The Airplane Cabin Microbiome

The Airplane Cabin Microbiome Serving over three billion passengers annually, air travel serves as a conduit for infectious disease spread, including emerging infections and pandemics. Over two dozen cases of in-flight transmissions have been documented. To understand these risks, a characterization of the airplane cabin microbiome is necessary. Our study team collected 229 environmental samples on ten transcontinental US flights with subsequent 16S rRNA sequencing. We found that bacterial communities were largely derived from human skin and oral commensals, as well as environmental generalist bacteria. We identified clear signatures for air versus touch surface microbiome, but not for individual types of touch surfaces. We also found large flight-to-flight beta diversity variations with no distinguishing signa- tures of individual flights, rather a high between-flight diversity for all touch surfaces and particularly for air samples. There was no systematic pattern of microbial community change from pre- to post-flight. Our findings are similar to those of other recent studies of the microbiome of built environments. In summary, the airplane cabin microbiome has immense airplane to airplane variability. The vast majority of airplane-associated microbes are human commensals or non-pathogenic, and the results provide a baseline for non-crisis-level airplane microbiome conditions. . . . . Keywords Commercial airplanes Microbiome Bacteria Pandemic Respiratory infection Howard Weiss and Vicki Stover Hertzberg contributed equally to this work. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00248-018-1191-3) contains supplementary material, which is available to authorized users. * Howard Weiss School of Mathematics, The Georgia Institute of Technology, 686 weiss@gatech.edu Cherry St. NW, Atlanta, GA 30313, USA Vicki Stover Hertzberg Nell Hodgson Woodruff School of Nursing, Emory University, 1520 vhertzb@emory.edu Clifton Rd. NE, Atlanta, GA 30322, USA Chris Dupont J. Craig Venter Institute, 4120 Capricorn Lane, La Jolla, CA 92037, cdupont@jcvi.org USA Josh L. Espinoza jespinoz@jcvi.org 4 HudsonAlpha Institute for Biotechnology, 601 Genome Way, Huntsville, AL 35806, USA Shawn Levy slevy@hudsonalpha.org J. Craig Venter Institute, 9714 Medical Center Drive, Karen Nelson Rockville, MD 20850, USA knelson@jcvi.org Sharon Norris Boeing Health Services, The Boeing Company, 3156 160th Ave. NE, sharon.l.norris@boeing.com Bellevue, WA 98008-2245, USA Weiss H. et al. Introduction airplane cabin microbiome might differ considerably from those of other built environments. Another key difference is With over three billion airline passengers annually, the risk of that in an airplane cabin, it is difficult to avoid a mobile sick in-flight transmission of infectious disease is a vital global person, or one sitting in close proximity. health concern [1, 2]. Over two dozen cases of in-flight trans- In another publication [42], we describe behaviors and mission have been documented, including influenza [3–7], close contacts of all passengers and flight attendants in the measles [8, 9], meningococcal infections [10], norovirus economy cabin on ten flights of duration 4 hours or more, [11], SARS [12, 13], shigellosis [14], cholera [15], and the FlyHealthy™ Study. FlyHealthy™ has provided first de- multi-drug resistant tuberculosis [1, 16–18]. Studies of tailed understanding of infectious disease transmission oppor- SARS [12, 13] and pandemic influenza (H1N1p) [19]trans- tunities in an airplane cabin. In addition to quantifying the mission on airplanes indicate that air travel can serve as a opportunities, we wanted to understand the infectious agents conduit for the rapid spread of newly emerging infections present in an airplane cabin that might be transmitted during and pandemics. Further, some of these studies suggest that these opportunities. the movements of passengers and crew (and their close con- To this end, we identified the microbiota present on these tacts) may be an important factor in disease transmission. In flights, allowing characterization of the airplane cabin 2014, a passenger infected with Ebola flew on Frontier airlines microbiome. We hypothesized that the airplane cabin the night before being admitted to a hospital [20]. Luckily, she microbiome differs from that of other built environments did not infect anybody during that trip. due to the above-stated reasons. Since the majority of flights Despite many sensational media stories and anecdotes, e.g., were during the seasonal flu epidemic in either the originating BFlying The Filthy Skies^ [21]or BThe Gross Truth About city or the destination city, we were interested to determine if Germs and Airplanes^ [22], the true risks of in-flight trans- we could detect influenza virus in our samples. Since the mission are unknown. An essential component of risk assess- transmission opportunities we characterized in the first part ment and public health guidance is characterizing the back- of the FlyHealthy™ study were those that would allow trans- ground microbial communities present, in particular those in mission by large droplets, we were interested in sampling air the air and on common touch surfaces. Next-generation se- as well as touch surfaces (fomites). Key questions related to quencing has the potential to identify all bacteria present via differences between types of samples (air versus touch sur- their genomes, commonly called the microbiome. There have faces), pre- to post-flight changes, and changes from flight- been a few previous