For Baric, that research started in the late 1990s. Coronaviruses were then considered low risk, but Baric’s studies on the genetics that allowed viruses to enter human cells convinced him that some might be just a few mutations away from jumping the species barrier.
That hunch was confirmed in 2002–’03, when SARS broke out in southern China, infecting 8,000 people. As bad as that was, Baric says, we dodged a bullet with SARS. The disease didn’t spread from one person to another until about a day after severe symptoms began to appear, making it easier to corral through quarantines and contact tracing. Only 774 people died in that outbreak, but if it had been transmitted as easily as SARS-CoV-2, “we would have had a pandemic with a 10% mortality rate,” Baric says. “That’s how close humanity came.”
As tempting as it was to write off SARS as a one-time event, in 2012 MERS emerged and began infecting people in the Middle East. “For me personally, that was a wake-up call that the animal reservoirs must have many, many more strains that are poised for cross-species movement,” says Baric.
By then, examples of such dangers were already being discovered by Shi’s team, which had spent years sampling bats in southern China to locate the origin of SARS. The project was part of a global viral surveillance effort spearheaded by the US nonprofit EcoHealth Alliance. The nonprofit—which has an annual income of over $16 million, more than 90% from government grants—has its office in New York but partners with local research groups in other countries to do field and lab work. The WIV was its crown jewel, and Peter Daszak, president of EcoHealth Alliance, has been a coauthor with Shi on most of her key papers.
By taking thousands of samples from guano, fecal swabs, and bat tissue, and searching those samples for genetic sequences similar to SARS, Shi’s team began to discover many closely related viruses. In a cave in Yunnan Province in 2011 or 2012, they discovered the two closest, which they named WIV1 and SHC014.
Shi managed to culture WIV1 in her lab from a fecal sample and show that it could directly infect human cells, proving that SARS-like viruses ready to leap straight from bats to humans already lurked in the natural world. This showed, Daszak and Shi argued, that bat coronaviruses were a “substantial global threat.” Scientists, they said, needed to find them, and study them, before they found us.
Many of the other viruses couldn’t be grown, but Baric’s system provided a way to rapidly test their spikes by engineering them into similar viruses. When the chimera he made using SHC014 proved able to infect human cells in a dish, Daszak told the press that these revelations should “move this virus from a candidate emerging pathogen to a clear and present danger.”
To others, it was the perfect example of the unnecessary dangers of gain-of-function science. “The only impact of this work is the creation, in a lab, of a new, non-natural risk,” the Rutgers microbiologist Richard Ebright, a longtime critic of such research, told Nature.
To Baric, the situation was more nuanced. Although his creation might be more dangerous than the original mouse-adapted virus he’d used as a backbone, it was still wimpy compared with SARS—certainly not the supervirus Senator Paul would later suggest.
In the end, the NIH clampdown never had teeth. It included a clause granting exceptions “if head of funding agency determines research is urgently necessary to protect public health or national security.” Not only were Baric’s studies allowed to move forward, but so were all studies that applied for exemptions. The funding restrictions were lifted in 2017 and replaced with a more lenient system.
Tyvek suits and respirators
If the NIH was looking for a scientist to make regulators comfortable with gain-of-function research, Baric was the obvious choice. For years he’d insisted on extra safety steps, and he took pains to point these out in his 2015 paper, as if modeling the way forward.
The CDC recognizes four levels of biosafety and recommends which pathogens should be studied at which level. Biosafety level 1 is for nonhazardous organisms and requires virtually no precautions: wear a lab coat and gloves as needed. BSL-2 is for moderately hazardous pathogens that are already endemic in the area, and relatively mild interventions are indicated: close the door, wear eye protection, dispose of waste materials in an autoclave. BSL-3 is where things get serious. It’s for pathogens that can cause serious disease through respiratory transmission, such as influenza and SARS, and the associated protocols include multiple barriers to escape. Labs are walled off by two sets of self-closing, locking doors; air is filtered; personnel use full PPE and N95 masks and are under medical surveillance. BSL-4 is for the baddest of the baddies, such as Ebola and Marburg: full moon suits and dedicated air systems are added to the arsenal.
