Next-generation sequencing reveals large connected networks of intra-host HCV variants

Widespread hepatitis C virus transmission network among people who inject drugs in Kenya

OBJECTIVES

Hepatitis C virus (HCV) disproportionately affects people who inject drugs (PWID) worldwide. Despite carrying a high HCV burden, little is known about transmission dynamics in low- and middle-income countries.

METHODS

We recruited PWID from Nairobi and coastal cities and towns of Mombasa, Kilifi, and Malindi in Kenya at needle and syringe programs. Next-generation sequencing data from HCV hypervariable region 1 were analyzed using Global Hepatitis Outbreak and Surveillance Technology to identify transmission clusters.

RESULTS

HCV strains belonged to genotype 1a (n = 64, 46.0%), 4a (n = 72, 51.8%) and mixed HCV/1a/4a (n = 3, 2.2%). HCV/1a was dominant (61.2%) in Nairobi, whereas HCV/4a was dominant in Malindi (85.7%) and Kilifi (60.9%), and both genotypes were evenly identified in Mombasa (45.3% for HCV/1a and 50.9% for HCV/4a). Global Hepatitis Outbreak and Surveillance Technology identified 11 transmission clusters involving 90 cases. Strains in the two largest clusters (n = 38 predominantly HCV/4a and n = 32 HCV/1a) were sampled from all four sites.

CONCLUSIONS

Transmission clusters involving 64.7% of cases indicate an effective sampling of major HCV strains circulating among PWID. Large clusters involving 77.8% of clustered strains from Nairobi and Coast suggest successful introduction of two ancestral HCV/1a and HCV/4a strains to PWID and the existence of a widespread transmission network in the country. The disruption of this network is essential for HCV elimination.

Antigenic cooperation in viral populations: Transformation of functions of intra-host viral variants

In this paper, we study intra-host viral adaptation by antigenic cooperation - a mechanism of immune escape that serves as an alternative to the standard mechanism of escape by continuous genomic diversification and allows to explain a number of experimental observations associated with the establishment of chronic infections by highly mutable viruses. Within this mechanism, the topology of a cross-immunoreactivity network forces intra-host viral variants to specialize for complementary roles and adapt to the host's immune response as a quasi-social ecosystem. Here we study dynamical changes in immune adaptation caused by evolutionary and epidemiological events. First, we show that the emergence of a viral variant with altered antigenic features may result in a rapid re-arrangement of the viral ecosystem and a change in the roles played by existing viral variants. In particular, it may push the population under immune escape by genomic diversification towards the stable state of adaptation by antigenic cooperation. Next, we study the effect of a viral transmission between two chronically infected hosts, which results in the merging of two intra-host viral populations in the state of stable immune-adapted equilibrium. In this case, we also describe how the newly formed viral population adapts to the host's environment by changing the functions of its members. The results are obtained analytically for minimal cross-immunoreactivity networks and numerically for larger populations.

Polyvalent immunization elicits a synergistic broadly neutralizing immune response to hypervariable region 1 variants of hepatitis C virus

A hepatitis C virus (HCV) vaccine is urgently needed. Vaccine development has been hindered by HCV's genetic diversity, particularly within the immunodominant hypervariable region 1 (HVR1). Here, we developed a strategy to elicit broadly neutralizing antibodies to HVR1, which had previously been considered infeasible. We first applied a unique information theory-based measure of genetic distance to evaluate phenotypic relatedness between HVR1 variants. These distances were used to model the structure of HVR1's sequence space, which was found to have five major clusters. Variants from each cluster were used to immunize mice individually, and as a pentavalent mixture. Sera obtained following immunization neutralized every variant in a diverse HCVpp panel (n = 10), including those resistant to monovalent immunization, and at higher mean titers (1/ID50 = 435) than a glycoprotein E2 (1/ID50 = 205) vaccine. This synergistic immune response offers a unique approach to overcoming antigenic variability and may be applicable to other highly mutable viruses.

Local Immunodeficiency: Combining Cross-Immunoreactivity Networks

This article continues the analysis of the recently observed phenomenon of local immunodeficiency (LI), which arises as a result of antigenic cooperation among intrahost viruses organized into a network of cross-immunoreactivity (CR). We study here what happens as the result of combining (connecting) the simplest CR networks, which have a stable state of LI. It turned out that many possibilities occur, particularly resulting in a change of roles of some viruses in the CR network. Our results also give some indications about a boundary of the set of CR networks with stable state of LI in the entire collection of all possible CR networks. Such borderline CR networks are characterized by only a marginally stable (neutral rather than stable) state of the LI, or by the existence of such subnetworks in a CR network that evolve independently of each other (although being connected).

Hepatitis C virus transmission cluster among injection drug users in Pakistan

Hepatitis C virus (HCV) infections are public health problem across the globe, particularly in developing countries. Pakistan has the second highest prevalence of HCV infection worldwide. Limited data exist from Pakistan about persons who inject drugs (PWID) and are at significant risk of exposure to HCV infection and transmission. Serum specimens (n = 110) collected from PWID residing in four provinces were tested for molecular markers of HCV infection. Next generation sequencing (NGS) of the hypervariable region (HVR1) of HCV and Global Hepatitis Outbreak and Surveillance Technology (GHOST) were used to determine HCV genotype, genetic heterogeneity, and construct transmission networks. Among tested specimens, 47.3% were found anti-HCV positive and 34.6% were HCV RNA-positive and belonged to four genotypes, with 3a most prevalent followed by 1a, 1b and 4a. Variants sampled from five cases formed phylogenetic cluster and a transmission network. One case harbored infection with two different genotypes. High prevalence of infections and presence of various genotypes indicate frequent introduction and transmission of HCV among PWID in Pakistan. Identification of a transmission cluster across three provinces, involving 20% of all cases, suggests the existence of a countrywide transmission network among PWIDs. Understanding the structure of this network should assist in devising effective public health strategies to eliminate HCV infection in Pakistan.

Polymorphic Molecular Signatures in Variable Regions of the Plasmodium falciparum var2csa DBL3x Domain Are Associated with Virulence in Placental Malaria

The Plasmodium falciparum protein VAR2CSA allows infected erythrocytes to accumulate within the placenta, inducing pathology and poor birth outcomes. Multiple exposures to placental malaria (PM) induce partial immunity against VAR2CSA, making it a promising vaccine candidate. However, the extent to which VAR2CSA genetic diversity contributes to immune evasion and virulence remains poorly understood. The deep sequencing of the var2csa DBL3X domain in placental blood from forty-nine primigravid and multigravid women living in malaria-endemic western Kenya revealed numerous unique sequences within individuals in association with chronic PM but not gravidity. Additional analysis unveiled four distinct sequence types that were variably present in mixed proportions amongst the study population. An analysis of the abundance of each of these sequence types revealed that one was inversely related to infant gestational age, another was inversely related to placental parasitemia, and a third was associated with chronic PM. The categorization of women according to the type to which their dominant sequence belonged resulted in the segregation of types as a function of gravidity: two types predominated in multigravidae whereas the other two predominated in primigravidae. The univariate logistic regression analysis of sequence type dominance further revealed that gravidity, maternal age, placental parasitemia, and hemozoin burden (within maternal leukocytes), reported a lack of antimalarial drug use, and infant gestational age and birth weight influenced the odds of membership in one or more of these sequence predominance groups. Cumulatively, these results show that unique var2csa sequences differentially appear in women with different PM exposure histories and segregate to types independently associated with maternal factors, infection parameters, and birth outcomes. The association of some var2csa sequence types with indicators of pathogenesis should motivate vaccine efforts to further identify and target VAR2CSA epitopes associated with maternal morbidity and poor birth outcomes.