studies of the bacterial community in to-flight in the Bcore^ airplane cabin microbiome. cabin air [23–26], but none, to our knowledge, on airplane touch surfaces. These studies estimated total bacterial burden of culturable cells present, and applied early forms of 16S Results rRNA sequencing and bioinformatics, claiming species-level resolution. At the time of these studies, there were far fewer Airplane Cabin Bacterial Communities in the Air reference genomes with which to align. Although these were and on Touch Surfaces at the vanguard of research of the microbiome of built envi- ronments, 10 years later, current methods and protocols are Skin commensals in the family Propionibacteriaceae domi- significantly more rigorous. nate both air (~ 20% post-filtered reads) and touch surfaces The microbiome of the built environment is an active re- (~ 27% post-filtered reads). There is substantial overlap of the search area. Using a wide range of methods, authors have top 20 families in air and touch surface samples (Fig. 1). The studied the microbiomes of classrooms [27–29], homes top ten families in both air and fomites additionally contain [30–32], offices [33, 34], hospitals [35], museums [36], nurs- Enterobacteriaceae, Staphylococcaceae, Streptococcaceae, ing homes [37], stores [38], and subways [39–41]. Several of Corynebacteriaceae,and Burkholderiaceae.The environ- these studies, particularly those of classrooms and offices, mental bacteria Sphingomonadaceae is quite prevalent in the identified significant quantities of Lactobacillus on seats. air, but much less so on touch surfaces. Note that Bunclassified With the exception of the hospital microbiome, all of these family^ aggregates different families from different higher studies indicate that the main microbiome constituents, at the level taxa. The top OTUs are shown in SM Fig. 1. family level, are human commensal and environmental bacte- OTUs within the genera Propionibacterium and ria. What else could they be? Burkholderia were present in every sample and two OTUs, Airplane environments are unique to the examples listed annotated as genus Staphylococcus and Streptococcus above. Special features include very dry air, periodic high (oralis), were present in all but one sample. These four occupant densities, exposure to the microbiota of the high OTUs are contained in three phyla: Actinobacteria, atmosphere, and long periods during which occupants have Proteobacteria,and Firmicutes,and comprise the Bcore^ extremely limited mobility. Thus, one might expect that the airplane cabin microbiome. The Airplane Cabin Microbiome Fig. 1 Most prevalent families in air (left) and touch surface samples (right) by relative abundance (proportion of families) Air and Touch Surface Communities Have Discernible with the variance explained by PC1 (Fig. 2b), this indicates a Signatures, but There Are No Discernible Signatures clear signature of the air community. The complement is the of Touch Surface Types signature of the touch surface community. There is a potpourri of touch surface types in the figure, again indicating the lack of Figure 2 shows the results of the principal component analysis clear signature of individual touch surface type. There are no (PCA) on a log-scale of families of all samples over all ten statistically significant differences of alpha diversity between flights. The associated scree plot (SM Fig. 3)indicates that air and fomites as measured by any of six indices (SM Fig. 2). the vast majority (73%) of the variability is captured by first Use of an infinite Dirichlet–multinomial mixture (iDMM) principal component, about an order of magnitude more than model [43] identified four clusters (or ecostates), with ecostate that captured by PC2. We observe that the air samples are 4 containing the vast majority of air samples, though it also primarily positive on PC1 and, in fact, greater than 50, while includes many fomite samples as well (Fig. 3a). Figure 3b the touch surface samples are largely negative. When combined shows the diagnostic OTUs present in this air cluster and their Fig. 2 Scatterplot of the logs of the first two principal components, colored by sample source. a Families. b OTUs Weiss H. et al. Fig. 3 Results of iDMM analysis indicating two distinct ecostates. a Composition of the four ecostates identified in the iDMM analysis. b Most prevalent OTUs identified in the two ecostates associated with cabin air weights. Note that the weights are an essential component of within-flight (W) beta diversity, that is, each flight is already this characterization. starting with microbiomes that are likely different from other Another important question is whether bacterial communi- flights. ties change discernibly during flight? Again, Fig. 4 shows the admixture of pre- and post-flight communities in the touch surface samples. Note the linearity of these scatterplots of Discussion the logged average number of reads for OTUs from pre- to post-flight for each touch surface type. There is no discernible Toward the goal of characterizing the airplane cabin pattern of change of pre-flight to post-flight communities. microbiome, our study team flew on ten transcontinental A final key question is whether bacterial communities in US flights on which we collected 229 air and touch surface the cabin air change discernibly from flight to flight? For samples. We employed highly stringent quality control example, is there a difference between east-bound versus criteria during sampling, sample extraction, 16S rRNA west-bound flights? A principle component analysis