At mospheri c aerosol  deposi t i on i nf l uencesmari ne mi crobi al  communi t i es i n ol i got rophi csurf ace wat ers of  t he west ern Paci f i c Ocean
著者Maki  Teruya,  I shi kawa Aki ra,  Mast unaga Tomoki ,Poi nt i ng St ephen B. ,  Sai t o Yuuki ,  KasaiTomoaki ,  Wat anabe Koi chi ,  Aoki  Kazuma,Hori uchi  Amane,  Lee Kevi n C. ,  HasegawaHi roshi ,  I wasaka Yasunobu
j ournal  orpubl i cat i on t i t l e
Deep- Sea Research Part  I :  Oceanographi cResearch Papers
vol ume118
page range37- 45
year2016- 12- 01
URLht t p: //hdl . handl e. net /2297/46781
doi: 10.1016/j.dsr.2016.10.002
Title: 
Atmospheric aerosol deposition influences marine microbial communities in 
oligotrophic surface waters of the western Pacific Ocean 
Authors:  
Teruya Maki*1, Akira Ishikawa2, Tomoki Mastunaga1, Stephen B. Pointing3, Yuuki 
Saito1, Tomoaki Kasai2, Koichi Watanabe4, Kazuma Aoki5, Amane Horiuchi1, Kevin C. 
Lee5, Hiroshi Hasegawa1, Yasunobu Iwasaka6 
Affiliation of all authors: 
1. College of Science and Engineering, Kanazawa University, Kakuma, Kanazawa, 
Ishikawa 920-1192, Japan. 
2. Graduate School of Bioresources, Mie University, 1577 Kurimamachiya, Tsu, Mie 
514-8507, Japan. 
3. School of Applied Sciences, Auckland University of Technology, 55 Wellesley Street 
East, Auckland 1010, New Zealand. 
4. Department of Environmental Engineering, Faculty of Engineering, Toyama 
Prefectural University, 5180 Kurokawa, Imizu, Toyama 939-0398, Japan. 
5. Department of Earth Sciences, Faculty of Science, University of Toyama 3190 
Gofuku, Toyama 930-8555, Japan.  
6. Community Research Service Group, University of Shiga Prefecture, 2500 
Yasakamachi, Hikoneshi, Shiga, 522-8533, Japan. 
*Corresponding author: 
Tel: +81-(0) 76-234-4793, Fax: +81-(0) 76-234-4800 
E-mail:makiteru@se.kanazawa-u.ac.jp  
Abstract 
Atmospheric aerosols contain particulates that are deposited to oceanic surface waters. 
These can represent a major source of nutrients, trace metals, and organic compounds 
for the marine environment. The Japan Sea and the western Pacific Ocean are 
particularly affected by aerosols due to the transport of desert dust and industrially 
derived particulate matter with aerodynamic diameter less than 2.5 µm (PM2.5) from 
continental Asia. We hypothesized that supplementing seawater with aerosol 
particulates would lead to measurable changes in surface water nutrient composition as 
well as shifts in the marine microbial community. Shipboard experiments in the Pacific 
Ocean involved the recovery of oligotrophic oceanic surface water and subsequent 
supplementation with aerosol particulates obtained from the nearby coastal mountains, 
to simulate marine particulate input in this region. Initial increases in nitrates due to the 
addition of aerosol particulates were followed by a decrease correlated with the increase 
in phytoplankton biomass, which was composed largely of Bacillariophyta (diatoms), 
including Pseudo-nitzschia and Chaetoceros species. This shift was accompanied by 
changes in the bacterial community, with apparent increases in the relative abundance 
of heterotrophic Rhodobacteraceae and Colwelliaceae in aerosol particulate treated 
seawater. Our findings provide empirical evidence revealing the impact of aerosol 
particulates on oceanic surface water microbiology by alleviating nitrogen limitation in 
the organisms. 
Keywords: Asian dust; bacteria; oligotrophic ocean; phytoplankton; Aerosol deposition
1. Introduction  
Aerosols transported by westerly winds are a major source of nutrients, trace 
metals, and organic matter in the western Pacific Ocean (Jo et al., 2007) and Japan Sea 
(Tan et al., 2013). In oceanic areas where photosynthetic and heterotrophic microbial 
communities are nutrient-limited, aerosol deposition can supply both necessary trace 
elements and nutrients. The subsequent growth of primary producers affects marine 
productivity and carbon sequestration (Blank et al., 1985; Prospero and Savoie, 1989; 
Duce and Tindale, 1991; Spokes and Jickells, 1996; Erickson et al., 2003; Yuan and 
Zhang, 2006). Changes in the dynamics of bacterial communities induced by aerosol 
deposition to oceanic areas are also thought to vary the mineralization of organic matter 
and therefore affect marine carbon cycles (Lekunberri et al., 2010; Romero et al., 2011). 
Recent economic and industrial development in continental Asia, particularly in 
China, has increased the emission of air pollution from the mainland coast (Chan and 
Yao, 2008). The deposition of anthropogenic aerosols from industrial regions delivers 
nutrients, such as nitrate and phosphate, to the ocean, significantly enhancing marine 
biological productivity along the Pacific Northwest coast (Zhang and Liu, 1994; Tan et 
al., 2011). Interestingly, trace elements, such as copper (Cu), found in dust particles 
have been reported to inhibit microbial growth in aquatic environments (Paytan et al., 
2009; Jordi et al., 2012). Aerosol deposition inputs nutrients and trace elements to 
oligotrophic oceanic surface waters. The atmospheric input of nutrients into the North 
Pacific Ocean increases during short-term episodic deposition events during the high 
dust season (DiTullio and Laws, 1991). In the North Pacific Ocean, one large dust event 
is found to have deposited aerosol particulates onto surface waters at a rate of 
approximately 6.0 mg L−1 one-event−1 (Duce and Tindale, 1991). The annual deposition 
of dust generally varies between the Japanese coastal area (21 g m-2) and the open ocean 
(0.8 g m-2) (Uematsu et al., 2003). Deposited aerosols remain suspended within 40 m of 
the surface for up to 72 h (Hashimoto et al., 2005). 
