with random nanomers for reverse transcription, after which dsDNA was produced and purified. Libraries were created using Nextera XT library preparation kit, and samples were run on a MiSeq desktop sequencer. Reads were trimmed and mapped to a reference sequence using the CLC Genomics workbench. To date, eight full-genome sequences were obtained, originating from four different islands and dating from the start of the outbreak (December 2013) to April 2015, when the outbreak was waning. High similarity (>99%) between sequences was found; nevertheless, all genome sequences were unique with a minimum of three SNPs differentiating one sequence from another. Thirty-three unique single nucleotide polymorphisms (SNPs) were identified, of which 29 were located in the coding regions of the genome. Eight SNPs were informative, and ten SNPs led to amino acid changes. Of the amino acid changes, nine were located in the non-structural proteins (1× nsP1, 5× nsP2, and 3× nsP3), and one was located in E2. In conclusion, we report the first whole-genome sequences of CHIKV isolates from the 2013 to 2015 outbreak that originated from the Dutch Caribbean islands. Sequencing of the remaining samples is still in progress.

Large-genome Nidoviruses and Nidovirus-like viruses reside at the current boundary of largest RNA genome sizes. They code for an unusually large number of gene products matching that of small DNA viruses (e.g. DNA bacteriophages). The order of appearance and distribution of enzyme genes along various virus families (e.g. helicase and ExoN) may be seen as an evolutionary marker in these large RNA genomes lying at the genome size boundary. A positive correlation exists between (+)RNA virus genome sizes and the presence of the RNA helicase and the ExoN domains. Although the mechanistic basis of the presence of the helicase is still unclear, the role of the ExoN activity has been linked to the existence of an RNA synthesis proofreading system. In large Nidovirales, ExoN is bound to a processive replicative RNA-dependent RNA polymerase (RdRp) and corrects mismatched bases during viral RNA synthesis. Over the last decade, a view of the overall process has been refined in Coronaviruses, and in particular in our lab (Ferron et al., PNAS, 2018). We have identified genetic markers of large RNA genomes that we wish to use to data-mine currently existing metagenomic datasets. We have also initiated a collaboration to sequence and explore new viromes that will be searched according to these criteria. Likewise, we have a collection of purified viral RdRps that are currently being used to generate RNA synthesis products that will be compared to existing NGS datasets of cognate viruses. We will be able to have an idea about how much genetic diversity is possibly achievable by viral RdRp (‘tunable fidelity’) versus the detectable diversity (i.e. after selection in the infected cell) that is actually produced.

The MOBIDIP trial evaluated the simplification by protease (PI/r) monotherapy for HIV infection versus dual therapy and boosted protease inhibitor plus lamivudine (PI/r + 3TC) in controlled patients under second-line regimens. MOBIDIP was interrupted because of a significant number of patients with virological failure (VF) at week 48 (W48) in PI/r (33/133, ∼25%) versus in PI/r + 3TC (4/132, ∼3%). At the time of first-line VF, 96 per cent of patients harbored the M184V mutation. The presence of the M184V mutation was related to a protective effect against VF in the PI/r + 3TC arm. We developed a methodology that allows to determine the frequency of M184V/I mutations in the HIV reverse transcriptase (RT) gene in peripheral blood mononuclear cells (PBMC) obtained before MOBIDIP simplification. Paired-end sequences were obtained from 252 PBMC samples covering the first 855 bp of the RT gene (HXB2: 2485–3405) by MiSeq technology. These sequences were subjected to an in-house Bioinformatics pipeline. The results of our pipeline were compared to the output of PASeq (https://www.paseq.org), an open web-tool for the identification of drug resistance mutations. The M184V mutation was identified at a frequency greater than 1 per cent in 178 individuals (∼71%). The M184I mutation was observed in 34 patients (∼13%), always in the presence of stop codons, and is in agreement with expectations, as this mutation is a known APOBEC-targeted site. Sixty-seven patients (∼27%) had a frequency of the M184V mutation with values greater than 75 per cent. PASeq confirmed the presence of M184V mutation in 173 patients. The frequencies estimated by the PASeq tool and in-house pipeline were correlated up to 99.5 per cent. We found a significant loss of the M184V mutation archived in PBMC between the first-line regimen treatment failure and the beginning of the MOBIDIP trial. In patients under long-term antiretroviral therapy, as in our case, viral sub-populations could be lost, reducing the presence, and frequency of a mutation. In the next step, we will evaluate the association between the presence and frequency of M184V mutation and MOBIDIP results.

HIV-2 is a retrovirus that mainly infects West Africans. In Europe, HIV-2 has been circulating since the 1980s, and more recent immigration has contributed to its spread. Excluding HIV-2 in all HIV seropositive individuals precludes misinterpretation of viral loads (VL) and antiretroviral (ART) choices. Surveillance registers enables tracking of epidemic spread and identification of major contributors, allowing the establishment of convenient preventive measures. The HIV-2 Spanish study group was founded in 1989. Since then, blood specimens from HIV-2 carriers have been collected. More than 40 Spanish hospitals are part of the group and provide clinical and epidemiological data. Records for each HIV-2 patient include country of origin, gender, age, transmission category, monitoring of HIV-2 VL, CD4 counts, drug resistance, and HIV-2 subtype. Up to December 2017, 354 HIV-2+ individuals were identified in Spain and incidence (15–20/year) has been stable within the last decade. At diagnosis, mean age was 44.6 years and 63 per cent were male. The majority were Africans (78%), whereas 16.5 per cent were native Spaniards. 78.2 per cent acquired HIV-2 by heterosexual contact. HIV-2 subtyping using the HIV2EU tool was performed in 126 subjects: 86 Africans and 27 native Spaniards. The subtype distribution was as follows: 108 (85.7%) HIV-2 subtype A and 18 (14.3%) B. Africans and Spaniards were mostly infected with subtype A (87.2% and 77.8%, respectively). HIV-2 subtype B was found in six native Spaniards (22.2%; 6/27), five patients from Equatorial Guinea (71.4%; 5/7), four from Senegal (18.1%; 4/22), two from Ivory Coast (100%; 2/2), and one from Burkina Faso (50%; 1/2). Using phylogenetic analyses, two clusters were identified among homosexual Spanish men (subtype A: 8 men and subtype B: 2 men with viral isolates related to Malian and Senegalese isolates). Before starting ART, CD4 count mean values for subtype A and B were 378 and 357, respectively. Corresponding VL values were 2.63 and 2.32 HIV-2 RNA log copies/ml, respectively.

Phylogenetic studies have contributed to our understanding of the early epidemic onset of HIV-1 in the Democratic Republic of Congo (DRC); however, the factors driving its early emergence and establishment in human populations still remain unresolved. In order to determine the key aspects of its successful epidemic spread, complete genome data are required from samples representative of the viral diversity in the DRC. In this study, we have established a universal PCR-assay that uses seven different panels of primers to produce overlapping amplicons covering the complete HIV genome. To circumvent the limitations of purifying these fragments and sequencing them with traditional approaches, we have developed a massive parallel sequencing method and a protocol for efficiently assembling HIV-1 genomes. A total of thirty-six samples, collected between 1997 and 2001 from different locations across the DRC, have been obtained, and, at this stage, we are focusing on complementing our dataset with more archival samples that can be used as HIV ‘molecular fossils’. By generating complete genome phylogeographic data from the DRC, we aim to create a genomic window into the past evolutionary and epidemiological dynamics of HIV-1 in Central Africa and understand the natural history of this devastating pandemic.

Antiretroviral treatment (ART) has provided substantial benefits for HIV-1-infected patients and has reduced incidence in areas with high uptake since its introduction in the late 1980s. As ART has led to shifts in the worldwide epidemiology of HIV-1, it may also have the potential to cause concomitant selective pressure on the virus population. Evidence for changes in HIV-1 virulence since the introduction of ART appears to be inconsistent. As well as reviewing both empirical and theoretical studies on the likely impact of ART on HIV-1 virulence, we developed a mathematical framework to evaluate the likely impact of ART on virulence selection under the widespread treatment programs and the future impact of recent test-and-treat recommendations. By quantifying both the relationship between virulence changes with the transmissibility through disease progression and the speed of diagnosis and treatment, we reconcile observational studies on virulence changes with the mathematical model predictions. On adoption of new test-and-treat programs—synonymous with early detection and immediate treatment—it is likely that increased virulence will be observed. Our findings highlight the potential public health consequences of mass treatment and the ensuing requirement for greater access and adherence to nullify the public health effect of these virulence changes.

Coronaviruses (CoVs) are enveloped, single stranded, positive-sense RNA viruses with a large genomic size of 26–32 kilobases. The first human CoV identified in the 1960s was isolated from patients presenting with common cold symptoms. Subsequent epidemic outbreaks of novel zoonotic CoV transmission were reported, examples including HCoV-229E (229E), HCoV-OC43 (OC43), severe acute respiratory syndrome, and Middle East respiratory syndrome (MERS). The ongoing outbreak of MERS in the Middle East is originating from a zoonotic source of dromedary camels. Surveillance later revealed that three CoV species—HCoV-229E (229E), camel-HKU23, and MERS-CoV—were co-circulating in Saudi Arabia dromedary camels. Camel-HKU23 belongs to Group 2a CoV, which also includes human coronavirus OC43, bovine coronavirus, and porcine hemagglutinating encephalomyelitis virus. Recombination, resulting in the generation of different novel genotypes, has been reported previously among these CoVs. Our surveillance of dromedary camels slaughtered in a major abattoir in Nigeria identified camel-HKU23 from nasal swab samples with a prevalence of 2.2 per cent. Phylogenetic analysis showed Nigeria camel-HKU23 is distinct from those previously identified in Saudi Arabia, while still genetically similar, as they share a monophyletic origin. Recombination analysis of Nigeria camel-HKU23 revealed two recombination breakpoints at positions of 22774–24100 base pairs (bp) and 28224–29362 bp. Recombination breakpoint at position 22774, encoding the Group 2a CoV-specific hemagglutinin esterase gene, exhibited high bootstrap support for clustering with RbCoV HKU14, which was previously detected in domestic rabbits in China. The recombination signal is only observed in Nigeria camel-HKU23, suggesting a regional varied evolutionary history of camel-HKU23. Our findings extended the knowledge of the evolutionary relationship among Group 2a CoVs. Further surveillance in other African camels will be important to elucidate the evolution of camel-HKU23.