Primary case inference in viral outbreaks through analysis of intra-host variant population

Background

Investigation of outbreaks to identify the primary case is crucial for the interruption and prevention of transmission of infectious diseases. These individuals may have a higher risk of participating in near future transmission events when compared to the other patients in the outbreak, so directing more transmission prevention resources towards these individuals is a priority. Although the genetic characterization of intra-host viral populations can aid the identification of transmission clusters, it is not trivial to determine the directionality of transmissions during outbreaks, owing to complexity of viral evolution. Here, we present a new computational framework, PYCIVO: primary case inference in viral outbreaks. This framework expands upon our earlier work in development of QUENTIN, which builds a probabilistic disease transmission tree based on simulation of evolution of intra-host hepatitis C virus (HCV) variants between cases involved in direct transmission during an outbreak. PYCIVO improves upon QUENTIN by also adding a custom heterogeneity index and identifying the scenario when the primary case may have not been sampled.

Results

These approaches were validated using a set of 105 sequence samples from 11 distinct HCV transmission clusters identified during outbreak investigations, in which the primary case was epidemiologically verified. Both models can detect the correct primary case in 9 out of 11 transmission clusters (81.8%). However, while QUENTIN issues erroneous predictions on the remaining 2 transmission clusters, PYCIVO issues a null output for these clusters, giving it an effective prediction accuracy of 100%. To further evaluate accuracy of the inference, we created 10 modified transmission clusters in which the primary case had been removed. In this scenario, PYCIVO was able to correctly identify that there was no primary case in 8/10 (80%) of these modified clusters. This model was validated with HCV; however, this approach may be applicable to other microbial pathogens.

Conclusions

PYCIVO improves upon QUENTIN by also implementing a custom heterogeneity index which empowers PYCIVO to make the important ‘No primary case’ prediction. One or more samples, possibly including the primary case, may have not been sampled, and this designation is meant to account for these scenarios.

Recovery of Recombinant Canine Distemper Virus That Expresses CPV-2a VP2: Uncovering the Mutation Profile of Recombinant Undergoing 50 Serial Passages In Vitro

Canine distemper and canine parvoviral enteritis are infections caused by the canine distemper virus (CDV) and canine parvovirus type 2 (CPV-2), respectively. They are two common infectious diseases that cause high morbidity and mortality in affected dogs. Combination vaccines have been broadly used to protect dogs from infections of CDV, CPV-2, and other viruses. VP2 is the most abundant protein of the CPV-2 capsid. It elicits potent immunity in animals and, therefore, is widely used for designing subunit antigen-based vaccines. In this study, we rescued a recombinant CDV (QN vaccine strain) using reverse genetics. The recombinant CDV (rCDV-VP2) was demonstrated to express stably the VP2 in cells for at least 33 serial passages in vitro. Unfortunately, a nonsense mutation was initially identified in the VP2 open reading frame (ORF) at passage-34 (P34) and gradually became predominant in rCDV-VP2 quasispecies with passaging. Neither test strip detection nor indirect immunofluorescence assay demonstrated the expression of the VP2 at P50. The P50 rCDV-VP2 was subjected to next-generation sequencing, which totally identified 17 single-nucleotide variations (SNVs), consisting of 11 transitions and 6 transversions. Out of the 17 SNVs, 1 and 9 were identified as nonsense and missense mutations, respectively. Since the nonsense mutation arose in the VP2 ORF as early as P34, an earlier rCDV-VP2 progeny should be selected for the vaccination of animals in future experiments.

Rescuing eGFP-Tagged Canine Distemper Virus for 40 Serial Passages Separately in Ribavirin- and Non-Treated Cells: Comparative Analysis of Viral Mutation Profiles

Due to lacking a proofreading mechanism in their RNA-dependent RNA polymerases (RdRp), RNA viruses generally possess high mutation frequencies, making them evolve rapidly to form viral quasispecies during serial passages in cells, especially treated with mutagens, like ribavirin. Canine distemper virus (CDV) belongs to the genus Morbillivirus. Its L protein functions as an RdRp during viral replication. In this study, a recombinant enhanced green fluorescence protein-tagged CDV (rCDV-eGFP) was rescued from its cDNA clone, followed by viral identification and characterization at passage-7 (P7). This recombinant was independently subjected to extra 40 serial passages (P8 to 47) in ribavirin- and non-treated cells. Two viral progenies, undergoing passages in ribavirin- and non-treated VDS cells, were named rCDV-eGFP-R and -N, respectively. Both progenies were simultaneously subjected to next-generation sequencing (NGS) at P47 for comparing their quasispecies diversities with each other. The rCDV-eGFP-R and -N showed 62 and 23 single-nucleotide mutations (SNMs) in individual antigenomes, respectively, suggesting that the ribavirin conferred a mutagenic effect on the rCDV-eGFP-R. The spectrum of 62 SNMs contained 26 missense and 36 silent mutations, and that of 23 SNMs was composed of 17 missense and 6 silent mutations. Neither the rCDV-eGFP-R nor -N exhibited nonsense mutation in individual antigenomes. We speculate that the rCDV-eGFP-R may contain at least one P47 sub-progeny characterized by high-fidelity replication in cells. If such a sub-progeny can be purified from the mutant swarm, its L protein would elucidate a molecular mechanism of CDV high-fidelity replication.

Next-generation sequencing studies on the E1-HVR1 region of hepatitis C virus (HCV) from non-high-risk HCV patients living in Punjab and Khyber Pakhtunkhwa, Pakistan

The incidence rate of hepatitis C virus (HCV) infection in Pakistan is very high. In this study, we evaluated the genetic heterogeneity of HCV hypervariable region 1 (HVR1) from the HCV-infected Pakistani population and compare the isolated genotypes with representative sequences from internationally diverse geographic regions. We also investigated potential transmission events in non-high-risk HCV patients. Next-generation sequencing (NGS) data from the E1-HVR1 region from 30 HCV patients were used for phylogenetic analysis. Reference sequences were retrieved from the Los Alamos HCV and GenBank databases. NGS data were analyzed to examine HCV HVR1 sequence diversity and identify transmission links among HCV-infected individuals using Global Hepatitis Outbreak and Surveillance Technology (GHOST). Phylogenetic analysis showed the predominance of HCV genotype 3a (86.6%), followed by 1a (6.6%), 1b (3.3%), and 3b (3.3%). NGS of HVR1 displayed significant genetic heterogeneity of HCV populations within each patient. The average nucleotide sequence diversity for HVR1 was 0.055. JR781281 was found to be the most diverse (0.14) of the specimens. Phylogenetic analysis demonstrated that all HCV specimens sequenced in this study were more similar to each other and showed variations from the representative sequences. The GHOST results suggested genetic relatedness between two (6.6%) HCV cases, possibly defining an incipient outbreak in a non-high-risk population. We urge rigorous countrywide investigation of outbreaks to identify transmission clusters and their sources to incorporate preventive measures for disease control.