Dust events are also known to transport airborne microorganisms, supporting 
microbial recruitment to ecosystems downwind (Hervàs et al., 2009). Although 
previous studies have analyzed the influence of aerosols on marine ecosystems using 
model simulations and chemical analyses, there have been few incubation experiments 
that have directly assessed the response of marine microbial communities to aerosol 
deposition (Lekunberri et al., 2010; Romero et al., 2011). Incubation experiments using 
aerosol-treated seawater samples are affected by several constraints. Some studies have 
investigated microbial dynamics in marine and lake water samples treated with dust 
particulates and incubated under laboratory conditions (Paytan et al., 2009; Lekunberri 
et al., 2010). However, the time required for the transfer of open ocean seawater 
samples to the laboratory affects the microbial community. Shipboard incubation 
experiments can overcome this issue. Another challenge consists of collecting the large 
volumes of aerosols required to perform seawater incubation experiments.  
During the winter and early spring, strong northwesterly winds result in heavy 
snowfall on Mt. Tateyama (3,015 m above sea level), which faces the Japan Sea. 
Aerosols are transported in a predictable manner by westerly wind from continental 
Asia to Japan and are preserved in the snowfall without undergoing local contamination 
(Osada et al., 2004; Watanabe et al., 2011). Snow cover is therefore regarded as a 
product of continuous precipitation during the Asian dust season, and can be a useful 
source of aerosol particulates. 
Here, we report a shipboard experiment undertaken in the Pacific Ocean to assess 
the impact of aerosol particulates, at levels typically experienced by oceanic surface 
waters on marine microbial communities. We used a combination of physicochemical 
analyses, direct cell counting and high-throughput sequencing approaches to identify 
changes in phytoplankton and heterotrophic microbial communities. 
2. Materials and Methods 
2.1. Aerosol particulate recovery 
To prepare aerosol samples for shipboard experiments, snow samples containing 
aerosol particulates (dust particles and PM2.5 pollution particles) were collected from 
snow cover at Murododaira on Mt. Tateyama (36.57ºN, 137.60ºE; 2,450 m, MR; Fig. 1) 
on 21 March 2012. At this location, strong northwesterly winds result in heavy snowfall 
during the winter and early spring leading to the deposition of aerosol particulates 
originating from the Asian continent (Watanabe et al., 2011). After a snow pit was dug, 
the walls of the pit were carefully smoothed to ensure the stratigraphy of the snow layer 
was undisturbed. The snow layers were composed of compacted or solid-type snow and 
included layers of melted and refrozen water (ice). In particular, the layer from the snow 
surface to a depth of 150 cm were included in the brown-color layers (dirty layers) that 
had not melted. Therefore, these snow layers would be expected to essentially maintain 
the record of atmospheric aerosol deposition, revealing chemical compound dynamics 
from the top of the snow wall to a depth of 615 cm (Fig. S1). The snow layer at a depth 
of 110 cm was a non-white color (to be referred to as the “dirty” layer) and had higher 
concentrations of mineral particles (1.90 × 105 particles mL-1) and calcium (18.8 µeq 
L-1) than other snow layers. The dirty layer harbored Na+ at a concentration of 13.8 µeq 
L-1, which primarily originated from sea salt. The contribution of sea salt Ca2+ to the 
total Ca2+ content was minor (approximately 3%). The solutions of snow samples from 
a depth of 110 cm contained nss-Ca2+ at a high concentration of 18.2 µeq L-1, 
suggesting that the mineral particles in the snow layers specifically contained calcium, 
which is a trace mineral found in Asian-dust mineral particles (Suzuki and Tsunogai, 
1993). Snow was recovered aseptically from a subsurface of a dirty snow layer at a 
depth of 110 cm. We extrapolated LIDAR measurements of dust events and used 
back-trajectory analysis to establish the origin of this dust, deposited from the 1st to the 
3rd of April 2012, in mainland Asia (Fig. S2). The snow samples were stored in 
polycarbonate bottles that were washed in a 3 mol L−1 HCl solution and sterilized at 
121°C for 20 min to remove metal, nitrate, and phosphate contamination, and frozen at 
-80oC until further analysis.  
2.2. Seawater incubations 
Seawater sampling and shipboard experiments were performed 70 km off the coast 
of Omaezaki in the Shizuoka prefecture (34.07ºN, 138.77ºE) on 26 May 2012 during 
the SE526 cruise of T/S Seisui Maru (Mie University) (Fig. 1). At this sampling site, the 
water column is thermally stratified from spring through summer, and the seawater 
temperature during the sampling periods decreased from 19.2 °C to 18.7 °C between a 
depth of 10 m and 18 m, indicating the presence of a weak thermocline (Fig. S3). These 
results suggest that the sampling area was oligotrophic on 26 May 2012. The nutrients 
in the surface layers are consumed by microbial activity, often causing oligotrophic 
conditions in the surface of the Pacific Ocean around Japan (Hashimoto et al., 2005). 
Seawater samples were collected from the surface at a depth of less than 1 m and stored 
in 20-L and 4-L sterilized holding tanks. One 20-L and two 4-L experimental tanks 
were used for each treatment, including ones filled with water as the control (C), ones 
with water exposed to 0.05 mg L−1 of aerosols simulating a light dust event (LS), and 
with water exposed to 0.25 mg L−1 of aerosols simulating a heavy dust event (HS). 
Treatments were incubated onboard the ship at surface temperature (24°C) under 
ambient light conditions for a 72-h period. Initial measurements were conducted 30 
minutes after addition of aerosol particulates, with 24-h sample intervals thereafter. 
2.3. Water chemistry 
For seawater samples, nitrate concentration was determined colorimetrically 
(Strickland and Parsons, 1972) after first removing particulates by filtration through 0.2 
µm pore-size polycarbonate filters (Millipore, Tokyo, Japan). Inorganic phosphorus, as 
well as particulate and dissolved organic phosphorus, were measured using the 
molybdenum blue method (Strickland and Parsons, 1972). Iron in seawater samples was 
measured using ICP-AES. 
