Holobiont Urbanism: sampling urban beehives reveals cities’ metagenomes

Background Over half of the world’s population lives in urban areas with, according to the United Nations, nearly 70% expected to live in cities by 2050. Our cities are built by and for humans, but are also complex, adaptive biological systems involving a diversity of other living species. The majority of these species are invisible and constitute the city’s microbiome. Our design decisions for the built environment shape these invisible populations, and as inhabitants we interact with them on a constant basis. A growing body of evidence shows us that human health and well-being are dependent on these interactions. Indeed, multicellular organisms owe meaningful aspects of their development and phenotype to interactions with the microorganisms—bacteria or fungi—with which they live in continual exchange and symbiosis. Therefore, it is meaningful to establish microbial maps of the cities we inhabit. While the processing and sequencing of environmental microbiome samples can be high-throughput, gathering samples is still labor and time intensive, and can require mobilizing large numbers of volunteers to get a snapshot of the microbial landscape of a city. Results Here we postulate that honeybees may be effective collaborators in gathering samples of urban microbiota, as they forage daily within a 2-mile radius of their hive. We describe the results of a pilot study conducted with three rooftop beehives in Brooklyn, NY, where we evaluated the potential of various hive materials (honey, debris, hive swabs, bee bodies) to reveal information as to the surrounding metagenomic landscape, and where we conclude that the bee debris are the richest substrate. Based on these results, we profiled 4 additional cities through collected hive debris: Sydney, Melbourne, Venice and Tokyo. We show that each city displays a unique metagenomic profile as seen by honeybees. These profiles yield information relevant to hive health such as known bee symbionts and pathogens. Additionally, we show that this method can be used for human pathogen surveillance, with a proof-of-concept example in which we recover the majority of virulence factor genes for Rickettsia felis , a pathogen known to be responsible for “cat scratch fever”. Conclusions We show that this method yields information relevant to hive health and human health, providing a strategy to monitor environmental microbiomes on a city scale. Here we present the results of this study, and discuss them in terms of architectural implications, as well as the potential of this method for epidemic surveillance.