Note by Jonathan Eisen
Last week I saw an interesting new paper in AEM entitled: Indoor-Air Microbiome in an Urban Subway Network: Diversity and Dynamics. I thought it was of relveance of microBEnet so I wrote to the senior author Dr. Patrick Lee from the School of Energy and Environment and the City University of Hong Kong inviting him to write a guest post for microBEnet. He recommended the first author, Marcus Leung, a post doc, as a possible contributor and Marcus agreed. Below is Marcus’ post.
If you think your city subway only consists of smelly disgruntled commuters, think again…
By: Marcus Leung (twitter @leungmarcus)
Have you ever wondered what microbes are around you when you take public transport? Personally, I think about it every day during my two-hour subway commute to and from our lab here in Hong Kong. Besides residential units, schools, and offices, modern urbanites like myself (and yourself!) also spend a lot of time on public transports such as subways. However, compared to the former urban settings, we know relatively little about the microbial composition of subway networks, and some of the potential factors that influence this composition. Furthermore, when one ponders that much of what we know about the subway microbiome over the past few decades comes from insensitive cultivation methods, there exists a knowledge gap waiting to be filled. We believe that, in this scientific age of molecular biology, systems biology, and bioinformatics, we can do more. This knowledge will ultimately lead to better air quality and well-beings of commuters, by highlighting the importance of microbial communities in this overlooked environment.
The works of Dybwad et al. and Robertson et al. act as pioneering cultivation-independent analysis of the subway systems of New York City and Oslo, respectively. While demonstrating the increased breadth of microbial life never documented previously on subways, evidences of temporal, anthropogenic, and environmental factors influencing subway microbiome were documented in these well-designed and investigations. These works in turn inspired our group at City University of Hong Kong’s School of Energy and Environment to hypothesized that, because these factors are also different for different subway systems, microbial communities should also differ between systems. However, contrary to the previous stationary sampling methods, we also wanted to provide a time-integrated sampling protocol to accurately represent commuter exposure.
After what seemed like countless hours on the subway, we determined the microbial composition of our local subway by targeting the V4 region of the 16S rRNA gene and sequencing performed on the Illumina MiSeq platform. In our recent publication to Applied and Environmental Microbiology, we demonstrated that the microbial community differed between architectural properties. Specifically, subway lines that are predominantly underground and indoor (and mechanically-ventilated) varied in community from those lines overground and exposed to the outdoor environment. Human-associated genera were more abundant in indoor/underground lines, compared to outdoor/overground lines. While diversity was greater in outdoors than the subway, what is encountered in the network is greatly influenced by microbial communities detected in the adjacent outdoors, and also there exists a significant positive correlation between the connectedness (i.e. how connected they are in terms of number of interchange stations, as explained in our work) of two lines and their community similarities. We also detected minor but significant differences in composition between daytime and nighttime, suggesting a temporal dynamics in the community of subway air. Some other findings include the potential roles of various environmental parameters (such as relative humidity, temperature, and CO2) on the microbial diversity of the samples, as well as relative abundances of selected genera.
Last but not least, when we compared our microbiome results from that of Meadow et al. on college air microbiome and Dunn et al. on household surface microbiome (both of these studies also uses the same sequencing platform targeting V4 region), based on UniFrac phylogenetic distances, we see significant compositional variations. Although many factors (e.g. sampling and other inter-laboratory methodological differences) may contribute to the observed variations, Hong Kong and NYC subways also differed at a taxonomic level, reflecting a potential geography-driven phenomenon.
We strongly believe that our study will act as a stepping-stone for additional air microbiome analysis of different subway systems around the world. Additionally, by employing identical (or similar) sequencing methodologies, we encourage other research groups to compare subway microbiome results across different investigations. This will not only allow local factors governing subway air microbial composition to be identified, but also general attributes that may act on general subway microbiome at a global level.