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About viruses and viral disease

mutation

The number of possible viral variants

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milky-wayIf you have been following our discussion of quasispecies here on virology blog, you might be wondering exactly how many possible variants there are for a viral genome. The answer is quite simple: for a genome N nucleotides in length, there are 4N possible variants, because there are 4 different nucleotides. This is a huge number, even for small viral genomes. For example, there are 10180 different variants for a genome that is only 300 nucleotides in length. The HIV-1 genome, which is about 10,000 nucleotides in length, can exist as 106020 different sequences. To put this number in perspective, there are 1011 stars in the Milky Way galaxy and 1080 protons in the universe.

How many different viral genomes are present at any given time? Here is an interesting calculation in Virus Dynamics by Martin A. Nowak and Robert McCredie May (Oxford University Press):

Suppose that the average virus load in an (untreated) HIV infected person is 1010 particles and that this amout of virus particles is produced every day. Thus in 10 years, an HIV infected individual could generate about 1013 virus particles. All HIV infected people in the world could generate up to 1020 virus particles in the course of 10 years. If we assume that only 1% of the nucleotides in the HIV genome are variable (which is a gross underestimation), then there would be about 1060 HIV mutants that coincide in 99% of their genetic sequences. Thus the worldwide pandemic would only produce a fraction 10-40 of all such variants during 10 years. While HIV is extremely variable, at any one time only a minute fraction of all possible variants is present worldwide.

Most of the HIV virions produced in an infected individual appear to be nonviable, suggesting that the population exists at its error threshold. What would happen if we could push replicating genomes over the error threshold?

Viral quasispecies and bottlenecks

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The genome sequence of an RNA virus population clusters around a consensus or average sequence, but each genome is different. A rare genome with a particular mutation may survive a selection event, and the mutation will then be found in all progeny genomes. The selection process is illustrated in this diagram:

quasispecies-selection

The diagram on the left shows a small subset of the viral genomes that are present in a virus stock. Genomes are indicated by lines, and mutations are shown by different symbols. The consensus sequence for this population is shown as a line at the bottom. There are no mutations in the consensus sequence, even though every viral genome contains mutations. One of these genomes, indicated by the arrow, is able to survive a selection event (also called a genetic bottleneck), such as passage to a new host. This virus multiplies in the host and a new population of viruses emerges, shown by the diagram on the right. The consensus sequence for this population indicates that three mutations selected to survive the bottleneck are found in every member of the population. Error-prone replication ensures that the members of the new population have many other mutations in their genomes.

The type of population selection illustrated above most likely took place during the emergence of the new influenza H1N1 virus that is currently circulating globally. Imagine that the upper left diagram represents the sequences of one viral RNA segment of an influenza virus that is infecting a pig. The animal sneezes and several million viral particles are inhaled by a human who happens to be nearby. Of all the virions inhaled by the worker, only the one near the arrow can replicate efficiently in human cells. The three mutations are then present in that RNA segment of all the viruses that multiply in the human’s respiratory tract. Imagine similar selection events leading to a new population of viruses that are well adapted for transmission from person to person.

The quasispecies theory predicts that viruses are not just a collection of random mutants, but an interactive group of variants. Diversity of the population is critical for propagation of the viral infection. Recently it became experimentally feasible to test the idea that viral populations, not individual mutants, are the target of selection. We’ll examine those data next.

The quasispecies concept

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quasispecies1Until the late 1970s the diversity of viral populations was not widely appreciated. The first study to quantitatively describe viral diversity employed the RNA bacteriophage Q-beta. The authors made a startling conclusion based on their analysis of variation within stocks of the virus:

A Q-beta phage population is in a dynamic equilibrium with viral mutants arising at a high rate on the one hand, and being strongly selected against on the other. The genome of Q-beta cannot be described as a defined unique structure, but rather as a weighted average of a large number of different individual sequences.

This variation, which is a consequence of the error prone nature of viral replication, has since been confirmed using other viral systems. Virologists now understand that virus populations are not made of a single member with a defined nucleic acid sequence. Rather, they are dynamic distributions of nonidentical but related members called a quasispecies. It was given this name because the classical definition of species – an interbreeding population of individuals – has little meaning for viruses.