“There are no enforceable standards of what you should and shouldn’t do. It’s up to the individual countries, institutions, and scientists.”
Filippa Lentzos, King’s College London
In Baric’s lab, the chimeras were studied at BSL-3, enhanced with additional steps like Tyvek suits, double gloves, and powered-air respirators for all workers. Local first-responder teams participated in regular drills to increase their familiarity with the lab. All workers were monitored for infections, and local hospitals had procedures in place to handle incoming scientists. It was probably one of the safest BSL-3 facilities in the world. That still wasn’t enough to prevent a handful of errors over the years: some scientists were even bitten by virus-carrying mice. But no infections resulted.
In 2014, the NIH awarded a five-year, $3.75 million grant to EcoHealth Alliance to study the risk that more bat-borne coronaviruses would emerge in China, using the same kind of techniques Baric had pioneered. Some of that work was to be subcontracted to the Wuhan Institute of Virology.
The hunter-gatherer groups at the heart of a microbiome gold rush
The first step to finding out is to catalogue what microbes we might have lost. To get as close to ancient microbiomes as possible, microbiologists have begun studying multiple Indigenous groups. Two have received the most attention: the Yanomami of the Amazon rainforest and the Hadza, in northern Tanzania.
Researchers have made some startling discoveries already. A study by Sonnenburg and his colleagues, published in July, found that the gut microbiomes of the Hadza appear to include bugs that aren’t seen elsewhere—around 20% of the microbe genomes identified had not been recorded in a global catalogue of over 200,000 such genomes. The researchers found 8.4 million protein families in the guts of the 167 Hadza people they studied. Over half of them had not previously been identified in the human gut.
Plenty of other studies published in the last decade or so have helped build a picture of how the diets and lifestyles of hunter-gatherer societies influence the microbiome, and scientists have speculated on what this means for those living in more industrialized societies. But these revelations have come at a price.
A changing way of life
The Hadza people hunt wild animals and forage for fruit and honey. “We still live the ancient way of life, with arrows and old knives,” says Mangola, who works with the Olanakwe Community Fund to support education and economic projects for the Hadza. Hunters seek out food in the bush, which might include baboons, vervet monkeys, guinea fowl, kudu, porcupines, or dik-dik. Gatherers collect fruits, vegetables, and honey.
Mangola, who has met with multiple scientists over the years and participated in many research projects, has witnessed firsthand the impact of such research on his community. Much of it has been positive. But not all researchers act thoughtfully and ethically, he says, and some have exploited or harmed the community.
One enduring problem, says Mangola, is that scientists have tended to come and study the Hadza without properly explaining their research or their results. They arrive from Europe or the US, accompanied by guides, and collect feces, blood, hair, and other biological samples. Often, the people giving up these samples don’t know what they will be used for, says Mangola. Scientists get their results and publish them without returning to share them. “You tell the world [what you’ve discovered]—why can’t you come back to Tanzania to tell the Hadza?” asks Mangola. “It would bring meaning and excitement to the community,” he says.
Some scientists have talked about the Hadza as if they were living fossils, says Alyssa Crittenden, a nutritional anthropologist and biologist at the University of Nevada in Las Vegas, who has been studying and working with the Hadza for the last two decades.
The Hadza have been described as being “locked in time,” she adds, but characterizations like that don’t reflect reality. She has made many trips to Tanzania and seen for herself how life has changed. Tourists flock to the region. Roads have been built. Charities have helped the Hadza secure land rights. Mangola went abroad for his education: he has a law degree and a master’s from the Indigenous Peoples Law and Policy program at the University of Arizona.
The Download: a microbiome gold rush, and Eric Schmidt’s election misinformation plan
Over the last couple of decades, scientists have come to realize just how important the microbes that crawl all over us are to our health. But some believe our microbiomes are in crisis—casualties of an increasingly sanitized way of life. Disturbances in the collections of microbes we host have been associated with a whole host of diseases, ranging from arthritis to Alzheimer’s.
