Emerging human infectious diseases of aquatic origin: a comparative biogeographic approach using Bayesian spatial modelling.

BACKGROUND: With the increase in unprecedented and unpredictable disease outbreaks due to human-driven environmental changes in recent years, we need new analytical tools to map and predict the spatial distribution of emerging infectious diseases and identify the biogeographic drivers underpinning their emergence. The aim of the study was to identify and compare the local and global biogeographic predictors such as landscape and climate that determine the spatial structure of leptospirosis and Buruli Ulcer (BU). METHODS: We obtained 232 hospital-confirmed leptospirosis (2007-2017) cases and 236 BU cases (1969-2017) in French Guiana. We performed non-spatial and spatial Bayesian regression modeling with landscape and climate predictor variables to characterize the spatial structure and the environmental drivers influencing the distribution of the two diseases. RESULTS: Our results show that the distribution of both diseases is spatially dependent on environmental predictors such as elevation, topological wetness index, proximity to cropland and increasing minimum temperature at the month of potential infection. However, the spatial structure of the two diseases caused by bacterial pathogens occupying similar aquatic niche was different. Leptospirosis was widely distributed across the territory while BU was restricted to the coastal riverbeds. CONCLUSIONS: Our study shows that a biogeographic approach is an effective tool to identify, compare and predict the geographic distribution of emerging diseases at an ecological scale which are spatially dependent to environmental factors such as topography, land cover and climate.

Causes and consequences of habitat fragmentation in river networks.

Increases in river fragmentation globally threaten freshwater biodiversity. Rivers are fragmented by many agents, both natural and anthropogenic. We review the distribution and frequency of these major agents, along with their effects on connectivity and habitat quality. Most fragmentation research has focused on terrestrial habitats, but theories and generalizations developed in terrestrial habitats do not always apply well to river networks. For example, terrestrial habitats are usually conceptualized as two-dimensional, whereas rivers often are conceptualized as one-dimensional or dendritic. In addition, river flow often leads to highly asymmetric effects of barriers on habitat and permeability. New approaches tailored to river networks can be applied to describe the network-wide effects of multiple barriers on both connectivity and habitat quality. The net effects of anthropogenic fragmentation on freshwater biodiversity are likely underestimated, because of time lags in effects and the difficulty of generating a single, simple signal of fragmentation that applies to all aquatic species. We conclude by presenting a decision tree for managing freshwater fragmentation, as well as some research horizons for evaluating fragmented riverscapes.

Systems biology: leading the revolution in ecotoxicology.

The rapid development of new technologies such as transcriptomics, proteomics, and metabolomics (Omics) are changing the way ecotoxicology is practiced. The data deluge has begun with genomes of over 65 different aquatic species that are currently being sequenced, and many times that number with at least some level of transcriptome sequencing. Integrating these top-down methodologies is an essential task in the field of systems biology. Systems biology is a biology-based interdisciplinary field that focuses on complex interactions in biological systems, with the intent to model and discover emergent properties of the system. Recent studies demonstrate that Omics technologies provide valuable insight into ecotoxicity, both in laboratory exposures with model organisms and with animals exposed in the field. However, these approaches require a context of the whole animal and population to be relevant. Powerful approaches using reverse engineering to determine interacting networks of genes, proteins, or biochemical reactions are uncovering unique responses to toxicants. Modeling efforts in aquatic animals are evolving to interrelate the interacting networks of a system and the flow of information linking these elements. Just as is happening in medicine, systems biology approaches that allow the integration of many different scales of interaction and information are already driving a revolution in understanding the impacts of pollutants on aquatic systems.