The award-winning New York Times science writer Carl Zimmer.
Carl Zimmer, the award-winning New York Times science writer, recently published a stellar book about human heredity called "She Has Her Mother's Laugh." Truly a magnum opus, the book delves into the cultural and scientific evolution of genetics, the field's outsize impact on society, and the new ways we might fundamentally alter our species and our planet.
"I was only prepared to write about how someday we would cross this line, and actually, we've already crossed it."
Zimmer spoke last week with editor-in-chief Kira Peikoff about the international race to edit the genes of human embryos, the biggest danger he sees for society (hint: it's not super geniuses created by CRISPR), and some outlandish possibilities for how we might reproduce in the future. This interview has been edited and condensed for clarity.
I was struck by the number of surprises you uncovered while researching human heredity, like how fetal cells can endure for a lifetime in a mother's body and brain. What was one of the biggest surprises for you?
Something that really jumped out for me was for the section on genetically modifying people. It does seem incredibly hypothetical. But then I started looking into mitochondrial replacement therapy, so-called "three parent babies." I was really surprised to discover that almost by accident, a number of genetically modified people were created this way [in the late 90s and early 2000s]. They walk among us, and they're actually fine as far as anyone can tell. I was only prepared to write about how someday we would cross this line, and actually, we've already crossed it.
And now we have the current arms race between the U.S. and China to edit diseases out of human embryos, with China being much more willing and the U.S. more reluctant. Do you think it's more important to get ahead or to proceed as ethically as possible?
I would prefer a middle road. I think that rushing into tinkering with the features of human heredity could be a disastrous mistake for a lot of reasons. On the other hand, if we completely retreat from it out of some vague fear, I think that we won't take advantage of the actual benefits that this technology might have that are totally ethically sound.
I think the United Kingdom is actually showing how you can go the middle route with mitochondrial replacement therapy. The United States has just said nope, you can't do it at all, and you have Congressmen talking about how it's just playing God or Frankenstein. And then there are countries like Mexico or the Ukraine where people are doing mitochondrial replacement therapy because there are no regulations at all. It's a wild west situation, and that's not a good idea either.
But in the UK, they said alright, well let's talk about this, let's have a debate in Parliament, and they did, and then the government came up with a well thought-through policy. They decided that they were going to allow for this, but only in places that applied for a license, and would be monitored, and would keep track of the procedure and the health of these children and actually have real data going forward. I would imagine that they're going to very soon have their first patients.
As you mentioned, one researcher recently traveled to Mexico from New York to carry out the so-called "three-parent baby" procedure in order to escape the FDA's rules. What's your take on scientists having to leave their own jurisdictions to advance their research programs under less scrutiny?
I think it's a problem when people who have a real medical need have to leave their own country to get truly effective treatment for it. On the other hand, we're seeing lots of people going abroad to countries that don't monitor all the claims that clinics are making about their treatments. So you have stem cell clinics in all sorts of places that are making all sorts of ridiculous promises. They're not delivering those results, and in some cases, they're doing harm.
"Advances in stem cell biology and reproductive biology are a much bigger challenge to our conventional ideas about heredity than CRISPR is."
It's a tricky tension for sure. Speaking of gene editing humans, you mention in the book that one of the CRISPR pioneers, Jennifer Doudna, now has recurring nightmares about Hitler. Do you think that her fears about eugenics being revived with gene editing are justified?
The word "eugenics" has a long history and it's meant different things to different people. So we have to do a better job of talking about it in the future if we really want to talk about the risks and the promises of technology like CRISPR. Eugenics in its most toxic form was an ideology that let governments, including the United States, sterilize their own citizens by the tens of thousands. Then Nazi Germany also used eugenics as a justification to exterminate many more people.
Nobody's talking about that with CRISPR. Now, are people concerned that we are going to wipe out lots of human genetic diversity with it? That would be a bad thing, but I'm skeptical that would actually ever happen. You would have to have some sort of science fiction one-world government that required every new child to be born with IVF. It's not something that keeps me up at night. Honestly, I think we have much bigger problems to worry about.
