1 protein to rule them all – why crowning the protein that makes jellyfish glow green as a model can help scientists streamline biology

Fruit flies, mice, zebra fish, yeast and the tiny worm C. elegans are model organisms that have carried modern biology on their backs.

Scientists did not choose them for their charisma. They were chosen because their similarities illuminate biological principles across many species. Their biology is simple enough for researchers to master yet deep enough to keep delivering new insights centuries later.

But biologists don’t have a common reference point for a vast area of the field: proteins, the cell’s doers. Proteins catalyze chemical reactions, give cells their structure and help them communicate with each other. Most organisms use tens of thousands of protein types, and each can be mutated, modified and measured in different ways and in countless environments. Thanks in part to artificial intelligence, researchers are also generating new proteins faster than they can study them.

Without a shared reference point, study results are hard to compare. Two labs can study the same protein under different experimental conditions and end up with findings that do not line up. The result is a scientific literature full of isolated findings that are sometimes duplicated and difficult to generalize.

As a computational chemist who studies fluorescent proteins, I argue that labs also need a set of model proteins. Like how fruit flies and mice anchor whole fields, model proteins can help researchers build on each other’s findings and better understand the fundamentals of biology.

Green fluorescent protein as a model

If model proteins are to be yardsticks, the best place to start is with proteins researchers already reach for when they need a reliable standard. Green fluorescent protein is at the top of that list.

Green fluorescent protein, first isolated from a jellyfish, glows bright green when under a blue light. Biologists fuse green fluorescent protein to other proteins to track where the proteins go and when they are made.

Green fluorescent protein is already a de facto reference point for the field, used as a practice protein in experiments before attempting bigger goals. In the early 2000s, researchers used the protein and a yellow version in cloned pigs to show that foreign genes could be added to large mammals and reliably work. Green fluorescent protein made it obvious that the new gene was successfully incorporated because researchers could literally see that the pigs’ cells were making the protein encoded by the fluorescence genes.

The long-term aim of these experiments was to engineer pigs to produce specific human proteins that help the immune system accept a pig organ rather than reject it. Green fluorescent protein helped show that the basic engineering of this idea could work, which eventually led to the first pig-to-human kidney transplants.

The use of green fluorescent protein is not the endpoint of most studies but the proof step. It allows researchers to say, yes, the new gene is there, the cell is making the protein, the protein is working and will probably work with other proteins.

AI is forcing benchmarks

When researchers are hunting for new proteins to use as enzymes, treatments or materials, protein language models and other generative AI methods can propose huge numbers of plausible protein sequences for them to test. While some AI-designed proteins do work in the lab and can help reduce trial and error, many candidate proteins fail.

Fluorescent proteins can be a useful stress test for protein language models. The hardest part of using AI to generate proteins is proving that the sequences it suggests can become a properly folded, working protein.

Green fluorescent protein makes that proof straightforward because fluorescence allows you to quickly see that the protein has folded correctly. You can predict the brightness, stability or color of fluorescent proteins, then directly check whether the AI-generated protein matches. Like a mouse study that hints a drug might work in humans, green fluorescent protein doesn’t guarantee an AI model will succeed on every protein, but it’s a quick, widely trusted sign that the design pipeline is doing something right.

Calling green fluorescent protein a model protein would also improve how biology is taught. Like classic model organisms, green fluorescent protein is safe and visual. It is also forgiving, producing a clear, fluorescent signal even when student study designs aren’t perfect.

These traits make it an educational gateway to ideas such as gene expression, protein folding and bioengineering. It can turn an abstract concept into something you can see in a test tube or under a microscope.

Model organisms work because scientific communities agreed to build around common reference points. I believe protein science is now vast enough to need the same, and naming green fluorescent protein as a model protein could make it easier to connect discoveries, teach students and assess new tools.

The glow, in other words, can still guide scientists – not just by dazzling, but by helping the whole field add up.

This article is republished from The Conversation, a nonprofit, independent news organization bringing you facts and trustworthy analysis to help you make sense of our complex world. It was written by: Marc Zimmer, Connecticut College

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Marc Zimmer received funding from NIH to research fluorescent proteins.