Mutation Profiles of eGFP-Tagged Small Ruminant Morbillivirus During 45 Serial Passages in Ribavirin-Treated Cells

Small ruminant morbillivirus (SRMV), formerly known as peste-des-petits-ruminants virus, classified into the genus Morbillivirus in the family Paramyxoviridae. Its L protein functions as the RNA-dependent RNA polymerases (RdRp) during viral replication. Due to the absence of efficient proofreading activity in their RdRps, various RNA viruses reveal high mutation frequencies, making them evolve rapidly during serial passages in cells, especially treated with a certain mutagen, like ribavirin. We have previously rescued a recombinant enhanced green fluorescence protein-tagged SRMV (rSRMV-eGFP) using reverse genetics. In this study, the rSRMV-eGFP was subjected to serial passages in ribavirin-treated cells. Due to the ribavirin-exerted selective pressure, it was speculated that viral progenies would form quasispecies after dozens of passages. Viral progenies at passage-10, -20, -30, -40, and -50 were separately subjected to next-generation sequencing (NGS), consequently revealing a total of 34 single-nucleotide variations, including five synonymous, 21 missense, and one non-sense mutations. The L sequence was found to harbor eight missense mutations during serial passaging. It was speculated that at least one high-fidelity variant was present in viral quasispecies at passage-50. If purified from the population of viral progenies, this putative variant would contribute to clarifying a molecular mechanism in viral high-fidelity replication in vitro.

An Essential Function for Auxin in Embryo Development

Embryogenesis in seed plants is the process during which a single cell develops into a mature multicellular embryo that encloses all the modules and primary patterns necessary to build the architecture of the new plant after germination. This process involves a series of cell divisions and coordinated cell fate determinations resulting in the formation of an embryonic pattern with a shoot-root axis and cotyledon(s). The phytohormone auxin profoundly controls pattern formation during embryogenesis. Auxin functions in the embryo through its maxima/minima distribution, which acts as an instructive signal for tissue specification and organ initiation. In this review, we describe how disruptions of auxin biosynthesis, transport, and response severely affect embryo development. Also, the mechanism of auxin action in the development of the shoot-root axis and the three-tissue system is discussed with recent findings. Biological tools that can be implemented to study the auxin function during embryo development are presented, as they may be of interest to the reader.

A Phylogenetic Analysis of Hepatitis C Virus Transmission, Relapse, and Reinfection Among People Who Inject Drugs Receiving Opioid Agonist Therapy

BACKGROUND

Understanding hepatitis C virus (HCV) transmission among people who inject drugs (PWID) is essential for HCV elimination. We aimed to differentiate reinfections from treatment failures and to identify transmission linkages and associated factors in a cohort of PWID receiving opioid agonist therapy (OAT).

METHODS

We analyzed baseline and follow-up specimens from 150 PWID from 3 OAT clinics in the Bronx, New York. Next-generation sequencing data from the hypervariable region 1 of HCV were analyzed using Global Hepatitis Outbreak and Surveillance Technology.

RESULTS

There were 3 transmission linkages between study participants. Sustained virologic response (SVR) was not achieved in 9 participants: 7 had follow-up specimens with similar sequences to baseline, and 2 died. In 4 additional participants, SVR was achieved but the participants were viremic at later follow-up: 2 were reinfected with different strains, 1 had a late treatment failure, and 1 was transiently viremic 17 months after treatment. All transmission linkages were from the same OAT clinic and involved spousal or common-law partnerships.

CONCLUSION

This study highlights the use of next-generation sequencing as an important tool for identifying viral transmission and to help distinguish relapse and reinfection among PWID. Results reinforce the need for harm reduction interventions among couples and those who report ongoing risk factors after SVR.

Epidemiological data analysis of viral quasispecies in the next-generation sequencing era

The unprecedented coverage offered by next-generation sequencing (NGS) technology has facilitated the assessment of the population complexity of intra-host RNA viral populations at an unprecedented level of detail. Consequently, analysis of NGS datasets could be used to extract and infer crucial epidemiological and biomedical information on the levels of both infected individuals and susceptible populations, thus enabling the development of more effective prevention strategies and antiviral therapeutics. Such information includes drug resistance, infection stage, transmission clusters and structures of transmission networks. However, NGS data require sophisticated analysis dealing with millions of error-prone short reads per patient. Prior to the NGS era, epidemiological and phylogenetic analyses were geared toward Sanger sequencing technology; now, they must be redesigned to handle the large-scale NGS datasets and properly model the evolution of heterogeneous rapidly mutating viral populations. Additionally, dedicated epidemiological surveillance systems require big data analytics to handle millions of reads obtained from thousands of patients for rapid outbreak investigation and management. We survey bioinformatics tools analyzing NGS data for (i) characterization of intra-host viral population complexity including single nucleotide variant and haplotype calling; (ii) downstream epidemiological analysis and inference of drug-resistant mutations, age of infection and linkage between patients; and (iii) data collection and analytics in surveillance systems for fast response and control of outbreaks.

Quantitative differences between intra-host HCV populations from persons with recently established and persistent infections

Detection of incident hepatitis C virus (HCV) infections is crucial for identification of outbreaks and development of public health interventions. However, there is no single diagnostic assay for distinguishing recent and persistent HCV infections. HCV exists in each infected host as a heterogeneous population of genomic variants, whose evolutionary dynamics remain incompletely understood. Genetic analysis of such viral populations can be applied to the detection of incident HCV infections and used to understand intra-host viral evolution. We studied intra-host HCV populations sampled using next-generation sequencing from 98 recently and 256 persistently infected individuals. Genetic structure of the populations was evaluated using 245,878 viral sequences from these individuals and a set of selected features measuring their diversity, topological structure, complexity, strength of selection, epistasis, evolutionary dynamics, and physico-chemical properties. Distributions of the viral population features differ significantly between recent and persistent infections. A general increase in viral genetic diversity from recent to persistent infections is frequently accompanied by decline in genomic complexity and increase in structuredness of the HCV population, likely reflecting a high level of intra-host adaptation at later stages of infection. Using these findings, we developed a machine learning classifier for the infection staging, which yielded a detection accuracy of 95.22 per cent, thus providing a higher accuracy than other genomic-based models. The detection of a strong association between several HCV genetic factors and stages of infection suggests that intra-host HCV population develops in a complex but regular and predictable manner in the course of infection. The proposed models may serve as a foundation of cyber-molecular assays for staging infection, which could potentially complement and/or substitute standard laboratory assays.

Convex hulls in hamming space enable efficient search for similarity and clustering of genomic sequences

Background

In molecular epidemiology, comparison of intra-host viral variants among infected persons is frequently used for tracing transmissions in human population and detecting viral infection outbreaks. Application of Ultra-Deep Sequencing (UDS) immensely increases the sensitivity of transmission detection but brings considerable computational challenges when comparing all pairs of sequences. We developed a new population comparison method based on convex hulls in hamming space. We applied this method to a large set of UDS samples obtained from unrelated cases infected with hepatitis C virus (HCV) and compared its performance with three previously published methods.

