Parviez R. Hosseini

A Strategy To Estimate Unknown Viral Diversity in Mammals

ABSTRACT The majority of emerging zoonoses originate in wildlife, and many are caused by viruses. However, there are no rigorous estimates of total viral diversity (here termed “virodiversity”) for any wildlife species, despite the utility of this to future surveillance and control of emerging zoonoses. In this case study, we repeatedly sampled a mammalian wildlife host known to harbor emerging zoonotic pathogens (the Indian Flying Fox, Pteropus giganteus) and used PCR with degenerate viral family-level primers to discover and analyze the occurrence patterns of 55 viruses from nine viral families. We then adapted statistical techniques used to estimate biodiversity in vertebrates and plants and estimated the total viral richness of these nine families in P. giganteus to be 58 viruses. Our analyses demonstrate proof-of-concept of a strategy for estimating viral richness and provide the first statistically supported estimate of the number of undiscovered viruses in a mammalian host. We used a simple extrapolation to estimate that there are a minimum of 320,000 mammalian viruses awaiting discovery within these nine families, assuming all species harbor a similar number of viruses, with minimal turnover between host species. We estimate the cost of discovering these viruses to be ~

Pathogen-induced reversal of native dominance in a grassland community

6.3 billion (or ~

Seasonality and wildlife disease: how seasonal birth, aggregation and variation in immunity affect the dynamics of Mycoplasma gallisepticum in house finches

1.4 billion for 85% of the total diversity), which if annualized over a 10-year study time frame would represent a small fraction of the cost of many pandemic zoonoses. IMPORTANCE Recent years have seen a dramatic increase in viral discovery efforts. However, most lack rigorous systematic design, which limits our ability to understand viral diversity and its ecological drivers and reduces their value to public health intervention. Here, we present a new framework for the discovery of novel viruses in wildlife and use it to make the first-ever estimate of the number of viruses that exist in a mammalian host. As pathogens continue to emerge from wildlife, this estimate allows us to put preliminary bounds around the potential size of the total zoonotic pool and facilitates a better understanding of where best to allocate resources for the subsequent discovery of global viral diversity. Recent years have seen a dramatic increase in viral discovery efforts. However, most lack rigorous systematic design, which limits our ability to understand viral diversity and its ecological drivers and reduces their value to public health intervention. Here, we present a new framework for the discovery of novel viruses in wildlife and use it to make the first-ever estimate of the number of viruses that exist in a mammalian host. As pathogens continue to emerge from wildlife, this estimate allows us to put preliminary bounds around the potential size of the total zoonotic pool and facilitates a better understanding of where best to allocate resources for the subsequent discovery of global viral diversity.

Workflows and extensions to the Kepler scientific workflow system to support environmental sensor data access and analysis

Disease may play a critical role in invasions by nonnative plants and animals that currently threaten global biodiversity. For example, a generalist viral pathogen has been recently implicated in one of the most extensive plant invasions worldwide, the invasion and domination of Californias perennial grasslands by exotic annual grasses. To date, disease has never been quantitatively assessed as a cause of this invasion. Using a model with field-estimated parameters, we demonstrate that pathogen presence was necessary to reverse competitive outcome and to allow exotic annual grass invasion and dominance. Although pathogen-induced reversal of a competitive hierarchy has been suggested as a mechanism of species invasion, here we quantitatively demonstrate the importance of this phenomenon by using field-derived parameters in a dynamical model. Pathogen-mediated reversals in competitive balance may be critically important for understanding past, and predicting future, invasions.

