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Indoor green wall affects health-associated commensal skin microbiota and enhances immune regulation: a randomized trial among urban office workers


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Urbanization reduces microbiological abundance and diversity, which has been associated with immune mediated diseases. Urban greening may be used as a prophylactic method to restore microbiological diversity in cities and among urbanites. This study evaluated the impact of air-circulating green walls on bacterial abundance and diversity on human skin, and on immune responses determined by blood cytokine measurements. Human subjects working in offices in two Finnish cities (Lahti and Tampere) participated in a two-week intervention, where green walls were installed in the rooms of the experimental group. Control group worked without green walls. Skin and blood samples were collected before (Day0), during (Day14) and two weeks after (Day28) the intervention. The relative abundance of genus Lactobacillus and the Shannon diversity of phylum Proteobacteria and class Gammaproteobacteria increased in the experimental group. Proteobacterial diversity was connected to the lower proinflammatory cytokine IL-17A level among participants in Lahti. In addition, the change in TGF-β1 levels was opposite between the experimental and control group. As skin Lactobacillus and the diversity of Proteobacteria and Gammaproteobacteria are considered advantageous for skin health, air-circulating green walls may induce beneficial changes in a human microbiome. The immunomodulatory potential of air-circulating green walls deserves further research attention.
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Scientic Reports | (2022) 12:6518 |
Indoor green wall aects
health‑associated commensal skin
microbiota and enhances immune
regulation: a randomized trial
among urban oce workers
L. Soininen1, M. I. Roslund 1,3, N. Nurminen2, R. Puhakka1, O. H. Laitinen2, H. Hyöty2,
A. Sinkkonen3* & ADELE research group*
Urbanization reduces microbiological abundance and diversity, which has been associated with
immune mediated diseases. Urban greening may be used as a prophylactic method to restore
microbiological diversity in cities and among urbanites. This study evaluated the impact of air
circulating green walls on bacterial abundance and diversity on human skin, and on immune responses
determined by blood cytokine measurements. Human subjects working in oces in two Finnish
cities (Lahti and Tampere) participated in a two‑week intervention, where green walls were installed
in the rooms of the experimental group. Control group worked without green walls. Skin and blood
samples were collected before (Day0), during (Day14) and two weeks after (Day28) the intervention.
The relative abundance of genus Lactobacillus and the Shannon diversity of phylum Proteobacteria
and class Gammaproteobacteria increased in the experimental group. Proteobacterial diversity
was connected to the lower proinammatory cytokine IL‑17A level among participants in Lahti. In
addition, the change in TGF‑β1 levels was opposite between the experimental and control group.
As skin Lactobacillus and the diversity of Proteobacteria and Gammaproteobacteria are considered
advantageous for skin health, air‑circulating green walls may induce benecial changes in a human
microbiome. The immunomodulatory potential of air‑circulating green walls deserves further research
Due to an increased hygiene level1, biodiversity loss and irregular soil contacts24 the exposure to environmen-
tal microbes has reduced in Western cities, which is seen as one of the major reasons for the rise in immune-
mediated diseases, such as autoimmune diseases and allergies5. Nature-derived microbes that have a commensal
relationship with humans contribute to the development and regulation of the human immune system1,4,68. e
skin microbiome can be altered via skin contact to microbial sources and hands are a common route of micro-
bial transmission913. Indoors, humans aect and are exposed to microbial communities by touching indoor
surfaces14. In addition to direct skin contact, humans are exposed to and aected by microbes in the air, for
example, via skin and airways1517.
Each city has its own unique microbiome18,19 and its composition in the soil20 and in the air21 is aected by
vegetation. Indeed, plant surfaces are a known source of airborne bacteria17,22,23. Additionally, indoor plants
increase the abundance and diversity in bacterial communities on indoor surfaces24. e amount of vegetated area
in the locality aects the odds of developing immune-mediated diseases as a child2527. Vegetation also aects the
composition of the human gut microbiome, which impacts human immunoregulation28. Previous research has
identied certain bacterial groups that are abundant in soil and vegetation as indicators of a healthy skin microbi-
ome. For example, Proteobacteria belongs to the most common phyla on human skin (relative abundance > 5%);
1Ecosystems and Environment Research Programme, Faculty of Biological and Environmental Sciences, University
of Helsinki, Niemenkatu 73, 15140 Lahti, Finland. 2Faculty of Medicine and Health Technology, Tampere University,
Arvo Ylpön katu 34, 33520 Tampere, Finland. 3Natural Resources Institute Finland, Horticulture Technologies,
Turku and Helsinki, Finland. *A list of authors and their aliations appears at the end of the paper. *email:
Scientic Reports | (2022) 12:6518 |
its diversity and relative abundance seems to have a role in human immune regulation4,12,25. e diversity and
relative abundance in bacteria belonging to the class Gammaproteobacteria is an indication of health on human
skin4,7 and on plants29. Additionally, bacteria belonging to the genus Lactobacillus on skin fend o pathogens and
better the integrity of skin30; some Lactobacillus species found on humans also occur on plants31,32.
Due to poor microbiological assemblages in cities, urbanization reduces indoor microbial diversity3335.
Microbial assemblages can be aected with urban gardening36 and urban greening12,37,38. In previous studies,
the eects of soil and plant-based biodiversity interventions have been observed in human subjects as bacterial
changes in skin and stool microbiome, and altered immunoregulatory cytokine levels in the blood9,11,12. Surpris-
ingly, hardly any studies survey whether indoor greening shapes commensal microbiota and immune response
among urban dwellers24.
e current study explored if bacterial communities in the human subjects spending time indoors can be
altered via vegetated walls that circulate indoor air. For the intervention, vegetated walls (green walls) were
brought into oces of university personnel for two weeks and the impact was investigated via skin and blood
samples. e study subjects were expected to be exposed to the green walls via microbial communities in the
air and on indoor surfaces but not by touching the green walls. e microbial focus was on the bacterial alpha
diversity and the relative abundance of health-associated proteobacterial taxa and Lactobacillus on skin. To
observe possible immune responses, the levels of the anti-inammatory cytokines interleukin 10 (IL-10) and
transforming growth factor– β1 (TGF-β1)39,40, and the proinammatory cytokine interleukin 17A (IL-17A)41
were measured from the blood samples. Immunomodulatory pathways respond to IL-10 concentration in the
blood and IL-10 has been researched for therapeutic use in immunomodulation9,12 and prevention of immune-
mediated diseases, such as inammatory bowel disease and rheumatoid arthritis40. Similarly, TGF-β1 is connected
to several immune-mediated diseases as an inhibitor and has an essential impact on all types of immune cells4244.
e upregulation of cytokines in the IL-17 family in turn, seem to advance the pathogenesis of immune-mediated
diseases41,45. We hypothesized that the intervention would increase the relative abundance and alpha diversity of
health-associated taxa on the skin and aect the levels of the measured immune system cytokines.
