Integration of phylogenomics and molecular modeling reveals lineage-specific diversification of toxins in scorpions.

Scorpions have evolved a variety of toxins with a plethora of biological targets, but characterizing their evolution has been limited by the lack of a comprehensive phylogenetic hypothesis of scorpion relationships grounded in modern, genome-scale datasets. Disagreements over scorpion higher-level systematics have also incurred challenges to previous interpretations of venom families as ancestral or derived. To redress these gaps, we assessed the phylogenomic relationships of scorpions using the most comprehensive taxonomic sampling to date. We surveyed genomic resources for the incidence of calcins (a type of calcium channel toxin), which were previously known only from 16 scorpion species. Here, we show that calcins are diverse, but phylogenetically restricted only to parvorder Iurida, one of the two basal branches of scorpions. The other branch of scorpions, Buthida, bear the related LKTx toxins (absent in Iurida), but lack calcins entirely. Analysis of sequences and molecular models demonstrates remarkable phylogenetic inertia within both calcins and LKTx genes. These results provide the first synapomorphies (shared derived traits) for the recently redefined clades Buthida and Iurida, constituting the only known case of such traits defined from the morphology of molecules.

Molecular evolution of Zika virus as it crossed the Pacific to the Americas.

Zika virus was previously considered to cause only a benign infection in humans. Studies of recent outbreaks of Zika virus in the Pacific, South America, Mexico and the Caribbean have associated the virus with severe neuropathology. Viral evolution may be one factor contributing to an apparent change in Zika disease as it spread from Southeast Asia across the Pacific to the Americas. To address this possibility, we have employed computational tools to compare the phylogeny, geography, immunology and RNA structure of Zika virus isolates from Africa, Asia, the Pacific and the Americas. In doing so, we compare and contrast methods and results for tree search and rooting of Zika virus phylogenies. In some phylogenetic analyses we find support for the hypothesis that there is a deep common ancestor between African and Asian clades (the "Asia/Africa" hypothesis). In other phylogenetic analyses, we find that Asian lineages are descendent from African lineages (the "out of Africa" hypothesis). In addition, we identify and evaluate key mutations in viral envelope protein coding and untranslated terminal RNA regions. We find stepwise mutations that have altered both immunological motif sets and regulatory sequence elements. Both of these sets of changes distinguish viruses found in Africa from those in the emergent Asia-Pacific-Americas lineage. These findings support the working hypothesis that mutations acquired by Zika virus in the Pacific and Americas contribute to changes in pathology. These results can inform experiments required to elucidate the role of viral genetic evolution in changes in neuropathology, including microcephaly and other neurological and skeletomuscular issues in infants, and Guillain-Barré syndrome in adults.

Syndromic Surveillance of Infectious Diseases meets Molecular Epidemiology in a Workflow and Phylogeographic Application.

Traditionally, epidemiologists have counted cases and groups of symptoms. Modeling on these data consists of predicting expansion or contraction in the number of cases over time in epidemic curves or compartment models. Geography is considered a variable when these data are presented in choropleth maps. These approaches have significant drawbacks if the cases counted are not accurately diagnosed. For example, most regional public health authorities count influenza like illnesses (ILI). Cases of these diseases are designated as ILI if the patient exhibits fever, respiratory symptoms, and perhaps gastrointestinal symptoms. Several molecular epidemiological studies have shown that there are many pathogens that cause these symptoms and the relative proportions of these pathogens change over time and space. One way to bridge the gap between syndromic and genetic surveillance of infectious diseases is to compare signals of symptoms to pathogens recorded in molecular databases. We present a web-based workflow application that uses chief complaints found in the public Twitter feed as a syndromic surveillance tool and connects outbreak signals in these data to pathogens historically known to circulate in the same area. For the pathogen(s) of interest, we provide Genbank links to metadata and sequences in a workflow for phylogeographic analysis and visualization. The visualizations provide information on the geographic traffic of the spread of the pathogens and places that are hubs for their transport.