What is the biggest danger relating to genetics that we should be aware of?
Part of what made eugenics such a toxic ideology was that it was used as a justification for indifference. In other words, if there are problems in society, like a large swath of people who are living in poverty, well, there's nothing you can do about it because it must be due to genetics.
If you look at genetics as being the sole place where you can solve humanity's problems, then you're going to say well, there's no point in trying to clean up the environment or trying to improve human welfare.
A major theme in your book is that we should not narrow our focus on genes as the only type of heredity. We also may inherit some epigenetic marks, some of our mother's microbiome and mitochondria, and importantly, our culture and our environment. Why does an expanded view of heredity matter?
We should think about the world that our children are going to inherit, and their children, and their children. They're going to inherit our genes, but they're also going to inherit this planet and we're doing things that are going to have an incredibly long-lasting impact on it. I think global warming is one of the biggest. When you put carbon dioxide into the air, it stays there for a very, very long time. If we stopped emitting carbon dioxide now, the Earth would stay warm for many centuries. We should think about tinkering with the future of genetic heredity, but I think we should also be doing that with our environmental heredity and our cultural heredity.
At the end of the book, you discuss some very bizarre possibilities for inheritance that could be made possible through induced pluripotent stem cell technology and IVF -- like four-parent babies, men producing eggs, and children with 8-celled embryos as their parents. If this is where reproductive medicine is headed, how can ethics keep up?
I'm not sure actually. I think that these advances in stem cell biology and reproductive biology are a much bigger challenge to our conventional ideas about heredity than CRISPR is. With CRISPR, you might be tweaking a gene here and there, but they're still genes in an embryo which then becomes a person, who would then have children -- the process our species has been familiar with for a long time.
"We have to recognize that we need a new language that fits with the science of heredity in the 21st century."
We all assume that there's no way to find a fundamentally different way of passing down genes, but it turns out that it's not really that hard to turn a skin cell from a cheek scraping into an egg or sperm. There are some challenges that still have to be worked out to make this something that could be carried out a lot in labs, but I don't see any huge barriers to it. Ethics doesn't even have the language to discuss the possibilities. Like for example, one person producing both male and female sex cells, which are then fertilized to produce embryos so that you have a child who only has one parent. How do we even talk about that? I don't know. But that's coming up fast.
We haven't developed our language as quickly as the technology itself. So how do we move forward?
We have to recognize that we need a new language that fits with the science of heredity in the 21st century. I think one of the biggest problems we have as a society is that most of our understanding about these issues largely comes from what we learned in grade school and high school in biology class. A high school biology class, even now, gets up to Mendel and then stops. Gregor Mendel is a great place to start, but it's a really bad place to stop talking about heredity.
[Ed. Note: Zimmer's book can be purchased through your retailer of choice here.]
Artificial Intelligence is already helping to grow some of the food we eat.
The chef-farmers choose from among 45 types of herb and leafy-greens seeds, plop them into grow trays, and a few weeks later they pick and serve. While success is predicated on at least a small amount of these humans’ care, the systems are autonomously surveilled round-the-clock from Babylon’s base of operations. And artificial intelligence is helping to run the show.
Babylon piloted the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off.
Imagine consistently perfect greens and tomatoes and strawberries, grown hyper-locally, using less water, without chemicals or environmental contaminants. This is the hefty promise of controlled environment agriculture (CEA) — basically, indoor farms that can be hydroponic, aeroponic (plant roots are suspended and fed through misting), or aquaponic (where fish play a role in fertilizing vegetables). But whether they grow 4,160 leafy-green servings per year, like one Babylon farm, or millions of servings, like some of the large, centralized facilities starting to supply supermarkets across the U.S., they seek to minimize failure as much as possible.
Babylon’s soilless hydroponic growing system
Courtesy Babylon Micro-Farms
Here, AI is starting to play a pivotal role. CEA growers use it to help “make sense of what’s happening” to the plants in their care, says Scott Lowman, vice president of applied research at the Institute for Advanced Learning and Research (IALR) in Virginia, a state that’s investing heavily in CEA companies. And although these companies say they’re not aiming for a future with zero human employees, AI is certainly poised to take a lot of human farming intervention out of the equation — for better and worse.