Materials and methods
Green walls. e green walls (size 2m × 1m × 0.3m) used in this study were Naava One (Naava, Jyväskylä,
Finland; www. naava. io) that circulate indoor air. ey rst absorb the indoor air through the plant roots and
soilless substrate, then automated fans circulate the air back to the room. When the indoor air passes through
the green wall, volatile organic compounds (VOC) are eciently removed via bioltration by microbes, plants
and the growing medium46. e watering system is automated and the water circulates within the wall. Each
green wall contains three plant taxa (heartleaf philodendron (Philodendron scandens), dragon tree (Dracaena
sp.) and bird’s nest fern (Asplenium antiquum) growing altogether in 63 units. Each unit consists of two to four
plant individuals.
Treatment groups and sample collection. e study (a randomized controlled trial with parallel
design) was conducted in oces of university personnel in two Finnish cities (Lahti and Tampere). e study
followed the recommendations of Finnish Advisory Board on Research Integrity, and it was approved by the
ethics committee of the local hospital district (Hospital District of Pirkanmaa, Finland). A written informed
consent in accordance with the Declaration of Helsinki was signed by all participants. e study subjects were
healthy adults. e exclusion criteria were age below 18 at the beginning of the study, daily smoking, immune
deciency (e.g., antibody deciency, HIV infection), immunosuppressive medication (e.g., corticosteroids), a
condition aecting immune response (e.g., rheumatoid arthritis, colitis ulcerosa, Crohns disease, diabetes, and
Down syndrome), or cancer diagnosis. All volunteers that lled the inclusion criteria were accepted to the study.
e resulting 28 study subjects were randomly divided (intended allocation ratio 1:1; simple randomization
done by an independent researcher at University of Helsinki; mechanism: random number table) into two treat-
ment groups that were the control group (without green wall exposure) and the experimental group exposed to
green walls (Table1). Aer the randomization, it was ensured that age and sex ratio were similar in both groups,
and no changes were needed. e nal allocation ratio was 17:11 in the control and the experimental group. e
study subjects in the green wall group received a green wall in the oce rooms and were exposed to the green
walls only at the oce during their workdays. e study was implemented in two buildings in Lahti and one
building in Tampere, Finland (Table1). All study subjects answered surveys about their living conditions and
history (such as type of housing, pets and land use type in their locality) and their living habits during the experi-
ment on Day14 and Day28 (such as hours spent in nature, travel, medication, illnesses and food supplements).
Depending on the oce room size, 1–2 green walls were installed in the treatment oce rooms in Tampere and
Lahti for two weeks, according to instructions of the manufacturer (www. naava. io). When the room size was
more than 60 m2, two green walls were used as instructed by the manufacturer.
Skin and blood samples were collected from both experimental and control group participants before install-
ing the green walls (Day0), on the last day of the intervention (Day14) and two weeks aer the intervention
(Day28) by trained nurses as described by Roslund etal.12. Briey, skin samples were collected by swabbing an
area of 5cm–by–5cm on the back of the palm for 10s. e swabs were wetted with saline buer (0.1% Tween
20 in 0.15M NaCl) before sample collection, and aer sampling the cotton tips were cut o into sterile poly-
ethene tubes and stored at 80°C until analysis. Venous blood was collected into Vacutainer CPT Mononuclear
Cell Preparation tubes containing sodium citrate (BD Biosciences, NJ, USA) and centrifuged according to the
manufacturer’s instructions to separate the plasma and the plasma samples were stored at − 80°C until analysis.
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Skin and blood sample processing. e skin samples were prepared for bacterial DNA sequencing as
in Roslund etal.47. e bacterial DNA was extracted from the skin swabs with Fast DNA spin kit for soil (MP
biomedicals, Santa Ana, CA) according to the manufacturer’s protocol. e DNA concentration was quanti-
ed by Quant-iTTM PicoGreen® dsDNA reagent kit (ermo Fisher Scientic, Waltham, MA, USA). e DNA
concentration in the samples was adjusted to 0.4ng/ml before polymerase chain reaction (PCR) with which
variable region V3-V4 within the 16S ribosomal RNA (rRNA) gene was amplied. Forward primer was 515F 50-
GTG CCA GCMGCC GCG GTAA-30 and reverse primer 806R 50- GGA CTA CHVGGG TWT CTAAT-30 with
truncated Illumina overhangs as in Hui etal.37. Negative controls for DNA extraction (sterile water) and PCR
(no sample) were sequenced with the samples. Positive control for PCR was made using (Cupriavidus necator
JMP134, DSM 4058). Success of amplication process was conrmed with agarose gel (1.5%) electrophoresis.
e primers were cleaned from the PCR products with Agencourt AMPure XP solution (Beckman Coulter Inc.,
Brea, CA, USA). e samples were sequenced with Illumina MiSeq 16S rRNA gene metabarcoding with read
length 2 × 300 base pairs using a V3-V4 reagent kit at the Institute for Molecular Medicine Finland (FIMM,
Helsinki, Finland).
e concentration of cytokines IL-17A and IL-10 were measured from the plasma samples using Milliplex
MAP high sensitivity T cell panel kit (Merck KGaA, Darmstadt, Germany) with Bio-Plex® 200 system (Bio-Rad
Laboratories, Hercules, CA, USA) and Bio-Plex Manager soware (version 4.1, Bio-Rad Laboratories, Hercules,
CA, USA). TGF-β1 concentration was analyzed using ELISA (BioVendor, Czech Republic).
