Spatiotemporal structure of molecular evolution of H5N1 highly pathogenic avian influenza viruses in Vietnam

Detecting geospatial patterns of Plasmodium falciparum parasite migration in Cambodia using optimized estimated effective migration surfaces

BACKGROUND

Understanding the genetic structure of natural populations provides insight into the demographic and adaptive processes that have affected those populations. Such information, particularly when integrated with geospatial data, can have translational applications for a variety of fields, including public health. Estimated effective migration surfaces (EEMS) is an approach that allows visualization of the spatial patterns in genomic data to understand population structure and migration. In this study, we developed a workflow to optimize the resolution of spatial grids used to generate EEMS migration maps and applied this optimized workflow to estimate migration of Plasmodium falciparum in Cambodia and bordering regions of Thailand and Vietnam.

METHODS

The optimal density of EEMS grids was determined based on a new workflow created using density clustering to define genomic clusters and the spatial distance between genomic clusters. Topological skeletons were used to capture the spatial distribution for each genomic cluster and to determine the EEMS grid density; i.e., both genomic and spatial clustering were used to guide the optimization of EEMS grids. Model accuracy for migration estimates using the optimized workflow was tested and compared to grid resolutions selected without the optimized workflow. As a test case, the optimized workflow was applied to genomic data generated from P. falciparum sampled in Cambodia and bordering regions, and migration maps were compared to estimates of malaria endemicity, as well as geographic properties of the study area, as a means of validating observed migration patterns.

RESULTS

Optimized grids displayed both high model accuracy and reduced computing time compared to grid densities selected in an unguided manner. In addition, EEMS migration maps generated for P. falciparum using the optimized grid corresponded to estimates of malaria endemicity and geographic properties of the study region that might be expected to impact malaria parasite migration, supporting the validity of the observed migration patterns.

CONCLUSIONS

Optimized grids reduce spatial uncertainty in the EEMS contours that can result from user-defined parameters, such as the resolution of the spatial grid used in the model. This workflow will be useful to a broad range of EEMS users as it can be applied to analyses involving other organisms of interest and geographic areas.

Incorporating sampling uncertainty in the geospatial assignment of taxa for virus phylogeography

Discrete phylogeography using software such as BEAST considers the sampling location of each taxon as fixed; often to a single location without uncertainty. When studying viruses, this implies that there is no possibility that the location of the infected host for that taxa is somewhere else. Here, we relaxed this strong assumption and allowed for analytic integration of uncertainty for discrete virus phylogeography. We used automatic language processing methods to find and assign uncertainty to alternative potential locations. We considered two influenza case studies: H5N1 in Egypt; H1N1 pdm09 in North America. For each, we implemented scenarios in which 25 per cent of the taxa had different amounts of sampling uncertainty including 10, 30, and 50 per cent uncertainty and varied how it was distributed for each taxon. This includes scenarios that: (i) placed a specific amount of uncertainty on one location while uniformly distributing the remaining amount across all other candidate locations (correspondingly labeled 10, 30, and 50); (ii) assigned the remaining uncertainty to just one other location; thus ‘splitting’ the uncertainty among two locations (i.e. 10/90, 30/70, and 50/50); and (iii) eliminated uncertainty via two predefined heuristic approaches: assignment to a centroid location (CNTR) or the largest population in the country (POP). We compared all scenarios to a reference standard (RS) in which all taxa had known (absolutely certain) locations. From this, we implemented five random selections of 25 per cent of the taxa and used these for specifying uncertainty. We performed posterior analyses for each scenario, including: (a) virus persistence, (b) migration rates, (c) trunk rewards, and (d) the posterior probability of the root state. The scenarios with sampling uncertainty were closer to the RS than CNTR and POP. For H5N1, the absolute error of virus persistence had a median range of 0.005–0.047 for scenarios with sampling uncertainty—(i) and (ii) above—versus a range of 0.063–0.075 for CNTR and POP. Persistence for the pdm09 case study followed a similar trend as did our analyses of migration rates across scenarios (i) and (ii). When considering the posterior probability of the root state, we found all but one of the H5N1 scenarios with sampling uncertainty had agreement with the RS on the origin of the outbreak whereas both CNTR and POP disagreed. Our results suggest that assigning geospatial uncertainty to taxa benefits estimation of virus phylogeography as compared to ad-hoc heuristics. We also found that, in general, there was limited difference in results regardless of how the sampling uncertainty was assigned; uniform distribution or split between two locations did not greatly impact posterior results. This framework is available in BEAST v.1.10. In future work, we will explore viruses beyond influenza. We will also develop a web interface for researchers to use our language processing methods to find and assign uncertainty to alternative potential locations for virus phylogeography.