Most of these companies are compiling their own data sets to identify anything that might block the success of their systems. Babylon had already integrated sensor data into its farms to measure heat and humidity, the nutrient content of water, and the amount of light plants receive. Last year, they got a National Science Foundation grant that allowed them to pilot the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off. “Will this plant be healthy tomorrow? Are there things…that the human eye can't see that the plant starts expressing?” says Amandeep Ratte, the company’s head of data science. “If our system can say, Hey, this plant is unhealthy, we can reach out to [users] preemptively about what they’re doing wrong, or is there a disease at the farm?” Ratte says. The earlier the better, to avoid crop failures.
Natural light accounts for 70 percent of Greenswell Growers’ energy use on a sunny day.
Courtesy Greenswell Growers
IALR’s Lowman says that other CEA companies are developing their AI systems to account for the different crops they grow — lettuces come in all shapes and sizes, after all, and each has different growing needs than, for example, tomatoes. The ways they run their operations differs also. Babylon is unusual in its decentralized structure. But centralized growing systems with one main location have variabilities, too. AeroFarms, which recently declared bankruptcy but will continue to run its 140,000-square foot vertical operation in Danville, Virginia, is entirely enclosed and reliant on the intense violet glow of grow lights to produce microgreens.
Different companies have different data needs. What data is essential to AeroFarms isn’t quite the same as for Greenswell Growers located in Goochland County, Virginia. Raising four kinds of lettuce in a 77,000-square-foot automated hydroponic greenhouse, the vagaries of naturally available light, which accounts for 70 percent of Greenswell’s energy use on a sunny day, affect operations. Their tech needs to account for “outside weather impacts,” says president Carl Gupton. “What adjustments do we have to make inside of the greenhouse to offset what's going on outside environmentally, to give that plant optimal conditions? When it's 85 percent humidity outside, the system needs to do X, Y and Z to get the conditions that we want inside.”
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen.
Nevertheless, every CEA system has the same core needs — consistent yield of high quality crops to keep up year-round supply to customers. Additionally, “Everybody’s got the same set of problems,” Gupton says. Pests may come into a facility with seeds. A disease called pythium, one of the most common in CEA, can damage plant roots. “Then you have root disease pressures that can also come internally — a change in [growing] substrate can change the way the plant performs,” Gupton says.
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen. So, while companies amass their own hyper-specific data sets, Lowman foresees a time within the next decade “when there will be some type of [open-source] database that has the most common types of plant stress identified” that growers will be able to tap into. Such databases will “create a community and move the science forward,” says Lowman.
In fact, IALR is working on assembling images for just such a database now. On so-called “smart tables” inside an Institute lab, a team is growing greens and subjects them to various stressors. Then, they’re administering treatments while taking images of every plant every 15 minutes, says Lowman. Some experiments generate 80,000 images; the challenge lies in analyzing and annotating the vast trove of them, marking each one to reflect outcome—for example increasing the phosphate delivery and the plant’s response to it. Eventually, they’ll be fed into AI systems to help them learn.
For all the enthusiasm surrounding this technology, it’s not without downsides. Training just one AI system can emit over 250,000 pounds of carbon dioxide, according to MIT Technology Review. AI could also be used “to enhance environmental benefit for CEA and optimize [its] energy consumption,” says Rozita Dara, a computer science professor at the University of Guelph in Canada, specializing in AI and data governance, “but we first need to collect data to measure [it].”
The chef-farmers can choose from 45 types of herb and leafy-greens seeds.
Courtesy Babylon Micro-Farms
Any system connected to the Internet of Things is also vulnerable to hacking; if CEA grows to the point where “there are many of these similar farms, and you're depending on feeding a population based on those, it would be quite scary,” Dara says. And there are privacy concerns, too, in systems where imaging is happening constantly. It’s partly for this reason, says Babylon’s Ratte, that the company’s in-farm cameras all “face down into the trays, so the only thing [visible] is pictures of plants.”
