atmosphere
Article
Aerosol Microbiome over the Mediterranean Sea
Diversity and Abundance
Esra Mescioglu 1, * , Eyal Rahav 2 , Natalia Belkin 2 , Peng Xian 3 , Jordan M. Eizenga 4 ,
Ania Vichik 2 , Barak Herut 2 and Adina Paytan 5
1
2
3
4
5
*
Earth and Planetary Science, University of California, Santa Cruz, CA 95060, USA
Israel Oceanographic and Limnological Research, National Institute of Oceanography, Haifa 3108000, Israel
Marine Meteorology Division, Naval Research Laboratory, 7 Grace Hopper Avenue, Monterey, CA 93940,
USA
Biomolecular Engineering, University of California, Santa Cruz, CA 95060, USA
Institute of Marine Science, University of California, Santa Cruz, CA 95060, USA
Correspondence: Emesciog@ucsc.edu
Received: 18 June 2019; Accepted: 24 July 2019; Published: 1 August 2019
Abstract: Prokaryotic microbes can become aerosolized and deposited into new environments located
thousands of kilometers away from their place of origin. The Mediterranean Sea is an oligotrophic to
ultra-oligotrophic marginal sea, which neighbors northern Africa (a major source of natural aerosols)
and Europe (a source of mostly anthropogenic aerosols). Previous studies demonstrated that airborne
bacteria deposited during dust events over the Mediterranean Sea may significantly alter the ecology
and function of the surface seawater layer, yet little is known about their abundance and diversity
during ‘background’ non-storm conditions. Here, we describe the abundance and genetic diversity of
airborne bacteria in 16 air samples collected over an East-West transect of the entire Mediterranean Sea
during non-storm conditions in April 2011. The results show that airborne bacteria represent diverse
groups with the most abundant bacteria from the Firmicutes (Bacilli and Clostridia) and Proteobacteria
(Alphaproteobacteria, Betaproteobacteria, and Gammaproteobacteria) phyla. Most of the bacteria in
our samples have previously been observed in the air at other open ocean locations, in the air over
the Mediterranean Sea during dust storms, and in the Mediterranean seawater. Airborne bacterial
abundance ranged from 0.7 × 104 to 2.5 × 104 cells m−3 air, similar to abundances at other oceanic
regimes. Our results demonstrate that airborne bacterial diversity is positively correlated with
the mineral dust content in the aerosols and was spatially separated between major basins of the
Mediterranean Sea. To our knowledge, this is the first comprehensive biogeographical dataset to
assess the diversity and abundance of airborne microbes over the Mediterranean Sea. Our results
shed light on the spatiotemporal distribution of airborne microbes and may have implications for
dispersal and distribution of microbes (biogeography) in the ocean.
Keywords: bioaerosols; airborne bacteria; Mediterranean Sea; aeromicrobiology
1. Introduction
Prokaryotic microorganisms are found in the air over the global ocean in substantial numbers,
with a median abundance of 6.7 × 103 m−3 air [1] and are referred to as ‘airborne microbes’.
These airborne microbes can originate from both land [2,3] and the ocean [4,5]. Upon aerosolization,
wind can transport microbes over great distances, including across large ocean basins and seas [6–10].
The residence time of microbes in the air can reach up to seven days [1], which enables them to cross
thousands of kilometers. Airborne, microbes can be exposed to atmospheric oxidant gases [11] and
meteorological factors, like variable temperatures and UV radiation [12], that can cause cell damage
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and reduce their viability. However, up to ~20% of these airborne microbes remain viable during
atmospheric transport [13], and this has important implications for receiving ecosystems. Airborne
microbes are deposited with dry (aerosol particles) or wet (rain) atmospheric deposition back onto
Earth’s surface, including the surface of the ocean [9,14,15].
Airborne microbes include a diverse array of organisms, and their deposition can impact human
health through spreading infectious diseases [16], agriculture through dispersal of plant pathogens [17],
and ecosystem productivity and function through introduction of new organisms [18]. Recently, it was
shown that abundance of microbes in outdoor air can be influenced by seasons, with Bragoszewska
and Pastuszka [12] reporting highest abundance in spring and Kaarakainen et al. [19] reporting
highest abundance in the summer. Interestingly, certain bacterial species, like Streptomyces and
Cladosporium, have stronger temperature and seasonal variation than other species, like Penicillium
and Aspergillus [19]. The diversity of microbes in outdoor air has also been shown to vary between
environments [19], yet there are only a few studies investigating airborne microbes over the ocean.
The few studies conducted so far indicate that airborne microbes are found ubiquitously over
marine environments, but their abundance, diversity, and the factors driving their diversity are still
poorly studied [3,20].
The Mediterranean Sea (MS) is an ideal marine environment to study airborne microbes. The MS
is a low-nutrient low-chlorophyll (LNLC) ecosystem [21,22], and the surrounding landmasses provide
ample aerosols: The densely populated land to the north is a source of anthropogenic aerosols, and the
arid land to the south is a source of mineral dust [20]. The effects of the high atmospheric deposition in
this basin (1–50 g dust m−2 y−1 [23]) has been studied extensively and shown to be important chemically,
providing limiting micro (e.g., Fe, Zn) and macro (e.g., N, P) nutrients to the MS [24–27]. These leached
nutrients support primary production in the mixed layer of the MS [28] and can stimulate N2 fixation,
which may induce further primary production [28,29]. In addition to leached nutrients and trace metals,
atmospheric deposition has been shown to add viable microbes to the MS [30]. These airborne microbes
can fix N2 and utilize organic carbon (i.e., leucine) in seawater after deposition [30]. Therefore, airborne
microbes may have an important contribution to the ecology of MS waters, with ecological implications
for other LNLC settings receiving high atmospheric deposition, such as the North Atlantic Ocean.
