H3N2 Brisbane

What are the key genetic characteristics of the A/Brisbane/10/2007 (H3N2) strain?

A/Brisbane/10/2007 (H3N2) represents an important strain in the evolutionary history of seasonal influenza viruses. The strain has distinct genetic features particularly in its hemagglutinin (HA) gene, which contains notable polymorphism at residue 194. Among the 11 amino acid sequences of Bris07 HA deposited in the NCBI protein database, five have proline (Pro) and five have leucine (Leu) at position 194, with one sequence showing an ambiguous amino acid at this position . This polymorphism is significant as it affects receptor binding properties.

The virus also shows characteristic mutations compared to predecessor strains, with K158N and N189K mutations in HA distinguishing it from its predecessor A/Perth/16/2009 . These mutations contributed to antigenic drift events that necessitated vaccine strain updates.

Methodologically, genetic characterization of H3N2 strains typically involves:

• Direct sequencing of HA genes from clinical specimens

• Alignment with reference strains such as A/Hong Kong/1/1968

• Analysis of glycosylation patterns using techniques like C18 Chip-Q-TOF-MS

• Phenotypic assessment through hemagglutination assays and receptor binding studies

How does the receptor binding profile of A/Brisbane/10/2007 compare to other H3N2 strains?

The receptor binding profile of A/Brisbane/10/2007 (Bris07) represents an intermediate stage in the evolutionary trajectory of H3N2 viruses as they've adapted to human hosts since 1968. Research has revealed significant differences in how Bris07 interacts with sialic acid receptors compared to both predecessor and successor strains.

When binding to human receptor analog 6'SLNLN, Bris07 with leucine at position 194 (L194) binds in a folded-back conformation that differs from earlier strains. The F193 side chain in Bris07 L194 adopts different rotamers depending on whether it's in its apo form or receptor-bound form, with the side chain pointing away from the receptor binding site when bound to 6'SLNLN . This change in F193 rotamer is critical for 6'SLNLN binding.

Compared to the pandemic A/Hong Kong/1/1968 (HK68) strain, Bris07 shows evolutionary changes in receptor binding:

• Bris07 exhibits a CH-π stacking interaction between F193 and Gal-4 of the receptor that isn't present in HK68 (which has Ser at position 193)

• This stacking interaction shifts Gal-4 toward the top of the receptor binding site

• The conformational differences between how 6'SLNLN binds to HK68 versus Bris07 can be attributed to several natural mutations at the base of the Bris07 receptor binding site

Later H3N2 viruses from mid-1970s onward showed progressively decreasing binding to N-linked and biantennary O-glycans containing only one or two LacNAc repeats, culminating in almost complete elimination of binding to shorter receptors in recent strains .

What is the significance of the A/Brisbane/10/2007 strain in the evolution of H3N2 viruses?

A/Brisbane/10/2007 (BR07) represents a critical node in the antigenic evolution of seasonal H3N2 influenza viruses. Sequence-based antigenic cartography identified BR07 as one of 16 antigenic clusters in the evolutionary history of H3N2 viruses from 1968-2016, positioned between A/Wisconsin/67/2005 and A/Perth/16/2009 (PE09) .

The transition from BR07 to PE09 was characterized by specific mutations K158N and N189K in the hemagglutinin protein . These mutations represent an antigenic drift event that necessitated vaccine strain updates. This is part of the pattern of continuous antigenic evolution of H3N2 viruses, where typically 1-5 key mutations lead to significant antigenic changes.

The lineage containing BR07 is also notable for its role in the evolution of receptor binding. As shown in longitudinal glycan array studies, BR07 exhibits a binding profile intermediate between early pandemic strains (which showed little length selectivity for receptors) and contemporary strains (which show strong preference for extended receptors) .

Additionally, BR07 serves as an important reference strain for antibody studies. Research has shown that N2-specific human monoclonal antibodies isolated from influenza patients demonstrate reactivity to N2 of both A/Brisbane/10/2007 and A/Wisconsin/67/2005, with some antibodies showing remarkably broad activity against diverse H3N2 strains .

How does the L194P mutation in the hemagglutinin of A/Brisbane/10/2007 affect receptor binding properties?

The L194P mutation in the hemagglutinin (HA) of A/Brisbane/10/2007 substantially impacts receptor binding through multiple mechanisms primarily related to changes in protein dynamics and conformation.