Bioinformatics. From the skin samples’ sequence data, the bacterial OTUs were identied to the genus level
according to studies by Schloss etal.48 and Kozich etal.49 as in Soininen etal.50. Briey, using Mothur (version
1.44.1) the sequences were aligned with SILVA (version 138)51 as a reference. e sequences were preclustered
to avoid sequencing errors52. Chimeras were searched by UCHIME53 and deleted. e sequences were classied
using Bayesian classier54 with SILVA (version 138)51 with 80% bootstrap threshold. Non-bacterial sequences
were deleted. Unique sequences were clustered to OTUs at 97% sequence similarity. OTUs with 10 sequences or
less were removed. Good’s coverage index (average ± SD: 0.98 ± 0.01) and alpha diversity indices were calculated
for each sample using summary.single command. ese calculations and the subsampling of the samples were
done according to the smallest sequence count (3893) in the samples. Contaminant OTUs were removed as
in Roslund etal.13. Abundant bacterial taxa (relative abundance of > 0.01%) were selected for further analyses.
Alpha diversity indices for phylum Proteobacteria, class Gammaproteobacteria and genus Lactobacillus were
calculated from the subsampled data using R version 3.6.155 function diversity of package vegan56.
Outcome measures and sample size estimation. Primary outcome measure was Alpha diversity of
skin Gammaproteobacteria, since it was associated with environmental biodiversity, andTGF-β in aprevious
study12. Gammaproteobacteria Shannon diversity index was measured at baseline and aer 28-day intervention.
Secondary outcome measure was relative abundance of skin Lactobacillus and cytokine levels measured from
plasma. All the secondary outcome measures were analyzed from baseline to end of intervention. No side eects
were observed.
e primary outcome measure for the power calculation was the dierence between intervention and control
study subjects in the change of Gammaproteobacterial diversity on the skin between baseline and day 28. We
used prior eect estimates from the study that estimates correlations between environmental biodiversity, human
microbiota and immune function12. In this study, the alpha diversity of Gammaproteobacteria was higher among
study subjects in the intervention arm in more biodiverse environment, and Gammaproteabacterial abundance
on skin was associated with TGF-β expression. Generic diversity of Gammaproteobacteria among study subjects
in contact with green materials (intervention arm) had an average of 17 Gammaproteobacterial genera in their
hands and a standard deviation of 5, whereas in the hands of study subjects in the urban control arm they had
an average of 8 and a standard deviation of 5. When the signicance level is set to P 0.05 and the statistical
Table 1. Characteristics of treatment groups: Ctrl = control, Exp = experimental.
Groups Ctrl Exp
Participants 17 11
Sex Female 13 9
Male 4 2
25–35 3 4
36–45 7 2
36–45 5 5
Average 40 40
SD 9 10
Type of residence
Apartment building 4 4
Rowhouse 2 2
Private house 10 5
Work place Lahti 10 7
Tampere 4 7
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force is 0.8 (80.1%), the between-cluster (between cities) coecient of variation is 0.2, the required sample size
for each group is 14.
Statistics. Bacterial diversity and relative abundance (dependent variables) of selected taxa were tested sta-
tistically in contrast to timepoint and treatment (explanatory variables) using linear mixed models (LMMs)
(function lmer in lme4 package in R) with study subject (nested in cities) as the random factor. LMMs are a
good t for analyzing clustered data and by using study subject as the random factor, the fact that one person
is the source for several samples, can be taken into account in the statistical evaluation57,58. Additionally, the
amount of change (between timepoints Day0–Day14 and Day0–Day28)59 in diversity and relative abundance
were calculated and compared using LMMs as in Roslund etal.12. Additionally, the treatments were compared
on each timepoint separately using t-test or Wilcoxon test depending on the Shapiro–Wilk distribution of the
variable. e cytokine levels and their changes (dependent variables) were tested in contrast to bacterial values,
the interaction of timepoint and treatment (explanatory variable) using LMMs with study subject (nested in cit-
ies) as the random factor. e background information and living habits were compared between the treatments
using Chi-Square test for nominal data and t-test or Wilcoxon’s test for quantitative data.
e relative abundance of Lactobacillus spp. (Fig.1 and Supplementary Table1) was higher in the skin samples
of the experimental group than the control group during the treatments, on Day14 (Wilcoxon P = 0.0058).
Additionally, the change (Day14 – Day0) in the relative abundance of Lactobacillus spp. was higher in the experi-
mental group than in the control group. Within the experimental group, the relative abundance of Lactobacillus
spp. increased in six study subjects and decreased in three study subjects. Within the control group, the relative
abundance decreased in 13 study subjects and increased in three study subjects. Importantly, random variation
between individuals explains total variation only partially (LMM All: P < 0.001, R2 = 0.05, R2 random = 0.21).
e signicance of the model did not depend on the city (LMM Lahti P < 0.001, R2 = 0.05, R2random = 0.31;
LMM Tampere P < 0.001, R2 = 0.25, R2random = 0.06).
ere were subtle dierences in the Shannon diversity of Gammaproteobacteria (Fig.2A and Supplemen-
tary Table1) and Proteobacteria (Fig.2B and Supplementary Table1). e change in Shannon diversity (Day28
– Day0) diered between treatment groups in Proteobacteria, plausibly due to high Day28 values in the experi-
mental group (LMM: P = 0.04, R2 = 0.02, R2random = 0.67) and Gammaproteobacteria (LMM: P = 0.02, R2 = 0.03,
R2random = 0.66). Interestingly, the diversity changes in Proteobacteria were dominant among participants in
Lahti but not in Tampere (Supplementary Fig.1).
