Last data update: Apr 29, 2024. (Total: 46658 publications since 2009)
Records 1-9 (of 9 Records) |
Query Trace: Knyazev S[original query] |
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High HIV diversity, recombination, and superinfection revealed in a large outbreak among persons who inject drugs in Kentucky and Ohio, USA
Switzer WM , Shankar A , Jia H , Knyazev S , Ambrosio F , Kelly R , Zheng H , Campbell EM , Cintron R , Pan Y , Saduvala N , Panneer N , Richman R , Singh MB , Thoroughman DA , Blau EF , Khalil GM , Lyss S , Heneine W . Virus Evol 2024 10 (1) veae015 We investigated transmission dynamics of a large human immunodeficiency virus (HIV) outbreak among persons who inject drugs (PWID) in KY and OH during 2017-20 by using detailed phylogenetic, network, recombination, and cluster dating analyses. Using polymerase (pol) sequences from 193 people associated with the investigation, we document high HIV-1 diversity, including Subtype B (44.6 per cent); numerous circulating recombinant forms (CRFs) including CRF02_AG (2.5 per cent) and CRF02_AG-like (21.8 per cent); and many unique recombinant forms composed of CRFs with major subtypes and sub-subtypes [CRF02_AG/B (24.3 per cent), B/CRF02_AG/B (0.5 per cent), and A6/D/B (6.4 per cent)]. Cluster analysis of sequences using a 1.5 per cent genetic distance identified thirteen clusters, including a seventy-five-member cluster composed of CRF02_AG-like and CRF02_AG/B, an eighteen-member CRF02_AG/B cluster, Subtype B clusters of sizes ranging from two to twenty-three, and a nine-member A6/D and A6/D/B cluster. Recombination and phylogenetic analyses identified CRF02_AG/B variants with ten unique breakpoints likely originating from Subtype B and CRF02_AG-like viruses in the largest clusters. The addition of contact tracing results from OH to the genetic networks identified linkage between persons with Subtype B, CRF02_AG, and CRF02_AG/B sequences in the clusters supporting de novo recombinant generation. Superinfection prevalence was 13.3 per cent (8/60) in persons with multiple specimens and included infection with B and CRF02_AG; B and CRF02_AG/B; or B and A6/D/B. In addition to the presence of multiple, distinct molecular clusters associated with this outbreak, cluster dating inferred transmission associated with the largest molecular cluster occurred as early as 2006, with high transmission rates during 2017-8 in certain other molecular clusters. This outbreak among PWID in KY and OH was likely driven by rapid transmission of multiple HIV-1 variants including de novo viral recombinants from circulating viruses within the community. Our findings documenting the high HIV-1 transmission rate and clustering through partner services and molecular clusters emphasize the importance of leveraging multiple different data sources and analyses, including those from disease intervention specialist investigations, to better understand outbreak dynamics and interrupt HIV spread. |
MicrobeTrace: Retooling Molecular Epidemiology for Rapid Public Health Response (preprint)
Campbell EM , Boyles A , Shankar A , Kim J , Knyazev S , Switzer WM . bioRxiv 2020 2020.07.22.216275 Motivation Outbreak investigations use data from interviews, healthcare providers, laboratories and surveillance systems. However, integrated use of data from multiple sources requires a patchwork of software that present challenges in usability, interoperability, confidentiality, and cost. Rapid integration, visualization and analysis of data from multiple sources can guide effective public health interventions.Results We developed MicrobeTrace to facilitate rapid public health responses by overcoming barriers to data integration and exploration in molecular epidemiology. Using publicly available HIV sequences and other data, we demonstrate the analysis of viral genetic distance networks and introduce a novel approach to minimum spanning trees that simplifies results. We also illustrate the potential utility of MicrobeTrace in support of contact tracing by analyzing and displaying data from an outbreak of SARS-CoV-2 in South Korea in early 2020.Availability and Implementation MicrobeTrace is a web-based, client-side, JavaScript application (https://microbetrace.cdc.gov) that runs in Chromium-based browsers and remains fully-operational without an internet connection. MicrobeTrace is developed and actively maintained by the Centers for Disease Control and Prevention. The source code is available at https://github.com/cdcgov/microbetrace.Contact ells{at}cdc.govCompeting Interest StatementThe authors have declared no competing interest. |
CliqueSNV: Scalable Reconstruction of Intra-Host Viral Populations from NGS Reads (preprint)
