Review Article | Published:

Microbiology of the built environment

Nature Reviews Microbiologyvolume 16pages661670 (2018) | Download Citation


The built environment comprises all structures built by humans, including our homes, workplaces, schools and vehicles. As in any ecosystem on Earth, microorganisms have been found in every part of the built environment that has been studied. They exist in the air, on surfaces and on building materials, usually dispersed by humans, animals and outdoor sources. Those microbial communities and their metabolites have been implied to cause (or exacerbate) and prevent (or mitigate) human disease. In this Review, we outline the history of the field of microbiology of the built environment and discuss recent insights that have been gained into microbial ecology, adaptation and evolution of this ecosystem. Finally, we consider the implications of this research, specifically, how it is changing the types of materials we use in buildings and how our built environments affect human health.


The built environment encompasses all manufactured structures, including buildings, transportation systems and other physical surroundings constructed by humans1. These are the spaces where we spend most of our time2, and they harbour unique microbial assemblages that are unlike most microbial communities found in other environments on Earth. For the most part, we design, build and operate our buildings to be inhospitable for microbial life, which often results in selective pressures that enable only a minority of dispersed microorganisms to survive3. We have continually manipulated our living and working spaces to reduce and remove aspects that are uncomfortable, unsightly, disease-promoting or inconvenient, thereby inadvertently shaping the ecology and evolution of the microorganisms that colonize those spaces. We can find many types of microorganism in built spaces, but many aspects of the composition of those complex microbial communities, their ecological role or their impact on human health remain unknown. Are they biologically active and alive? Can they promote disease, or do they have a role in protecting us from illness? Are they actively adapting to our attempts to control them? Can we harness beneficial microbial organisms while simultaneously eradicating harmful ones? How can we further optimize our built environments by taking into consideration the existing microbial communities?

In this Review, we discuss the history of the field of microbiology of the built environment and explore our current understanding of the ecology and evolution of this microbiome. The surprisingly long history of research in this field dates back hundreds of years and includes visual observations, microscopy and application of culture-based techniques (Box 1) and more recent advances enabled by rapid growth in the application of culture-independent techniques that have addressed new fundamental evolutionary and ecological questions (Box 2). We review what these studies have taught us about the factors that shape the metabolism, ecology and evolution of bacteria, viruses, fungi and archaea in our built environments. We also consider the implications of this research, specifically, how it is changing the types of materials we use in buildings, how we clean and manage our spaces and how we understand human health in relation to our built environments. Although many studies have contributed to cataloguing microbial species that can be found in built environments, there has been a recent shift towards investigating the translational potential, as well as creating more fundamental knowledge on how microorganisms biochemically adapt to the resources available in human-made spaces and the impact on their evolution.

Ecology of the built environment

Although ribosomal RNA (rRNA) amplicon sequencing of cultured isolates became common in the 1990s, it was not until 2004 that the first sequence-based bacterial community-wide survey of an indoor environment was performed4. This study comprised a 16S rRNA amplicon survey of the bacterial biofilms associated with the soap scum film on shower curtains. The complex communities that were identified included many alphaproteobacterial genera, such as Sphingomonas and Methylobacterium. Although these surveys were limited in terms of what could be inferred about the microbiome, the authors interpreted the presence of these bacteria as potentially contributing to the pink coloration of many of the biofilms. They also highlighted the potential pathogenicity of those bacteria, as closely related strains have been shown to be opportunistic pathogens. Dozens of studies over the following decade continued to characterize patterns, associations and drivers of microbial community structures in various built environments, elucidating the most abundant taxa and investigating the similarities and differences of the microbial communities between spaces. Many of these studies have demonstrated that the majority of bacterial microorganisms found on surfaces seem to originate from human skin and oral sites. By contrast, built environments that are situated in more biodiverse environments (for example, farms or rural sites) have a greater number of organisms that originate from that environment, such as animal-associated microorganisms5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29 (Fig. 1). A number of studies have quantified the absolute biomass of bacteria and fungi in built environment samples using molecular methods30,31,32,33 and chemical surrogates, including ergosterol34, glucans, hydroxy fatty acids and muramic acid35. Using DNA-based methods and leveraging a mass-balance modelling approach, one study estimated the average human emission rates of total particles to be 31 mg per hour, with approximately 37 million bacterial genome copies and approximately 7 million fungal genome copies per hour being dispersed from a human30. There have also been recent promising attempts to merge relative taxonomic abundance data with absolute abundance data from quantitative PCR36,37,38. Much less attention has been paid to viruses that may be present in built environment samples, in large part owing to the methodological challenges associated with analysing samples with extremely low viral biomass39,40.

Fig. 1: Bacterial diversity of the built environment.
Fig. 1

Cataloguing the bacterial diversity of hospitals, public transport and rural homes has revealed the abundance of bacteria associated with human skin and oral sites in built spaces, such as common potential human pathogens Staphylococcus spp. and Streptococcus spp., as well as commensals of the human microbiota, including Corynebacterium spp. and Propionibacterium spp. This suggests that humans are the major source of microorganisms found in the built environment. However, the microbial communities commonly associated with rural homes, for example, the homes of Amish farmers72, also had an increased abundance of Bartonella spp., which have been associated with many animals and are potential opportunistic human pathogens. In addition, Enterococcus spp. and Ruminococcus spp., which are common gut-associated microorganisms in humans and animals, were also detected in rural homes. Hospital environments are associated with human-associated microorganisms, including common potential pathogens such as Pseudomonas spp., Acinetobacter spp., Staphylococcus spp. and Streptococcus spp., as well as common commensals such as Anaerococcus spp., Prevotella spp., Corynebacterium spp. and Neisseria spp.

To advance beyond characterizing microbial taxonomic affiliation, it was necessary to sequence the genetic information for each microbiome (that is, metagenomics). In 2008, a study that applied shotgun metagenomic sequencing to indoor air sampled from two shopping centres in Singapore41 found that the microbiota in the air comprised primarily bacteria that originate from indoor sources, such as occupants, and included potential opportunistic pathogens, including species of Brucella, Bordetella and Mycobacterium. A few years later, another study applied shotgun metagenomics sequencing to indoor and outdoor air samples from a modern high-rise building in New York City, as well as a hospital medical centre, a family home and a pier in San Diego42. The study described the bacterial and fungal taxonomic composition and functional gene diversity in these samples, revealing that indoor air often contained human and fungal associated DNA, whereas external air samples contained a more diverse mix of DNA fragments, including DNA fragments from mice, fish, plants and insects. The indoor air was dominated by genera such as Pseudomonas, which are commonly associated with human skin. Interestingly, although the functional gene abundances were mostly consistent across all environments (both indoor and outdoor), outdoor air in New York City was enriched for β-lactamases and tetracycline resistance genes.

Other recent advances in understanding the microbial ecology of the built environment include efforts to further characterize the microorganisms that were identified to colonize those spaces. One study43 used 16S rDNA amplicon sequencing of reverse transcribed RNA, a technique that attempts to characterize the microbial organisms that are actively transcribing in the environment. However, there is substantial evidence that, unlike most RNA, the RNA transcript of the 16S rDNA gene is very stable in the environment, and as such, it is not a good indicator of viability and metabolic activity44. The viability of microorganisms that exist in indoor environments is an area of great interest, with decades of research suggesting extensive viability of bacteria and fungi (Box 1). However, many studies indicate that most DNA detected using recent molecular tools does not represent viable microorganisms3,5,45. In contrast to these findings, a study reported that some of the organisms are alive, as bacterial and fungal growth were observed when water became available on household surfaces43. Most efforts to determine microbial viability have used axenic isolation on a limited range of substrates in vitro, limiting the detection of viable organisms as well as reflecting a bias towards organisms that may be able to grow in vitro but will not contribute actively in vivo. Advances in techniques to visualize microorganisms in situ, to determine their viability and activity, and to apply computational models of microbial metabolism are now being used to analyse samples from the built environment, and such approaches may soon lead to novel findings regarding the metabolic associations between organisms that support growth or competition on surfaces of those environments. Applying these tools to a biologically active event, such as material wetting, could be valuable in identifying the mechanisms by which moisture facilitates mould growth; these fungi can produce microbial volatile organic compounds (MVOCs) that influence human health outcomes46. We expect that fungi will spontaneously grow when wetted; however, it is equally likely that their growth rate and metabolic activity are influenced by co-occurring species of fungi and bacteria, or even by archaea and viruses. Catalogues of indoor microbial genomic diversity can facilitate building these models, which will also benefit substantially from metatranscriptomic and metaproteomic data47. These data, in combination with metabolomics (which can be used to validate metabolite predictions), may help to identify the fundamental components that underlie the ecological characteristics of the built environment and also aid the identification of small molecules or elements that could be used to intervene in the microbial emergent properties that have negative health consequences.

