Protein reutilisation in corms of Colchicum autumnale

Colchicum autumnale L. is a monocotyledonous geophyte with hysteranthous leaves, i.e. flowering and leaf growth occur in different time periods. Because after the starch, the second prominent storage compound of corm is represented by proteins, we were interested in nitrogen remobilisation during the annual life cycle of C. autumnale. In this context the content of soluble and insoluble proteins were measured in parallel with determination of some exo-and endopeptidase activities. Our results indicate that the continual proteolysis occurs in both mother and new daughter corms during the whole life-cycle of the plant. L-Ala-aminopeptidase and trypsin-like endopeptidase were the most active peptidases in both mother and daughter corms. As the protein level of mother corm did not change significantly during the development of the future above-ground part under the soil surface (the first, autumnal developmental stage), the developmental profile of nitrate reductase activity was estimated followed by evaluation of total nitrogen and amino acid contents. Significant activity of root nitrate reductase was detected in the roots only in the second, vernal stage. Our results showed that the stored proteins constituted a relevant nitrogen source partly required by the growth processes of the late autumnal stage, but mainly by the intensive growth of leaves and reproductive structures during the second, photosynthetically active stage of the life-cycle.     

Bioinformatics analysis of bacteriophage and prophage endolysin domains

Endolysins as a class of antibacterial enzymes are expected to become a very useful tool for many purposes to control spreading of, e.g., multiresistant bacteria in different environments. Their antimicrobial properties could be broadened or altered by mutagenesis, domain swapping or gene shuffling. Therefore, the specific designing of endolysins to achieve their desired properties is challenging. This work is focused on the in silico analysis of protein domains presence in sequences of phage and prophage endolysins, followed by the study of variety of domain combinations in the individual endolysin types. The multiple sequence alignment of endolysin sequences revealed the recognition of sequence types with typical domain arrangement and conserved amino acids, divided according to the target substrate in bacterial cell walls. The five protein families of catalytic domains are specifically occurring in dependence of bacterial Gram-type. The presence, types and numbers of binding domains within endolysin sequences were also studied. The obtained results enable a more targeted design of endolysins with required antimicrobial properties.     

Tissue Specific Electrochemical Fingerprinting

Background

Proteomics and metalloproteomics are rapidly developing interdisciplinary fields providing enormous amounts of data to be classified, evaluated and interpreted. Approaches offered by bioinformatics and also by biostatistical data analysis and treatment are therefore of extreme interest. Numerous methods are now available as commercial or open source tools for data processing and modelling ready to support the analysis of various datasets. The analysis of scientific data remains a big challenge, because each new task sets its specific requirements and constraints that call for the design of a targeted data pre-processing approach.

Methodology/Principal Findings

This study proposes a mathematical approach for evaluating and classifying datasets obtained by electrochemical analysis of metallothionein in rat 9 tissues (brain, heart, kidney, eye, spleen, gonad, blood, liver and femoral muscle). Tissue extracts were heated and then analysed using the differential pulse voltammetry Brdicka reaction. The voltammograms were subsequently processed. Classification models were designed making separate use of two groups of attributes, namely attributes describing local extremes, and derived attributes resulting from the level = 5 wavelet transform.

Conclusions/Significance

On the basis of our results, we were able to construct a decision tree that makes it possible to distinguish among electrochemical analysis data resulting from measurements of all the considered tissues. In other words, we found a way to classify an unknown rat tissue based on electrochemical analysis of the metallothionein in this tissue.