A Team of Israeli Students Just Created Honey Without Bees
The bee-free honey on the left, and the Israeli team that won the iGEM competition.
Can you make honey without honeybees? According to 12 Israeli students who took home a gold medal in the iGEM (International Genetically Engineered Machine) competition with their synthetic honey project, the answer is yes, you can.
The honey industry faces serious environmental challenges, like the mysterious Colony Collapse Disorder.
For the past year, the team from Technion-Israel Institute of Technology has been working on creating sustainable, artificial honey—no bees required. Why? As the team explains in a video on the project's website, "Studies have shown the amazing nutritional values of honey. However, the honey industry harms the environment, and particularly the bees. That's why vegans don't use honey and why our honey will be a great replacement."
Indeed, honey has long been a controversial product in the vegan community. Some say it's stealing an animal's food source (though bees make more honey than they can possibly use). Some avoid eating honey because it is an animal product and bees' natural habitats are disturbed by humans harvesting it. Others feel that because bees aren't directly killed or harmed in the production of honey, it's not actually unethical to eat.
However, there's no doubt that the honey industry faces some serious environmental challenges. Colony Collapse Disorder, a mysterious phenomenon in which worker bees in colonies disappear in large numbers without any real explanation, came to international attention in 2006. Several explanations from poisonous pesticides to immune-suppressing stress to new or emerging diseases have been posited, but no definitive cause has been found.
There's also the problem of human-managed honey farms having a negative impact on the natural honeybee population.
So how can honey be made without honeybees? It's all about bacteria and enzymes.
The way bees make honey is by collecting nectar from flowers, transporting it in their "honey stomach" (which is separate from their food stomach), and bringing it back to the hive, where it gets transferred from bee mouth to bee mouth. That transferal process reduces the moisture content from about 70 percent to 20 percent, and honey is formed.
The product is still currently under development.
The Technion students created a model of a synthetic honey stomach metabolic pathway, in which the bacterium Bacillus subtilis "learns" to produce honey. "The bacteria can independently control the production of enzymes, eventually achieving a product with the same sugar profile as real honey, and the same health benefits," the team explains. Bacillus subtilis, which is found in soil, vegetation, and our own gastrointestinal tracts, has a natural ability to produce catalase, one of the enzymes needed for honey production. The product is still currently under development.
Whether this project results in a real-world jar of honey we'll be able to buy at the grocery store remains to be seen, but imagine how happy the bees—and vegans—would be if it did.
The large genetic studies underlying certain disease risk tests have primarily been done in populations of European ancestry, limiting their accuracy.
Earlier this year, California-based Ambry Genetics announced that it was discontinuing a test meant to estimate a person's risk of developing prostate or breast cancer. The test looks for variations in a person's DNA that are known to be associated with these cancers.
Known as a polygenic risk score, this type of test adds up the effects of variants in many genes — often in the dozens or hundreds — and calculates a person's risk of developing a particular health condition compared to other people. In this way, polygenic risk scores are different from traditional genetic tests that look for mutations in single genes, such as BRCA1 and BRCA2, which raise the risk of breast cancer.
Traditional genetic tests look for mutations that are relatively rare in the general population but have a large impact on a person's disease risk, like BRCA1 and BRCA2. By contrast, polygenic risk scores scan for more common genetic variants that, on their own, have a small effect on risk. Added together, however, they can raise a person's risk for developing disease.
These scores could become a part of routine healthcare in the next few years. Researchers are developing polygenic risk scores for cancer, heart, disease, diabetes and even depression. Before they can be rolled out widely, they'll have to overcome a key limitation: racial bias.
"The issue with these polygenic risk scores is that the scientific studies which they're based on have primarily been done in individuals of European ancestry," says Sara Riordan, president of the National Society of Genetics Counselors. These scores are calculated by comparing the genetic data of people with and without a particular disease. To make these scores accurate, researchers need genetic data from tens or hundreds of thousands of people.
Myriad's old test would have shown that a Black woman had twice as high of a risk for breast cancer compared to the average woman even if she was at low or average risk.
A 2018 analysis found that 78% of participants included in such large genetic studies, known as genome-wide association studies, were of European descent. That's a problem, because certain disease-associated genetic variants don't appear equally across different racial and ethnic groups. For example, a particular variant in the TTR gene, known as V1221, occurs more frequently in people of African descent. In recent years, the variant has been found in 3 to 4 percent of individuals of African ancestry in the United States. Mutations in this gene can cause protein to build up in the heart, leading to a higher risk of heart failure. A polygenic risk score for heart disease based on genetic data from mostly white people likely wouldn't give accurate risk information to African Americans.
Accuracy in genetic testing matters because such polygenic risk scores could help patients and their doctors make better decisions about their healthcare.
For instance, if a polygenic risk score determines that a woman is at higher-than-average risk of breast cancer, her doctor might recommend more frequent mammograms — X-rays that take a picture of the breast. Or, if a risk score reveals that a patient is more predisposed to heart attack, a doctor might prescribe preventive statins, a type of cholesterol-lowering drug.