2.4. Particulate estimates 
Water samples were fixed with a paraformaldehyde solution at a final 
concentration of 1%, stained with DAPI (4', 6-diamidino-2-phenylindole), and 
processed through a 0.22 µm pore-size polycarbonate filter (Whatman, Tokyo, Japan; 
Russell et al., 1974). Cells and particulates on the filter were observed using an 
epifluorescence microscope (Olympus, Tokyo, Japan). Bacterial particles and yellow 
particles observed on the filter transect were counted. The detection limit of each 
particle was 104 particles mL−1 seawater, and 103 particles per filter. Yellow particles 
stained with DAPI were classified as organic matter (Mostajir et al., 1995). The 
majority of the yellow particles were not found in the snow sample solutions after 
protease treatment, suggesting that they were composed of proteins (Fig. S4). In 
seawater, phytoplankton and cyanobacteria can be observed using the DAPI staining 
technique, but we rarely counted these cells, as they were broken by the 
paraformaldehyde fixation and the filtration processes. Accordingly, we used this 
technique for counting bacterial and yellow particles only. 
2.5. Phytoplankton biomass estimation and identification 
Phytoplankton biomass was estimated using Chl a concentration of 4 size fractions 
in the 20 L experimental tanks. A 200 mL aliquot of each sample was gravity filtered 
through a 20-µm mesh (>20 µm fraction). The filtrate was sequentially gravity filtered 
through Nuclepore filters (ADVANTEC, Tokyo, Japan) with a pore size of 10 µm 
(10–20 µm fraction), then passed through a 2-µm filter (2–10 µm fraction) with a 
vacuum pressure of <50 mmHg, and finally through a Whatman GF/F glass fiber filter 
(ADVANTEC, Tokyo, Japan) (<2 µm fraction) with a vacuum pressure <100 mmHg. 
The Chl a retained on the filters was extracted in N,N-dimethylformamide at -20ºC for 
24 h (Suzuki and Ishimaru, 1990), and its concentration was determined using the 
fluorometric method defined previously by Parsons et al. (1984) with a Turner Design 
fluorometer Model 10-AU-005 (Turner Designs, CA, USA). 
Microscopic identification of diatoms was also conducted in order to quantify the 
number of diatom cells in subsamples collected from the experimental tanks. The 
subsamples were fixed using borax-buffered formaldehyde at a final concentration of 
1% (v/v). After an aliquot (50–100 mL) of the subsample settled in an Utermöhl 
chamber, the cells were counted under an inverted microscope (NIKON ECLIPSE 
TE-300, Tokyo, Japan) at a magnification of 200×. 
2.6. High-throughput sequencing 
Water samples (10 mL) were centrifuged at 20,000 g for 5 minutes. Genomic 
DNA (gDNA) was extracted using a modified phenol-chloroform method (Maki et al., 
2008). Fragments of 16S rDNA (approximately 500 bp) were amplified from the 
extracted gDNA by PCR using universal 16S rDNA bacterial primers for the V4 region: 
515F (5′- Seq A - TGT GCC AGC MGC CGC GGT AA -3′) and 806R (5′- Seq B - GGA 
CTA CHV GGG TWT CTA AT -3′) (Maidak et al., 1997, where Seq A and Seq B 
represent nucleotide sequences targeted by the second PCR primers. PCR amplification 
was performed under the following conditions: denaturation at 94°C for 1 min, 
annealing at 52°C for 2 min, and extension at 72°C for 2 min for 20 cycles. Fragments 
of the 16S rDNA PCR products were amplified again using additional PCR forward (5′- 
Adaptor C – Tag sequence - Seq A -3′) and reverse primers (5′- Adaptor D - Seq B -3′), 
where Adaptors C and D were used for the MiSeq sequencing reaction. The Tag 
sequence included 8 nucleotides designed for sample identification barcoding. Thermal 
cycling was performed under the following conditions: denaturation at 94°C for 1 min, 
annealing at 59°C for 2 min, and extension at 72°C for 2 min for 12 cycles. PCR 
amplicons from each sample were used for high-throughput sequencing on a MiSeq 
Genome Sequencer (Illumina, CA, USA). The sequences obtained for each sample were 
grouped based on tag sequences, and average read lengths of 450 bp were obtained. 
Negative controls (reactions with no template or template from unused filters) were 
prepared for all steps of the process after DNA extraction to check for contamination. 
Before the analysis of the bacterial community, we removed sequences according 
to the following criteria: <200 bp in length, with a phred-equivalent quality score of <25, 
containing ambiguous characters, with an uncorrectable barcode, or missing the primer 
sequence. The remaining sequences were clustered into phylotypes using QIIME (ver. 
1.8.0) with a minimum coverage of 99% and a minimum identity of 97%. The identities 
of phylotypes were analyzed by comparison of sequences against the DNA Data Bank 
of Japan (DDBJ) using a BLAST analysis. 
2.7. Phylogenetic analysis 
Full-length sequences of 16S rDNA (approximately 1,450 bp) were amplified 
from the extracted gDNA by PCR using the following oligonucleotide primers: 27F, 
5′-AGA GTT TGA TCM TGG CTC AG-3′; and 1492R, 5′-GGY TAC CTT GTT ACG 
ACT T-3′ (Maidak et al., 1997). PCR amplicons were cloned using a TA Cloning Kit 
(Invitrogen, Carlsbad, CA, USA). One hundred clones were obtained for each sample. 
The amplicons were sequenced using an ABI Dye Deoxy Terminator Cycle Sequencing 
Kit (Life Technologies, Carlsbad, CA, USA). The 27F primer was used as the 
sequencing primer. Sequences were assigned to phylotypes using BLAST to identify 
their closest matching sequences. Select clone sequences related to the dominant 
phylotypes detected by MiSeq sequencing analysis were chosen for additional 
sequencing using the 1492R primer. Phylogenetic trees including clone sequences were 
constructed according to the neighbor-joining algorithm using TreeViewPPC (Saitou 
and Nei, 1987).  
