Why Are Some Virus Capsids So Geometric?

Why Are Some Virus Capsids So Geometric?

Keywords – viral capsid, assembly, symmetric, geometric, icosahedron, subunits, pentamers, hexamers

phage heads
Upon doing some literature searching for phages, I came across a paper written in 1967 on the topic of ultrastructure of phages. Scrolling through, there were some subjectively pretty microscopy images of infecting phages and other diagrams. The diagram of phage head shapes in particular caught my eye. I began to think about how nice and satisfying the symmetry and geometry is in bacteriophages. I then wondered why phage heads have this characteristic and what advantages it has.

The general structure of a phage head:
A phage head is formed of either 2 or 3 parts. All freshly formed virions have a core of genomic material. This could be double or single stranded RNA or DNA. This is surrounded by the capsid. This is a proteinaceous coat, formed of number of identical subunits, which may be formed by even smaller molecular subunits. These subunits are called capsomeres [1].

Why the patterns?
It seems I am not the only one to question this, and in fact the question was almost fully answered by Crick and Watson back in the 1950s. They were studying small viruses, and hypothesised that the virus requires the protein coat to protect its genomic material. The best and most efficient way to do that is to form the coat from lots of small identical molecular subunits. These are then easier to produce when inside the host cell than say, one or two large molecules. These subunits also have the added advantage that they can only arrange themselves in so many ways around the core to create a shell [2].

So, this explains why capsids tend to have such a regular shape. But what other advantages does this confer?
Perhaps this can be put down to evolutionary adaptations. The easier the molecule is to reproduce; the more virion offspring are produced. It also makes sense that identical subunits can only attach in so many ways, and that this results in a pattern, seen in all those offspring. But this formation seems to be like puzzle pieces, in that this method does not require any energy [3]. This is ideal for spontaneous formation of virion capsids in the host cell, as the virus does not have to concern itself with sequestering energy from elsewhere.

Phage heads tend to take on the shape of a platonic body; one of five regular shapes, of which only octahedrons and icosahedrons have been seen using microscopy. Icosahedrons, as seen in the image below, are commonly seen in phages, and are 20 sided shapes with 12 vertices. This geometry offers stability and strength [4].

Another way is to look at this from the genetic material’s point of view. It needs to be protected from stray or attacking enzymes and needs a way to nicely organise itself. These structures not only allow for nice neat organisation of the genome, but also by doing this, it can create secondary characteristics. For example, it is thought that some regions can take on translation and replication roles, brought about by the way that the nucleic acids are stored within the capsid, allowing them to form double-stranded loops, such as in Leviviridae viruses [5].

It seems that these phage heads are well adapted to their purpose. I’m sure we can all agree that they are very clever and the stuff of nightmares!!!


Post by Jessica Friedersdorff.

[1] Bradley DE. Ultrastructure of bacteriophage and bacteriocins. Bacteriol Rev 1967;31:230–314.
[2] Crick FH, Watson JD. P1-Structure of small viruses. Nature 1956;177:473–5.
[3] Bruinsma RF, Gelbart WM, Reguera D, Rudnick J, Zandi R. Viral self-assembly as a thermodynamic process. Phys Rev Lett 2003;90:248101. doi:10.1103/PhysRevLett.90.248101.
[4] Mannige R V., Brooks CL. Periodic table of virus capsids: Implications for natural selection and design. PLoS One 2010;5:1–7. doi:10.1371/journal.pone.0009423.
[5] Morais MC. Breaking the symmetry of a viral capsid. Proc Natl Acad Sci 2016;113:201613612. doi:10.1073/pnas.1613612113.

But what does it mean?!?


But what does it mean?!?

During practical-based modules, I often ask undergraduates to start their practical reports with a statement of their hypothesis. This usually throws them into a mild panic, as class practicals are primarily about generating data rather than proving/disproving a hypothesis and they cannot easily negotiate that apparent disparity.

The relationship between data-generating and hypothesis-driven research is a troubled one. Twenty years ago, a loud and often-heard cry of the experimentalist after a ‘big data’ or ’-omics’ talk was ‘but what IS the hypothesis?’. Testing a hypothesis was the mantra of every bench scientist, and even today some funding agencies and scientific publishers still insist on placing hypotheses front and centre of all submissions.

But what was the hypothesis being tested when the E. coli genome was sequenced? Should we look down our noses disapprovingly at the humble genome, denigrated as a mere ‘fishing trip’, or ‘stamp collection’, because of its lack of a noble hypothesis? Do we emulate my poor undergraduates and struggle valiantly to find a hidden rationale behind the data-collecting exercise and justify its existence? Or should we celebrate the diversity, abundance and scale of the datasets that we can now generate, with or without accompanying hypothesis?

We can’t all be the ones to discover the next cure for cancer, or the novel antibiotic to which there is no possibility of resistance. However, we can all contribute resources to aid those explorers in their search. Those resources can be new knowledge, acquired through the steadfast testing of hypotheses, or they can be collections of datasets, alongside the tools and knowhow to interrogate those data.
The genome is the ultimate blueprint of an organism’s biology, however we have barely begun learning how to look inside a genome, and from its sequence deduce salient features of the host’s biology. Hypothesis-led experimentation is one way to improve our understanding of the sequence/function relationship, and now increasingly we find ourselves testing hypotheses that have themselves come directly from big datasets.

In essence, big datasets are trying to tell us everything we want to know, but to get there we need to find out what questions to ask, for which they are the answer.

Post by Dr. Dave Whitworth.