Expected trends and surprises in the Lateglacial and Holocene vegetation history of the Iberian Peninsula and Balearic Islands

Recent, high-resolution palaeoecological records are changing the traditional picture of post-glacial vegetation succession in the Iberian Peninsula. In addition to the influence of Lateglacial and Early Holocene climatic changes, other factors are critical in the course of vegetation development and we observe strong regional differences. The floristic composition, location and structure of glacial tree populations and communities may have been primary causes of vegetation development. Refugial populations in the Baetic cordilleras would have been a source, but not the only one, for the early Lateglacial oak expansions. From Mid to Late Holocene, inertial, resilient, and rapid responses of vegetation to climatic change are described, and regional differences in the response are stressed. The role of fire, pastoralism, agriculture, and other anthropogenic disturbances (such as mining), during the Copper, Bronze, Iberian, and Roman times, is analysed. The implications of ecological transitions in cultural changes, especially when they occur as societal collapses, are discussed.     

Architecture and function of metallopeptidase catalytic domains

The cleavage of peptide bonds by metallopeptidases (MPs) is essential for life. These ubiquitous enzymes participate in all major physiological processes, and so their deregulation leads to diseases ranging from cancer and metastasis, inflammation, and microbial infection to neurological insults and cardiovascular disorders. MPs cleave their substrates without a covalent intermediate in a single‐step reaction involving a solvent molecule, a general base/acid, and a mono‐ or dinuclear catalytic metal site. Most monometallic MPs comprise a short metal‐binding motif (HEXXH), which includes two metal‐binding histidines and a general base/acid glutamate, and they are grouped into the zincin tribe of MPs. The latter divides mainly into the gluzincin and metzincin clans. Metzincins consist of globular ～130–270‐residue catalytic domains, which are usually preceded by N‐terminal pro‐segments, typically required for folding and latency maintenance. The catalytic domains are often followed by C‐terminal domains for substrate recognition and other protein–protein interactions, anchoring to membranes, oligomerization, and compartmentalization. Metzincin catalytic domains consist of a structurally conserved N‐terminal subdomain spanning a five‐stranded β‐sheet, a backing helix, and an active‐site helix. The latter contains most of the metal‐binding motif, which is here characteristically extended to HEXXHXXGXX(H,D). Downstream C‐terminal subdomains are generally shorter, differ more among metzincins, and mainly share a conserved loop—the Met‐turn—and a C‐terminal helix. The accumulated structural data from more than 300 deposited structures of the 12 currently characterized metzincin families reviewed here provide detailed knowledge of the molecular features of their catalytic domains, help in our understanding of their working mechanisms, and form the basis for the design of novel drugs.     

Drug2ways: Reasoning over causal paths in biological networks for drug discovery

Elucidating the causal mechanisms responsible for disease can reveal potential therapeutic targets for pharmacological intervention and, accordingly, guide drug repositioning and discovery. In essence, the topology of a network can reveal the impact a drug candidate may have on a given biological state, leading the way for enhanced disease characterization and the design of advanced therapies. Network-based approaches, in particular, are highly suited for these purposes as they hold the capacity to identify the molecular mechanisms underlying disease. Here, we present drug2ways, a novel methodology that leverages multimodal causal networks for predicting drug candidates. Drug2ways implements an efficient algorithm which reasons over causal paths in large-scale biological networks to propose drug candidates for a given disease. We validate our approach using clinical trial information and demonstrate how drug2ways can be used for multiple applications to identify: i) single-target drug candidates, ii) candidates with polypharmacological properties that can optimize multiple targets, and iii) candidates for combination therapy. Finally, we make drug2ways available to the scientific community as a Python package that enables conducting these applications on multiple standard network formats.     

Reproducibility and Consistency of Proteomic Experiments on Natural Populations of a Non-Model Aquatic Insect

Population proteomics has a great potential to address evolutionary and ecological questions, but its use in wild populations of non-model organisms is hampered by uncontrolled sources of variation. Here we compare the response to temperature extremes of two geographically distant populations of a diving beetle species (Agabus ramblae) using 2-D DIGE. After one week of acclimation in the laboratory under standard conditions, a third of the specimens of each population were placed at either 4 or 27°C for 12 h, with another third left as a control. We then compared the protein expression level of three replicated samples of 2–3 specimens for each treatment. Within each population, variation between replicated samples of the same treatment was always lower than variation between treatments, except for some control samples that retained a wider range of expression levels. The two populations had a similar response, without significant differences in the number of protein spots over- or under-expressed in the pairwise comparisons between treatments. We identified exemplary proteins among those differently expressed between treatments, which proved to be proteins known to be related to thermal response or stress. Overall, our results indicate that specimens collected in the wild are suitable for proteomic analyses, as the additional sources of variation were not enough to mask the consistency and reproducibility of the response to the temperature treatments.