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D-graph clusters flaviviruses and ?-coronaviruses according to their hosts, disease type and human cell receptors.

ABSTRACT: Motivation:There is a need for rapid and easy to use, alignment free methods to cluster large groups of protein sequence data. Commonly used phylogenetic trees based on alignments can be used to visualize only a limited number of protein sequences. DGraph, introduced here, is a dynamic programming application developed to generate 2D-maps based on similarity scores for sequences. The program automatically calculates and graphically displays property distance (PD) scores based on physico-chemical property (PCP) similarities from an unaligned list of FASTA files. Such "PD-graphs" show the interrelatedness of the sequences, whereby clusters can reveal deeper connectivities. Results:PD-Graphs generated for flavivirus (FV), enterovirus (EV), and coronavirus (CoV) sequences from complete polyproteins or individual proteins are consistent with biological data on vector types, hosts, cellular receptors and disease phenotypes. PD-graphs separate the tick- from the mosquito-borne FV, clusters viruses that infect bats, camels, seabirds and humans separately and the clusters correlate with disease phenotype. The PD method segregates the ?-CoV spike proteins of SARS, SARS-CoV-2, and MERS sequences from other human pathogenic CoV, with clustering consistent with cellular receptor usage. The graphs also suggest evolutionary relationships that may be difficult to determine with conventional bootstrapping methods that require postulating an ancestral sequence. Availability and implementation:DGraph is written in Java, compatible with the Java 5 runtime or newer. Source code and executable is available from the GitHub website ( https://github.com/bjmnbraun/DGraph/releases ). Documentation for installation and use of the software is available from the Readme.md file at ( https://github.com/bjmnbraun/DGraph ). Contact:bjmnbraun@gmail.com or webraun@utmb.edu. Supplementary information:Supplementary information Table S1 and Fig. S1 are online available.

SUBMITTER: Braun BA

PROVIDER: S-EPMC7430575 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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D-graph clusters flaviviruses and β-coronaviruses according to their hosts, disease type and human cell receptors.

Braun Benjamin A BA Schein Catherine H CH Braun Werner W

bioRxiv : the preprint server for biology 20200814

<h4>Motivation</h4>There is a need for rapid and easy to use, alignment free methods to cluster large groups of protein sequence data. Commonly used phylogenetic trees based on alignments can be used to visualize only a limited number of protein sequences. DGraph, introduced here, is a dynamic programming application developed to generate 2D-maps based on similarity scores for sequences. The program automatically calculates and graphically displays property distance (PD) scores based on physico- ...[more]

PMID: 32817945

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Project description:Most described flaviviruses (family Flaviviridae) are disease-causing pathogens of vertebrates maintained in zoonotic cycles between mosquitoes or ticks and vertebrate hosts. Poor sampling of flaviviruses outside vector-borne flaviviruses such as Zika virus and dengue virus has presented a narrow understanding of flavivirus diversity and evolution. In this study, we discovered three crustacean flaviviruses (Gammarus chevreuxi flavivirus, Gammarus pulex flavivirus, and Crangon crangon flavivirus) and two cephalopod flaviviruses (Southern Pygmy squid flavivirus and Firefly squid flavivirus). Bayesian and maximum likelihood phylogenetic methods demonstrate that crustacean flaviviruses form a well-supported clade and share a more closely related ancestor with terrestrial vector-borne flaviviruses than with classical insect-specific flaviviruses. In addition, we identify variants of Wenzhou shark flavivirus in multiple gazami crab (Portunus trituberculatus) populations, with active replication supported by evidence of an active RNA interference response. This suggests that Wenzhou shark flavivirus moves horizontally between sharks and gazami crabs in ocean ecosystems. Analyses of the mono- and dinucleotide composition of marine flaviviruses compared to that of flaviviruses with known host status suggest that some marine flaviviruses share a nucleotide bias similar to that of vector-borne flaviviruses. Furthermore, we identify crustacean flavivirus endogenous viral elements that are closely related to elements of terrestrial vector-borne flaviviruses. Taken together, these data provide evidence of flaviviruses circulating between marine vertebrates and invertebrates, expand our understanding of flavivirus host range, and offer potential insights into the evolution and emergence of terrestrial vector-borne flaviviruses.IMPORTANCE Some flaviviruses are known to cause disease in vertebrates and are typically transmitted by blood-feeding arthropods such as ticks and mosquitoes. While an ever-increasing number of insect-specific flaviviruses have been described, we have a narrow understanding of flavivirus incidence and evolution. To expand this understanding, we discovered a number of novel flaviviruses that infect a range of crustaceans and cephalopod hosts. Phylogenetic analyses of these novel marine flaviviruses suggest that crustacean flaviviruses share a close ancestor to all terrestrial vector-borne flaviviruses, and squid flaviviruses are the most divergent of all known flaviviruses to date. Additionally, our results indicate horizontal transmission of a marine flavivirus between crabs and sharks. Taken together, these data suggest that flaviviruses move horizontally between invertebrates and vertebrates in ocean ecosystems. This study demonstrates that flavivirus invertebrate-vertebrate host associations have arisen in flaviviruses at least twice and may potentially provide insights into the emergence or origin of terrestrial vector-borne flaviviruses.

Dataset Information

D-graph clusters flaviviruses and ?-coronaviruses according to their hosts, disease type and human cell receptors.

Publications

D-graph clusters flaviviruses and β-coronaviruses according to their hosts, disease type and human cell receptors.

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