at both gene sequencing, and the bioinformatics pipeline. The ob- the family and OTU levels shows a wide variation with no served microbial communities, when merged across sam- clustering by flight (Fig. 5). Furthermore, without exception, ples, are comprised of human commensals and common between-flight (B) beta diversity is statistically higher than environmental (water and soil) genera. We identified a The Airplane Cabin Microbiome Fig. 4 Logged average number of reads for OTUs from pre- to post-flight for each touch surface (fomite) type Bcore^ airplane cabin microbiome containing OTUs within Propionibacterium is a genus of the phylum the genera Propionibacterium, Burkholderia (glumae), Actinobacteria, comprised of commensal bacteria that live Staphylococcus,and Streptococcus (oralis). We identified on human skin and commonly implicated in acne. clear OTU signatures for the air microbiome, but not for Burkholderia glumae is a species of the phylum individual touch surface types. We found no meaningful Proteobacteria and is a soil bacterium. Staphylococcus is a differences between air and touch surfaces with respect to genus of the phylum Firmicutes that is found on the skin alpha diversity measures. Finally, we found no systematic and mucus membranes of humans. Most species of pattern of change from pre- to post-flight. Staphylococcus are harmless. Streptococcus oralis, a species We also found large flight-to-flight variations with no of the phylum Firmicutes, is normally found in the oral cav- distinguishing signatures of individual flights. This would ities of humans. These constituents of the core airplane cabin suggest that each flight starts with a different microbiome microbiome are usually harmless to humans unless an unusual from other flights, which would greatly hinder pre-and opportunity for infection is present, such as a weakened im- post-flight microbiome comparisons (e.g., Fig. 4)that ag- mune system, an altered gut microbiome, or a breach in the gregate samples between flights. A methodological impli- integumentary system. cation is that aggregating communities between flights for While airplane cabins are certainly examples of built statistical analyses is problematic. Instead, sample repli- environments, there are unique features. These include cation must be derived from within a flight in order to very dry air, periodic high occupant densities, exposure determine how passengers alter the airplane cabin to the microbiota of the high atmosphere, long periods microbiome. Every plane being different in terms of its during which occupants have extremely limited mobility, microbiome suggests that each retains aspects of its his- and it is difficult to avoid a mobile sick person or one torical living microbiome, that is, the passengers. The de- sitting in close proximity. Half of the cabin air is recycled velopment of a cleaning routine that erases much of this after passing through a bank of HEPA filters, and the inherited microbiome could be a powerful preventative other half is taken from the outside. Furthermore, the air- measure against the spread of disease. line’s cabin cleaning policy is to disinfect all hard surfaces Weiss H. et al. ab Fig. 5 Beta diversity of samples. Scatterplot of the first two principal components of the beta diversity analysis, for a OTU-level and b family-level abundance, based on a Bray-Curtis distance. c Distributions of Bray-Curtis distances for different touch surface types, within and between flights whenever the plane Bovernights,^ and all touch surface species, Propionibacterium acnes, a common skin commen- samples were taken from hard surfaces. Different airlines sal, was excluded from discovery in the New York City sub- have different cabin disinfection protocols and supervise way microbiome study. their cabin cleaning staff in different ways. Although different primers and sequencing techniques Despite the uniqueness of the airplane cabin as a built en- were used, the core microbiome identified in the Boston sub- vironment, our findings are surprisingly consistent with other way system study has significant overlap with airplane cabins recent studies of the microbiome of built environments. This [41]. Corynebacteriaceae, a skin commensal, appeared in consistency is reassuring in light of frequent sensationalistic nearly every subway sample, and while we do not include it media stories about dangerous germs found on airplanes. For in the airplane cabin core list, it was present in all but ten of this reason, there is no more risk from 4 to 5 hours spent in an our samples. A study of the microbiome of the International airplane cabin than 4–5 hours spent in an office, all other Space Station, the only other airborne built environment that exposures being the same. Our microbiome characterization has been studied, led to the same conclusion [44], as did two also provides a baseline for non-crisis level airplane studies of office spaces [33, 34]. microbiome conditions. A number of previous studies identified large amounts of It is not possible to make quantitative comparisons to other Lactobacillus,but Lactobacillaceae did not appear in our list studies which used different primers and different sequencing of 20 most prevalent families in our touch surface samples. methods and technologies. For example, the genus Lactobacillus is commonly found in vaginal microbiota, sug- Propionibacterium is a core component of the airplane cabin gesting that it should be found on surfaces where women sit. microbiome, but by choice of primers, the most common Many other studies