Recombinant Apple stem pitting virus Capsid protein (ORF5)

Basic Research Questions

• What is the genomic organization of Apple stem pitting virus and where does the capsid protein fit?

  The ASPV genome comprises approximately 9,300 nucleotides with five open reading frames (ORFs). The genomic structure includes ORF1 encoding the replication-related protein containing methyltransferase, helicase, and RNA-dependent RNA polymerase motifs; ORFs 2-4 encoding the triple gene block movement proteins (TGBp1-3); and ORF5 encoding the coat protein (CP) of approximately 42-44 kDa . A hypothetical ORF6 overlapping ORF5 has been reported, potentially encoding a product of 119 amino acids with no known function, though it remains unclear whether this is expressed in vivo . The genome includes 5' and 3' untranslated regions (UTRs) and a poly(A) tail at the 3' end .

• How do ASPV isolates cluster phylogenetically based on capsid protein sequences?

  Phylogenetic analysis of ASPV CP sequences reveals grouping patterns correlated with host origin (apple, pear, and Korla pear) . Specifically, ASPV isolates from pear can be divided into six evolutionary divergent subgroups (A-F) based on CP sequences . Two subgroups (B and F) were identified in newer studies . Multiple alignment analysis indicates continuous nucleotide insertions or deletions in CP of ASPV pear isolates . The CP variants from different subgroups have different CP sizes due to amino acid insertions or deletions in the N-terminal portion of CP . This phylogenetic clustering suggests host-driven adaptations have affected genetic diversification of ASPV CP variants .

• What methods are most effective for detecting and analyzing ASPV CP genetic diversity?

  Reverse transcription polymerase chain reaction (RT-PCR) has been reported to be more effective than enzyme-linked immunosorbent assay (ELISA) for ASPV detection . For detecting ASPV in diverse samples, researchers should consider:

  • Using multiple primer pairs, as demonstrated in studies where some isolates failed to amplify with common primers but were detected with alternative primers

  • Employing high-throughput RNA sequencing for comprehensive viral genome characterization

  • Implementing Single-Strand Conformation Polymorphism (SSCP) analysis to identify sequence variants

  • Analyzing recombination events using specialized software like Recombination Detection Program (RDP4)

  For cloning and sequencing, the use of pGEM-T cloning vectors with blue-white screening methods has proven effective . Due to the high genetic diversity of ASPV, primers need continuous reassessment to ensure they remain sensitive and specific for all virus variants .

• How do different ASPV CP variants affect serological detection?

  Recombinant CPs expressed in Escherichia coli BL21 (DE3) demonstrate varying levels of serological reactivity to anti-ASPV antibodies . In one study, six CP variants belonging to different subgroups showed different levels of serological reactivity to three anti-ASPV antibodies . This variability in serological detection presents significant challenges for routine testing procedures, as recombination can lead to the generation of new viral progeny that may remain undetected . The difference in antibody binding may be attributed to structural variations in the CP resulting from amino acid substitutions, insertions, or deletions, particularly in epitope regions .

Intermediate Research Questions

• What are the functional differences among ASPV CP variants?

  ASPV CP variants exhibit several functional differences:

  • Aggregation ability: Fusion CPs with Yellow Fluorescent Protein (YFP-CPs) expressed in N. benthamiana cells differ in their ability to form aggregates

  • Serological reactivity: CP variants show different levels of reactivity to anti-ASPV antibodies

  • Symptom induction: Different ASPV isolates induce varying biological symptoms on the herbaceous host N. occidentalis

  • Conserved VSR activity: Despite amino acid differences, all six CP variants studied showed similar viral suppressor of RNA silencing (VSR) activity when expressed in PVX vector

  These functional differences suggest that while some CP functions (like VSR activity) are conserved across variants, others (like aggregation) may be influenced by structural differences resulting from sequence variations .

• How can recombination events in ASPV CP be accurately detected and analyzed?

  Recombination detection in ASPV CP requires multiple complementary approaches:

  1. Software-based detection: Use RDP4 (Recombination Detection Program) implementing multiple methods including RDP, GENECONV, Chimaera, MaxChi, BootScan, SiScan, and 3Seq

  2. Statistical validation: Consider recombination events significant if supported by at least 5-6 different methods with an associated P-value < 0.05

  3. Phylogenetic evidence: Confirm recombination through phylogenetic analysis showing incongruencies in tree topology

  4. Split network analysis: Perform split decomposition analysis with software like SplitsTree4 to represent ambiguous signals that may indicate recombination

  5. Visual inspection: Analyze sequence alignments for abrupt changes in sequence similarity patterns

  Recombination events have been detected in both CP and TGB sequences, with studies identifying specific recombinants such as FS06-2, X5-2, and XLF-C-2 for CP, and TH2-5, X8-2, FS05-2, X6-2 and XLF-A-1 for TGB from Chinese apple isolates .

• What experimental design is optimal for expressing recombinant ASPV CP variants?