The consequence of a quasispecies is that most viral infections are initiated not by a single virion, but a population of particles. The progeny produced after this infection results from selective forces that operate inside the infected host. The virions that go on to infect a new host have passed through another set of external selective forces. A steady-state population of a viral quasispecies consists of a vast number of particles.

The diagram above shows a small subset of the viral genomes that are present in a virus stock. Genomes are indicated by lines, and mutations are shown by different symbols. The consensus sequence for this population is shown as a line at the bottom. There are no mutations in the consensus sequence, even though every viral genome contains mutations. This is because no mutation is present at sufficiently high levels to achieve a consensus at any position.

Although this concept may seem abstract, as we consider more aspects of viral biology it will become obvious. A key point is that the genome sequences of viruses cluster around an average sequence, but every genome is probably different from that consensus. This means that sequences of the new influenza H1N1 viruses on NCBI or GISAID sequences represent a consensus, and do not represent the population that infected any of the thousands of individuals in Mexico during the past month. Luis Villareal, a prominent evolutionary virologist, had the following thoughts about quasispecies and the current influenza epidemic:

Flu researchers believe in the master template as being the fittest type. I think this has been to their detriment and is currently confusing the field as we witness the evolution of emergence. I would be willing to bet money, that if the quasispecies composition were measured, we would see clear differences between those patients that died in Mexico compared to the much less virulent outcome in the USA.

Until recently it was not possible to know the sequences of all the viral genomes present in a population such as that illustrated in the figure. The development of deep sequencing methods such as 454 pyrosequencing has now made it possible to study the quasispecies. This method can detect the individual variants within a viral population.

Tomorrow we’ll consider how selection pressures within a host can change the quasispecies.

Domingo, E. (1978). Nucleotide sequence heterogeneity of an RNA phage population Cell, 13 (4), 735-744 DOI: 10.1016/0092-8674(78)90223-4

The error-prone ways of RNA synthesis

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Now that we have examined influenza viral RNA synthesis, it’s a good time to step back and look at a very important property of this step in viral replication. All nucleic acid polymerases insert incorrect nucleotides during chain elongation. This misincorporation is one of the major sources of diversity that allows viral evolution to take place at an unprecedented scale. Put another way, viruses are so successful because they make a lot of mistakes.

Nucleic acids are amazing molecules not only because they can encode proteins, but because they can be copied or replicated. Copying is done by nucleic acid polymerases that ‘read’ a strand of DNA or RNA and synthesize the complementary strand. Let’s start by examining DNA synthesis. Below is a DNA chain, which consists of the bases A, G, C or T strung together in a way that codes for a specific protein. In this example, the template strand is at the bottom, and consists of the bases A, C, C, T, G, A, C, G, and G (from left to right). A DNA polymerase is copying this template strand to form a complementary strand. So far the complementary bases T, G, G, A, and C have been added to the growing  DNA chain. The next step is the addition of a T, which is the complementary base for the A on the template strand:

dna-polymerase-1

So far all is well. But all nucleic acid polymerases are imperfect – they make mistakes now and then. This means that they insert the wrong base. In the next step below, the DNA polymerase has inserted an A instead of the correct G:

dna-polymerase-2

Insertion of the wrong base leads to a mutation – a change in the sequence of the DNA. In general, it’s not a good idea to make new DNAs with a lot of mutations, because the encoded protein won’t function well (but there are exceptions, as well will see). But in this case, there is a solution – DNA-dependent DNA polymerases (enzymes that copy DNA templates into DNA) have proofreading abilities. The proofreader is an enzyme called exonuclease, which recognizes the mismatched A-C base pair, and removes the offending A. DNA polymerase then tries again, and this time inserts the correct G:

dna-polymerase-3

Even though DNA polymerases have proofreading abilities, they still make mistakes – on the order of about one misincorporation per 107 to 109 nucleotides polymerized. But the RNA polymerases of RNA viruses are the kings of errors – these enzymes screw up as often as one time for every 1,000 – 100,000 nucleotides polymerized. This high rate of mutation comes from the lack of proofreading ability in RNA polymerases. These enzymes make mistakes, but they can’t correct them. Therefore the mutations remain in the newly synthesized RNA.