of the built environment have sampled The Airplane Cabin Microbiome seats, and thus, it is not surprising to find Lactobacilli present Air Sampling Methods in those environments. We did not sample from the seat fabric where passengers sat; thus, the absence of Lactobacilli in the The two air sampling pumps used were model SKC 20 most prevalent families is to be expected. AirChek XR5000. These were located in a seat at the Airplanes fly through clouds. The narrow-body twin-en- back of the economy class cabin. Both pumps sampled gine models on which we flew use about 50% bleed at 3.5 liters per second, the NIOSH protocol for station- (outside) air to refresh the cabin air throughout the flight. ary sampling and approximately the normal breathing A study of the microbiome of clouds finds some members rate of adults. of the Propionibacterium and Burkholderia families in their Just prior to each sampling, each pump was calibrated core, as well as Streptococcus in some samples [45]. A using a MesaLab Defender Calibrator. Air samples of 30- more recent study of cloud water found Burkholderia, mindurationwere collected onboardtheaircraft during Staphylococcus,and Streptococcus in samples [46]. five distinct sampling intervals. Once the pilot an- Interesting future research would be to ascertain the nounced the flight time, we calculated the quarter-way influence of the cloud microbiome on the airplane cabin point, halfway point, and three quart-way point. Thus, microbiome. the five sampling periods were pre-boarding and boarding, In conclusion, our study found that although the Q1 ± 15 min, Q2 ± 15 min, Q3 ± 15 min, and touchdown microbiome of airplane cabins has large flight-to-flight to end of deplaning. In addition, one sample was col- variations, it resembles the microbiome of many other lected throughout the whole flight from 10,000 ft on built environments. This work adds to the growing body ascent to 10,000 ft on descent. Flight 2 only has data of evidence characterizing the built environment. These for four time points. Following each sampling period, investigations form critical linkages between the categories the sampling cartridges were wrapped with Teflon tape, of environmental and human-associated microbial ecology, labeled, logged, and placed in a cooler with chemical and thus must meet the challenges of both areas. ice packs. Improvements in future studies should include incorpora- tion of rich metadata, such as architectural and other de- Fomite Sampling Methods sign features, human-surface contacts, and environmental exposures, as well as determination of microbe viability Prior to each flight, we prepared an ordered list of seven ran- and the mechanisms used to persist in the airplane cabin domly selected seats, of which the first two occupied seats, as environment. Identification of microbes that can be trans- confirmed by the gate agent prior to boarding, were sampled. ferred between passengers and specific fomites will be We also randomly chose a rear lavatory door (port or star- especially important in informing public health and trans- board) for sampling. portation policy. We hope to undertake an analogous study We swabbed the laboratory door handles using Bode on significantly longer, international flights, as well as at SecurSwab DNA Collector dual swabs, placing three drops key locations at departing and arriving airports. An im- of DNA- and RNA-free water on one of the two swabs, then, proved understanding of the airplane cabin microbiome swabbing in one direction within a 9 cm × 9 cm template, and and how it is affected by passengers and crew may lead finally swabbing in the perpendicular direction within the ultimately to construction of airplane cabins that maintain same template. Afterwards, we placed each swab into its se- human health. cure tube, labeled it, logged it, and placed it into a cooler on a chemical ice pack. We sampled three touch surfaces at each passenger seat— Materials and Methods the inside tray table, the outside tray table, and the seat belt buckle. Using the templates and the dual swabs, we sampled Selection of Flights the bottom corners of each side of the tray table as described above. We did not use the template to swab the seat belt Each of five round-trips, on non-stop flights, targeted a differ- buckle; rather, we swabbed the entire upper surface in one ent west coast destination to provide data representative of direction and then in the perpendicular direction. We placed transcontinental flights. We flew to San Diego, Los Angeles, each swab into its secure tube, labeled it, logged it, and placed San Francisco, and Portland, OR, between November 2012 it into a cooler on a chemical ice pack. and March 2013. 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Nucleic Acids Res 41(D1): e00022-00016 D590–D596 34. Hewitt KM, Gerba CP, Maxwell SL, Kelley ST (2012) Office space 50. Edgar RC (2013) UPARSE: highly accurate OTU sequences from bacterial abundance and diversity in three metropolitan areas. PLoS microbial amplicon reads. Nat Methods 10(10):996–998 One 7(5):e37849 51. Paulson JN, Stine OC, Bravo HC, Pop M (2013) Robust methods 35. Kelley ST, Gilbert JA (2013) Studying the microbiology of the for differential abundance analysis in marker gene surveys. Nat indoor environment. Genome Biol 14(2):202 Methods 10(12):1200–1202 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Microbial Ecology Springer Journals
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Abstract