Crystal structure analysis reveals that the L194P substitution significantly increases the conformational dynamics of the 190-helix (residues 188-197) in the receptor binding domain. This is evidenced by:

• Higher B-values in the 190-helix region of Bris07 P194 (142 Ų) compared to Bris07 L194 (109 Ų)

• Weaker electron density in 2Fo-Fc maps for the 190-helix of P194 variant

• Increased mobility confirmed by molecular dynamics simulations

The conformational changes extend beyond the local environment of residue 194:

• A major peak in normalized B-value differences is centered around residue 193 (ranging from residues 186-200)

• Minor peaks appear at the 150-loop region (residues 155-164) and a region proximal to the 190-helix (residues 214-218)

These structural changes translate to functional differences in receptor binding:

The L194P substitution effectively:

• Destabilizes the 190-helix structure

• Disrupts the proper positioning of key receptor-interacting residues

• Reduces binding affinity to human-type receptors

• May impact antibody recognition of the antigenic site

This knowledge is crucial for understanding how egg adaptation during vaccine production may alter receptor binding properties and potentially compromise vaccine effectiveness.

What methodologies are most effective for analyzing glycosylation changes in H3N2 strains like A/Brisbane/10/2007?

Several complementary methodologies have proven effective for analyzing glycosylation changes in H3N2 influenza strains. When studying strains like A/Brisbane/10/2007, researchers should consider a multi-technique approach:

Mass Spectrometry-Based Methods:

• C18 Chip-Q-TOF-MS: This combines chromatographic separation with quadrupole time-of-flight mass spectrometry, allowing for detailed characterization of glycosylation patterns. This technique was specifically employed to analyze glycosylation changes in novel H3N2 strains in China that failed to bind red blood cells .

• Glycopeptide Analysis: This approach identifies site-specific glycosylation by analyzing glycopeptides generated from protease digestion of viral proteins, providing information about both the glycan structure and attachment site.

Structural Biology Approaches:

• X-ray Crystallography: By solving crystal structures of HA proteins (as done with Bris07 L194 and P194 variants), researchers can directly visualize N-linked glycosylation sites and assess their impact on protein structure .

• Molecular Dynamics Simulations: These can model the dynamic effects of glycosylation on protein conformation and flexibility. Parameters should include:

  • Amber ff14SB force field for proteins

  • GLYCAM06 force field for glycans

  • TIP4P-Ew water model

  • Chlorine counterions for charge neutralization

  • Energy minimization in sequential steps

  • Heating from 0K to 300K over 250ps

  • Equilibration at 300K in NPT ensemble

Functional Assays:

• Glycan Microarrays: These high-throughput platforms can determine how glycosylation changes affect binding to diverse sialic acid-containing receptors .

• Hemagglutination Assays with Glycosylation Inhibitors: These can reveal how specific glycosylation sites affect receptor binding. When working with strains that don't agglutinate RBCs, complementary assays are essential:

  • Quantitative real-time PCR (qPCR)

  • Direct immunofluorescence assay (DFA)

  • Reverse genetics to insert HA genes into backbone viruses for functional testing

Computational Prediction:

• Homology Modeling: This can predict the structure of glycosylated proteins based on templates with known structures. For example, models of influenza B virus HA were constructed with high-mannose-type asparagine-linked sugar chains attached at specific residues .

• Energy Minimization: Applying the AMBER99 force field combined with generalized Born model of aqueous solvation can optimize glycoprotein structure predictions .

For comprehensive glycosylation analysis, researchers should integrate data from multiple techniques, correlating structural observations with functional outcomes.

How do conformational dynamics of the 190-helix in H3N2 Brisbane HA affect binding to human receptors?

The conformational dynamics of the 190-helix (residues 188-197) in H3N2 Brisbane HA play a critical role in receptor binding through several interrelated mechanisms:

Structural Foundation:
The 190-helix forms a crucial part of the receptor binding site (RBS) and contains key residues that directly interact with sialic acid receptors. Crystal structures and molecular dynamics simulations of A/Brisbane/10/2007 (Bris07) have revealed that changes in the stability and flexibility of this helix substantially affect receptor binding modes .