Some might not be completely gone, though. Scientists believe many might still be hiding inside the intestines of people who don’t live in the polluted, processed environment that most of the rest of us share. They’ve been studying the feces of people like the Yanomami, an Indigenous group in the Amazon, who appear to still have some of the microbes that other people have lost.
But there is a major catch: we don’t know whether those in hunter-gatherer societies really do have “healthier” microbiomes—and if they do, whether the benefits could be shared with others. At the same time, members of the communities being studied are concerned about the risk of what’s called biopiracy—taking natural resources from poorer countries for the benefit of wealthier ones. Read the full story.
Eric Schmidt has a 6-point plan for fighting election misinformation
—by Eric Schmidt, formerly the CEO of Google, and current cofounder of philanthropic initiative Schmidt Futures
The coming year will be one of seismic political shifts. Over 4 billion people will head to the polls in countries including the United States, Taiwan, India, and Indonesia, making 2024 the biggest election year in history.
Navigating a shifting customer-engagement landscape with generative AI
A strategic imperative
Generative AI’s ability to harness customer data in a highly sophisticated manner means enterprises are accelerating plans to invest in and leverage the technology’s capabilities. In a study titled “The Future of Enterprise Data & AI,” Corinium Intelligence and WNS Triange surveyed 100 global C-suite leaders and decision-makers specializing in AI, analytics, and data. Seventy-six percent of the respondents said that their organizations are already using or planning to use generative AI.
According to McKinsey, while generative AI will affect most business functions, “four of them will likely account for 75% of the total annual value it can deliver.” Among these are marketing and sales and customer operations. Yet, despite the technology’s benefits, many leaders are unsure about the right approach to take and mindful of the risks associated with large investments.
Mapping out a generative AI pathway
One of the first challenges organizations need to overcome is senior leadership alignment. “You need the necessary strategy; you need the ability to have the necessary buy-in of people,” says Ayer. “You need to make sure that you’ve got the right use case and business case for each one of them.” In other words, a clearly defined roadmap and precise business objectives are as crucial as understanding whether a process is amenable to the use of generative AI.
The implementation of a generative AI strategy can take time. According to Ayer, business leaders should maintain a realistic perspective on the duration required for formulating a strategy, conduct necessary training across various teams and functions, and identify the areas of value addition. And for any generative AI deployment to work seamlessly, the right data ecosystems must be in place.
Ayer cites WNS Triange’s collaboration with an insurer to create a claims process by leveraging generative AI. Thanks to the new technology, the insurer can immediately assess the severity of a vehicle’s damage from an accident and make a claims recommendation based on the unstructured data provided by the client. “Because this can be immediately assessed by a surveyor and they can reach a recommendation quickly, this instantly improves the insurer’s ability to satisfy their policyholders and reduce the claims processing time,” Ayer explains.
All that, however, would not be possible without data on past claims history, repair costs, transaction data, and other necessary data sets to extract clear value from generative AI analysis. “Be very clear about data sufficiency. Don’t jump into a program where eventually you realize you don’t have the necessary data,” Ayer says.
The benefits of third-party experience
Enterprises are increasingly aware that they must embrace generative AI, but knowing where to begin is another thing. “You start off wanting to make sure you don’t repeat mistakes other people have made,” says Ayer. An external provider can help organizations avoid those mistakes and leverage best practices and frameworks for testing and defining explainability and benchmarks for return on investment (ROI).
Using pre-built solutions by external partners can expedite time to market and increase a generative AI program’s value. These solutions can harness pre-built industry-specific generative AI platforms to accelerate deployment. “Generative AI programs can be extremely complicated,” Ayer points out. “There are a lot of infrastructure requirements, touch points with customers, and internal regulations. Organizations will also have to consider using pre-built solutions to accelerate speed to value. Third-party service providers bring the expertise of having an integrated approach to all these elements.”