Mohamed Salem (L), Youssef Ali, and Guglielmo Raymo have found a simple genetic marker to detect stress in fish.
Mohamed Salem and his team spend their days looking for subtle signs of stress in animals that cannot communicate when something is wrong. They can’t talk, but they can get stressed out by things like heat, low oxygen, over-crowding, and improper diet. All of which can reduce their growth and make them more susceptible to disease. Salem’s subjects are fish, and the University of Maryland professor of animal and avian science has discovered an easy way to measure their stress levels with genomics, because a happy fish is a healthy fish.
But it’s more than just feel-good animal husbandry for Salem. Globally, more than 3.3 billion people get at least 20% of their daily animal protein from fish, and with rising water temperatures threatening commercial fish stocks, and ever- increasing demands on modern fish farming, understanding and more importantly, preventing fish stress is critical for both conservation and the world’s food supply.
Traditionally, scientists test levels of the hormone cortisol in fish blood to determine stress levels. But that approach can yield variable results, so Salem’s team has been looking for something more precise and definitive. Although fish can't tell him what they feel, their bodies are talking all the time through the language of genetics. And Salem’s lab is learning to decode it.
Every single cell in an animal’s body is constantly reacting to the world around it on a genomic level. And those reactions leave behind a trail of evidence. For example, when we go out into the sun, we’re exposed to damaging UV rays, so our skin cells turn on genes involved in DNA repair. They also turn off genes involved in cell division to prevent damage from being copied. So, reading the genes to see what’s been turned on and off can tell someone quite a bit about an animal’s environment.
The challenge for Salem’s team was in the sheer number of genes in a fish and the possible responses they could have to different stressors. When he and the students working in his lab looked at rainbow trout exposed to five different kinds of stressors, things like high heat, low oxygen and bad water, they found that over 21,000 different genes were either switched on or switched off. What’s more, each type of stress created its own unique genetic signature.
Testing thousands of genes to determine a fish’s stress level is not a practical solution, so the team needed to sift through all that data to identify patterns and pare it down to something more usable. They turned to machine learning with the help of freshman Animal Science student Youssef Ali, who was a high school intern in the lab at the time. Youssef had always been interested in computer science, and he recognized that AI tools could help make sense of all the data Salem had been collecting.
Under the guidance of PhD student Guglielmo Raymo, Youssef took the lead in applying AI to the problem, first looking for a handful of genes that could tell them when a fish was experiencing any kind of stress, like a single key to decode all possible stresses. But that effort turned out to be too broad. The AI algorithm identified 39 core genes associated with stress in the test data the team provided, but it was unable to use them to accurately predict general stress in the genomes of fish it hadn’t seen before.
So the team took another approach and guided their machine learning algorithms to look for genetic markers of just one type of stress, heat stress. The algorithm searched the 12,000 plus genes related specifically to that, narrowing it from thousands to hundreds to dozens, until finally they were able to identify just two genes that, taken together, could act as a nearly perfect biomarker for telling if a rainbow trout was suffering from heat stress.
First, there’s one called HSP 47, which protects collagen in cells and basically keeps the fish's muscles from falling apart. The second one is HspA four L, the protein re-folder. This one is like the emergency responder that rushes in to fix other proteins that could be damaged by heat stress. Using only those two genes, the AI models could predict heat stress with up to 98.6% accuracy.
“It could be a game changer,” Salem said. “A simple, elegant, and incredibly powerful tool that gives us a real-world, practical framework for actually improving stress resilience in fish.”
The discovery, which was published in the journal Nature Scientific Reports in December, 2025, provides fish farmers and conservationists alike with a tool to know when fish are in danger. So far, the work has focused on rainbow trout, but the genetic markers Salem and his team identified are present across fish species. The researchers expect further studies to show similar success in other commercially important fish.
“If they prove transferable, it can help conservationists monitor wild fish populations, and fish farmers monitor health and environmental stress in aquaculture systems,” Salem said. “And it can even be used in breeding programs to select for fish that are naturally more resilient to heat.”
The team is also expanding their work to look at additional stressors, and they recently received a grant from USDA NIFA to identify similar markers for stress across a broader range of environmental conditions.