Among Lahti dwellers, low cytokine IL-17A levels were associated to high Shannon diversity in class Gam-
maproteobacteria and phylum Proteobacteria (Fig.3 and Supplementary Table2) with time as the random
factor. e association with Gammaproteobacteria was observed when both treatment groups were included
in the model (LMM: P = 0.04, R2 = 0.08, R2random = 0.02). e association with Proteobacteria was observed
when both treatment groups were included (LMM: P = 0.017, R2 = 0.10, R2random = 0.029; Fig.3) and within
the experimental group (LMM: P = 0.045, R2 = 0.19, R2random = 0).
e study groups diered signicantly (LMM: P = 0.04, R2 = 0.08, R2random = 0.52) in the level of change
in the anti-inammatory cytokine TGF-β1 on Day28 (Day28 – Day0). e concentration of TGF-β1 (Fig.4 and
Supplementary Table1) increased in the experimental group and lowered in the control group. According to the
R2 –values, location (city) explains the result more (52%) than the treatment (8%) (Supplementary Fig.2). In
IL-10 levels, there were no signicant changes in connection to the treatments or health-associated bacterial taxa.
Figure1. Relative abundance of Lactobacillus spp. (mean ± SE). e relative abundance was calculated by
subsampling to the lowest sequence count in the samples (3893). e relative abundance on Day14 (Wilcoxon
P = 0.0058) and the amount of change (Day14–Day0) was higher in the experimental group.
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Regarding the living habits during the experiment and the background information, there were no signicant
dierences found between the treatment groups.
e changes observed in this green wall study were connected to Proteobacteria and Lactobacillus that have been
shown to be benecial for human health. As far as we are aware of, this is the rst study that shows a change
in the relative abundance of Lactobacillus spp. on skin in response to green wall exposure. e bacteria from
Lactobacillaceae family (such as Lactobacillus spp.) are known to act against pathogens and inammation on
skin30,60. eir application as a probiotic on skin has been recommended in the treatment of sunburns61, skin
oxidative damage and hyperpigmentation62. erefore, the observed steady and continuous increase in the
Figure2. Shannon diversity index of class Gammaroteobacteria (a) and phylum Proteobacteria (b) on
days 0, 14 and 28 for the experimental group (Exp) and the control group (Ctrl). e change in Shannon
diversity (Day28–Day0) diered between treatment groups in Proteobacteria and (LMM: P = 0.04, R2 = 0.02,
R2random = 0.67) and Gammaproteobacteria (LMM: P = 0.02, R2 = 0.03, R2random = 0.66).
Figure3. Shannon diversity (y-axis) in phylum Proteobacteria on skinassociated with IL-17A concentration
(pg/ml) in blood (x-axis) among Lahti participants. High Shannon diversity of Proteobacteria was associated to
a low levels of proinammatory IL-17A concentration (LMM: P = 0.017, R2 = 0.10, R2random = 0.029).
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relative abundance of skin Lactobacillus is an important nding. Spending time in green wall rooms seems to
be related to increasing abundance of health-supporting skin microbiota within a relatively short time period
of two weeks. is support health benets of working in rooms having green walls with air circulation system;
usually green wall are long-term interior design elements.
e diversity of Proteobacteria and Gammaproteobacteria has been observed to be higher among healthy
people compared to people with immune-mediated diseases such as atopy and allergies4,7,25. e diversity of Gam-
maproteobacteria on skin has successfully been altered via biodiversity intervention with an impact to immune
regulation12,13. e elevation in the diversity of proteobacterial taxa on the skin of participants working in the
green wall oces of this study makes sense because Proteobacteria are a common part of plant microbiomes.
However, the elevation was observed only in Lahti (17 study subjects), and according to the R2 values regarding
proteobacterial taxa, city as a factor had a high eect on the results. As seen in Fig.3, the plausible reason for the
dierence in IL-17A level is the increasing proteobacterial abundance in Lahti experimental group. An inter-
esting detail is that graphically even Day0 values were slightly higher in Lahti, though there were no statistical
dierence (Fig.3). In Tampere, all study rooms were situated in the area of Tampere University Hospital, whereas
in Lahti the study rooms were at two separate campus areas (in the city center and between industrial areas)
without a connection to medical sciences. erefore, the daily hygiene practices were probably dierent between
the oce workers at the medical campus in Tampere and the two non-medical campuses in Lahti. Due to the
dierences in the location, the surroundings of the study buildings may also have dierent hygiene levels which
aects microbial diversity1,4. Further, the building in Tampere was built in 2016 whereas the buildings Lahti were
considerably older (built 1993 and 1980); the age of a building aects the indoor microbiome composition26. A
third, potentially parallel explanation is that microbial communities in oces are city-specic18,19; it is tempting
to speculate whether the impact of city is strong enough to mask subtle changes in the relative abundance of
e current study was not designed to explore the mechanisms that lead to changes in skin microbiota. Our
hypothesis is that green walls balance air moisture and release spores or live bacteria that land on skin17. How-
ever, we cannot separate the role of the introduced microbiome from the green walls from the consequences
of the removal of volatile organic compounds (VOC) by the green walls; the green walls used in this study
remove VOCs46. Since VOCs are known to aect the composition and processes of bacterial communities in
the environment63,64 and on skin65, the green walls could have an indirect impact to indoor and skin bacterial
communities. VOCs include pollutants released from materials used in interior decoration46 but they also include
compounds emitted by organisms which may use them for interaction65. For example, skin bacteria may inhibit
one another via VOCs66. erefore, the green walls may remove VOCs that would otherwise impact the bacte-
rial communities indoors and on skin. To distinguish the mechanism responsible for altered skin microbiota,
the microbiome of the green walls should be sampled and the VOC composition in the study rooms should be
Since IL-17A is a proinammatory cytokine associated with adverse health outcomes, like low-grade
inammation67, the association between the high proteobacterial diversity and the low IL-17A concentration
seems benecial. In addition, the change of anti-inammatory cytokine TGF-β1 in the experimental group on
Day28 seems benecial due to the gain of concentration. As with bacterial results, the cytokine results were
impacted by the random factors (city and study subject). Individual dierences are typically large when the
study subjects live outside lab conditions. However, this does not diminish the importance of the observed dif-
ference between the experimental and control group; based on our results, air-circulating green walls change
skin microbial communities among urban dwellers.
