The Supramap project: linking pathogen genomes with geography to fight emergent infectious diseases

Abstract

Novel pathogens have the potential to become critical issues of national security, public health and economic welfare. As demonstrated by the response to Severe Acute Respiratory Syndrome (SARS) and influenza, genomic sequencing has become an important method for diagnosing agents of infectious disease. Despite the value of genomic sequences in characterizing novel pathogens, raw data on their own do not provide the information needed by public health officials and researchers. One must integrate knowledge of the genomes of pathogens with host biology and geography to understand the etiology of epidemics. To these ends, we have created an application called Supramap (http://supramap.osu.edu) to put information on the spread of pathogens and key mutations across time, space and various hosts into a geographic information system (GIS). To build this application, we created a web service for integrated sequence alignment and phylogenetic analysis as well as methods to describe the tree, mutations, and host shifts in Keyhole Markup Language (KML). We apply the application to 239 sequences of the polymerase basic 2 (PB2) gene of recent isolates of avian influenza (H5N1). We map a mutation, glutamic acid to lysine at position 627 in the PB2 protein (E627K), in H5N1 influenza that allows for increased replication of the virus in mammals. We use a statistical test to support the hypothesis of a correlation of E627K mutations with avian-mammalian host shifts but reject the hypothesis that lineages with E627K are moving westward. Data, instructions for use, and visualizations are included as supplemental materials at: http://supramap.osu.edu/sm/supramap/publications. Ó The Willi Hennig Society 2010.We have created a web-based workflow application, Supramap (http://supramap.osu.edu). Using a web browser, a user inputs text files containing sequence and or phenotypic data, latitude and longitude coordinates, and (optionally) a date of isolation for each strain. Our application then executes a workflow that entails integrated sequence alignment and phylogenetic analysis, computation of character changes (e.g., mutations and host shifts), and geographical projection of the tree on a computing cluster. Once the analyses are complete, the user can download a phylogenetic layer expressed in KML file and view the file with a Geographic Information System (GIS). The user can use the phylogenetic layer to visualize several aspects of pathogen evolution including: spread of lineages, mutations, shifts among hosts, and phenotypic changes over geography and time. We illustrate the use of the system with a case study on H5N1 and discuss use of visualization in conjunction with statistical validation. Other tree projection effortsSupramap is superficially similar to other efforts for projecting phylogenetic trees in GIS, such as

Visualization and analytics tools for infectious disease epidemiology: A systematic review

“…In molecular epidemiology, relationships between isolates are often calculated and conveyed through phylogenetic trees or dendrograms (Figure 4). Visualization tools for molecular epidemiology often included phylogenetic analysis and visualization capabilities [113-115] and visualization of contextual data using connected graphs [70, 113]. The tools we reviewed were primarily designed to be accessed through the internet [70, 113, 114, 116].…”

“…Most studies in our review included the capability to integrate GIS or location-based data with genetic or serotype visualizations [11, 70, 84, 113-117]. Two of the tools were designed to produce visualization (KML) files for display in other GIS packages [11, 115], while other web based tools made use of external GIS services embeded within the website, primarily Google maps, ESRI/ArcGIS or HealthMap [70, 116, 117]. …”

“…These tools allow spatial views of molecular epidemiological properties associated with outbreaks, for example showing sequence variation of genes associated with disease virulence between outbreak locations. Other tools were designed to accommodate multiple organisms or user-specified organisms [113-115]. One such tool, designed specifically for geospatial surveillance of genomic characteristics of NIAID category A–C viral and bacterial pathogens, is GeMIna [11].…”

GenGIS 2: Geospatial Analysis of Traditional and Genetic Biodiversity, with New Gradient Algorithms and an Extensible Plugin Framework

“…Purpose-built software tools allow the geographic analysis of biodiversity by incorporating phylogenetic information in different ways. Several programs provide visualizations of 2D or 3D geophylogenies, along with functionality to explore the temporal structure of this data [3], [4] or the geographic uncertainty associated with Bayesian techniques for phylogeographic inference [5]. Other programs have focused on displaying the spatial distribution and diversity of taxa using pie charts or geographic heat maps, and incorporate phylogenetic information by focusing on specific lineages or assigning molecular sequences to haplotypes [6]–[8].…”

GenGIS 2: Geospatial analysis of traditional and genetic biodiversity, with new gradient algorithms and an extensible plugin framework

“…Purpose-built software tools allow the geographic analysis of biodiversity by incorporating phylogenetic information in different ways. Several programs provide visualizations of 2D or 3D geophylogenies, along with functionality to explore the temporal structure of this data (Kidd and Liu 2008;Janies et al 2011) or the geographic uncertainty associated with Bayesian techniques for phylogeographic inference (Bielejec et al 2011). Other programs have focused on displaying the spatial distribution and diversity of taxa using pie charts or geographic heat maps, and incorporate phylogenetic information by focusing on specific lineages or assigning molecular sequences to haplotypes (Hijmans et al 2001;Laffan et al 2010;Tsai 2011).…”