As submitted by the proposer: The composition of microbial organisms associated with skin is unique to an individual. This is because the experiences each person has since birth are unique, and it is these physical interactions with the world that allow microbes to colonize and form communities (microbiomes) on our bodies. Even identical twins, whose microbiota are significantly more similar than other siblings, each have a unique profile. Growing up together means that you will share similar microbial sources, but the key to forensic application of the microbiome, is in the differences. We are born sterile, and are normally first colonized by bacteria associated with our mother. Subsequent to that our microbial assemblages are shaped by, for example, what we eat, whom we touch, where we live, and how much time we spend indoors versus outdoors. While, an individuals core microbiome is considered stable by the age of 2-3, it can still undergo variation as we change aspects of our lifestyle that cause us to be exposed to different microbial worlds. The skin microbiome is our primary interface with the world and the interface we most readily leave behind when we interact with a space. The microbial communities on our hands, noses, buttocks, and feet are unique to us, but are also impacted by our lifestyle and physical interactions with others. We therefore posit that the microbiome can be highly predictive of elements of our self and our lifestyle. To date, the evidence to support this has been limited by small studies and anecdotal enquiry. We propose to perform a systematic analysis of a human population around Miami, FL, to determine categorically whether elements of their lives can be predicted from their microbiome, both on their bodies, and that left behind on surfaces they interact with. In doing so, we will create a list of highly specific microbial biomarkers for particular traits (e.g. young adult female vegetarian, who lives in the suburbs and works in a bakery or bread counter). We will also build a sophisticated artificial neural network and database to enable extrapolation of microbial signature detection to other samples, so that a persons traits can be detected from the microbial community they leave behind. This proof of principle study will form the foundation of a forensic effort in Miami to create a new suite of trace evidence options that can be leveraged by investigators to help shape their interpretation of a crime scene.
This project contains a research and/or development component, as defined in applicable law.