This holiday season, many of us will have enjoyed the convenience of ordering presents online. Want gift, find gift, buy. Behind the scenes, your gift was found in a warehouse full of other stuff, selected by a person or machine, labelled with a delivery address and transported to the right place (hopefully your door!). But what if you’re a flu virus, hanging out inside a lung cell with only the gift of more flu on your wish list?
Down at the size of molecules, nobody is going to take your order. Influenza has a genome made out of 8 separate segments of RNA, each containing genes essential for building the virus. Imagine one long set of instructions, but chopped into eight pieces. If you have one complete piece of genetic material – like Poliovirus, for example – you have the easy task of sticking exactly one copy of RNA into one empty virus shell before leaving the infected cell. If you’re flu, you need to collect eight pieces: eight different pieces.
Headache. But just how good is flu at stuffing itself with RNA?1
According to an article published in 2013, flu doesn’t care much for finishing the full set. When Brooke and colleagues2 looked at infected cells using fluorescent antibodies to see the flu virus’ proteins, they found many in which at least one protein was missing. Some of these proteins included HA and NA, proteins sitting on the outside of the virus that act as both the key into cells and the knife to cut the virus free – in short, proteins the virus needs to spread between cells and people.
This observation is weird because it suggests that some flu viruses either don’t carry all eight RNA segments (after all, no HA gene segment in the incoming virus = no HA protein in the infected cell), or that individual genes just randomly fail to be read during infection.
To the last point, the authors infected the same type of cells with Vesicular Stomatitis Virus (VSV), which has a genome made from just one piece of RNA. When they looked at the production of two VSV proteins during infection, they couldn’t find cells in which one or the other was missing – failing to make proteins at random doesn’t look like a regular foible of virus infection. The authors are also trying to make the point here that unlike flu, VSV can’t misplace any of its genome, and perhaps this explains the difference between the viruses when it comes to gene expression3. Maybe. But these data are a bit weak for me – they’re different viruses. You wouldn’t infer dog behaviour by studying cats.
Much better evidence comes from flow cytometry experiments analysing many thousands of cells for the presence and absence of individual virus proteins. Not only is this approach higher throughput, but it also allowed the authors to study the effect of increasing the amount of flu used to infect the cells. When flu virus was outnumbered by cells, more than half of all infected cells were shown to have at least one flu protein missing. But by increasing the amount of flu so as to outnumber the cells, the vast majority then contained a full set of virus proteins4. Whilst a large number of individual flu viruses are sloppy enough to forget segments of their genome, when they gang up in the same cell, together they have everything they need.
Looking for proteins is cool, but viruses live and die on their ability to transmit themselves to new cells. When the authors looked at flu’s ability to spread to new cells5 they found that this happened just over a tenth of the time. By all accounts, this suggests that influenza is rubbish at its job of making more flu. And yet yearly flu epidemics suggest otherwise.
I think we virologists6 get hung up on a faux “physiological relevance” when we study viruses in a dish. We have the ability to infect cells with billions of virus particles, but as most people don’t get infected by a scientist wielding a pipette, we imagine the individual invaders staking their claim to just a few cells in our body. Therefore, when it comes to scientific thinking, experimenting with low virus concentrations appears to be inherently more “realistic” than high concentrations. This thinking is probably correct when a host is first infected, but once each hijacked cell begins to spew out hundreds of new viruses into the neighbourhood, co-infection of nearby cells with 10’s to 100’s of viruses is probably common. All this is to say, if flu needs more than one virus to infect a cell successfully, no problem.
That aside, what I find most interesting about this work is the idea that influenza infects as a swarm of viruses by necessity. Flu, like many RNA viruses, is renowned for the sloppy reproduction of its genetic code. What we have here is not only a virus that creates a population of mutants in its host, but a virus that appears to be critically dependent on co-infection of cells to successfully complete its life cycle.
Some final thoughts on this study. I’d have liked to see some effort to address the impact of defective interfering particles (DIPs) on these results. DIPs are viruses with a large deletion in one or more of their genome segments and crop up in lab stocks of flu. Cells infected with DIPs would appear just the same as the cells studied in this work: missing one or more flu proteins. While I doubt DIPs can explain the high frequency of cells observed to lack flu proteins, the suggestion that influenza often fails to package its entire genome is extraordinary and thus needs all the evidence it can get – including ruling out a significant contribution from other known phenomena.
Also, regarding the infectious foci assays, it would be interesting if the relatively rare clusters of infected cells the authors observed were actually the result of co-infection themselves – just how often can a flu virus go in alone and be successful?
This study looked at flu infection of cells in a dish, but what’s the story in a complex species like a rodent or human? More on this next time.
- I’m only covering one article today (and another related piece soon!), but I’ve no desire to sell the field short: there’s a wealth of research into flu genome packaging that I can’t get into now. Here’s a great open access review if you want to get your teeth into this area: Hutchinson et al. 2010.↩
- Brooke et al. 2013. (Open Access)↩
- Authors! This would be way more compelling if you could have looked at more than 2 VSV proteins, and also quantified the analysis with flow cytometry to make a better point. #nitpick↩
- I’d like to bring you a number here, but this isn’t directly quantified in the paper. Check out the flow cytometry in Figure.3D to see how the top right hand quadrant of the graph (NA and HA co-expression) increases in intensity as multiplicity of infection (the number of viruses per cell) increases.↩
- The authors used an infectious foci assay here, whereby they looked at cell layers with fluorescent antibodies to flu proteins again. After 15 hours they could see either single infected cells or clusters. In the clusters, the virus had colonised the neighbouring cells around the original victim.↩
- By which, I essentially mean ME. Me, me, me.↩