The new COST Action European Venom Network (EUVEN)—synergy and future perspectives of modern venomics

Venom research is a highly multidisciplinary field that involves multiple subfields of biology, informatics, pharmacology, medicine, and other areas. These different research facets are often technologically challenging and pursued by different teams lacking connection with each other. This lack of coordination hampers the full development of venom investigation and applications. The COST Action CA19144–European Venom Network was recently launched to promote synergistic interactions among different stakeholders and foster venom research at the European level

Modern venomics – Current insights, novel methods and future perspectives in biological and applied animal venom research

Venoms have evolved >100 times in all major animal groups, and their components, known as toxins, have been fine-tuned over millions of years into highly effective biochemical weapons. There are many outstanding questions on the evolution of toxin arsenals, such as how venom genes originate, how venom contributes to the fitness of venomous species, and which modifications at the genomic, transcriptomic, and protein level drive their evolution. These questions have received particularly little attention outside of snakes, cone snails, spiders, and scorpions. Venom compounds have further become a source of inspiration for translational research using their diverse bioactivities for various applications. We highlight here recent advances and new strategies in modern venomics and discuss how recent technological innovations and multi-omic methods dramatically improve research on venomous animals. The study of genomes and their modifications through CRISPR and knockdown technologies will increase our understanding of how toxins evolve and which functions they have in the different ontogenetic stages during the development of venomous animals. Mass spectrometry imaging combined with spatial transcriptomics, in situ hybridization techniques, and modern computer tomography gives us further insights into the spatial distribution of toxins in the venom system and the function of the venom apparatus. All these evolutionary and biological insights contribute to more efficiently identify venom compounds, which can then be synthesized or produced in adapted expression systems to test their bioactivity. Finally, we critically discuss recent agrochemical, pharmaceutical, therapeutic, and diagnostic (so-called translational) aspects of venoms from which humans benefit

Potential pitfalls of modelling ribosomal RNA data in phylogenetic tree reconstruction: Evidence from case studies in the Metazoa

<p>Abstract</p> <p>Background</p> <p>Failure to account for covariation patterns in helical regions of ribosomal RNA (rRNA) genes has the potential to misdirect the estimation of the phylogenetic signal of the data. Furthermore, the extremes of length variation among taxa, combined with regional substitution rate variation can mislead the alignment of rRNA sequences and thus distort subsequent tree reconstructions. However, recent developments in phylogenetic methodology now allow a comprehensive integration of secondary structures in alignment and tree reconstruction analyses based on rRNA sequences, which has been shown to correct some of these problems. Here, we explore the potentials of RNA substitution models and the interactions of specific model setups with the inherent pattern of covariation in rRNA stems and substitution rate variation among loop regions.</p> <p>Results</p> <p>We found an explicit impact of RNA substitution models on tree reconstruction analyses. The application of specific RNA models in tree reconstructions is hampered by interaction between the appropriate modelling of covarying sites in stem regions, and excessive homoplasy in some loop regions. RNA models often failed to recover reasonable trees when single-stranded regions are excessively homoplastic, because these regions contribute a greater proportion of the data when covarying sites are essentially downweighted. In this context, the RNA6A model outperformed all other models, including the more parametrized RNA7 and RNA16 models.</p> <p>Conclusions</p> <p>Our results depict a trade-off between increased accuracy in estimation of interdependencies in helical regions with the risk of magnifying positions lacking phylogenetic signal. We can therefore conclude that caution is warranted when applying rRNA covariation models, and suggest that loop regions be independently screened for phylogenetic signal, and eliminated when they are indistinguishable from random noise. In addition to covariation and homoplasy, other factors, like non-stationarity of substitution rates and base compositional heterogeneity, can disrupt the signal of ribosomal RNA data. All these factors dictate sophisticated estimation of evolutionary pattern in rRNA data, just as other molecular data require similarly complicated (but different) corrections.</p

How does silicon lead the kinetics of the galvanizing reaction to lose its solid-solid character

The galvanizing reaction is very sensitive to alloying elements of steel. Therefore when industrial processes are considered the method is trying to counterbalance the influence of alloying elements in the steel by adding Al, Ni, Mn in the zinc bath. Although Si is often considered by steelmakers as necessary for killing and improving the mechanical properties of steel, it is usually undesirable by galvanizers because the reactivity of steel with zinc dramatically changes with % Si. This phenomenon is best illustrated by the thickness of the coating versus % Si which presents a sharp maximum near 0.08% Si and a minimum near 0.20% Si. This phenomenon discovered by Sandelin (1941) has not yet received any uncontroversial interpretation. In the present studies, we compared the morphologies and kinetics obtained in the same conditions for different silicon contents and we specially considered the coating obtained for small times of immersion. It is shown that in all cases, the first intermetallic phase which appears is [MATH]. The experimental analysis of the compounds as well as thermodynamical calculations prove that the solubility of Si in [MATH] is negligible but of about 1 at.% in [MATH]. Moreover, thermodynamical evaluation of Gibbs free energy of Fe-Zn liquid shows that, if zinc diffusion in substrate is negligible, [MATH] is in a metastable equilibrium at 450°C with the liquid containing about 7% Fe, which corresponds to the [MATH] compound. Our modelling shows that for Sandelin steels, the fist stage of the reaction is not driven by diffusion of Fe in solid phases but in the liquid, leading to a linear variation of the reaction with time t. In a second stage the kinetics obeys a [MATH] law and corresponds to the solid state diffusion observed for hypo-Sandelin steel. The diffusion paths across liquid domains introduce supplementary degrees of freedom in the morphologies of the coating which then corresponds to numerous equilibria and pseudo-equilibria