Results

The convex hull in hamming space is a data structure that provides information on: (1) average hamming distance within the set, (2) average hamming distance between two sets; (3) closeness centrality of each sequence; and (4) lower and upper bound of all the pairwise distances among the members of two sets. This filtering strategy rapidly and correctly removes 96.2% of all pairwise HCV sample comparisons, outperforming all previous methods. The convex hull distance (CHD) algorithm showed variable performance depending on sequence heterogeneity of the studied populations in real and simulated datasets, suggesting the possibility of using clustering methods to improve the performance. To address this issue, we developed a new clustering algorithm, k-hulls, that reduces heterogeneity of the convex hull. This efficient algorithm is an extension of the k-means algorithm and can be used with any type of categorical data. It is 6.8-times more accurate than k-mode, a previously developed clustering algorithm for categorical data.

Conclusions

CHD is a fast and efficient filtering strategy for massively reducing the computational burden of pairwise comparison among large samples of sequences, and thus, aiding the calculation of transmission links among infected individuals using threshold-based methods. In addition, the convex hull efficiently obtains important summary metrics for intra-host viral populations.

Rescue of Senecavirus A to uncover mutation profiles of its progenies during 80 serial passages in vitro

Senecavirus A (SVA), also known as Seneca Valley virus, belongs to the genus Senecavirus in the family Picornaviridae. In this study, a China SVA isolate (CH-LX-01-2016) was rescued from its cDNA clone, and then identified by RT-PCR, indirect immunofluorescence assay and mass spectrometry. The rescued SVA could separately induce typical plaque formations and cytopathic effects in cell monolayers. In order to uncover its evolutionary dynamics, the SVA was subjected to eighty serial passages in vitro. Its progenies per ten passages were analyzed by next-generation sequencing (NGS). The NGS analyses showed that neither sequence-deleting nor -inserting phenotype was detectable in eight progenies, within which a total of forty-one intra-host single-nucleotide variations (SNVs) arose with passaging. Almost all SNVs were identified as the single-nucleotide polymorphism with mixture of two nucleotides. SNVs led to eighteen nonsynonymous mutations, out of which sixteen could directly reflect their own frequencies of amino acid mutation, due to only one SNV occurring in their individual codons. Compared with its parental virus without passaging, the passage-80 SVA progeny had formed a viral quasispecies, as evidenced by a total of twenty-eight SNVs identified in it.

Analysis of heterogeneous genomic samples using image normalization and machine learning

BACKGROUND

Analysis of heterogeneous populations such as viral quasispecies is one of the most challenging bioinformatics problems. Although machine learning models are becoming to be widely employed for analysis of sequence data from such populations, their straightforward application is impeded by multiple challenges associated with technological limitations and biases, difficulty of selection of relevant features and need to compare genomic datasets of different sizes and structures.

RESULTS

We propose a novel preprocessing approach to transform irregular genomic data into normalized image data. Such representation allows to restate the problems of classification and comparison of heterogeneous populations as image classification problems which can be solved using variety of available machine learning tools. We then apply the proposed approach to two important problems in molecular epidemiology: inference of viral infection stage and detection of viral transmission clusters using next-generation sequencing data. The infection staging method has been applied to HCV HVR1 samples collected from 108 recently and 257 chronically infected individuals. The SVM-based image classification approach achieved more than 95% accuracy for both recently and chronically HCV-infected individuals. Clustering has been performed on the data collected from 33 epidemiologically curated outbreaks, yielding more than 97% accuracy.

CONCLUSIONS

Sequence image normalization method allows for a robust conversion of genomic data into numerical data and overcomes several issues associated with employing machine learning methods to viral populations. Image data also help in the visualization of genomic data. Experimental results demonstrate that the proposed method can be successfully applied to different problems in molecular epidemiology and surveillance of viral diseases. Simple binary classifiers and clustering techniques applied to the image data are equally or more accurate than other models.

Reconstruction of clone- and haplotype-specific cancer genome karyotypes from bulk tumor samples

Many cancer genomes are extensively rearranged with aberrant chromosomal karyotypes. Deriving these karyotypes from high-throughput DNA sequencing of bulk tumor samples is complicated because most tumors are a heterogeneous mixture of normal cells and subpopulations of cancer cells, or clones, that harbor distinct somatic mutations. We introduce a new algorithm, Reconstructing Cancer Karyotypes (RCK), to reconstruct haplotype-specific karyotypes of one or more rearranged cancer genomes from DNA sequencing data from a bulk tumor sample. RCK leverages evolutionary constraints on the somatic mutational process in cancer to reduce ambiguity in the deconvolution of admixed sequencing data into multiple haplotype-specific cancer karyotypes. RCK models mixtures containing an arbitrary number of derived genomes and allows the incorporation of information both from short-read and long-read DNA sequencing technologies. We compare RCK to existing approaches on 17 primary and metastatic prostate cancer samples. We find that RCK infers cancer karyotypes that better explain the DNA sequencing data and conform to a reasonable evolutionary model. RCK's reconstructions of clone- and haplotype-specific karyotypes will aid further studies of the role of intra-tumor heterogeneity in cancer development and response to treatment. RCK is freely available as open source software.

Graph fractal dimension and the structure of fractal networks

Fractals are geometric objects that are self-similar at different scales and whose geometric dimensions differ from so-called fractal dimensions. Fractals describe complex continuous structures in nature. Although indications of self-similarity and fractality of complex networks has been previously observed, it is challenging to adapt the machinery from the theory of fractality of continuous objects to discrete objects such as networks. In this article, we identify and study fractal networks using the innate methods of graph theory and combinatorics. We establish analogues of topological (Lebesgue) and fractal (Hausdorff) dimensions for graphs and demonstrate that they are naturally related to known graph-theoretical characteristics: rank dimension and product dimension. Our approach reveals how self-similarity and fractality of a network are defined by a pattern of overlaps between densely connected network communities. It allows us to identify fractal graphs, explore the relations between graph fractality, graph colourings and graph descriptive complexity, and analyse the fractality of several classes of graphs and network models, as well as of a number of real-life networks. We demonstrate the application of our framework in evolutionary biology and virology by analysing networks of viral strains sampled at different stages of evolution inside their hosts. Our methodology revealed gradual self-organization of intra-host viral populations over the course of infection and their adaptation to the host environment. The obtained results lay a foundation for studying fractal properties of complex networks using combinatorial methods and algorithms.

Global transmission network of SARS-CoV-2: from outbreak to pandemic

Background

The COVID-19 pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is straining health systems around the world. Although the Chinese government implemented a number of severe restrictions on people's movement in an attempt to contain its local and international spread, the virus had already reached many areas of the world in part due to its potent transmissibility and the fact that a substantial fraction of infected individuals develop little or no symptoms at all. Following its emergence, the virus started to generate sustained transmission in neighboring countries in Asia, Western Europe, Australia, Canada and the United States, and finally in South America and Africa. As the virus continues its global spread, a clear and evidence-based understanding of properties and dynamics of the global transmission network of SARS-CoV-2 is essential to design and put in place efficient and globally coordinated interventions.

Methods

We employ molecular surveillance data of SARS-CoV-2 epidemics for inference and comprehensive analysis of its global transmission network before the pandemic declaration. Our goal was to characterize the spatial-temporal transmission pathways that led to the establishment of the pandemic. We exploited a network-based approach specifically tailored to emerging outbreak settings. Specifically, it traces the accumulation of mutations in viral genomic variants via mutation trees, which are then used to infer transmission networks, revealing an up-to-date picture of the spread of SARS-CoV-2 between and within countries and geographic regions.