Interactions between microorganisms and hosts

Humans and other animal occupants of built spaces have extensive microbial interactions with the air and surfaces. These interactions have traditionally been examined only with regard to the transmission of potential pathogens. For example, bacterial pathogens such as Bacillus anthracis48, Legionella pneumophila49 and Mycobacterium tuberculosis50; fungal pathogens such as Cryptococcus neoformans51, Histoplasma capsulatum52 and Aspergillus fumigatus53; and pathogenic viruses such as rhinovirus54,55,56 and influenza virus57,58,59 can be transmitted by direct inhalation. Other pathogens, such as Clostridium difficile60, Staphylococcus aureus61, Pseudomonas aeruginosa61, Pseudomonas putida61 and Enterococcus faecalis61, as well as norovirus61,62 and influenza virus57,63, can be transmitted through surface contact, whereby they are transferred to the mucous membranes by hand-to-face contact (Fig. 2). These same transmission routes also occur for usually benign microorganisms, although they have been investigated in much less mechanistic detail than possible human pathogens.

Fig. 2: Routes of microbial transmission.
Fig. 2

Microbial transmission between human occupants and the built environment is reciprocal. For the majority of the history of this field, the emphasis has been on understanding the potential for human pathogens to be transmitted via air or surfaces in the built environment. For example, bacterial pathogens such as Bacillus anthracis48, Legionella pneumophila49 and Mycobacterium tuberculosis50; fungal pathogens such as Cryptococcus neoformans51, Histoplasma capsulatum52 and Aspergillus fumigatus53; and pathogenic viruses such as rhinovirus54,55,56 and influenza virus57,58,59, can be transmitted by direct inhalation. Other pathogens, such as Clostridium difficile60, Staphylococcus aureus61, Pseudomonas aeruginosa61, Pseudomonas putida61 and Enterococcus faecalis61, as well as norovirus61,62 and influenza virus57,63, can be transmitted through surface contact. These same transmission routes also occur for usually benign microorganisms, although they have been investigated in much less mechanistic detail than possible human pathogens. Moreover, human-associated microorganisms are also being transmitted to the built environment.

The first study to examine the correlative relationships between the human microbiome and the microbiome of the built environment focused on home environments and mapped the sharing of bacteria between occupants and their homes12. This investigation demonstrated that the majority of bacteria associated with the surfaces had a statistically significant probability of having originated from the occupants of that home. Also, owing to the longitudinal design of the study, it was possible to correlate the occurrence of bacteria between occupants and surfaces and thus predict the ‘movement’ of organisms. For example, genotypes reassembled from metagenomic data, including uncultivated taxa assigned to Enterobacteriaceae, Acinetobacter and bacteriophages, which often comprised genes associated with pathogenicity and antibiotic resistance, could be identified on the hand of one of the occupants, and subsequently on home surfaces, and then on the hand of another occupant12.

Subsequent human and indoor surface co-sampling studies have demonstrated that these patterns are not always conserved. For example, although the airborne microbiome inside homes was shown to be dominated by human-associated bacteria that were specific to each household, these microbiota did not resemble the microbiome of the occupants’ skin any more than the skin microbiome from occupants of other households64. This confirms other studies that have demonstrated that, although occupant density influences the density of microbial particles in indoor air6,13,65, outdoor air-associated microorganisms seem to comprise a greater proportion of the indoor air microbiome, particularly in well-ventilated spaces64,66. It is likely that the majority of microbial biomass dispersal from humans to the built environment occurs via skin-to-surface contact and/or direct shedding of larger biological particles. In support of this, a longitudinal study of surface-associated microbiota in a hospital, which comprised 365 consecutive days of observation in multiple patient rooms and staff spaces, and which included the staff- and patient-associated microbiota, highlighted the specificity of the surface-associated microbiota to the occupant of each room67. Although, maybe not surprisingly, the microbiota of an individual patient room initially resembled the microbiota of the previous occupant, within 24 hours of occupation, the surface microbiota originated from the new occupant entirely67. Patients also seemed to be a greater recipient of microorganisms from staff members than staff members were from patients. These results suggest a constant transfer of microorganisms within this environment, and although the majority of these organisms may not be active or even alive, it is still possible that this exchange could have health implications, such as from exposure to allergenic elements of dead organisms.

In fact, new understanding of the microbiology of the built environment and human health has shifted our perspective of microorganisms from a purely negative role (that is, being pathogenic or infectious) to a potentially positive role (that is, protective or preventive). Throughout history, most efforts to determine the influence of the indoor microbiome on health have focused primarily on the negative impact of fungi and other allergens on respiratory and skin diseases68. People inhale a considerable volume of indoor air daily, on average ~16,000 litres for adults69. Therefore, it stands to reason that the interactions between humans and buildings that facilitate microbial exposure will have a profound impact on human health.

Accepting that we are regularly exposed to ubiquitous microbiota necessitates research initiatives to elucidate the mechanism by which this exposure can influence health and disease. The concept of ‘old friends’ or the ‘hygiene hypothesis’, which suggests that improved hygiene is possibly linked to the rise in autoimmune conditions, is adaptable to this concept of beneficial microbial exposure70. For example, exposure to a complex microbial community in house dust has been inversely associated with the likelihood of developing asthma71. In another study, children exposed to household dust from homes immediately adjacent to a farming environment and who were actively working on the farm, presented with a statistically significant reduction in the risk of developing asthma compared with children who were not exposed to farming environments72. To investigate the biological underpinnings of that association, mice were exposed to house dust from the respective homes and then provided an allergic challenge. Farm home dust was protective against eosinophilia (asthma-associated inflammation), whereas the non-farm home dust was not protective. The association between this phenotype and exposure to particular species of bacteria (for example, taxa associated with mammalian gut-associated phyla Bacteroidetes and Firmicutes were more abundant in the farm-house dust) suggests that certain sources of bacteria may be better than others at offering protection73,74. Animal-associated microorganisms seem to offer some of the most effective protection against the development of asthma; for example, exposure of sensitized mice to dog stool-derived Lactobacillus johnsonii was associated with protection of these animal models against allergen challenge75.

Microbial metabolism indoors

Besides direct infection, one of the primary concerns for the impact of microbial exposures in the built environment on human health is the influence of microbial metabolism. Although evidence for the associations between indoor dampness, mould odour and visible mould, and disease states (including allergies and asthma76,77,78) exists, the links between the microbial community composition in the built environment, the abundance of their members, their metabolites and disease remain elusive. Bacterial and fungal toxins, allergenic components of the cellular wall and MVOCs have all been implicated in observed associations between indoor dampness and human health effects, but the evidence remains limited and inconclusive79,80. MVOCs are chemicals of low molecular mass, high vapour pressure and low water solubility, and as such are easily inhaled or can travel across the skin, and hence interact with human metabolic, immune and endocrine processes. Some studies have shown that MVOCs are enriched in damp buildings81, and MVOCs have been associated with temperature and the type of building material, which functions as a nutritional and structural substrate for microbial growth82. However, the technical resolution of metabolomics has greatly improved in recent years, and prior confusion about whether MVOCs originate from microorganisms, plants or building material82,83 is now being resolved. For example, a recent study under controlled laboratory conditions demonstrated the first attempt to combine advanced amplicon sequencing approaches with metabolomics to analyse samples from the built environment and showed that predicted microbial metabolites in periodically wetted environments correlate with changes in the microbial community structure and composition43.