Revised time scales of RNA virus evolution based on spatial information

The time scales of pathogen evolution are of major concern in the context of public and veterinary health, epidemiology and evolutionary biology. Dating the emergence of a pathogen often relies on estimates of evolutionary rates derived from nucleotide sequence data. For many viruses, this has yielded estimates of evolutionary origins only a few hundred years in the past. Here we demonstrate through the incorporation of geographical information from virus sampling that evolutionary age estimates of two European hantaviruses are severely underestimated because of pervasive mutational saturation of nucleotide sequences. We detected very strong relationships between spatial distance and genetic divergence for both Puumala and Tula hantavirus-irrespective of whether nucleotide or derived amino acid sequences were analysed. Extrapolations from these relationships dated the emergence of these viruses most conservatively to at least 3700 and 2500 years ago, respectively. Our minimum estimates for the age of these hantaviruses are ten to a hundred times older than results from current non-spatial methods, and in much better accordance with the biogeography of these viruses and their respective hosts. Spatial information can thus provide valuable insights on the deeper time scales of pathogen evolution and improve our understanding of disease emergence.

How's the Flu Getting Through? Landscape genetics suggests both humans and birds spread H5N1 in Egypt

First introduced to Egypt in 2006, H5N1 highly pathogenic avian influenza has resulted in the death of millions of birds and caused over 350 infections and at least 117 deaths in humans. After a decade of viral circulation, outbreaks continue to occur and diffusion mechanisms between poultry farms remain unclear. Using landscape genetics techniques, we identify the distance models most strongly correlated with the genetic relatedness of the viruses, suggesting the most likely methods of viral diffusion within Egyptian poultry. Using 73 viral genetic sequences obtained from infected birds throughout northern Egypt between 2009 and 2015, we calculated the genetic dissimilarity between H5N1 viruses for all eight gene segments. Spatial correlation was evaluated using Mantel tests and correlograms and multiple regression of distance matrices within causal modeling and relative support frameworks. These tests examine spatial patterns of genetic relatedness, and compare different models of distance. Four models were evaluated: Euclidean distance, road network distance, road network distance via intervening markets, and a least-cost path model designed to approximate wild waterbird travel using niche modeling and circuit theory. Samples from backyard farms were most strongly correlated with least cost path distances. Samples from commercial farms were most strongly correlated with road network distances. Results were largely consistent across gene segments. Results suggest wild birds play an important role in viral diffusion between backyard farms, while commercial farms experience human-mediated diffusion. These results can inform avian influenza surveillance and intervention strategies in Egypt.

Spread and persistence of influenza A viruses in waterfowl hosts in the North American Mississippi migratory flyway

While geographic distance often restricts the spread of pathogens via hosts, this barrier may be compromised when host species are mobile. Migratory waterfowl in the order Anseriformes are important reservoir hosts for diverse populations of avian-origin influenza A viruses (AIVs) and are assumed to spread AIVs during their annual continental-scale migrations. However, support for this hypothesis is limited, and it is rarely tested using data from comprehensive surveillance efforts incorporating both the temporal and spatial aspects of host migratory patterns. We conducted intensive AIV surveillance of waterfowl using the North American Mississippi Migratory Flyway (MMF) over three autumn migratory seasons. Viral isolates (n = 297) from multiple host species were sequenced and analyzed for patterns of gene dispersal between northern staging and southern wintering locations. Using a phylogenetic and nucleotide identity framework, we observed a larger amount of gene dispersal within this flyway rather than between the other three longitudinally identified North American flyways. Across seasons, we observed patterns of regional persistence of diversity for each genomic segment, along with limited survival of dispersed AIV gene lineages. Reassortment increased with both time and distance, resulting in transient AIV constellations. This study shows that within the MMF, AIV gene flow favors spread along the migratory corridor within a season, and also that intensive surveillance during bird migration is important for identifying virus dispersal on time scales relevant to pandemic responsiveness. In addition, this study indicates that comprehensive monitoring programs to capture AIV diversity are critical for providing insight into AIV evolution and ecology in a major natural reservoir.