Most studies investigating airborne microbes over the MS have focused on determining their
diversity and abundance during dust storm events [20]. These studies showed that during storm
events, airborne microbial abundance increases, and diversity is dependent on source [31,32]. However,
it is also important to evaluate these variables during background conditions (clear days), which are
far more common than dust storms events. Understanding background conditions may help identify
what is unique about storm events that have resulted in measurable changes in the receiving water
following deposition events [20]. Moreover, identifying airborne microbes and the factors driving
their diversity over the ocean during background conditions may further our understanding of the
mechanisms of bioaerosol dispersion, with possible implications for biogeography.
In this study, we analyzed aerosol samples collected at all major basins of the MS (Levantine,
Ionian Sea, Tyrrhenian Sea, Algero-Provencal basin, Alboran Sea) during “normal” background
non-dust-storm conditions in April 2011 (spring). We analyzed the microbial diversity using 16S
rRNA sequencing and microbial abundance using microscopy. Due to the proximity of the MS to
terrestrial sources of aerosols, we hypothesized that we would find a high number of airborne bacteria
comprising a diverse community. We further hypothesized that this community would encompass
both marine and terrestrial microbes.
2. Methods and Materials
2.1. Sampling
Samples were collected aboard the R/V Meteor (cruise M84/3) during an east to west transect in the
MS from 6th to 28th April 2011 (Figure 1). Aerosols were collected in all major basins onto Whatman
Atmosphere 2019, 10, 440
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41 filters for 24 h using a high-volume sampler pumping air at 42 m3 h−1 [30]. − The sampler was
positioned at the front of the ship (to reduce collection of ship emissions) and samples were processed
in an aerosol designated laboratory. Volumes of air pumped, and the start and end coordinates of
sample collection were recorded (Supplementary Table S1). The filters were frozen and kept at −80 ◦ C
until processing.
−
Z1
Z2
14 13
16
12
11 10
15
9
Z3
Eastern Med
Central Med
Western Med
8 7
6
5 4 3 2 1
Z4
Figure 1. Map of the sites where aerosols were collected throughout the Mediterranean Sea (MS) in
April on the R/V METEOR cruise M84/3, with sample IDs, region of collection (eastern Med = blue,
central Med = red, and western Med = black), and airmass origin zones (Z1Z4)
shown.
–
2.2. Aerosol Optical Depth
To assemble additional information about the aerosols present over the MS at the time of
sample collection, we used a global 1 × 1 degree and six-hourly 550 nm aerosol optical depth
(AOD, an approximate measure of total atmospheric column of aerosol mass) reanalysis product
that was developed and validated at the Naval Research Laboratory, CA, USA [33]. The core model
of this aerosol reanalysis product is the Navy Aerosol Analysis and Prediction System (NAAPS),
which characterizes anthropogenic and biogenic fine aerosol species (ABF, including pollutions from
industry, fossil fuel and biofuel, and organic aerosols), dust, biomass-burning smoke and sea salt
aerosols. The reanalyzed aerosol fields were obtained by running NAAPS with the assimilation of
quality-controlled retrievals of AOD from moderate resolution imaging spectroradiometer (MODIS)
on Terra and Aqua and the multi-angle imaging spectro radiometer (MISR) on Terra [34–36]. The fine
and coarse mode AOD at 550 nm from the reanalysis is shown to have good agreement with the
ground-based global scale sun photometer Aerosol Robotic Network (AERONET) observations
regionally and seasonally [33]. Speciated AOD data were extracted (with the nearest neighbor method)
from the NAAPS reanalysis along the ship track for the study period. Correlational relationships were
analyzed between bacterial abundance and diversity and ABF, dust and total AODs, to compare to
studies that have found increased abundances of bacteria associated with elevated pollution [37] and
dust [38] levels.
2.3. Air Mass Backward Trajectories
Seventy-two-hour isentropic back trajectories were constructed from the National Oceanic and
Atmospheric Administration (NOAA) database using the hybrid single-particle Langrangian integrated
trajectories (HYSPLIT) program [39]. Back trajectories for elevations 50, 250, and 500 m were computed
using the GPS coordinates of the midpoint between the start and end locations of sampling for each filter
Atmosphere 2019, 10, 440
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(Supplementary Table S1, Supplementary Figure S1). The samples were assigned to one of four origin
zones according to the geographic location from which the airmass originated, as determined from
the backward trajectory model results (Table 1, Supplemental Figure S1). The four zones are Western
Europe (Z1), Eastern Europe (Z2), Mediterranean Sea (Z3), Northern Africa (Z4) (Figure 1). Note that
in some cases the airmass crossed more than one zone during collection (Supplemental Figure S1).
Table 1. Sample ID, region of the MS samples were collected from, airmass origin of samples based on
HYSPLIT back trajectory models (Z1 = Western Europe, Z2 = Eastern Europe, Z3 = Mediterranean Sea,
and Z4 = Northern Africa), distance between the sampling site to the closest landmass or island (km),
total aerosol optical depth (AOD), aluminum concentrations (ng m−3 air), number of OTUs observed,
and Shannon’s Diversity Index (H) are shown for each sample.
