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Jun 9 17 tweets 10 min read
In a new preprint led by @annasimsbiol, we ask:
Why Don’t These Viruses Want to be Friends?
A 🧵...
biorxiv.org/cgi/content/sh… An image showing two infected regions, one green and one mag
Coinfection is an important aspect of viral evolution. If two viruses can get into the same cell, they can undergo genetic exchange. A dramatic example of this is when different strains of influenza A virus (IAVs) use coinfection to generate novel pandemic strains A schematic showing a green and magenta virus coinfecting a
However, many viruses actively push back against coinfection. In a variety of ways, they change an infected cell until it becomes resistant to infection by related viruses. This effect is known as superinfection exclusion (SIE) A schematic showing a cell infected by a green virus which,
What does this mean for coinfection? In the lab we can set up experiments in which cells are coinfected simultaneously, but the chances of two unrelated viruses actually entering a host organism, and finding exactly the same cell, at exactly the same moment are… slim
Instead, we assume that, for viruses such as IAVs, unrelated viruses first establish separate infections inside a host, and then encounter each other when those infections spread through tissue. How would SIE control these spreading infections?
Following infections inside a living animal is not easy. Instead, we started with cells, using two IAVs that differed only in the colour of a fluorescent tag. SIE by IAV is rapid and early – there is a short window for coinfection, and then the door slams closed, fast A graph showing the proportion of cells infected with a gree
Next, to observe spread we used everyone's favourite model of virus spread: the #PlaqueAssay. When different spreading viruses meet, or two plaques bump together, coinfection can only occur in a thin boundary of recently-infected cells. Beyond that point, SIE is fully effective Coinfection limited to a thin boundary of cells between a gr
But what about interactions within a single spreading region? To look at this we needed plaques that started with a mixture of the two viruses. As the mixed plaques spread, would coinfection be maintained, or would the plaques segregate into regions descended from a single virus? Two models of a spreading plaque, one in which coinfection b
To set up mixed plaques we coinfected cells simultaneously, dissociated them with trypsin, diluted them, then reseeded them onto new cells so that each coinfected cell was a plaque forming unit. We found… A schematic showing the cell seeding method described in the
… that they stayed well mixed as they spread. This wasn’t the result we expected, but it makes sense – each new cell in a growing plaque can receive plenty of both colours of virus before SIE kicks in A spreading plaque of green and magenta viruses, maintaining
This is all very well and good, but is it just a cell culture artefact? Plaque assays are not lungs, after all.
So we infected mice with both viruses… A micrograph showing a thick section of a lung infected with
… and found that once lesions had grown there were clear boundaries between the two colours inside the same anatomical compartments. So it seems SIE can impose its patterns inside a host as well as in a dish Distinct regions of green and magenta infection in the same
What does this mean?
•Within a host IAV naturally partitions into a landscape of microdomains
•Within domains genetic exchange is maintained but between them it is inhibited
•Because it relies on kinetics, rather than a specific mechanism, this could apply for many viruses A landscape of green, magenta and mixed infections in the sa
Things not in the paper but worth mentioning.
This project was triggered by two ideas:
(1) listening to #TWiV while lagging the loft, I heard about this cool paper and thought ‘I wonder if flu does that?’ (it probably doesn't, but...)
pubmed.ncbi.nlm.nih.gov/30318351/
... and (2) after a seminar in which I carelessly claimed cells inside a host would get coinfected all the time, @Digs66768072 asked the best and most annoying question in science, which is of course
‘… but why do you think that’s true?’
(It was not true)
… But most of all thanks to lead author @annasimsbiol,

all of whose infections

are super

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More from @CVRHutchinson

Sep 21, 2021
A quick Tweetorial about our new paper with the #BoutellLab, which @CharmanMatthew led during his PhD @CVRinfo

Alternative title: ‘Why are virologists’ cells stupid and does this matter?’ 🧵 (1/N)
If you work with human influenza viruses in the lab you most likely grow them in MDCK cells, or possibly MDBK cells, or maybe A549 cells if you are fussy enough to want a cell line that comes from (a) the right organ system and (b) the right species of animal (2/N)
These cell lines are super-convenient – they grow forever, and it’s so much easier to grow influenza in them than in, say, human bronchial epithelial cells. Great, right? (3/N) Influenza does not like growing in primary lung cells
Read 11 tweets
Dec 31, 2020
Earlier this year, @Scient_Art collaborated with us to produce one of the first detailed 3D models of the #SARSCoV2 virus particle. To round off 2021 she's updated her model, and it looks great (1/N) Image
... the first model drew heavily on existing work on related viruses (SARS-CoV-1 and MHV). The updated model has an improved representation of the spike protein, building on the detailed model from @RommieAmaro's lab (pubs.acs.org/doi/10.1021/ac…) (2/N) Image
The spacing and flexing of the spikes was also updated based on cryoEM data, particularly from the labs of @BriggsGroup (disq.us/t/3r34r8p) and @drlisai (doi.org/10.1016/j.cell…) (3/N) Image
Read 7 tweets
Jun 18, 2020
We’ve just had a paper published and I would like to tell you a story about people in science being nice to each other – a thread cell.com/cell/fulltext/…
This is a large, collaborative effort – 54 authors across multiple institutions, led @MountSinaiNYC and @CVRinfo. But the science in the story is quite simple (and you can read it in the paper), so I’ll explain it quickly before telling a different story (which you cannot)
Briefly, here’s the science of it. THE BACKGROUND: (i) Viruses need to make mRNA that host ribosomes can translate into proteins Baltimore classification of viruses
Read 35 tweets
May 27, 2020
Thread! It’s great to have been able to collaborate with @Scient_Art on a detailed model of the #SARS-CoV-2 virus particle, the cause of #COVID-19, using methods we’ve developed with @GSofASimVis @GSofA and @CVRinfo #scicomm #sciart (1/13) Image
These have been used by @snjasim to illustrate an @UKRI_News article on ‘Getting to know the new coronavirus’ coronavirusexplained.ukri.org/en/article/cad… (2/13)
Thanks to @Scient_Art and @GlasgowLifeSci you can explore #SARS-CoV-2 in 3D on @Sketchfab here: sketchfab.com/3d-models/sars… (3/13) Image
Read 13 tweets

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