Given a typical RNA viral genome of 10,000 bases, a mutation frequency of 1 in 10,000 corresponds to an average of 1 mutation in every replicated genome. If a single cell infected with poliovirus produces 10,000 new virus particles, this error rate means that in theory, about 10,000 new viral mutants have been produced. This enormous mutation rate explains why RNA viruses evolve so readily. For example, it is the driving force behind influenza viral antigenic drift.

Here is a stunning example of the consequences of RNA polymerase error rates. Tens of millions of humans are infected with HIV-1, and every infected person produces billions of viral genomes per day, each with one mutation. Over 1016 genomes are produced daily on the entire planet. As a consequence, thousands of mutants arise by chance every day that are resistant to every combination of antiviral compounds in use or in development.

I cannot overemphasize the importance of error-prone nucleic acid synthesis in RNA viral evolution and disease production. We’ll spend the next two days examining the consequences of error prone replication. First we’ll consider the implications for viruses as a population, and then we’ll discuss the outcome when a virus produces an RNA polymerase that makes fewer mistakes. Please bear with me as we diverge slightly from influenza virus; these concepts will be an important and enduring component of your toolbox of virology knowledge.

Virology prediction for 2009: Virus evolution will continue

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1856663523_cffa76bfbc_mAt the end of each year, many websites, blogs, and podcasts (to name a few) summarize the past year’s events. We did the same at TWiV, naming our picks for the top 10 virology stories of 2008. Then, as the new year begins, many of the same sites predict what will happen in 2009. Such predictions are fine for areas like politics, technology, and the arts, but for virology, it’s just not possible to know what is going to happen. Why not?

The sources of viral diversity are mutation, recombination, reassortment, and selection. The interplay of these forces result in the changes in a viral population known as virus evolution.  The number of all possible virus mutants is so large that it can never be tested in nature. Sequence comparisons of some RNA virus genomes have revealed that over half of the nucleotides can be changed by mutation. In other words, for a 10 kB viral RNA genome, over 45000 sequences are possible. Since there are 4135 atoms in the visible universe, this is clearly an astronomical number. With so many possibilities, it is impossible to predict the future. And this does not even take into consideration the fact that we barely understand the selective forces acting upon viral populations in nature.

The problem is best summarized in Principles of Virology: “Those who seek to predict the trajectory of virus evolution face enormous challenges, as mutation rates are probabilistic and viral quasispecies are indeterminate”.

We can make one virology prediction for 2009: that virus evolution will continue. New viral mutants will arise, and the possibilities are unfathomable. The new viruses that arise will come from those existing today, by mutation, recombination, and reassortment.

H5N1 expert says ‘The virus is definitely mutating’

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Guan Yi, an expert on H5N1 influenza virus, is quoted in China Daily as saying that “The virus is definitely mutating”.

Yi’s comments were in reference to the continuing pandemic of H5N1 influenza in poultry farms. He indicates that some farms are using a vaccine against an American H5N2 strain, which is not likely to be fully protective against the currently circulating H5N1 strains. In the past 10 years, at least 10 strains of the H5N1 virus have been identified, providing the fodder for Dr. Yi’s overly obvious statement.

I find it hard to believe that a virus ‘expert’ would ever make such a statement as ‘the virus is definitely mutating’. Virus genomes continuously undergo mutation, as a consequence of error-prone nucleic acid polymerases. The error rate for RNA virus genomes is phenomenal, because the viral polymerases cannot correct its mistakes. The error rates for viral RNA-dependent RNA polymerases have been estimated to be between 1 in 10,000 to 100,000 nucleotides polymerized. For a virus with a 10 kb genome, a frequency of 1 in 10,000 means that each RNA produced contains at least one mutation. Dr. Yi states the obvious when he says that the H5N1 virus is mutating. The genomes of these viruses are constantly undergoing change, not just in this specific outbreak.

What should Dr. Yi have said? I would have indicated that the rapid change in the antigenic composition of circulating H5N1 strains is likely rendering the vaccine ineffective. Maybe he said that, but was misquoted by the press. These things do happen, right?