IMPORTANCE

Migratory birds are a reservoir for antigenic and genetic diversity of influenza A viruses (AIVs) and are implicated in the spread of virus diversity that has contributed to previous pandemic events. Evidence for dispersal of avian-origin AIVs by migratory birds is rarely examined on temporal scales relevant to pandemic or panzootic threats. Therefore, characterizing AIV movement by hosts within a migratory season is important for implementing effective surveillance strategies. We conducted surveillance following birds along a major North American migratory route and observed that within a migratory season, AIVs rapidly reassorted and gene lineages were dispersed primarily within the migratory corridor. Patterns of regional persistence were observed across seasons for each gene segment. We show that dispersal of AIV gene lineages by migratory birds occurs quickly along migratory routes and that surveillance for AIVs threatening human and animal health should focus attention on these routes.

Spatial, temporal and genetic dynamics of highly pathogenic avian influenza A (H5N1) virus in China

BACKGROUND

The spatial spread of H5N1 avian influenza, significant ongoing mutations, and long-term persistence of the virus in some geographic regions has had an enormous impact on the poultry industry and presents a serious threat to human health.

METHODS

We applied phylogenetic analysis, geospatial techniques, and time series models to investigate the spatiotemporal pattern of H5N1 outbreaks in China and the effect of vaccination on virus evolution.

RESULTS

Results showed obvious spatial and temporal clusters of H5N1 outbreaks on different scales, which may have been associated with poultry and wild-bird transmission modes of H5N1 viruses. Lead-lag relationships were found among poultry and wild-bird outbreaks and human cases. Human cases were preceded by poultry outbreaks, and wild-bird outbreaks were led by human cases. Each clade has gained its own unique spatiotemporal and genetic dominance. Genetic diversity of the H5N1 virus decreased significantly between 1996 and 2011; presumably under strong selective pressure of vaccination. Mean evolutionary rates of H5N1 virus increased after vaccination was adopted in China. A clear signature of positively selected sites in the clade 2.3.2 virus was discovered and this may have resulted in the emergence of clade 2.3.2.1.

CONCLUSIONS

Our study revealed two different transmission modes of H5N1 viruses in China, and indicated a significant role of poultry in virus dissemination. Furthermore, selective pressure posed by vaccination was found in virus evolution in the country.

The geography of malaria genetics in the Democratic Republic of Congo: A complex and fragmented landscape

Understanding how malaria parasites move between populations is important, particularly given the potential for malaria to be reintroduced into areas where it was previously eliminated. We examine the distribution of malaria genetics across seven sites within the Democratic Republic of Congo (DRC) and two nearby countries, Ghana and Kenya, in order to understand how the relatedness of malaria parasites varies across space, and whether there are barriers to the flow of malaria parasites within the DRC or across borders. Parasite DNA was retrieved from dried blood spots from 7 Demographic and Health Survey sample clusters in the DRC. Malaria genetic characteristics of parasites from Ghana and Kenya were also obtained. For each of 9 geographic sites (7 DRC, 1 Ghana and 1 Kenya), a pair-wise RST statistic was calculated, indicating the genetic distance between malaria parasites found in those locations. Mapping genetics across the spatial extent of the study area indicates a complex genetic landscape, where relatedness between two proximal sites may be relatively high (RST > 0.64) or low (RST < 0.05), and where distal sites also exhibit both high and low genetic similarity. Mantel's tests suggest that malaria genetics differ as geographic distances increase. Principal Coordinate Analysis suggests that genetically related samples are not co-located. Barrier analysis reveals no significant barriers to gene flow between locations. Malaria genetics in the DRC have a complex and fragmented landscape. Limited exchange of genes across space is reflected in greater genetic distance between malaria parasites isolated at greater geographic distances. There is, however, evidence for close genetic ties between distally located sample locations, indicating that movement of malaria parasites and flow of genes is being driven by factors other than distance decay. This research demonstrates the contributions that spatial disease ecology and landscape genetics can make to understanding the evolutionary dynamics of infectious diseases.