Sample ID
Region
Airmass
Origin
Distance from
Land (km)
Total
AOD
Aluminum (ng
m−3 air)
Observed
OTUs
Shannon’s
Index (H)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Eastern
Eastern
Eastern
Eastern
Eastern
Central
Central
Central
Central
Central
Central
Western
Western
Western
Western
Western
Z2
Z3
Z3
Z3
Z1
Z1
Z1
Z1
Z2
Z2
Z1
Z4
Z4
Z4
Z4
Z1
155
154
102
204
156
78
213
288
48
112
49
135
126
56
36
42
0.282
0.285
0.22
0.224
0.196
0.233
0.225
0.133
0.18
0.115
0.147
0.359
0.252
0.134
0.2
0.11
569
516
331
410
205
220
661
404
134
41
104
196
172
395
355
103
241
158
100
141
119
95
96
92
66
76
96
164
82
70
108
75
7.48
6.76
6.06
6.41
5.94
5.75
6.03
5.89
5.17
5.64
6.04
6.83
5.83
5.7
6.37
5.79
2.4. Region and Distance to Land
Samples were grouped according to the location of collection (Figure 1, Table 1) in order to
determine if the diversity was influenced by location and if proximal sites had similar diversity.
We also measured the distance from the closest landmass, including islands, at five points of sampling
(beginning, quarter-point, midpoint, three-quarters point, and end) for each sample, and used the
average of the five values as the distance from land in our analysis (Table 1).
2.5. Aluminum
After collection, a subsample of the Whatman 41 filters was dried in a desiccator for 24 h before
being reweighed. Filters were digested with hydrogen fluoride (HF) following the procedure of ASTM
(1983) [27]. Aluminum (Al) concentrations in the bulk digest were measured on an atomic absorption
spectrometer Agilent 280FS AA and graphite furnace Agilent 240Z AA.
2.6. Bacterial Abundance
Subsamples from each of the filters were cut with sterile scissors (3 × 3 cm), placed into 5 mL
of sterile MS water, and fixed with ultrapure glutaraldehyde solution (Sigma, St. Louis, MO USA,
final concentration 0.02% v:v). The filters were sonicated for 5 min to detach organisms from the filter,
stained with SYBR green solution (Applied Biosystems, Foster City, CA USA), and filtered through
a 0.2 µm polycarbonate filter (PALL). The filters were placed on a microscope slide, and bacterial cells
were enumerated using epifluorescence microscopy (Olympus BH12). The values were normalized to
the area of the whole filter (17 × 23 cm) and divided by the volume of air pumped during collection
to determine the number of cells per m3 of air. SYBR green is a robust bacterial stain [40] used in
numerous microbiology studies, including aeromicrobiology studies [1,41]. We used microscopy-grade
SYBR, so the introduction of counting errors is unlikely.
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2.7. DNA Extraction, Amplification, Sequencing
Subsamples from each of the filters were cut with sterile scissors (2 cm × 2 cm), and total DNA
was extracted in triplicates using the phenol chloroform method, modified from Massana et al. [42].
The triplicates were pooled into one sample to ensure enough DNA for sequencing. The DNA was
sent to Mr. DNA Molecular Research Laboratories. Polymerase chain reaction (PCR) using primers
515 (forward) and 806 (reverse) to amplify 16S rRNA, with barcodes on the forward primer, were carried
out using the HotStarTaq Plus master mix kit (Qiagen, Valencia, CA USA). The conditions of the
protocol were as following: 94 ◦ C for 3 min, 28 cycles of 94 ◦ C for 30 s, 53 ◦ C for 40 s and 72 ◦ C for
1 min, and a final elongation step at 72 ◦ C for 5 min. PCR products were visualized in 2% agarose
gel using electrophoresis to confirm successful amplification. The samples were pooled together in
equal proportions (based on their molecular weight and DNA concentrations), purified using calibrated
Ampure XP beads, and used to prepare libraries using a Nextera DNA sample preparation kit (Illumina,
Foster City, CA USA). Libraries were loaded to a 600 cycles v3 reagent cartridge (Illumina) and the
sequencing was performed on Miseq (Illumina). DNA extraction and amplification protocols were
repeated for blank filters brought onboard the cruise and treated similarly to the samples, and the PCR
products were checked by electrophoresis. The electrophoresis visualization showed no amplification
bands indicating there was no contamination by the filters (i.e., no microbes present on the blank filters).
2.8. Bioinformatics
Samples were processed using the open-source Quantitative Insights into Microbial Ecology 2
(QIIME 2) pipeline [43]. Sequences were demultiplexed and barcodes were trimmed using the cutadapt
plugin [44]. Data were denoised using dada2 [45], sequences were clustered into amplicon sequence
variants (ASVs) which can be thought of as 100% operational taxonomic units (OTUs). Taxonomic
classifier was trained [46] using Greengenes [47]. Taxonomies were assigned using the Naive Bayes
method [48]. Samples were filtered to remove sequences identified as mitochondria and chloroplast.
Alpha-diversity metrics, observed OTUs and Shannon’s diversity index [H] [49], beta diversity metrics
(weighted UniFrac [50]), and principle coordinate analysis (PCoA) were estimated using q2-diversity
after samples were rarefied (subsampled without replacement). The samples were grouped according
to the location in which they were collected in the MS (i.e., region) (Figure 1) and the origin of the
air mass (Figure 1) to test how abundance, richness, and diversity were influenced by these factors.