Foot-and-mouth disease (FMD) is a highly contagious disease of livestock affecting animal production and trade throughout Asia and Africa. Understanding FMD virus (FMDV) global movements and evolution can help to reconstruct the disease spread between endemic regions and predict the risks of incursion into FMD-free countries. Global expansion of a single FMDV lineage is rare but can result in severe economic consequences. Using extensive sequence data, we have reconstructed the global space-time transmission history of the O/ME-SA/Ind-2001 lineage (which normally circulates in the Indian sub-continent) providing evidence of at least fifteen independent escapes during 2013–7 that have led to outbreaks in North Africa, the Middle East, Southeast Asia, and the Far East and the FMD-free islands of Mauritius. We demonstrated that sequence heterogeneity of this emerging FMDV lineage is accommodated within two co-evolving divergent sublineages, and that recombination by exchange of capsid-coding sequences can impact upon the reconstructed evolutionary histories. Thus, we recommend that only sequences encoding the outer capsid proteins should be used for broad-scale phylogeographical reconstruction. These data emphasize the importance of the Indian subcontinent as a source of FMDV that can spread across large distances and illustrates the impact of FMDV genome recombination on FMDV molecular epidemiology.

Next-generation sequencing technologies provide unique possibilities for the comprehensive assessment of the environmental diversity of bacteriophages. Many Bacillus bacteriophages have been isolated, but very few Bacillus megaterium bacteriophages have been characterized. Here, we describe biological characteristics and whole-genome sequences and their annotations for two new isolates of the B. megaterium bacteriophages (BM5 and BM10), isolated from Egyptian soil samples and representing two different groups according to their host range and amplified fragment length polymorphism profiles. Both phages have been displaying different thermal inactivation points (82 and 78 °C) and pH tolerance range (5–9.2 and 5–8.4 pH) while having the same longevity in vitro (192 h). Electron microscopy observation has proved that both phages belonged to the Myoviridiae family. Furthermore, growth analyses indicated that phages BM5 and BM10 have a shorter latent period (20 and 25 min) and smaller burst size (103 and 117 PFU) than is typical for Bacillus phages. The genome sizes of phages BM5 and BM10 were 165,031 bp and 165,213 bp, respectively, with a modular organization. Bioinformatic analyses of BM5 and BM10 genomes enabled assignments of putative functions to 97 and 65 putative ORFs, respectively. Comparative analysis of BM5 and BM10 genome structures with other B. megaterium bacteriophages revealed relatively high levels of sequence and organizational identity. Both genomic comparisons and phylogenetic analyses support the conclusion that the sequenced phages (BM5 and BM10) belong to different sub-clusters (L5 and L7) within L cluster and display different lifestyles (lysogenic and lytic). Sequenced phages encode proteins associated with Bacillus pathogenesis. BM5 does not contain any tRNA sequences, while BM10 genome codes for 17 tRNAs.

In winter 2016–7 the highly pathogenic avian influenza (HPAI) virus, H5N8 subtype, clade 2.3.4.4 group B, circulated extensively both in wild and domestic birds in Europe. Northern Italy was hit by three epidemic waves: the first in January–May 2017, the second in July–December 2017, and the latest in March 2018. To genetically characterize the viruses circulating in Italy we used the Illumina MiSeq platform to sequence the complete genome of representative viruses from each infected farm, for a total of 86 cases in poultry and 17 in wild birds. Maximum likelihood phylogenetic analyses performed using PhyML version 3.1 identified multiple viral introductions of distinct genotypes of HPAI H5N8 viruses in Italy at the beginning of the epidemic (January–February 2017). During the second epidemic wave a single genetic group originating from the virus A/wild duck/Poland/82A/2016 seemed to have been selected, further evolving into two different clusters, namely Italy-A and Italy-B. We identified four clusters of secondary outbreaks, the largest being the epidemic in the province of Brescia between October 2017 and March 2018, which had affected 26 farms. Evolutionary and phylogeographic analyses performed with the BEAST v1.8.4 package (applying a Bayesian Markov chain Monte Carlo approach, using a constant size coalescent tree prior and a SRD06 model of nucleotide substitution) indicated that different viral introductions had probably occurred through migratory birds from West Russia, Siberia, Central and East Europe. The discrete and continuous phylogeographic analyses showed that group Italy-A had probably emerged between February and April 2017 in the province of Mantua and had then spread eastwards, circulating in the Veneto region and eastern Lombardy; on the contrary, Italy-B had arisen between March and July 2017 in the central part of Lombardy and had spread westwards, circulating in the western part of Lombardy, Emilia Romagna, and Piedmont regions. This study was instrumental to reconstruct the virus dissemination routes and indicated that wild and domestic birds from Lombardy most likely represented the key source for the re-emergence and spread of the HPAI virus during the second and the third epidemic waves. This key spatial information will help to define appropriate disease control strategies.

Until now, three genotypes of Zika virus (ZIKV) have been detected (two African lineages and one Asian lineage). After the declaration of Public Health Emergency of International Concern issued by The Pan American Health Organization and the World Health Organization authors from some Latin American countries have identified the Asian genotype as the lineage responsible for the Zika epidemic in the western hemisphere. However, data from the Caribbean are sparse, and there is no published data regarding the genotypes that produced isolated outbreaks in Cuba. Aiming to realize the molecular characterization of ZIKV in Cuba, we will sequence by next-generation sequencing the full genome of the ZIKV identified in samples from Cuban patients of different provinces in which ZIKV produced outbreaks. All samples required for this study have been collected during the molecular surveillance of Arboviral diseases conducted at the National Reference Laboratory at Pedro Kourí Tropical Medicine Institute. Viral RNA will be purified from urine and serum samples collected from patients with confirmed ZIKV infection by real time PCR. Using evolutionary dynamics studies, we will map the spread of a virus or of particular variants in time and space in order to understand how frequently ZIKV has been introduced into Cuba. Moreover, we will evaluate the amino acid diversity of each ZIKV proteins. Further, we will evaluate the population dynamics of ZIKV in samples from patients with varying clinical outcomes. The results will allow us to characterize the ZIKV genome and its evolution into the Cuban population that would also have impact for vaccine development, diagnosis, and pathogenesis studies.

Zika virus (ZIKV) has caused an unprecedented epidemic linked to severe congenital syndromes. Transmission of ZIKV in the Americas was first confirmed in May 2015 in northeast Brazil, though the virus was likely introduced 1–2 years prior to its detection. Manaus, the capital city of the Amazonas State, the largest territory of any state in Brazil and the main economic center in the northern region, reported between 2016 and 2017 more than 2,327 suspected cases of ZIKV infection. To gain insights into the timing, source, and likely route(s) of ZIKV introduction in the Amazonas State, we tracked the virus by sequencing ZIKV genomes from infected patients. Using nanopore sequencing technology, we generated 56 Brazilian ZIKV genomes from Manaus city in the Amazonas state, sampled from human cases. On the basis of available sequences of isolates from the Americas, the Manaus sequences, we analyzed fell within a single strongly supported monophyletic clade (bootstrap support = 99%, posterior support = 1.00) that belongs to the Asian genotype. Genetic analysis suggests the outbreak most likely originated from transmission cycles not previously identified in North Brazil and not from a separate introduction into the Americas. Molecular dating analysis indicates that the outbreak was caused by a single founder strain that is estimated to have arrived in Manaus around February 2015. By analyzing surveillance and genetic data, we discovered that ZIKV moved among transmission zones in Manaus. Geographical analysis further indicates that the Northern part of the Manaus regions has a high transmission potential for ZIKV. Our work illustrates that near-real time genomics in the field can augment traditional approaches to infectious disease surveillance and control. Estimated dates for the international spread of ZIKV from the north region indicate the persistence of the virus transmission in recipient regions. Our study provides an understanding of how ZIKV initiates transmission in new regions.

The V3 loop of the HIV-1 envelope (env) gene is involved in binding to the chemokine receptors CCR5 and CXCR4, thus determining viral tropism. With the aim of genetically characterizing the C2V3 env region of HIV-1 samples from Cuban patients, naive to Maraviroc (MVC) therapy, 115 plasma samples were taken in the period of 2014–6 and analyzed by sequencing of the C2V3 region. HIV-1 subtyping was performed using COMET V.2 and Rega subtyping toolV.3 software. Subtypes were confirmed by phylogenetic analyses using Mega-6. Prediction of co-receptor tropism was performed using the geno2pheno algorithm. The viral mutations associated to MVC resistance were analyzed, as well as the association of the subtype with clinical, epidemiological, virological, and immunological variables. The subtypes detected using the C2V3 region were CRF20, 23, 24_BG (35 patients, 30.4%); Subtype B (33 patients, 28.7%); CRF19_cpx (30 patients, 26.1%); CRF18_cpx (10 patients, 8.7%); and others (7 patients, 6.1%). Overall, 60 per cent of the viruses exhibited R5 phenotype, 14.8 per cent were R5X4 and 25.2 per cent were X4. Interestingly, CRF19_cpx virus was associated with having phenotype X4 [46.7%, P = 0.0047, odds ratio (OR): 3.96, 95% confidence interval (95% CI): 1.59–9.84], with infection in young individuals (39.1%, P = 0.025, OR: 3,548; 95% CI: 1,136–11,077) and with higher values of viral load (P ≤ 0.05). The comparison of the amino acid sequences of the V3 loop showed differences between the B and non-B subtypes (P = 0.0001). Mutations reported to be associated with MVC resistance, were detected in 75.7 per cent of the samples, in positions 11 (6.1%), 13 (49.6%), 25 (6.1%), 316 (7.0%), 323 (11.3%), and 319 (3.5%) of Gp120, particularly in the recombinant forms CRF19_cpx and CRF_BGs. HIV variants that use the CXCR4 co-receptor were associated with more than 10 years of diagnosis, with older individuals, in the AIDS stage, with low CD4 counts and higher viral load levels (P

The availability of evolutionary rate estimates in recent years led to the observation that they may depend on the time-scale on which they are measured. Specifically, RNA virus evolutionary rates are frequently estimated to be low towards the past and high towards the present. This time-dependent rate phenomenon (TDRP) has important implications for evolutionary studies as it could severely bias divergence time estimates. While recent studies are providing insights into the relationship between viral evolutionary rate and time, formal probabilistic models to draw inference under TDRP scenarios remain lacking. Here, we adopt epoch-modelling to develop a Bayesian model of discrete rate changes through time in an unknown evolutionary history and combine this with a log-linear parameterization of rates as a function of times in the past. We provide an implementation for nucleotide substitution rates as well as for nonsynonymous rates change in a codon substitution model. Using a foamy virus dataset for which internal node calibrations can be applied based on host-virus co-divergence, we estimate a significant decline in evolutionary rates as a function of time into the past for nucleotide substitutions as well as for non-synonymous substitutions in a codon model. We also estimate a deep evolutionary history for primate Lentiviruses by combining an HIV-1 group M node calibration and a biogeographic calibration for viruses in drill monkeys in the TDRP model. Our analyses lead to the conclusion that studies of evolutionary timescales require a reconsideration of substitution rates, in either codon and nucleotide substitution model, as a dynamic feature of molecular evolution.

