Species identity, diversity and microbial carbon flow in reassembling macrobenthic communities

Intense disturbance may locally destroy patches of habitat and shape the landscape into a mosaic of reassembling communities. The development of ecosystem properties during such community reassembly is poorly understood. In intertidal bare sediments, trophic relations between microphytobenthos or heterotrophic bacteria and macrofauna invertebrates may guarantee fundamental ecosystem properties such as carbon flow through the food web. We studied the dynamic relation between reassembling macrofauna communities and such microbial carbon flow during recovery after severe disturbance. We deliberately induced prolonged hypoxia in winter and early summer and allowed recolonisation for periods of two and five months. Carbon flow was quantified from basal resources (microphytobenthos and bacteria) to intermediate consumers using ¹³C as a tracer. Within the period of study (5 months), microbial carbon flow fully recovered, although macrofauna diversity was still very low compared to the natural communities (ranging from 6 to 17 species). More than 90% of microbial carbon flow to macrofauna was due to the consumers that recolonised within two months. Two of these species were dominant contributors to microphytobenthos carbon transfer to fauna. Furthermore, at an early stage of reassembly, this ecosystem property was remarkably similar when disturbance took place at different times of the year (winter or early summer), although there were differences in assemblage composition and functional diversity. We conclude that species assemblages and ecosystem function developed relatively independently in this benthic system. We discuss which ecological factors may have caused such non-parallel development of macrofaunal communities and carbon flow.     

Inhibition of net nitrification activity in a Mediterranean woodland: possible role of chemicals produced by Arbutus unedo

Nitrification is a key biological process for the control of soil NO₃ ^? availability and N losses from terrestrial ecosystems. The study investigates the causes for the absence of net nitrification activity in the soil of a Mediterranean monospecific woodland of Arbutus unedo, focusing in particular on the possible role of chemicals produced by this plant. The mineral N pool, net rates of mineralization and nitrification were measured in the soil top 10 cm over 18 months. Raw extracts of leaves and roots of Arbutus unedo and soil underneath Arbutus plant canopy were purified using chromatographic techniques and the structure of chemicals was defined using spectroscopic and spectrometric methods. Leaf extracts (raw, aqueous and organic fractions) were tested for their toxicity on net nitrification, using a test soil. Field and laboratory incubations showed soil NO₃ ^? concentration below the detection limit over the whole study period, despite the significant NH₄ ⁺ availability. Toxicity tests indicated that more than 400 μg of extract g^?1 dry soil were needed to have more than 50% reduction of net NO₃ ^? production. Gallocatechin and catechin were among the most abundant chemicals in the extracts of leaves, roots and soil. Their soil concentration was significantly higher than the annual calculated input via leaf litter, and it was in the range of toxic concentrations, as deduced from the dose-response curve of the toxicity test. Data support the hypothesis that plant produced chemicals might be involved in the limited net nitrate production in this Mediterranean woodland.

     

Predicting protein pKa by environment similarity

A statistical method to predict protein pK_a has been developed by using the 3D structure of a protein and a database of 434 experimental protein pK_a values. Each pK_a in the database is associated with a fingerprint that describes the chemical environment around an ionizable residue. A computational tool, MoKaBio, has been developed to identify automatically ionizable residues in a protein, generate fingerprints that describe the chemical environment around such residues, and predict pK_a from the experimental pK_a values in the database by using a similarity metric. The method, which retrieved the pK_a of 429 of the 434 ionizable sites in the database correctly, was crossvalidated by leave‐one‐out and yielded root mean square error (RMSE) = 0.95, a result that is superior to that obtained by using the Null Model (RMSE 1.07) and other well‐established protein pK_a prediction tools. This novel approach is suitable to rationalize protein pK_a by comparing the region around the ionizable site with similar regions whose ionizable site pK_a is known. The pK_a of residues that have a unique environment not represented in the training set cannot be predicted accurately, however, the method offers the advantage of being trainable to increase its predictive power. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

Identification and characterization of protease inhibitors in Diplotaxis species

PCR analysis of the genomes of two wild Brassicaceae plants, Diplotaxis muralis and Diplotaxis tenuifolia, demonstrated the presence of several genes coding for potential protease inhibitors, classifiable within the mustard inhibitor family (MSI). This is a small family of plant protease inhibitors named after the mustard trypsin inhibitor MTI-2, the first protease inhibitor characterized in Brassicaceae. From identified sequences two recombinant inhibitors were expressed in Pichia pastoris. In comparison with MTI-2, they show a reduced activity against bovine trypsin. However, when tested against trypsin-like proteases present in the guts of Helicoverpa zea larvae, the Diplotaxis inhibitors and MTI-2 show similar activities, indicating that the usually adopted procedure of reporting activity of plant protease inhibitors against bovine trypsin may lead to wrong estimation of their effect on insect proteases. This issue is of particular relevance when planning the use of PI genes for developing insect resistant plants.