Weighted UniFrac distances (a quantitative measure of community dissimilarity that incorporates
phylogenetic relationships between the bacteria) were used to generate the PCoA plots. Associations
between regions of sample collection and UniFrac were tested using PERMANOVA [51] to investigate
whether microbial communities in samples within a region (e.g., Eastern MS) were more similar to each
other than they were to samples from the other regions (e.g., Central MS and Western MS). We also
tested for any association between geographical distances and community dissimilarity (weighted
UniFrac) using the Mantel test. To simplify visualization of relative abundance, we clustered bacteria
into two categories based on their relative abundance in our samples: (1) “Common” bacteria (families
that made up more than 5% of at least 1 sample) (Table 2), and (2) “rare” bacteria which did not meet
the 5% relative abundance threshold (Table 3).
3. Results and Discussion
3.1. Aerosol Origin and Chemical Properties
The aerosol optical depth (AOD) data derived from the Navy Aerosol Analysis and Prediction
System (NAAPS) AOD reanalysis, as described in the methods section are shown in Figure 2. Total
AOD, which includes mineral dust, anthropogenic and biogenic fine aerosol species (ABF), smoke,
and sea salt, during the cruise ranged from 0.11 to 0.36, with the lowest values measured during
collection of sample 16 and the highest measured during collection of sample 12, both collected from
the Western MS (Figures 1 and 2, Table 1). ABF and mineral dust were the main contributors to the
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total AOD during our study, together comprising between 60% and 88% of total AOD. Smoke and sea
salt estimates from the NAAPS model were both relatively low in concentration and evenly distributed
in all the samples. Smoke and sea salt contributed only to a small portion of total AOD during our
sampling period, and thus were not included in further analysis.
Aerosol Optical Depth
0.3
Aerosol type
0.2
ABF
Dust
Sea Salt + Smoke
0.1
0.0
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
Sample ID
Figure 2. Aerosol optical depth (AOD) from Navy Aerosol Analysis and Prediction System (NAAPS)
reanalysis at the time of collection at sample sites. Each bar represents one sample, with the height of
each bar corresponding to total AOD. ABF (anthropogenic and biogenic fine aerosol species) in black,
mineral dust in dark gray, and sea salt + and smoke in light gray, fractions of the total AOD are shown
for each station.
The average AOD fraction, based on NAAPS reanalysis, attributed to dust in the MS during
the month of April for 2003–2018 was on the order of 0.1–0.2 with a decreasing gradient from the
south (closer to the African continent, the main aerosol source) to the north, and generally decreasing
from east to west. However, this long-term average for April likely included some dust-storm events.
During our sampling (April 2011) dust AOD on April 7–8, (samples 1 and 2), April 12–13 (samples 6
and 7) and April 18 (sample 9) was relatively high compared to other days (Figure 2). However, dust
AOD for these days was still low compared to dust contribution to AOD during storms, which can
frequently exceed 1.0 [52,53]. From the low-level wind and the movement of dust plumes based on
NAAPS reanalysis and NOAA HYSPLIT back trajectories (), dust detected at the location of the ship
on April 7–8 (samples 1 and 2) likely originated from Turkey. The April 12–13 (sample 6 and 7) dust
peak observed is related to a dust storm that occurred in the northwest of Africa on April 5 (with
maximum dust AOD around 2.0) [52]. NAAPS reanalysis shows that the dust plume originating from
this storm moved northwest and reached 60◦ N on April 9 and then moved southeastward and reached
the location of the ship on April 12. After this long-range transport, dust AOD was much weaker
when it arrived at the MS (0.14). As this air mass traveled over the European continent, it mixed with
anthropogenic aerosols (ABF). Throughout the cruise, ABF ranged from 0.04 to 0.14, with the lowest
ABF AOD during collection of sample 6, in the central MS, and the highest during collection of sample
12 in the western MS (Table 1, Figure 2).
Aluminum (Al) concentration, a proxy for mineral dust [27], ranged between 41 and 661 ng−
−3
m air, and was highest on April 13 during collection of sample 7, which occurred when the dust
storm originating from northwest Africa arrived in the MS. Overall, Al measurements were positively
correlated with total AOD (Spearman correlation: ρ𝜌= 0.694, p = 0.004), and especially with the AOD
fraction attributed to dust (Spearman correlation: ρ = 0.834, p < 0.0001) (Table 1). There was also
Atmosphere 2019, 10, 440
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𝜌
𝜌
a significant positive correlation of Al concentrations and longitude, with more Al in samples
collected
in the air above the Eastern MS than above the Western MS (Spearman correlation: ρ = 0.597, p = 0.017)
(Table 1).
Overall, the aerosol concentration in the air during our sampling campaign (background
non-dust-storm period), particularly the mineral dust (as derived from the dust fraction of AOD and
Al), were within the range of previously measured values in days without dust storms and about an
order of magnitude lower than values recorded during dust storm event in the region [52,53].
3.2. Airborne Bacterial Abundance
−
Bacterial abundances in our samples ranged from
to
cells
air (Figure −3). The highest
abundance of bacteria was measured in sample 6 in the Central MS (2.12 × 104 cells m−3 air), near the
island of Crete, during the arrival of the tail of the dust storm that originated from North Africa.