2.8. Accession numbers 
The DDBJ accession numbers for the 16S rDNA clone sequences obtained in this 
study are shown in Table 2. All sequences have been deposited in the DDBJ database 
(accession number of the submission is PRJDB4118). 
3. Results 
3.1. Changes in chemical compounds and DAPI-stained particles 
Ambient seawater samples had relatively low nitrate concentrations of 0.16 ± 0.05 
µmol L-1. The addition of snow solutions containing aerosol particulates initially 
resulted in an increase in the nitrate concentration to more than 1.10 µmol L-1 (ANOVA; 
P < 0.05) (Fig. 2a). The snow samples used in this study harbored higher concentrations 
of nitrate (35.0 µeq L-1) than those in other snow layers (Fig. S1). Thus, the soluble 
fraction of aerosol particulates likely released nitrate into the seawater. The initial 
concentration of soluble nitrate was mostly similar in both the HS and LS tanks 
regardless of aerosol treatment, because nitrate attached to insoluble particulates (eg.; 
mineral particles) might be slowly released into the seawater. After the incubation, 
nitrate in the LS and HS treatments decreased slightly to low concentrations of below 
0.5 µmol L-1, similar to levels in the C tank. The C tank maintained a low concentration 
of nitrate during the incubation. In contrast, the initial concentrations of phosphate in 
the all three sets of tanks (C, LS, and HS) were similar, ranging from 0.13 µmol L-1 to 
0.33 µmol L-1, and only the HS tank showed a gradual increase of phosphate to 0.83 
µmol L-1 during the 2-day incubation (ANOVA; P < 0.05) (Fig. 2b). The iron 
concentration increased proportionally to the amount added in the snow solution 
(ANOVA; P < 0.05), and was maintained during the incubation period (Fig. 2c). These 
results indicate that the snow-solution treatments added nitrate, phosphate, and iron to 
the LS and HS tanks. 
During microscopic observations using DAPI staining, several types of fluorescent 
particles were observed in the subsamples, mainly composed of bacteria and yellow 
fluorescent particles. Most bacteria emitting blue fluorescence were observed as a single 
cell, while some formed heterogeneous aggregates ranging from 2.0 µm to 50 µm in 
diameter. Yellow fluorescent particles, thought to be organic matter, ranged from 1.0 
µm to 10 µm in diameter. The bacteria in the LS and HS tanks increased from 
approximately 5.0 × 104 cells mL-1 to 8.5 × 104 cells mL-1 during the 2 days of 
incubation, while those in the control seawater fluctuated at relatively low 
concentrations of approximately 4.0 × 104 cells mL-1 (Table 1). The concentration of 
yellow particles in the LS and HS tanks increased to 1.18 × 104 particles mL-1 and 0.77 
× 104 particles mL-1, respectively, and decreased to 0.89 × 104 particles mL-1 and 0.34 × 
104 particles mL-1, respectively, after 1 day of incubation. In contrast, yellow particles 
remained under the detection limit in the C tank. 
3.3. Abundance and composition of phytoplankton 
There was a significant increase in total Chl a concentration in the LS and HS 
tanks from approximately 0.90 µg L-1 to more than 2.40 µg L-1 during the 2-day 
incubation, corresponding to the observed decrease in nitrate (ANOVA; P < 0.05) (Fig. 
3a). In contrast, the total concentration of Chl a in the C tank gradually decreased from 
1.1 µg L-1 to 0.2 µg L-1 during the incubation. This suggests that the nitrate from the 
snow-solution treatments stimulated phytoplankton growth. In particular, Chl a from the 
size fraction >20 µm in the LS and HS tanks significantly increased (ANOVA; P < 0.05) 
after the incubation (Fig. 3b) compared to the smaller size fractions, indicating that this 
was primarily due to the growth of large-celled eukaryotic photoautotrophs (Fig. 3c–e).  
Observation of the phytoplankton community under a microscope confirmed the 
growth of Bacillariophyta (diatoms), mainly comprised of Pseudo-nitzschia and 
Chaetoceros species in the LS and HS treatments, respectively (Fig. S5). During the 
incubation, cell concentrations of Pseudo-nitzschia species significantly increased from 
less than 0.85 × 105 cells mL-1 to 6.90 × 105 cells mL-1 in the LS and HS tanks 
(ANOVA; P < 0.05), while cell concentrations in the C tank fluctuated from 0.28 × 105 
to 0.72 × 105 cells mL-1 (Fig. 4). In the HS tank, Chaetoceros species increased in 
concentration from 0.45 × 105 to 6.00 × 105 cells mL-1 during the incubation period. In 
contrast, Chaetoceros species maintained relatively low densities of less than 0.35 × 105 
cells mL-1 in both the C and LS tanks. 
3.4. Bacterial community structure 
For the bacterial community analysis, we obtained a total of 447,411 sequences 
with an average length of 450bp. After sequences were filtered for quality a total of 
382,801 remained, with sequence library size for each sample normalized at 27,388. 
Phylogenetic assignment of sequences revealed that overall the diverse data set was 
comprised of representatives of 13–18 classes, and 37–47 families (Fig. 5). We found 
similar patterns among the rarefaction curves determined for the 6 subsamples (Fig. 
S6a). A UniFrac weighted analysis confirmed bacterial communities from LS and HS 
tanks were distinct from the untreated control (C) (Fig. S6b). 
The majority of phylotypes belonged to 6 classes, namely, the Cyanobacteria, 
Acidimicrobiia, Flavobacteria, Alpha- and Gamma-proteobacteria, and SAR406, which 
are typically observed in marine environments (Fig. 5a). The phylotypes belonging to 
the Cyanobacteria had a low relative abundances ranging from 0.5% to 2.9% (Fig. 5b). 
