Название | Principles of Virology |
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Автор произведения | Jane Flint |
Жанр | Биология |
Серия | |
Издательство | Биология |
Год выпуска | 0 |
isbn | 9781683673583 |
METHODS
How to read a phylogenetic tree
Phylogenetic dendrograms, or trees, provide information about the inferred evolutionary relationships between viruses. The example shown in the figure is a phylogenetic tree for sequenced viral isolates from 10 different individuals. The horizontal dimension of the tree represents the degree of genetic change, and the scale (0.07) is the number of changes divided by the length of the sequence (in some trees this may be expressed as % change). The blue circles, called nodes, represent putative ancestors of the sampled viruses. Therefore, the branches represent chains of infections that have led to sampled viruses. The vertical distances have no significance.
The tree in the figure is rooted, which means that the root of the tree represents the common ancestor of all the sampled viruses. As we move from the root to the tips, we are moving forward in time, although the unit of time might not be known. The numbers next to each node represent the measure of support; these are computed by a variety of statistical approaches including “bootstrapping” and “Bayesian posterior probabilities.” A value close to 1 indicates strong evidence that sequences to the right of the node cluster together better than any other sequences. Often there is no known isolate corresponding to the root of the tree; in this case, an arbitrary root may be estimated, or the tree will be unrooted. In these cases, it can no longer be assumed that the order of ancestors proceeds from left to right.
Phylogenetic trees can also be constructed by grouping sampled viruses by host of isolation. Such an arrangement sometimes makes it possible to identify the animal source of a human virus. Circular forms, such as a radial format tree, are often displayed when the root is unknown.
Trees relating nucleic acid sequences depict the relationships as if sampled and intermediary sequences were on a trajectory to the present. This deduction is an oversimplification, because any intermediate that was lost during evolution will not be represented in the tree. In addition, any recombination or gene exchange by coinfection with similar viral genomes will scramble ordered lineages.
A fair question is whether we can predict the future trajectory or branches of the tree. We can never answer this question for two reasons: any given sample may not represent the diversity of any given virus population in an ecosystem, and we cannot predict the selective pressures that will be imposed.
Hall BG. 2011. Phylogenetic Trees Made Easy: A How- to Manual, 4th ed. Sinauer Associates, Sunderland, MA.
ViralZone. Phylogenetics of animal pathogens: basic principles and applications (a tutorial). http://viralzone.expasy.org/e_learning/phylogenetics/content.html
Figure 2.18 Comparison of bacterial and viral reproduction. (A) Growth curve for a bacterium. The number of bacteria is plotted as a function of time. One bacterium is added to the culture at time zero; after a brief lag, the bacterium begins to divide. The number of bacteria doubles every 20 min until nutrients in the medium are depleted and the growth rate decreases. The inset illustrates the propagation of bacteria by binary fission. (B) One- and two-step growth curves of bacteriophages. Growth of a bacteriophage in E. coli under conditions when all cells are infected (left) and when only a few cells are infected (right).
The results of these experiments defined two new terms in virology: the eclipse period, the phase in which infectivity is lost when virions are disassembled after penetrating cells, and the latent period, the time it takes to replicate and assemble new virus particles before lysis, ∼20 to 25 min for some E. coli bacteriophages.
Synchronous infection, the key to the one-step growth cycle, is usually accomplished by infecting cells with a sufficient number of virus particles to ensure that most of the cells are infected rapidly. Exactly how many virus particles must be added is described by the multiplicity of infection (Box 2.11).
One-Step Growth Analysis: a Valuable Tool for Studying Animal Viruses
One-step growth analysis soon became adapted for studying the reproduction of animal viruses. The experiment begins with removal of the medium from the cell monolayer and addition of virus in a small volume to promote rapid adsorption. After ∼1 h, unadsorbed inoculum containing virus particles is removed, the cells are washed, and fresh medium is added. At different times after infection, samples of the cell culture supernatant are collected and the virus titer is determined. The kinetics of intracellular virus production can be monitored by removing the medium containing extracellular particles, scraping the cells into fresh medium, and lysing them. A cell extract is prepared after removal of cellular debris by centrifugation, and the virus titer in the extract is measured.
The results of a one-step growth experiment establish a number of important features about viral reproduction. In the example shown in Fig. 2.19A, the first 11 h after infection constitute the eclipse period, during which the viral nucleic acid is uncoated from its protective shell and no infectious virus can be detected inside cells. The small number of infectious particles detected during this period probably represents adsorbed virus that was not uncoated. Beginning at 12 h after adsorption, the quantity of intracellular infectious virus particles begins to increase, marking the onset of the synthetic phase, during which assembly begins. During the latent period, no extracellular virus can be detected. At 18 h after adsorption, virions are released from cells into the extracellular medium. Ultimately, virus numbers plateau as the cells become metabolically and structurally incapable of supporting additional reproduction.
DISCUSSION
Multiplicity of infection (MOI)
Infection depends on the random collision of cells and virus particles. When susceptible cells are mixed with a suspension of virus particles, some cells are uninfected and other cells receive one, two, three, etc., particles. The distribution of virus particles per cell is best described by the Poisson distribution:
P(k) = e–mmk/k!
In this equation, P(k) is the fraction of cells infected by k virus particles. The multiplicity of infection, m, is calculated from the proportion of uninfected cells, P(0), which can be determined experimentally. If k is made 0 in the above equation, then
P(0) = e–m