Serving over three billion passengers annually, air travel serves as a conduit for infectious disease spread, including emerging infections and pandemics. Over two dozen cases of in-flight transmissions have been documented. To understand these risks, a characterization of the airplane cabin microbiome is necessary. Our study team collected 229 environmental samples on ten transcontinental US flights with subsequent 16S rRNA sequencing. We found that bacterial communities were largely derived from human skin and oral commensals, as well as environmental generalist bacteria. We identified clear signatures for air versus touch surface microbiome, but not for individual types of touch surfaces. We also found large flight-to-flight beta diversity variations with no distinguishing signa- tures of individual flights, rather a high between-flight diversity for all touch surfaces and particularly for air samples. There was no systematic pattern of microbial community change from pre- to post-flight. Our findings are similar to those of other recent studies of the microbiome of built environments. In summary, the airplane cabin microbiome has immense airplane to airplane variability. The vast majority of airplane-associated microbes are human commensals or non-pathogenic, and the results provide a baseline for non-crisis-level airplane microbiome conditions. . . . . Keywords Commercial airplanes Microbiome Bacteria Pandemic Respiratory infection Howard Weiss and Vicki Stover Hertzberg contributed equally to this work. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00248-018-1191-3) contains supplementary material, which is available to authorized users. * Howard Weiss School of Mathematics, The Georgia Institute of Technology, 686 weiss@gatech.edu Cherry St. NW, Atlanta, GA 30313, USA Vicki Stover Hertzberg Nell Hodgson Woodruff School of Nursing, Emory University, 1520 vhertzb@emory.edu Clifton Rd. NE, Atlanta, GA 30322, USA Chris Dupont J. Craig Venter Institute, 4120 Capricorn Lane, La Jolla, CA 92037, cdupont@jcvi.org USA Josh L. Espinoza jespinoz@jcvi.org 4 HudsonAlpha Institute for Biotechnology, 601 Genome Way, Huntsville, AL 35806, USA Shawn Levy slevy@hudsonalpha.org J. Craig Venter Institute, 9714 Medical Center Drive, Karen Nelson Rockville, MD 20850, USA knelson@jcvi.org Sharon Norris Boeing Health Services, The Boeing Company, 3156 160th Ave. NE, sharon.l.norris@boeing.com Bellevue, WA 98008-2245, USA Weiss H. et al. Introduction airplane cabin microbiome might differ considerably from those of other built environments. Another key difference is With over three billion airline passengers annually, the risk of that in an airplane cabin, it is difficult to avoid a mobile sick in-flight transmission of infectious disease is a vital global person, or one sitting in close proximity. health concern [1, 2]. Over two dozen cases of in-flight trans- In another publication [42], we describe behaviors and mission have been documented, including influenza [3–7], close contacts of all passengers and flight attendants in the measles [8, 9], meningococcal infections [10], norovirus economy cabin on ten flights of duration 4 hours or more, [11], SARS [12, 13], shigellosis [14], cholera [15], and the FlyHealthy™ Study. FlyHealthy™ has provided first de- multi-drug resistant tuberculosis [1, 16–18]. Studies of tailed understanding of infectious disease transmission oppor- SARS [12, 13] and pandemic influenza (H1N1p) [19]trans- tunities in an airplane cabin. In addition to quantifying the mission on airplanes indicate that air travel can serve as a opportunities, we wanted to understand the infectious agents conduit for the rapid spread of newly emerging infections present in an airplane cabin that might be transmitted during and pandemics. Further, some of these studies suggest that these opportunities. the movements of passengers and crew (and their close con- To this end, we identified the microbiota present on these tacts) may be an important factor in disease transmission. In flights, allowing characterization of the airplane cabin 2014, a passenger infected with Ebola flew on Frontier airlines microbiome. We hypothesized that the airplane cabin the night before being admitted to a hospital [20]. Luckily, she microbiome differs from that of other built environments did not infect anybody during that trip. due to the above-stated reasons. Since the majority of flights Despite many sensational media stories and anecdotes, e.g., were during the seasonal flu epidemic in either the originating BFlying The Filthy Skies^ [21]or BThe Gross Truth About city or the destination city, we were interested to determine if Germs and Airplanes^ [22], the true risks of in-flight trans- we could detect influenza virus in our samples. Since the mission are unknown. An essential component of risk assess- transmission opportunities we characterized in the first part ment and public health guidance is characterizing the back- of the FlyHealthy™ study were those that would allow trans- ground microbial communities present, in particular those in mission by large droplets, we were interested in sampling air the air and on common touch surfaces. Next-generation se- as well as touch surfaces (fomites). Key questions related to quencing has the potential to identify all bacteria present via differences between types of samples (air versus touch sur- their genomes, commonly called the microbiome. There have faces), pre- to post-flight changes, and changes from flight- been a few previous studies of the bacterial community in to-flight in the Bcore^ airplane cabin microbiome. cabin air [23–26], but none, to our knowledge, on airplane