The bacterial composition was similar among all three (C, LS and HS) tanks at day 0, 
whereas relative abundances of some bacterial groups changed after the incubation in 
the snow-solution treatments (LS and HS) compared to the control (C). In the class 
Alpha-proteobacteria, representatives of the family Rhodobacteraceae were relatively 
high in abundance in the HL and HS tanks (18.7% and 14.8%, representatively), while 
they only accounted for 7.8% of sequences in the C tank. In the class 
Gamma-proteobacteria, sequences belonging to the family Colwelliaceae had a relative 
abundance greater than 9.6% in the HS tank after incubation, whereas those of the C 
and LS tanks were equal or less than 0.6%. In contrast, the phylotype ratios of the 
family Halomonadaceae decreased from 19.1% to 10.2%, which corresponded to the 
increasing amount of snow solution added to the treatments. The phylotypes belonging 
to the AB16 group in the SAR406 class, known to be pelagic bacteria, decreased from 
approximately 4.5% to less than 1% in the snow-solution treated seawater after 
incubation, while their relative abundance in the control tank remained above 3.0%. 
3.5. Phylogenetic analysis of full-length 16S rDNA sequences 
The 16S rDNA PCR amplicons from the clone libraries produced a total of 172 
clones from all three (C, LS, and HS) tanks. The 16S rDNA sequences mainly belonged 
to the following six classes: Cyanobacteria, Actinobacteria, Bacilli, Bacteroidetes, 
Alpha- and Gamma-proteobacteria, as well as the chloroplast group, and included 15 
families that overlapped with the MiSeq sequencing database (Table 2). We found that 
14 representative clones formed clusters with known bacterial sequences belonging to 
these families, which dominated the MiSeq sequencing database (Fig. 6). Chloroplast 
sequences from diatoms, such as Pseudo-nitzschia seriata and Thalassiosira 
pseudonana, were often detected from clone libraries recovered from the LS and HS 
tanks. Most clones belonging to the class Alpha-proteobacteria were closely related to 
Roseobacter species in the family Rhodobacteraceae (DSE12-5-583L-7, 
DSE12-5-583H-30), and Pelagibacter species in the SAR clade (DSE12-5-Control-1, 
DSE12-5-583L44). In the class Gamma-proteobacteria, the clone DSE12-5-583H-5 
belonging to the family Colwelliaceae was related to Colwellia species. The sequences 
DSE12-5-Control-14 and DSE12-5-583L-15 classified as Gamma-proteobacteria 
clustered with pelagic bacteria (Bacterium WHC3-1) in the order Oceanospirillales. 
Some sequences of the class Bacteroidetes (DSE12-5-583L-31, DSE12-5-Control-31) 
and the class SAR 406 (Control-33) were detected in all three (C, LS and HS) tanks 
(Table 2). 
4. Discussion 
4.1. Changes in nutrient and particle concentrations 
Aerosol deposition to oceanic surface waters inputs various compounds including 
metals, nitrate and sulfate, and is thought to influence primary production, export 
production, and carbon sequestration (Zhang and Liu, 1994; Erickson et al., 2003; Tan 
et al., 2011). This is thought to potentially influence primary production, export 
production, and carbon sequestration although data are scarce. Here we add new insight 
to this important issue by demonstrating that aerosol dust input results in significant 
changes to the surface microbiota. Major changes observed included an increase in 
diatom biomass and changes in phytoplankton and bacterial diversity, which appeared 
to be linked to the alleviation of nitrate limitation. Diatom blooms in response to aerosol 
dust events have also been observed in the western North Pacific (Yuan and Zhang, 
2006). 
Organic matter associated with dust-mineral particles has been reported to be 
deposited in coastal areas and stimulate the growth of marine heterotrophic bacteria 
(Lekunberri et al., 2010). Additionally, dust addition experiments have previously led to 
a 1.5- to 3-fold increase in bacterial abundance and activity in seawater (Bonnet et al., 
2005; Herut et al., 2005; Pulido-Villena et al., 2008). Taken together, these results 
indicate that nitrate and organic matter associated with aerosol deposition stimulate 
microbial growth in nutrient-deficient seawater.  
Unlike nitrate, concentrations of phosphate and iron in all experimental tanks 
remained still or changed regardless of the growth patterns of microorganisms. 
Phosphate concentrations did not change immediately after the addition of snow, but 
instead gradually increased over the 2 days of incubation (Fig. 2b). Phosphate attached 
to the aerosols would require additional days of incubation in order to be released into 
the experimental tanks. In contrast, higher concentrations of iron were measured 
immediately after the snow solution was added, and these levels were maintained at 
their initial values throughout the incubation period (Fig. 2c). The deposition of 
Asian-dust mineral particles has been reported to provide iron to the open ocean. Iron is 
also a growth-limiting nutrient for oceanic phytoplankton communities (Duce and 
Tindale, 1991) in our study, however, iron levels did not appear to be growth limiting. 
4.2. Dynamics of phytoplankton composition 
Diatoms belonging to the Bacillariophyta, such as species in the Pseudo-nitzschia 
and Chaetoceros, were observed in the snow-solution treated seawater, while members 
of Chlorophyta were not found in any experimental tanks (Fig. 4). The chloroplast 
sequences of diatoms were mainly detected in the clone library recovered from the 
snow-solution treated seawater (Table 2). In the MiSeq sequencing database, the 
Stramenopiles, including the chloroplasts of diatoms, were relatively higher in 
abundance in the snow-solution treated seawater than the control (data not shown). 
Furthermore, these diatoms are categorized as microplankton, which are typically 
20–150 µm in size. The Chl a concentration in the large size fraction (>20 µm) 
increased in the treated seawater (Fig. 3). Diatoms often increase in the western North 
Pacific after Asian dust events (Yuan and Zhang, 2006). Consequently, nitrate 
enrichment caused by the addition of snow solution likely accelerated the growth of 
Bacillariophyta (in particular Pseudo-nitzschia and Chaetoceros species). 
4.3. Bacterial community dynamics 
We conclude that aerosol dust input causes changes to existing marine bacterial 
populations rather than acting as a source of inoculum for dust-borne bacteria. Dust 
aerosols are reported to include terrestrial bacterial species, mainly belonging to the 
phyla Actinobacteria and Firmicutes (Maki et al., 2011; Tanaka et al., 2011). The 
bacterial communities in snow samples used in this experiment were also dominated by 
these phyla as well as the Beta-proteobacteria, whereas treated tanks harbored 
communities dominated by marine bacteria (Fig. S7). Shipboard experiments conducted 
during other voyages in May 2013 also identified an increase in these bacteria due to 
aerosol supplements (Asahi et al. 2016, Fig. S8). 