Host and viral traits predict zoonotic spillover from mammals

We examine the role of host seasonal breeding, host seasonal social aggregation and partial immunity in affecting wildlife disease dynamics, focusing on the dynamics of house finch conjunctivitis (Mycoplasma gallisepticum (MG) in Carpodacus mexicanus). This case study of an unmanaged emerging infectious disease provides useful insight into the important role of seasonal factors in driving ongoing disease dynamics. Seasonal breeding can force recurrent epidemics through the input of fresh susceptibles, which will clearly affect a wide variety of wildlife disease dynamics. Seasonal patterns of social aggregation and foraging behaviour could change transmission dynamics. We use latitudinal variation in the timing of breeding, and social systems to model seasonal dynamics of house finch conjunctivitis across eastern North America. We quantify the patterns of seasonal breeding, and social aggregation across a latitudinal gradient in the eastern range of the house finch, supplemented with known field and laboratory information on immunity to MG in finches. We then examine the interactions of these factors in a theoretical model of disease dynamics. We find that both forms of seasonality could explain the dynamics of the house finch–MG system, and that these factors could have important effects on the dynamics of wildlife diseases generally. In particular, while either alone is sufficient to create recurrent cycles of prevalence in a population with an endemic disease, both are required to produce the specific semi–annual pattern of disease prevalence seen in the house finch conjunctivitis system.

EXPERIMENTAL INFECTION OF HOUSE FINCHES WITH MYCOPLASMA GALLISEPTICUM

Environmental sensor networks are now commonly being deployed within environmental observatories and as components of smaller-scale ecological and environmental experiments. Effectively using data from these sensor networks presents technical challenges that are difficult for scientists to overcome, severely limiting the adoption of automated sensing technologies in environmental science. The Realtime Environment for Analytical Processing (REAP) is an NSF-funded project to address the technical challenges related to accessing and using heterogeneous sensor data from within the Kepler scientific workflow system. Using distinct use cases in terrestrial ecology and oceanography as motivating examples, we describe workflows and extensions to Kepler to stream and analyze data from observatory networks and archives. We focus on the use of two newly integrated data sources in Kepler: DataTurbine and OPeNDAP. Integrated access to both near real-time data streams and data archives from within Kepler facilitates both simple data exploration and sophisticated analysis and modeling with these data sources.

Global biogeography of human infectious diseases

The majority of human emerging infectious diseases are zoonotic, with viruses that originate in wild mammals of particular concern (for example, HIV, Ebola and SARS). Understanding patterns of viral diversity in wildlife and determinants of successful cross-species transmission, or spillover, are therefore key goals for pandemic surveillance programs. However, few analytical tools exist to identify which host species are likely to harbour the next human virus, or which viruses can cross species boundaries. Here we conduct a comprehensive analysis of mammalian host–virus relationships and show that both the total number of viruses that infect a given species and the proportion likely to be zoonotic are predictable. After controlling for research effort, the proportion of zoonotic viruses per species is predicted by phylogenetic relatedness to humans, host taxonomy and human population within a species range—which may reflect human–wildlife contact. We demonstrate that bats harbour a significantly higher proportion of zoonotic viruses than all other mammalian orders. We also identify the taxa and geographic regions with the largest estimated number of ‘missing viruses’ and ‘missing zoonoses’ and therefore of highest value for future surveillance. We then show that phylogenetic host breadth and other viral traits are significant predictors of zoonotic potential, providing a novel framework to assess if a newly discovered mammalian virus could infect people.

Life History and Demographic Drivers of Reservoir Competence for Three Tick-Borne Zoonotic Pathogens

Mycoplasma gallisepticum (MG) has caused an endemic upper respiratory and ocular infection in the eastern house finch (Carpodacus mexicanus) after the epidemic first described in 1994. The disease has been studied by a number of investigators at a population level and reports describe experimental infection in group-housed MG-free house finches. Because detailed observation and evaluation of individual birds in group housed passerines is problematic, we studied individually housed house finches that were experimentally inoculated with the finch strain of MG in a controlled environment. To accomplish this, a study was conducted spanning the period of November 2001–April 2002 with 20 MG-free (confirmed by the rapid plate agglutination assay and polymerase chain reaction [PCR] assay) eastern house finches captured in the Cayuga Basin area of central New York (USA) in the summer of 2001. After a period of acclimatization and observation (12 wk), 20 finches were inoculated with a 0.05-ml aliquot of MG (3.24×105 colony-forming units/ml) via bilateral conjunctival sac instillations. Two additional finches acted as controls and were inoculated in the same manner with preservative-free sterile saline solution. After inoculation, all finches except the controls exhibited clinical signs of conjunctivitis within 2–6 days. The progression of the disease was evaluated by several methods, including PCR, behavioral observations, and physical examination including eye scoring, body weight, and body condition index. Over a period of 21 wk, MG-infected finches developed signs of disease and recovered (80%), developed signs of disease and progressed to become chronically infected (15%), or died (5%). We hypothesize that the high survival rate and recovery of these finches after infection was associated with the use of controlled environmental conditions, acclimatization, a high plane of nutrition, and low stocking (housing) density, all of which are factors documented to be important in the outcome of MG infections in domestic poultry and other species.