Tweaks to improve AI for CEA are happening all the time. Greenswell made its first harvest in 2022 and now has annual data points they can use to start making more intelligent choices about how to feed, water, and supply light to plants, says Gupton. Ratte says he’s confident Babylon’s system can already “get our customers reliable harvests. But in terms of how far we have to go, it's a different problem,” he says. For example, if AI could detect whether the farm is mostly empty—meaning the farm’s user hasn’t planted a new crop of greens—it can alert Babylon to check “what's going on with engagement with this user?” Ratte says. “Do they need more training? Did the main person responsible for the farm quit?”
Lowman says more automation is coming, offering greater ability for systems to identify problems and mitigate them on the spot. “We still have to develop datasets that are specific, so you can have a very clear control plan, [because] artificial intelligence is only as smart as what we tell it, and in plant science, there's so much variation,” he says. He believes AI’s next level will be “looking at those first early days of plant growth: when the seed germinates, how fast it germinates, what it looks like when it germinates.” Imaging all that and pairing it with AI, “can be a really powerful tool, for sure.”
Researchers from the University of Cambridge have laid the foundations for growing synthetic embryos that could develop a beating heart, gut and brain.
The organoid revolution
In 1981, scientists discovered how to keep stem cells alive. This was a significant breakthrough, as stem cells have notoriously rigorous demands. Nevertheless, stem cells remained a relatively niche research area, mainly because scientists didn’t know how to convince the cells to turn into other cells.
Then, in 1987, scientists embedded isolated stem cells in a gelatinous protein mixture called Matrigel, which simulated the three-dimensional environment of animal tissue. The cells thrived, but they also did something remarkable: they created breast tissue capable of producing milk proteins. This was the first organoid — a clump of cells that behave and function like a real organ. The organoid revolution had begun, and it all started with a boob in Jello.
For the next 20 years, it was rare to find a scientist who identified as an “organoid researcher,” but there were many “stem cell researchers” who wanted to figure out how to turn stem cells into other cells. Eventually, they discovered the signals (called growth factors) that stem cells require to differentiate into other types of cells.
For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells.
By the end of the 2000s, researchers began combining stem cells, Matrigel, and the newly characterized growth factors to create dozens of organoids, from liver organoids capable of producing the bile salts necessary for digesting fat to brain organoids with components that resemble eyes, the spinal cord, and arguably, the beginnings of sentience.
Synthetic embryos
Organoids possess an intrinsic flaw: they are organ-like. They share some characteristics with real organs, making them powerful tools for research. However, no one has found a way to create an organoid with all the characteristics and functions of a real organ. But Magdalena Żernicka-Goetz, a developmental biologist, might have set the foundation for that discovery.
Żernicka-Goetz hypothesized that organoids fail to develop into fully functional organs because organs develop as a collective. Organoid research often uses embryonic stem cells, which are the cells from which the developing organism is created. However, there are two other types of stem cells in an early embryo: stem cells that become the placenta and those that become the yolk sac (where the embryo grows and gets its nutrients in early development). For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells. In other words, Żernicka-Goetz suspected the best way to grow a functional organoid was to produce a synthetic embryoid.
As described in the aforementioned Nature paper, Żernicka-Goetz and her team mimicked the embryonic environment by mixing these three types of stem cells from mice. Amazingly, the stem cells self-organized into structures and progressed through the successive developmental stages until they had beating hearts and the foundations of the brain.
“Our mouse embryo model not only develops a brain, but also a beating heart [and] all the components that go on to make up the body,” said Żernicka-Goetz. “It’s just unbelievable that we’ve got this far. This has been the dream of our community for years and major focus of our work for a decade and finally we’ve done it.”
If the methods developed by Żernicka-Goetz’s team are successful with human stem cells, scientists someday could use them to guide the development of synthetic organs for patients awaiting transplants. It also opens the door to studying how embryos develop during pregnancy.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