−
The lowest
abundances were measured in the Central and Eastern Mediterranean (6.64 × 103 to
7.17 × 103 cells m−3 air) in samples 9 and 4, respectively. Bacterial abundances in aerosols collected
over the MS were in agreement with previous studies from the eastern Mediterranean coast [10] and
the Atlantic, Pacific, and Indian ocean basins [1], yet were lower than those reported in the East China
Sea [54] and the Red Sea [55]. Rahav et al. [10] measured the abundance of airborne prokaryotes at
−
a coastal site located at the easternmost MS during 34 sampling events (between 2015 and 2018)
and
found that abundances were positively correlated to the concentration of aerosols in the air (mg m−3
air). Here, however, we did not find such a correlation, likely because the range of concentrations
during non-dust-storm conditions, represented by our samples, was relatively small in comparison to
previous studies. Mayol et al. [1] measured bacterial abundances in the Atlantic, Indian, and Pacific
Ocean basins and found that sites closer to land (including islands) had significantly higher numbers of
airborne microbes (normalized to the aerosol mass) than those further away from landmasses. This was
also not observed in the MS, possibly because the MS is surrounded by land, and all sampling sites are
relatively close to land when compared to samples obtained in the open ocean by Mayol et al. [1].
103
104
m−3
Bacterial cells m-3 air
Figure 3. Spatial distribution of airborne bacterial abundance (cells− m−3 air) over the MS during
April 2011.
3.3. Airborne Microbiome above the MS
Fifty-nine unique families of bacteria were found in the samples collected during this study.
The relative abundance was used to group bacteria into two categories: “Common” (Table 2) or “Rare”
(Table 3). Families that had a relative abundance of 5% or greater in at least one of our samples were
considered “Common”, and families that did not meet the 5% threshold were considered “Rare”.
Atmosphere 2019, 10, 440
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Common bacteria in our samples belonged to five phyla: Actinobacteria (three families), Bacteroidetes
(two families), Firmicutes (eight families), Proteobacteria (eleven families), and Deinococcus-Thermus
(one family) (Table 2). These bacteria are of variable gram stains, have diverse oxygen requirements,
spore formation, and come from many different habitats (Supplementary Table S2). Five bacteria in
our samples, Chitinophagaceae sediminibacterium, Clostridiaceae SMB53, Veillonellaceae spp., Moraxellaceae
acinetobacterlwoffii, and Sinobacteraceae spp., had not previously been reported in aerosol samples.
All other organisms have previously been identified in airborne bacterial studies in different locations
around the world (Supplementary Table S2) and may represent the consortium of bacteria that are
more likely to be aerosolized, transported long distance, and hence dispersed over large areas.
The relative abundances of the “Common” orders of bacteria in each region of the MS (Eastern,
Central, Western) are shown in a bar plot (Figure 4), with rare bacteria (constituting less than 5%
of all samples) grouped into “other”. The Eastern MS had a higher relative abundance of Bacillales,
Salinisphaerales, and Enterobacteriales, and lower relative abundances of Clostridiales and Saprospirales
than the Western and Central regions (Figure 4). The most abundant bacteria found over the MS
were Firmicutes (Bacilli and Clostridia) and Proteobacteria (Alphaproteobacteria, Betaproteobacteria,
and Gammaproteobacteria) (Figure 4). The Firmicutes and Proteobacteria families we found over the MS
have previously been isolated from variable habitats, including soil, plant microbiota, aquatic (including
marine) and thermal environments, and human and animal microbiota (Figure 4, Supplementary
Table S2). This suggests that the bacterial community of the MS air during non-storm conditions are
not tied to one habitat source. The organisms that were significantly more abundant during higher
concentrations of dust (Bacillaceae, Paenibacillaceae) are both from the Bacillales order and are terrestrial
(
microbes, commonly found in soil and plant microbiomes (Supplementary Table S2). This is consistent
with data from coastal Mediterranean aerosol studies conducted during dust storms [3,31,32,57,58],
which also reported the presence of Bacillaceae in the air during storm events. Certain bacteria were
more abundant in samples with high concentrations of ABF (Chitinophagaceae, Staphylococcaceae,
Planococcaceae, Turicibacteraceae). However, these organisms are found in a wide array of habitats,
and thus implication of their association to high concentrations of ABF is not as clear.
Figure 4. Relative abundance of prokaryote operational taxonomic units (OTUs) in the different
regions of the MS. The colors correspond to different taxonomic orders of prokaryotes, as shown in the
detailed legend.
–
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Table 2. ‘Common’ organisms found over the Mediterranean Sea in this study compared to five studies focusing on marine aerosols [1,8,38,55,56], five studies focusing
on coastal aerosols [3,31,32,57,58], and six samples from one study focusing on Mediterranean surface seawater [59]. Columns under open ocean studies refer to
references [1,8,38,55,56], columns under Mediterranean coastal studies refer to references [3,31,32,57,58], and columns under Mediterranean seawater samples refer to
six samples from reference [59].