Although access to nature outside workhours was permitted, the hours spent in nature was surveyed on Day14
and Day28 and no dierence was found between the experimental and control group. erefore, it seems unlikely
that free time in nature was sucient to overcome the eect of green walls. e access to other study oces was
Figure4. e concentration of the cytokine TGF-β1 (ng/ml) increased in the experimental group and
decreased in the control group on Day28 in comparison to Day0 (LMM: P = 0.04, R2 = 0.08, R2random = 0.52) in
the level of change in the anti-inammatory cytokine TGF-β1 on Day28 (Day28–Day0).
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not restricted (contamination) but visits to other oces were either very short or nonexistent; the typical places
of interaction were the coee rooms.
Based on our ndings, air-circulating green walls alter the microbiome and modulate the immune system
among oce workers. Air-circulating green walls have potential in promoting microbiological diversity and
human health in built environments and the topic requires further research attention.
Data availability
Raw sequencing data has been deposited to the Sequence Read Archive (SRA) under BioProject PRJNA757748.
e sensitive data that support the ndings of this study are available from University of Helsinki but restrictions
dened in General Data Protection Regulation (EU 2016/679) and Finnish Data Protection Act 1050/2018 apply
to the availability of these data, and so are not publicly available. Data are, however, available from the authors
upon reasonable request and with permission from the ethical committee of the local hospital district (Ethical
statement number R18026 by Tampereen yliopistollisen sairaalan erityisvastuualue, Pirkanmaa, Finland, the full
trial protocol can be requested from the authors).
Received: 21 September 2021; Accepted: 29 March 2022
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We thank the participants of this study for their time and input. is study was funded by Business Finland (grant
numbers 6766/31/2017 and 7941/31/2017) (grant to A.S. and H.H) and Doctoral Programme in Interdisciplinary
Environmental Sciences (DENVI) in the University of Helsinki, and supported by Naava who provided the green
walls for this study. We thank Environmental Laboratory at University of Helsinki, CSC – IT Center for Science,
Finland, for computational resources, and Institute for Molecular Medicine Finland (FIMM) for their work.
Author contributions
A.S., H.H., O.H.L., R.P., M.I.R., and N.N. wrote the ethical application for the study. L.S. wrote the rst dra of
the manuscript. N.N. performed the cytokine analyses. L.S and M.I.R performed the bioinformatic and statistical
analyses and prepared the gures. L.S., R.P., M.I.R., A.S., N.N., and O.H.L. implemented the study. L.S., M.I.R.,
A.S., R.P., N.N., H.H., and O.H.L. wrote the nal version of the manuscript. A.S. and H.H. were the principal
investigators of the project.
Scientic Reports | (2022) 12:6518 |
Competing interests
A.S., H.H. and O.H.L are members of the board of Uute scientic LtD which develops topical immunomodula-
tory treatments.
Additional information
Supplementary Information e online version contains supplementary material available at https:// doi. org/
10. 1038/ s41598- 022- 10432-4.
Correspondence and requests for materials should be addressed to A.S.
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© e Author(s) 2022
ADELE research group
Damiano Cerrone2, Mira Grönroos1, Nan Hui1, Anna Luukkonen3, Iida Mäkelä1,
Noora Nurminen2, Sami Oikarinen2, Anirudra Parajuli1, Riikka Puhakka1,3, Marja I. Roslund1,
Mika Saarenpää1, Laura Soininen1, Yan Sun1, Heli K. Vari1, Olli H. Laitinen2, Juho Rajaniemi2,
Heikki Hyoty2 & Aki Sinkkonen3
... The health effects of the compositions, functions, and dynamics of indoor microbiota are being studied to an increasing extent. Over the past decade, widespread and affordable large-scale, culture-independent, highthroughput metagenomic, and metatranscriptomic sequencing of DNA and RNA, respectively, has opened up new possibilities for identifying microbial communities that are beneficial or harmful to health, especially with the addition of immune response data gathered from indoor residents exposed to certain microbial communities (Kelley and Gilbert, 2013;Byrd et al., 2018;Boers et al., 2019;Soininen et al., 2022). Microbial ecology tools, such as microbial community diversity metrics of targeted and shotgun metagenomic sequencing data, have improved the possibility of understanding microbiota dynamics (Birtel et al., 2015;Horve et al., 2020). ...
... Working in an office with a green wall was associated with an increased relative abundance of beneficial skin bacteria, such as the genus Lactobacillus, and an increase in the Shannon diversity of phylum Proteobacteria and class Gammaproteobacteria. These findings support the idea that plant elements in an urban environment can alter residents' microbiomes and immune responses and may promote health in built environments (Chapat et al., 2004;Soininen et al., 2022). However, more research is needed to provide sufficient evidence of the effects of nature-derived microbes on human health, taking allergic reactions into consideration (Tischer et al., 2022). ...
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Indoor residents are constantly exposed to dynamic microbiota that have significant health effects. In addition to hand hygiene, cleaning, and disinfection, antimicrobial coatings (AMCs) can prevent the spread of infectious diseases in public areas. The sustainable use of antimicrobial-coated products requires an assessment of their pros and cons for human health and the environment. The toxicity and resistance risks of AMCs have been considered, but large-scale genetic studies on the microbial community compositions and resistomes of AMCs are scarce. The use of an AMC can reduce the total number of microbes on a surface but poses the risk of dysbiosis, microbial imbalance, such as the polarized growth of metallophilic, metal- and antimicrobial-resistant, and other survivor bacteria, and the overall reduction of microbial diversity. Loss of diversity may lead to the enrichment of harmful bacteria and an increased risk of communicable or immunological non-communicable inflammatory diseases (NCDs). In public buildings, such as kindergartens and nursing homes for the elderly, the use of AMCs is likely to increase due to epidemics and pandemics in recent years. Therefore, comprehensive metagenomic research is needed to monitor the effects of AMCs on indoor microbial community compositions and functions. Although the determination of good indoor microbiota and homeostasis is difficult, microbial communities that have health-protective or harmful effects can and should be identified using a metagenomic sequencing approach before the large-scale implementation of AMCs.
... Microbiomes can also play a role in the health and functioning of buildings. In an encouraging example, indoor air-circulating "green walls" have been shown to increase bacterial abundance and diversity on the skin of office workers with an associated lowering of proinflammatory blood cytokine measurements [192]. In children, using microbiomeenriched soils (from forest floors) in daycare yards increases both environmental and skin microbial diversity which, in turn, is associated with favorable immunological effects [193]. ...