Most of our knowledge of microbial metabolism in the built environment comes from studies of indoor microbial isolates in vitro. However, a number of studies have attempted to determine the influence of moisture and other environmental variables on microbial metabolic activity. Studies of house dust have provided evidence of the moisture-dependent metabolic activity of the microorganisms in this particulate material84,85. Dust is a rich, heterogeneous mixture of materials, providing plentiful substrate for microbial growth. When exposed to moisture, the resulting germination of fungal and bacterial spores or dormant cells leads to an increase of metabolic products, which can include chlorinated hydrocarbons, amines, terpenes, alcohols, aldehydes and ketones, as well as sulfuric and aromatic compounds86 (Fig. 3). However, metabolic activity is dependent on the amount of available water, whereby a relative humidity of 84–86% will cause an 8-day lag in CO2 production (which is evidence of microbial respiration) compared with a relative humidity of 96–98%84. In a study of 40 homes with evidence of mould damage and 44 homes where mould damage was not found, most MVOCs could not be linked to the presence of mould87. The exceptions were 2-methyl-1-butanol (black truffle smell) and 1-octen-3-ol (so-called mushroom alcohol), which were weakly enriched in the presence of mould. It is possible that large variability in local environmental conditions, including local weather, building materials, humidity, temperature and household activities, could have contributed to the lack of statistical power in this study87. Another potential explanation is that variation in the species or strain of mould, and maybe in the co-associating bacterial organisms, could have affected the metabolic activity of these mould species, as well as the quantity of MVOCs in the air. Molecular detectors (such as mass spectrometers) could be used to detect the presence of fungus by association with high levels of fungal secondary metabolites in the absence of visible growth88. However, these approaches remain limited with little practical success thus far, as real life applications involve a large number of confounding factors and low concentrations near the detection limits of many analytical methods89. In most environments, short-chain fatty acids and medium-chain fatty acids were mainly detected as persistent MVOCs on periodically wetted surfaces, whereas amides, pyridine, dimethylsulfide, ethanethiol and benzothiazole were mostly detected in the kitchen environment, and sulfoxides, cyclic amides and other acids and esters mainly in the bathroom43. Interestingly, metabolic derivatives of phenyl acetic acid have been found on kitchen surfaces; it has been reported that this compound is produced by skin-associated bacteria, which supports the notion that those bacteria, now colonizing the built environment, exhibit metabolic activity43.

Fig. 3: Effects of the microbial metabolic products on human health.
Fig. 3

a,b | Indoor air and surfaces are associated with dust and microbial chemical products. Increased relative humidity in the environment results in an increase in the amount of microbial metabolites in dust and on surfaces. Indoor dampness and mouldy conditions (for example, visible mould and mould odour) have been associated with many different disease states, but associations between the composition and concentration of microorganisms and their metabolites in the built environment and disease remain elusive168 (part a). When exposed to moisture, the resulting germination of fungal and bacterial spores or dormant cells leads to an increase in metabolic products, which can include chlorinated hydrocarbons, amines, terpenes, alcohols, aldehydes, ketones, and sulfuric and aromatic compounds (part b).

Whether bacterial and fungal metabolites actually metabolically or physically interact remains a key question. Fungal–bacterial interactions have important roles in plant productivity and human disease, and thus there has been substantial research on how soil-associated and human-associated fungi interact with bacteria90. The potential for bacterial–fungal relationships, especially in biofilms, to alter the phenotypic characteristics of the isolated taxa makes these relationships so important for the built environment91. Fungal growth is a great concern in the modern home, owing in part to the impact of inhaling spores and the MVOCs released during active growth on human health. It has been suggested that bacteria can alter the virulence of clinically relevant fungal infections. For example, Enterococcus faecalis has been shown to inhibit hyphal formation and hence the virulence of Candida albicans; in fact, this relationship is bidirectional, whereby C. albicans can suppress the virulence of E. faecalis92. It was shown that inhibition of hyphal formation, biofilm formation and virulence of C. albicans is mediated by the E. faecalis bacteriocin EntV, which could represent a valuable clinical antifungal agent93. It is possible that the same mechanism could control the growth and lifestyle traits of indoor fungal and bacterial biofilms.

Culture-dependent and culture-independent studies suggest that the most common microorganisms associated with indoor surfaces belong to the fungal genera Cladosporium, Penicillium, Aspergillus and Stachybotrys (in damp buildings) and the bacterial taxa Corynebacterium, Staphylococcus, Lactobacillus, Streptococcus, Enterobacteriaceae, Acinetobacter, Sphingomonas, Mycobacterium, Methylobacterium, Bacillus and Pseudomonas94,95. However, the growth potential of these organisms is determined by the water activity (a measure of water availability in a material), chemical composition, pH and the physical properties of surfaces. Keeping building materials dry (that is, with water activity below 0.7) completely limits microbial growth for most known organisms on most materials96. Water activities above 0.7 are typically not observed in most built environments unless there are active moisture sources, such as water leakage or water vapour diffusion97. For example, a recent study of microbial communities on office surfaces in three climate zones in the Unites States reported water activities ranging from ~0.1 to ~0.7 (ref.14). Temperature affects both water activity and microbial growth, and although warmer temperatures probably promote more rapid growth, many psychrophilic organisms, especially bacteria, can still flourish at lower temperatures. The surface material is also very important; although all surfaces can function as a physical substrate, the chemical composition of the material provides a food source for the colonizing microorganisms and potentially selects for different species. Studies have demonstrated that cellulose-based surface materials, such as, for example, wood, can stimulate microbial growth more rapidly than inorganic materials such as gypsum, mortar and concrete98,99. pH is also important, as many metabolic processes are more energetically favourable at neutral pH; therefore, materials with an alkaline or acid pH can retard microbial growth. Moreover, the physical composition of the surface material will affect which organisms can access the surface. As in many decomposition processes, the physical and chemical disruption of a surface material by a fungus may be essential for bacterial colonization or growth, as the surface material might become more accessible for bacterial degraders. Even the surface roughness, porosity and its position in the environment (for example, the ceiling or the floor) can influence the dynamics of microbial colonization and growth14. However, how these variables influence microbial metabolism and fungal–bacterial interactions remains to be elucidated and is an active area of research.

Microbial adaptation

The physical and chemical properties of buildings and the surface materials encountered by microorganisms in the built environment are for the most part very different compared with materials and surfaces in natural environments. Even wooden surfaces are often treated with chemicals to preserve them. Gypsum, fibreboard, drywall, synthetic carpets and surface lacquers, as well as a myriad of other unique hydrocarbons and polymers, create ecosystems unlike any other. The diversity of novel niches provides unique selection pressures that could shape microbial evolution, especially when one considers the short generation times of many microorganisms100. Even before the advent of genomic sequencing, culture-based studies routinely demonstrated that different surface chemistries and physical structures promote the growth of different organisms95. Even early studies using genomic sequencing technologies found that carbon chemistry can drive microbial evolution on synthetic surfaces. For example, shower curtains are mainly colonized by bacterial taxa associated with Sphingomonas and Methylobacterium, which are known to be readily adaptable to the availability of multiple chain length carbon compounds4,101. In addition, physical surfaces in buildings have been shown to be primary sites for bacterial adhesion and biofilm formation. For example, biofilm adhesion and/or formation on catheter tubing combined with antibiotic selection pressure resulting from the administration of antibiotics to a patient can lead to the acquisition of antibiotic resistance genes within these material surface-associated biofilms102,103.

Using whole-genome and metagenomics sequencing, it is possible to reconstruct last common ancestors and explore the selective pressures that shape functional attributes necessary for adaptation and that are of relevance to human health104. Hospital environment-associated bacterial genotypes seem to acquire antibiotic resistance and virulence genes over time, although this trend was not statistically significantly associated with antibiotic administration67. This suggests that microorganisms that have survived antibiotic treatment and that are being released from patients into the hospital environment, which is very clean, dry and cold compared with the host, are likely to be experiencing environmental stress that selects for cells in the population with the characteristics necessary for survival or may trigger horizontal gene transfer events that facilitate the acquisition of new genes and hence new phenotypes. A similar impact on microbial phenotype has been observed in the International Space Station105,106,107 and in clean-rooms used for space craft manufacturing108. This suggests a mostly unexplored influence of the built environment on microbial stress with potential health implications for humans as a result of the evolution of harmless microorganisms into opportunistic pathogens.

