Bacteria are resilient organisms with the ability to change their metabolism to enter a dormant state that allows them to survive long periods. Dormant bacteria, known as spores, are able to come back to life after a long period of time and can even withstand extreme pressure and temperature. However, researchers have been trying to discover how bacteria sense changes in their environment and take action to break out of dormancy. Now, researchers from Harvard Medical School (HMS) have discovered a new kind of cellular sensor that allows spores to detect the presence of nutrients in their environment and quickly spring back to life.

Their findings are published in the journal Science in an article titled, “Bacterial spore germination receptors are nutrient-gated ion channels,” and may illuminate new paths for disease prevention.

“This discovery solves a puzzle that’s more than a century old,” said study senior author David Rudner, PhD, professor of microbiology at the Blavatnik Institute at HMS.

For more than a century, scientists have known that when spores detect nutrients in their environment, they rapidly shed their protective layers and reignite their metabolic engines. Although the sensor that enables them to detect nutrients was discovered almost 50 years ago, the means of delivering the wake-up signal, and how that signal triggers bacterial revival has remained a mystery.

In most cases, signaling relies on metabolic activity and often involves genes encoding proteins to make specific signaling molecules. However, these processes are all shut off inside a dormant bacterium, raising the question of how the signal induces the sleeping bacteria to wake up.

In this study, the scientists discovered that the nutrient sensor itself assembles into a conduit that opens the cell back up. In response to nutrients, the conduit, a membrane channel, opens, allowing ions to escape from the spore interior. This initiates a cascade of reactions that allow the dormant cell to shed its protective armor and resume growth.

The scientists used artificial intelligence tools to predict the structure of the folded sensor complex, a structure made of five copies of the same sensor protein. They applied machine learning to identify interactions between subunits that make up the channel. They also used gene-editing techniques to induce bacteria to produce mutant sensors as a way to test how the computer-based predictions played out in living cells.

“The thing that I love about science is when you make a discovery and suddenly all these disparate observations that don’t make sense suddenly fall into place,” Rudner said. “It’s like you’re working on a puzzle, and you find where one piece goes and suddenly you can fit six more pieces very quickly.”

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