Bloodstream infection (BSI) caused by carbapenemase-producing Enterobacteriaceae (CPE) is a major public health concern, particularly in the hospital setting. The rapid detection of resistance patterns is of paramount importance for establishing the proper antibiotic regime. In addition, in countries where CPE are endemic, it is also important to evaluate genetic relationship among the isolates in order to trace pathogen circulation and to improve the infection control programs. This study is an application of a rapid blood culture (BC) workflow consisting of fast reporting of Gram stain results, rapid pathogen identification (using MALDI TOF technology), and a molecular assay for the detection of the major genes conferring resistance, all of them performed directly from positive BCs. The application of phylogenetic and phylodynamic analyses to bacterial whole-genome sequencing (WGS) data have become essential in the epidemiological surveillance of multidrug-resistant nosocomial pathogens. We analyzed 40 strains of Klebsiella pneumoniae subsp. pneumoniae (KP) carrying blaKPC (KP-KPC), randomly selected among 147 CPE identified from BCs collected from consecutive patients from 2013 to 2016. The number of BSIs-related CPE were 23, 31, 43, and 50 in 2013, 2014, 2015, and 2016, respectively. Among 147 CPE isolates, 143 were KP and four were Escherichia coli (EC). The gene blaKPC was detected in 117 strains of KP and in four strains of EC. Other carbapenemase genes, such as blaVIM and blaOXA-48, were detected in four and nine different isolates of KP, respectively. Moreover, 13 KP strains carried two resistance genes: twelve vehicled blaKPC plus blaVIM and one blaKPC plus blaOXA-48. Phylogenetic analysis of bacterial WGS data was used to investigate the evolution and spatial dispersion of KP in support of hospital infection control. The maximum likelihood tree showed two main clades statistically supported, with statistical support for several subclusters within as well. The minimum spanning tree showed mixing between sequences from different years and wards with only few specific groups. Bayesian analyses are ongoing, as the aid of Bayesian genomic epidemiology in combination with active microbial surveillance is highly informative regarding the development of effective infection prevention in healthcare settings or constant strain reintroduction.

Transmission trees can be established through detailed contact histories, statistical inference, phylogenetic inference, or a combination of methods. Each method has its limitations, and the extent to which they succeed in revealing a ‘true’ transmission history remains unclear. Moreover, the net value of pathogen sequencing in transmission tree reconstruction is yet to be assessed. We explored the accuracy and sensitivity to biases of a range of methods for transmission chain inference. We studied eight transmission chains determined by contact tracing, each one having more than a third of its cases sequenced (87 samples over 199 cases in total). We compared three inference methods on the selected transmission chains: (i) phylogenetic inference: the Ebola virus (EBOV) sequences derived from patients were mapped onto a dated EBOV phylogeny tree including 398 EBOV sequences sampled in Guinea between March 2014 and October 2015; (ii) statistical inference: we used the maximum likelihood framework developed by Wallinga and Teunis to infer the most likely transmitter-recipient relationships from the onset dates; (iii) combined method: we inferred probabilistic transmission events using both pathogen sequences and collection dates with the R package Outbreaker2. The cases coming from each transmission chain were mostly clustered together in the phylogenetic tree. The few misclassified cases were most likely allocated to the wrong chains of transmission because of the timing of their symptom onsets. Probabilistic transmission tree using only onset dates broadly matched the contact tracing data, but multiple potential infectors were identified for each case. The combined method showed that an a priori knowledge of the number of independent imports had an important impact on the outcome. Although cases were allocated to the correct transmission chains, discrepancies were found in identifying direct case linkage and transmission generations within a chain. Phylogenetic, epidemiological, and combined approaches for transmission chain reconstructions globally concurred in their output. Sequence data proved useful (if not necessary) to place the sampled cases in a wider context, identify transmission clusters, and misclassified cases when epidemiological chains are inferred from date of symptom onset only, and to identify links between supposedly independent chains of transmission.

A combination of high rates of mutation and replication, coupled with strong natural selection, ensures that RNA viruses experience rapid genotypic and phenotypic evolution. Such a ‘fast-forward’ evolution enables viruses to rapidly adapt to new host species, evade host immune responses, and to develop resistance to anti-viral drugs. Similarly, rapid evolution allows viruses to attain new levels of virulence, defined as the ability to cause severe disease in hosts. We hypothesize that distinct viral groups share genetic determinants that modulate virulence that have been acquired through convergent evolution. Thus, common patterns reflecting changing virulence-related specific viral groups could be detected. The main goals for this project are (1) to understand how genetic and phenotypic diversity can be generated among different viral groups by analyzing the variation patterns and determining the selective forces behind them (impact in viral fitness) and (2) to understand how fixed mutations can modulate virulence within different viral groups by performing comparison of strains with differing virulence within a longitudinal timescale. The subject of the study is key emerging and re-emerging virus families of medical importance. Such groups include: Coronaviridae (severe acute respiratory syndrome and Middle East respiratory syndrome-associated coronaviruses), Picornaviridae (Hepatitis A virus), Flaviviridae (Yellow fever, West Nile, Hepatitis C, Dengue, and Zika viruses), Togaviridae (Rubella and Chikungunya virus), Bornaviridae (Borna-disease virus), Filoviridae (Ebola and Marburg viruses), Paramyxoviridae (Measles, Nipah, and Hendra viruses), Rhabdoviridae (Lyssaviruses), Arenaviridae (Lassa virus), Bunyaviridae (Hanta- and Crimean-Congo hemorrhagic fever viruses), and Orthomyxoviridae (Influenza A viruses). Viral genomes collected at different time points, different hosts (human and their most closely related animal reservoirs) and different locations will be compiled. Extensive molecular evolutionary analyses will be carried out to infer gene expansion/contraction within groups, rates of evolution, and changes in selection pressure, including the detection of positive selected genes and sites (adaptive evolution). Positively selected sites will be mapped onto the viral protein structures to reveal their impact on function, and hence the location of potential virulence determinants. Virulence changes among particular viral strains and types will be defined and measured according to definitions based on an increase in: (1) transmissibility, (2) host tropism, (3) immune evasion, (4) morbidity and mortality, (5) drug resistance, and by the incorporation of epidemiological data to determine whether high or low virulence strains within different hosts and localities are spreading most efficiently in nature.

Despite impressive uptake of direct acting antivirals for hepatitis C virus (HCV) in the Netherlands among HIV/HCV co-infected men who have sex with men (MSM), HCV transmission continues, especially among patients previously successfully treated for HCV. The incidence of reinfection occurs at the extremely high rate of 15 per 100 person-years. Clearly, more sophisticated methods are necessary to identify the sources and timing of new HCV infections among MSM. The aim of this research is to phylogenetically characterize HCV transmission dynamics within MSM-specific networks in order to provide a solid base for targeted interventions to monitor, control, and eventually stop the ongoing transmission of HCV among HIV-infected MSM and to prevent further spread of HCV to the community at large. The methodology that will be used is two-fold. Firstly, it concerns setting up a real-time monitoring system to track the HCV epidemic using phylogenetic tools and open-source software from http://nextstrain.org. Secondly, several phylogenetic methods will be used to retrospectively identify transmission clusters in Amsterdam and define epidemiological characteristics, including the directionality of transmission and the size and introduction dates of the clusters. This means that cluster cut-off points will have to be calculated. This research will result in a web-based molecular surveillance tool to monitor the persistence of endemic clades, emergence of new clades, and transmission clusters in ‘real time’, which, combined with clinical and epidemiological data, will be used for targeted interventions. The surveillance tool will be based on the open-source software from nextstrain.org. Secondly, by retrospectively describing the HCV transmission clusters in terms of introduction dates and subsequent dynamics, we may be able to better predict the future dynamics of the different clusters. High-resolution viral sequencing will allow us to identify the source and timing of (new) HCV infections and follow the trajectory of these MSM-specific lineages through the MSM population. Real-time insight in transmission networks using a web-based molecular surveillance tool will identify key targets for rapid interventions, awareness campaigns, and testing strategies. This can be used to prevent further spread to HIV-negative MSM and to control and eventually eliminate HCV from the MSM population.