Sequences from the family Rhodobacteraceae recovered from the clone library 
were classified into clusters within the genus Roseobacter (Fig. 6) and were closely 
related to the sequences previously recovered from a variety of pelagic marine 
environments in the North Pacific Ocean and East Sea. Roseobacter species in the 
family Rhodobacteraceae have been associated with phytoplankton blooms (Elifantz et 
al., 2013), and they grow abundantly under high-nutrient conditions in marine 
environments (Wagner-Döbler and Biebl, 2006, Yeo et al., 2013). The genus 
Roseobacter includes ubiquitous marine bacteria, which contribute to the 
metabolization of a large variety of organic compounds and the demethylation of 
algae-producing DMSP (dimethylsulfoniopropionate) in oceanic environments 
(Brinkhoff et al., 2008), and are often reported to increase in relative abundance in 
seawater amended with organic matter (Landa et al. 2013). Members of Colwelliaceae 
are also known to degrade organic matter, such as aromatic hydrocarbons, which are 
stable in aquatic environments (Mason et al., 2014). Moreover, the bacterial species 
belonging to the families Rhodobacteraceae (Wagner-Döbler and Biebl, 2006) and 
Colwelliaceae (Mason et al., 2014) have been reported to consume nitrate via 
denitrification pathways. Therefore, in the snow solution-treated seawater, increased 
nitrate and organic matter leading to more yellow particles and microalgal cells, would 
induce the growth of heterotrophic bacteria (including representatives from the 
Colwelliaceae and Rhodobacteraceae), implying consequences for the carbon cycle in 
these aerosol-affected waters. 
In contrast, in the MiSeq sequencing database, phylotypes belonging to the 
SAR406 clade, Pelagibacteraceae, and Halomonadaceae decreased in seawater treated 
with snow solution over the course of the 2-day incubation (Fig. 5b). The clones 
recovered from subsamples collected from the experimental tanks clustered with 
sequences from members of the SAR406 clade, which are often detected in oligotrophic 
ocean regions (Table 2, Fig. 6) (Gordon and Giovannoni, 1996; Pham et al., 2008). The 
Pelagibacter representative of the Alpha-proteobacteria belonged mainly to the SAR 
clade, which dominate in the oligotrophic regions of the Pacific Ocean. Individuals 
from the family Halomonadaceae are members of the order Oceanospirillales, clones of 
which were more abundant in the clone libraries recovered from the control compared 
to the treated seawaters, and were related to pelagic bacterial sequences (Bacterium 
WBC-3-9) (Martinez-Garcia et al., 2012). Since marine bacterial communities, such as 
the Pelagibacter of the SAR clade, are mainly composed of obligate oligotrophic 
bacteria (Giovannoni and Stingl, 2005), nutrient enrichment is thought to reduce their 
growth. 
5. Conclusions 
In conclusion, we demonstrated that snow-borne aerosol particulates from the 
Asian continent have a measurable impact on the sea surface microbial community of 
the Pacific Ocean. Diatom growth was enhanced following the release of nitrate from 
snow and shifts in the bacterial community also occurred in the oligotrophic seawater 
after aerosol exposure. In the future, aerosol transport due to Chinese economic and 
industrial development is expected to increase the long-range transport of aerosols and 
aerosol deposition. This study highlights the potential impact that changes in aerosol 
production could have on marine chemistry and microbiology. 
Acknowledgements 
We are grateful to the captain and crew of the T/S Seisui Maru for their support at sea. 
Members of Fasmac Co., Ltd. helped with the MiSeq sequencing analyses. This 
research was supported by a Grant-in-Aid for the Encouragement of Young Scientists 
(26340049, 26304003) from the Ministry of Education, Culture, Sports, Science, and 
Technology of Japan. The Bilateral Joint Research Projects from the Japan Society for 
the Promotion of Science also supported this work, as did the Strategic International 
Collaborative Research Program (SICORP: 7201006051). 
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Figure legends 
Fig. 1. Snow samples were collected from Murododaira (36.58ºN, 137.60ºE) on Mt. 
Tateyama. The shipboard incubation experiment was performed in the Pacific Ocean at 
Site A (34.07ºN, 138.77ºE). 
Fig. 2. Changes in the concentration of nitrate, phosphate, and iron in the control (C), 
light dust event (LS), and high dust event (HS) tanks. Seawater samples were collected 
at Site A in the Pacific Ocean on 26 May 2012 and incubated for 2 days. The error bars 
were calculated from samples obtained from one 20-L and two 4-L experimental tanks. 
Fig. 3. Change in chlorophyll concentrations in the unfiltered subsample and the 
subsample fractions of >20 µm, 10–20 µm, 2.0–10 µm, and <2.0 µm in the control (C), 
light dust event (LS), and high dust event (HS) tanks. Seawater samples were collected 
at Site A in the Pacific Ocean on 26 May 2012 and incubated for 2 days. 
Fig. 4. Concentrations of cells classified as Pseudo-nitzschia and Chaetoceros species, 
and other diatom species in the control (C), light dust event (LS), and high dust event 
(HS) 20-L experimental tanks, at time points 0, 1, and 2 days. 
Fig. 5. Bacterial composition at the (a) class and (b) family level of the partial 
sequences in the MiSeq sequencing database (approximately 400 bp) obtained from the 
control (C), light dust event (LS), and high dust event (HS) 20-L experimental tanks, at 
initial and 2-day time-points. 
Fig. 6. Phylogenetic tree constructed from the partial sequences of 16S rDNA amplicons 
obtained from the clone libraries from the control (C), light dust event (LS), and high 
dust event (HS) tanks, and the known members of Cyanobacteria, Flavobacteria, 
Alpha-proteobacteria and Gamma-proteobacteria. The phylogenetic tree was calculated 
from a dissimilarity matrix of an approximately 550 bp alignment (E. coli numbered 
from 41 to 592) using a neighbor-joining algorithm. The names of representative clones 
(DSE12-5 series) are indicated. Open circles at branch points indicate bootstrap values 
obtained by the neighbor-joining analysis exceeded 50% after 1,000 replicate 
samplings. 