Knyazev S , Tsyvina V , Melnyk A , Artyomenko A , Malygina T , Porozov YB , Campbell EM , Switzer WM , Skums P , Zelikovsky A . bioRxiv 2019 264242 Highly mutable RNA viruses such as influenza A virus, human immunodeficiency virus and hepatitis C virus exist in infected hosts as highly heterogeneous populations of closely related genomic variants. The presence of low-frequency variants with few mutations with respect to major strains may result in an immune escape, emergence of drug resistance, and an increase of virulence and infectivity. Next-generation sequencing technologies permit detection of sample intra-host viral population at extremely great depth, thus providing an opportunity to access low-frequency variants. Long read lengths offered by single-molecule sequencing technologies allow all viral variants to be sequenced in a single pass. However, high sequencing error rates limit the ability to study heterogeneous viral populations composed of rare, closely related variants.In this article, we present CliqueSNV, a novel reference-based method for reconstruction of viral variants from NGS data. It efficiently constructs an allele graph based on linkage between single nucleotide variations and identifies true viral variants by merging cliques of that graph using combinatorial optimization techniques. The new method outperforms existing methods in both accuracy and running time on experimental and simulated NGS data for titrated levels of known viral variants. For PacBio reads, it accurately reconstructs variants with frequency as low as 0.1%. For Illumina reads, it fully reconstructs main variants. The open source implementation of CliqueSNV is freely available for download at https://github.com/vyacheslav-tsivina/CliqueSNV |
MicrobeTrace: Retooling molecular epidemiology for rapid public health response.
Campbell EM , Boyles A , Shankar A , Kim J , Knyazev S , Cintron R , Switzer WM . PLoS Comput Biol 2021 17 (9) e1009300 Outbreak investigations use data from interviews, healthcare providers, laboratories and surveillance systems. However, integrated use of data from multiple sources requires a patchwork of software that present challenges in usability, interoperability, confidentiality, and cost. Rapid integration, visualization and analysis of data from multiple sources can guide effective public health interventions. We developed MicrobeTrace to facilitate rapid public health responses by overcoming barriers to data integration and exploration in molecular epidemiology. MicrobeTrace is a web-based, client-side, JavaScript application (https://microbetrace.cdc.gov) that runs in Chromium-based browsers and remains fully operational without an internet connection. Using publicly available data, we demonstrate the analysis of viral genetic distance networks and introduce a novel approach to minimum spanning trees that simplifies results. We also illustrate the potential utility of MicrobeTrace in support of contact tracing by analyzing and displaying data from an outbreak of SARS-CoV-2 in South Korea in early 2020. MicrobeTrace is developed and actively maintained by the Centers for Disease Control and Prevention. Users can email microbetrace@cdc.gov for support. The source code is available at https://github.com/cdcgov/microbetrace. |
Accurate assembly of minority viral haplotypes from next-generation sequencing through efficient noise reduction.
Knyazev S , Tsyvina V , Shankar A , Melnyk A , Artyomenko A , Malygina T , Porozov YB , Campbell EM , Switzer WM , Skums P , Mangul S , Zelikovsky A . Nucleic Acids Res 2021 49 (17) e102 Rapidly evolving RNA viruses continuously produce minority haplotypes that can become dominant if they are drug-resistant or can better evade the immune system. Therefore, early detection and identification of minority viral haplotypes may help to promptly adjust the patient's treatment plan preventing potential disease complications. Minority haplotypes can be identified using next-generation sequencing, but sequencing noise hinders accurate identification. The elimination of sequencing noise is a non-trivial task that still remains open. Here we propose CliqueSNV based on extracting pairs of statistically linked mutations from noisy reads. This effectively reduces sequencing noise and enables identifying minority haplotypes with the frequency below the sequencing error rate. We comparatively assess the performance of CliqueSNV using an in vitro mixture of nine haplotypes that were derived from the mutation profile of an existing HIV patient. We show that CliqueSNV can accurately assemble viral haplotypes with frequencies as low as 0.1% and maintains consistent performance across short and long bases sequencing platforms. |
Molecular Epidemiological Analysis of the Origin and Transmission Dynamics of the HIV-1 CRF01_AE Sub-Epidemic in Bulgaria.