Implications and translation

The finding that the ecology, metabolism and transmission pathways of microbial communities in indoor environments are dynamic has led to renewed interest in refining how we practise health care, how we design, operate and build buildings, and how we shape our built environments. Examples include identifying the types and sources of microorganisms in homes that influence the development of asthma in children, changing surface materials to reduce the transmission of pathogenic viruses and bacteria, controlling water activity to reduce mould growth and changing ventilation rates or filtration requirements to reduce the accumulation of bacteria that are being dispersed from humans in work spaces and homes (Fig. 4). Although there is substantial evidence that some bacteria can influence the onset of asthma, we still do not know whether it would be possible to intervene in homes of at-risk children with microbial probiotics (that is, the introduction of health-promoting microorganisms) to reduce the risk, although an ongoing study in Finland called PROBIOM is attempting to determine whether the introduction of microorganisms associated with forest soil could influence human health outcomes. Similarly, although large-scale efforts have shown that it is possible to map potential transmission routes for microorganisms in hospitals, it is not yet possible to determine how the ubiquitous distribution of bacteria in the hospital influences health outcomes, through either infections or immune activation. Research is also focused on investigating whether the microbiome left behind at a crime scene by a perpetrator can be used as trace evidence in forensic cases109,110; however, we are many decades away from being able to apply this technology to create support for a legal case.

Fig. 4: Shaping the indoor microbiome.
Fig. 4

Sensors that can detect the indoor microbiome will be valuable in increasing our understanding of which organisms or microbial antigens are associated with disease onset or prevention. Practices that promote possible health-promoting microbial exposure while minimizing the influence of disease-associated metabolites and organisms include, but are not limited to, increasing the proportion of outdoor air in the indoor environment through increased ventilation, changing the type of building material used in construction and reducing moisture. Exposure to pets and plants presents a relatively simple way to increase microbial diversity in indoor environments. Controlled exposure to farming environments has been shown to be effective, but implementation will require more insights into the underlying mechanisms. These approaches represent a possible way to advance human health outcomes based on understanding microbial colonization, activity and host interaction in buildings.

The largest potential translational impact from the field of the indoor microbiome may be the idea of manipulating the building design and material choices to influence human health outcomes6,68,111,112. The primary route for manipulating human health is to alter human exposure to the environmental microbiome and metabolome. Importantly, this is not proposed to be a direct way of manipulating the human microbiome but a subtler approach focused on influencing the human immune system. As studies have shown that neutrophil ageing can influence the onset of inflammatory disorders72,113, it is paramount that we understand how to target the stimulation of immune responses leading to positive health outcomes. This includes understanding the timing and dosage of such exposures, as well as what components are required (for example, exposures to various microorganisms, antigens and chemicals)114. While we now understand that pets75, occupant density115, geography14, moisture, building materials116 and building operation117 are associated with the structure of indoor microbial communities, and likely with human health outcomes, we are still unable to accurately manipulate these parameters to fine-tune exposures and promote human health. As a result, the default approach is to ensure the indoor environment is as hostile to microbial life as possible to prevent exposure to harmful microorganisms (Fig. 2). However, we simply do not yet know what the right balance is between too little and too much microbial exposure.

There is an immediate need for the development of accurate real-time microbial sensors to detect exposures for individuals within the built environment. Developing sensors that can detect the airborne microbiome will be especially valuable in yielding a more refined understanding of which organisms, functions or microbial antigens are associated with disease onset or prevention. Large-scale studies to provide the statistical power to assess these exposures at the level of resolution needed to make these associations are lacking. Regular longitudinal detection and analysis of the microbiome and metabolome of the built environment will help architects and building operators to understand the impact of their decisions; meanwhile, personal environmental sensors will help people who regularly move between different indoor settings to track their exposure and correlate it with health and disease metrics. In combination, these new data streams would have a profound impact on the future of our indoor lives.


The microbiome of the built environment is still very much a nascent field. This is despite considerable investment in research from both private foundations and federal programmes across the globe. Owing to the complexity of this environment, it has been profoundly difficult to determine the microbial characteristics that directly or indirectly influence human health and disease. However, there is substantial and compelling evidence that microbial exposures influence the onset and exacerbation of disease. In addition, evidence that microbial exposure can have beneficial health impacts has sparked interest in how to manipulate indoor environments to refine such exposures. We have spent the past few hundred years attempting to make the built environment as hostile to microbial life as possible to prevent microbial infections. However, there is also a need for balance to stimulate the human immune system and possibly to prevent the onset of non-communicable disease. To achieve this, continued investment in this field is essential to understand the ecology and evolution of indoor microorganisms.

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PROBIOM — Towards a health-promoting indoor microbiome:


  1. 1.

    Martin, L. J. et al. Evolution of the indoor biome. Trends Ecol. Evol. 30, 223–232 (2015).

  2. 2.

    Klepeis, N. E. et al. The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants. J. Expo. Anal. Environ. Epidemiol. 11, 231–252 (2001).

  3. 3.

    Gibbons, S. M. The built environment is a microbial wasteland. mSystems 1, e00033 (2016).

  4. 4.

    Kelley, S. T., Theisen, U., Angenent, L. T., St Amand, A. & Pace, N. R. Molecular analysis of shower curtain biofilm microbes. Appl. Environ. Microbiol. 70, 4187–4192 (2004). This is the first study to apply molecular amplicon sequencing approaches to the actual microbiome of the built environment.

  5. 5.

    Gibbons, S. M. et al. Ecological succession and viability of human-associated microbiota on restroom surfaces. Appl. Environ. Microbiol. 81, 765–773 (2015).

  6. 6.

    Kembel, S. W. et al. Architectural design influences the diversity and structure of the built environment microbiome. ISME J. 6, 1469–1479 (2012).

  7. 7.

    Adams, R. I., Miletto, M., Taylor, J. W. & Bruns, T. D. Dispersal in microbes: fungi in indoor air are dominated by outdoor air and show dispersal limitation at short distances. ISME J. 7, 1262–1273 (2013).

  8. 8.

    Flores, G. E. et al. Diversity, distribution and sources of bacteria in residential kitchens: bacterial diversity of residential kitchens. Environ. Microbiol. 15, 588–596 (2013).

  9. 9.

    Dunn, R. R., Fierer, N., Henley, J. B., Leff, J. W. & Menninger, H. L. Home life: factors structuring the bacterial diversity found within and between homes. PLOS ONE 8, e64133 (2013).

  10. 10.

    Bokulich, N. A., Ohta, M., Richardson, P. M. & Mills, D. A. Monitoring seasonal changes in winery-resident microbiota. PLOS ONE 8, e66437 (2013).

  11. 11.

    Jeon, Y.-S., Chun, J. & Kim, B.-S. Identification of household bacterial community and analysis of species shared with human microbiome. Curr. Microbiol. 67, 557–563 (2013).

  12. 12.

    Lax, S. et al. Longitudinal analysis of microbial interaction between humans and the indoor environment. Science 345, 1048–1052.This study applies longitudinal analysis of both the human and animal occupants and built surfaces in homes, providing the first examples of the intensity of bidirectional colonization events.

  13. 13.

    Miletto, M. & Lindow, S. E. Relative and contextual contribution of different sources to the composition and abundance of indoor air bacteria in residences. Microbiome 3, 61 (2015).

  14. 14.

    Chase, J. et al. Geography and location are the primary drivers of office microbiome composition. mSystems 1, e00022-16 (2016). This study shows that under normal (dry) office conditions, bacterial communities do not differ on the basis of material but do differ on the basis of the location in a room.

  15. 15.

    Adams, R. I., Bateman, A. C., Bik, H. M. & Meadow, J. F. Microbiota of the indoor environment: a meta-analysis. Microbiome 3, 49 (2015).

  16. 16.

