Phylogenetic analysis and assessment of the pathogenic potential of the first H9N2 avian influenza viruses isolated from wild birds and Lagoon water in Tunisia.

H9N2 avian influenza virus (AIV) has been isolated from various species of wild birds and domestic poultry worldwide. It has been reported since the late 1990s, that H9N2 AIV has infected humans as reported in some Asian and North African countries. This subtype has already been circulating and constituting a serious threat to the poultry industry in Tunisia back in 2009. To investigate zoonotic potential and pathogenicity of H9N2 AIV in chickens and mice in Tunisia, five strains have been isolated during the period from 2014 to 2018. Samples were withdrawn from several wild bird species and environment (Lagoon water) of Maamoura and Korba Lagoons as well as Kuriat Island. Phylogenetic analyzes demonstrated that the isolated H9N2 strains belonged to the G1-like sublineage and were close to AIV H9N2 poultry viruses from North Africa, West Africa and the Middle East. All strains carried in their hemagglutinin the residue 226 L, which is an important marker for avian-to-human viral transmission. The hemagglutinin cleavage site has several motifs: PSKSSR/G, PARSSR/G and HARSSR/G. The neuraminidase showed S372A and R403W substitutions that have been previously detected in H3N2 and H2N2 viruses that were reported in human pandemics. Many mutations associated with mammalian infections have been detected in internal proteins. Pathogenicity evaluation in chickens showed that GF/14 replicates effectively in the lungs, tracheas, spleens, kidneys and brains and that it was transmitted among contact chickens. However, GHG/18 replicates poorly in chickens and has not an efficient transmission in contact chickens. GF/14 and GHG/18 could not kill mice though they replicated in their respiratory tract and caused a significant body weight loss (p < 0.05). This study highlights the importance of H9N2 AIV monitoring in both migratory birds and the environment to prevent virus transmission to humans.

How does evolutionary variation in Basal metabolic rates arise? A statistical assessment and a mechanistic model.

Metabolic rates are related to the pace of life. Hence, research into their variability at global scales is of vital importance for several contemporary theories in physiology, ecology, and evolution. Here we evaluated the effect of latitude, climate, primary productivity, habitat aridity, and species trophic habits, on mass-independent basal metabolic rates (BMRs) for 195 rodent species. The aims of this article were twofold. First, we evaluated the predictive power of different statistical models (via a model selection approach), using a dimensional reduction technique on the exogenous factor matrix to achieve a clear interpretation of the selected models. Second, we evaluated three specific predictions derived from a recently proposed hypothesis, herein called the "obligatory heat" model (OHM), for the evolution of BMR. Obtained results indicate that mean/minimum environmental temperature, rainfall/primary productivity and, finally, species trophic habits are, in this order, the major determinants of mass-independent BMR. Concerning the mechanistic causes behind this variation, obtained data agree with the predictions of the OHM: (1) mean annual environmental temperature was the best single predictor of residual variation in BMR, (2) herbivorous species have greater mass-independent metabolic rates, and tend to be present at high-latitude cold environments, than species in other trophic categories.

Inferring parameters shaping amino acid usage in prokaryotic genomes via Bayesian MCMC methods.

Molar content of guanine plus cytosine (G + C) and optimal growth temperature (OGT) are main factors characterizing the frequency distribution of amino acids in prokaryotes. Previous work, using multivariate exploratory methods, has emphasized ascertainment of biological factors underlying variability between genomes, but the strength of each identified factor on amino acid content has not been quantified. We combine the flexibility of the phylogenetic mixed model (PMM) with the power of Bayesian inference via Markov Chain Monte Carlo (MCMC) methods, to obtain a novel evolutionary picture of amino acid usage in prokaryotic genomes. We implement a Bayesian PMM which incorporates the feature that evolutionary history makes observed data interdependent. As in previous studies with PMM, we present a variance partition; however, attention is also given to the posterior distribution of "systematic effects" that may shed light about the relative importance of and relationships between evolutionary forces acting at the genomic level. In particular, we analyzed influences of G + C, OGT, and respiratory metabolism. Estimates of G + C effects were significant for amino acids coded by G + C or molar content of adenine plus thymine (A + T) in first and second bases. OGT had an important effect on 12 amino acids, probably reflecting complex patterns of protein modifications, to cope with varying environments. The effect of respiratory metabolism was less clear, probably due to the already reported association of G + C with aerobic metabolism. A "heritability" parameter was always high and significant, reinforcing the importance of accommodating phylogenetic relationships in these analyses. "Heritable" component correlations displayed a pattern that tended to cluster "pure" G + C (A + T) in first and second codon positions, suggesting an inherited departure from linear regression on G + C.