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Glycosylation focuses sequence variation in the influenza A virus H1 hemagglutinin globular domain.

Das SR, Puigbò P, Hensley SE, Hurt DE, Bennink JR, Yewdell JW - PLoS Pathog. (2010)

Bottom Line: The FI predicts the predominance of glycosylation states among existing strains.Our analyses show that while the number of glycosylation sites in the HA globular domain does not influence the overall magnitude of variation in defined antigenic regions, variation focuses on those regions unshielded by glycosylation.This supports the conclusion that glycosylation generally shields HA from antibody-mediated neutralization, and implies that fitness costs in accommodating oligosaccharides limit virus escape via HA hyperglycosylation.

View Article: PubMed Central - PubMed

Affiliation: NIAID, Bethesda, MA, USA.

ABSTRACT
Antigenic drift in the influenza A virus hemagglutinin (HA) is responsible for seasonal reformulation of influenza vaccines. Here, we address an important and largely overlooked issue in antigenic drift: how does the number and location of glycosylation sites affect HA evolution in man? We analyzed the glycosylation status of all full-length H1 subtype HA sequences available in the NCBI influenza database. We devised the "flow index" (FI), a simple algorithm that calculates the tendency for viruses to gain or lose consensus glycosylation sites. The FI predicts the predominance of glycosylation states among existing strains. Our analyses show that while the number of glycosylation sites in the HA globular domain does not influence the overall magnitude of variation in defined antigenic regions, variation focuses on those regions unshielded by glycosylation. This supports the conclusion that glycosylation generally shields HA from antibody-mediated neutralization, and implies that fitness costs in accommodating oligosaccharides limit virus escape via HA hyperglycosylation.

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Schematic representation of the flow among the different states of the virus generated by the Flow Index.Each heptagon represents a glycosylation state of H1 HAs from human viruses isolated until mid-2009 (i.e. no Swine origin HAs are represented). Based on the number of isolates with each glycosylation pattern (show in the Table below as number of sequences), we binned viruses into optimal (red), sub-optimal states (yellow), transitional (grey) and lone lethal state (black). The different states are connected by red arrows to indicate an increase in the number of glycosylation from the pre-state to the post-state or green arrows to indicate a decrease in the number of glycosylation sites. Values of arrows indicate the Flow Index (FI), i.e., the tendency of going from one pre-state to a post-state. Data for figure are provided in Table S1. The net FI acting on each state is given by the sum of the forces as calculated in the Table below, note that this correlates well with the number of isolates in a given state.
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ppat-1001211-g008: Schematic representation of the flow among the different states of the virus generated by the Flow Index.Each heptagon represents a glycosylation state of H1 HAs from human viruses isolated until mid-2009 (i.e. no Swine origin HAs are represented). Based on the number of isolates with each glycosylation pattern (show in the Table below as number of sequences), we binned viruses into optimal (red), sub-optimal states (yellow), transitional (grey) and lone lethal state (black). The different states are connected by red arrows to indicate an increase in the number of glycosylation from the pre-state to the post-state or green arrows to indicate a decrease in the number of glycosylation sites. Values of arrows indicate the Flow Index (FI), i.e., the tendency of going from one pre-state to a post-state. Data for figure are provided in Table S1. The net FI acting on each state is given by the sum of the forces as calculated in the Table below, note that this correlates well with the number of isolates in a given state.

Mentions: Is it possible to predict the tendency of acquisition of glycosylation sites (losses as well as gains) as a function of likelihood of mutation of codons present in the glycosylation regions? We devised a simple algorithm, termed the flow index (FI) to model glycan site evolution based on the sequences present in the glycosylation regions of H1N1 viruses with a given oligosaccharide status. The tendency of mutating to (green arrow) or from (red arrow) a given glycosylation state is assigned is shown in Figure 8. Summing the probabilities to and from a given state provides a measure of the probability of remaining in that state (Table S1).