Alexiev I , Campbell EM , Knyazev S , Pan Y , Grigorova L , Dimitrova R , Partsuneva A , Gancheva A , Kostadinova A , Seguin-Devaux C , Elenkov I , Yancheva N , Switzer WM . Viruses 2021 13 (1) HIV-1 subtype CRF01_AE is the second most predominant strain in Bulgaria, yet little is known about the molecular epidemiology of its origin and transmissibility. We used a phylodynamics approach to better understand this sub-epidemic by analyzing 270 HIV-1 polymerase (pol) sequences collected from persons diagnosed with HIV/AIDS between 1995 and 2019. Using network analyses at a 1.5% genetic distance threshold (d), we found a large 154-member outbreak cluster composed mostly of persons who inject drugs (PWID) that were predominantly men. At d = 0.5%, which was used to identify more recent transmission, the large cluster dissociated into three clusters of 18, 12, and 7 members, respectively, five dyads, and 107 singletons. Phylogenetic analysis of the Bulgarian sequences with publicly available global sequences showed that CRF01_AE likely originated from multiple Asian countries, with Vietnam as the likely source of the outbreak cluster between 1988 and 1990. Our findings indicate that CRF01_AE was introduced into Bulgaria multiple times since 1988, and infections then rapidly spread among PWID locally with bridging to other risk groups and countries. CRF01_AE continues to spread in Bulgaria as evidenced by the more recent large clusters identified at d = 0.5%, highlighting the importance of public health prevention efforts in the PWID communities. |
Molecular Epidemiology of the HIV-1 Subtype B Sub-Epidemic in Bulgaria.
Alexiev I , Campbell EM , Knyazev S , Pan Y , Grigorova L , Dimitrova R , Partsuneva A , Gancheva A , Kostadinova A , Seguin-Devaux C , Switzer WM . Viruses 2020 12 (4) HIV-1 subtype B is the predominant strain in Bulgaria, yet little is known about the molecular epidemiology of these infections, including its origin and transmissibility. We used a phylodynamics approach by combining and analyzing 663 HIV-1 polymerase (pol) sequences collected from persons diagnosed with HIV/AIDS between 1988-2018 and associated epidemiologic data to better understand this sub-epidemic in Bulgaria. Using network analyses at a 1.5% genetic distance threshold (d) we found several large phylogenetic clusters composed mostly of men who have sex with men (MSM) and male heterosexuals (HET). However, at d = 0.5%, used to identify more recent transmission, the largest clusters dissociated to become smaller in size. The majority of female HET and persons with other transmission risks were singletons or pairs in the network. Phylogenetic analysis of the Bulgarian pol sequences with publicly available global sequences showed that subtype B was likely introduced into Bulgaria from multiple countries, including Israel and several European countries. Our findings indicate that subtype B was introduced into Bulgaria multiple times since 1988 and then infections rapidly spread among MSM and non-disclosed MSM. These high-risk behaviors continue to spread subtype B infection in Bulgaria as evidenced by the large clusters at d = 0.5%. Relatively low levels of antiretroviral drug resistance were observed in our study. Prevention strategies should continue to include increased testing and linkage to care and treatment, as well as expanded outreach to the MSM communities. |
QUENTIN: reconstruction of disease transmissions from viral quasispecies genomic data.
Skums P , Zelikovsky A , Singh R , Gussler W , Dimitrova Z , Knyazev S , Mandric I , Ramachandran S , Campo D , Jha D , Bunimovich L , Costenbader E , Sexton C , O'Connor S , Xia GL , Khudyakov Y . Bioinformatics 2018 34 (1) 163-170 Motivation: Genomic analysis has become one of the major tools for disease outbreak investigations. However, existing computational frameworks for inference of transmission history from viral genomic data often do not consider intra-host diversity of pathogens and heavily rely on additional epidemiological data, such as sampling times and exposure intervals. This impedes genomic analysis of outbreaks of highly mutable viruses associated with chronic infections, such as human immunodeficiency virus and hepatitis C virus, whose transmissions are often carried out through minor intra-host variants, while the additional epidemiological information often is either unavailable or has a limited use. Results: The proposed framework QUasispecies Evolution, Network-based Transmission INference (QUENTIN) addresses the above challenges by evolutionary analysis of intra-host viral populations sampled by deep sequencing and Bayesian inference using general properties of social networks relevant to infection dissemination. This method allows inference of transmission direction even without the supporting case-specific epidemiological information, identify transmission clusters and reconstruct transmission history. QUENTIN was validated on experimental and simulated data, and applied to investigate HCV transmission within a community of hosts with high-risk behavior. It is available at https://github.com/skumsp/QUENTIN. Contact: pskums@gsu.edu or alexz@cs.gsu.edu or rahul@sfsu.edu or yek0@cdc.gov. Supplementary information: Supplementary data are available at Bioinformatics online. |
Inference of genetic relatedness between viral quasispecies from sequencing data.
Glebova O , Knyazev S , Melnyk A , Artyomenko A , Khudyakov Y , Zelikovsky A , Skums P . BMC Genomics 2017 18 918 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. |
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