The increased access of antiretroviral therapy (ART) has drastically improved the health of infected individuals. However, increased levels of ART resistance globally threaten ART effectiveness. Resistance monitoring is currently limited to viremic individuals or prior to ART initiation. The archival nature of the HIV latent reservoir (LR) of virally suppressed patients allows examination for the persistence of ART-resistant latent viral variants. Whole blood samples were collected longitudinally in Rakai, Uganda, from 70 virally suppressed HIV-1 infected individuals. The quantitative viral outgrowth assay was performed to measure the frequency of replication-competent latently infected resting-memory CD4 + (rCD4) T-cells. RNA was extracted from HIV p24-positive outgrowth supernatant, and the reverse transcriptase (RT) region was sequenced using a validated site-specific next-generation sequencing assay (Illumina, San Diego, CA). Consensus sequences containing >2.5 per cent of the total raw amplicons of each outgrowth well were analyzed for ART drug resistance mutations using the Stanford Database. The presence of clonal sequence is expressed as both percent clonality and Shannon Entropy. Replication-competent virus was cultured from 52/70 (74.3%) individuals, of which, RT-pol sequence data were obtained from 49/52 (94.3%) individuals. The presence of ART-resistant virus was found in the LR from one individual on second-line therapy that included a protease inhibitor. There were 20 and 44 total prominent consensus sequences from all wells at years 1 and 3 of follow-up, respectively. ART-resistant mutations for both RT-inhibitor drug classes were found in 30 per cent and 27.3 per cent of the total prominent consensus sequences of this one individual from years 1 and 3, respectively. The major ART resistance profile in this individual included: M184V, Y188L, K191E, and G190A. The percentage of total outgrowth that was clonal (percent clonality) increased from year 1 to year 3 (38.1–81.8%) and Shannon Entropy decreased (0.722–0.576). The presence of archived replication-competent ART-resistant virus in the LR was found in only one individual. There were two ART-resistant prominent consensus sequences isolated at year 3 that were not sampled 2 years earlier. The persistence of resistant, intact replication-competent proviral sequences in the LR of this individual seem to be supported by clonal expansion.

Wild ducks and gulls are the major reservoirs for avian influenza A viruses (AIVs). The mechanisms that drive AIV evolution are complex at sites where various duck and gull species from multiple flyways breed, winter, or stage. The Republic of Georgia is located at the intersection of three migratory flyways: the Central Asian Flyway, East Asian/East African Flyway, and Black Sea/Mediterranean Flyway. For six consecutive years (2010–6), we collected AIV samples from various duck and gull species that breed, migrate, and overwinter in Georgia. We found substantial subtype diversity of viruses that varied in prevalence from year to year. Low pathogenic (LP)AIV subtypes included H1N1, H2N3, H2N5, H2N7, H3N8, H4N2, H6N2, H7N3, H7N7, H9N1, H9N3, H10N4, H10N7, H11N1, H13N2, H13N6, H13N8, and H16N3, plus two H5N5 and H5N8 highly pathogenic (HP)AIVs belonging to clade 2.3.4.4. Whole-genome phylogenetic trees showed significant host species lineage restriction for nearly all gene segments and significant differences for LPAIVs among different host species in observed reassortment rates, as defined by quantification of phylogenetic incongruence, and in nucleotide diversity. Hemagglutinin clade 2.3.4.4 H5N8 viruses, circulated in Eurasia during 2014–5 did not reassort, but analysis after its subsequent dissemination during 2016–7 revealed reassortment in all gene segments except NP and NS. Some virus lineages appeared to be unrelated to AIVs in wild bird populations in other regions with maintenance of local AIV viruses in Georgia, whereas other lineages showed considerable genetic inter-relationship with viruses circulating in other parts of Eurasia and Africa, despite relative under-sampling in the area.

Sewage samples have a high potential benefit for surveillance of circulating pathogens because they are easy to obtain and reflect population-wide circulation of pathogens. These type of samples typically contain a great diversity of viruses. Therefore, one of the main challenges of metagenomic sequencing of sewage for surveillance is sequence annotation and interpretation. Especially for high-threat viruses, false positive signals can trigger unnecessary alerts, but true positives should not be missed. Annotation thus requires high sensitivity and specificity. To better interpret annotated reads for high-threat viruses, we attempt to determine how classifiable they are in a background of reads of closely related low-threat viruses. As an example, we attempted to distinguish poliovirus reads, a virus of high public health importance, from other enterovirus reads. A sequence-based deep learning algorithm was used to classify reads as either polio or non-polio enterovirus. Short reads were generated from 500 polio and 2,000 non-polio enterovirus genomes as a training set. By training the algorithm on this dataset we try to determine, on a single read level, which short reads can reliably be labeled as poliovirus and which cannot. After training the deep learning algorithm on the generated reads we were able to calculate the probability with which a read can be assigned to a poliovirus genome or a non-poliovirus genome. We show that the algorithm succeeds in classifying the reads with high accuracy. The probability of assigning the read to the correct class was related to the location in the genome to which the read mapped, which conformed with our expectations since some regions of the genome are more conserved than others. Classifying short reads of high-threat viral pathogens seems to be a promising application of sequence-based deep learning algorithms. Also, recent developments in software and hardware have facilitated the development and training of deep learning algorithms. Further plans of this work are to characterize the hard-to-classify regions of the poliovirus genome, build larger training databases, and expand on the current approach to other viruses.

The H3N2 subtype of influenza A (H3N2) was the predominant strain during the early months of the 2017 influenza epidemic in Brazil. In Australia, it was responsible for a strong and prolonged 2017 season and reached the Northern hemisphere causing an intense 2017/8 influenza season. Several genetic and antigenic A(H3N2) variants were circulating, which made the decision about which strain to incorporate into the influenza vaccine challenging. For 2018, the WHO selected a new H3N2 strain, A/Singapore/INFIMH-16-0019/2016-like, to replace the strain A/HongKong/4801/2014-like in the Southern Hemisphere trivalent vaccine. The aim of this study was to describe the genetic diversity of influenza A (H3N2) viruses circulating in Brazil between January 2017 and January 2018, checking the match between the vaccines and worldwide circulating strains with the Brazilian influenza strains. Hemagglutinin gene sequencing of the influenza A (H3N2) was performed, followed by a phylogenetic reconstruction using additional database sequences to define genetic groups and compare with other worldwide circulating strains. We observed a large diversity of H3N2 genetic clusters, including 3C.2a, 3C.2a1, 3C.3a, and their subgroups. During the 2016–7, inter-epidemic and 2017 epidemic period the cluster most frequently detected belonged to clade 3C.2a1 (148/185; 80.0%), a distinct group related to the 2017 vaccine strain A/HongKong/4801/2014-like (3C.2a). However, the genetic profile changed during the study period and in the inter-epidemic season 2017–8 the most commonly detected genetic group was the 3C.2a cluster (43/58; 74.1%). Inside this cluster, the majority (34/43; 79.1%) of strains belonged to a single genetic 3C.2a subgroup 2 (3C.2a2), bearing antigenic substitutions T131K and R142K (site A) and R261Q (site E). The dominance of this 3C.2a2 in the 2017–8 inter-epidemic period in Brazil was similar to the 2017–8 season in Europe and Canada according their surveillance data. The new vaccine strain has five to six antigenic changes in comparison to the predominant 3C.2a2 circulating in South America since September 2017 until now. It is possible that the vaccine mismatch will not protect the population against a majority of circulating strains. Surveillance of the vaccine effectiveness supported by antigenic and serological analysis are necessary to prove this hypothesis. However, this highlights the difficulty of vaccine strain selection and highlights the need for of a universal influenza vaccine.

Chikungunya is a viral disease (genus Alphavirus) which is transmitted to humans by infected mosquitoes—including Aedes aegypti and A. albopictus. An outbreak of febrile illness, suspected to have been caused by chikungunya, was reported in June 2016 from Dolloado district, Suuf Kebele, in the Somalia regional state of Ethiopia that borders the Mandera county of Kenya where a confirmed chikungunya outbreak was ongoing. Laboratory investigation was carried out to confirm if the outbreak in Ethiopia was caused by Chikungunya virus. Ten serum samples were collected from suspected patients visiting a health center in Suuf Kebel, who were then sent to the Nation laboratory in Ethiopian Public Health Institute. RNA was extracted from the serum samples using QIAgene RNA Mini kit, and PCR detection of dengue, chikungunya, and Zika virus nucleic acid was done using Trioplex Real-time RT-PCR Assay following the protocol from the Center for Disease Control (CDC). The Trioplex Real-time RT-PCR assay, for detection and differentiation of RNA from dengue, Chikungunya and Zika, was provided by CDC as part of the zika emergency preparedness effort. Of the nine samples tested, eight (88.88%) were found to be positive for chikungunya virus nucleic acid but negative for dengue and Zika virus nucleic acids. The median age of the affected sampled patients was 40 years, and males appear to be more affected (66.6% of sampled patients). The laboratory investigation confirmed that the outbreak was caused by chikungunya virus. Even though further molecular characterization of the positive isolates will provide more information as to the circulating genotypes and elucidate the origin of the outbreak virus, it is also possible to assume that the outbreak was an extension of the outbreak in neighboring countries in Kenya and, therefore, warrants that cross-border integration efforts to control chikungunya should be implemented by the concerned countries.

Romania has faced an HIV outbreak among people who inject drugs (PWID) since 2011. The introduction of so-called ‘legal highs’ (amphetamine-type stimulants) on the drug market a few years prior contributed substantially to this outbreak. Next-generation sequencing (NGS) provides the possibility to detect drug resistance mutations with higher sensitivity than Sanger sequencing. The aim of this study was to search for transmitted drug resistance (TDR) mutations in strains from PWID recently diagnosed with HIV infection by parallel use of Sanger sequencing and NGS. The study was conducted on strains from 34 PWID diagnosed with HIV infection between 2016 and 2017. Sequencing was performed for the pol (PR, RT, and INT) and env (V2-V3 loop) regions. Sanger sequencing was performed with the commercial ViroseqTMHIV-1 Genotyping system (Abbott Laboratories) and with an in-house protocol for the env gene. NGS was performed in the same genomic regions using Nextera DNA Library Preparation Kit (Illumina) and the Miseq instrument (Illumina). NGS data were processed for error correction, read mapping, and detection of drug resistance mutations with HIV-1 Deepchek analysis software. Geno2pheno algorithm was used for viral tropism prediction and the WHO 2009 list for TDRM analysis. By using NGS, we detected seven cases (20.6%) of TDR in PWID and only two cases (5.8%) with standard sequencing. The TDR mutations detected by NGS were K103N, K101EN, Y181C, T215S in RT gene, I54V and M46L in PR, and none in INT. Two NNRTI mutations (K103N and K101EN) were detected in the same sample. Most of the TDR identified were present in the minority population (between 1% and 2% of the total reads) explaining the higher sensitivity of NGS method compared with standard sequencing. No significant differences were observed between these two methods when tropism prediction was analyzed. The majority of the viruses circulating in this group were R5-tropic. All strains showed more resistance mutations when analyzed by deep sequencing than by Sanger sequencing and more than previously observed in other risk groups. NGS proved to be a sensitive tool to detect TDR in newly infected PWID.

