Tick-borne encephalitis virus (TBEV) is transmitted to vertebrates by taiga or forest ticks through bites, inducing disease of variable severity. The reasons underlying these differences in the severity of the disease are unknown. In order to identify genetic factors affecting the pathogenicity of virus strains, we have sequenced and compared the complete genomes of 34 Far-Eastern subtype (FE) TBEV strains isolated from patients with different disease severity (Primorye, the Russian Far East). We analyzed the complete genomes of 11 human pathogenic strains isolated from the brains of dead patients with the encephalitic form of the disease (Efd), 4 strains from the blood of patients with the febrile form of TBE (Ffd), and 19 strains from patients with the subclinical form of TBE (Sfd). On the phylogenetic tree, pathogenic Efd strains formed two clusters containing the prototype strains, Senzhang and Sofjin, respectively. Sfd strains formed a third separate cluster, including the Oshima strain. The strains that caused the febrile form of the disease did not form a separate cluster. In the viral proteins, we found 198 positions with at least one amino acid residue substitution, of which only 17 amino acid residue substitutions were correlated with the variable pathogenicity of these strains in humans and they authentically differed between the groups. We considered the role of each amino acid substitution and assumed that the deletion of 111 amino acids in the capsid protein in combination with the amino acid substitutions R16K and S45F in the NS3 protease may affect the budding process of viral particles. These changes may be the major reason for the diminished pathogenicity of TBEV strains. We recommend Sfd strains for testing as attenuation vaccine candidates.

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The methods for data presentation are important in bioinformatics as data processing algorithms. The article describes the software package for the extensive analysis of tables with estimates of bacterial abundance levels in environmental samples. The package was designed to be executed in a distributed hardware environment, with powerful packages in Python in the backend and interactive front-end forms. Most of microbial ecology-specific functionality is implemented by the scikit-bio Python package, together with the other Python packages intended for big data analysis. Interactive visualisation tools are implemented by the D3.js software library, therefore, the software project is named D3b. The package is a suite of tools for the analysis of microbial ecology data implemented as a web-service and as a desktop application. It supports a substantial part of the graphical and analytical descriptions of microbial communities used in scientific publications. Source codes are available at github (sferanchuk/d3b_charts) and the on-line version of the system is accessible at d3b-charts.bri-shur.com.

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In recent years, a large scale ecological crisis has been observed in the Lake Baikal ecosystem. It is clearly shown by several signs, including the mass disease of sponges in the coastal zone. To investigate the causes of the crisis, the composition of symbiotic communities in sponges was investigated in 2015 by sequencing of the 16S rRNA gene in three locations of the lake. The methods of fractal theory were adopted in order to detect a fractal structure in the distribution of the sequencing reads, being considered as fragments of the 16S rRNA gene for individual bacteria within the collected samples. The fractal-like distributions were constructed for the seven most abundant phylotypes, and the observed properties of the distributions reflect microevolution processes within the selected genera and species. The values of the fractal dimension, evaluated for the distributions, are observed to correlate with an anthropogenic load at the place of sample collection, for the Flavobacterium and Synechococcus genera. The sampling sites were also observed to be associated with the properties of the distributions for chloroplasts of Trebouxiophyceae algae, the endosymbiont of Lubomirskia baicalensis sponge.The long-scale time dependency of fractal dimension was also evaluated for the data from temperature detectors in four locations of Lake Baikal. The values of the fractal dimension for fluctuations of temperature are also observed to be associated with an anthropogenic load in the place of measurement. The consistency of both approaches validates the usefulness of fractal-based methods in the interpretation of the experiments designed to study the ecological crisis in Lake Baikal.

Background: The study of ecosystems of the great lakes is important as observations can be extended to ecosystems of larger scale. The ecological crisis of Lake Baikal needs investigations to discover the molecular mechanisms involved in the crisis. The disease of Baikal sponges is one of the processes resulting in the degradation of the littoral zone of the lake. Methods: The chloroplast genome fragment for the algae endosymbiont of Baikal sponge was assembled from metagenomic sequencing data. The distributions of polymorphic sites were obtained for the genome fragment, separately for samples from healthy sponge, diseased sponge and dead sponge tissues. Results: The comparative analysis of chloroplast genome sequences suggests that the symbiotic algae from Baikal sponge is close to Choricystis genus of unicellular algae. Also, the distributions of polymorphic sites allowed detection of the signs of extensive mutations in the chloroplasts isolated from the diseased sponge tissues. Conclusions: The study demonstrate the particular case of evolution at the molecular level due to the conditions of a severe crisis of a whole ecosystem in Lake Baikal. The detection of adaptive mutations in the chloroplast genome is an important feature which could represent the behavior of an ecosystem in the event of a severe crisis.

Background: Monitoring and investigating the ecosystem of the great lakes provide a thorough background when forecasting the ecosystem dynamics at a greater scale. Nowadays, changes in the Baikal lake biota require a deeper investigation of their molecular mechanisms. Understanding these mechanisms is especially important, as the endemic Baikal sponge disease may cause a degradation of the littoral ecosystem of the lake. Methods: The chloroplast genome fragment for the algae endosymbiont of the Baikal sponge was assembled from metagenomic sequencing data. The distributions of the polymorphic sites were obtained separately for the genome fragments from healthy, diseased and dead sponge tissues. Results: The distribution of polymorphic sites allows for the detection of the signs of extensive mutations in the chloroplasts isolated from the diseased sponge tissues. Additionally, the comparative analysis of chloroplast genome sequences suggests that the symbiotic algae from Baikal sponge is close to the Choricystis genus of unicellular algae. Conclusions: Mutations observed in the chloroplast genome could be interpreted as signs of rapid adaptation processes in the symbiotic algae. The development of sponge disease is still expanding in Baikal, but an optimistic prognoses regarding a development of the disease is nevertheless considered.