These news came out sometime last week and I am somewhat late posting about it. Nevertheless, a very interesting study.
New York City's subway system is used by an average of 5.5 million people per day which makes it an ideal place for some serious microbial ecosystem studies. Therefore, a group of researchers from different institutions of the city decided to undertake a large-scale metagenomic study.
Over a period of 17 months a team of students used nylon swabs to collect DNA from turnstiles, wooden and metal benches, stairway hand railings, trashcans, and kiosks in all open subway stations in 24 subway lines in five boroughs of New York City. They also collected samples from the inside of trains, including seats, doors, poles and handrails.
All these samples were sequenced as the colleagues sought to characterize the NYC metagenome by surveying the genetic material of the microorganisms and other DNA present in, around, and below NYC, with a focus on the highly trafficked subways and public areas.
The results were quite interesting. What struck me most was the fact that about half of the sequences of DNA collected could not be identified. They did not match any organism in GenBank or other databases, e,g. at the CDC. The findings underscore the vast potential for scientific exploration that is still largely untapped and yet quite literally right under our fingertips.
The microbes that call the New York City subway system home are mostly harmless
, but include samples of disease-causing bacteria that are resistant to drugs - even a few DNA fragments associated with anthrax and Bubonic plague. The publication contains a citywide microbiome map which the colleagues call "PathoMap". They see their work as a baseline assessment, and repeated sampling could be used for long-term, accurate disease surveillance, bioterrorism threat mitigation, and large scale health management for New York.
What I particularly like about this publication is the wealth of data that came with it. The supplementary data part of the paper is huge (about 100MB zipped) and the paper is open access because the authors choose to pay for this option. A great example of reproducible science.