Glycosylation focuses sequence variation in the influenza A virus H1 hemagglutinin globular domain.

Das SR, Puigbò P, Hensley SE, Hurt DE, Bennink JR, Yewdell JW - PLoS Pathog. (2010)

Schematic representation of the flow among the different states of the virus generated by the Flow Index.Each heptagon represents a glycosylation state of H1 HAs from human viruses isolated until mid-2009 (i.e. no Swine origin HAs are represented). Based on the number of isolates with each glycosylation pattern (show in the Table below as number of sequences), we binned viruses into optimal (red), sub-optimal states (yellow), transitional (grey) and lone lethal state (black). The different states are connected by red arrows to indicate an increase in the number of glycosylation from the pre-state to the post-state or green arrows to indicate a decrease in the number of glycosylation sites. Values of arrows indicate the Flow Index (FI), i.e., the tendency of going from one pre-state to a post-state. Data for figure are provided in Table S1. The net FI acting on each state is given by the sum of the forces as calculated in the Table below, note that this correlates well with the number of isolates in a given state.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2991263&req=5

ppat-1001211-g008: Schematic representation of the flow among the different states of the virus generated by the Flow Index.Each heptagon represents a glycosylation state of H1 HAs from human viruses isolated until mid-2009 (i.e. no Swine origin HAs are represented). Based on the number of isolates with each glycosylation pattern (show in the Table below as number of sequences), we binned viruses into optimal (red), sub-optimal states (yellow), transitional (grey) and lone lethal state (black). The different states are connected by red arrows to indicate an increase in the number of glycosylation from the pre-state to the post-state or green arrows to indicate a decrease in the number of glycosylation sites. Values of arrows indicate the Flow Index (FI), i.e., the tendency of going from one pre-state to a post-state. Data for figure are provided in Table S1. The net FI acting on each state is given by the sum of the forces as calculated in the Table below, note that this correlates well with the number of isolates in a given state.
Mentions: Is it possible to predict the tendency of acquisition of glycosylation sites (losses as well as gains) as a function of likelihood of mutation of codons present in the glycosylation regions? We devised a simple algorithm, termed the flow index (FI) to model glycan site evolution based on the sequences present in the glycosylation regions of H1N1 viruses with a given oligosaccharide status. The tendency of mutating to (green arrow) or from (red arrow) a given glycosylation state is assigned is shown in Figure 8. Summing the probabilities to and from a given state provides a measure of the probability of remaining in that state (Table S1).

Bottom Line: The FI predicts the predominance of glycosylation states among existing strains.Our analyses show that while the number of glycosylation sites in the HA globular domain does not influence the overall magnitude of variation in defined antigenic regions, variation focuses on those regions unshielded by glycosylation.This supports the conclusion that glycosylation generally shields HA from antibody-mediated neutralization, and implies that fitness costs in accommodating oligosaccharides limit virus escape via HA hyperglycosylation.

View Article: PubMed Central - PubMed

Affiliation: NIAID, Bethesda, MA, USA.

ABSTRACT
Antigenic drift in the influenza A virus hemagglutinin (HA) is responsible for seasonal reformulation of influenza vaccines. Here, we address an important and largely overlooked issue in antigenic drift: how does the number and location of glycosylation sites affect HA evolution in man? We analyzed the glycosylation status of all full-length H1 subtype HA sequences available in the NCBI influenza database. We devised the "flow index" (FI), a simple algorithm that calculates the tendency for viruses to gain or lose consensus glycosylation sites. The FI predicts the predominance of glycosylation states among existing strains. Our analyses show that while the number of glycosylation sites in the HA globular domain does not influence the overall magnitude of variation in defined antigenic regions, variation focuses on those regions unshielded by glycosylation. This supports the conclusion that glycosylation generally shields HA from antibody-mediated neutralization, and implies that fitness costs in accommodating oligosaccharides limit virus escape via HA hyperglycosylation.

Show MeSH
Related in: MedlinePlus