Dynamic Effects on Key Residues:
When the 190-helix exhibits increased flexibility (as seen in the P194 variant), several key receptor-interacting residues are affected:

• D190: In Bris07 L194, D190 forms water-mediated hydrogen bonds with Sia-1 (the terminal sialic acid) and GlcNAc-3 of the human receptor analog 6'SLNLN. With increased flexibility in the P194 variant, these interactions are disrupted .

• F193: The side chain of F193 undergoes a conformational change upon receptor binding in Bris07 L194, pointing away from the RBS to accommodate the receptor. This rotamer change is critical as it:

  • Prevents steric clash with GlcNAc-3

  • Establishes a carbohydrate-aromatic CH-π stacking interaction with Gal-4

  • This stacking interaction isn't present in ancestral strains like A/Hong Kong/1/1968, which has Ser at position 193

Impact on Receptor Binding Mode:
The stability of the 190-helix determines the binding conformation of human receptors:

The more stable helix in Bris07 L194 allows for:

Evolutionary Implications:
These structure-function relationships explain why egg adaptation during vaccine production (which often selects for the P194 variant) can reduce vaccine effectiveness. The L194P substitution destabilizes the 190-helix, compromising binding to human receptors and potentially altering antigenic properties recognized by vaccine-induced antibodies .

Understanding these dynamics is essential for improving influenza vaccine design, potentially through approaches that stabilize the natural conformation of the 190-helix during vaccine production.

What are the implications of antigenic drift events from A/Brisbane/10/2007 to subsequent strains for vaccine development?

The antigenic drift events from A/Brisbane/10/2007 (BR07) to subsequent strains have significant implications for vaccine development, affecting strain selection, vaccine effectiveness, and evolutionary surveillance strategies.

Specific Mutations Driving Antigenic Drift:
Detailed sequence analysis and computational models have identified the key mutations responsible for antigenic transitions from BR07 to later strains:

These mutations are primarily concentrated in antibody binding sites A and B, illustrating how immune pressure drives antigenic change .

Impact on Vaccine Effectiveness:
The recognition that just 1-5 key mutations can lead to significant antigenic changes has important implications:

• Egg Adaptation Concerns: The L194P mutation that occurs during egg passaging of vaccine strains like BR07 substantially alters receptor binding properties, potentially compromising antigenic properties and vaccine effectiveness .

• Prediction Challenges: While machine learning approaches can predict antigenic differences with correlation coefficients up to 0.75 compared with HI assay-based antigenic distances, unexpected co-mutations or epistatic effects can complicate predictions .

• Emerging Sublineages: The pattern observed with TX12 splitting into two distinct antigenic variants (SWZ13-like and HK14-like) illustrates how co-circulating sublineages can complicate vaccine strain selection .

Methodological Approaches for Improved Vaccine Development:

• Sequence-Based Antigenic Cartography: Large-scale analysis of 39,370 H3N2 viruses (1968-2016) using techniques like Graph-guided Multi-task Sparse Learning (GG-MTSL) can identify and predict antigenic clusters without requiring extensive serological testing .

• Structural Vaccinology: Understanding how specific mutations affect both antibody recognition and receptor binding (particularly in antigenic site B) can guide rational vaccine design to avoid egg-adaptation issues .

• Monitoring Neuraminidase Evolution: Research has shown that neuraminidase (N2) undergoes concurrent evolutionary changes, with features like E344K mutations and changes in 329-N-glycosylation affecting antibody recognition. These changes should be considered alongside HA changes for comprehensive vaccine design .

These findings emphasize the need for integrated approaches that consider both genetic sequence data and structural/functional implications of mutations when selecting vaccine strains.

What experimental approaches can be used to study the antibody response against neuraminidase in H3N2 Brisbane infections?

Studying neuraminidase (NA) antibody responses requires specialized techniques that go beyond traditional hemagglutination inhibition (HI) assays. The following methodologies provide comprehensive insights into NA-directed immunity:

Core Assays for NA Antibody Analysis:

• NA Activity Inhibition (NI) Assay: This functional assay measures antibodies that inhibit the enzymatic activity of NA.

  • Methodology: Serum samples are incubated with standardized amounts of virus or recombinant NA, followed by addition of substrate (typically MUNANA or fetuin)

  • Readout: Reduction in fluorescence or colorimetric signal indicates NI antibody presence

  • Application: Particularly useful for H3N2 infection diagnosis in children, with conversion rates of 68.42% observed versus 41.17% in adults

• NA-Binding Antibody ELISA: This measures total binding antibodies regardless of functional inhibition.