Open Ocean Studies
Common Bacteria
Phyla
Class
Order
Family
1
Actinobacteria
Actinobacteria
Actinobacteria
Bacteroidetes
Bacteroidetes
Firmicutes
Firmicutes
Firmicutes
Firmicutes
Firmicutes
Firmicutes
Firmicutes
Firmicutes
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Deinococcus-Thermus
Actinobacteria
Actinobacteria
Actinobacteria
Flavobacteriia
Saprospirae
Bacilli
Bacilli
Bacilli
Bacilli
Bacilli
Clostridia
Clostridia
Clostridia
Alphaproteobacteria
Alphaproteobacteria
Alphaproteobacteria
Alphaproteobacteria
Betaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Deinococci
Actinomycetales
Actinomycetales
Bifidobacteriales
Flavobacteriales
Saprospirales
Bacillales
Bacillales
Bacillales
Bacillales
Turicibacterales
Clostridiales
Clostridiales
Clostridiales
Rhizobiales
Rhodobacterales
Rhodospirillales
Sphingomonadales
Burkholderiales
Enterobacteriales
Pseudomonadales
Pseudomonadales
Salinisphaerales
Vibrionales
Xanthomonadales
Thermales
Actinomycetaceae
Corynebacteriaceae
Bifidobacteriaceae
Weeksellaceae
Chitinophagaceae
Bacillaceae
Paenibacillaceae
Planococcaceae
Staphylococcaceae
Turicibacteraceae
Clostridiaceae
Peptostreptococcaceae
Veillonellaceae
Bradyrhizobiaceae
Rhodobacteraceae
Rhodospirillaceae
Sphingomonadaceae
Comamonadaceae
Enterobacteriaceae
Moraxellaceae
Pseudomonadaceae
Salinisphaeraceae
Vibrionaceae
Sinobacteraceae
Thermaceae
×
×
×
×
×
×
×
×
×
2
×
3
4
×
5
×
×
×
×
1
2
×
×
×
×
×
×
×
3
4
×
×
×
×
×
×
1
×
×
×
×
×
×
×
×
×
×
2
3
4
5
6
×
×
×
×
×
×
×
×
×
×
5
×
×
×
×
×
×
×
×
×
×
×
×
×
Med Seawater Samples
Med Coastal Studies
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
Atmosphere 2019, 10, 440
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To quantitatively assess the diversity and estimate the differences in airborne bacterial communities
over the MS, we report microbial community richness, expressed as the number of unique OTUs
observed, and diversity expressed as Shannon’s diversity index (H), estimated from the abundance of
bacteria in each sample (Table 1). Observed OTUs corresponds to the number of unique bacteria in
each sample, whereas H is a commonly used quantitative measure of diversity [49]. The abundance
of observed OTUs ranged from 66 (sample 9) to 241 (sample 1) (Table 1). Observed OTUs varied
significantly between the three regions of the MS: Eastern (median = 141), Central (median = 93),
and Western (median = 82) (KruskalWallis pairwise test: H = 6.732, df = 2, p = 0.034) (Table 1) and
correlated positively to Al concentration (Spearman correlation: ρ = 0.549, p = 0.028), mineral dust
AOD (Spearman correlation: ρ = 0.68, p = 0.003), ABF AOD (Spearman correlation: ρ = 0.538, p = 0.031),
and total AOD (Spearman correlation: ρ = 0.70, p = 0.002) (Table 1). The diversity ranged from 5.17
(sample 9) to 7.48 (sample 1) (Table 1). H values were positively correlated to mineral dust (Spearman
correlation: ρ = 0.547, p = 0.028), ABF (Spearman correlation: ρ = 0.599, p = 0.014), and total AOD
𝜌
𝜌
concentrations
(Spearman correlation: ρ = 0.653, p = 0.007) (Figure 5). Prokaryotic
communities from
samples within the Eastern MS were significantly more similar to each other than samples from the
Western MS (PERMANOVA: F = 1.83, p = 0.009) (Figure 6A). Moreover, distance to land, including
islands, was positively correlated to community similarity (Spearman: ρ = 0.377, p = 0.009) (Table 1,
𝜌
Figure 6B), even though the bacterial abundance did not correlate to distance to shore.
Figure 5. The relationship between bacterial diversity (Shannon’s diversity index) and atmospheric
aerosols variables, (A) aluminum, (B) dust, (C) ABF, (D) total aerosol optical density.
Atmosphere 2019, 10, 440
11 of 18
Figure 6. PCoA showing the differences in beta diversity using weighted UniFrac with (A) shapes
representing regions of the MS samples were collected in, and (B) distance (km) between each sample
site and closest landmass.
Previous studies conducted during different dust storms have shown that the origin and
atmospheric route of airmass influences bacterial community composition [30,54]. Our findings
show that, during non-dust-storm events, neither bacterial richness nor diversity are influenced by
the origin of the airmass. This is likely because during intense dust events copious amounts of desert
topsoil from different locations are transported and these topsoil particles have distinct microbial
communities [32,60]. Our study took place during non-storm conditions over the ocean, and hence
terrestrial origin signatures were less pronounced. Instead, we show that airborne bacterial richness
and diversity varied by geographic location over the MS (not the origin of the airmass) (Table 1)
and correlated to the concentration of Al (Table 1) (as well as dust AOD, ABF AOD, and total AOD;
Table 1, Figure 2). Similarly, the diversity of airborne microbes over the MS increased with increasing
concentration of Al, mineral dust AOD, ABF AOD, and total AOD measurements (Table 1, Figure 5).
Microbes in the air are predominantly associated with particles, hence when there are more
particles in the air, it is likely to find more bacteria. Interestingly, it has been suggested that crevices in
particles maintain local humidity due to moisture adsorption to particles and provide shelter from
UV, thus protecting airborne microbes from desiccation and exposure to damaging UV radiation,
two elements reducing survival of bacteria in the atmosphere [61–63]. Dust may also increase the
survival potential of airborne bacteria because dust particles can scatter light and UV radiation,
reducing exposure. Thus, high Al, which indicates more mineral dust particles (Figure 5), may protect
airborne microbes and results in an increased diversity of airborne microbes (Figure 5). This may also be
because there are more unique OTUs when there are more mineral dust particles in the air since mineral
dust has higher microbial diversity compared to anthropogenic pollutant sources. Alternatively,
the chance of encountering more unique OTUs in the air may increase when there are more dust
particles in the air because sampling, DNA extraction, PCR, and sequencing methods are better at
detecting “Rare” OTUs under such conditions. The correlation between mineral dust and diversity
suggests that the microbiome of the air will become more diverse with increased desertification and
related dust input to the atmosphere due to projected changes in climate.
