Everybody poops—and after a few thousand years underground, these droppings often start to look the same. That stool-based similarity poses something of a puzzle for archaeologists investigating sites where dogs and humans once cohabited, as it isn’t always easy to deduce which species left behind specific feces.
But as a team of researchers writes in the journal PeerJ, a newly developed artificial intelligence system may end these troubles once and for all. Called corpoID—an homage to “coprolite,” the formal term for fossilized feces—the program is able to distinguish the subtle differences between ancient samples of human and canine excrement based on DNA data alone, reports David Grimm for Science magazine.
Applied to feces unearthed from sites around the world, the new method could help researchers unveil a trove of valuable information about a defecator’s diet, health, and perhaps—if the excretion contains enough usable DNA—identity. But in places where domesticated dogs once roamed, canine and human DNA often end up mixed in the same fecal samples: Dogs are known to snack on people’s poop, and some humans have historically dined on canine meat.
Still, differences in the defecations do exist—especially when considering the genetic information left behind by the microbiome, or the microbes that inhabit the guts of all animals. Because microbiomes vary from species to species (and even from individual to individual within a species), they can be useful tools in telling droppings apart.
To capitalize on these genetic differences, a team led by Maxime Borry of Germany’s Max Planck Institute for the Science of Human History trained a computer to analyze the DNA in fossilized feces, comparing it to known samples of modern human and canine stool. The researchers then tested the program’s performance on a set of 20 samples with known (or at least strongly suspected) species origins, including seven that only contained sediments.
The system was able to identify all of the sediments as “uncertain,” and it correctly classified seven other samples as either dog or human. But the final six appeared to stump the program.
Writing in the study, Borry and his colleagues suggest that the system may have struggled to identify microbiomes that didn’t fall in line with modern human and canine samples. People who had recently eaten large quantities of dog meat, for instance, might have thrown the program for a loop. Alternatively, ancient dogs with unusual diets could have harbored gut microbes that differed vastly from their peers, or from modern samples.
“There is not so much known about the microbiome of dogs,” Borry tells Vice’s Becky Ferreira.
With more information on how diverse canine gut microbes can get, he says, the team’s machine learning program may have a shot at performing better.
Ainara Sistiaga, a molecular geoarchaeologist at the University of Copenhagen who wasn’t involved in the study, echoes this sentiment in an interview with Science, pointing out that the data used to train coproID came exclusively from dogs living in the modern Western world. It therefore represented just a small sliver of the riches found in canine feces.
CoproID also failed to determine the origins of highly degraded samples that contained only minimal microbial DNA. With these issues and others, “there are definite issues that need to be resolved before the method can be used widely,” Lisa-Marie Shillito, an archaeologist at Newcastle University who wasn’t involved in the study, tells Michael Le Page of New Scientist.
With more tinkering, the method could reveal a great deal about the history of humans and dogs alike—including details about how the two species first became close companions, Melinda Zeder, an archaeozoologist at the Smithsonian Institution’s National Museum of Natural History who wasn’t involved in the study, tells Science.
As dogs swapped the fleshy, protein-heavy diets of their wolfish ancestors for starchy human fare, their gut microbes were almost certainly taken along for the ride. Even thousands of years after the fact, feces could benchmark this transition.
Says Zeder, “The ability to track this through time is really exciting.”