Recurrent fish kills in the Spanish Alfacs Bay (NW Mediterranean) have been detected during winter seasons since 1994, and were attributed to an unarmored, ichthyotoxic, dinoflagellate, initially identified as Gyrodinium corsicum Paulmier, Berland, Billard, & Nezan. Several strains were isolated from the bay and their clonal cultures were compared by combined techniques, including light and electron microscopy, internal transcribed spacer and 5.8S rDNA nucleotide sequencing, and HPLC pigment analyses, together with studies of their photochemical performance, growth rates, and toxicity. Using phylogenetic analyses, all strains were identified as members of the genus Karlodinium, but they were separated into two genetically distinct groups. These groups, identified as Karlodinium veneficum (Ballantine) J. Larsen and K. armiger Bergholtz, Daugbjerg et. Moestrup, were also supported by the other techniques used. Detailed analyses of fine structural characteristics (including plug-like structures in amphiesma and a possible layer of semi-opaque material beneath the outer membrane) allowed discrimination of the mentioned two species. Specific differences in pigment patterns coincided with that expected for low-(K. veneficum) and high-light (K. armiger) adapted relatives. The higher photosynthetic efficiency of K. veneficum and the longer reactivation times of the PSII reaction centers observed for K. armiger were in agreement with this hypothesis. The two species differed in toxicity, but the strains used always induced mortality when incubated with bivalves, rotifers, and finfish. Compared with K. armiger, strains of K. veneficum yielded higher cell densities, but had lower growth rates.

In recent years, numerous biocomputational tools have been designed to extract functional and evolutionary information from multiple sequence alignments (MSAs) of proteins and genes. Most biologists working actively on the characterization of proteins from a single or family perspective use the MSA analysis to retrieve valuable information about amino acid conservation and the functional role of residues in query protein(s). In MSAs, adjustment of alignment parameters is a key point to improve the quality of MSA output. However, this issue is frequently underestimated and/or misunderstood by scientists and there is no in-depth knowledge available in this field. This brief review focuses on biocomputational approaches complementary to MSA to help distinguish functional residues in protein families. These additional analyses involve issues ranging from phylogenetic to statistical, which address the detection of amino acids pivotal for protein function at any level. In recent years, a large number of tools has been designed for this very purpose. Using some of these relevant, useful tools, we have designed a practical pipeline to perform in silico studies with a view to improving the characterization of family proteins and their functional residues. This review-guide aims to present biologists a set of specially designed tools to study proteins. These tools are user-friendly as they use web servers or easy-to-handle applications. Such criteria are essential for this review as most of the biologists (experimentalists) working in this field are unfamiliar with these biocomputational analysis approaches.

Apicomplexa are an extremely diverse group of unicellular organisms that infect humans and other animals. Despite the great advances in combating infectious diseases over the past century, these parasites still have a tremendous social and economic burden on human societies, particularly in tropical and subtropical regions of the world. Proteases from apicomplexa have been characterized at the molecular and cellular levels, and central roles have been proposed for proteases in diverse processes. In this work, 16 new genes encoding for trypsin proteases are identified in 8 apicomplexan genomes by a genome-wide survey. Phylogenetic analysis suggests that these genes were gained through both intracellular gene transfer and vertical gene transfer. Identification, characterization and understanding of the evolutionary origin of protease-mediated processes are crucial to increase the knowledge and improve the strategies for the development of novel chemotherapeutic agents and vaccines.