touch surfaces. These studies estimated total bacterial burden of culturable cells present, and applied early forms of 16S Results rRNA sequencing and bioinformatics, claiming species-level resolution. At the time of these studies, there were far fewer Airplane Cabin Bacterial Communities in the Air reference genomes with which to align. Although these were and on Touch Surfaces at the vanguard of research of the microbiome of built envi- ronments, 10 years later, current methods and protocols are Skin commensals in the family Propionibacteriaceae domi- significantly more rigorous. nate both air (~ 20% post-filtered reads) and touch surfaces The microbiome of the built environment is an active re- (~ 27% post-filtered reads). There is substantial overlap of the search area. Using a wide range of methods, authors have top 20 families in air and touch surface samples (Fig. 1). The studied the microbiomes of classrooms [27–29], homes top ten families in both air and fomites additionally contain [30–32], offices [33, 34], hospitals [35], museums [36], nurs- Enterobacteriaceae, Staphylococcaceae, Streptococcaceae, ing homes [37], stores [38], and subways [39–41]. Several of Corynebacteriaceae,and Burkholderiaceae.The environ- these studies, particularly those of classrooms and offices, mental bacteria Sphingomonadaceae is quite prevalent in the identified significant quantities of Lactobacillus on seats. air, but much less so on touch surfaces. Note that Bunclassified With the exception of the hospital microbiome, all of these family^ aggregates different families from different higher studies indicate that the main microbiome constituents, at the level taxa. The top OTUs are shown in SM Fig. 1. family level, are human commensal and environmental bacte- OTUs within the genera Propionibacterium and ria. What else could they be? Burkholderia were present in every sample and two OTUs, Airplane environments are unique to the examples listed annotated as genus Staphylococcus and Streptococcus above. Special features include very dry air, periodic high (oralis), were present in all but one sample. These four occupant densities, exposure to the microbiota of the high OTUs are contained in three phyla: Actinobacteria, atmosphere, and long periods during which occupants have Proteobacteria,and Firmicutes,and comprise the Bcore^ extremely limited mobility. Thus, one might expect that the airplane cabin microbiome. The Airplane Cabin Microbiome Fig. 1 Most prevalent families in air (left) and touch surface samples (right) by relative abundance (proportion of families) Air and Touch Surface Communities Have Discernible with the variance explained by PC1 (Fig. 2b), this indicates a Signatures, but There Are No Discernible Signatures clear signature of the air community. The complement is the of Touch Surface Types signature of the touch surface community. There is a potpourri of touch surface types in the figure, again indicating the lack of Figure 2 shows the results of the principal component analysis clear signature of individual touch surface type. There are no (PCA) on a log-scale of families of all samples over all ten statistically significant differences of alpha diversity between flights. The associated scree plot (SM Fig. 3)indicates that air and fomites as measured by any of six indices (SM Fig. 2). the vast majority (73%) of the variability is captured by first Use of an infinite Dirichlet–multinomial mixture (iDMM) principal component, about an order of magnitude more than model [43] identified four clusters (or ecostates), with ecostate that captured by PC2. We observe that the air samples are 4 containing the vast majority of air samples, though it also primarily positive on PC1 and, in fact, greater than 50, while includes many fomite samples as well (Fig. 3a). Figure 3b the touch surface samples are largely negative. When combined shows the diagnostic OTUs present in this air cluster and their Fig. 2 Scatterplot of the logs of the first two principal components, colored by sample source. a Families. b OTUs Weiss H. et al. Fig. 3 Results of iDMM analysis indicating two distinct ecostates. a Composition of the four ecostates identified in the iDMM analysis. b Most prevalent OTUs identified in the two ecostates associated with cabin air weights. Note that the weights are an essential component of within-flight (W) beta diversity, that is, each flight is already this characterization. starting with microbiomes that are likely different from other Another important question is whether bacterial communi- flights. ties change discernibly during flight? Again, Fig. 4 shows the admixture of pre- and post-flight communities in the touch surface samples. Note the linearity of these scatterplots of Discussion the logged average number of reads for OTUs from pre- to post-flight for each touch surface type. There is no discernible Toward the goal of characterizing the airplane cabin pattern of change of pre-flight to post-flight communities. microbiome, our study team flew on ten transcontinental A final key question is whether bacterial communities in US flights on which we collected 229 air and touch surface the cabin air change discernibly from flight to flight? For samples. We employed highly stringent quality control example, is there a difference between east-bound versus criteria during sampling, sample extraction, 16S rRNA west-bound flights? A principle component analysis at both gene sequencing, and the bioinformatics pipeline. The ob- the family and OTU levels shows a wide variation with no served microbial