Ecological niche modeling of Bacillus anthracis on three continents: evidence for genetic-ecological divergence?

We modeled the ecological niche of a globally successful Bacillus anthracis sublineage in the United States, Italy and Kazakhstan to better understand the geographic distribution of anthrax and potential associations between regional populations and ecology. Country-specific ecological-niche models were developed and reciprocally transferred to the other countries to determine if pathogen presence could be accurately predicted on novel landscapes. Native models accurately predicted endemic areas within each country, but transferred models failed to predict known occurrences in the outside countries. While the effects of variable selection and limitations of the genetic data should be considered, results suggest differing ecological associations for the B. anthracis populations within each country and may reflect niche specialization within the sublineage. Our findings provide guidance for developing accurate ecological niche models for this pathogen; models should be developed regionally, on the native landscape, and with consideration to population genetics. Further genomic analysis will improve our understanding of the genetic-ecological dynamics of B. anthracis across these countries and may lead to more refined predictive models for surveillance and proactive vaccination programs. Further studies should evaluate the impact of variable selection of native and transferred models.

Evolutionary and Ecological Dynamics of Transboundary Disease Caused by H5N1 Virus in Southeast Asia

Southeast Asia has been the breeding ground for many emerging diseases in the past decade, and it is in this region that new genetic variants of HPAI H5N1 viruses have been emerging. Cross-border movement of animals accelerates the spread of H5N1, and the changing environmental conditions also exert strong selective pressure on the viruses. The transboundary zoonotic diseases caused by H5N1 pose a serious and continual threat to global economy and public health. Here, we divided the H5N1 viruses isolated in Southeast Asia during 2003-2009 into four groups according to their phylogenetic relationships among HA gene sequences. Molecular evolution analysis suggests populations in expansion rather than a positive selection for group 2 and group 3, yet group 4 is under strong positive selection. Site 193 was found to be a potential glycosylation site and located in receptor-binding domain. Note that site 193 tends to appear in avian isolates instead of human strains. Population dynamics analysis reveals that the effective population size of infections in Southeast Asia has undergone three obvious increases, and the results are consistent with the epidemiological analysis. Ecological and phylogeographical analyses show that agro-ecological environments, migratory birds, domestic waterfowl, especially free-ranging ducks, are crucial in the occurrence, maintenance and spread of H5N1 virus. The epidemiological links between Indonesia and Suphanburi observed suggest that viruses in Indonesia were originated from multiple introductions.

Molecular phylogeography of tick-borne encephalitis virus in central Europe

In order to obtain a better understanding of tick-borne encephalitis virus (TBEV) strain movements in central Europe the E gene sequences of 102 TBEV strains collected from 1953 to 2011 at 38 sites in the Czech Republic, Slovakia, Austria and Germany were determined. Bayesian analysis suggests a 350-year history of evolution and spread in central Europe of two main lineages, A and B. In contrast to the east to west spread at the Eurasian continent level, local central European spreading patterns suggest historic west to east spread followed by more recent east to west spread. The phylogenetic and network analyses indicate TBEV ingressions from the Czech Republic and Slovakia into Germany via landscape features (Danube river system), biogenic factors (birds, red deer) and anthropogenic factors. The identification of endemic foci showing local genetic diversity is of paramount importance to the field as these will be a prerequisite for in-depth analysis of focal TBEV maintenance and long-distance TBEV spread.

