[1] https://onlinelibrary.wiley.com/doi/abs/10.1002/jmv.25902
[1] https://onlinelibrary.wiley.com/doi/abs/10.1002/jmv.25902
https://blogs.sciencemag.org/pipeline/archives/2020/05/07/mu...
Someone reading this might be wondering how speciation can be measured with viruses, since viruses don't reproduce sexually. Well, we don't test whether different species of animals can reproduce with each other. There's no way to conduct such experiments at any meaningful scale. The vast majority of defined species are educated guesses, and in reality has very little to do with whether two groups of organisms can reproduce with each other. In a lot of cases, species are simply determined by the appearance or behavior of one group of organisms over another group of closely related organisms. The term "species" didn't even originally have anything specifically to do with reproduction; the word effectively meant "looks like", which is why the words "species" and "spectacle" share the first 4 letters.
"They've been in the room an hour, sir. Nothing's happening."
"Hmmm... Ok, looks like polar bears and flamingoes are different species. Mark that down. Next on the list... swap out the flamingo for the barnacle. Be sure to keep watching closely."
Viruses clearly reproduce with humans. By a strict "reproduction / species" definition, Viruses are human.
The species definition you brought up does not apply to asexual organisms, for them it's a matter of genomic analysis. As for sexual organisms, it is still a good definition because it is stricter and more "correct" than genomic analysis, although bioinformatics has been getting pretty good with the addition of more sophisticated statistical techniques that go past simple DNA-DNA hybridization.
Put more simply, two samples of virus can be of the same "strain" even if they aren't _exactly_ the same sequence. This is because replication can sometimes make errors on segments of the genome that do not impact functionality - moreover these same irrelevant loop segments are not error-corrected either, so mutations are common - despite not modifying the properties of the virus. These irrelevant mutations are actually very useful for tracking the virus spread.
A virus mutation becomes a different "strain" when the change is meaningful for the viruses interaction with the host or the environment.
SARS-COV2-2 is a type of virus that does error correction (unlike flu), so the rates of mutation are extremely low. This is good news because if means a vaccine will work, and we won't need a yearly one - like the flu.
You are literally nitpicking the wrong people here. They're trying (well, I thought, though clearly not well enough to satisfy HN pedants) to explain the distinction in a way that conveys the fact that there are no known distinct outbreaks with different medical properties. How that's for precision?
That's way ahead of the facts. It means we're more likely to be able to develop a vaccine that works and it's more likely we won't need frequent vaccination to be effective.
Vaccine success involves a certain amount of finger crossing, because it's a natural system rather than an engineered one that we're trying to tamper with. If you've ever boggled at a large spaghetti program, the human immune system makes that look like two dozen lines of clearly documented Java by comparison. None of it has to make sense because Mother Nature doesn't care why she only does results, and in the most brutal way possible.
This is why we've got a bunch of different vaccine programmes in different centres. Some of them might work, hopefully at least one does, and hopefully it produces an immunity that lasts a useful amount of time, has minimal side effects and is cheap to produce in bulk. But there aren't any promises without us having way more advanced biotechnology than exists anywhere today.
Of course, that also means that detecting different strains is dependent on understanding those interactions and where they differ. If the post-infection cluster of pediatric multisystem inflammatory syndrome in NYC isn't just NYC being better at identifying that effect, it could well be a sign of a different strain with meaningfully different interactions with hosts. (It could still be a variety of other things, too.)
Doctors in the UK were seeing this throughout April, and issued an alert in late April: https://twitter.com/PICSociety/status/1254508725227982848
https://www.santafenewmexican.com/news/coronavirus/lanl-find...
What is the biological process that does this? I'd love to learn more.
Influenza is smaller about 13K nucleotides vs 30K for corona, it mutates about 4 times faster. It can maintain its larger genome basically because it has better tech. (It seems to better integrate with what it can find in host cells.)
"We demonstrate here, at the molecular level, that CoVs have indeed acquired an enzyme able to enhance the overall fidelity, and that this event might have directly promoted the jump in size of CoV genomes"
"Well before the discovery of nsp14-ExoN in the large Nidovirales genomes (22), this observation led to Drake’s visionary proposition that “RNA viruses would have to acquire several host genes and adapt them to RNA substrates to achieve a major reduction in spontaneous mutation rate. The result would be a substantial increase in genome size” "
https://www.pnas.org/content/115/2/E162
https://www.ncbi.nlm.nih.gov/genomes/GenomesGroup.cgi?taxid=...
https://www.ncbi.nlm.nih.gov/nuccore/1798174254
"Specifically, SARS-CoV-2 seems to have a mutation rate of less than 25 mutations per year, whereas the seasonal flu has a mutation rate of almost 50 mutations per year."
What about the reports of different strains that focus on having found them having different properties (such as "much more infective")? Are they bogus?
[1] https://www.biorxiv.org/content/10.1101/2020.04.29.069054v1....
In any case, there are multiple credible sources that some of the mutations of the SARS-CoV-2 have a meaningful effect. In which case the claim of this article that "there's only one strain" may be technically correct (based on some obscure scientific definition), but completely misguiding as far as the general public is concerned.
[1] https://english.alarabiya.net/en/features/2020/03/25/Coronav...
I don't see any support at all for that theory though. It is also known that "X show no symptoms" could mean many things, depending who says it and when, and certainly doesn't prove anything alone, only in context, compared to something else, and only when comparison is fair.
For example, from many old news, those "with no symptoms" eventually had the symptoms, it was just that the tests were positive before they developed the symptoms. Second, it is now known that the probability of "having" symptoms is very dependent on the age of the person.
I didn't have a particular paper in mind that I remembered.
Just remember reading several articles in the past month about new strains. Some examples are easy to find:
https://www.abc.net.au/news/2020-05-06/new-coronavirus-covid...
https://www.cnbc.com/2020/05/05/the-coronavirus-mutated-and-...
https://www.usnews.com/news/health-news/articles/2020-05-06/...
E.g. somebody claiming they invented a perpetual motion machine.
Their claims might not include any conspiracy involved, just a bogus idea of what they accomplished...
Strain implies functional differences. SARS-CoV-2, like it’s Coronavirus cousins, is quite stable. The genomic sequences found on NextStrain.org are a powerful tool to track the spread of this virus but it is wrong to assume that the difference in each “isolate” carries with it a functional difference; it does not.
The blog post comes from the same scientists that create the TWiV (This Week I’m Virology) podcast which continues to be a tremendous source of quality information for me.
Is that what people are assuming?
It's not that every mutation causes a [medically relevant] functional change, it's that a mutation could have. And, AFAIK, we don't have the ability to sequence _and_ relate sequences to differences in symptoms in the general case at present.
Maybe in 10 years someone will have developed an AI to relate RNA sequences, medical history, and functional changes in real time??