Japan Sea 
Pacific Ocean 
Fig. 1  T. Maki et al. 
Iron  
Phosphate 
Fig. 2 T. Maki et al. 
Nitrate 
Incubation time (day) 
Concentrations (µmol L-1) 
Tank HS 
Tank LS 
Tank C 
Fig. 3  T. Maki et al. 
Unfiltered sub-sample  
2.0-10 µm  
>20 µm  10-20 µm 
<2.0 µm  
Incubation time (day) 
Concentrations (µg L-1) 
Incubation time (day) 
Tank HS 
Tank LS 
Tank C 
Fig. 4  T. Maki et al. Incubation days 
0                    1                   2 
Concentrations of cells (106 cells /mL) 
Tank HS 
Others 
Pseudo-nitzschia species 
Chaetoceros species 
Tank C 
Tank LS 
Fig. 5  Maki et al. 
Relative abundance of 16S rDNA sequences (%) 
0 day 
Tank C 
2 day 
others 
Flavo   bacteriia   Alpha-proteo  bacteria   Gamma-   proteobacteria 
Cyano    bacteria 
SAR406 
Tank LS 
Tank HS 
Acidimicrobiia OCS155 
Flavobacteriaceae 
Rhodobacteraceae 
Alteromonadaceae 
Colwelliaceae 
Halomonadaceae 
Piscirickettsiaceae  
Others 
Alpha-proteobacteria unknown  
Gammaproteobacteria others  
Alphaproteobacteria others  
Pelagibacteraceae 
Cryomorphaceae  
Flavobacteriia others 
Class level 
Acidi   microbiia 
Cyanobacteria  others  
Family level 
Tank C 
Tank LS 
Tank HS 
0 day 
Tank C 
2 day 
Tank LS 
Tank HS 
Tank C 
Tank LS 
Tank HS 
 Fluviicola taffensis DSM 16823 (CP002542) Tenacibaculum maritimum FL-65 (KJ651994) 
 Polaribacter sp. J2-11 (HM010401)  Bacterium IMCC8968 (KJ492214) 
Flavobacteriaceae bacterium Hel1_33_7  (KF023505) 
Acidobacterium capsulatum (AB561885) 
Bacteroidetes 
C r y o m o r p h a c e a e  b a c t e r i u m  D G1 5 7 9  ( KM 2 7 9 0 2 8 )    
DSE12-5-Control-31 
DSE12-5-583L-31 
Polaribacter sp. HMF226 (KJ72884) 
 Tenacibaculum sp. KYW (JQ687111) 
Polaribacter porphyra (AB758590) 
 Bacterium IMCC7878 (KJ492024) 
 Bacterium IMCC11408 (KJ491882) 
Gamma proteobacteria 
Colwellia demingiae ACAM606 (U85844) 
Colwellia psychrotropica ACAM179T (U85846) 
Thalassomonas sp. CAU1252 (JX624251) 
 Alteromonas sp. CF12-5 (FJ170023) 
Glaciecola sp. Za3-19 (HQ875493) 
 Glaciecola sp. Ant12 (GQ149229) Glaciecola sp. 4H-3-7+YE-5 (CP002526) Alteromonadaceae bacterium ACEMC 8-7 (FM163113) Glaciecola agarilytica SW210 (KC178934) 
 Teredinibacter turnerae T7901 (EU604078)  Gammaproteobacteria bacterium (AB900126) 
Gamma proteobacterium JL-463 (DQ285073) 
Umboniibacter marinipuniceus KMM 3891 (AB467279) 
 Oceanospirillum multiglobuliferum NBRC 13614 (AB680461)  Marinomonas blandensis MED121 (DQ403809) 
 Reinekea aestuarii NBRC 106079 (AB682357) 
 Oceanospirillales bacterium SCGC AAA298-N10 (HQ675262) Gamma proteobacterium SCGC AAA076-C17 (JF488416) 
Gamma proteobacterium SCGC AAA160-J06 (JF488577)  Gamma proteobacterium SCGC AAA163-B13 (JF488625) Bacterium WHC3-1 (JQ269279) 
Gamma proteobacterium SCGC AAA158-C07 (JF488479) 
DSE12-5-583H-5 
DSE12-5-Control-40 
DSE12-5-583H-29 
DSE12-5-583H-10 
DSE12-5-Control-14 
DSE12-5-583L-15 
 Bacterium IMCC11662 (KJ491928) 
Thalassomonas sp. 0ma3 (JX436362) Colwellia sp. STAB604 (JF825446) 
Colwellia sp. Nordb14 (KC462890) 
Alpha proteobacteria 
Agrobacterium tumefaciens 
Phaeobacter caeruleus DSM 24564 (KC176242)  Alpha proteobacterium SCGC AAA298-K06 (HQ675249 ) 
Roseobacter sp. isolate PRLISY01 (Y15346)  Roseobacter sp.  (Y15339) 
Roseovarius sp. ZS4020 (FJ889548) Rhodobacteraceae bacterium LS53 (FJ937900) Rhodobacteraceae bacterium 5F6 (AB362414) 
 Amylibacter marinus (AB917595)  
Ophiopholis aculeata (U63548) 
Alpha proteobacterium SCGC AAA298-C20 (HQ675220) Alpha proteobacterium SCGC AAA298-C11 (HQ675217) 
Alpha proteobacterium SCGC AAA015-A04 (HQ675122) 
Pelagibacter ubique HTCC1002 (AF510192) Alpha proteobacterium IMCC14512 (JX439016) 
Candidatus Pelagibacter ubique (EU410957) Bacterium WHC5-1 (JQ269290) 
DSE12-5-583L-7 
DSE12-5-583H-30 
DSE12-5-Control-1 
DSE12-5-583L44 
 SAR406 cluster bacterium SCGC AAA240-I10 (HQ675595) 
SAR406 cluster bacterium SCGC AAA288-E05 (HQ675668) 
 ChlorobibacteriumSCGCAAA160-P03 (JF488613) 
SAR406 cluster bacterium SCGC AAA298-D23 (HQ675226) DSE12-5-Control-33 
Synechococcus sp WH8109 (AY172836)  Synechococcus sp. CC9605 (AY172802) 
Micromonas sp. RCC299 (FJ858267)  Bacterium WHC4-11 (JQ269289) 
Bacterium WHC4-8 (JQ269287) 
 Ostreococcus tauri RCC1561 chloroplast  (KF285533) 
Bacterium WHC3-9 (JQ269283) 
Cyano-bacteria 
DSE12-5-583L42 
Fig. 6  T. Maki et al. 