Evidence for the circulation and inter-hemispheric movement of the H14 subtype influenza A virus

Three H14 influenza A virus (IAV) isolates recovered in 2010 during routine virus surveillance along the Mississippi Migratory Bird Flyway in Wisconsin, U.S.A. raised questions about the natural history of these rare viruses. These were the first H14 IAV isolates recovered in the Western Hemisphere and the only H14 IAV isolates recovered since the original four isolates in 1982 in Asia. Full length genomic sequencing of the 2010 H14 isolates demonstrated the hemagglutinin (HA) gene from the 1982 and 2010 H14 isolates showed 89.6% nucleotide and 95.6% amino acid similarity and phylogenetic analysis of these viruses placed them with strong support within the H14 subtype lineage. The level of genomic divergence observed between the 1982 and 2010 viruses provides evidence that the H14 HA segment was circulating undetected in hosts and was not maintained in environmental stasis. Further, the evolutionary relationship observed between 1982 H14 and the closely related H4 subtype HA segments were similar to contemporary comparisons suggesting limited adaptive divergence between these sister subtypes. The nonstructural (NS) segment of one 2010 isolate was placed in a NS clade isolated infrequently over the last several decades that includes the NS segment from a previously reported 1982 H14 isolate indicating the existence of an unidentified pool of genomic diversity. An additional neuraminidase reassortment event indicated a recent inter-hemispheric gene flow from Asia into the center of North America. These results demonstrate temporal and spatial gaps in the understanding of IAV natural history. Additionally, the reassortment history of these viruses raises concern for the inter-continental spread of IAVs and the efficacy of current IAV surveillance efforts in detecting genomic diversity of viruses circulating in wild birds.

Genetics: A New Landscape for Medical Geography

The emergence and re-emergence of human pathogens resistant to medical treatment will present a challenge to the international public health community in the coming decades. Geography is uniquely positioned to examine the progressive evolution of pathogens across space and through time, and to link molecular change to interactions between population and environmental drivers. Landscape as an organizing principle for the integration of natural and cultural forces has a long history in geography, and, more specifically, in medical geography. Here, we explore the role of landscape in medical geography, the emergent field of landscape genetics, and the great potential that exists in the combination of these two disciplines. We argue that landscape genetics can enhance medical geographic studies of local-level disease environments with quantitative tests of how human-environment interactions influence pathogenic characteristics. In turn, such analyses can expand theories of disease diffusion to the molecular scale and distinguish the important factors in ecologies of disease that drive genetic change of pathogens.

Molecular epidemiology of circulating highly pathogenic avian influenza (H5N1) virus in chickens, in Bangladesh, 2007-2010

Bangladesh has been severely hit by highly pathogenic avian influenza H5N1 (HPAI-H5N1). However, little is known about the genetic diversity and the evolution of the circulating viruses in Bangladesh. In the present study, we analyzed the hemagglutinin gene of 30 Bangladeshi chicken isolates from 2007 through 2010. We analyzed the polybasic amino acid sequence motif of the cleavage site and amino acid substitution pattern. Phylogenetic history was reconstructed using neighbor-joining and Bayesian time-scaled methods. In addition, we used Mantel correlation tests to analyze the relation between genetic relatedness and spatial and temporal distances. Neighbor-joining phylogeography revealed that virus circulating in Bangladesh from 2007 through 2010 belonged to clade 2.2. The results suggest that clade 2.2 viruses are firmly entrenched and have probably become endemic in Bangladesh. We detected several amino acid substitutions, but they are not indicative of adaptation toward human infection. The Mantel correlation test confirmed significant correlation between genetic distances and temporal distances between the viruses. The Bayesian tree shows that isolates from waves 3 and 4 derived from a subgroup of isolates from the previous waves grouping with a high posterior probability (pp=1.0). This indicates the possibility of formation of local subclades. One surprising finding of spatio-temporal analysis was that genetically identical virus caused independent outbreaks over a distance of more than 200 km and within 14 days of each other. This might indicate long distance dispersal through vectors such as migratory birds and vehicles, and challenges the effectiveness of movement restriction around 10 km radius of an outbreak. The study indicates possible endemicity of the clade 2.2 HPAI-H5N1 virus in Bangladesh. Furthermore, the formation of a subclade capable of transmission to humans cannot be ruled out. The findings of this study might provide valuable information for future surveillance, prevention and control programme.