  • Methodology: Recombinant N2 proteins are coated on plates, followed by serial dilution of serum samples

  • Readout: Endpoint titers or area under the curve measurements

  • Correlation: Significant correlation with microneutralization (MN) antibodies observed in children (r = 0.59, p < 0.01) but not in adults (r = 0.11, p > 0.05)

Complementary Techniques:

• Microneutralization (MN) Assay: Though primarily measuring HA-directed antibodies, correlations with NA responses can be informative.

  • Finding: MN antibodies against A/Singapore/INFIMH-16-0019/2016(H3N2) showed a significant correlation with NA inhibiting antibodies in children

• Cross-Reactivity Panel Testing: Testing sera against multiple historical and contemporary N2 proteins to assess breadth of response.

  • Example: N2-specific human monoclonal antibodies from patients showed varied cross-reactivity patterns, with some (like 1122B9) binding broadly to N2 from both A/Brisbane/10/2007 and diverse strains including avian isolates

• Avidity Measurements: Assessing antibody binding strength using chaotropic agents.

  • Methodology: Bound antibodies are incubated with increasing concentrations of urea (up to 8M)

  • Finding: N2-specific antibodies maintain binding even at high urea concentrations, suggesting strong avidity

Advanced Analytical Approaches:

• Antigenic Cartography of N2: Computational analysis of antigenic relationships between different N2 variants.

  • Implementation: Testing sera against a panel of N2 variants with known mutations (E344K, changes in 329-N-glycosylation)

  • Application: Tracking N2 antigenic drift patterns in circulating H3N2 variants

• Integrated HA/NA Antibody Analysis: Correlation analysis between different antibody types.

  • Finding: Significant correlations between MN antibodies and both HA-binding and NA-binding/inhibiting antibodies in certain age groups

When designing NA antibody studies, researchers should consider age stratification, as children and adults show different correlation patterns between antibody types, suggesting age-dependent immune response mechanisms to N2 antigens.

How can molecular dynamics simulations be optimized for studying H3N2 HA protein conformational changes?

Molecular dynamics (MD) simulations provide crucial insights into the conformational dynamics of H3N2 HA proteins, but must be carefully optimized for reliable results. Based on successful approaches used with A/Brisbane/10/2007 variants, the following methodology is recommended:

System Preparation:

• Structure Selection:

  • Use residues 57-263 from monomeric HA1 as the starting structure

  • When studying mutation effects, prepare both wild-type and mutant structures using identical crystallization conditions to minimize experimental bias

  • Consider whether monomeric or trimeric structures are appropriate (trimeric structures may better represent biological reality for some analyses)

• Force Field Selection:

  • Amber ff14SB force field for protein components

  • GLYCAM06 force field for glycan components

  • TIP4P-Ew water model for solvent

• System Setup:

  • Add chlorine counterions to neutralize charge

  • Use cubic box with 10 Å between solute surface and box boundary

  • Implement periodic boundary conditions

Simulation Protocol:

• Energy Minimization (Sequential Approach):

  • 1000 steps of hydrogen-only minimization

  • 4000 steps of solvent minimization

  • 2000 steps with protein backbone constrained

  • 5000 steps of all-atom minimization

• Heating Phase:

  • Heat from 0K to 300K linearly over 250 ps in NVT ensemble

  • Use 2 fs time-step

  • Apply position restraints of 5.0 kcal mol⁻¹ Å⁻² on protein backbone atoms

  • Control temperature using Langevin thermostat with collision frequency of 1 ps⁻¹

• Equilibration:

  • First 500 ps with position restraints in NPT ensemble (relaxation time 2 ps)

  • Second 500 ps without position restraints in NPT ensemble

• Production Run:

  • Minimum 500 ns in NPT ensemble at 300K

  • Use pmemd.cuda module of Amber16 for GPU acceleration

  • Apply Langevin thermostat with collision frequency of 5 ps⁻¹

  • Monitor constant pressure using Berendsen barostat (pressure relaxation time: 2 ps)

  • Employ hydrogen mass repartitioning to allow 4 fs time-steps instead of 2 fs

Analysis Techniques:

• Root-Mean-Square Fluctuations (RMSF):

  • Calculate for all Cα atoms from aligned trajectories

  • Discard first 20 ns of production run as additional equilibration

  • Compare RMSF between wild-type and mutant structures to identify regions with altered dynamics

