Conserved amino acid markers from past influenza pandemic strains

Abstract

Background: Finding the amino acid mutations that affect the severity of influenza infections remains an open and challenging problem. Of special interest is better understanding how current circulating influenza strains could evolve into a new pandemic strain. Influenza proteomes from distinct viral phenotype classes were searched for class specific amino acid mutations conserved in past pandemics, using reverse engineered linear classifiers.

Results: Thirty-four amino acid markers associated with host specificity and high mortality rate were found. Some markers had little impact on distinguishing the functional classes by themselves, however in combination with other mutations they improved class prediction. Pairwise combinations of influenza genomes were checked for reassortment and mutation events needed to acquire the pandemic conserved markers. Evolutionary pathways involving H1N1 human and swine strains mixed with avian strains show the potential to acquire the pandemic markers with a double reassortment and one or two amino acid mutations.

Conclusion: The small mutation combinations found at multiple protein positions associated with viral phenotype indicate that surveillance tools could monitor genetic variation beyond single point mutations to track influenza strains. Finding that certain strain combinations have the potential to acquire pandemic conserved markers through a limited number of reassortment and mutation events illustrates the potential for reassortment and mutation events to lead to new circulating influenza strains.

Figure 1

Persistent human markers in non-human strains. Each column in the table is a genotype with the bars showing genotype frequency for avian (red), avian to human crossovers (blue) and non-avian non-human strains (orange). A table entry with H (green) means the amino acid position has the human consensus for the amino acid position, and N means non-human consensus. The last row "Rank" labels each genotype and shows its frequency rank among avian strains. Rank is in increasing order with 0 being the most common genotype. Select strain subtypes are shown in the figure, with details given in the text.

Figure 2

High mortality rate genotypes. Each genotype is specified by a column in the table, where the bars above the column reflect relative frequency in the sequenced genomes. V (green) means the genotype has the virulent consensus for the position, and N means non-virulent consensus. Bars above each table column mark the relative frequency for avian (red), human – both high mortality rate and low mortality rate cases (blue) and non-avian non-human strains (orange bars).

Figure 3

Strain combinations with 34 markers. Frequency distribution for the number evolutionary events needed to acquire the 34 pandemic markers. The 9 pairwise combinations are shown for human, avian and non-human non-avian. Red bar overlays show the average contribution of reassortment events (shift) to the total event count with mutations (drift).

Figure 4

Mutation combination sizes. Relative frequency of mutation combination sizes for different classification accuracy thresholds. Red is the highest accuracy cut off, followed by blue, orange and green.

Figure 5

Host marker classification accuracy. Relative contribution of the human transmission markers to classification accuracy (Acc. = Accuracy). Positions increasing classification accuracy by at least 10% are shown. The colored bars show each mutation's contribution at the 4 different accuracy thresholds. Red is the highest accuracy cut off (99.5%), followed by blue (98.9%), orange (98.5%) and green (98.3%).

Figure 6

High mortality rate marker classification accuracy. Contribution to classification accuracy of high mortality rate markers (Acc. = Accuracy). Positions increasing classification accuracy by at least 5% are shown. Blue is the highest accuracy cut off (94.8%), followed by orange (93.5%) and green (92.8%).