As research next-generation sequencing (NGS) metagenomic pipelines transition to clinical diagnostics, the user-base changes from bioinformaticians to biologists, medical doctors, and lab-technicians. Besides the obvious need for benchmarking and assessment of diagnostic outcomes of the pipelines and tools, other focus points remain: reproducibility, data immutability, user-friendliness, portability/scalability, privacy, and a clear audit trail. We have a research metagenomics pipeline that takes raw fastq files and produces annotated contigs, but it is too complicated for non-bioinformaticians. Here, we present preliminary findings in adapting this pipeline for clinical diagnostics. We used information available on relevant fora (www.bioinfo-core.org) and experiences and publications from colleague bioinformaticians in other institutes (COMPARE, UBC, and LUMC). From this information, a robust and user-friendly storage and analysis workflow was designed for non-bioinformaticians in a clinical setting. Via Conda [https://conda.io] and Docker containers [http://www.docker.com], we made our disparate pipeline processes self-contained and reproducible. Furthermore, we moved all pipeline settings into a separate JSON file. After every analysis, the pipeline settings and virtual-environment recipes will be archived (immutably) under a persistent unique identifier. This allows long-term precise reproducibility. Likewise, after every run the raw data and final products will be automatically archived, complying with data retention laws/guidelines. All the disparate processes in the pipeline are parallelized and automated via Snakemake1 (i.e. end-users need no coding skills). In addition, interactive web-reports such as MultiQC [http://multiqc.info] and Krona2 are generated automatically. By combining Snakemake, Conda, and containers, our pipeline is highly portable and easily scaled up for outbreak situations, or scaled down to reduce costs. Since patient privacy is a concern, our pipeline automatically removes human genetic data. Moreover, all source code will be stored on an internal Gitlab server, and, combined with the archived data, ensures a clear audit trail. Nevertheless, challenges remain: (1) reproducible reference databases, e.g. being able to revert to an older version to reproduce old analyses. (2) A user-friendly GUI. (3) Connecting the pipeline and NGS data to in-house LIMS. (4) Efficient long-term storage, e.g. lossless compression algorithms. Nevertheless, this work represents a step forward in making user-friendly clinical diagnostic workflows.

Salmonellosis is one of the leading causes of foodborne disease worldwide, with an estimated one million cases a year in the United States. Salmonella 4,[5],12: i:-, a monophasic variant of Salmonella typhimurium, is an emerging serovar that has been associated with multiple foodborne outbreaks throughout the world, mostly attributed to pig and pig products. Recently, we have demonstrated that two distinct groups of Salmonella 4,[5],12:i:- circulate in the USA and Europe, with the majority of isolates recovered during recent years belonging to an emerging multidrug-resistant clade (Elnekave et al. 2018). We applied Bayesian phylodynamic reconstruction to uncover the evolutionary history of this clade. We used a dataset of whole-genome sequences of 1446 4,[5],12:i:- isolates from different sources (livestock, human, food products, and others) from the USA (n = 752) and Europe (n = 694), collected between 2008 and 2017 and belonging to the Multilocus Subtype 34, which was predominant in the emerging clade (Elnekave et al. 2018). A subset (n = 110) of Salmonella 4,[5],12:i: isolates was then randomly selected after stratifying by location and year of isolation in order to achieve balanced sampling. Evidence of temporal signal was confirmed by looking at root-to-tip divergences using TempEst. Evolutionary hypotheses using strict and relaxed-clock models were tested using BEAST for a variety of demographic models and assuming a general time reversible substitution model. Model selection was performed by estimating Bayes Factors using path sampling and stepping-stone sampling. The selected model was then used for applying discrete trait models comparing different scenarios of transmission between locations (i.e. bidirectional symmetric/asymmetric or unidirectional). Our preliminary phylodynamic inference results indicate that the origin of this subtype was in Europe and dates back to 1990 (HPD 95%: 1984–2001). We report an exponential growth rate of 0.362 per year, which corresponds to a doubling time of 1.43 years. Our results suggest that this subtype was introduced to the US in the year 2000 (HPD 95%: 1994–2006). Phylodynamic analysis suggests that the recent increase in isolation of Salmonella 4,[5],12:i:- from different sources in the USA may be due to the exponential expansion of an emerging clone which originated in Europe and then expanded to the USA. The emergence and expansion of this serovar is of great public health importance due to the high prevalence of multidrug resistance traits found in USA isolates from this group and especially due to the presence of plasmid-mediated resistance genes for quinolones and extended spectrum cephalosporins, key antimicrobials used for the treatment of invasive Salmonella infections.

The Swedish HIV-1 epidemic is characterized by a high diversity in HIV subtypes and recombinants as a result of migration. To study the time from infection through viral diversification, transmission patterns, and drug resistance in minor quasispecies, a robust protocol for pan-genotypic near full-length HIV-1 genome (HIV-NFLG) next-generation sequencing (NGS) is key. Our group has established two protocols for HIV-NFLG on the Illumina platform that we aim to compare and, if necessary, modify to find a method with optimized coverage, depth, and subtype inclusivity. Zanini et al. (https://doi.org/10.7554/eLife.11282.001) have developed a method with one-step RT-PCR with six overlapping primer sets, followed by NGS and quality filtering and assembly with in-house methods. Aralaguppe et al. (https://doi.org/10.1016/j.jviromet.2016.07.010) have designed amplification in two fragments, followed by multiplexed NGS and quality control and assembly with Iterative Virus Assembler and VICUNA. Both methods have high coverage per nucleotide and low error rates in amplification and sequencing and can reliably identify SNPs at 1 per cent of the viral population with linkage within the quasispecies. Subtype inclusivity remains a challenge even though both methods show success in amplifying and sequencing subtypes B, C, and the common recombinants 01_AE and 02_AG. Therefore, we aim to evaluate and optimize our NFLG NGS methods on a panel of patient samples that more completely reflects HIV-1 diversity in Sweden. Patient samples from fifty treatment-naïve viremic individuals representing the genotypic HIV-1 panorama in Sweden, including CRFs, are being amplified and sequenced by both protocols. Coverage of the genome, error rate, and possible depth of quasispecies analysis is being evaluated. We will compare number of reads, coverage across the HIV genome, and representation of minor single nucleotide variants as well as subtype inclusivity and impact of plasma RNA levels. To do this we will use an in-house bioinformatic pipeline. The NFLG sequences will also be analyzed with phylogenetic tools for determination of subtypes including CRFs and URFs.

Rodents play a key role as reservoirs of many zoonotic pathogens which represent an emerging public health threat worldwide. Among these, Dobrava-Belgrade virus (DOBV) is the most pathogenic hantavirus in Europe with a case-fatality rate of up to 12 per cent, while Lymphocytic choriomeningitis virus (LCMV) has a mortality rate below 1 per cent. Both viruses are predominantly transmitted to humans through the inhalation of infected particles in aerosolized urine, feces, or saliva that are shed in the environment by chronically infected hosts, such as the yellow-necked mouse Apodemus flavicollis. Although no human cases of DOBV or LCMV have been reported in the Province of Trento (northeastern Italy) thus far, in order to evaluate the human hazard for these viruses, the prevalence of antibodies to DOBV and LCMV has been monitored using a specific immunofluorescence assay test in a wild population of A. flavicollis since 2000. These investigations have shown that the two RNA viruses circulate silently in this species in the study area. In particular, a sudden increase (up to 12.5%) in DOBV seroprevalence was observed in this rodent species between 2010 and 2012. Several efforts have been undertaken to isolate these viruses and characterize their genomes, but it has not yet been possible to detect viral RNA from seropositive mice using traditional methods such as RT-PCR. Since RNA viruses are very diverse and often difficult to isolate, innovative molecular methods based on viral targeted enrichment and high-throughput sequencing have been applied. We intend to report on this long-term seroprevalence study and provide an overview of the molecular approaches adopted in the attempt to confirm the presence of these viruses, and identify which variants are circulating in the region, as well as their pathogenicity.

We are interested in using phylodynamics to better understand molecular clusters of HIV within the state of Florida, USA. To our knowledge, there is currently no study using such methodology to understand the epidemic in Florida. Viral sequences collected from 2007 to 2017 (about 50,000) will be linked with individual-level data (demographics—sex, race/ethnicity—and mode of transmission) accessed through the Patient Reporting Investigating Surveillance Manager (PRISM), and the Enhanced HIV/AIDS Reporting System (eHARS) via the Florida Department of Health (FDOH). Through the use of HIV-TRACE, which analyzes genetic distance matrices, we will create molecular transmission networks including data on mode of transmission, race/ethnicity, and sex. Furthermore, a maximum likelihood phylogenetic tree will be created using software (e.g. IQ-Tree, PhyML, and FastTree2) run on a high-performance cluster. Phylogenetic comparative analysis will be performed to assess the association between phylogenetic clades and demographics (including extended demographics like syphilis and other comorbidities queried from PRISM and eHARS).

We used Bayesian evolutionary analysis to study linguistic data and infer phylogenetic trees of language evolution. Languages were encoded as binary strings indicating the presence or absence of members of cognate classes, the equivalence of classes of words with similar meaning, and shared ancestry. These strings formed the alignment data used to compute the posterior likelihood of a tree with respect to Bayes’ formula. Informative priors are crucial for testing hypotheses regarding the age of common ancestry and divergence times and should include as much available information as possible. Here, we investigated the birth–death process as a method to construct tree priors specifically suitable for modeling the evolution of cognate data. To test these models, we will use a dataset of the languages from Vanuatu, an island nation featuring world’s highest language density.