Results and Conclusions

The analysis suggest multiple introductions of SARS-CoV-2 into the majority of world regions by means of heterogeneous transmission pathways. The transmission network is scale-free, with a few genomic variants responsible for the majority of possible transmissions. The network structure is in line with the available temporal information represented by sample collection times and suggest the expected sampling time difference of few days between potential transmission pairs. The inferred network structural properties, transmission clusters and pathways and virus introduction routes emphasize the extent of the global epidemiological linkage and demonstrate the importance of internationally coordinated public health measures.

HCV transmission in high-risk communities in Bulgaria

Background

The rate of HIV infection in Bulgaria is low. However, the rate of HCV-HIV-coinfection and HCV infection is high, especially among high-risk communities. The molecular epidemiology of those infections has not been studied before.

Methods

Consensus Sanger sequences of HVR1 and NS5B from 125 cases of HIV/HCV coinfections, collected during 2010–2014 in 15 different Bulgarian cities, were used for preliminary phylogenetic evaluation. Next-generation sequencing (NGS) data of the hypervariable region 1 (HVR1) analyzed via the Global Hepatitis Outbreak and Surveillance Technology (GHOST) were used to evaluate genetic heterogeneity and possible transmission linkages. Links between pairs that were below and above the established genetic distance threshold, indicative of transmission, were further examined by generating k-step networks.

Results

Preliminary genetic analyses showed predominance of HCV genotype 1a (54%), followed by 1b (20.8%), 2a (1.4%), 3a (22.3%) and 4a (1.4%), indicating ongoing transmission of many HCV strains of different genotypes. NGS of HVR1 from 72 cases showed significant genetic heterogeneity of intra-host HCV populations, with 5 cases being infected with 2 different genotypes or subtypes and 6 cases being infected with 2 strains of same subtype. GHOST revealed 8 transmission clusters involving 30 cases (41.7%), indicating a high rate of transmission.

Four transmission clusters were found in Sofia, three in Plovdiv, and one in Peshtera. The main risk factor for the clusters was injection drug use. Close genetic proximity among HCV strains from the 3 Sofia clusters, and between HCV strains from Peshtera and one of the two Plovdiv clusters confirms a long and extensive transmission history of these strains in Bulgaria.

Conclusions

Identification of several HCV genotypes and many HCV strains suggests a frequent introduction of HCV to the studied high-risk communities. GHOST detected a broad transmission network, which sustains circulation of several HCV strains since their early introduction in the 3 cities. This is the first report on the molecular epidemiology of HIV/HCV coinfections in Bulgaria.

Local immunodeficiency: Minimal networks and stability

Some basic aspects of the recently discovered phenomenon of local immunodeficiency (Skums et al. [1]) generated by antigenic cooperation in cross-immunoreactivity (CR) networks are investigated. We prove that local immunodeficiency (LI) that is stable under perturbations already occurs in very small networks and under general conditions on their parameters. Therefore our results are applicable not only to Hepatitis C where CR networks are known to be large (Skums et al. [1]), but also to other diseases with CR. A major necessary feature of such networks is the non-homogeneity of their topology. It is also shown that one can construct larger CR networks with stable LI by using small networks with stable LI as their building blocks. Our results imply that stable LI occurs in networks with quite general topology. In particular, the scale-free property of a CR network, assumed in Skums et al. [1], is not required.

Dynamic interactions between RNA viruses and human hosts unravelled by a decade of next generation sequencing

BACKGROUND

Next generation sequencing (NGS) methods have significantly contributed to a paradigm shift in genomic research for nearly a decade now. These methods have been useful in studying the dynamic interactions between RNA viruses and human hosts.

SCOPE OF THE REVIEW

In this review, we summarise and discuss key applications of NGS in studying the host - pathogen interactions in RNA viral infections of humans with examples.

MAJOR CONCLUSIONS

Use of NGS to study globally relevant RNA viral infections have revolutionized our understanding of the within host and between host evolution of these viruses. These methods have also been useful in clinical decision-making and in guiding biomedical research on vaccine design.

GENERAL SIGNIFICANCE

NGS has been instrumental in viral genomic studies in resolving within-host viral genomic variants and the distribution of nucleotide polymorphisms along the full-length of viral genomes in a high throughput, cost effective manner. In the future, novel advances such as long read, single molecule sequencing of viral genomes and simultaneous sequencing of host and pathogens may become the standard of practice in research and clinical settings. This will also bring on new challenges in big data analysis.

A large HCV transmission network enabled a fast-growing HIV outbreak in rural Indiana, 2015

Background

A high prevalence (92.3%) of hepatitis C virus (HCV) co-infection among HIV patients identified during a large HIV outbreak associated with injection of oxymorphone in Indiana prompted genetic analysis of HCV strains.

Methods

Molecular epidemiological analysis of HCV-positive samples included genotyping, sampling intra-host HVR1 variants by next-generation sequencing (NGS) and constructing transmission networks using Global Hepatitis Outbreak and Surveillance Technology (GHOST).

Findings

Results from the 492 samples indicate predominance of HCV genotypes 1a (72.2%) and 3a (20.4%), and existence of 2 major endemic NS5B clusters involving 49.8% of the sequenced strains. Among 76 HIV co-infected patients, 60.5% segregated into 2 endemic clusters. NGS analyses of 281 cases identified 826,917 unique HVR1 sequences and 51 cases of mixed subtype/genotype infections. GHOST mapped 23 transmission clusters. One large cluster (n = 130) included 50 cases infected with ≥2 subtypes/genotypes and 43 cases co-infected with HIV. Rapid strain replacement and superinfection with different strains were found among 7 of 12 cases who were followed up.

Interpretation

GHOST enabled mapping of HCV transmission networks among persons who inject drugs (PWID). Findings of numerous transmission clusters, mixed-genotype infections and rapid succession of infections with different HCV strains indicate a high rate of HCV spread. Co-localization of HIV co-infected patients in the major HCV clusters suggests that HIV dissemination was enabled by existing HCV transmission networks that likely perpetuated HCV in the community for years. Identification of transmission networks is an important step to guiding efficient public health interventions for preventing and interrupting HCV and HIV transmission among PWID.

Fund

US Centers for Disease Control and Prevention, and US state and local public health departments.

Genetic diversity of Hepatitis C Virus in Pakistan using Next Generation Sequencing

BACKGROUND

In Pakistan, HCV disease is considered a major public health issue with about 10-17 million people suffering with this infection and rate is increasing every day without any hindrance. The currently available Pyrosequencing approach used to analyze complex viral genomes as it can determine minor variants. It is crucial to understand viral evolution and quasispecies diversity in complex viral strains.

OBJECTIVES

To assess genetic diversity in patients with HCV using Next Generation Sequencing (NGS) and compare nucleotide diversity of genotype 3a with respect to other genotypes.

STUDY DESIGN

Intra-host viral diversity of HCV was determined using NGS from 13 chronically HCV infected individuals. NGS of three different regions (E2 (HVR1), NS3 and NS5B) of HCV-3a allowed for a comprehensive analysis of the viral population.

RESULT

Phylogenetic analysis of different HCV genes revealed great variability within the Pakistani population. The average nucleotide diversity for HVR1, NS3 and NS5B was 0.029, 0.011 and 0.010 respectively.

CONCLUSION

Our findings clearly indicate that patient-2 greater quasispecies heterogeneity than other patients of same genotype-3a using phylogenetic and one step network analyses. Initially phylogenetic analysis of these three genes showed that genotype 3a samples have greater genetic diversity. However, no significant difference was determined when nucleotide variability of genotype 3a compared with other genotypes (1a, 1b, 2a & 4a).