Our samples contained a high percentage (44%) of bacteria that are also found in MS surface
water [61]. Additionally, we found that weighted UniFrac, (a measure of beta diversity) positively
correlated to distance from land, including islands, regardless of the landmass type (island, populated,
un-populated, desert or vegetated) (Table 1, Figure 6B). Although this correlation was rather weak, it may
be explained by samples far from land containing a higher proportion of marine prokaryotes, in agreement
with Mayol et al. [1]. Waves and bubble bursting in the sea surface result in the aerosolization and
transportation of microbes [64]. Indeed, other open ocean aerosol studies have also identified marine
bacteria in aerosols [1,54]. Our study demonstrates that aerosolization can be a mechanism for long-distance
dispersal for marine bacteria [54,64]. This can have ecological implications for receiving ecosystems
Atmosphere 2019, 10, 440
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and may impact the biogeography of various strains. Airborne microbes can change the community
structures of environments into which they are deposited [15,65]. Furthermore, bacteriophages associated
with marine bacteria can also be transported to new environments and spread viral infections [15,66].
Therefore, airborne microbes and viruses may impact both microbial community structure and microbial
production and should be further studied.
The average number of OTUs in our aerosol samples collected during springtime was similar to
the number of OTUs in the Norwegian Sea and the Western Pacific in the summer and lower than OTUs
in the Northern and Western Pacific Ocean in the fall [56]. Since seasonality impacts airborne bacterial
abundance [12,19] and community composition [56], spatiotemporal variability of airborne microbes
should be studied during other seasons to assess interannual variability in this region. The number of
observed OTUs during non-storm conditions was lower than those measured in coastal cities in the
Mediterranean during dust storms [31,58]. This is likely due to the positive correlation between the
concentrations of various aerosol constituents (mineral dust and ABF) and the number of OTUs as
observed in our study (Figure 5) and previous studies [31].
To our knowledge, there are only two other studies of airborne microbes in the MS during
non-storm conditions [10,32]. The study site of Gat et al. [32] was done at a coastal city in Israel
(~10 Km away from the shoreline) and the study site of Rahav et al. [10] was at the rooftop of
a building directly next to the ocean. Thus, these studies represent different ecological systems than
the open ocean. However, all of the organisms that were prominent during clear non-storm days
in Gat et al. [32] were also found in our samples (aside from Dermabacteraceae [Actinobacteria])
indicating that they are commonly found in the air over both the land and the water in this region.
Several other studies have reported on the airborne bacterial communities during dust storms in the
MS and found organisms that were also present in our samples (Table 2) [3,31,32,57,58], suggesting that
some organisms previously assumed as being associated with dust-events exist over the MS during
non-storm conditions as well. Some organisms observed during dust storms, however, were absent
during non-storm conditions [3,31,32,57,58], particularly many that are ubiquitously found in soils [60].
There are only a few studies which have identified and reported airborne microbial diversity in
open ocean settings. However, the few reports cover diverse ocean basins, including the East China
Sea [54], Caribbean Sea [8], Norwegian Sea [56], Atlantic Ocean [1,8], Pacific Ocean [1,56], and the
Indian Ocean [1]. All these studies identified organisms at the family level, except for Mayol et al. [1],
which identified organisms at the class level. We compared the microbes found in our study to
organisms found in other open ocean studies (Tables 2 and 3) and found that 44% of the most common
bacteria in our study were also reported in other open ocean aerosol studies at the family level. We also
found that 80% of the bacteria at the class level were found in aerosols in other marine studies. Of the
rare bacteria (<5% in our samples), 16% were reported in other open ocean aerosol studies at the family
level and 60% at the class level (Table 2).
When compared to airborne bacteria in samples collected on the Mediterranean coast [3,31,32,57,58]
(Tables 2 and 3), 48% of the common bacteria and 13% of the rare bacteria found in our study were also
reported in these studies at the family level. Highly abundant families (Bacillaceae, Sphingomonadaceae,
and Pseudomonadaceae) were also found in the air over other marine environments [1,8,56] at the
class level, suggesting that these organisms are commonly dispersed via airmasses. If these organisms
are viable upon deposition and have a cosmopolitan distribution throughout the oceans, it could be
inferred that airmasses are a vehicle of biogeographical distribution.
Atmosphere 2019, 10, 440
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Table 3. ‘Rare’ organisms found over the Mediterranean Sea in this study compared to five studies focusing on marine aerosols [1,8,38,55,56], five studies focusing
on coastal aerosols [3,31,32,57,58], and six samples from one study focusing on Mediterranean surface seawater [59]. Columns under open ocean studies refer to
references [1,8,38,55,56], columns under Mediterranean coastal studies refer to references [3,31,32,57,58], and columns under Mediterranean seawater samples refer to
six samples from reference [59].