Flavobacteriace Rhodo-bacteraceae  
Pelagi-bacteracea 
Colwellia-ceae 
Alteromo- 
nadaceae 
Halomo- 
nadaceae AB16 
Incubationtime (day)CLSHSCLSHS
04.16 ± 1.435.70 ± 1.624.83 ± 1.07< 0.10.77 ± 0.391.18 ± 0.27
13.69 ± 0.875.85 ± 0.925.31 ± 1.69< 0.10.34 ± 0.140.89 ± 0.43
23.95 ± 1.088.53 ± 4.008.76 ± 2.11< 0.10.22 ± 0.190.86 ± 0.57
* Standard deviation was obtained from the values in one 20 L and two 4 L experimental tanks.(105 particles mL-1)
Table 1. Concentration of DAPI fluorescent particles in the control (C), light dust event (LS), and high dust event (HS) tanks.
Bacterial particles *Yellow fluorescence particls *
Control
1 mL snow
solution
5 mL snow
solution
Representative clonename*2
Cyanobacteria042  DSE12-5-583L-42590LC088185 Bacterium WHC3-9 (JQ269283)587/590(99.5%)
Actinobacteria011  DSE12-5-583L-11587LC088186 Phytomonospora  sp. KT1403 (KJ755850)509/590 (86.3%)
020  DSE12-5-583L-38519LC088187Actinobacterium SCGC AAA163-G08 (JF488172)511/520 (98.3%)
010  DSE12-5-583L-26522LC088188Kribbella catacumbae  (KM096442)461/522 (88.3%)
Alpha-proteobacteria10109  DSE12-5-583L-44591LC088189Candidatus Pelagibacter ubique  HTCC1062 (CP000084)586/591 (99.2%)
542  DSE12-5-Control-1536LC088190Alpha proteobacterium SCGC AAA298-C11 (HQ675217)532/536 (99.3%)
421  DSE12-5-Control-3      641LC088191Alpha proteobacterium HIMB5 (CP003809)633/641 (98.8%)
110  DSE12-5-Control-41      752LC088192Candidatus Pelagibacter ubique ( EU410957)696/752 (92.6%)
030  DSE12-5-583L-7646LC088193alpha proteobacterium SCGC AAA160-J18 (JF488581)638/646 (98.8%)
134  DSE12-5-583H-30   571LC088194Bacterium IMCC4848 ( KJ491760)571/571 (100%)
Bacteroidetes122  DSE12-5-Control-31564LC088195Bacterium IMCC11498 ( KJ491882)564/564 (100%)
111  DSE12-5-583H-24   592LC088196Bacterium WHC3-2 (JQ269280)566/592 (95.6%)
110  DSE12-5-583L-31582LC088197Polaribacter sp. HMF2268 (KJ728849)538/582 (92.4%)
Gamma-proteobacteria1455  DSE12-5-Control-14720LC088198Bacterium WHC3-1 (JQ269279)716/720 (99.4%)
111  DSE12-5-583L-15590LC088199Bacterium WHC3-1 (JQ269279)587/590 (99.5%)
110  DSE12-5-Control-40706LC088200Alteromonadaceae bacterium GWS-BW-H8gM (AY515434)671/706 (95.0%)
002  DSE12-5-583H-29571LC088201Bacterium IMCC8835 (KJ492170)563/571 (98.6%)
001  DSE12-5-583H-5 683LC088202Colwellia  sp. STAB604 (JF825446)668/683 (97.8%)
001  DSE12-5-583H-12778LC088203Alteromonadaceae bacterium NB0076-02 (KP770091)767/778 (98.6%)
001  DSE12-5-583H-10791LC088204Umboniibacter marinipuniceus (AB467279)783/791 (99.0%)
Eukaryota111  DSE12-5-Control-36       789LC088205Pinus merkusii  chloroplast (KP771703)787/789 (99.7%)
022  DSE12-5-583L-28333LC088206Thalassiosira pseudonana mitochondrion (DQ186202)312/337 (92.6%)
013  DSE12-5-583L-43593LC088207Pseudo-nitzschia multiseries  chloroplast (KR709240)583/593 (98.3%)
002  DSE12-5-583H-3      619LC088208Pseudo-nitzschia multiseries mitochondrion (KR149143)582/620 (93.9%)
002  DSE12-5-583H-27     592LC088209Chaetoceros sp. C134 chloroplast (FJ002204)586/590 (99.3%)
001  DSE12-5-583H-35775LC088210Emiliania huxleyi  strain CCMP 373 chloroplast (AY741371)773/775 (99.7%)
SAR406 (AB16)120  DSE12-5-Control-33563LC088211SAR406 cluster bacterium SCGC AAA298-D23 (HQ675226)563/563 (100%)
*1  Numbers of the clones in 16S rDNA clone libraries recovered from the seawater samples treated without snow solution, with 1 mL and 5 mL snow solutions. 
*2  Representative clones in 16S rDNA library indicate phylotepes that were classified with more than 97% similarity, and were named as the DSE12-5 series.
*3  The sequence length of each representative clone.
*4  Similarity value between each representative clone and the closest relative in databases.
Similarity (%)*4
Table 2. Phylogenetic affiliation of 16S rDNA gene sequences obtained from clone libraries.  
Category
Numbers of clones*1
Length(bp)*3GenBankaccession no.Closest relative