Ancient genomes revisit the ancestry of domestic and Przewalski’s horses

The Eneolithic Botai culture of the Central Asian steppes provides the earliest archaeological evidence for horse husbandry, ~5500 years ago, but the exact nature of early horse domestication remains controversial. We generated 42 ancient-horse genomes, including 20 from Botai. Compared to 46 published ancient- and modern-horse genomes, our data indicate that Przewalski’s horses are the feral descendants of horses herded at Botai and not truly wild horses. All domestic horses dated from ~4000 years ago to present only show ~2.7% of Botai-related ancestry. This indicates that a massive genomic turnover underpins the expansion of the horse stock that gave rise to modern domesticates, which coincides with large-scale human population expansions during the Early Bronze Age.

Inference of genetic relatedness between viral quasispecies from sequencing data

BACKGROUND

RNA viruses such as HCV and HIV mutate at extremely high rates, and as a result, they exist in infected hosts as populations of genetically related variants. Recent advances in sequencing technologies make possible to identify such populations at great depth. In particular, these technologies provide new opportunities for inference of relatedness between viral samples, identification of transmission clusters and sources of infection, which are crucial tasks for viral outbreaks investigations.

RESULTS

We present (i) an evolutionary simulation algorithm Viral Outbreak InferenCE (VOICE) inferring genetic relatedness, (ii) an algorithm MinDistB detecting possible transmission using minimal distances between intra-host viral populations and sizes of their relative borders, and (iii) a non-parametric recursive clustering algorithm Relatedness Depth (ReD) analyzing clusters' structure to infer possible transmissions and their directions. All proposed algorithms were validated using real sequencing data from HCV outbreaks.

CONCLUSIONS

All algorithms are applicable to the analysis of outbreaks of highly heterogeneous RNA viruses. Our experimental validation shows that they can successfully identify genetic relatedness between viral populations, as well as infer transmission clusters and outbreak sources.

Transmissibility of intra-host hepatitis C virus variants

Background

Intra-host hepatitis C virus (HCV) populations are genetically heterogeneous and organized in subpopulations. With the exception of blood transfusions, transmission of HCV occurs via a small number of genetic variants, the effect of which is frequently described as a bottleneck. Stochasticity of transmission associated with the bottleneck is usually used to explain genetic differences among HCV populations identified in the source and recipient cases, which may be further exacerbated by intra-host HCV evolution and differential biological capacity of HCV variants to successfully establish a population in a new host.

Results

Transmissibility was formulated as a property that can be measured from experimental Ultra-Deep Sequencing (UDS) data. The UDS data were obtained from one large hepatitis C outbreak involving an epidemiologically defined source and 18 recipient cases. k-Step networks of HCV variants were constructed and used to identify a potential association between transmissibility and network centrality of individual HCV variants from the source. An additional dataset obtained from nine other HCV outbreaks with known directionality of transmission was used for validation.

Transmissibility was not found to be dependent on high frequency of variants in the source, supporting the earlier observations of transmission of minority variants. Among all tested measures of centrality, the highest correlation of transmissibility was found with Hamming centrality (r = 0.720; p = 1.57 E-71). Correlation between genetic distances and differences in transmissibility among HCV variants from the source was found to be 0.3276 (Mantel Test, p = 9.99 E-5), indicating association between genetic proximity and transmissibility. A strong correlation ranging from 0.565–0.947 was observed between Hamming centrality and transmissibility in 7 of the 9 additional transmission clusters (p < 0.05).

Conclusions

Transmission is not an exclusively stochastic process. Transmissibility, as formally measured in this study, is associated with certain biological properties that also define location of variants in the genetic space occupied by the HCV strain from the source. The measure may also be applicable to other highly heterogeneous viruses. Besides improving accuracy of outbreak investigations, this finding helps with the understanding of molecular mechanisms contributing to establishment of chronic HCV infection.

Efficient detection of viral transmissions with Next-Generation Sequencing data

BACKGROUND

Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections associated with unsafe injection practices, drug diversion, and other exposures to blood are difficult to detect and investigate. Molecular analysis has been frequently used in the study of HCV outbreaks and transmission chains; helping identify a cluster of sequences as linked by transmission if their genetic distances are below a previously defined threshold. However, HCV exists as a population of numerous variants in each infected individual and it has been observed that minority variants in the source are often the ones responsible for transmission, a situation that precludes the use of a single sequence per individual because many such transmissions would be missed. The use of Next-Generation Sequencing immensely increases the sensitivity of transmission detection but brings a considerable computational challenge because all sequences need to be compared among all pairs of samples.

METHODS

We developed a three-step strategy that filters pairs of samples according to different criteria: (i) a k-mer bloom filter, (ii) a Levenhstein filter and (iii) a filter of identical sequences. We applied these three filters on a set of samples that cover the spectrum of genetic relationships among HCV cases, from being part of the same transmission cluster, to belonging to different subtypes.

RESULTS

Our three-step filtering strategy rapidly removes 85.1% of all the pairwise sample comparisons and 91.0% of all pairwise sequence comparisons, accurately establishing which pairs of HCV samples are below the relatedness threshold.

CONCLUSIONS

We present a fast and efficient three-step filtering strategy that removes most sequence comparisons and accurately establishes transmission links of any threshold-based method. This highly efficient workflow will allow a faster response and molecular detection capacity, improving the rate of detection of viral transmissions with molecular data.

Increased Mitochondrial Genetic Diversity in Persons Infected With Hepatitis C Virus

BACKGROUND & AIMS

The host genetic environment contributes significantly to the outcomes of hepatitis C virus (HCV) infection and therapy response, but little is known about any effects of HCV infection on the host beyond any changes related to adaptive immune responses. HCV persistence is associated strongly with mitochondrial dysfunction, with liver mitochondrial DNA (mtDNA) genetic diversity linked to disease progression.

METHODS

We evaluated the genetic diversity of 2 mtDNA genomic regions (hypervariable segments 1 and 2) obtained from sera of 116 persons using next-generation sequencing.

RESULTS

Results were as follows: (1) the average diversity among cases with seronegative acute HCV infection was 4.2 times higher than among uninfected controls; (2) the diversity level among cases with chronic HCV infection was 96.1 times higher than among uninfected controls; and (3) the diversity was 23.1 times higher among chronic than acute cases. In 2 patients who were followed up during combined interferon and ribavirin therapy, mtDNA nucleotide diversity decreased dramatically after the completion of therapy in both patients: by 100% in patient A after 54 days and by 70.51% in patient B after 76 days.

CONCLUSIONS

HCV infection strongly affects mtDNA genetic diversity. A rapid decrease in mtDNA genetic diversity observed after therapy-induced HCV clearance suggests that the effect is reversible, emphasizing dynamic genetic relationships between HCV and mitochondria. The level of mtDNA nucleotide diversity can be used to discriminate recent from past infections, which should facilitate the detection of recent transmission events and thus help identify modes of transmission.