Open Ocean Studies
Rare Bacteria
Phyla
Class
Order
Actinobacteria
Actinobacteria
Actinobacteria
Bacteroidetes
Bacteroidetes
Bacteroidetes
Bacteroidetes
Bacteroidetes
Chlamydiae
Chlamydiae
Cyanobacteria
Firmicutes
Firmicutes
Firmicutes
Firmicutes
Firmicutes
Firmicutes
Firmicutes
Firmicutes
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Spirochaetes
WPS
Deinococcus-Thermus
Actinobacteria
Actinobacteria
Rubrobacteria
BME43
Bacteroidia
Cytophagia
Saprospirae
Saprospirae
Chlamydiia
Chlamydiia
4C0d2
Bacilli
Bacilli
Bacilli
Bacilli
Bacilli
Bacilli
Bacilli
Clostridia
Undefined
Alphaproteobacteria
Alphaproteobacteria
Alphaproteobacteria
Alphaproteobacteria
Alphaproteobacteria
Betaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Spirochaetes
Unassigned
Deinococci
Actinomycetales
Actinomycetales
Rubrobacterales
Unassigned
Bacteroidales
Cytophagales
Saprospirales
Saprospirales
Chlamydiales
Chlamydiales
MLE112
Bacillales
Bacillales
Bacillales
Bacillales
Gemellales
Lactobacillales
Lactobacillales
Clostridiales
Unassigned
Rhizobiales
Rhizobiales
Rhizobiales
Rhizobiales
Rhodobacterales
Burkholderiales
Alteromonadales
Oceanospirillales
Pasteurellales
Spirochaetales
Unassigned
Deinococcales
Family
Dietziaceae
Micrococcaceae
Rubrobacteraceae
Unassigned
Porphyromonadaceae
Amoebophilaceae
Undefined
Saprospiraceae
Undefined
Rhabdochlamydiaceae
Unassigned
Unassigned
Alicyclobacillaceae
Thermoactinomycetaceae
Exiguobacteraceae
Gemellaceae
Leuconostocaceae
Streptococcaceae
Tissierellaceae
Unassigned
Hyphomicrobiaceae
Methylobacteriaceae
Methylocystaceae
Phyllobacteriaceae
Hyphomonadaceae
Oxalobacteraceae
Alteromonadaceae
Halomonadaceae
Pasteurellaceae
Spirochaetaceae
Unassigned
Deinococcaceae
1
2
×
×
×
3
4
Med Coastal Studies
5
×
1
2
×
×
×
3
4
5
Med Seawater Studies
1
2
3
4
5
6
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
×
Atmosphere 2019, 10, 440
14 of 18
Mediterranean seawater samples contained the Bacillaceae family, as well as nine other
bacterial families from the Proteobacteria (Bradyrhizobiaceae, Rhodobacteraceae, Rhodospirillaceae,
Sphingomonadaceae, Comamonadaceae, Enterobacteriaceae, Pseudomonadaceae, Vibrionaceae) and
Deinococcus-Thermus (Thermaceae) phyla [59]. Vibrionaceae and Alteromonadaceae families,
which were present in our as well as other studies, have most commonly been found in the sea
surface microlayer [67], the ~100 µm surface layer of the ocean where there is a dynamic exchange
between the sea and air [68]. Overall, 44% of common airborne bacteria and 16% of rare airborne
bacteria in our study were previously reported to be found in the MS surface water [61] (Tables 2
and 3). The large proportion of organisms being found in both air and water as opposed to air only
suggests that the bacterial exchange between sea and air during ‘normal’ atmospheric conditions is an
important process that can influence the community structure of both environments.
Current data show a wide range of biogeochemical responses related to atmospheric deposition
events in LNLC areas [20]. However, the specific contribution of airborne microbes to the changes
documented in these studies is typically not considered [3,33]. To predict the future of LNLC regions
and how they will contribute to global biogeochemical cycles, it is imperative to understand how
atmospheric deposition impacts these regions [20], and to specifically determine the contribution of
airborne microbes to these impacts.
The prevalence and importance of airborne microbes is clear, but key methods in aeromicrobiology
have not yet been standardized (sample collection, quantification). We used filters to collect aerosols,
but different studies have used other techniques, such as liquid impingement [69–71] or electrostatic
precipitation [72–74]. Similarly, we measured bacterial abundance directly from filters after sonication
to promote detachment from the filter, while others used different methods, such as qPCR [54],
culture-based methods [3] and flow cytometry [10]. As a result, it is difficult to reliably compare results
between studies, even if the sampling site and environmental conditions are similar. These issues merit
further research and would provide meaningful advancements to the field.
4. Conclusions
Our results show that a diverse array of microbes is present in the air over the MS, with abundances
similar to those over other ocean settings. We found that the diversity of the airborne microbes over
the MS during non-dust-storm conditions is influenced by aerosol content (mineral dust as well as
polluted aerosols) in the air, with higher diversity linked to increases in particle numbers. Our results
also show high percentages of marine bacteria in the air, indicating that there is a significant exchange
of microbes between the sea surface and the air, even during background non-storm conditions.
We also note that several groups of bacteria are more commonly found in the air, hence these
groups may be readily dispersed by air movement with implications to their biogeography. Since
desertification may increase with climate change, more particles will be introduced to the air, increasing
the abundance and diversity of airborne microbes. This may have a significant impact on the microbial
communities and biogeochemical cycles of oceans, particularly in regions that are subject to high rates
of atmospheric deposition.
Supplementary Materials: The following are available online at http://www.mdpi.com/2073-4433/10/8/440/s1,
Figure S1: Backward trajectories constructed using NOAA HYPSPLIT MODEL for each sample, Table S1: Metadata
of Samples, Table S2: Detailed Description of Common Bacteria.
Author Contributions: Project administration and design A.P. and E.R; Writing—original draft, E.M.;
Writing—review and editing, E.M., A.P., E.R., P.X., N.B., J.M.E., A.V. and B.H.
Funding: This research was funded by the Israel Science Foundation (grant 1211/17) to B.H and E.R. E.M was
supported by the NSF GRFP.
Acknowledgments: The authors would like to thank Katie Roberts for her assistance.
Conflicts of Interest: The authors declare no conflict of interest.
Atmosphere 2019, 10, 440
15 of 18
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