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The vast and growing challenges for human health and all life on Earth require urgent and deep structural changes to the way in which we live. Broken relationships with nature are at the core of both the modern health crisis and the erosion of planetary health. A declining connection to nature has been implicated in the exploitative attitudes that underpin the degradation of both physical and social environments and almost all aspects of personal physical, mental, and spiritual health. It is increasingly clear that the entwined challenges of biodiversity loss, climate change, and human health cannot be addressed without addressing selfishness, greed, apathy, and the value systems that created these global problems. Calls for a spiritual and cultural transformation recognize that “inner” development is important and necessary for meaningful “outward” transitions with a shared purpose for wiser, more sustainable societies. Many of these emotional and spiritual assets appear to be facilitated by a connection to nature, which is also strongly associated with community cohesion, prosocial attitudes, and pro-environmental actions. Restoring the human connection to nature may therefore provide a critical common pathway to promote the physical and spiritual wellbeing of individuals and communities as well as personal and social environmental responsibility. In this paper, we summarize and reflect on the discussions of the Nova Network planetary health community with respect to nature-based solutions as pathways to promote both personal and planetary health with a more mutualistic mindset. These discussions spanned biological to psychological interactions with nature—including the critical relationships with environmental microbes that influence the physical, emotional, and behavioral aspects of health. We consider the ways in which stronger relationships with nature promote “inner assets” to support “outward actions” for personal and planetary health.
... Environmental microbial exposure, human commensal microbiota, and immunological pathways are generally assumed to be interconnected. A high hygiene level and urban lifestyle may result in microbial imbalance, referred to as dysbiosis, which has been associated with immune-mediated diseases [4,[48][49][50][51]. ...
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Sport facilities represent extreme indoor environments due to intense cleaning and disin-fection. The aim of this study was to describe the composition of the cultivated microbiota in dust samples collected in sport facilities during the COVID-19 pandemic. A dust sample is defined as the airborne dust sedimented on 0.02 m 2 within 28 d. The results show that the microbial viable counts in samples of airborne dust (n = 9) collected from seven Finnish sport facilities during the pandemic contained a high proportion of pathogenic filamentous fungi and a low proportion of bacteria. The microbial viable counts were between 14 CFU and 189 CFU per dust sample. In seven samples from sport facilities, 20-85% of the microbial viable counts were fungi. Out of 123 fungal colonies, 47 colonies belonged to the potentially pathogenic sections of Aspergillus (Sections Fumigati, Nigri, and Flavi). Representatives of each section were identified as Aspergillus fumigatus, A. flavus, A. niger and A. tubingensis. Six colonies belonged to the genus Paecilomyces. In six samples of dust, a high proportion (50-100%) of the total fungal viable counts consisted of these potentially pathogenic fungi. A total of 70 isolates were considered less likely to be pathogenic, and were identified as Aspergillus section Nidulantes, Chaetomium cochliodes and Penicillium sp. In the rural (n = 2) and urban (n = 7) control dust samples, the microbial viable counts were >2000 CFU and between 44 CFU and 215 CFU, respectively, and consisted mainly of bacteria. The low proportion of bacteria and the high proportion of stress tolerant, potentially pathogenic fungi in the dust samples from sport facilities may reflect the influence of disinfection on microbial communities.
... Living walls are designed for providing an aesthetic focal point of an indoor space, at the same time, provide additional benefits such as air purification, healthy skin microbiota, or thermal regulation [15]. ...
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The reliance of modern society on indoor environments increasing has made them crucial sites for human exposure to microbes. Extensive research has identified ecological drivers that influence indoor microbial assemblages. However, few studies have examined the dispersion of microbes in different locations of identical indoor environments. In this study, we employed PacBio Sequel full-length amplicon sequencing to examine the distribution of microbes at distinct locations in a single home and to identify the potential pathogens and microbial functions. Microbial communities differed considerably among the indoor sampling sites (P < 0.05). In addition, bacterial diversity was influenced by human activities and contact with the external environment at different sites, whereas fungal diversity did not significantly differ among the sites. Potential pathogens, including bacteria and fungi, were significantly enriched on the door handle (P < 0.05), suggesting that door handles may be hotpots for potential pathogens in the household. A high proportion of fungal allergens (34.37 %-56.50 %), which can cause skin diseases and asthma, were observed. Co-occurrence network analysis revealed the essential ecological role of microbial interactions in the development of a healthy immune system. Overall, we revealed the differences in microbial communities at different sampling sites within a single indoor environment, highlighting the distribution of potential pathogens and ecological functions of microbes, and providing a new perspective and information for assessing indoor health from a microbiological viewpoint.
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One’s personal health and well-being can improve with activity in natural environments or decline without it. Many chronic illnesses to which personal nature deficiency contributes—including anxiety, depression, attention deficit, diabetes, hypertension, myopia, and obesity—have been exacerbated with the pandemic. That those illnesses may be preventable, treatable, and even reversible with an added nature-based approach may seem novel, but it is not. Though the field of nature-based medicine is just emerging in the U.S., it has been taught and practiced in Asia and the EU for decades. As the prescriptive, evidence-based use of natural settings and nature-based interventions, it aims to prevent and treat disease and improve well-being. Nature-based medicine blends particular activity in nature with the science of medicine to attempt to empower self-care safely, effectively, and happily. Its vision is to be readily available to all, regardless of proximity to blue (water-related) or green (land-related) space. The common sense of nature-based medicine belies its scientific evidence base, which is growing but not well-known, so it may seem unfamiliar to prescribe nature to patients. It will take education, training and practice to help patients access nature-based medicine and to help clinicians prescribe it.