Hepatitis C virus whole genome sequencing: Current methods/issues and future challenges

Therapy for hepatitis C is currently undergoing a revolution. The arrival of new antiviral agents targeting viral proteins reinforces the need for a better knowledge of the viral strains infecting each patient. Hepatitis C virus (HCV) whole genome sequencing provides essential information for precise typing, study of the viral natural history or identification of resistance-associated variants. First performed with Sanger sequencing, the arrival of next-generation sequencing (NGS) has simplified the technical process and provided more detailed data on the nature and evolution of viral quasi-species. We will review the different techniques used for HCV complete genome sequencing and their applications, both before and after the apparition of NGS. The progress brought by new and future technologies will also be discussed, as well as the remaining difficulties, largely due to the genomic variability.

TCR gene-modified T cells can efficiently treat established hepatitis C-associated hepatocellular carcinoma tumors

The success in recent clinical trials using T cell receptor (TCR)-genetically engineered T cells to treat melanoma has encouraged the use of this approach toward other malignancies and viral infections. Although hepatitis C virus (HCV) infection is being treated with a new set of successful direct anti-viral agents, potential for virologic breakthrough or relapse by immune escape variants remains. Additionally, many HCV+ patients have HCV-associated disease, including hepatocellular carcinoma (HCC), which does not respond to these novel drugs. Further exploration of other approaches to address HCV infection and its associated disease are highly warranted. Here, we demonstrate the therapeutic potential of PBL-derived T cells genetically engineered with a high-affinity, HLA-A2-restricted, HCV NS3:1406-1415-reactive TCR. HCV1406 TCR-transduced T cells can recognize naturally processed antigen and elicit CD8-independent recognition of both peptide-loaded targets and HCV+ human HCC cell lines. Furthermore, these cells can mediate regression of established HCV+ HCC in vivo. Our results suggest that HCV TCR-engineered antigen-reactive T cells may be a plausible immunotherapy option to treat HCV-associated malignancies, such as HCC.

Next Generation Sequencing-Based Investigation of Potential Patient-to-Patient Hepatitis C Virus Transmission during Hemodialytic Treatment

We investigated potential patient-to-patient transmission of hepatitis C virus (HCV) in two hemodialysis centers in Beijing, China. Approximately 8.25% (32/388) hemodialysis patients were HCV antibody positive, and 4.90% (19/388) were HCV RNA-positive, which consisted of 2a genotype (1/19) and 1b genotypes (18/19). Using next generation sequencing (NGS) approach, MiSeq platform, we sequenced HCV, targeting hypervariable region 1 (263 base-pairs) of genotype 1b specimens and obtained 18 to 243 unique HCV variants. Analysis of phylogenetic tree, viral epidemiology signature pattern (VESP) and Shannon entropy indicated no obvious HCV similarity for most HCV infections but limited HCV variants from Patient 31 (P31) were closer with respect to evolutionary relationship with Patient 24 (P24). However, it was unlikely that HCV was transmitted directly from P24 to P31 in the hemodialysis center. Otherwise, their genetic distance (3.92%-8.92%), would have been much less. Moreover, P31 was infected less than two years before specimen collection, and other external high risk factors existed for these two patients. Thus, our data indicated no evidence of patient-to-patient transmission of HCV in the two hemodialysis centers, suggesting that current HCV infection control measures are effective.

Founder-cell-specific transcription of the DORNRÖSCHEN-LIKE promoter and integration of the auxin response

Transcription of the DORNRÖSCHEN (DRNL) promoter marks lateral-organ founder cells throughout Arabidopsis development, from cotyledons to flowers or floral organs. In the inflorescence apex, DRNL::GFP depicts incipient floral phyllotaxy, and organs in the four floral whorls are differentially prepatterned: the sepals unidirectionally along an abaxial-adaxial axis, the four petals and two lateral stamens in two putative morphogenetic fields, and the medial stamens subsequently in a ring-shaped domain, before two groups of carpel founder cells are specified. The dynamic DRNL transcription pattern is controlled by three enhancer elements, which redundantly and synergistically control qualitative or quantitative aspects of expression, and differentially integrate the auxin response in Arabidopsis inflorescence and floral meristems. The high sequence conservation of all three enhancer elements among the Brassicaceae is striking, which suggests that densely packed cis-regulatory elements are conserved to recruit multiple transcription factors, including auxin response factors, into higher-order enhanceosome complexes. The spatial organization of the enhancers is also conserved, by a microsynteny that extends beyond the Brassicaceae, which relates to enhancer sharing, as the distal element En1 bidirectionally serves DRNL and the upstream At1g24600 gene; the genes are transcribed in opposite directions and possibly comprise a conserved functional chromatin domain.

Network Analysis of the Chronic Hepatitis C Virome Defines Hypervariable Region 1 Evolutionary Phenotypes in the Context of Humoral Immune Responses

Hypervariable region 1 (HVR1) of hepatitis C virus (HCV) comprises the first 27 N-terminal amino acid residues of E2. It is classically seen as the most heterogeneous region of the HCV genome. In this study, we assessed HVR1 evolution by using ultradeep pyrosequencing for a cohort of treatment-naive, chronically infected patients over a short, 16-week period. Organization of the sequence set into connected components that represented single nucleotide substitution events revealed a network dominated by highly connected, centrally positioned master sequences. HVR1 phenotypes were observed to be under strong purifying (stationary) and strong positive (antigenic drift) selection pressures, which were coincident with advancing patient age and cirrhosis of the liver. It followed that stationary viromes were dominated by a single HVR1 variant surrounded by minor variants comprised from conservative single amino acid substitution events. We present evidence to suggest that neutralization antibody efficacy was diminished for stationary-virome HVR1 variants. Our results identify the HVR1 network structure during chronic infection as the preferential dominance of a single variant within a narrow sequence space.

IMPORTANCE

HCV infection is often asymptomatic, and chronic infection is generally well established in advance of initial diagnosis and subsequent treatment. HVR1 can undergo rapid sequence evolution during acute infection, and the variant pool is typically seen to diverge away from ancestral sequences as infection progresses from the acute to the chronic phase. In this report, we describe HVR1 viromes in chronically infected patients that are defined by a dominant epitope located centrally within a narrow variant pool. Our findings suggest that weakened humoral immune activity, as a consequence of persistent chronic infection, allows for the acquisition and maintenance of host-specific adaptive mutations at HVR1 that reflect virus fitness.

Accurate Genetic Detection of Hepatitis C Virus Transmissions in Outbreak Settings

Hepatitis C is a major public health problem in the United States and worldwide. Outbreaks of hepatitis C virus (HCV) infections are associated with unsafe injection practices, drug diversion, and other exposures to blood and are difficult to detect and investigate. Here, we developed and validated a simple approach for molecular detection of HCV transmissions in outbreak settings. We obtained sequences from the HCV hypervariable region 1 (HVR1), using end-point limiting-dilution (EPLD) technique, from 127 cases involved in 32 epidemiologically defined HCV outbreaks and 193 individuals with unrelated HCV strains. We compared several types of genetic distances and calculated a threshold, using minimal Hamming distances, that identifies transmission clusters in all tested outbreaks with 100% accuracy. The approach was also validated on sequences obtained using next-generation sequencing from HCV strains recovered from 239 individuals, and findings showed the same accuracy as that for EPLD. On average, the nucleotide diversity of the intrahost population was 6.2 times greater in the source case than in any incident case, allowing the correct detection of transmission direction in 8 outbreaks for which source cases were known. A simple and accurate distance-based approach developed here for detecting HCV transmissions streamlines molecular investigation of outbreaks, thus improving the public health capacity for rapid and effective control of hepatitis C.

