Looking Beyond Mice: Why Biology Needs Stranger Model Organisms

Looking Beyond Mice: Why Biology Needs Stranger Model Organisms

It’s been almost a month since my last post, with finals, Thanksgiving, and friends visiting Boston keeping me completely busy. While diving into papers for my final projects, a concept that I’d thought about before but never really looked into has been brought back to my attention.

I’ve always wondered why academics don’t put a greater focus on studying organisms outside the usual B6 mice, zebrafish, fruit flies, etc. These organisms are great for modeling human diseases, but not all medical breakthroughs are achieved directly from human cellular biology. If you look at some of the most impactful medical breakthroughs in the past 20 years, many of them stem from non-traditional model organisms, despite the majority of biomedical research focusing directly on humans via model organisms. Just off the top of my head, discoveries such as GFP thanks to the crystal jellyfish, neuronal memory storage thanks to sea slugs, and CRISPR-Cas9 thanks to Streptococcus have all been awarded Nobel Prizes. The blood of horseshoe crabs has saved millions of lives due to its use in vaccines, and I read the other day about how the FoxO gene in freshwater hydra is being studied to reverse scar tissue in burn victims. All of these things lead me to wonder why we are so much more obsessed with finding out every possible cellular interaction in a mouse model than looking outside the box for strange organisms that could ultimately drive more unique breakthroughs.

One of the main allures of using standard models is that they are easier, thanks to well-established protocols and hosts of literature and databases supporting them. But I think the biggest hindrance to thinking outside the model organism box is funding. Funding agencies often favor projects using familiar systems because reviewers are confident in the reliability and comparability of the results. The most recent paper I was able to find (that actually published their own stats) showed that 75% of publications used one of the 13 NIH-recognized model organisms (Dietrich, 2014). This concentration of research, data, and tools creates a self-reinforcing feedback loop: the more a model is used, the more resources are developed for it, which in turn makes it even easier to get funding and publish studies, further enabling its dominance.

But this feedback loop system comes with a downside. By focusing narrowly on traditional models, scientists can unconsciously limit the questions they ask and overlook biological phenomena that only appear in unusual organisms. This causes something of an “academic inertia,” where research priorities reinforce themselves over decades, making it harder for unconventional models to gain traction, even if they hold amazing potential to drive breakthroughs.

Finally, it is important that we as scientists think to the future, and the closer we get to fully characterizing human biology, the more incremental new discoveries will inevitably become at some point. Thanks to decades of intense study, many core pathways in human cells are well mapped. Progress still happens, but it often comes in smaller, more specialized steps rather than paradigm-shifting leaps. In contrast to our decades of research, evolution has spent billions of years exploring solutions to biological problems for millions of organisms that go well beyond just keeping us alive. Studying these systems won’t just fill gaps in our understanding; it will introduce entirely new questions and mechanisms that we would be unable to discover by studying human cells alone.

To sum things up, our current academic research system rewards efficiency and reproducibility, but not so much novelty or exploring nature’s extremes. If we want to avoid future bottlenecks and drive the next generation of breakthroughs, we can’t rely solely on extracting fine details from the same 13 organisms. Looking outside the box isn’t rejecting our traditional models; it’s a complement to them. By embracing biological diversity, we allow discovery to be driven not just by what is convenient or familiar, but by what evolution has already proven possible.

Michael R. Dietrich, Rachel A. Ankeny, Patrick M. Chen, Publication Trends in Model Organism Research, Genetics, Volume 198, Issue 3, 1 November 2014, Pages 787–794.

I’ve reached out to a couple of labs studying unconventional model organisms with questions, and hopefully I can include their insights in future posts.