Each person has a 'germ cloud' that surrounds them containing millions of bugs, say scientists
Every one of us is surrounded by a "microbial cloud" containing millions of bugs which is almost as personal as a fingerprint, research has shown.
Scientists were able to identify individuals from a group of volunteers just by sampling germs from the air around them.
Each cloud had a "signature" that could be read by carrying out genetic analysis of the bacteria.
The noxious nimbus consists of combinations of microbes emitted from our bodies that vary from person to person.
Scientists who tested 11 volunteers identified thousands of different types of bacteria in 312 samples of air and dust taken from a chamber in which each participant was asked to sit alone.
Most of the chamber occupants could be identified within four hours by matching them to their bugs.
Lead researcher Dr James Meadow, from the University of Oregon in the US, said: "We expected that we would be able to detect the human microbiome in the air around a person, but we were surprised to find that we could identify most of the occupants just by sampling their microbial cloud."
The study, published in the online journal PeerJ, sheds light on the way bacteria are shed by humans into their surrounding environment.
It may improve understanding of the way infectious diseases are spread in buildings, say the scientists.
Identifying microbial clouds may also, like fingerprints, be useful to forensic investigations. One possibility is using bacterial traces to track people's movements, although it is unclear whether individuals could be spotted in a crowd.
Humans typically shed around a million microscopic particles from their breath, skin, clothes and hair per hour, many of which contain bacteria, said the researchers.
The scientists wrote: "Our data make clear that an occupied space is microbially distinct from an unoccupied one, and reveal for the first time that individuals occupying a space can emit their own distinct personal microbial cloud."
Belfast Telegraph Digital