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Influenza A/Mexico/2009 (H1N1) virulence and transmission

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b00528_h1n1_flu_blue_smlThe influenza H1N1 outbreak in Mexico has been analyzed to provide information on the pandemic potential of the new virus strain. The estimates offer some insight into the transmissibility and severity of the virus but must be tempered with the understanding that there are still uncertainties about all aspects of the outbreak.

Influenza incidence is difficult to determine because most infections are not confirmed by laboratory tests. Consequently case estimates play an important role in understanding transmission and spread. In this study, the authors used mathematical models to calculate the number of infections in Mexico based on exportation of the disease by travelers. They estimate that 23,000 infections had occurred in the country by late April. From this number they calculated a case fatality ratio of 0.4%. I note that my own crude calculations yielded a similar number.

To determine the transmissibility of the virus the authors first attempted to pinpoint the start date of the outbreak. One estimate is 15 February 2009 based on the first reported case in La Gloria. But the authors have another method as well:

An alternative approach to estimating the start date of the outbreak is to look at the diversity in the genetic sequences of viral samples collected from confirmed cases, assuming that diversity accumulates according to a molecular clock model.

The authors went on to compare 23 viral HA gene sequences from the Mexican outbreak. Readers of virology blog will understand the reference to a ‘molecular clock’ in the previous paragraph, having read previous posts on the error-prone nature of RNA virus replication. These approaches allow an estimation of the onset of the outbreak in Mexico to 12 January 2009. In other words, an influenza virus with a genome sequence that is the most common ancestor to those represented by the 23 HA gene sequences was circulating in humans in Mexico in January of this year.

The start date of the epidemic and the total number of infections can then be used to calculate the reproductive number, R0. This is the average number of secondary infections that result from one infected host in an otherwise uninfected population. In general, if R0 is less than 1, it is impossible to sustain an epidemic. If R0 is high, an epidemic is almost certain. Very high R0 values are typical of diseases with ‘super-spreaders’, such as the individual who transmitted SARS to others in the Hotel Metropole.

An R0 of 1.4 – 1.6 was calculated for the Mexican outbreak, which means that 14 to 73 generations of human to human transmission took place as of the end of April. This number is higher than observed for seasonal influenza, but in line with estimates from influenza pandemics of 1918, 1957, and 1968.

Fraser, C., Donnelly, C., Cauchemez, S., Hanage, W., Van Kerkhove, M., Hollingsworth, T., Griffin, J., Baggaley, R., Jenkins, H., Lyons, E., Jombart, T., Hinsley, W., Grassly, N., Balloux, F., Ghani, A., Ferguson, N., Rambaut, A., Pybus, O., Lopez-Gatell, H., Apluche-Aranda, C., Chapela, I., Zavala, E., Guevara, D., Checchi, F., Garcia, E., Hugonnet, S., Roth, C., & , . (2009). Pandemic Potential of a Strain of Influenza A (H1N1) : Early Findings Science DOI: 10.1126/science.1176062

Influenza virus RNA: Translation into protein

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influenza-rna-2
figure 1

Let’s resume our discussion of the influenza virus genome. Last time we established that there are eight negative-stranded RNAs within the influenza virion, each coding for one or two proteins. Now we’ll consider how proteins are made from these RNAs.

Figure 1 shows influenza RNA segment 2, which encodes two proteins: PB1 and PB1-F2. The (-) strand viral RNA is copied to form a (+) strand mRNA, which in turn is used as a template for protein synthesis. Figure 2 (below) shows the nucleotide sequence of the first 180 bases of this mRNA.

The top line, mostly in small letters, is the nucleotide sequence of the viral mRNA. During translation this sequence is read in triplets, each of which specifies an amino acid (the one-letter code for amino acids is used here). Translation usually begins with an ATG which specifies the amino acid methionine; the next triplet, gat, specifies aspartic acid, and so on. Only the first 60 amino acids of the PB1 protein are shown; the protein contains a total of 758 amino acids.

Most of the influenza viral RNAs code for only one protein. However, RNA 2 (and two other RNAs) code for two proteins. In the case of RNA 2, the second protein is made by translation of what is known as an overlapping reading frame.

On the second line of the RNA sequence in figure 2 is an atg highlighted in red. You can see that this atg is not in the reading frame of the PB1 protein. However, it is the start codon for the second protein encoded in RNA 2, the PB1-F2 protein (F2 stands for frame 2, because the protein is translated from the second open reading frame). Figure 3 shows how PB1-F2 is translated. The sequence of the viral RNA is shown from the beginning, except that reading frame 1, which begins at the first ATG, is not translated. Rather, we have begun translation with the internal atg, which is in the second reading frame. This open reading frame encodes the PB1-F2 protein which, in this case, is 90 amino acids in length (its length varies in different isolates). The protein is much shorter than PB1 because translation stops at a termination codon (tga) long before the end of the RNA. Because PB1-F2 is encoded in reading frame 2, its amino acid sequence is completely different from that of PB1.

figure 2
figure 2
figure 3
figure 3

The sequences used for this example are from the 1918 H1N1 strain of influenza. Notice the amino acid of PB1-F2 which is highlighted in blue. This amino acid has an important role in the biological function of the protein, which we will consider in a future post.

My apologies if the figures and text are not optimally aligned. A blog post is not the optimal format for such information, but in the interest of time I have not explored other options. Suggestions for improvement are welcome.

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