Anil Rinat for the New York Times
The COVID-19 pandemic was a lesson in speed:
the speed with which a new virus can spread among humans; the speed with which it can accumulate deaths and paralyze economies; the speed with which vaccines can be developed and produced and the speed with which misinformation can harm public health.
In the midst of all this speed there is a different speed, which makes the others move, like the engine that makes the booths of the fairs spin soaring: the speed of the viral evolution.
Coronavirus, like many other viruses in its class (RNA viruses with highly variable genomes), evolves rapidly.
He immediately adapted to us.
Now the fundamental question arises whether humans and their ingenuity can adapt faster.
Unless the answer is yes, we face a long and pitiful future of continued suffering.
Some experts estimate that the death toll from the endemic COVID-19 could be between 100,000 and 250,000 per yearonly in the United States.
Millions of lives depend on human science, governance and wisdom to overcome SARS-CoV-2, a relatively simple but entrepreneurial agent made up of four proteins and an RNA genome.
Carlo Darwin He said that the mechanisms of evolution never act quickly, but Darwin knew nothing about viruses.
“We fully admit that natural selection generally works very slowly,” he wrote in On the Origin of Species, published in 1859.
The very first virus discovered, the tobacco mosaic virus, was not noticed by scientists until decades later.
When evolutionary theory was developed from Darwin’s work and for much of the 20th century, it was based primarily on evidence from fields such as paleontology, biogeography, embryology and comparative anatomy:
visible patterns that can reveal slow changes over long periods of time.
These data, in general, are many less useful to measure evolution when it happens very quickly.
However, we have a new kind of scientific evidence to study evolution:
genome sequencing and comparison.
Extraordinary machines perform the sequencing, reading the genetic code, letter by letter, and powerful computers help to put it in order, and it’s all much faster and cheaper than ever.
Scientists can now track the changes, mutation after mutation, in the DNA or RNA that encodes the genetic instructions of each creature, observe and measure them as some of those mutations, those useful to the virus, spread among themselves in a population.
They can compose a live portrait of even the fastest evolving creatures such as bacteria and viruses.
When these bacteria or viruses are pathogens that can infect humans, this discipline is called genomic epidemiology.
One of the pioneers of genomic epidemiology is Sharon Peacock, Professor of Public Health and Microbiology at the University of Cambridge and Executive Director of the COVID-19 Genomics UK Consortium.
It is a group of public health agencies and research institutes founded in April 2020 to sequence and analyze the genomes of the novel coronavirus.
At this time, the UK lab contribution amounts to nearly 2.8 million SARS-CoV-2 sequences reported globally, nearly 23% of the total.
Peacock and those who helped create and finance this initiative knew from the start that genetic information could be critical to the pandemic response.
However, it is not enough to just collect the sequences and make them available to other scientists.
It would be genomics without epidemiology:
the application of population knowledge to public health.
“When it comes to speed, the key is to think of the whole chain, from one end to the other,” Peacock told me recently.
The “chain” he was referring to is a series of physical steps (such as taking samples from a patient), laboratory processes (such as extracting viral genetic material and sequencing that virus’s genome) and analysis (interpretation of the differences between one genome and another).
They get data that can help guide therapies and protect the population.
Hardware tools are important for that job.
Software is also essential.
During the first year of the COVID-19 pandemic, a young college student named Áine O’Toole, along with other members of Andrew Rambaut’s lab at the University of Edinburgh, developed a tool called PANGOLINO (Acronym of Phylogenetic Assignment of Named Global Outbreak Lineges).
It has become one of the reference systems for placing new genomes in the SARS-CoV-2 family tree, assigning them rational, though impossible to remember, labels (such as B.1.1.7), and contextualizing new variants of the virus to how they appeared. .
It was Rambaut, O’Toole and their laboratory partners who helped detect and locate the first important variant, now called alpha, when it appeared in south east England and spread to London in the fall of 2020.
A year later, other scientists in South Africa and Botswana who were sequencing traveler samples detected another variant on the rise, called omicron
Such rapid variant detection is invaluable, but only if the data is quickly turned into clear guidelines that can be applied in practice.