Thanks to high-throughput sequencing (HTS) and dedicated bioinformatics tools, it is possible to study all viruses present in a sample with an unprecedented detection of viral diversity. Applied to wildlife and humans, HTS becomes a powerful means to understand viral emerging infectious diseases. BLAST searches to find remote homolog sequences after an assembly of shotgun-generated sequences are often used to analyze virome datasets. However, this process might be biased by molecular biology approaches (use of whole genome/transcriptome amplification) and bioinformatics assembly that can induce chimeric sequences formation. Our objective was to identify confounding factors (molecular biology and bioinformatics) that can bias virome composition. Hence, we studied the viromes from cloacal swab samples of two migratory birds. Viral DNA and RNA were extracted using three different methods (easymag®, phenol, and trizol), followed by whole genome amplification (WGA)/WTA amplifications, before Illumina MiSeq sequencing. After trimming and assembly, sequences underwent BLAST (BLASTn and BLASTx). At the end of the first BLAST (n/x), some portions of sequences were uncovered and unassigned. We, then, implemented a novel recursive split-resubmit python program that searched for homologs of > 50 base pairs (bp), uncovering parts for a better exploitation of the datasets. Thirty-eight known viral families were detected in our samples. Circoviridae, Parvoviridae, and Microviridae were found in the majority of the results from easymag® and Phenol extracted samples, while trizol samples resulted in a majority of Picornaviridae and Coronaviridae. These results show that the viromes are of different composition depending on extraction methods. Most of the viral sequences were predominantly identified at the blastx step reflecting a high level of divergence with known viral sequences. Compared to a unique BLAST search, our resubmission pipeline allowed the assignment of up to 23 per cent of the viral sequences. Most of these sequences belonged to taxa already observed at the first blast step and few viral sequences of different families were detected. Knowing the complementarities between extraction methods and a better identification of viral sequences using our pipeline, the next step will be to get a precise position of each viral genomic segment in phylogenetic distance-based tree that will give a more accurate representation of viral diversity.

There is still no cure for chronic hepatitis B virus infection (CHBV), a major cause of liver cancers and related malignancies. Elucidating the role of CD4+ T-helper cells in activating immunological responses that clear antigenic peptides during primary HBV infection holds a potential strategy for developing potent vaccines. Since the strength of CD4+ T cell responses is dictated by binding of viral epitopes to class-II human leukocyte antigens (HLAs), we hypothesize that the quality of immunological responses in CHBV patients is influenced by host genetics and HBV genotypes. Here, ninety-two non-recombinant complete HBV surface-gene proteins (PreS1/S) from Botswana were sequenced (genotype A 44(47.8%); D 48(52.2%)) and 15-mer binding epitopes restricted to nine HLA-class II molecules (DRB5/1) were mapped in silico. The HLAs used have high population coverage in Botswana. The total predicted epitopes per HLA were 94-(genotype A) and 105-(genotype D) for PreS1, 42 (A and D) for PreS2, and 105 (A and D) for S. Epitope densities (binding peptides to total epitopes) were 3 per cent and 6 per cent (PreS1A&D), 4 per cent and 2 per cent (PreS2A&D), and 23 per cent and 22 per cent (S1A&D). SA&D proteins had most polytopes: CPGYRWMCLRRFII66-81, PGYRWMCLRRFIIF67-82, GYRWMCLRRFIIFL68-83, and YRWMCLRRFIIFLF69-84 binding to 5 (55.6%) HLAs (DRB1*0101/0701/1101/1501 and DRB5*0101) used. HLA-DRB*0101 bound the most epitopes, and the least were bound by HLA-DRB*0302/0701/0401 for both genotypes. PreS1D polytope: PAFRANTANPDWDFN32-46 binds to DRB1*0101/0401/1302 and PreS2 polytopes: TAFHQALQDPRVRG6-19 and AFHQALQDPRVRGL7-20 bind to DRB1*010/1501 alleles. Non-synonymous mutations impair peptide-HLA binding when assessed as combinations of > 2. The least active HLAs may be associated with CHBV and vice-versa for HBV clearance, thus the algorithm may be used to predict HBV prognosis for different haplotypes. The results favor the use of epitopes from S protein as broad genotype vaccine. This study highlights the need to explore further the mechanisms of PreS1 and its effect on the immune system.

In order to assess the molecular epidemiology of African swine fever (ASF) in Sardinia, we analyzed a wide range of isolates from wild and domestic pigs over a 31-year period (1978–2009) by genotyping sequence data from the genes encoding the p54 and the p72 proteins and the CVR. On this basis, the analysis of the B602L gene revealed a minor difference, placing the Sardinian isolates into two clusters according to their temporal distribution. As an extension of this study, in order to achieve a higher level of discrimination, three further variable genome regions, namely p30, CD2v, and I73R/I329L, of a large number of isolates collected from outbreaks in the years 2002–14 have been investigated. Sequence analysis of the CD2v region revealed a temporal subdivision of the viruses into two subgroups. These data, together with those from the B602L gene analysis, demonstrated that the viruses circulating in Sardinia belong to p72/genotype I, but since 1990 have undergone minor genetic variations in respect to its ancestor, thus making it impossible to trace isolates, enabling a more accurate assessment of the origin of outbreaks, and extending knowledge of virus evolution. To solve this problem, we have sequenced and annotated the complete genome of nine ASF isolates collected in Sardinia between 1978 and 2012. This was achieved using sequence data determined by next-generation sequencing. The results showed a very high identity with range of nucleotide similarity among isolates of 99.5 per cent to 99.9 per cent. The ASF virus (ASFV) genomes were composed of terminal inverted repeats and conserved and non-conserved ORFs. Among the conserved ORFs, B385R, H339R, and O61R-p12 showed 100 per cent amino acid identity. The same was true for the hypervariable ORFs, with regard to X69R, DP96R, DP60R, EP153R, B407L, I10L, and L60L genes. The EP402R and B602L genes showed, as expected, an amino acid identity range of 98.5 per cent to 100 per cent and 91 per cent to 100 per cent, respectively. In addition, all of the isolates displayed variable intergenic sequences. As a whole, the results from our studies confirmed a remarkable genetic stability of the ASFV/p72 genotype I viruses circulating in Sardinia.

Bacteriophages and their endolysins, enzymes that degrade the cell walls of bacteria, are emerging as alternative tools to detect and inhibit growth of pathogen bacteria. Listeria monocytogenes is a foodborne pathogen that causes listeriosis, a serious invasive disease that affects both humans and a wide range of animals. Listeria spp. are ubiquitous in the dairy farm environment and could be present in dairy-processing plants and wastewater. All Listeria-specific bacteriophages found to date are members of the Caudovirales, of the Siphoviridae or Myoviridae families. Myophages infecting Listeria have been recently classified by the ICTV in the Spounavirinae subfamily, as well as in the P100 virus genus. The aim of this work was to isolate Listeria spp. bacteriophages and their endolysin codifying genes from wastewater of a dairy industry. Wastewater with and without treatment was sampled during the course of a year, and isolation of bacteriophages was performed after an enrichment step using as hosts L. innocua, L. ivanovii, and L. monocytogenes serotypes 1/2a, 1/2b, and 4b. Bacteriophages infecting L. innocua and L. ivanovii were isolated (n = 24) from 3 out of 12 samples. Bacteriophages were purified, and the host range was determined using spot test and EOP against five collection strains and several field isolates of Listeria spp. Two bacteriophages of narrow and broad host range, vB_Lino_VEfB7, and vB_Liva_VAfA18, were selected for further characterization. High titer stocks of bacteriophages were purified by centrifugation with ammonium acetate, and morphological information on the purified bacteriophages was obtained by negative staining and transmission electronic microscopy. Their morphology, size, and contractile tails indicated that these bacteriophages belonged to the Myoviridae family. Bacteriophage genomes were extracted using phenol-chloroform, followed by ethanol precipitation, and tested by digestion with RNAsa A and DNAse I. RFLP was performed, digesting genomes with restriction enzymes HindIII and NcoI. Consistent with the morphological findings, bacteriophages contained dsDNA genomes but showed different RFLP patterns. A PCR designed to amplify conserved domains of endolysins—PGRP and CwlA—was applied to characterize this gene. Another PCR was designed to amplify the complete endolysin gene, and the complete sequence of this gene was obtained and analyzed. Substitution model selection and a maximum likelihood phylogenetic tree of the endolysin gene was carried out using IQ-Tree software. The sequences of the endolysin gene indicated that the codified enzyme is an N-acetyl-muramoyl-L-alanine amidase, related to A511 and P100 species of the recently described P100virus genus. Further evolutionary analyses are needed to evaluate their belonging to this species or their taxonomy within this genus.

Foodborne viruses such as hepatitis E virus (HEV) pose an increasing risk to public health and to confidence in Irish food. Hepatitis E has been acknowledged as a significant pathogen of likely zoonotic transmission, with pork products and shellfish being implicated as potential sources. The European Food Safety Authority has recommended that systematic strain typing of viruses in humans, animals, and food commodities is needed to improve understanding of etiological agents and foodborne transmission pathways, in particular for HEV. The dominant autochthonous genotype of HEV in Europe is genotype 3, thought to be associated with consumption of contaminated food, specifically pork products. However, little is known about the epidemiology of HEV in Ireland. In 2016, HEV became a notifiable disease in Ireland. Following this, as part of the Department of Agriculture, Food and the Marine-funded FoVIRA study, the molecular epidemiology of HEV in Irish clinical samples has been characterized for the first time. HEV RNA-positive clinical specimens from 2016 were genetically characterized (n = 14). A 450 nucleotide fragment of the ORF2 region of the HEV genome was amplified, with contiguous sequence assembly performed using DNA Lasergene v14. Sequences were aligned with ClustalW implemented in Bioedit v7.1.9 and compared to reference strains from GenBank. A maximum likelihood phylogenetic tree was constructed using the Hasegawa–Kishino–Yano model and a discrete gamma distribution to model evolutionary rate distances between sites. Evolutionary analyses were conducted in MEGA7. Statistical support was provided by bootstrapping with 1,000 replicates. Fourteen strains belonged to genotype 3 and were classified as the following subtypes: 3c (n = 7), 3e (n = 4), 3f (n = 1), 3 untyped (n = 1), and 1 untyped. Phylogenetic analysis showed the formation of two distinct clusters of genotype 3:3abchij and 3efg, with strong bootstrap support. A genotype 1 was detected and found to be associated with travel. Data generated from this research will contribute to a risk exposure assessment and will be used to identify potential control points and risk mitigation measures for viral foodborne pathogens. This study will provide a unique opportunity to build national capability in the area of food testing within Irish public laboratories.

