Evolutionary Analysis of Inter-Farm Transmission Dynamics in a Highly Pathogenic Avian Influenza Epidemic

Phylogenetic studies have largely contributed to better understand the emergence, spread and evolution of highly pathogenic avian influenza during epidemics, but sampling of genetic data has never been detailed enough to allow mapping of the spatiotemporal spread of avian influenza viruses during a single epidemic. Here, we present genetic data of H7N7 viruses produced from 72% of the poultry farms infected during the 2003 epidemic in the Netherlands. We use phylogenetic analyses to unravel the pathways of virus transmission between farms and between infected areas. In addition, we investigated the evolutionary processes shaping viral genetic diversity, and assess how they could have affected our phylogenetic analyses. Our results show that the H7N7 virus was characterized by a high level of genetic diversity driven mainly by a high neutral substitution rate, purifying selection and limited positive selection. We also identified potential reassortment in the three genes that we have tested, but they had only a limited effect on the resolution of the inter-farm transmission network. Clonal sequencing analyses performed on six farm samples showed that at least one farm sample presented very complex virus diversity and was probably at the origin of chronological anomalies in the transmission network. However, most virus sequences could be grouped within clearly defined and chronologically sound clusters of infection and some likely transmission events between farms located 0.8–13 Km apart were identified. In addition, three farms were found as most likely source of virus introduction in distantly located new areas. These long distance transmission events were likely facilitated by human-mediated transport, underlining the need for strict enforcement of biosafety measures during outbreaks. This study shows that in-depth genetic analysis of virus outbreaks at multiple scales can provide critical information on virus transmission dynamics and can be used to increase our capacity to efficiently control epidemics

Quantifying predictors for the spatial diffusion of avian influenza virus in China

BACKGROUND: Avian influenza virus (AIV) causes both severe outbreaks and endemic disease among poultry and has caused sporadic human infections in Asia, furthermore the routes of transmission in avian species between geographic regions can be numerous and complex. Using nucleotide sequences from the internal protein coding segments of AIV, we performed a Bayesian phylogeographic study to uncover regional routes of transmission and factors predictive of the rate of viral diffusion within China. RESULTS: We found that the Central area and Pan-Pearl River Delta were the two main sources of AIV diffusion, while the East Coast areas especially the Yangtze River delta, were the major targets of viral invasion. Next we investigated the extent to which economic, agricultural, environmental and climatic regional data was predictive of viral diffusion by fitting phylogeographic discrete trait models using generalised linear models. CONCLUSIONS: Our results highlighted that the economic-agricultural predictors, especially the poultry population density and the number of farm product markets, are the key determinants of spatial diffusion of AIV in China; high human density and freight transportation are also important predictors of high rates of viral transmission; Climate features (e.g. temperature) were correlated to the viral invasion in the destination to some degree; while little or no impacts were found from natural environment factors (such as surface water coverage). This study uncovers the risk factors and enhances our understanding of the spatial dynamics of AIV in bird populations. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12862-016-0845-3) contains supplementary material, which is available to authorized users

Epidemic reconstruction in a Phylogenetics framework:Transmission trees as partitions of the node set

The reconstruction of transmission trees for epidemics from genetic data has been the subject of some recent interest. It has been demonstrated that the transmission tree structure can be investigated by augmenting internal nodes of a phylogenetic tree constructed using pathogen sequences from the epidemic with information about the host that held the corresponding lineage. In this paper, we note that this augmentation is equivalent to a correspondence between transmission trees and partitions of the phylogenetic tree into connected subtrees each containing one tip, and provide a framework for Markov Chain Monte Carlo inference of phylogenies that are partitioned in this way, giving a new method to co-estimate both trees. The procedure is integrated in the existing phylogenetic inference package BEAST.Comment: 40 pages, 3 figure

On the dynamics of the adenylate energy system: homeorhesis vs homeostasis.

Biochemical energy is the fundamental element that maintains both the adequate turnover of the biomolecular structures and the functional metabolic viability of unicellular organisms. The levels of ATP, ADP and AMP reflect roughly the energetic status of the cell, and a precise ratio relating them was proposed by Atkinson as the adenylate energy charge (AEC). Under growth-phase conditions, cells maintain the AEC within narrow physiological values, despite extremely large fluctuations in the adenine nucleotides concentration. Intensive experimental studies have shown that these AEC values are preserved in a wide variety of organisms, both eukaryotes and prokaryotes. Here, to understand some of the functional elements involved in the cellular energy status, we present a computational model conformed by some key essential parts of the adenylate energy system. Specifically, we have considered (I) the main synthesis process of ATP from ADP, (II) the main catalyzed phosphotransfer reaction for interconversion of ATP, ADP and AMP, (III) the enzymatic hydrolysis of ATP yielding ADP, and (IV) the enzymatic hydrolysis of ATP providing AMP. This leads to a dynamic metabolic model (with the form of a delayed differential system) in which the enzymatic rate equations and all the physiological kinetic parameters have been explicitly considered and experimentally tested in vitro. Our central hypothesis is that cells are characterized by changing energy dynamics (homeorhesis). The results show that the AEC presents stable transitions between steady states and periodic oscillations and, in agreement with experimental data these oscillations range within the narrow AEC window. Furthermore, the model shows sustained oscillations in the Gibbs free energy and in the total nucleotide pool. The present study provides a step forward towards the understanding of the fundamental principles and quantitative laws governing the adenylate energy system, which is a fundamental element for unveiling the dynamics of cellular life

Profiling of diet-induced neuropeptide changes in rat brain by quantitative mass spectrometry.

Neuropeptides are intercellular signal transmitters that play key roles in modulation of many behavioral and physiological processes. Neuropeptide signaling in several nuclei in the hypothalamus contributes to the control of food intake. Additionally, food intake regulation involves neuropeptide signaling in the reward circuitry in the striatum. Here, we analyze neuropeptides extracted from hypothalamus and striatum from rats in four differentially treated dietary groups including a high-fat/high-sucrose diet, mimicking diet-induced obesity. We employ high-resolution tandem mass spectrometry using higher-energy collision dissociation and electron transfer dissociation fragmentation for sensitive identification of more than 1700 unique endogenous peptides, including virtually all key neuropeptides known to be involved in food intake regulation. Label-free quantification of differential neuropeptide expression revealed comparable upregulation of orexigenic and anorexigenic neuropeptides in rats that were fed on a high-fat/high-sucrose diet