• Simulated B-values:

  • Convert RMSF to simulated B-values for direct comparison with crystallographic B-values

  • Use normalized B-values to minimize systematic differences between structures

  • Plot difference in normalized B-values against residue position to identify regions with significant changes

• Conformational Analysis:

  • Extract and align multiple frames (e.g., 50 random frames) to visualize conformational diversity

  • Pay special attention to regions like the 190-helix that may show different dynamics between variants

Important Considerations:

When interpreting results, be aware of potential artifacts:

• Simulations of monomeric HA may show artificial behavior at interfaces that would normally contact other protomers in the trimeric structure

• Sharp inverse peaks in B-value differences may represent simulation artifacts rather than biologically relevant differences

For optimal results, validate simulation findings against experimental data such as crystallographic B-values and functional assays.

What computational methods are effective for predicting antigenic distances between H3N2 strains?

Predicting antigenic distances between H3N2 strains is crucial for vaccine strain selection and understanding viral evolution. Several computational approaches have demonstrated effectiveness in this domain:

1. Graph-guided Multi-task Sparse Learning (GG-MTSL) Model:

This sophisticated machine learning approach has proven particularly effective for sequence-based antigenic distance prediction:

• Methodology:

  • Represents each virus as a feature vector based on amino acid sequence

  • Employs 50 learning tasks to identify residues associated with antigenicity

  • Incorporates pairwise co-mutations among surface residues

  • Uses graph-guidance to leverage the relationship between multiple learning tasks

• Performance:

  • Achieves correlation coefficient of 0.75 compared with HI assay-based antigenic distances

  • Successfully identified mutations driving antigenic drift events (e.g., K158N-N189K in BR07→PE09 transition)

  • Capable of handling large datasets (39,370 H3N2 sequences spanning 1968-2016)

• Key Features Selected:

  • Identified 66 unique residues associated with antigenicity

  • 59 of these residues were located in reported antibody binding sites A-E

  • Also identified 186 co-mutation pairs with significant effects on antigenicity

2. Structural Bioinformatics Approaches:

• Methodology:

  • Use homology modeling to predict structures of different HA variants

  • Apply energy minimization with AMBER99 force field and generalized Born model

  • Validate structures using Ramachandran plots

  • Compare binding site architecture and receptor interactions between strains

• Applications:

  • Useful for predicting effects of specific mutations (e.g., L194P) on receptor binding

  • Can identify structural changes that might affect antibody recognition

3. Integrated Sequence-Structure Models:

• Methodology:

  • Combine sequence features with predicted structural properties

  • Use machine learning algorithms trained on known antigenic relationships

  • Employ spectral clustering algorithms for antigenic variant identification

• Performance:

  • Capable of identifying distinct antigenic clusters without predetermined cluster numbers

  • Achieved average Silhouette index of 0.7486 (values range from -1 to 1, with higher values indicating better clustering)

4. Serological Data Reconstruction Methods:

• Methodology:

  • For cohort studies with limited serological data, use antibody kinetics models

  • Incorporate time-dependent antibody kinetics

  • Account for cross-reactivity between antigenically related strains

  • Implement Bayesian inference to reconstruct infection histories

• Applications:

  • Estimate historical and contemporary attack rates

  • Identify periods of high antigenic drift

  • Compare antigenic evolution across different geographical locations

Implementation Recommendations:

For optimal antigenic distance prediction:

• Begin with sequence-based approaches like GG-MTSL for large-scale screening

• Validate key predictions with structural modeling of specific mutations

• When possible, integrate contemporary serological data to ground-truth computational predictions

• Consider population-specific factors that might influence antigenic evolution in different geographic regions

These computational approaches provide powerful tools for tracking and predicting H3N2 antigenic evolution, enabling more informed vaccine strain selection and providing insights into the mechanisms driving influenza virus antigenic drift.

What statistical approaches are most appropriate for analyzing attack rates in H3N2 influenza studies?