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Background In modern urban environments children have a high incidence of inflammatory disorders, including allergies, asthma, and type 1 diabetes. The underlying cause of these disorders, according to the biodiversity hypothesis, is an imbalance in immune regulation caused by a weak interaction with environmental microbes. In this 2-year study, we analyzed bacterial community shifts in the soil surface in day-care centers and commensal bacteria inhabiting the mouth, skin, and gut of children. We compared two different day-care environments: standard urban day-care centers and intervention day-care centers. Yards in the latter were amended with biodiverse forest floor vegetation and sod at the beginning of the study. Results Intervention caused a long-standing increase in the relative abundance of nonpathogenic environmental mycobacteria in the surface soils. Treatment-specific shifts became evident in the community composition of Gammaproteobacteria, Negativicutes, and Bacilli, which jointly accounted for almost 40 and 50% of the taxa on the intervention day-care children’s skin and in saliva, respectively. In the year-one skin swabs, richness of Alpha-, Beta-, and Gammaproteobacteria was higher, and the relative abundance of potentially pathogenic bacteria, including Haemophilus parainfluenzae, Streptococcus sp., and Veillonella sp., was lower among children in intervention day-care centers compared with children in standard day-care centers. In the gut, the relative abundance of Clostridium sensu stricto decreased, particularly among the intervention children. Conclusions This study shows that a 2-year biodiversity intervention shapes human commensal microbiota, including taxa that have been associated with immune regulation. Results indicate that intervention enriched commensal microbiota and suppressed the potentially pathogenic bacteria on the skin. We recommend future studies that expand intervention strategies to immune response and eventually the incidence of immune-mediated diseases.
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We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities.
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Increase of allergic conditions has occurred at the same pace with the Great Accleration, which stands for the rapid growth rate of human activities upon Earth from 1950s. Changes of environment and lifestyle along with escalating urbanization, are acknowledged as the main underlying causes. Secondary (tertiary) preventionfor better disease control hasadvanced considerably with innovations for oral immunotherapy and effective treatment of inflammation with corticosteroids, calcineurin inhibitors and biologic medications. Patients are less disabled than before. However, primary prevention has remained a dilemma. Factors predicting allergy and asthma risk have proven complex: risk factors increase the risk while protective factors counteract them. Interaction of human body with environmental biodiversity with micro-organisms and biogenic compounds as well as the central role of epigenetic adaptation in immune homeostasis have given new insight.Allergic diseases are good indicators of the twisted relation to environment. In various non-communicable diseases, the protective mode of the immune system indicates low-grade inflammation without apparent cause.Giving microbes, pro- and prebiotics, has shownsome promise in prevention and treatment. The real-world public health programme in Finland (2008-2018) emphasized nature relatedness and protective factors for immunological resilience, instead of avoidance.The nationwide action mitigated the allergy burden, but in the lack of controls, primary preventive effect remains to be proven. The first results of controlled biodiversity interventions are promising. In the fastly urbanizing world, new approaches are called for allergy prevention, which also has a major cost saving potential.
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Objective: Environmental microbial exposures have been implicated to protect against immune-mediated diseases such as type 1 diabetes. Our objective was to study the association of land cover around the early-life dwelling with the development of islet autoimmunity and type 1 diabetes to evaluate the role of environmental microbial biodiversity in the pathogenesis. Research design and methods: Association between land cover types and the future risk of type 1 diabetes was studied by analyzing land cover types classified according to Coordination of Information on the Environment (CORINE) 2012 and 2000 data around the dwelling during the first year of life for 10,681 children genotyped for disease associated HLA-DQ alleles and monitored from birth in the Type 1 Diabetes Prediction and Prevention (DIPP) study. Land cover was compared between children who developed type 1 diabetes (n = 271) or multiple diabetes-associated islet autoantibodies (n = 384) and children without diabetes who are negative for diabetes autoantibodies. Results: Agricultural land cover around the home was inversely associated with diabetes risk (odds ratio 0.37, 95% CI 0.16-0.87, P = 0.02 within a distance of 1,500 m). The association was observed among children with the high-risk HLA-genotype and among those living in the southernmost study region. Snow cover on the ground seemed to block the transfer of the microbial community indoors, leading to reduced bacterial richness and diversity indoors, which might explain the regional difference in the association. In survival models, an agricultural environment was associated with a decreased risk of multiple islet autoantibodies (hazard ratio [HR] 1.60, P = 0.008) and a decreased risk of progression from single to multiple autoantibody positivity (HR 2.07, P = 0.001) compared with an urban environment known to have lower environmental microbial diversity. Conclusions: The study suggests that exposure to an agricultural environment (comprising nonirrigated arable land, fruit trees and berry plantations, pastures, natural pastures, land principally occupied by agriculture with significant areas of natural vegetation, and agroforestry areas) early in life is inversely associated with the risk of type 1 diabetes. This association may be mediated by early exposure to environmental microbial diversity.
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Man-made landscaping materials form uppermost soil layers in urban green parks and lawns. To optimize effects of landscaping materials on biodiversity, plant growth and human health, it is necessary to understand microbial community dynamics and physicochemical characteristics of the landscaping materials during storage. In the current three-year study, the consequences of long-term storage on biotic and abiotic characteristics of eight commercial landscaping materials were evaluated. We hypothesized that long-term storage results in changes in microbial utilization of various energy sources and the diversity and relative abundance of bacteria with pathogenic or immunomodulatory characteristics. Three-year storage led to remarkable changes in bacterial community composition. Diversity and richness of taxa associated with immune modulation, particularly phylum Proteobacteria and class Gammaproteobacteria, decreased over time. Bacteroidetes decreased while Actinobacteria increased in relative abundance. Functional orthologs associated with biosynthesis of antibiotics and degradation of complex carbon sources increased during storage. Relative abundance of genera containing potential pathogens were mostly constant or decreased with time. Major changes can be explained by tightening competition over lessening resources. Bacterial communities in landscaping materials adjust to absent inflow of carbon and nutrients during storage. The increased signalling of functional orthologs related to degradation of complex carbon sources hints that bacteria dependent on labile carbon and readily available nutrients were outcompeted. This suggests storage reduces plant seedling growth. Long-term storage seems to decrease immunomodulatory potential of landscaping materials, but storage did not enrich pathogens or functional orthologs associated with pathogenicity. We recommend short storage and shelf life of organic landscaping materials.
