THREAD - What happened at the Huanan #seafood market?
The @WHO report is quite clear on this point: #SARSCoV2 might have jumped from a wild animal sold in this market and maybe other markets in #Wuhan. But what do we know exactly? 1/15
After all this time, the Huanan seafood market still remains the main suspect for a simple reason: most of the early cases had visited at least one market in Wuhan city, and several of them visited the Huanan market. 2/15
According to the report, 10,000 people visited this place every day, making it a perfect setting for an #outbreak. One might argue: what about the cases without market exposure? Good question! 3/15
However, if we plot the early cases according to the onset date, we notice that the cases with market exposure peaked earlier than those without it. In other words, the virus appeared first in the markets and then started spreading outside. 4/15
Interestingly, the first case didn't visit the Huanan market, but another supermarket in the Southern part of the city, more than 20 km away from the Huanan market. Due to the high number of cases, though, Huanan got all the attention. 5/15
Unfortunately, once you enter the market, few things make sense. First of all, only 10 out of 678 stalls sold wild (domesticated) #animals: remember this is a #seafood market, and most products were aquatic or seafood. Not ideal hosts for SARS-CoV-2! 6/15
Second, those 10 vendors didn't even sell live #mammals. According to sale records from December 2019, most animals were frozen/dead. Only #crocodiles were sold alive, while live #snakes and #salamanders were slaughtered before being sold. 7/15
The @WHO team even interviewed two local residents who had been visiting the market for 20-30 years: they never witnessed any live animal being sold. But old photographs and media reports suggest the opposite, so.. Who knows! 8/15
Anyway, Chinese scientists tested several animals or parts of animals in the market area. Some species are now known to be susceptible to SARS2 infection (#rabbits, #cats, #badgers), but unfortunately no sample tested positive. 9/15
They did find some positive samples though: not animal, but #environmental samples (surfaces, sewage, etc). Interestingly, the highest % of positive samples were found in stalls selling #vegetables and #poultry (which can't be infected). 10/15
Ok, but what about the early cases? 30 of them were vendors at the Huanan market, but none of them sold domesticated animals: in fact, the highest % of positive cases were among people selling #vegetables. Weird! 11/15
Also checking the very first cases in the market did not help. This market is a brain teaser! 12/15
Let's recap: no live mammal was officially sold, no vendor selling wildlife products tested positive and only one environmental sample tested positive in their stalls. So where did SARS2 come from? 13/15
Nobody really knows. However, the @WHO experts think there are interesting clues: some of the #wildlife vendors sold animal products coming from farms in Southern China, where SARS-CoV-2 closest relatives were found. 14/15
Scientists hope that sampling more animals among the market suppliers will finally reveal the source of SARS-CoV-2. Easier said than done: more than 80,000 samples from livestock, poultry and wild animals across China have already been tested. All negative! 15/15
La prima permette a SARS-COV-2 di legarsi meglio al recettore ACE2, in altre parole i virus con questa mutazione riescono a entrare più facilmente nelle nostre cellule. 1/
Variante inglese 🇬🇧 (B.1.1.7), sudafricana 🇿🇦 (B.1.351) e brasiliana 🇧🇷 (P.1) hanno tutte quante la mutazione N501Y.
Probabilmente, è proprio per questo motivo che queste varianti tendono a essere più contagiose. 2/
La E484K, invece, aiuta il virus a sfuggire agli #anticorpi, pertanto potrebbe ridurre in parte l'efficacia dei #vaccini.
La #varianteinglese non ha questa mutazione (per ora), ma brasiliana e sudafricana sì. Per questo sono così temute! 3/
Question for bioinformaticians! Believe it or not, the first genome of bat virus #RaTG13 had some nucleotides that were supported by zero reads: in other words, the genome didn't match the sequences that were used to assemble it. How is it possible? 1/ #originsofSARSCoV2
Assemblers are computer programs, they do not "invent" nucleotides. So, what happened here? My explanation was that this genome was assembled using other reads, maybe in addition to the ones that were uploaded. 2/
In that case, I expected the authors to upload the missing reads.. Instead they did the opposite: they updated the genome, replacing the nucleotides supported by zero reads with the correct ones. So, the question is: how the heck did they assemble the genome the first time? 3/
Conspiracist, May 2020: "Look, these sequences in database are dated 2017/2018. So you didn't sequence RaTG13 this year, as you wrote in the paper!" 🔬
Average scientist, May 2020: 😴
Shi Zhengli, July 2020: "Yes, actually we got the sequence in 2018."
2/
Conspiracist, May 2020: "Have a look at these Chinese theses we found on the internet: RaTG13 was found in a #mineshaft were people died of #pneumonia!" 😱
Average scientist, May 2020: 😴
Shi Zhengli, June 2020: "Oh yes we found it there, but.. well, the cause was a fungus"
3/
Ora, è vero che a Wuhan facevano chimere a scopi di ricerca, ma questi due virus sono troppo diversi da SARS2 per essere i suoi antenati diretti. 2/
Il nuovo #coronavirus infatti ha una similarità dell'87% con questi due virus, troppo poco per essere il risultato di una loro ricombinazione (il virus più simile a SARS2 è #RaTG13). 3/
Il modello di @istsupsan che ha guidato le decisioni del governo sulla fase 2 è un modello SIR stocastico strutturato per età. Uno dei punti di partenza è questa tabella, che quantifica i contatti medi degli italiani in base a età e luogo del contatto. 1/
La suddivisione dei lavoratori in base al settore di attività (es. edilizia, manifattura) si basa su dati INAIL. Il modello fa molte assunzioni: ad esempio ipotizza che i contatti nel tempo libero passino dal 10% (dati Google) al 34% in caso di apertura di bar e ristoranti. 2/
Le simulazioni prevedono due modalità di trasmissione della malattia: uno immagina che siamo tutti ugualmente suscettibili all'infezione, l'altro ipotizza che gli anziani siano più suscettibili della fascia 15-64, che a sua volta è più suscettibile dei bambini. 3/