  Based on successful studies, an optimal experimental design for expressing recombinant ASPV CP variants includes:

  For E. coli expression:

  • Cloning CP genes into expression vectors with His-tags for purification

  • Expression in E. coli BL21 (DE3) induced by IPTG

  • Purification using standard methods for His-tagged proteins

  For in planta expression:

  • Agrobacterium-mediated infiltration (agroinfiltration) to express YFP-ASPV-CPs in N. benthamiana

  • Using a PVX vector for expressing CP variants in N. occidentalis

  • Employing confocal microscopy to detect YFP-ASPV-CPs fluorescence and study aggregation patterns

  For gene amplification and cloning:

  • Total RNA extraction from infected plant material

  • RT-PCR with optimized primers specific to the CP region

  • Cloning into pMD18-T simple vector or pGEM-T cloning vector

  • Verification through restriction digestion and sequencing

• How does the nucleotide diversity pattern vary across the ASPV genome, and what does this tell us about CP evolution?

  The nucleotide diversity index (π) varies significantly across the ASPV genome, with specific patterns in the CP region. In one study of GRSPaV (a related virus), the hypervariable region (HVR) showed the highest diversity, while the CP region exhibited moderate diversity . This pattern suggests:

  • Different regions of the viral genome experience varying evolutionary pressures

  • The CP gene maintains a balance between conservation (to preserve essential functions) and variation (to adapt to host defenses)

  • Recombination events may contribute to localized increases in diversity

  The diversity index can be calculated using software like DnaSP with a sliding window approach (100 nucleotides moved by steps of 25 nucleotides) . For ASPV specifically, studies have shown the CP gene is under negative selection, suggesting functional constraints despite the observed diversity . The variation pattern in CP sequences may reflect both adaptation to different host species and the need to maintain core functional properties.

Advanced Research Questions

• What are the selection pressures acting on ASPV CP variants and how do they shape evolutionary trajectories?

  Selection pressures on ASPV CP variants involve a complex interplay of factors:

  • Negative (purifying) selection: Studies suggest ASPV CP genes are predominantly under negative selection, indicating functional constraints

  • Positive selection: Some amino acid positions show evidence of positive selection, particularly within isolates, which may drive diversification

  • Host adaptation: Selection pressures may differ between apple and pear hosts, contributing to host-specific variants

  • Deletion patterns: Phylogenetic analyses show that isolates classify according to deletion patterns rather than host species, suggesting deletions play a significant role in clade diversification

  • Quasispecies dynamics: Significant levels of variability within individual hosts support a quasispecies population structure, allowing rapid adaptation to changing environments

  These selection pressures, combined with mutation, genetic drift, and recombination, collectively shape the ASPV population structure . The balance between these forces determines the evolutionary trajectory of CP variants and may influence virulence, host range, and adaptation to new environments.

• How can we differentiate between selection and genetic drift in ASPV CP sequence evolution?

  Differentiating between selection and genetic drift in ASPV CP evolution requires multiple analytical approaches:

  1. dN/dS ratio analysis: Calculate the ratio of non-synonymous to synonymous substitutions. Ratios significantly different from 1 indicate selection (>1 for positive selection, <1 for negative selection)

  2. Population genetic analyses: Conduct analyses to detect variation among isolates from different hosts, between isolates from the same host species, and within isolates

  3. Site-specific selection tests: Use methods like Fixed Effects Likelihood (FEL) and Single Likelihood Ancestor Counting (SLAC) to identify specific amino acid positions under selection

  4. Tajima's D test: Determine whether sequences are evolving neutrally or under selection by comparing two measures of genetic diversity

  5. Statistical tests for genetic differentiation: Apply these between populations to identify patterns inconsistent with neutral evolution

  Studies have found significant variation among ASPV isolates from pear and apple trees, between isolates from the same host species, and within isolates, supporting that selection might be an important force driving diversification .

• What methodologies are most effective for resolving the quasispecies structure of ASPV populations?

  Resolving ASPV quasispecies structure requires a combination of experimental and computational approaches:

  Experimental methods:

  • Deep sequencing: High-throughput RNA sequencing provides comprehensive coverage of viral population diversity

  • Single-Strand Conformation Polymorphism (SSCP): Identifies sequence variants at various genome positions

  • Cloning and sequencing multiple variants: Essential for capturing the diversity within individual hosts

  Computational analyses:

  • Variant calling pipelines: Specialized for viral quasispecies from next-generation sequencing data

  • Population genetic analyses: To quantify variation within and between isolates

  • Phylogenetic network analysis: Using SplitsTree4 to visualize complex evolutionary relationships

  Sampling strategies:

  • Multiple samples from the same host plant

  • Samples from different plant tissues

  • Temporal sampling to track population changes

  Studies have demonstrated significant levels of variability within individual hosts, supporting the existence of quasispecies population structure in ASPV . This approach has revealed that mutations, drift, selection pressure, and recombination collectively shape the ASPV population structure, with quasispecies populations seemingly uncorrelated with host species but associated with symptom severity .

• How do recombination and insertion/deletion events interact to drive ASPV CP evolution?