Analyzing attack rates in H3N2 influenza studies presents unique statistical challenges due to incomplete case ascertainment, antigenic variation, and complex antibody kinetics. The following methodological approaches have proven effective for robust attack rate estimation:

Bayesian Inference Frameworks

Bayesian methods provide powerful tools for estimating H3N2 attack rates while accounting for uncertainty:

• Implementation Approach:

  • Employ Markov Chain Monte Carlo (MCMC) sampling to generate posterior distributions of attack rates

  • Incorporate prior distributions based on surveillance data or previous studies

  • Generate credible intervals (CrIs) to quantify uncertainty

• Example Application:

  • Analysis of the Fluscape cohort (1,130 individuals) estimated a median quarterly sample attack rate of 3.54% (95% CrI: 3.08% to 4.01%)

  • This translated to a median annual attack rate of 19.1% (95% CrI: 17.2% to 20.9%)

  • Comparable findings from Ha Nam, Vietnam data validated these estimates (18.6%; 95% CrI: 14.5% to 22.9%)

Antibody Kinetics Modeling

Complex antibody dynamics necessitate specialized statistical approaches:

• Key Components to Model:

  • Initial antibody boosting following infection

  • Waning of antibody titers over time

  • Cross-reactive antibody responses between antigenically related strains

  • Age-dependent differences in antibody response magnitude

• Mathematical Framework:

  • Model antibody kinetics using exponential decay functions

  • Incorporate strain-specific antigenic distances to quantify cross-reactivity

  • Account for measurement error in serological assays

  • Adjust for censoring in antibody titer data

Infection History Reconstruction

Reconstructing individual infection histories provides the foundation for population-level attack rate estimation:

• Methodology:

  • For each individual i and time period t, estimate probability of infection P(I_i,t)

  • Generate multiple posterior samples of possible infection histories

  • Aggregate individual histories to estimate population-level attack rates

• Statistical Considerations:

  • Account for uncertainty in whether elevated titers result from homologous infection or cross-reactive antibodies

  • Consider multiple plausible infection histories consistent with observed antibody profiles

  • Incorporate prior information on seasonal influenza circulation patterns

Comparative Validation Approaches

Cross-validation between different estimation methods strengthens confidence in attack rate estimates:

• Methods for Validation:

  • Compare serologically estimated attack rates with RT-PCR-confirmed cases

  • Validate between geographically distinct cohorts (e.g., China vs. Vietnam)

  • Compare antigenic cartography derived from serological vs. genetic data

• Findings from Implementation:

  • Attack rates were "reasonably well synchronized" between Fluscape and Ha Nam cohorts

  • Both datasets showed very high attack rates for specific years (1968, 1989, 2009)

  • Differences in specific time periods (higher in Ha Nam 2000-2003; higher in Fluscape 2010-2012) highlight geographical variation

Age-Stratified Analysis

Age-specific differences in susceptibility and immune history necessitate stratified analysis:

• Analytical Approach:

  • Stratify population by age cohorts

  • Estimate age-specific attack rates

  • Account for birth year relative to strain emergence

  • Model age-dependent antibody response magnitudes

When implementing these approaches, researchers should:

• Report both point estimates and credible intervals

• Clearly state all modeling assumptions

• Conduct sensitivity analyses to assess robustness to key assumptions

• Consider geographical and temporal factors affecting H3N2 circulation

These statistical frameworks enable rigorous estimation of H3N2 attack rates from serological data, providing insights into influenza transmission dynamics that may be missed by traditional surveillance.

How should researchers interpret changes in B-values in crystal structures of H3N2 hemagglutinin proteins?

B-values (also called temperature factors or Debye-Waller factors) in crystal structures provide critical insights into protein dynamics and flexibility. For H3N2 hemagglutinin (HA) proteins, careful interpretation of these values can reveal functional mechanisms underlying receptor binding and antigenic evolution:

Fundamental Principles for B-value Analysis:

• Basic Interpretation Framework:

  • Higher B-values indicate greater atomic mobility or disorder

  • Lower B-values suggest more rigid or ordered regions

  • Absolute B-values depend on multiple factors including resolution, refinement methods, and crystal quality

• Normalization Approach:

  • To compare B-values between different structures, normalization is essential

  • Normalize B-values by subtracting the mean and dividing by the standard deviation for each structure

  • Plot differences in normalized B-values to identify regions with significant changes in mobility

Methodological Implementation:

• Controlled Comparison Protocol:

  • Crystallize proteins under identical conditions

  • Obtain structures at similar resolutions

  • Process diffraction data using identical methods

  • Example: A/Brisbane/10/2007 L194 and P194 variants were crystallized in the same precipitant condition and diffracted to similar resolution (2.35 Å)