Arbovirus transmission involves an interplay between host, virus, and environmental factors. Because of the complexity of interactions, the transmission success of arboviruses could either be a function of viral fitness or be stochastic. In the present study, using 1,963 envelope (E) gene sequences and 239 whole genomes, we conducted a large-scale molecular epidemiological analysis of a dengue virus type 1 (DENV-1) population to understand the transmission success, evolution, and dispersal patterns of different lineages of DENV-1 circulating in Singapore from 2011 to 2016. The study population was highly dynamic and heterogeneous. However, only a handful of genetically distinct strains (n = 6) established sustained transmission, but at variable levels of dominance. Phylogeographic analysis revealed a weak spatial clustering and 35 well-supported diffusion pathways, implying widespread and complex dispersal of these strains in local settings. Yet, the dominant strains were neither evolving faster than less dominant ones nor under positive selection. These observations suggested that lineage dominance was likely to be stochastic and opportunistically driven by non-viral factors such as host immune pressure and vector abundance. Our findings, therefore, emphasize the implications of understanding the vector and human factors in parallel to virus dynamics on continuing efforts to control the arbovirus disease transmission in endemic regions.

Human Middle East respiratory syndrome is a zoonotic respiratory disease caused by Middle East respiratory syndrome coronavirus (MERS-CoV) originating from camels in the Arabian Peninsula. While there are a large number of camels in East Africa, often traded to the Arabian Peninsula, no autochthonous human MERS-CoV case is reported in East Africa. Furthermore, there is limited information of MERS-CoV in East Africa. In this study, MERS-CoV in dromedary camels from Ethiopia was detected using RT-qPCR. Next-generation sequencing was used to obtain the full genome of MERS-CoV. MERS-CoV antibodies were also detected through MERS-spike pseudoparticle neutralization assay. Phylogenetic analysis of full-genome sequences and spike-genome antibodies indicates that MERS-CoV in East Africa is genetically distinct from those in the Arabian Peninsula. The results from this study show that MERS-CoV circulating in dromedary camels in East Africa are genetically distinct from those in the Arabian Peninsula. Further studies are needed to evaluate the risk of zoonotic transmission in East Africa.

Accurate definition of the HIV-1 reservoir on antiretroviral therapy (ART) is of paramount importance to the development of curative strategies. Much of this reservoir is derived from clonal expansion of latently infected CD4+ T cells. Methods used to characterize the reservoir include near full-length single-genome sequencing (NFL-SGS) and integration site analysis (ISA). However, current technologies do not link the intact proviruses detected by NFL-SGS to their sites of integration. Therefore, we developed a method to obtain both near full-length single-proviral sequences and their sites of integration. We call our method full-length integrated proviral single-genome sequencing (FLIP-SGS). Genomic DNA from ACH2 and CEM cells mixed at 1:1,000, or patient samples were diluted to a single proviral endpoint. An in-house, optimized whole genome amplification (WGA) method was performed on wells at the endpoint, generating multiple copies of all DNA molecules within each well. The number of proviral copies after WGA was determined by droplet digital PCR targeting the long terminal region (LTR). Forty per cent of each WGA reaction was used to obtain the provirus–host integration sites with ISA (linker ligation, nested PCR, and Illumina sequencing). The remaining fraction was used to amplify the full-length proviruses in four overlapping fragments (LTR-pol, gag-int, int-env, and env-LTR) for Sanger sequencing. WGA performed on the endpoint-diluted ACH2:CEM DNA amplified single-copy HIV-1 proviral templates greater than 500-fold, making it possible to obtain unique integration sites from single proviruses in ACH2 cells, including one that was previously reported (in the NT5C3A gene on chromosome 7) and two that were not previously reported (in the EIF4ENIF1 gene of chromosome 22 and an unknown region of chromosome 6). Near full-length PCR amplification and Sanger sequencing was performed on proviruses integrated in the NT5C3A gene. FLIP-SGS was applied to peripheral blood mononuclear cells from one HIV-1 infected donor with viremia suppressed on ART and yielded integration sites of four genomes that appear to contain large internal deletions. We report a method for near full-length HIV-1 single-genome sequencing combined with host integration site detection that we call FLIP-SGS. This assay will further define clonal expansion of infected CD4+ T cells as a mechanism that maintains the HIV-1 reservoir and as the source of identical sequences observed during therapy and rebound, rather than from ongoing replication.

Zika virus (ZIKV) has been circulating in the South Pacific since 2007, and transmission in Fiji was first confirmed in 2015. To better understand the history and transmission dynamics of ZIKV in Fiji, we combined a transmission dynamic model with serological and surveillance data from Central Division, Fiji. A longitudinal population representative of seroepidemiological data were available from participants sampled in 2013, 2015, and 2017. In addition, ZIKV case reports were available from 2015 and 2016. Using a Bayesian approach, we fitted a transmission dynamic model with a seasonally varying transmission to these data. We also estimated the virus introduction date, given the effect this has on transmission dynamics as it interacts with the observed seasonal pattern of transmission. We found evidence that the virus was introduced in October 2013 (95% credible interval: April 2013–April 2014) and that the strong seasonal transmission pattern meant the virus persisted for several years with multiple waves of infection in consecutive years. It is important to corroborate this evidence against other work done in the same area. A phylogenetic analysis was performed on 5 ZIKV strains obtained from Fiji in 2015 and 2016, which were aligned with 33 E gene sequences from the Pacific, Americas, and Africa. This analysis showed evidence of virus persistence over multiple years in Central Division, Fiji. The estimated most recent common ancestor of the group isolated from Central Division was November 2013 (95% credible interval: March 2013–July 2015). Our modeling estimate is consistent with these results despite the very different methods being used. The availability of detailed case and serology data in an island outbreak setting, combined with mathematical models, presented a unique opportunity to gain crucial insights into these infections. Our analysis provides evidence that seasonal variation in transmission, combined with other co-circulating flaviviruses, means the timing of ZIKV introduction can have a major impact on outbreak transmission dynamics.

An increasing number of zoonotic viruses have been detected in animals, especially in poultry species. Understanding the diversity of zoonotic infections and the local behavior helps to characterize the pathogen diversity in human and animals and predict the risk of pathogen spill-over from animals to human. Vietnam is considered, along with other countries in Southeast Asia, as a hotspot for zoonotic viruses. In Vietnam, domestic animals are typically farmed in close proximity to humans, which may increase the risk of transmission of zoonotic pathogens. Our previous studies found the presence of some zoonotic viruses (e.g. rotavirus group A, hepatitis E virus) in domestic pigs. However, the risk of pathogenic transmission from domestic animals to humans has not been determined. Detailed genomic sequence data may help to track the origin and evolution of zoonotic pathogens. To understand the origins and emergence of zoonotic infections in people, who have regular contact with animals, we will investigate the viral diversity in farmers and domestic animals in their farm, using high-throughput sequencing technique. Viral RNA was extracted from pooled fecal samples of 30 farmers and 50 pigs, and used as input for SureSelect target enrichment and Illumina MiSeq sequencing.

Influenza D virus (IDV) is a new viral genus identified within the Orthomyxoviridae family, showing 50 per cent amino acid identity with human influenza C virus. Similar to human influenza viruses of the C genus, IDV also harbors 7 genomic segments and uses 9-O-acetylated sialic acids as cell receptors. This newly emerged virus exhibits a broad host range and is capable of infecting swine, cattle, sheep, goats, ferrets, and guinea pigs. In Italy, IDV was first detected in archived samples collected between 2014 and 2015 from cattle and swine in the Po Valley area. Here, we report the genetic characterization of IDV viruses detected in an extensive area of northern Italy, namely Veneto, Lombardy, and Piedmont, through passive surveillance between September 2015 and October 2017. A total of 482 samples, including nasal swabs, lungs, and bronchoalveolar lavage fluid, collected from 309 cattle farms were tested. Thirty cattle herds turned out to be positive, for a total of 40 samples positive by Real Time RT-PCR targeting the PB2 gene. Representative IDV positive swabs were sequenced on an Illumina Miseq platform, and phylogenetic analyses were performed for each genome segment. The analyses of the seven gene segments demonstrated that the viruses identified in the north of Italy clearly grouped within a genetic cluster of IDV sequences previously described in Italy and in the USA, thus suggesting a common origin for these viruses. Interestingly, the IDVs identified in Italy presented a low similarity (96.1% to 98.8% for the seven gene segments) to the French IDVs, which is the only other European country where this pathogen has been identified and characterized so far. The wide IDV host range and the ability of this virus to reassort are a matter of concern. Results of this study indicate that IDV is extensively circulating among bovine herds in Northern Italy and suggest a potential role of IDV in the bovine respiratory disease complex, highlighting the need to perform surveillance on an ongoing basis to track its spread and evolution.

Namao virus (NV) is a sturgeon nucleocytoplasmic large DNA virus (sNCLDV) that can cause a lethal disease of the integumentary system in lake sturgeon Acipenser fulvescens. As a group, the sNCLDV have not been assigned to any currently recognized taxonomic family of viruses. In this study, a dataset of NV DNA sequences was generated and assembled as two non-overlapping contigs of 306 and 448 base pairs (bp) and then used to conduct a comprehensive systematics analysis using Bayesian phylogenetic inference for NV, other sNCLDV, and representative members of six families of the NCLDV superfamily. The phylogeny of NV was reconstructed using protein homologues encoded by nine nucleocytoplasmic virus orthologous genes (NCVOGs): NCVOG0022—mcp, NCVOG0038—DNA polymerase B elongation subunit, NCVOG0076—VV A18-type helicase, NCVOG0249—VV A32-type ATPase, NCVOG0262—AL2 VLTF3-like transcription factor, NCVOG0271—RNA polymerase II subunit II, NCVOG0274—RNA polymerase II subunit I, NCVOG0276—ribonucleotide reductase small subunit, and NCVOG1117—mRNA capping enzyme. The accuracy of our phylogenetic method was evaluated using a combination of Bayesian statistical analysis and congruence analysis. Stable tree topologies were obtained with datasets differing in target molecule(s), sequence length, and taxa. Congruent topologies were obtained in phylogenies constructed using individual protein datasets and when four proteins were used in a concatenated approach. The major capsid protein phylogeny indicated that ten representative sNCLDV form a monophyletic group comprised of four lineages within a polyphyletic Mimi-Phycodnaviridae group of taxa. Overall, the analyses revealed that Namao virus is a member of the Mimiviridae family with strong and consistent support for a clade containing NV and CroV as sister taxa.