communities, when merged across sam- clustering by flight (Fig. 5). Furthermore, without exception, ples, are comprised of human commensals and common between-flight (B) beta diversity is statistically higher than environmental (water and soil) genera. We identified a The Airplane Cabin Microbiome Fig. 4 Logged average number of reads for OTUs from pre- to post-flight for each touch surface (fomite) type Bcore^ airplane cabin microbiome containing OTUs within Propionibacterium is a genus of the phylum the genera Propionibacterium, Burkholderia (glumae), Actinobacteria, comprised of commensal bacteria that live Staphylococcus,and Streptococcus (oralis). We identified on human skin and commonly implicated in acne. clear OTU signatures for the air microbiome, but not for Burkholderia glumae is a species of the phylum individual touch surface types. We found no meaningful Proteobacteria and is a soil bacterium. Staphylococcus is a differences between air and touch surfaces with respect to genus of the phylum Firmicutes that is found on the skin alpha diversity measures. Finally, we found no systematic and mucus membranes of humans. Most species of pattern of change from pre- to post-flight. Staphylococcus are harmless. Streptococcus oralis, a species We also found large flight-to-flight variations with no of the phylum Firmicutes, is normally found in the oral cav- distinguishing signatures of individual flights. This would ities of humans. These constituents of the core airplane cabin suggest that each flight starts with a different microbiome microbiome are usually harmless to humans unless an unusual from other flights, which would greatly hinder pre-and opportunity for infection is present, such as a weakened im- post-flight microbiome comparisons (e.g., Fig. 4)that ag- mune system, an altered gut microbiome, or a breach in the gregate samples between flights. A methodological impli- integumentary system. cation is that aggregating communities between flights for While airplane cabins are certainly examples of built statistical analyses is problematic. Instead, sample repli- environments, there are unique features. These include cation must be derived from within a flight in order to very dry air, periodic high occupant densities, exposure determine how passengers alter the airplane cabin to the microbiota of the high atmosphere, long periods microbiome. Every plane being different in terms of its during which occupants have extremely limited mobility, microbiome suggests that each retains aspects of its his- and it is difficult to avoid a mobile sick person or one torical living microbiome, that is, the passengers. The de- sitting in close proximity. Half of the cabin air is recycled velopment of a cleaning routine that erases much of this after passing through a bank of HEPA filters, and the inherited microbiome could be a powerful preventative other half is taken from the outside. Furthermore, the air- measure against the spread of disease. line’s cabin cleaning policy is to disinfect all hard surfaces Weiss H. et al. ab Fig. 5 Beta diversity of samples. Scatterplot of the first two principal components of the beta diversity analysis, for a OTU-level and b family-level abundance, based on a Bray-Curtis distance. c Distributions of Bray-Curtis distances for different touch surface types, within and between flights whenever the plane Bovernights,^ and all touch surface species, Propionibacterium acnes, a common skin commen- samples were taken from hard surfaces. Different airlines sal, was excluded from discovery in the New York City sub- have different cabin disinfection protocols and supervise way microbiome study. their cabin cleaning staff in different ways. Although different primers and sequencing techniques Despite the uniqueness of the airplane cabin as a built en- were used, the core microbiome identified in the Boston sub- vironment, our findings are surprisingly consistent with other way system study has significant overlap with airplane cabins recent studies of the microbiome of built environments. This [41]. Corynebacteriaceae, a skin commensal, appeared in consistency is reassuring in light of frequent sensationalistic nearly every subway sample, and while we do not include it media stories about dangerous germs found on airplanes. For in the airplane cabin core list, it was present in all but ten of this reason, there is no more risk from 4 to 5 hours spent in an our samples. A study of the microbiome of the International airplane cabin than 4–5 hours spent in an office, all other Space Station, the only other airborne built environment that exposures being the same. Our microbiome characterization has been studied, led to the same conclusion [44], as did two also provides a baseline for non-crisis level airplane studies of office spaces [33, 34]. microbiome conditions. A number of previous studies identified large amounts of It is not possible to make quantitative comparisons to other Lactobacillus,but Lactobacillaceae did not appear in our list studies which used different primers and different sequencing of 20 most prevalent families in our touch surface samples. methods and technologies. For example, the genus Lactobacillus is commonly found in vaginal microbiota, sug- Propionibacterium is a core component of the airplane cabin gesting that it should be found on surfaces where women sit. microbiome, but by choice of primers, the most common Many other studies of the built environment have sampled The Airplane Cabin Microbiome seats, and thus, it is not surprising to find Lactobacilli present Air