TBEV Core

What are the main subtypes and lineages of TBEV?

TBEV is classified into several major subtypes with distinct geographic distributions and evolutionary histories. Current phylogenetic analyses identify the following primary subtypes:

• Eastern subtypes:

  • Far-Eastern (TBEV-FE)

  • Siberian (TBEV-Sib)

  • East-Siberian/Baikalean/886-84-like (TBEV-Bkl-2)

• Western subtypes:

  • European (TBEV-Eur)

  • Western European lineage

• Other distinct lineages:

  • Himalayan (TBEV-Him)

  • Baikalean-1 (TBEV-Bkl-1, strain 178-79)

  • N5-17 strain

Each subtype exhibits characteristic molecular properties and epidemiological patterns. The Far-Eastern and Siberian subtypes typically associate with Ixodes persulcatus tick vectors, while the European subtype primarily transmits through Ixodes ricinus .

How is TBEV phylogenetic classification conducted methodologically?

Modern TBEV classification employs a multi-step process:

• Genome sequence collection from public databases (e.g., NCBI GenBank)

• Multiple sequence alignment using tools like MAFFT v7.453

• Maximum likelihood (ML) phylogeny inference with iq-tree, employing ultrafast bootstrap replicates

• Classification based on distinguishing subtype- or lineage-specific monophyletic clades

• Extraction of unique 3′UTR variants within each subtype and lineage

Researchers should exclude vaccine strains, highly cell-passaged specimens, and artificially modified sequences to ensure accurate classification. For comprehensive analysis, metadata including location, date of collection, and host species should be incorporated .

What does the TBEV molecular clock reveal about virus evolution?

Timed phylogenetic trees provide critical insights into TBEV evolution. Analysis using the TBEVnext platform reveals estimated times of the most recent common ancestor (TMRCA) for different TBEV clades:

Phylogeographic analyses suggest TBEV originated in Central Russia approximately 2,700 years ago, subsequently spreading eastward (forming TBEV-Sib and TBEV-FE lineages) and westward into Europe. The deep splits of Western types with TMRCAs approximately 1,000–1,500 years ago suggest TBEV may have arrived in Central Europe earlier than previously theorized .

How do researchers account for variable evolutionary rates across TBEV subtypes?

• Different TBEV subtypes likely evolve at divergent rates

• Simple timed trees serve as approximations rather than definitive evolutionary timelines

• More computationally intensive Bayesian approaches may provide greater accuracy for subtype-specific evolutionary rates

Researchers should interpret molecular clock data with caution, considering them as proxies that align with established TBEV tree topologies and divergence patterns. For precise evolutionary rate calculations, subtype-specific analyses using Bayesian methods are recommended .

What methods are effective for determining TBEV structure at high resolution?

Single-particle imaging (SPI) using X-ray free-electron lasers (XFELs) represents a promising technique for high-resolution TBEV structure determination. The methodological approach includes:

• Sample preparation: Purified TBEV particles in random orientations

• Exposure to femtosecond X-ray pulses focused on individual virus specimens

• Collection of 2D diffraction patterns before sample destruction

• Computational reconstruction of 3D virus structure from multiple 2D patterns

Critical experimental parameters for successful SPI at facilities like European XFEL include:

• Optimal incident photon flux

• Appropriate sample-to-detector distance

• Effective data analysis pipeline for structure reconstruction

This technique allows researchers to capture the virus structure in its native state without crystallization requirements .

What computational approaches are used for TBEV structure reconstruction from diffraction data?

Structure reconstruction from SPI experiments requires sophisticated algorithms:

• Data preprocessing to filter noise and normalize intensities

• Orientation determination of virus particles from 2D diffraction patterns

• Phasing algorithms to recover structural information

• 3D reconstruction through iterative refinement

Existing platforms like those developed by Bobkov et al. (2020) provide specialized tools for TBEV structure determination. The reconstruction process may incorporate a priori knowledge of virus orientations to improve accuracy, though more advanced approaches can work without such information .

Researchers should consider experimental limitations including background signal interference, orientation determination challenges, and radiation damage effects when planning structural studies .

How does the TBEVnext platform facilitate molecular epidemiology research?