  Recombination and insertion/deletion (indel) events interact in complex ways to drive ASPV CP evolution:

  Recombination patterns:

  • Recombination is prevalent in the CP gene of ASPV

  • Multiple distinct recombination breakpoints have been identified

  • Recombination events can give rise to new virus isolates with potentially altered properties

  Insertion/deletion patterns:

  • CP variants differ in the length, number, and arrangement of deletions

  • 17 ASPV molecular variants with different deletion patterns have been identified

  • Phylogenetic analyses show isolates classify according to deletion patterns rather than host species

  Interaction effects:

  • Recombination can introduce or remove indels, generating novel sequence combinations

  • Selective pressures may favor certain indel patterns following recombination

  • Both mechanisms contribute to quasispecies diversity within individual hosts

  This interaction creates a dynamic evolutionary landscape where recombination generates novel sequence combinations, while indels provide additional structural variation. Together, these mechanisms facilitate rapid adaptation to changing environments and hosts, potentially influencing virulence and host range .

Methodological Approaches and Experimental Design

• What are the critical considerations for designing primers to detect all ASPV CP variants?

  Designing primers for comprehensive ASPV CP detection requires addressing several critical factors:

  Key considerations:

  • Sequence diversity: ASPV CP shows high genetic variability, with nucleotide identities between variants as low as 67.4%

  • Recombination: CP genes frequently undergo recombination events that create novel sequence combinations

  • Indel patterns: CP variants contain different patterns of insertions/deletions that affect primer binding

  Recommended approaches:

  • Multiple primer pairs: Use complementary primer sets targeting different CP regions, as demonstrated in studies where standard primers failed with certain isolates

  • Conserved regions: Design primers targeting the most conserved sections of the CP gene based on comprehensive sequence alignments

  • Degenerate primers: Incorporate degeneracy at variable positions to accommodate sequence diversity

  • Primer validation: Test primers against a diverse panel of ASPV isolates, representing different phylogenetic groups

  • Regular reassessment: Continuously update primer designs as new CP sequences become available

  Empirical example:
  In one study, researchers found that samples from cultivar Gold Spur failed to amplify using common primer pairs (ASPVF and ASPVC). They then used alternative primers (TGB3F and ASPVNC) to obtain an amplicon, and based on the new sequence, designed specific primers (ASPVCPN and ASPVNC) for CP amplification .

• What computational approaches can predict functional changes resulting from CP recombination events?

  Several computational approaches can predict functional impacts of CP recombination:

  Sequence-based predictions:

  • Protein domain analysis: Identify how recombination affects functional domains within the CP

  • Secondary structure prediction: Use tools like MFold to predict RNA structural changes

  • Functional RNA motif analysis: Employ RegRNA 2.0 to identify functional RNA motifs and sites that may be affected

  Structural predictions:

  • Homology modeling: Generate 3D structural models of recombinant CPs

  • Epitope prediction: Analyze how recombination affects antibody-binding regions

  • Protein-protein interaction sites: Predict changes in interaction interfaces

  Evolutionary analysis:

  • Selection pressure analysis: Calculate dN/dS ratios to identify how recombination affects selective constraints

  • Ancestral sequence reconstruction: Compare recombinants with predicted ancestral sequences

  Network analysis:

  • Co-evolution networks: Identify co-evolving positions that may maintain functional interactions

  • Residue interaction networks: Model how recombination disrupts or creates residue interaction networks

  Machine learning approaches:

  • Train models on known CP functions to predict functional changes in recombinants

  • Use feature importance analysis to identify key sequence positions affecting function

  The combination of these approaches can provide comprehensive predictions about how recombination events may alter CP functions, including aggregation behavior, serological properties, and VSR activity .

• How can we experimentally determine the impact of specific mutations on ASPV CP functionality?

  Experimentally determining the impact of specific mutations on ASPV CP functionality requires a systematic approach:

  Site-directed mutagenesis strategy:

  • Generate point mutations, deletions, or insertions at target sites in the CP gene

  • Create chimeric CPs by swapping domains between variants with different functional properties

  • Construct a panel of mutants targeting conserved motifs, variable regions, and sites under selection

  Functional assays:

  1. Aggregation analysis:

     • Express YFP-tagged CP mutants in N. benthamiana

     • Use confocal microscopy to quantify aggregation patterns

     • Compare aggregation behavior with wild-type variants

  2. Serological reactivity:

     • Express mutant CPs in E. coli BL21 (DE3)

     • Test reactivity with a panel of anti-ASPV antibodies

     • Identify mutations affecting epitope recognition

  3. VSR activity assessment:

     • Use agroinfiltration to express mutant CPs alongside reporter genes in silencing assays

     • Quantify suppression efficiency compared to wild-type CPs

     • Evaluate the impact on different steps of the RNA silencing pathway

  4. Symptom induction:

     • Express mutant CPs in PVX vector in N. occidentalis

     • Monitor and characterize symptom development

     • Compare with symptoms induced by wild-type variants

  By systematically applying these approaches to a panel of mutants, researchers can map the sequence-function relationships in ASPV CP and identify critical residues for different functional properties. This information can help understand the molecular basis of host adaptation and symptom variation among ASPV isolates.