Bacterial community dynamics in spontaneous sourdoughs made from wheat, spelt, and rye wholemeal flour.

Sourdough fermentation is a traditional process that is used to improve bread quality. A spontaneous sourdough ecosystem consists of a mixture of flour and water that is fermented by endogenous lactic acid bacteria (LAB) and yeasts. The aim of this study was to identify bacterial diversity during backslopping of spontaneous sourdoughs prepared from wheat, spelt, or rye wholemeal flour. Culture-dependent analyses showed that the number of LAB (109  CFU/ml) was higher by three orders of magnitude than the number of yeasts (106  CFU/ml), irrespective of the flour type. These results were complemented by next-generation sequencing of the 16S rDNA V3 and V4 variable regions. The dominant phylum in all sourdough samples was Firmicutes, which was represented exclusively by the Lactobacillales order. The two remaining and less abundant phyla were Proteobacteria and Bacteroidetes. The culture-independent approach allowed us to detect changes in microbial ecology during the 72-hr fermentation period. Weissella sp. was the most abundant genus after 24 hr of fermentation of the rye sourdough, but as the process progressed, its abundance decreased in favor of the Lactobacillus genus similarly as in wheat and spelt sourdoughs. The Lactobacillus genus was dominant in all sourdoughs after 72 hr, which was consistent with our results obtained using culture-dependent analyses. This work was carried out to determine the microbial biodiversity of sourdoughs that are made from wheat, spelt, and rye wholemeal flour and can be used as a source of strains for specific starter cultures to produce functional bread.

Host-parasite interactions and ecology of the malaria parasite-a bioinformatics approach.

Malaria remains one of the highest mortality infectious diseases. Malaria is caused by parasites from the genus Plasmodium. Most deaths are caused by infections involving Plasmodium falciparum, which has a complex life cycle. Malaria parasites are extremely well adapted for interactions with their host and their host's immune system and are able to suppress the human immune system, erase immunological memory and rapidly alter exposed antigens. Owing to this rapid evolution, parasites develop drug resistance and express novel forms of antigenic proteins that are not recognized by the host immune system. There is an emerging need for novel interventions, including novel drugs and vaccines. Designing novel therapies requires knowledge about host-parasite interactions, which is still limited. However, significant progress has recently been achieved in this field through the application of bioinformatics analysis of parasite genome sequences. In this review, we describe the main achievements in 'malarial' bioinformatics and provide examples of successful applications of protein sequence analysis. These examples include the prediction of protein functions based on homology and the prediction of protein surface localization via domain and motif analysis. Additionally, we describe PlasmoDB, a database that stores accumulated experimental data. This tool allows data mining of the stored information and will play an important role in the development of malaria science. Finally, we illustrate the application of bioinformatics in the development of population genetics research on malaria parasites, an approach referred to as reverse ecology.

Metagenomic Analysis of Some Potential Nitrogen-Fixing Bacteria in Arable Soils at Different Formation Processes.

The main goal of the study was to determine the diversity of the potential nitrogen-fixing (PNF) bacteria inhabiting agricultural (A) soils versus wastelands serving as controls (C). The soils were classified into three groups based on the formation process: autogenic soils (Albic Luvisols, Brunic Arenosols, Haplic Phaeozem) formed on loess material, hydrogenic soils (Mollic Gleysols, Eutric Fluvisol, Eutric Histosol) formed under the effect of stagnant water and lithogenic soils (Rendzina Leptosols) formed on limestone. In order to determine the preferable conditions for PNF bacteria, the relationships between the soil chemical features and bacterial operational taxonomic units (OTUs) were tested. Additionally, the nitrogen content and fertilisation requirement of the lithogenic (LG), autogenic (AG) and hydrogenic (HG) soils were discussed. The composition of the bacterial communities was analysed with the next-generation sequencing (NGS) by the Ion Torrent™ technology. The sequences were clustered into OTU based on a 99 % similarity threshold. The arable soils tested were distinctly dominated by ß-Proteobacteria representatives of PNF bacteria belonging to the genus Burkholderia. Bacteria from the α-Proteobacteria class and Devosia genus were subdominants. A free-living Cyanobacteria population dominated in A rather than in C soils. We have found that both soil agricultural management and soil formation processes are the most conducive factors for PNF bacteria, as a majority of these microorganisms inhabit the AG group of soils, whilst the LG soils with the lowest abundance of PNF bacteria revealed the need for additional mineral fertilisation. Our studies have also indicated that there are close relationships between soil classification with respect to soil formation processes and PNF bacteria preference for occupation of soil niches.