Currently, the lowest formal taxon in virus classification is species; however, unofficial lower-level units are commonly used in everyday work. Tick-borne encephalitis virus (TBEV) is a species of mammalian tick-borne flaviviruses that may cause encephalitis. Many known representatives of TBEV are grouped into subtypes, mostly according to their phylogenetic relationship. However, the emergence of novel sequences could dissolve this phylogenetic grouping; in the absence of strict quantitative criterion, it may be hard to define the borders of the first TBEV taxonomic unit below the species level. In this study, the nucleotide/amino-acid space of all known TBEV sequences was analyzed. Amino-acid sequence p-distances could not reliably distinguish TBEV subtypes. Viruses that differed by less than 10% of nucleotides in the polyprotein-coding gene belonged to the same subtype. At the same time, more divergent viruses were representatives of different subtypes. According to this distance criterion, TBEV species may be divided into seven subtypes: TBEV-Eur, TBEV-Sib, TBEV-FE, TBEV-2871 (TBEV-Ob), TBEV-Him, TBEV-178-79 (TBEV-Bkl-1), and TBEV-886-84 (TBEV-Bkl-2).

Rheumatoid arthritis (RA) is a systemic inflammatory joint disease affecting about 1% of the population worldwide. Current treatment approaches do not ensure a cure for every patient. Moreover, classical regimens are based on nontargeted systemic immune suppression and have significant side effects. Biological treatment has advanced considerably but efficacy and specificity issues remain. Gene therapy is one of the potential future directions for RA therapy, which is rapidly developing. Several gene therapy trials done so far have been of moderate success, but experimental and genetics studies have yielded novel targets. As a result, the arsenal of gene therapy tools keeps growing. Currently, both viral and nonviral delivery systems are used for RA therapy. Herein, we review recent approaches for RA gene therapy.

Tick-borne encephalitis (TBE) is one of the most important viral zoonosis transmitted by the bite of infected ticks. In this study, all tick-borne encephalitis virus (TBEV) E gene sequences available in GenBank as of June 2019 with known date of isolation (n = 551) were analyzed. Simulation studies showed that a sample bias could significantly affect earlier studies, because small TBEV datasets (n = 50) produced non-overlapping intervals for evolutionary rate estimates. An apparent lack of a temporal signal in TBEV, in general, was found, precluding molecular clock analysis of all TBEV subtypes in one dataset. Within all subtypes and most of the smaller groups in these subtypes, there was evidence of many medium- and long-distance virus transfers. These multiple random events may play a key role in the virus spreading. For some groups, virus diversity within one territory was similar to diversity over the whole geographic range. This is best exemplified by the virus diversity observed in Switzerland or Czech Republic. These two countries yielded most of the known European subtype Eu3 subgroup sequences, and the diversity of viruses found within each of these small countries is comparable to that of the whole Eu3 subgroup, which is prevalent all over Central and Eastern Europe. Most of the deep tree nodes within all three established TBEV subtypes dated less than 300 years back. This could be explained by the recent emergence of most of the known TBEV diversity. Results of bioinformatics analysis presented here, together with multiple field findings, suggest that TBEV may be regarded as an emerging disease.

The viral family Coronaviridae comprises four genera, termed Alpha-, Beta-, Gamma-, and Deltacoronavirus. Recombination events have been described in many coronaviruses infecting humans and other animals. However, formal analysis of the recombination patterns, both in terms of the involved genome regions and the extent of genetic divergence between partners, are scarce. Common methods of recombination detection based on phylogenetic incongruences (e.g., a phylogenetic compatibility matrix) may fail in cases where too many events diminish the phylogenetic signal. Thus, an approach comparing genetic distances in distinct genome regions (pairwise distance deviation matrix) was set up. In alpha, beta, and delta-coronaviruses, a low incidence of recombination between closely related viruses was evident in all genome regions, but it was more extensive between the spike gene and other genome regions. In contrast, avian gammacoronaviruses recombined extensively and exist as a global cloud of genes with poorly corresponding genetic distances in different parts of the genome. Spike, but not other structural proteins, was most commonly exchanged between coronaviruses. Recombination patterns differed between coronavirus genera and corresponded to the modular structure of the spike: recombination traces were more pronounced between spike domains (N-terminal and C-terminal parts of S1 and S2) than within domains. The variability of possible recombination events and their uneven distribution over the genome suggest that compatibility of genes, rather than mechanistic or ecological limitations, shapes recombination patterns in coronaviruses.

Noroviruses infect a wide range of mammals and are the major cause of gastroenteritis in humans. Recombination at the junction of ORF1 encoding nonstructural proteins and ORF2 encoding major capsid protein VP1 is a well-known feature of noroviruses. Using all available complete norovirus sequences, we systematically analyzed patterns of natural recombination in the genus Norovirus both throughout the genome and across the genogroups. Recombination events between nonstructural (ORF1) and structural genomic regions (ORF2 and ORF3) were found in all analyzed genogroups of noroviruses, although recombination was most prominent between members of GII, the most common genogroup that infects humans. The half-life times of recombinant forms (clades without evidence of recombination) of human GI and GII noroviruses were 10.4 and 8.4–11.3 years, respectively. There was evidence of many recent recombination events, and most noroviruses that differed by more than 18% of nucleotide sequence were recombinant relative to each other. However, there were no distinct recombination events between viruses that differed by over 42% in ORF2/3, consistent with the absence of systematic recombination between different genogroups. The few inter-genogroup recombination events most likely occurred between ancient viruses before they diverged into contemporary genogroups. The recombination events within ORF1 or between ORF2/3 were generally rare. Thus, noroviruses routinely exchange full structural and nonstructural blocks of the genome, providing a modular evolution.

Statistical phylogenetic methods are a powerful tool for inferring the evolutionary history of viruses through time and space. The selection of mathematical models and analysis parameters has a major impact on the outcome, and has been relatively well-described in the literature. The preparation of a sequence dataset is less formalized, but its impact can be even more profound. This article used simulated datasets of enterovirus sequences to evaluate the effect of sample bias on picornavirus phylogenetic studies. Possible approaches to the reduction of large datasets and their potential for introducing additional artefacts were demonstrated. The most consistent results were obtained using “smart sampling”, which reduced sequence subsets from large studies more than those from smaller ones in order to preserve the rare sequences in a dataset. The effect of sequences with technical or annotation errors in the Bayesian framework was also analyzed. Sequences with about 0.5% sequencing errors or incorrect isolation dates altered by just 5 years could be detected by various approaches, but the efficiency of identification depended upon sequence position in a phylogenetic tree. Even a single erroneous sequence could profoundly destabilize the whole analysis by increasing the variance of the inferred evolutionary parameters.