Skip to Content

Chemists Churn Out Synthetic Sugars

Automated production of highly complex molecules could aid understanding of many major diseases.
February 1, 2001

When scientists were finally able to create synthetic proteins and nucleic acids in the lab, gene sequencing and DNA chips quickly followed.

But synthesizing these was child’s play compared with the third category of biopolymers known as carbohydrates, or sugars.

MIT researchers report in the Feb. 2 online edition of Science that they have automated the production of these extremely complex molecules for the first time. In so doing, they have opened the door to a flood of potential new research-and disease treatments.

“We have developed a tool that cuts the time required to make an oligosaccharide (a molecule made up of several simple sugar groups joined in a chain) by a factor of 100,” said Peter H. Seeberger, assistant professor of chemistry at MIT and the paper’s main author.

For the first time, biologically significant structures-ones that are involved in cancers and a whole host of diseases-will be readily available for any researcher to probe, analyze and manipulate. Researchers for the first time will be able to design and synthesize large numbers of different sugars, and test their effect on cells.

Complex Building Blocks

Carbohydrates come in so many three-dimensional shapes, and connect to each other in so many ways, that building even a simple oligosaccharide could involve an astronomical number of possible construction combinations.

The difference in complexity between building a protein and building a sugar is akin to stringing beads versus constructing a 3-D scale model of the cathedral of Notre Dame.

Sugars are so difficult for biologists to purify and chemists to synthesize that researchers have been largely unable to study them closely in the body. “People have not gotten their hands on a good quantity of ‘clean’ carbohydrates” to study, Seeberger said.

That is about to change. Seeberger and MIT graduate students Obadiah J. Plante and Emma R. Palmacci started with a commercially available peptide synthesizer (they found a used one relatively cheap). They modified it to mix, wash and cool a series of sugar-based reagents.

Following a simple sequence of steps that ensure that the sugar bonds form as desired, the substance ends up in a small glass cylinder that bubbles and shakes like a witch’s cauldron at regular intervals while it produces the exactly right chain of molecules.

In about 18 hours, the tabletop machine made a complex chain of 12 sugar units, which would have taken around three months to accomplish by hand.

Working Cell-to-Cell

While carbohydrates have a number of functions, including energy storage and metabolism, Seeberger is most excited about their apparent use as a bioreceptor in cell-to-cell communication.

When two cells come together, it is often the loosely attached carbohydrate protruding from one that interacts with the protein on the other. The carbohydrate moderates the interaction-whether beneficial or lethal-between the two.

The challenging sugar structures that Seeberger’s group is attempting to create with the machine are involved in cancer and other diseases. If researchers know what role a specific carbohydrate played in a disease, they may be able to design a drug that either enhances or halts that role.

Carbo Loading

The long-term goal, Seeberger says, is for a biologist or biochemist to be able to buy some monomers (the building blocks of a chain of sugar molecules), and program a machine that spits out the carbohydrate of choice.

While that reality is probably five to 10 years away, within six months researchers will be able to call in an order for a carbohydrate to Plante, one of the authors of the Science paper, who is starting a company to do just that. “Once the chemistry works, the automation is easy,” said Seeberger.

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

The problem with plug-in hybrids? Their drivers.

Plug-in hybrids are often sold as a transition to EVs, but new data from Europe shows we’re still underestimating the emissions they produce.

Google DeepMind’s new generative model makes Super Mario–like games from scratch

Genie learns how to control games by watching hours and hours of video. It could help train next-gen robots too.

How scientists traced a mysterious covid case back to six toilets

When wastewater surveillance turns into a hunt for a single infected individual, the ethics get tricky.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.