“We still lack some things to bring them into the clinical arena,” Peacock said.
These include making it easy for public health and medical staff without sequencing skills to use the data and for healthcare facilities, such as hospitals, to fund such work.
“Right now, most of the sequencing beyond COVID-19 is funded by public health agencies and research funds,” Peacock said.
That hasn’t changed since 2014, when Harvard University computational geneticist Pardis Sabeti led a team of scientists to respond to the horrific Ebola outbreak in West Africa.
They sequenced 99 viral genomes from samples taken from patients at a hospital in Sierra Leone.
A sequence match revealed that all cases were probably due to aa contagion from person to personand not an overflow from a myriad of the animal world.
The West African epidemic ended after 28,000 Ebola cases and 11,000 deaths, by which time epidemiology had proved its worth in revealing how the virus was spreading.
With COVID-19 there have been 589 million known cases and more than 6 million deaths to date.
The new discipline can barely keep up with the virus, let alone anticipate it.
Sarah Cobey, a University of Chicago evolutionary biologist working at the intersection of immunology, viral evolution, and epidemiology, sees “big holes” in the genetic surveillance of COVID-19.
“Even though we have a lot of sequences, they fit too few places,” Cobey told me.
During the first year of the pandemic, the UK, New Zealand, Australia and Iceland were among the first countries to sequence a high percentage of cases.
The Netherlands and the Democratic Republic of the Congo also stood out for their readiness in sequencing.
As the pandemic progresses, scientists in South Africa have initiated a major sequencing initiative, as evidenced by the detection of the beta variant and, subsequently, omicron, and coverage in Canada and Scandinavia has also improved.
Other parts of the world remain “blind spots,” Cobey said.
An unfortunate, though unsurprising, fact is that high-income countries have sequenced a portion of the coronavirus genomes in relation to cases 16 times higher compared to low- and middle-income countries.
Money is a limiting factor, but not the only one.
“I think the fundamental problem is a real lack of scientific leadership to coordinate this type of data collection,” Cobey said.
Few countries have their Sharon Peacock, or leaders who pay attention and support to scientific leaders.
The world needs it commandthat expands and pays for surveillance by sequencing this coronavirus and its changes, wherever the virus goes.
But we need much more, as Cobey, Peacock and other scientists warn.
Ambitious studies are needed on seroprevalence —Checking blood samples for signs of previous infections — which help scientists know how many undetected infections have occurred.
What is the true total of cases in a country and in the world?
We need forward-looking and well-funded research on vaccine platforms that can be rapidly adapted for use against new pathogens, not just the rushed development of booster doses for the newly emerged variant.
We need a universal coronavirus vaccine and a universal flu vaccine, although neither can be achieved given the enormous evolutionary capacity of these viruses.
Simpler: we need vaccines thermosetting and given without needles which can reduce rejection problems in high-income countries and shortages in hot, low-income countries.
We need better antiviral drugs, even for rare but dangerous viruses (such as the Nipah virus), which involves development efforts that may never pay off pharmaceutical companies.
Even simpler, as Cobey pointed out:
we need to invest in much better ventilation and air filtration systems in our public buildings and reduce the spread of coronavirus and other pathogens in the air.
It’s not very exciting from a scientific point of view, he admitted; it is important and effective only in relation to its cost.
The evolutionary journey of this coronavirus has been sinister and impressive.
Arguably, the SARS-CoV-2 transformations measured over the past 31 months, from the parent strain to the omicron subvariants, provide one of the most accurate images of extremely rapid global evolution in nature.
In nature: that is, not in glasses and flasks, not in laboratories, but in us.
Evolution deniers: take note.
We should all take note.
We have 12 million snapshots of this moving thing, which is enough, at the standard speed of 24 frames per second, to make a film about the evolution of SARS-CoV-2 from 138 hours in duration.
Since evolutionary biology is a descriptive, not a predictive science, we still don’t know how the story might end.
It probably won’t end.
And genomic epidemiologists, intelligent as they are, cannot save us from what keeps on coming.
We have to save ourselves.
c.2022 The New York Times Company
David Quammen
Source: Clarin