• Regional Analysis:

  • Compare average B-values of specific regions (e.g., epitopes, receptor binding domains)

  • Example: 190-helix (residues 188-197) in Bris07 P194 had significantly higher B-values (142 Ų) than Bris07 L194 (109 Ų)

• Validation with Complementary Methods:

  • Confirm B-value findings with molecular dynamics simulations

  • Compare electron density quality in 2Fo-Fc maps

  • Conduct root-mean-square fluctuation (RMSF) analysis

Functional Interpretation Guidelines:

• Receptor Binding Site Dynamics:

  • Higher B-values in the 190-helix (as in L194P mutation) correlate with altered receptor binding

  • Changes may propagate to adjacent regions (e.g., 150-loop) affecting receptor interactions

  • Differences in B-values can explain altered binding modes to receptor analogs

• Antigenic Site Flexibility:

  • Changes in B-values at antigenic sites may indicate altered antibody recognition

  • Increased flexibility can potentially create "moving targets" for antibodies

  • Evolution may select for optimal balance between flexibility and stability

• Structural Interpretation Decision Tree:

  B-value Pattern	Structural Interpretation	Functional Implication
  Higher in loops/surface	Normal flexibility pattern	Expected dynamics
  Higher in secondary structures	Potential destabilization	May affect function
  Local increase after mutation	Direct effect on flexibility	Likely functional relevance
  Global increase	Potential experimental artifact	Requires validation
  Changes propagating to distant sites	Allosteric effects	Complex functional impacts

• Evolutionary Context:

  • Compare B-values across evolutionary timepoints

  • Assess whether changes correlate with antigenic drift events

  • Site B of H3N2 HA shows significant evolutionary flexibility in its local fitness landscape

Analytical Cautions:

By applying these methodological principles, researchers can extract meaningful biological insights from B-value analysis, particularly in understanding how mutations like L194P affect receptor binding through altered protein dynamics rather than direct changes to binding residues.

What are the latest findings regarding the evolution of H3N2 receptor specificity since the A/Brisbane/10/2007 strain?

The evolution of H3N2 receptor specificity since A/Brisbane/10/2007 represents a fascinating case of continuous adaptation under dual selective pressures. Recent research has revealed several key developments:

Progressive Glycan Length Preference:

A major evolutionary trend has been the increasing preference for extended glycan receptors. While A/Brisbane/10/2007 showed an intermediate binding profile, subsequent H3N2 strains have demonstrated:

• Near-Complete Elimination of Binding to Short Receptors:

  • Since the late 1990s-early 2000s, H3N2 viruses have evolved a receptor specificity phenotype that almost entirely eliminates binding to shorter glycan receptors

  • This restricted receptor specificity has persisted through the most recent strains analyzed

• Enhanced Binding to Extended Poly-LacNAc Structures:

  • Contemporary H3N2 viruses make increasingly complex interactions with elongated receptors

  • These viruses continuously select for strains maintaining this phenotype

Molecular Basis of Length Selection:

Recent structural studies have revealed the mechanisms underlying this evolving specificity:

• Extended Receptor Binding Site:

  • The traditional receptor binding site has expanded to include residues in key antigenic sites

  • Saturation Transferred Difference NMR (STD-NMR) experiments show that contemporary H3N2 viruses interact with sugars beyond the terminal sialic acid

  • Specific residues like Y159 play substantial roles in interactions with internal sugar units (e.g., Gal-6)

• Integration of Immune Escape with Receptor Binding:

  • Mutations arising from antigenic selection are now linked to receptor binding

  • Residues in antigenic site B have dual roles in antibody evasion and maintaining binding to human receptors

  • This creates an evolutionary constraint where viruses must both avoid neutralization and maintain fitness for transmission

Fitness Implications:

This evolving receptor specificity appears to confer selective advantages:

• Competitive Advantage of Extended Receptor Binding:

  • Analysis of subdominant clades that emerged but were ultimately selected against showed compromised binding to extended receptors

  • For example, when clade 3C strains became dominant over prior 3B lineages, viruses maintaining extended receptor binding prevailed

• Local Fitness Landscape Evolution:

  • Deep mutational scanning of site B in six different human H3N2 strains (1968-2016) revealed significant variation in fitness effects

  • 55% of parameters for additive fitness effects and 43% for pairwise epistatic effects had different signs in different genetic backgrounds

  • This indicates extensive evolution of the local fitness landscape while maintaining the extended receptor binding phenotype

Most Recent Developments:

Latest research on contemporary H3N2 strains reveals:

These findings highlight how H3N2 receptor specificity continues to evolve, with contemporary viruses exhibiting increasingly sophisticated interactions with human receptors while simultaneously evading antibody recognition.

