A rendering of in vitro fertilization.
Imagine two men making a baby. Or two women. Or an infertile couple. Or an older woman whose eggs are no longer viable. None of these people could have a baby today without the help of an egg or sperm donor.
Cells scraped from the inside of your cheek could one day be manipulated to become either eggs or sperm.
But in the future, it may be possible for them to reproduce using only their own genetic material, thanks to an emerging technology called IVG, or in vitro gametogenesis.
Researchers are learning how to reprogram adult human cells like skin cells to become lab-created egg and sperm cells, which could then be joined to form an embryo. In other words, cells scraped from the inside of your cheek could one day be manipulated to become either eggs or sperm, no matter your gender or your reproductive fitness.
In 2016, Japanese scientists proved that the concept could be successfully carried out in mice. Now some experts, like Dr. John Zhang, the founder and CEO of New Hope Fertility Center in Manhattan, say it's just "a matter of time" before the method is also made to work in humans.
Such a technological tour de force would upend our most basic assumptions about human reproduction and biology. Combined with techniques like gene editing, these tools could eventually enable prospective parents to have an unprecedented level of choice and control over their children's origins. It's a wildly controversial notion, and an especially timely one now that a Chinese scientist has announced the birth of the first allegedly CRISPR-edited babies. (The claims remain unverified.)
Zhang himself is no stranger to controversy. In 2016, he stunned the world when he announced the birth of a baby conceived using the DNA of three people, a landmark procedure intended to prevent the baby from inheriting a devastating neurological disease. (Zhang went to a clinic in Mexico to carry out the procedure because it is prohibited in the U.S.) Zhang's other achievements to date include helping a 49-year-old woman have a baby using her own eggs and restoring a young woman's fertility through an ovarian tissue transplant surgery.
Zhang recently sat down with our Editor-in-Chief in his New York office overlooking Columbus Circle to discuss the fertility world's latest provocative developments. Here are his top ten insights:
Clearly [gene-editing embryos] will be beneficial to mankind, but it's a matter of how and when the work is done.
1) On a Chinese scientist's claim of creating the first CRISPR-edited babies:
I'm glad that we made a first move toward a clinical application of this technology for mankind. Somebody has to do this. Whether this was a good case or not, there is still time to find out.
Clearly it will be beneficial to mankind, but it's a matter of how and when the work is done. Like any scientific advance, it has to be done in a very responsible way.
Today's response is identical to when the world's first IVF baby was announced in 1978. The major news media didn't take it seriously and thought it was evil, wanted to keep a distance from IVF. Many countries even abandoned IVF, but today you see it is a normal practice. And it took almost 40 years [for the researchers] to win a Nobel Prize.
I think we need more time to understand how this work was done medically, ethically, and let the scientist have the opportunity to present how it was done and let a scientific journal publish the paper. Before these become available, I don't think we should start being upset, scared, or giving harsh criticism.
2) On the international outcry in response to the news:
I feel we are in scientific shock, with many thinking it came too fast, too soon. We all embrace modern technology, but when something really comes along, we fear it. In an old Chinese saying, one of the masters always dreamed of seeing the dragon, and when the dragon really came, he got scared.
Dr. John Zhang, the founder and CEO of New Hope Fertility Center in Manhattan, pictured in his office.
3) On the Western world's perception that Chinese scientists sometimes appear to discount ethics in favor of speedy breakthroughs:
I think this perception is not fair. I don't think China is very casual. It's absolutely not what people think. I don't want people to feel that this case [of CRISPR-edited babies] will mean China has less standards over how human reproduction should be performed. Just because this happened, it doesn't mean in China you can do anything you want.
As far as the regulation of IVF clinics, China is probably the most strictly regulated of any country I know in this world.
4) On China's first public opinion poll gauging attitudes toward gene-edited babies, indicating that more than 60 percent of survey respondents supported using the technology to prevent inherited diseases, but not to enhance traits:
There is a sharp contrast between the general public and the professional world. Being a working health professional and an advocate of scientists working in this field, it is very important to be ethically responsible for what we are doing, but my own feeling is that from time to time we may not take into consideration what the patient needs.
5) On how the three-parent baby is doing today, several years after his birth:
No news is good news.
6) On the potentially game-changing research to develop artificial sperm and eggs:
First of all I think that anything that's technically possible, as long as you are not harmful to other people, to other societies, as long as you do it responsibly, and this is a legitimate desire, I think eventually it will become reality.
My research for now is really to try to overcome the very next obstacle in our field, which is how to let a lady age 44 or older have a baby with her own genetic material.
Practically 99 percent of women over age 43 will never make a baby on their own. And after age 47, we usually don't offer donor egg IVF anymore.
But with improved longevity, and quality of life, the lifespan of females continues to increase. In Japan, the average for females is about 89 years old. So for more than half of your life, you will not be able to produce a baby, which is quite significant in the animal kingdom. In most of the animal kingdom, their reproductive life is very much the same as their life, but then you can argue in the animal kingdom unlike a human being, it doesn't take such a long time for them to contribute to the society because once you know how to hunt and look for food, you're done.
"I think this will become a major ethical debate: whether we should let an older lady have a baby at a very late state of her life."
But humans are different. You need to go to college, get certain skills. It takes 20 years to really bring a human being up to become useful to society. That's why the mom and dad are not supposed to have the same reproductive life equal to their real life.
I think this will become a major ethical debate: whether we should let an older lady have a baby at a very late state of her life and leave the future generation in a very vulnerable situation in which they may lack warm caring, proper guidance, and proper education.
7) On using artificial gametes to grant more reproductive choices to gays and lesbians:
I think it is totally possible to have two sperm make a baby, and two eggs make babies.
If we have two guys, one guy to produce eggs, or two girls, one would have to become sperm. Basically you are creating artificial gametes or converting with gametes from sperm to become egg or egg to become a sperm. Which may not necessarily be very difficult. The key is to be able to do nuclear reprogramming.
So why can two sperm not make offspring now? You get exactly half of your genes from each parent. The genes have their own imprinting that say "made in mom," "made in dad." The two sperm would say "made in dad," "made in dad." If I can erase the "made in dad," and say "made in mom," then these sperm can make offspring.
8) On how close science is to creating artificial gametes for clinical use in pregnancies:
It's very hard to say until we accomplish it. It could be very quick. It could be it takes a long time. I don't want to speculate.
"I think these technologies are the solid foundation just like when we designed the computer -- we never thought a computer would become the iPhone."
9) On whether there should be ethical red lines drawn by authorities or whether the decisions should be left to patients and scientists:
I think we cannot believe a hundred percent in the scientist and the patient but it should not be 100 percent authority. It should be coming from the whole of society.
10) On his expectations for the future:
We are living in a very exciting world. I think that all these technologies can really change the way of mankind and also are not just for baby-making. The research, the experience, the mechanism we learn from these technologies, they will shine some great lights into our long-held dream of being a healthy population that is cancer-free and lives a long life, let's say 120 years.
I think these technologies are the solid foundation just like when we designed the computer -- we never thought a computer would become the iPhone. Imagine making a computer 30 years ago, that this little chip will change your life.
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.