"Let's be clear, these are not diagnostic tools," says Alicia Martin, a population and statistical geneticist at the Broad Institute of MIT and Harvard. "We can't use a polygenic score to say you will or will not get breast cancer or have a heart attack."
But combining a patient's polygenic risk score with other factors that affect disease risk — like age, weight, medication use or smoking status — may provide a better sense of how likely they are to develop a specific health condition than considering any one risk factor one its own. The accuracy of polygenic risk scores becomes even more important when considering that these scores may be used to guide medication prescription or help patients make decisions about preventive surgery, such as a mastectomy.
In a study published in September, researchers used results from large genetics studies of people with European ancestry and data from the UK Biobank to calculate polygenic risk scores for breast and prostate cancer for people with African, East Asian, European and South Asian ancestry. They found that they could identify individuals at higher risk of breast and prostate cancer when they scaled the risk scores within each group, but the authors say this is only a temporary solution. Recruiting more diverse participants for genetics studies will lead to better cancer detection and prevent, they conclude.
Recent efforts to do just that are expected to make these scores more accurate in the future. Until then, some genetics companies are struggling to overcome the European bias in their tests.
Acknowledging the limitations of its polygenic risk score, Ambry Genetics said in April that it would stop offering the test until it could be recalibrated. The company launched the test, known as AmbryScore, in 2018.
"After careful consideration, we have decided to discontinue AmbryScore to help reduce disparities in access to genetic testing and to stay aligned with current guidelines," the company said in an email to customers. "Due to limited data across ethnic populations, most polygenic risk scores, including AmbryScore, have not been validated for use in patients of diverse backgrounds." (The company did not make a spokesperson available for an interview for this story.)
In September 2020, the National Comprehensive Cancer Network updated its guidelines to advise against the use of polygenic risk scores in routine patient care because of "significant limitations in interpretation." The nonprofit, which represents 31 major cancer cancers across the United States, said such scores could continue to be used experimentally in clinical trials, however.
Holly Pederson, director of Medical Breast Services at the Cleveland Clinic, says the realization that polygenic risk scores may not be accurate for all races and ethnicities is relatively recent. Pederson worked with Salt Lake City-based Myriad Genetics, a leading provider of genetic tests, to improve the accuracy of its polygenic risk score for breast cancer.
The company announced in August that it had recalibrated the test, called RiskScore, for women of all ancestries. Previously, Myriad did not offer its polygenic risk score to women who self-reported any ancestry other than sole European or Ashkenazi ancestry.
"Black women, while they have a similar rate of breast cancer to white women, if not lower, had twice as high of a polygenic risk score because the development and validation of the model was done in white populations," Pederson said of the old test. In other words, Myriad's old test would have shown that a Black woman had twice as high of a risk for breast cancer compared to the average woman even if she was at low or average risk.
To develop and validate the new score, Pederson and other researchers assessed data from more than 275,000 women, including more than 31,000 African American women and nearly 50,000 women of East Asian descent. They looked at 56 different genetic variants associated with ancestry and 93 associated with breast cancer. Interestingly, they found that at least 95% of the breast cancer variants were similar amongst the different ancestries.
The company says the resulting test is now more accurate for all women across the board, but Pederson cautions that it's still slightly less accurate for Black women.
"It's not only the lack of data from Black women that leads to inaccuracies and a lack of validation in these types of risk models, it's also the pure genomic diversity of Africa," she says, noting that Africa is the most genetically diverse continent on the planet. "We just need more data, not only in American Black women but in African women to really further characterize that continent."
Martin says it's problematic that such scores are most accurate for white people because they could further exacerbate health disparities in traditionally underserved groups, such as Black Americans. "If we were to set up really representative massive genetic studies, we would do a much better job at predicting genetic risk for everybody," she says.
Earlier this year, the National Institutes of Health awarded $38 million to researchers to improve the accuracy of polygenic risk scores in diverse populations. Researchers will create new genome datasets and pool information from existing ones in an effort to diversify the data that polygenic scores rely on. They plan to make these datasets available to other scientists to use.
"By having adequate representation, we can ensure that the results of a genetic test are widely applicable," Riordan says.
New Podcast: George Church on Woolly Mammoths, Organ Transplants, and Covid Vaccines
Dr. George Church, a leading pioneer of gene editing, updates our listeners on several of his noteworthy projects.
The "Making Sense of Science" podcast features interviews with leading medical and scientific experts about the latest developments and the big ethical and societal questions they raise. This monthly podcast is hosted by journalist Kira Peikoff, founding editor of the award-winning science outlet Leaps.org.
This month, our guest is notable genetics pioneer Dr. George Church of Harvard Medical School. Dr. Church has remarkably bold visions for how innovation in science can fundamentally transform the future of humanity and our planet. His current moonshot projects include: de-extincting some of the woolly mammoth's genes to create a hybrid Asian elephant with the cold-tolerance traits of the woolly mammoth, so that this animal can re-populate the Arctic and help stave off climate change; reversing chronic diseases of aging through gene therapy, which he and colleagues are now testing in dogs; and transplanting genetically engineered pig organs to humans to eliminate the tragically long waiting lists for organs. Hear Dr. Church discuss all this and more on our latest episode.
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Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.