Predicting Hotspots for Influenza Virus Reassortment

Significance Understanding the distributions of infectious diseases is a central public and global health objective. We show that human infectious diseases exhibit striking biogeographic grouping patterns at a global scale, reminiscent of “Wallacean” zoogeographic patterns. This result is surprising, given the global distribution and unprecedented connectivity of humans as hosts and the homogenizing forces of globalization; despite these factors, infectious disease assemblages remain fundamentally constrained in their distributions by ecological barriers to dispersal or establishment. Biogeographic processes thus appear to provide an overarching context in which other factors promoting infectious disease emergence and spread are set. We use outbreaks of Ebola virus to illustrate how such patterns could be leveraged to provide a “head start” or added focus for risk management activities. The distributions of most infectious agents causing disease in humans are poorly resolved or unknown. However, poorly known and unknown agents contribute to the global burden of disease and will underlie many future disease risks. Existing patterns of infectious disease co-occurrence could thus play a critical role in resolving or anticipating current and future disease threats. We analyzed the global occurrence patterns of 187 human infectious diseases across 225 countries and seven epidemiological classes (human-specific, zoonotic, vector-borne, non–vector-borne, bacterial, viral, and parasitic) to show that human infectious diseases exhibit distinct spatial grouping patterns at a global scale. We demonstrate, using outbreaks of Ebola virus as a test case, that this spatial structuring provides an untapped source of prior information that could be used to tighten the focus of a range of health-related research and management activities at early stages or in data-poor settings, including disease surveillance, outbreak responses, or optimizing pathogen discovery. In examining the correlates of these spatial patterns, among a range of geographic, epidemiological, environmental, and social factors, mammalian biodiversity was the strongest predictor of infectious disease co-occurrence overall and for six of the seven disease classes examined, giving rise to a striking congruence between global pathogeographic and “Wallacean” zoogeographic patterns. This clear biogeographic signal suggests that infectious disease assemblages remain fundamentally constrained in their distributions by ecological barriers to dispersal or establishment, despite the homogenizing forces of globalization. Pathogeography thus provides an overarching context in which other factors promoting infectious disease emergence and spread are set.

Phylogeny and provenance affect plant–soil feedbacks in invaded California grasslands

Animal and plant species differ dramatically in their quality as hosts for multi-host pathogens, but the causes of this variation are poorly understood. A group of small mammals, including small rodents and shrews, are among the most competent natural reservoirs for three tick-borne zoonotic pathogens, Borrelia burgdorferi, Babesia microti, and Anaplasma phagocytophilum, in eastern North America. For a group of nine commonly-infected mammals spanning >2 orders of magnitude in body mass, we asked whether life history features or surrogates for (unknown) encounter rates with ticks, predicted reservoir competence for each pathogen. Life history features associated with a fast pace of life generally were positively correlated with reservoir competence. However, a model comparison approach revealed that host population density, as a proxy for encounter rates between hosts and pathogens, generally received more support than did life history features. The specific life history features and the importance of host population density differed somewhat between the different pathogens. We interpret these results as supporting two alternative but non-exclusive hypotheses for why ecologically widespread, synanthropic species are often the most competent reservoirs for multi-host pathogens. First, multi-host pathogens might adapt to those hosts they are most likely to experience, which are likely to be the most abundant and/or frequently bitten by tick vectors. Second, species with fast life histories might allocate less to certain immune defenses, which could increase their reservoir competence. Results suggest that of the host species that might potentially be exposed, those with comparatively high population densities, small bodies, and fast pace of life will often be keystone reservoirs that should be targeted for surveillance or management.