The diversity of life is shaped by rates of speciation and extinction, and so estimating these rates correctly is crucial for understanding diversity patterns among clades, regions, and habitats. In 2011, Morlon and collaborators developed a promising likelihood-based approach to estimate speciation and extinction and to infer the model describing how these rates change over time based on AICc. This approach is now implemented in an R package (RPANDA). Here, we test the accuracy of this approach under simulated conditions, to evaluate its ability to correctly estimate rates of speciation, extinction, and diversification (speciation—extinction) and to choose the correct underlying model of diversification (e.g. constant or changing rates of speciation and extinction over time). We found that this likelihood-based approach frequently picked the incorrect model. For example, with changing speciation rates over time, the correct model was chosen in only ∼10 per cent of replicates. There were significant relationships between true and estimated speciation rates using this approach, but relationships were weak when speciation rates were constant within clades. Relationships were consistently weak between true and estimated rates of extinction and of diversification. Overall, we suggest that results from this approach should be interpreted with considerable caution.

In recent years, several outbreaks of hepatitis C virus (HCV) infections have been observed among HIV-infected men who have sex with men (MSM) in Europe. In the Netherlands, high incidence rates of 10/1,000 person-years are reported. In this analysis, we describe whether acute HCV is linked to specific transmission networks. A total of 50 Dutch HIV-infected MSM, diagnosed with acute HCV genotype 1a between 2013 and 2014, were included. Target enrichment for viral nucleic acid separation and deep sequencing were used to recover whole HCV genomes. Phylogenetic trees were constructed by use of the maximum likelihood method. Pairwise distance matrices were generated by use of the Kimura-2 parameter distance estimation method. The consistency of the phylogenetic clustering was tested by bootstrap analysis with 1,000 replicates. A cluster was defined as having a genetic distance of at most 1.5 per cent and bootstrap values of 100 per cent. The most recent common ancestor was estimated with a coalescent-based model with a Bayesian statistical framework. Four transmission clusters were identified that included a total of 38 patients (76% of the total). The clusters were indicative of recent outbreaks, as highlighted by small genetic distances and a most recent common ancestor after the year 2000, when the first cases of HCV infection in HIV-infected MSM were reported. The HCV epidemic among HIV-infected MSM is a young epidemic, with most of the acute infections linked within the four major transmission networks. Prevention strategies identifying and targeting these transmission networks can potentially curb the epidemic.

The transitions study examines HIV risk among adolescent girls and young women through their sexual life course from first sex, to past and current engagement in casual sex, transactional sex, and, for some, formal sex work (FSW). Understanding the timing of HIV infection and the circumstances around early infection in young females is critical to HIV prevention interventions. We inferred time since HIV infection using next-generation sequencing (NGS) of the HIV pol gene isolated from cross-sectional samples among high-risk young women in Dnipro, Ukraine. Dried blood spots were collected on Whatman 903 cards from young women aged 14–24 engaged in casual sex (n = 894), transactional sex (n = 464), and FSW (n = 452). The HIV pol gene was sequenced using an in-house NGS HIV drug resistance mutation genotyping assay. Time since HIV infection was inferred using an online tool as described by Puller et al. (2017) freely available at https://hiv.biozentrum.unibas.ch/ETI/. The mean estimated time since HIV infection (ETI) for participants engaged in casual sex, transactional sex, and FSW is 1.98, 1.84, and 3.01 years, respectively. ETI was used to determine the duration of HIV infection for each participant and compared to the number of sexually active years prior to FSW. Among FSW, 61 per cent of participants were infected with HIV prior to entry into sex work. In general, ETI from NGS data suggests that FSWs were infected with HIV before entry into FSW. Expansion of targeted prevention programs beyond FSW could play an important role in mitigating HIV transmission at the population level.

Next-generation sequencing (NGS) produces comprehensive insights across the entire genome of the human cytomegalovirus (HCMV), which is an important opportunistic pathogen following hematopoietic stem cell transplantation (HSCT). To assess the clinical impact of HCMV diversity, genotype distribution, and resistance mutations, we performed NGS directly on plasma specimens from HSCT recipients with HCMV reactivation. Twenty-nine HCMV-positive plasma samples (median viral load 1.7 × 103 IU/ml) collected from a prospective allogenic HSCT recipient cohort (n = 16) between 21 and 80 days after transplantation were sequenced on an Illumina MiSeq after preparation of target-enriched sequencing libraries. Consensus HCMV genome sequences were assembled for 24 samples. The presence of multiple-strain infections and antiviral resistance mutations in genes UL54 and UL97 was determined by variant analysis. Genotype distribution was determined by specific marker analysis of several hypervariable genes (RL5A, RL6, RL12, RL13, UL1, UL9, UL11, UL73, UL74, UL120, UL146, and UL139). Associations between genomic and clinical features (e.g. graft-versus-host disease (GvHD), donor/recipient HCMV serostatus, dynamics of HCMV antigenemia, survival) were explored. Multiple infections involving up to 3 HCMV strains were detected in seven out of sixteen patients, with one patient analyzed at > 2 time points, showing a switch of the dominant HCMV population. No known antiviral resistance mutations were detected, which may be expected due to sample collection early after HSCT from patients without antiviral prophylaxis. Multiple-strain infection was associated with an earlier peak of HCMV-antigenemia (P = 0.054), but not with duration of viremia, antigenemia peak values, donor/recipient HCMV serostatus, T-cell depletion, acute or chronic GvHD, disease relapse, or reduced survival. Genotype distribution analysis revealed a potential link of one genotype of the immunomodulatory gene UL11 with GvHD incidence after HCMV reactivation. NGS of HCMV diversity directly from plasma samples, even with low viral loads, enables the acquisition of data of potential clinical interest. To identify reliable associations between clinical features and HCMV diversity, further patient cohorts with suitable sample sizes are required.

Hand, Foot, and Mouth Disease (HFMD) is a major public health issue in the Asia-Pacific region. Our research program aims to address unanswered questions about clinical, epidemiology, pathogen evolution, cost of illness, and host-genetic makers associated with severe HFMD in Vietnam. A multi-hospital-based observational study has been conducted at three referral hospitals in Ho Chi Minh City, Vietnam since 2013. Demographic, clinical data, and cost of illness were collected alongside clinical specimens. Multiplex PCR and next-generation sequencing were employed to identify enterovirus serotypes and to study pathogen evolution, respectively. A genome-wide association-based approach was used to explore genetic markers of disease severity. From 2013 to 2017, 2,191 HFMD patients were enrolled. More than twenty enterovirus serotypes were detected in 84.3 per cent of patients. EV-A71 was the major cause, accounting for 22 per cent of total number of cases, followed by CV-A6 (21%), CV-A16 (13%), and CV-A10 (8%). Interestingly, these four common enteroviruses replaced each other during the study period. EV-A71 and CV-A6 were the two most predominant viruses detected in 2013 and 2014. However, CV-A6 was replaced by CV-A16 and CV-A10 in 2015 and 2016, respectively. A total of 396 whole-genome sequences (EV-A71 (n = 200), CV-A6 (n = 98), CV-A10 (n = 66), and CV-A16 (n = 32)) were obtained. Phylogenetic analysis showed that EV-A71 subgenogroup B5 has replaced C4 in 2012, and, since then, B5 has continued to circulate predominantly, while C4 has been sporadically detected. All Vietnamese CV-A6 isolates belonged to genogroup A, which has caused large outbreaks of HFMD worldwide. Costs of illness varied between disease severities, ranging from $USD 244 [95% confidence interval (95% CI): 230–258] per patient for grade 2A (mild) to $USD 1984 (95% CI: 1,752–2,227) for grade 3 (severe). The genome-wide association study identified two genetic markers potentially associated with severe HFMD. The results highlight that active surveillance and understanding pathogen evolution are essential to inform public health in prioritizing the development of intervention strategies. Efforts to unravel the evolutionary process of Vietnamese CV-A10 and CV-A16 in relation to global strains are ongoing. An independent cohort is needed to replicate the preliminary findings of the genome-wide association study.

Bovine enteroviruses (BEV) are non-enveloped RNA viruses of the genus Enterovirus, family Picornaviridae, which are commonly found in cattle. They have been classified into two species, enterovirus E (EV-E) and enterovirus F (EV-F). The viruses were previously considered non-pathogenic, but recent evidences suggest their association with pathogenesis in cattle. BEV-like enteroviruses have also been increasingly isolated from a wide range of animals, such as sheep, goats, horses, geese, possum, and deer, from many countries. The isolation and characterization of novel enteroviruses expands the range of the genus. Our data show that both EV-E and EV-F are circulating in cattle in Thailand. The viruses have been detected in 35–67 per cent of dairy and meat cattle feces in Kanchanaburi Province. Recently, we retrieved EV-E isolates from cattle feces by virus isolation in Madin-Darby Bovine Kidney cells. Four virus isolates were subjected to whole-genome sequencing using Illumina next-generation sequencing. A phylogenetic analysis of VP1 capsid protein, which is used for virus genotyping, suggested that there are at least two EV-E genotypes circulating in cattle in the area of study. Two virus strains, closely related to EV-E1 with amino acid sequence identities >88 per cent were identified as EV-E1. The other two strains, closely related to EV-E2 with amino acid sequence identities < 85 per cent, were likely to constitute a new EV-E genotype separate from the existing EV-E2.