    Lee, L., Tin, S. & Kelley, S. T. Culture-independent analysis of bacterial diversity in a child-care facility. BMC Microbiol. 7, 27 (2007).

  17. 17.

    Rintala, H., Pitkaranta, M., Toivola, M., Paulin, L. & Nevalainen, A. Diversity and seasonal dynamics of bacterial community in indoor environment. BMC Microbiol. 8, 56 (2008).

  18. 18.

    Hewitt, K. M., Gerba, C. P., Maxwell, S. L. & Kelley, S. T. Office space bacterial abundance and diversity in three metropolitan areas. PLOS ONE 7, e37849 (2012).

  19. 19.

    Hewitt, K. M. et al. Bacterial diversity in two neonatal intensive care units (NICUs). PLOS ONE 8, e54703 (2013).

  20. 20.

    Kembel, S. W. et al. Architectural design drives the biogeography of indoor bacterial communities. PLOS ONE 9, e87093 (2014).

  21. 21.

    Meadow, J. F. et al. Bacterial communities on classroom surfaces vary with human contact. Microbiome 2, 7 (2014).

  22. 22.

    Meadow, J. F. et al. Humans differ in their personal microbial cloud. PeerJ. 3, e1258 (2015).

  23. 23.

    Amend, A. S., Seifert, K. A., Samson, R. & Bruns, T. D. Indoor fungal composition is geographically patterned and more diverse in temperate zones than in the tropics. Proc. Natl Acad. Sci. USA 107, 13748–13753 (2010). This is the first study to explore the geographical and climate-driven diversity of indoor fungal communities, providing evidence to support the potential relationship between fungal diversity and composition and differences in health characteristics.

  24. 24.

    Barberán, A. et al. The ecology of microscopic life in household dust. Proc. R. Soc. B Biol. Sci. 282, 20151139 (2015).

  25. 25.

    Emerson, J. B. et al. Impacts of flood damage on airborne bacteria and fungi in homes after the 2013 Colorado Front Range flood. Environ. Sci. Technol. 49, 2675–2684 (2015).

  26. 26.

    Flores, G. E. et al. Microbial biogeography of public restroom surfaces. PLOS ONE 6, e28132 (2011).

  27. 27.

    Dannemiller, K. C., Gent, J. F., Leaderer, B. P. & Peccia, J. Influence of housing characteristics on bacterial and fungal communities in homes of asthmatic children. Indoor Air 26, 179–192 (2016).

  28. 28.

    Weikl, F. et al. Fungal and bacterial communities in indoor dust follow different environmental determinants. PLOS ONE 11, e0154131 (2016).

  29. 29.

    Emerson, J. B. et al. High temporal variability in airborne bacterial diversity and abundance inside single-family residences. Indoor Air 27, 576–586 (2017).

  30. 30.

    Qian, J., Hospodsky, D., Yamamoto, N., Nazaroff, W. W. & Peccia, J. Size-resolved emission rates of airborne bacteria and fungi in an occupied classroom: size-resolved bioaerosol emission rates. Indoor Air 22, 339–351 (2012). This study involves a fundamental quantitative analysis of the abundance of bacterial and fungal particles emitted by occupants in a built environment, which supports the important contribution of humans and animals to the discovered diversity of indoor microbial communities.

  31. 31.

    Hospodsky, D. et al. Human occupancy as a source of indoor airborne bacteria. PLOS ONE 7, e34867 (2012).

  32. 32.

    Hospodsky, D. et al. Characterizing airborne fungal and bacterial concentrations and emission rates in six occupied children’s classrooms. Indoor Air 25, 641–652 (2015).

  33. 33.

    Kunkel, S. A., Azimi, P., Zhao, H., Stark, B. C. & Stephens, B. Quantifying the size-resolved dynamics of indoor bioaerosol transport and control. Indoor Air 27, 977–987 (2017).

  34. 34.

    Miller, J. D. & Young, J. C. The use of ergosterol to measure exposure to fungal propagules in indoor air. Am. Ind. Hyg. Assoc. J. 58, 39–43 (1997).

  35. 35.

    Rao, C. Y., Cox-Ganser, J. M., Chew, G. L., Doekes, G. & White, S. Use of surrogate markers of biological agents in air and settled dust samples to evaluate a water-damaged hospital. Indoor Air 15, 89–97 (2005).

  36. 36.

    Vandeputte, D. et al. Quantitative microbiome profiling links gut community variation to microbial load. Nature 551, 507–511 (2017).

  37. 37.

    Dannemiller, K. C., Lang-Yona, N., Yamamoto, N., Rudich, Y. & Peccia, J. Combining real-time PCR and next-generation DNA sequencing to provide quantitative comparisons of fungal aerosol populations. Atmos. Environ. 84, 113–121 (2014).

  38. 38.

    Props, R. et al. Absolute quantification of microbial taxon abundances. ISME J. 11, 584–587 (2017).

  39. 39.

    Prussin, A. J. & Marr, L. C. Sources of airborne microorganisms in the built environment. Microbiome 3, 78 (2015).

  40. 40.

    Prussin, A. J., Garcia, E. B. & Marr, L. C. Total concentrations of virus and bacteria in indoor and outdoor air. Environ. Sci. Technol. Lett. 2, 84–88 (2015).

  41. 41.

    Tringe, S. G. et al. The airborne metagenome in an indoor urban environment. PLOS ONE 3, e1862 (2008). This is the first metagenomics study of the indoor microbiome that found that the indoor air microorganisms were not random transients from surrounding outdoor environments, but rather originated from indoor niches.

  42. 42.

    Yooseph, S. et al. A metagenomic framework for the study of airborne microbial communities. PLOS ONE 8, e81862 (2013).

  43. 43.

    Adams, R. I. et al. Microbes and associated soluble and volatile chemicals on periodically wet household surfaces. Microbiome 5, 128 (2017). This is the first example of the integration of metabolomics and microbiome data in an indoor environment, enabling a clearer understanding of how the household conditions shape microbial metabolism.

  44. 44.

    Blazewicz, S. J., Barnard, R. L., Daly, R. A. & Firestone, M. K. Evaluating rRNA as an indicator of microbial activity in environmental communities: limitations and uses. ISME J. 7, 2061–2068 (2013).

  45. 45.

    Emerson, J. B. et al. Schrödinger’s microbes: tools for distinguishing the living from the dead in microbial ecosystems. Microbiome 5, 86 (2017).

  46. 46.

    Miller, J. D. & McMullin, D. R. Fungal secondary metabolites as harmful indoor air contaminants: 10 years on. Appl. Microbiol. Biotechnol. 98, 9953–9966 (2014). This study is a synthesis of available data on the low-molecular-weight toxins reliably known from fungi common on damp building materials and the toxins that have been measured on mouldy building materials.

  47. 47.

    Hegarty, B., Dannemiller, K. & Peccia, J. Gene expression of indoor fungal communities under damp building conditions: implications for human health. Indoor Air 28, 548–558 (2018).This is the first example of the application of metatranscriptomics to a built environment system, providing knowledge of how microbial transcription of genes is influenced by damp conditions.

  48. 48.

    Weis, C. P. et al. Secondary aerosolization of viable Bacillus anthracis spores in a contaminated US Senate Office. JAMA 288, 2853–2858 (2002).

  49. 49.

    Blatny, J. M. et al. Tracking airborne Legionella and Legionella pneumophila at a biological treatment plant. Environ. Sci. Technol. 42, 7360–7367 (2008).

  50. 50.

    Nazaroff, W. W., Nicas, M. & Miller, S. L. Framework for evaluating measures to control nosocomial tuberculosis transmission. Indoor Air 8, 205–218 (1998).

  51. 51.

    Nosanchuk, J. D. et al. Evidence of zoonotic transmission of Cryptococcus neoformans from a pet cockatoo to an immunocompromised patient. Ann. Intern. Med. 132, 205 (2000).

  52. 52.

    Furcolow, M. L., Menges, R. W. & Larsh, H. W. An epidemic of histoplasmosis involving man and animals. Ann. Intern. Med. 43, 173–181 (1955).

  53. 53.