Population-environment drivers of H5N1 avian influenza molecular change in Vietnam

This study identifies population and environment drivers of genetic change in H5N1 avian influenza viruses (AIV) in Vietnam using a landscape genetics approach. While prior work has examined how combinations of local-level environmental variables influence H5N1 occurrence, this research expands the analysis to the complex genetic characteristics of H5N1 viruses. A dataset of 125 highly pathogenic H5N1 AIV isolated in Vietnam from 2003 to 2007 is used to explore which population and environment variables are correlated with increased genetic change among viruses. Results from non-parametric multidimensional scaling and regression analyses indicate that variables relating to both the environmental and social ecology of humans and birds in Vietnam interact to affect the genetic character of viruses. These findings suggest that it is a combination of suitable environments for species mixing, the presence of high numbers of potential hosts, and in particular the temporal characteristics of viral occurrence, that drive genetic change among H5N1 AIV in Vietnam.

Using knowledge fusion to analyze avian influenza H5N1 in East and Southeast Asia

Highly pathogenic avian influenza (HPAI) H5N1, a disease associated with high rates of mortality in infected human populations, poses a serious threat to public health in many parts of the world. This article reports findings from a study aimed at improving our understanding of the spatial pattern of the highly pathogenic avian influenza, H5N1, risk in East-Southeast Asia where the disease is both persistent and devastating. Though many disciplines have made important contributions to our understanding of H5N1, it remains a challenge to integrate knowledge from different disciplines. This study applies genetic analysis that identifies the evolution of the H5N1 virus in space and time, epidemiological analysis that determines socio-ecological factors associated with H5N1 occurrence, and statistical analysis that identifies outbreak clusters, and then applies a methodology to formally integrate the findings of the three sets of methodologies. The present study is novel in two respects. First it makes the initiative attempt to use genetic sequences and space-time data to create a space-time phylogenetic tree to estimate and map the virus' ability to spread. Second, by integrating the results we are able to generate insights into the space-time occurrence and spread of H5N1 that we believe have a higher level of corroboration than is possible when analysis is based on only one methodology. Our research identifies links between the occurrence of H5N1 by area and a set of socio-ecological factors including altitude, population density, poultry density, and the shortest path distances to inland water, coastlines, migrating routes, railways, and roads. This study seeks to lay a solid foundation for the interdisciplinary study of this and other influenza outbreaks. It will provide substantive information for containing H5N1 outbreaks.

Highly pathogenic H5N1 avian influenza viruses exhibit few barriers to gene flow in Vietnam

Locating areas where genetic change is inhibited can illuminate underlying processes that drive evolution of pathogens. The persistence of highly pathogenic H5N1 avian influenza in Vietnam since 2003, and the continuous molecular evolution of Vietnamese avian influenza viruses, indicates that local environmental factors are supportive not only of incidence but also of viral adaptation. This article explores whether gene flow is constant across Vietnam, or whether there exist boundary areas where gene flow exhibits discontinuity. Using a dataset of 125 highly pathogenic H5N1 avian influenza viruses, principal components analysis and wombling analysis are used to indicate the location, magnitude, and statistical significance of genetic boundaries. Results show that a small number of geographically minor boundaries to gene flow in highly pathogenic H5N1 avian influenza viruses exist in Vietnam, but that overall there is little division in genetic exchange. This suggests that differences in genetic characteristics of viruses from one region to another are not the result of barriers to H5N1 viral exchange in Vietnam, and that H5N1 avian influenza is able to spread relatively unimpeded across the country.

Alignment free characterization of the influenza-A hemagglutinin genes by the ISSCOR method

Analyses and visualizations by the ISSCOR method of the influenza virus hemagglutinin genes of three different A-subtypes revealed some rather striking temporal (for A/H3N3), and spatial relationships (for A/H5N1) between groups of individual gene subsets. The application to the A/H1N1 set revealed also relationships between the seasonal H1, and the swine-like novel 2009 H1v variants in a quick and unambiguous manner. Based on these examples we consider the application of the ISSCOR method for analysis of large sets of homologous genes as a worthwhile addition to a toolbox of genomics-it allows a rapid diagnostics of trends, and possibly can even aid an early warning of newly emerging epidemiological threats.