TBEVnext (available at https://nextstrain.org/groups/ViennaRNA/TBEVnext) is an interactive visualization tool that provides comprehensive phylogeographic analysis of TBEV. The platform's research applications include:

• Visualization of global TBEV spread across geographical regions

• Tracking evolutionary relationships between TBEV strains

• Examination of host/vector associations across different virus lineages

• Estimation of divergence times for different TBEV subtypes

The platform incorporates 225+ TBEV strains encompassing all subtypes and lineages, with fine-grained geographic location labeling that enables sub-national analysis of strain distribution. This is particularly valuable for studying diverse subtype presence in extended regions like the Russian Federation .

What is the clusteron approach and how is it applied to TBEV analysis?

The clusteron approach, implemented in the TBEV Analyzer platform, provides hierarchical phylogenetic classification:

• First level: Subtype classification (Far-Eastern, European, etc.)

• Second level: Phylogenetic lineage determination

• Third level: Clusteron identification

A clusteron represents a group of TBEV strains sharing identical amino acid sequences in the glycoprotein E fragment. These strains typically demonstrate phylogeographic proximity and characteristic territorial distribution patterns .

The TBEV Analyzer integrates with GenBank data and provides enhanced visualization including:

• Phylogenetic tree generation

• Geographic map visualization

• Heat map distribution of TBEV strains

• Detailed analysis reports

This approach is particularly valuable for public health surveillance, enabling researchers to track the spread and evolution of TBEV strains at multiple hierarchical levels.

What conserved RNA structural elements characterize the TBEV genome?

TBEV genomes contain evolutionarily conserved RNA elements, particularly in the 3′UTR regions. These structures are identified through:

• Multiple sequence alignment of full-length TBEV genomes

• RNA family model analysis using infernal covariance models (CMs)

• Realignment of uncovered regions with locARNA

• Consensus structure prediction using RNAalifold and RNALalifold

The conservation patterns of these RNA structures vary between TBEV subtypes, providing insight into functional constraints and adaptation mechanisms. Researchers investigating these elements should focus on regions with covariant mutations that maintain secondary structure despite sequence variation .

How do host-vector relationships influence TBEV subtype evolution?

TBEV subtypes demonstrate varying degrees of vector specialization, though this relationship is not absolute:

• Eastern subtypes (Far-Eastern, Siberian) primarily transmit via Ixodes persulcatus

• Western subtypes (European) typically transmit through Ixodes ricinus

Analysis of 225 full genome isolates reveals exceptions to these patterns:

• Nine Ixodes persulcatus-derived isolates collected between 1971-2009 in Russia carried the European subtype

• Two Ixodes ricinus ticks were found to carry the Siberian subtype

These exceptions suggest complex evolutionary dynamics and potential host switching events. Researchers should consider both the predominant vector associations and these exceptions when studying TBEV transmission and epidemiology.

What are the key methodological challenges in TBEV comparative genomics?

Researchers face several challenges when conducting comparative genomic analyses of TBEV:

• Sampling bias: Current genomic databases contain geographical and temporal sampling disparities

• Sequence quality: Variable sequence quality and completeness affect alignment and phylogenetic inference

• Metadata limitations: Incomplete or inconsistent metadata hampers epidemiological analysis

• Evolutionary rate heterogeneity: Assumption of constant evolutionary rates may distort timing estimates

• Host adaptation signatures: Detecting selection pressures in different host environments requires sophisticated statistical approaches

To address these challenges, researchers should:

• Implement rigorous sequence quality filtering

• Apply Bayesian approaches for evolutionary rate estimation

• Conduct sensitivity analyses with different methodological parameters

• Collaborate on standardized metadata collection protocols

How can integration of structural and evolutionary data enhance TBEV research?

An integrative approach combining structural and evolutionary analyses offers significant advantages:

• Correlating conserved RNA structures with evolutionary constraints

• Identifying structure-function relationships across TBEV subtypes

• Mapping antigenic variation onto structural models to inform vaccine development

• Linking structural features to host adaptation mechanisms

Methodologically, this requires:

• Alignment of homologous structural elements across diverse TBEV strains

• Mapping of sequence conservation onto structural models

• Application of evolutionary algorithms that incorporate structural constraints

• Integration of laboratory experimental data with computational predictions

The development of platforms that unite structural data from techniques like SPI with evolutionary analyses from TBEVnext represents a promising direction for comprehensive TBEV research .