    Anderson, K. et al. Aspergillosis in immunocompromised paediatric patients: associations with building hygiene, design, and indoor air. Thorax 51, 256–261 (1996).

  54. 54.

    Dick, E. C., Jennings, L. C., Mink, K. A., Wartgow, C. D. & Inborn, S. L. Aerosol transmission of rhinovirus colds. J. Infect. Dis. 156, 442–448 (1987).

  55. 55.

    Myatt, T. A. et al. Detection of airborne rhinovirus and its relation to outdoor air supply in office environments. Am. J. Respir. Crit. Care Med. 169, 1187–1190 (2004).

  56. 56.

    Fabian, P., Brain, J., Houseman, E. A., Gern, J. & Milton, D. K. Origin of exhaled breath particles from healthy and human rhinovirus-infected subjects. J. Aerosol Med. Pulm. Drug Deliv. 24, 137–147 (2011).

  57. 57.

    Jones, R. M. & Adida, E. Influenza infection risk and predominate exposure route: uncertainty analysis. Risk Anal. 31, 1622–1631 (2011).

  58. 58.

    Cowling, B. J. et al. Aerosol transmission is an important mode of influenza A virus spread. Nat. Commun. 4, 1935 (2013).

  59. 59.

    Lindsley, W. G. et al. Viable influenza A virus in airborne particles from human coughs. J. Occup. Environ. Hyg. 12, 107–113 (2015).

  60. 60.

    Weber, D. J., Rutala, W. A., Miller, M. B., Huslage, K. & Sickbert-Bennett, E. Role of hospital surfaces in the transmission of emerging health care-associated pathogens: norovirus. Clostridium difficile, and Acinetobacter species. Am. J. Infect. Control 38, S25–S33 (2010).

  61. 61.

    Otter, J. A., Yezli, S. & French, G. L. The role played by contaminated surfaces in the transmission of nosocomial pathogens. Infect. Control Hosp. Epidemiol. 32, 687–699 (2011).

  62. 62.

    Lopman, B. et al. Environmental transmission of norovirus gastroenteritis. Curr. Opin. Virol. 2, 96–102 (2012).

  63. 63.

    Brankston, G., Gitterman, L., Hirji, Z., Lemieux, C. & Gardam, M. Transmission of influenza A in human beings. Lancet Infect. Dis. 7, 257–265 (2007).

  64. 64.

    Wilkins, D., Leung, M. H. & Lee, P. K. Indoor air bacterial communities in Hong Kong households assemble independently of occupant skin microbiomes: household air bacteria differ from occupant skin. Environ. Microbiol. 18, 1754–1763 (2016).

  65. 65.

    Meadow, J. F. et al. Indoor airborne bacterial communities are influenced by ventilation, occupancy, and outdoor air source. Indoor Air 24, 41–48 (2014).

  66. 66.

    Leung, M. H. Y., Wilkins, D., Li, E. K. T., Kong, F. K. F. & Lee, P. K. H. Indoor-air microbiome in an urban subway network: diversity and dynamics. Appl. Environ. Microbiol. 80, 6760–6770 (2014).

  67. 67.

    Lax, S. et al. Bacterial colonization and succession in a newly opened hospital. Sci. Transl Med. 9, eaah6500 (2017).

  68. 68.

    Peccia, J. & Kwan, S. E. Buildings, beneficial microbes, and health. Trends Microbiol. 24, 595–597 (2016).

  69. 69.

    USEPA. Exposure Factors Handbook (US Environmental Protection Agency, 2011).

  70. 70.

    Eder, W. & von Mutius, E. Hygiene hypothesis and endotoxin: what is the evidence? Curr. Opin. Allergy Clin. Immunol. 4, 113–117 (2004).

  71. 71.

    Ege, M. J. et al. Exposure to environmental microorganisms and childhood asthma. N. Engl. J. Med. 364, 701–709 (2011).

  72. 72.

    Stein, M. M. et al. Innate immunity and asthma risk in Amish and Hutterite farm children. N. Engl. J. Med. 375, 411–421 (2016).

  73. 73.

    O’Connor, G. T. et al. Early-life home environment and risk of asthma among inner-city children. J. Allergy Clin. Immunol. 141, 1468–1475 (2017).

  74. 74.

    Lynch, S. V. et al. Effects of early-life exposure to allergens and bacteria on recurrent wheeze and atopy in urban children. J. Allergy Clin. Immunol. 134, 593–601 (2014). This study demonstrates the association between indoor microbial allergens and asthmatic diseases, providing a solid association between disease and indoor microbiome.

  75. 75.

    Fujimura, K. E. et al. House dust exposure mediates gut microbiome Lactobacillus enrichment and airway immune defense against allergens and virus infection. Proc. Natl Acad. Sci. USA 111, 805–810 (2014).

  76. 76.

    Kanchongkittiphon, W., Mendell, M. J., Gaffin, J. M., Wang, G. & Phipatanakul, W. Indoor environmental exposures and exacerbation of asthma: an update to the 2000 Review by the Institute of Medicine. Environ. Health Perspect. 123, 6–20 (2014).

  77. 77.

    Mendell, M. J., Mirer, A. G., Cheung, K., Tong, M. & Douwes, J. Respiratory and allergic health effects of dampness, mold, and dampness-related agents: a review of the epidemiologic evidence. Environ. Health Perspect. 119, 748–756 (2011). This is a systematic review of the epidemiological evidence for associations between dampness and mould and respiratory and allergic effects in humans. Evident dampness or mould has consistent positive associations with multiple allergic and respiratory effects, but measured microbiological agents in dust have limited suggestive associations.

  78. 78.

    Fisk, W. J., Lei-Gomez, Q. & Mendell, M. J. Meta-analyses of the associations of respiratory health effects with dampness and mold in homes. Indoor Air 17, 284–296 (2007).

  79. 79.

    Bush, R. K., Portnoy, J. M., Saxon, A., Terr, A. I. & Wood, R. A. The medical effects of mold exposure. J. Allergy Clin. Immunol. 117, 326–333 (2006).

  80. 80.

    Portnoy, J. M., Kwak, K., Dowling, P., VanOsdol, T. & Barnes, C. Health effects of indoor fungi. Ann. Allergy. Asthma. Immunol. 94, 313–320 (2005).

  81. 81.

    Wessén, B. & Schoeps, K. O. Microbial volatile organic compounds—what substances can be found in sick buildings? Analyst 121, 1203–1205 (1996).

  82. 82.

    Korpi, A., Pasanen, A. L. & Pasanen, P. Volatile compounds originating from mixed microbial cultures on building materials under various humidity conditions. Appl. Environ. Microbiol. 64, 2914–2919 (1998).

  83. 83.

    Araki, A. et al. Diffusive sampling and measurement of microbial volatile organic compounds in indoor air. Indoor Air 19, 421–432 (2009).

  84. 84.

    Korpi, A., Pasanen, A.-L., Pasanen, P. & Kalliokoski, P. Microbial growth and metabolism in house dust. Int. Biodeterior. Biodegrad. 40, 19–27 (1997).

  85. 85.

    Kirjavainen, P. V. et al. Microbial secondary metabolites in homes in association with moisture damage and asthma. Indoor Air 26, 448–456 (2016).

  86. 86.

    Ezeonu, I. M., Price, D. L., Simmons, R. B., Crow, S. A. & Ahearn, D. G. Fungal production of volatiles during growth on fiberglass. Appl. Environ. Microbiol. 60, 4172–4173 (1994).

  87. 87.

    Schleibinger, H., Laussmann, D., Bornehag, C.-G., Eis, D. & Rueden, H. Microbial volatile organic compounds in the air of moldy and mold-free indoor environments. Indoor Air 18, 113–124 (2008).

  88. 88.

    Kuske, M., Romain, A.-C. & Nicolas, J. Microbial volatile organic compounds as indicators of fungi. Can an electronic nose detect fungi in indoor environments? Build. Environ. 40, 824–831 (2005).

  89. 89.

    Ryan, T. J. & Beaucham, C. Dominant microbial volatile organic compounds in 23 US homes. Chemosphere 90, 977–985 (2013).

  90. 90.