Spatiotemporal Reconstruction of the Introduction of Hepatitis C Virus into Scotland and Its Subsequent Regional Transmission

A more comprehensive understanding of hepatitis C virus (HCV) transmission dynamics could facilitate public health initiatives to reduce the prevalence of HCV in people who inject drugs. We aimed to determine how HCV sequences entered and spread throughout Scotland and to identify transmission hot spots. A Scottish data set with embedded demographic data was created by sequencing the NS5B of 125 genotype 1a (Gt1a) samples and 166 Gt3a samples and analyzed alongside sequences from public databases. Applying Bayesian inference methods, we reconstructed the global origin and local spatiotemporal dissemination of HCV in Scotland. Scottish sequences mainly formed discrete clusters interspersed between sequences from the rest of the world; the most recent common ancestors of these clusters dated to 1942 to 1952 (Gt1a) and 1926 to 1942 (Gt3a), coincident with global diversification and distribution. Extant Scottish sequences originated in Edinburgh (Gt1a) and Glasgow (Gt3a) in the 1970s, but both genotypes spread from Glasgow to other regions. The dominant Gt1a strain differed between Edinburgh (cluster 2 [C2]), Glasgow (C3), and Aberdeen (C4), whereas significant Gt3a strain specificity occurred only in Aberdeen. Specific clusters initially formed separate transmission zones in Glasgow that subsequently overlapped, occasioning city-wide cocirculation. Transmission hot spots were detected with 45% of samples from patients residing in just 9 of Glasgow's 57 postcode districts. HCV was introduced into Scotland in the 1940s, concomitant with its worldwide dispersal likely arising from global-scale historical events. Cluster-specific transmission hubs were identified in Glasgow, the key Scottish city implicated in HCV dissemination. This fine-scale spatiotemporal reconstruction improves understanding of HCV transmission dynamics in Scotland.

IMPORTANCE

HCV is a major health burden and the leading cause of hepatocellular carcinoma. Public health needle exchange and "treatment as prevention" strategies targeting HCV are designed to reduce prevalence of the virus in people who inject drugs (PWID), potentially mitigating the future burden of HCV-associated liver disease. Understanding HCV transmission dynamics could increase the effectiveness of such public health initiatives by identifying and targeting regions playing a central role in virus dispersal. In this study, we examined HCV transmission in Scotland by analyzing the genetic relatedness of strains from PWID alongside data inferring the year individuals became infected and residential information at a geographically finer-scale resolution than in previous studies. Clusters of Scotland-specific strains were identified with regional specificity, and mapping the spread of HCV allowed the identification of key areas central to HCV transmission in Scotland. This research provides a basis for identifying HCV transmission hot spots.

Antigenic cooperation among intrahost HCV variants organized into a complex network of cross-immunoreactivity

Hepatitis C virus (HCV) has the propensity to cause chronic infection. Continuous immune escape has been proposed as a mechanism of intrahost viral evolution contributing to HCV persistence. Although the pronounced genetic diversity of intrahost HCV populations supports this hypothesis, recent observations of long-term persistence of individual HCV variants, negative selection increase, and complex dynamics of viral subpopulations during infection as well as broad cross-immunoreactivity (CR) among variants are inconsistent with the immune-escape hypothesis. Here, we present a mathematical model of intrahost viral population dynamics under the condition of a complex CR network (CRN) of viral variants and examine the contribution of CR to establishing persistent HCV infection. The model suggests a mechanism of viral adaptation by antigenic cooperation (AC), with immune responses against one variant protecting other variants. AC reduces the capacity of the host's immune system to neutralize certain viral variants. CRN structure determines specific roles for each viral variant in host adaptation, with variants eliciting broad-CR antibodies facilitating persistence of other variants immunoreacting with these antibodies. The proposed mechanism is supported by empirical observations of intrahost HCV evolution. Interference with AC is a potential strategy for interruption and prevention of chronic HCV infection.

From benchtop to desktop: important considerations when designing amplicon sequencing workflows

Amplicon sequencing has been the method of choice in many high-throughput DNA sequencing (HTS) applications. To date there has been a heavy focus on the means by which to analyse the burgeoning amount of data afforded by HTS. In contrast, there has been a distinct lack of attention paid to considerations surrounding the importance of sample preparation and the fidelity of library generation. No amount of high-end bioinformatics can compensate for poorly prepared samples and it is therefore imperative that careful attention is given to sample preparation and library generation within workflows, especially those involving multiple PCR steps. This paper redresses this imbalance by focusing on aspects pertaining to the benchtop within typical amplicon workflows: sample screening, the target region, and library generation. Empirical data is provided to illustrate the scope of the problem. Lastly, the impact of various data analysis parameters is also investigated in the context of how the data was initially generated. It is hoped this paper may serve to highlight the importance of pre-analysis workflows in achieving meaningful, future-proof data that can be analysed appropriately. As amplicon sequencing gains traction in a variety of diagnostic applications from forensics to environmental DNA (eDNA) it is paramount workflows and analytics are both fit for purpose.

Interferon alpha (IFNα)-induced TRIM22 interrupts HCV replication by ubiquitinating NS5A

TRIM22, a tripartite-motif (TRIM) protein, is upregulated upon interferon alpha (IFNα) administration to hepatitis C virus (HCV)-infected patients. However, the physiological role of TRIM22 upregulation remains unclear. Here, we describe a potential antiviral function of TRIM22's targeting of the HCV NS5A protein. NS5A is important for HCV replication and for resistance to IFNα therapy. During the first 24 h following the initiation of IFNα treatment, upregulation of TRIM22 in the peripheral blood mononuclear cells (PBMCs) of HCV patients correlated with a decrease in viral titer. This phenomenon was confirmed in the hepatocyte-derived cell line Huh-7, which is highly permissive for HCV infection. TRIM22 over-expression inhibited HCV replication, and Small interfering RNA (siRNA)-mediated knockdown of TRIM22 diminished IFNα-induced anti-HCV function. Furthermore, we determined that TRIM22 ubiquitinates NS5A in a concentration-dependent manner. In summary, our results suggest that TRIM22 upregulation is associated with HCV decline during IFNα treatment and plays an important role in controlling HCV replication in vitro.

Computational framework for next-generation sequencing of heterogeneous viral populations using combinatorial pooling

MOTIVATION

Next-generation sequencing (NGS) allows for analyzing a large number of viral sequences from infected patients, providing an opportunity to implement large-scale molecular surveillance of viral diseases. However, despite improvements in technology, traditional protocols for NGS of large numbers of samples are still highly cost and labor intensive. One of the possible cost-effective alternatives is combinatorial pooling. Although a number of pooling strategies for consensus sequencing of DNA samples and detection of SNPs have been proposed, these strategies cannot be applied to sequencing of highly heterogeneous viral populations.

RESULTS

We developed a cost-effective and reliable protocol for sequencing of viral samples, that combines NGS using barcoding and combinatorial pooling and a computational framework including algorithms for optimal virus-specific pools design and deconvolution of individual samples from sequenced pools. Evaluation of the framework on experimental and simulated data for hepatitis C virus showed that it substantially reduces the sequencing costs and allows deconvolution of viral populations with a high accuracy.

AVAILABILITY AND IMPLEMENTATION

The source code and experimental data sets are available at http://alan.cs.gsu.edu/NGS/?q=content/pooling.