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There is evidence that polycyclic aromatic hydrocarbons (PAHs) and human gut microbiota are associated with the modulation of endocrine signaling pathways. Independently, studies have found associations between air pollution, land cover and commensal microbiota. We are the first to estimate the interaction between land cover categories associated with air pollution or purification, PAH levels and endocrine signaling predicted from gut metagenome among urban and rural populations. The study participants were elderly people (65–79 years); 30 lived in rural and 32 in urban areas. Semi-Permeable Membrane devices were utilized to measure air PAH concentrations as they simulate the process of bioconcentration in the fatty tissues. Land cover categories were estimated using CORINE database and geographic information system. Functional orthologues for peroxisome proliferator-activated receptor (PPAR) pathway in endocrine system were analyzed from gut bacterial metagenome with Kyoto Encyclopaedia of Genes and Genomes. High coverage of broad-leaved and mixed forests around the homes were associated with decreased PAH levels in ambient air, while gut functional orthologues for PPAR pathway increased along with these forest types. The difference between urban and rural PAH concentrations was not notable. However, some rural measurements were higher than the urban average, which was due to the use of heavy equipment on active farms. The provision of air purification by forests might be an important determining factor in the context of endocrine disruption potential of PAHs. Particularly broad-leaved forests around homes may reduce PAH levels in ambient air and balance pollution-induced disturbances within commensal gut microbiota.
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As the incidence of immune-mediated diseases has increased rapidly in developed societies, there is an unmet need for novel prophylactic practices to fight against these maladies. This study is the first human intervention trial in which urban environmental biodiversity was manipulated to examine its effects on the commensal microbiome and immunoregulation in children. We analyzed changes in the skin and gut microbiota and blood immune markers of children during a 28-day biodiversity intervention. Children in standard urban and nature-oriented daycare centers were analyzed for comparison. The intervention diversified both the environmental and skin Gammaproteobacterial communities, which, in turn, were associated with increases in plasma TGF-β1 levels and the proportion of regulatory T cells. The plasma IL-10:IL-17A ratio increased among intervention children during the trial. Our findings suggest that biodiversity intervention enhances immunoregulatory pathways and provide an incentive for future prophylactic approaches to reduce the risk of immune-mediated diseases in urban societies.
The human skin microbiota forms a key barrier against skin pathogens and is important in modulating immune responses. Recent studies identify lactobacilli as endogenous inhabitants of healthy skin, while inflammatory skin conditions are often associated with a disturbed skin microbiome. Consequently, lactobacilli-based probiotics are explored as a novel treatment of inflammatory skin conditions through their topical skin application. This review focuses on the potential beneficial role of lactobacilli (family Lactobacillaceae) in the skin habitat, where they can exert multifactorial local mechanisms of action against pathogens and inflammation. On one hand, lactobacilli have been shown to directly compete with skin pathogens through adhesion inhibition, production of antimicrobial metabolites, and by influencing pathogen metabolism. The competitive anti-pathogenic action of lactobacilli has already been described mechanistically for common different skin pathogens, such as Staphylococcus aureus, Cutibacterium acnes, and Candida albicans. On the other hand, lactobacilli also have an immunomodulatory capacity associated with a reduction in excessive skin inflammation. Their influence on the immune system is mediated by bacterial metabolites and cell wall-associated or excreted microbe-associated molecular patterns (MAMPs). In addition, lactobacilli can also enhance the skin barrier function, which is often disrupted as a result of infection or in inflammatory skin diseases. Some clinical trials have already translated these mechanistic insights into beneficial clinical outcomes, showing that topically applied lactobacilli can temporarily colonize the skin and promote skin health, but more and larger clinical trials are required to generate in vivo mechanistic insights and in-depth skin microbiome analysis.
Exposure to biodiverse environments such as forests can benefit human well-being, and evidence suggests exposure to high microbial diversity may improve mental and immune health. However, the factors that drive microbial community assembly are poorly understood, as is the relationship between exposure to these communities and human health. We characterized airborne bacterial communities in two disparate types of urban greenspace (forest and grass) in late-spring 2017 at sites previously sampled in late-summer 2015 in Eugene-Springfield, Oregon, using high-throughput metabarcode sequencing. While all sites shared a core aerobiome in late-spring consisting of plant- and soil-associated genera, forests had significantly higher diversity than grass sites (F = 12, P = 0.004). Vegetation type explained 14% of the difference between forest and grass aerobiomes, yet individual site location explained 41% of the variation. These results were similar to but amplified over those from late summer, suggesting that both aerobiome diversity and vegetation-driven effects are higher when deciduous foliage is fresher and more active, temperatures cooler, and humidity higher. Continued exploration and hypothesis-driven research will enable development of mechanistic theory describing key drivers of urban aerobiome assembly and its relationship to human health, which, in turn, will help urban designers and planners create evidence-based salutogenic cities for future generations.
Over half of people live in cities and while urban environments offer myriad social, cultural and economic benefits, they alter the microbial communities to which people are exposed: with potentially important but underexplored health impacts. In particular, higher rates of asthma and allergies in urban areas have been linked to urban-altered microbial communities – including aerial microbial communities. To date, however, there has been no synthesis of the disparate literature on the impacts of urbanisation on aerial microbial communities, making it difficult to ascertain potential health impacts. We fill this knowledge gap by systematically examining studies that compare the characteristics (e.g. microbial abundance/diversity) and/or health effects of airborne fungal and bacterial communities (hereafter referred to as ‘aerobiomes’) across urban and rural locations. We included 19 studies, with 31 distinct urban-rural comparisons, in our analysis. We found that rural aerobiomes more often have a greater abundance of microbes (57% of studies). Aerobiome diversity was under-reported but when comparisons were made, rural aerobiome diversity was often higher (67%). Only two studies experimentally examined the impact of urban and rural aerobiomes on human health outcomes; both found rural aerobiomes shifted immune function away from allergic (Th2-type) responses. Overall, we conclude that significant gaps remain in our understanding of how urbanisation impacts aerobiomes and the health implications of those changes. We highlight the need to standardise methods and make aerobiome data open access to facilitate cross-study comparisons. Further mechanistic studies are urgently needed to examine the impact of aerobiome composition on immune function to demonstrate how urban-driven changes to the aerobiome impact human health – ultimately facilitating the development of healthier cities.