    Wargo, M. J. & Hogan, D. A. Fungal — bacterial interactions: a mixed bag of mingling microbes. Curr. Opin. Microbiol. 9, 359–364 (2006).

  91. 91.

    Gilbert, J. A. How do we make indoor environments and healthcare settings healthier? Microb. Biotechnol. 10, 11–13 (2017).

  92. 92.

    Cruz, M. R., Graham, C. E., Gagliano, B. C., Lorenz, M. C. & Garsin, D. A. Enterococcus faecalis inhibits hyphal morphogenesis and virulence of Candida albicans. Infect. Immun. 81, 189–200 (2013).

  93. 93.

    Graham, C. E., Cruz, M. R., Garsin, D. A. & Lorenz, M. C. Enterococcus faecalis bacteriocin EntV inhibits hyphal morphogenesis, biofilm formation, and virulence of Candida albicans. Proc. Natl Acad. Sci. USA 114, 4507–4512 (2017).

  94. 94.

    Kelley, S. T. & Gilbert, J. A. Studying the microbiology of the indoor environment. Genome Biol. 14, 202 (2013).

  95. 95.

    Verdier, T., Coutand, M., Bertron, A. & Roques, C. A review of indoor microbial growth across building materials and sampling and analysis methods. Build. Environ. 80, 136–149 (2014).

  96. 96.

    Dedesko, S. & Siegel, J. A. Moisture parameters and fungal communities associated with gypsum drywall in buildings. Microbiome 3, 71 (2015). This is a critical review of measurable moisture parameters on one of the most common building materials and associations with fungal growth.

  97. 97.

    Gravesen, S., Nielsen, P. A., Iversen, R. & Nielsen, K. F. Microfungal contamination of damp buildings—examples of risk constructions and risk materials. Environ. Health Perspect. 107(Suppl. 3), 505–508 (1999).

  98. 98.

    Hoang, C. P., Kinney, K. A., Corsi, R. L. & Szaniszlo, P. J. Resistance of green building materials to fungal growth. Int. Biodeterior. Biodegrad. 64, 104–113 (2010).

  99. 99.

    Gutarowska, B. Metabolic activity of moulds as a factor of building materials biodegradation. Pol. J. Microbiol. 59, 119–124 (2010).

  100. 100.

    Good, B. H., McDonald, M. J., Barrick, J. E., Lenski, R. E. & Desai, M. M. The dynamics of molecular evolution over 60,000 generations. Nature 551, 45–50 (2017).

  101. 101.

    Anesti, V. et al. Molecular detection and isolation of facultatively methylotrophic bacteria, including Methylobacterium podarium sp. nov., from the human foot microflora. Environ. Microbiol. 6, 820–830 (2004).

  102. 102.

    Frank, D. N. et al. Molecular-phylogenetic characterization of microbial community imbalances in human inflammatory bowel diseases. Proc. Natl Acad. Sci. USA 104, 13780–13785 (2007).

  103. 103.

    Zhang, L. et al. Microbiological pattern of arterial catheters in the intensive care unit. BMC Microbiol. 10, 266 (2010).

  104. 104.

    Sangwan, N. et al. Reconstructing an ancestral genotype of two hexachlorocyclohexane-degrading Sphingobium species using metagenomic sequence data. ISME J. 8, 398–408 (2014).

  105. 105.

    Hammond, T. G. et al. Effects of microgravity on the virulence of Listeria monocytogenes, Enterococcus faecalis, Candida albicans, and methicillin-resistant Staphylococcus aureus. Astrobiology 13, 1081–1090 (2013).

  106. 106.

    Wilson, J. W. et al. Space flight alters bacterial gene expression and virulence and reveals a role for global regulator Hfq. Proc. Natl Acad. Sci. USA 104, 16299–16304 (2007).

  107. 107.

    Allen, C. A., Niesel, D. W. & Torres, A. G. The effects of low-shear stress on adherent-invasive Escherichia coli. Environ. Microbiol. 10, 1512–1525 (2008).

  108. 108.

    La Duc, M. T. et al. Isolation and characterization of bacteria capable of tolerating the extreme conditions of clean room environments. Appl. Environ. Microbiol. 73, 2600–2611 (2007).

  109. 109.

    Hampton-Marcell, J. T., Lopez, J. V. & Gilbert, J. A. The human microbiome: an emerging tool in forensics. Microb. Biotechnol. 10, 228–230 (2017).

  110. 110.

    Lax, S. et al. Forensic analysis of the microbiome of phones and shoes. Microbiome 3, 21 (2015).

  111. 111.

    Brown, G. Z., Kline, J., Mhuireach, G., Northcutt, D. & Stenson, J. Making microbiology of the built environment relevant to design. Microbiome 4, 6 (2016).

  112. 112.

    Beans, C. The microbiome of green design. BioScience 66, 801–806 (2016).

  113. 113.

    Zhang, D., Xu, C., Manwani, D. & Frenette, P. S. Neutrophils, platelets, and inflammatory pathways at the nexus of sickle cell disease pathophysiology. Blood 127, 801–809 (2016).

  114. 114.

    Gilbert, J. A. et al. Current understanding of the human microbiome. Nat. Med. 24, 392–400 (2018).

  115. 115.

    Leung, M. H. Y. & Lee, P. K. H. The roles of the outdoors and occupants in contributing to a potential pan-microbiome of the built environment: a review. Microbiome 4, 21 (2016).

  116. 116.

    Coombs, K., Vesper, S., Green, B. J., Yermakov, M. & Reponen, T. Fungal microbiomes associated with green and non-green building materials. Int. Biodeterior. Biodegrad. 125, 251–257 (2017).

  117. 117.

    Adams, R. I. et al. Ten questions concerning the microbiomes of buildings. Build. Environ. 109, 224–234 (2016).

  118. 118.

    Sundell, J. On the history of indoor air quality and health. Indoor Air 14 (Suppl. 7), 51–58 (2004).

  119. 119.

    Russell, F. A. R. The Atmosphere in Relation to Human Life and Health (Smithsonian Institution, 1896).

  120. 120.

    Carnelley, T., Haldane, J. S. & Anderson, A. M. The carbonic acid, organic matter, and micro-organisms in air, more especially of dwellings and schools. Phil. Trans. R. Soc. B Biol. Sci. 178, 61–111 (1887). This is a seminal study on indoor microorganisms — ahead of its time by about 100 years.

  121. 121.

    Carnelley, P. & Haldane, J. S. The air of sewers. Proc. R. Soc. 42, 394–396 (1887).

  122. 122.

    Carnelley, T. & Foggie, J. The air of schools. J. Pathol. Bacteriol. 2, 157–173 (1894).

  123. 123.

    Sedgwick, W. T. Principles of Sanitary Science and the. Public Health: With Special Reference to the Causation and Prevention of Infectious Diseases. (Macmillan, London, 1902).

  124. 124.

    Huddleson, I. F. & Hull, T. G. Bacteria of the air in an amusement hall. Am. J. Public Health N. Y. N. 1912 10, 583–585 (1920).

  125. 125.

    Sundell, J. et al. Ventilation rates and health: multidisciplinary review of the scientific literature: ventilation rates and health. Indoor Air 21, 191–204 (2011).

  126. 126.

    Quansah, R., Jaakkola, M. S., Hugg, T. T., Heikkinen, S. A. M. & Jaakkola, J. J. K. Residential dampness and molds and the risk of developing asthma: a systematic review and meta-analysis. PLOS ONE 7, e47526 (2012).

  127. 127.

    Carnelley, T. & Wilson, T. A. New method of determining the number of micro-organisms in air. Proc. R. Soc. 44, 455–464 (1888).

  128. 128.

    Graham-Smith, G. S. The microorganisms in the air of the House of Commons. J. Hyg. 3, 498–514 (1903).

  129. 129.

    Forbes, J. G. The atmosphere of the underground electric railways of London: a study of its bacterial content in 1920. J. Hyg. 22, 123–155 (1923).

  130. 130.

    Luckiesh, M., Taylor, A. H. & Holladay, L. L. Sampling devices for air-borne bacteria. J. Bacteriol. 52, 55–65 (1946).

