Population structure of the invasive ambrosia beetle,Euwallacea fornicatus,indicates multiple introductions into South Africa

Biological Invasions - The ambrosia beetle Euwallacea fornicatus (Polyphagous Shot Hole Borer; PSHB), native to Asia, was documented in South Africa for the first time in 2012. Death of susceptible...     

Leaf growth rate per unit thermal time follows QTL-dependent daily patterns in hundreds of maize lines under naturally fluctuating conditions

We have analysed daily patterns of leaf elongation rate (LER) in large data sets with 318 genotypes placed in naturally fluctuating temperature and evaporative demand, and examined the effect of targeted alleles on these patterns. The method consisted, firstly, in expressing elongation rate per unit thermal time, so it became temperature independent; secondly, in a joint analysis of diurnal fluctuations of elongation rate and of micrometeorological conditions in several experiments, and finally, in a comparison of daily patterns between groups of genotypes possessing targeted alleles. (1) Conditions for using thermal time at a time step of 15 min were first tested successfully in 318 recombinant inbred lines (RILs) of three mapping populations. (2) An analysis of 1989 time courses revealed a robust daily pattern of LER per unit thermal time (LERth) over several experiments. LERth was constant during the night and was reproducible (for a given RIL) over up to 10 consecutive nights in different experiments. It declined rapidly during the early morning, closely following the daily pattern of transpiration rate. (3) Groups of RILs carrying alleles conferring a high response to temperature had markedly higher night-time plateau of LER than those with low responses. Groups of RILs with high response to evaporative demand had rapid decreases in elongation rate at the transition between night and day, while this decrease was slower in groups of RILs with low response. These results open the way for using kinetics of responses to environmental stimuli as a phenotyping tool in genetic analyses.     

Classification methods for ongoing EEG and MEG signals

Classification algorithms help predict the qualitative properties of a subject's mental state by extracting useful information from the highly multivariate non-invasive recordings of his brain activity. In particular, applying them to Magneto-encephalography (MEG) and electro-encephalography (EEG) is a challenging and promising task with prominent practical applications to e.g. Brain Computer Interface (BCI). In this paper, we first review the principles of the major classification techniques and discuss their application to MEG and EEG data classification. Next, we investigate the behavior of classification methods using real data recorded during a MEG visuomotor experiment. In particular, we study the influence of the classification algorithm, of the quantitative functional variables used in this classifier, and of the validation method. In addition, our findings suggest that by investigating the distribution of classifier coefficients, it is possible to infer knowledge and construct functional interpretations of the underlying neural mechanisms of the performed tasks. Finally, the promising results reported here (up to 97% classification accuracy on 1-second time windows) reflect the considerable potential of MEG for the continuous classification of mental states.     

High intercontinental migration rates and population admixture in the sapstain fungus Ophiostoma ips

Ophiostoma ips is a common fungal associate of various conifer-infesting bark beetles in their native ranges and has been introduced into non-native pine plantations in the Southern Hemisphere. In this study, we used 10 microsatellite markers to investigate the population biology of O. ips in native (Cuba, France, Morocco and USA) and non-native (Australia, Chile and South Africa) areas to characterize host specificity, reproductive behaviour, and the potential origin as well as patterns of spread of the fungus and its insect vectors. The markers resolved a total of 41 alleles and 75 haplotypes. Higher genetic diversity was found in the native populations than in the introduced populations. Based on the origin of the insect vectors, the populations of O. ips in Australia would be expected to reflect a North American origin, and those in Chile and South Africa to reflect a European origin. However, most alleles observed in the native European population were also found in the native North American population; only the allele frequencies among the populations varied. This admixture made it impossible to confirm the origin of the introduced Southern Hemisphere (SH) populations of O. ips. There was also no evidence for specificity of the fungus to particular bark beetle vectors or hosts. Although O. ips is thought to be mainly self-fertilizing, evidence for recombination was found in the four native populations surveyed. The higher genetic diversity in the North American than in the European population suggests that North America could be the possible source region of O. ips.     

Predicted effects of missense mutations on native-state stability account for phenotypic outcome in phenylketonuria, a paradigm of misfolding diseases

Phenylketonuria (PKU) is a genetic disease caused by mutations in human phenylalanine hydroxylase (PAH). Most missense mutations result in misfolding of PAH, increased protein turnover, and a loss of enzymatic function. We studied the prediction of the energetic impact on PAH native-state stability of 318 PKU-associated missense mutations, using the protein-design algorithm FoldX. For the 80 mutations for which expression analyses have been performed in eukaryote systems, in most cases we found substantial overall correlations between the mutational energetic impact and both in vitro residual activities and patient metabolic phenotype. This finding confirmed that the decrease in protein stability is the main molecular pathogenic mechanism in PKU and the determinant for phenotypic outcome. Metabolic phenotypes have been shown to be better predicted than in vitro residual activities, probably because of greater stringency in the phenotyping process. Finally, all the remaining 238 PKU missense mutations compiled at the PAH locus knowledgebase (PAHdb) were analyzed, and their phenotypic outcomes were predicted on the basis of the energetic impact provided by FoldX. Residues in exons 7-9 and in interdomain regions within the subunit appear to play an important structural role and constitute hotspots for destabilization. FoldX analysis will be useful for predicting the phenotype associated with rare or new mutations detected in patients with PKU. However, additional factors must be considered that may contribute to the patient phenotype, such as possible effects on catalysis and interindividual differences in physiological and metabolic processes.     

Biofilm Cohesiveness Measurement Using a Novel Atomic Force Microscopy Methodology

Biofilms can be undesirable, as in those covering medical implants, and beneficial, such as when they are used for waste treatment. Because cohesive strength is a primary factor affecting the balance between growth and detachment, its quantification is essential in understanding, predicting, and modeling biofilm development. In this study, we developed a novel atomic force microscopy (AFM) method for reproducibly measuring, in situ, the cohesive energy levels of moist 1-day biofilms. The biofilm was grown from an undefined mixed culture taken from activated sludge. The volume of biofilm displaced and the corresponding frictional energy dissipated were determined as a function of biofilm depth, resulting in the calculation of the cohesive energy. Our results showed that cohesive energy increased with biofilm depth, from 0.10 ± 0.07 nJ/μm³ to 2.05 ± 0.62 nJ/μm³. This observation was reproducible, with four different biofilms showing the same behavior. Cohesive energy also increased from 0.10 ± 0.07 nJ/μm³ to 1.98 ± 0.34 nJ/μm³ when calcium (10 mM) was added to the reactor during biofilm cultivation. These results agree with previous reports on calcium increasing the cohesiveness of biofilms. This AFM-based technique can be performed with available off-the-shelf instrumentation. It could therefore be widely used to examine biofilm cohesion under a variety of conditions.