Sampling Methods in those environments. We did not sample from the seat fabric where passengers sat; thus, the absence of Lactobacilli in the The two air sampling pumps used were model SKC 20 most prevalent families is to be expected. AirChek XR5000. These were located in a seat at the Airplanes fly through clouds. The narrow-body twin-en- back of the economy class cabin. Both pumps sampled gine models on which we flew use about 50% bleed at 3.5 liters per second, the NIOSH protocol for station- (outside) air to refresh the cabin air throughout the flight. ary sampling and approximately the normal breathing A study of the microbiome of clouds finds some members rate of adults. of the Propionibacterium and Burkholderia families in their Just prior to each sampling, each pump was calibrated core, as well as Streptococcus in some samples [45]. A using a MesaLab Defender Calibrator. Air samples of 30- more recent study of cloud water found Burkholderia, mindurationwere collected onboardtheaircraft during Staphylococcus,and Streptococcus in samples [46]. five distinct sampling intervals. Once the pilot an- Interesting future research would be to ascertain the nounced the flight time, we calculated the quarter-way influence of the cloud microbiome on the airplane cabin point, halfway point, and three quart-way point. Thus, microbiome. the five sampling periods were pre-boarding and boarding, In conclusion, our study found that although the Q1 ± 15 min, Q2 ± 15 min, Q3 ± 15 min, and touchdown microbiome of airplane cabins has large flight-to-flight to end of deplaning. In addition, one sample was col- variations, it resembles the microbiome of many other lected throughout the whole flight from 10,000 ft on built environments. This work adds to the growing body ascent to 10,000 ft on descent. Flight 2 only has data of evidence characterizing the built environment. These for four time points. Following each sampling period, investigations form critical linkages between the categories the sampling cartridges were wrapped with Teflon tape, of environmental and human-associated microbial ecology, labeled, logged, and placed in a cooler with chemical and thus must meet the challenges of both areas. ice packs. Improvements in future studies should include incorpora- tion of rich metadata, such as architectural and other de- Fomite Sampling Methods sign features, human-surface contacts, and environmental exposures, as well as determination of microbe viability Prior to each flight, we prepared an ordered list of seven ran- and the mechanisms used to persist in the airplane cabin domly selected seats, of which the first two occupied seats, as environment. Identification of microbes that can be trans- confirmed by the gate agent prior to boarding, were sampled. ferred between passengers and specific fomites will be We also randomly chose a rear lavatory door (port or star- especially important in informing public health and trans- board) for sampling. portation policy. We hope to undertake an analogous study We swabbed the laboratory door handles using Bode on significantly longer, international flights, as well as at SecurSwab DNA Collector dual swabs, placing three drops key locations at departing and arriving airports. An im- of DNA- and RNA-free water on one of the two swabs, then, proved understanding of the airplane cabin microbiome swabbing in one direction within a 9 cm × 9 cm template, and and how it is affected by passengers and crew may lead finally swabbing in the perpendicular direction within the ultimately to construction of airplane cabins that maintain same template. Afterwards, we placed each swab into its se- human health. cure tube, labeled it, logged it, and placed it into a cooler on a chemical ice pack. We sampled three touch surfaces at each passenger seat— Materials and Methods the inside tray table, the outside tray table, and the seat belt buckle. Using the templates and the dual swabs, we sampled Selection of Flights the bottom corners of each side of the tray table as described above. We did not use the template to swab the seat belt Each of five round-trips, on non-stop flights, targeted a differ- buckle; rather, we swabbed the entire upper surface in one ent west coast destination to provide data representative of direction and then in the perpendicular direction. We placed transcontinental flights. We flew to San Diego, Los Angeles, each swab into its secure tube, labeled it, logged it, and placed San Francisco, and Portland, OR, between November 2012 it into a cooler on a chemical ice pack. and March 2013. We flew to Seattle, WA, in May 2013. We Material from the two swabs was combined in Tris Buffer flew on narrow-body twin-engine aircraft, with all but one and homogenized per kit instructions. The air filters were sim- flight on a specific model. Our movement data are represen- ilarly prepared. DNA isolations were performed using the tative of passenger and crew movements in a single aisle Power Soil kit (MoBio Laboratories, Carlsbad, CA) according B3+3^ economy cabin configuration. to the manufacturer’s directions with an elution volume of Weiss H. et al. 50 μl. The 16S rRNA gene was amplified for sequencing References using the 515F primer (5′ GTGCCAGCMGCCGCGGTAA 3′) and 806R primer (5′ GGACTACHVGGGTWTCTAAT 1. Mangili A, Gendreau MA (2005) Transmission of infectious diseases during commercial air travel. Lancet 365(9463):989– 3′)[47]. 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Microbial EcologySpringer Journals

Published: Jun 6, 2018

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