  131. 131.

    Williams, R. E. O. & Hirch, A. The detection of streptococci in air. J. Hyg. 48, 504–524 (1950).

  132. 132.

    Williams, R. E. O., Lidwell, O. M. & Hirch, A. The bacterial flora of the air of occupied rooms. J. Hyg. 54, 512–523 (1956).

  133. 133.

    Reid, D. D., Lidwell, O. M. & Williams, R. E. O. Counts of air-borne bacteria as indices of air hygiene. J. Hyg. 54, 524–532 (1956).

  134. 134.

    Swaebly, M. A. & Christensen, C. M. Molds in house dust, furniture stuffing, and in the air within homes. J. Allergy 23, 370–374 (1952).

  135. 135.

    Buchbinder, L., Solowey, M. & Solotorovsky, M. Alpha hemolytic streptococci of air: their variant forms, origin and numbers per cubic foot of air in several types of locations. Am. J. Publ. Health Nat. Health 28, 61–71 (1938).

  136. 136.

    Christensen, C. M. Intramural dissemination of spores of Hormodendrum resinae. J. Allergy 21, 409–413 (1950).

  137. 137.

    Lidwell, O. M. & Lowbury, E. J. The survival of bacteria in dust. I. The distribution of bacteria in floor dust. J. Hyg. 48, 6–20 (1950).

  138. 138.

    Caplan, H. Observations on the role of hospital blankets as reservoirs of infection. J. Hyg. 60, 401–410 (1962).

  139. 139.

    Lidwell, O. M. & Lowbury, E. J. The survival of bacteria in dust. II. The effect of atmospheric humidity on the survival of bacteria in dust. J. Hyg. 48, 21–27 (1950).

  140. 140.

    Lidwell, O. M. & Lowbury, E. J. The survival of bacteria in dust. III. The effect of light on the survival of bacteria in dust. J. Hyg. 48, 28–37 (1950).

  141. 141.

    Wright, J., Cruickshank, R. & Gunn, W. Control of dust-borne streptococcal infection in measles wards. Br. Med. J. 1, 611–614 (1944).

  142. 142.

    Nash, T. Physical aspects of air disinfection. J. Hyg. 49, 382–399 (1951).

  143. 143.

    Hollaender, A. Ultra-violet irradiation as a means of disinfection of air. Am. J. Publ. Health Nat. Health 33, 980–984 (1943).

  144. 144.

    Lidwell, O. M. & Lowbury, E. J. The survival of bacteria in dust. IV. Atmospheric humidity and the bactericidal action of ultra-violet irradiation. J. Hyg. 48, 38–43 (1950).

  145. 145.

    Schaffer, N., Seidmon, E. E. & Bruskin, S. The clinical evaluation of air-borne and house dust fungi in New Jersey. J. Allergy 24, 348–354 (1953).

  146. 146.

    Maunsell, K. Air-borne fungal spores before and after raising dust; sampling by sedimentation. Int. Arch. Allergy Appl. Immunol. 3, 93–102 (1952).

  147. 147.

    Maunsell, K. Concentration of airborne spores in dwellings under normal conditions and under repair. Int. Arch. Allergy Appl. Immunol. 5, 373–376 (1954).

  148. 148.

    Winslow, C. E. & Robinson, E. A. An Investigation of the extent of the bacterial pollution of the atmosphere by mouth-spray. Am. J. Publ. Hyg. 20, 566–569 (1910).

  149. 149.

    Du Buy, H., Arnold, F. A. & Olson, B. J. Studies on the air transmission of micro-organisms derived from the respiratory tract: Lactobacillus acidophilus as a test organism. Publ. Health Rep. 62, 1391–1413 (1947).

  150. 150.

    Bourdillon, R. B. & Lidwell, O. M. Sneezing and the spread of infection. Lancet 238, 365–367 (1941).

  151. 151.

    Hart, D. Role of the respiratory tract in contamination of air: a comparative study. Arch. Surg. 38, 788 (1939).

  152. 152.

    Torrey, J. C. & Lake, M. Streptococci in air as an indicator of nasopharyngeal contamination. JAMA 117, 1425 (1941).

  153. 153.

    Wells, W. F. On air-borne infection. Study II. droplets and droplet nuclei. Am. J. Epidemiol. 20, 611–618 (1934). This is a seminal study on the method of disease transmission by small and large droplets expelled by humans.

  154. 154.

    Acheson, F. & Hewitt, D. Spread of influenza in a factory. Br. J. Soc. Med. 6, 68–75 (1952).

  155. 155.

    Moschandreas, D. J., Pagilla, K. R. & Storino, L. V. Time and space uniformity of indoor bacteria concentrations in Chicago area residences. Aerosol. Sci. Technol. 37, 899–906 (2003).

  156. 156.

    Tsai, F. C. & Macher, J. M. Concentrations of airborne culturable bacteria in 100 large US office buildings from the BASE study. Indoor Air 15, 71–81 (2005).

  157. 157.

    Reponen, T., Nevalainen, A. & Raunemaa, T. Bioaerosol and particle mass levels and ventilation in finnish homes. Environ. Int. 15, 203–208 (1989).

  158. 158.

    Kodama, A. M. & McGee, R. I. Airborne microbial contaminants in indoor environments. naturally ventilated and air-conditioned homes. Arch. Environ. Health Int. J. 41, 306–311 (1986).

  159. 159.

    Burger, H. Bioaerosols: prevalence and health effects in the indoor environment. J. Allergy Clin. Immunol. 86, 687–701 (1990).

  160. 160.

    Kaeberlein, T. Isolating ‘uncultivable’ microorganisms in pure culture in a simulated natural environment. Science 296, 1127–1129 (2002).

  161. 161.

    Zengler, K. et al. Cultivating the uncultured. Proc. Natl Acad. Sci. USA 99, 15681–15686 (2002).

  162. 162.

    Pace, N. R. A. Molecular view of microbial diversity and the biosphere. Science 276, 734–740 (1997).

  163. 163.

    Amann, R. I., Ludwig, W. & Schleifer, K. H. Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol. Rev. 59, 143–169 (1995).

  164. 164.

    Jackrel, S. L., Owens, S. M., Gilbert, J. A. & Pfister, C. A. Identifying the plant-associated microbiome across aquatic and terrestrial environments: the effects of amplification method on taxa discovery. Mol. Ecol. Resour. 17, 931–942 (2017).

  165. 165.

    Hatzenpichler, R. & Orphan, V. J. in Hydrocarbon and Lipid Microbiology Protocols (eds McGenity, T. J., Timmis, K. N. & Nogales, B.) 145–157 (Springer, Berlin, 2015)

  166. 166.

    Henry, C. S. et al. High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat. Biotechnol. 28, 977–982 (2010).

  167. 167.

    Cardona, C., Weisenhorn, P., Henry, C. & Gilbert, J. A. Network-based metabolic analysis and microbial community modeling. Curr. Opin. Microbiol. 31, 124–131 (2016).

  168. 168.

    Committee on Microbiomes of the Built Environment. Microbiomes of the Built Environment: A Research Agenda for Indoor Microbiology, Human Health, and Buildings (National Academies Press, 2017).

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J.A.G. and B.S. acknowledge funding from the Alfred P. Sloan Foundation (060115). J.A.G. acknowledges S. Lax, C. Cardona and A. Sharma for their help in compiling references and for education about aspects of specific research elements.

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Nature Reviews Microbiology thanks R. Adams, M. Hernandez and M. Täubel for their contribution to the peer review of this work.

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  1. Department of Surgery, University of Chicago, Chicago, IL, USA

    • Jack A. Gilbert
  2. Bioscience Division, Argonne National Laboratory, Lemont, IL, USA

    • Jack A. Gilbert
  3. Department of Civil, Architectural, and Environmental Engineering, Illinois Institute of Technology, Chicago, IL, USA

    • Brent Stephens


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J.A.G. and B.S. researched data for the article, made substantial contributions to discussions of the content, wrote the article and reviewed and/or edited the manuscript before submission.

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The authors declare no competing interests.

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Correspondence to Jack A. Gilbert.

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