The LC8 family members of dynein light chains (DYNLL1 and DYNLL2 in vertebrates) are highly conserved ubiquitous eukaryotic homodimer proteins that interact, besides dynein and myosin 5a motor proteins, with a large (and still incomplete) number of proteins involved in diverse biological functions. Despite an earlier suggestion that LC8 light chains function as cargo adapters of the above molecular motors, they are now recognized as regulatory hub proteins that interact with short linear motifs located in intrinsically disordered protein segments. The most prominent LC8 function is to promote dimerization of their binding partners that are often scaffold proteins of various complexes, including the intermediate chains of the dynein motor complex. Structural and functional aspects of this intriguing hub protein will be highlighted in this minireview.

Aminoacyl tRNA synthetases (aaRS) are grouped into Class I and II based on primary and tertiary structure and enzyme properties suggesting two independent phylogenetic lineages. Analogously, tRNA molecules can also form two respective classes, based on the class membership of their corresponding aaRS. Although some aaRS–tRNA interactions are not extremely specific and require editing mechanisms to avoid misaminoacylation, most aaRS–tRNA interactions are rather stereospecific. Thus, class-specific aaRS features could be mirrored by class-specific tRNA features. However, previous investigations failed to detect conserved class-specific nucleotides. Here we introduce a discrete mathematical approach that evaluates not only class-specific ‘strictly present’, but also ‘strictly absent’ nucleotides. The disjoint subsets of these elements compose a unique partition, named extended consensus partition (ECP). By analyzing the ECP for both Class I and II tDNA sets from 50 (13 archaeal, 30 bacterial and 7 eukaryotic) species, we could demonstrate that class-specific tRNA sequence features do exist, although not in terms of strictly conserved nucleotides as it had previously been anticipated. This finding demonstrates that important information was hidden in tRNA sequences inaccessible for traditional statistical methods. The ECP analysis might contribute to the understanding of tRNA evolution and could enrich the sequence analysis tool repertoire.

Staphylococcosis is one of the most important infectious diseases in rabbit medicine, especially in commercial farming. Previous studies revealed the existence of virulent variants adapted to rabbits. Typical and atypical, highly virulent as well as low virulent variants have been isolated and reported from industrial units in all major rabbit-meat-producing countries. Preceding the research focused on detecting defined nucleotide sequences, the genome of these organisms as a whole was rarely subjected to scientific investigations. The authors sequenced 51 Staphylococcus strains originating from industrial rabbit farms in Hungary. Another 12 draft genomes of rabbit isolates were constructed from read sequences available in digital repositories, and were compared based on whole-genome multilocus sequence typing. The clonal origin of highly virulent variants is confirmed, the strains from Hungary were closely related with the strains isolated in the UK, Italy, and Spain. Atypical highly virulent strains are the most prevalent in Hungary, they form a separate clonal cluster. The low virulent strains were genetically similar, but more heterogeneous than the highly virulent (HV) and aHV strains even by the traditional MLST typing scheme. Other “non-aureus” Staphylococcus species were also identified.

The recently published discrete mathematical method, extended consensus partition (ECP), identifies nucleotide types at each position that are strictly absent from a given sequence set, while occur in other sets. These are defined as discriminating elements (DEs). In this study using the ECP approach, we mapped potential hidden identity elements that discriminate the 20 different tRNA identities. We filtered the tDNA data set for the obligatory presence of well-established tRNA features, and then separately for each identity set, the presence of already experimentally identified strictly present identity elements. The analysis was performed on the three kingdoms of life. We determined the number of DE, e.g. the number of sets discriminated by the given position, for each tRNA position of each tRNA identity set. Then, from the positional DE numbers obtained from the 380 pairwise comparisons of the 20 identity sets, we calculated the average excluding value (AEV) for each tRNA position. The AEV provides a measure on the overall discriminating power of each position. Using a statistical analysis, we show that positional AEVs correlate with the number of already identified identity elements. Positions having high AEV but lacking published identity elements predict hitherto undiscovered tRNA identity elements.