What contradictions exist in current research on H3N2 Brisbane antibody responses, and how might they be resolved?

Research on antibody responses to H3N2 Brisbane has revealed several important contradictions that require methodological resolution. These discrepancies highlight the complexity of influenza immunology and offer opportunities for more nuanced understanding.

Age-Dependent Contradictions in Antibody Correlations

One significant contradiction appears in the relationship between different antibody types across age groups:

• Observed Contradiction:

  • In children, microneutralization (MN) antibodies show significant correlation with neuraminidase inhibition (NI) antibodies (r = 0.59, p < 0.01)

  • In adults, no significant correlation exists between these antibody types (r = 0.11, p > 0.05)

• Methodological Resolution Approach:

  • Implement age-stratified analysis with narrower age bands

  • Adjust for infection history using statistical models

  • Consider differential boosting of pre-existing immunity versus de novo responses

  • Analyze antibody repertoire breadth and affinity maturation differences between age groups

Contradictions in Antibody Avidity Measurements

Contradictory findings exist regarding antibody binding strength to different viral components:

• Observed Contradiction:

  • H3-specific human monoclonal antibodies show significant binding diminishment at 8M urea

  • N2-specific antibodies maintain binding even at 8M urea, suggesting higher avidity

• Resolution Methods:

  • Standardize avidity testing protocols across laboratories

  • Employ multiple chaotropic agents beyond urea (guanidine HCl, sodium thiocyanate)

  • Complement avidity assays with surface plasmon resonance for direct kinetic measurements

  • Investigate structural basis for differential stability of antibody-antigen complexes

Vaccine Effectiveness vs. Serological Response Contradictions

A critical contradiction exists between measured antibody responses and clinical effectiveness:

• Observed Contradiction:

  • Standard hemagglutination inhibition assays may show adequate antibody responses to egg-adapted vaccines

  • Yet clinical effectiveness of these vaccines can be notably lower than predicted

  • This discrepancy is partially explained by the L194P egg-adaptation mutation affecting antigenic properties

• Integrative Resolution Approach:

  • Develop improved correlates of protection that incorporate both HA and NA antibodies

  • Assess antibody functionality through multiplexed assays

  • Measure antibodies against cell-grown vs. egg-grown viruses

  • Incorporate epitope-specific antibody measurements

Contradictions in Serological Protection with Age

Evidence suggests contradictory relationships between antibody titers and protection across age groups:

• Observed Contradiction:

  • Elevated antibody titers are associated with reduced infection risk

  • But this protection becomes less effective with increasing age

  • This occurs despite potentially higher antibody titers in older individuals due to repeated exposures

• Resolution Framework:

  • Analyze antibody quality metrics (avidity, neutralization potency) alongside quantity

  • Investigate immunosenescence markers

  • Assess B cell memory populations and functionality

  • Develop models that incorporate both antibody titers and age-dependent immune function

Historical vs. Contemporary Incidence Rate Contradictions

Contradictions exist between contemporary and historical infection rate estimates:

• Observed Contradiction:

  • Recent studies suggest annual H3N2 incidence rates around 19%

  • These values exceed previous historical estimates and suggest multiple infections per year may occur

  • Particularly high rates (20-61%) observed during 2010-2014 in the Fluscape cohort exceed Hong Kong estimates (7-19%) for the same period

• Methodological Resolution:

  • Implement standardized serological testing across studies

  • Apply consistent statistical frameworks for incidence estimation

  • Account for geographical variation in virus circulation

  • Consider changing viral diversity and multiple co-circulating clades

By applying these resolution frameworks, researchers can transform apparent contradictions into deeper insights about the complex and heterogeneous nature of antibody responses to H3N2 viruses, ultimately improving vaccine design and immunological understanding.

What are the most critical unresolved questions regarding H3N2 Brisbane that require further research?

Despite extensive study of the A/Brisbane/10/2007 (H3N2) strain and its evolutionary descendants, several critical knowledge gaps remain that warrant dedicated research efforts: