Origin-Dependent Variations in the Atmospheric Microbiome

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Origin-Dependent Variations in the Atmospheric Microbiome Community in Eastern Mediterranean Dust Storms Daniella Gat, Yinon Mazar, Eddie Cytryn, and Yinon Rudich Environ. Sci. Technol., Just Accepted Manuscript • Publication Date (Web): 19 Apr 2017 Downloaded from http://pubs.acs.org on April 20, 2017

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Environmental Science & Technology

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Origin-Dependent Variations in the Atmospheric

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Microbiome Community in Eastern Mediterranean

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Dust Storms

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Daniella Gat,1 Yinon Mazar,1 Eddie Cytryn,2 Yinon Rudich1*

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1

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Department of Earth and Planetary Sciences, Weizmann Institute of Science,

Rehovot 7610001, Israel. 2

Institute of Soil, Water and Environmental Sciences, The Volcani Center,

Agriculture Research Organization, Rishon Lezion 7528809, Israel

1

ACS Paragon Plus Environment


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Abstract Microorganisms carried by dust storms are transported through the atmosphere and

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may affect human health and the functionality of microbial communities in various

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environments. Characterizing the dust-borne microbiome in dust storms of different

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origins or that followed different trajectories, provides valuable data to improve our

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understanding of global health and environmental impacts. We present a comparative

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study on the diversity of dust-borne bacterial communities in dust storms from three

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distinct origins—North Africa, Syria and Saudi Arabia—and compare them with local

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bacterial communities sampled on clear days, all collected at a single location, in

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Rehovot, Israel. Storms from different dust origins exhibited distinct bacterial

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communities, with signature bacterial taxa. Dust storms were characterized by a lower

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abundance of selected antibiotic resistance genes (ARGs) compared with ambient

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dust, asserting that the origin of these genes is local, possibly anthropogenic. With the

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progression of the storm, the storm-borne bacterial community showed increasing

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resemblance to ambient dust, suggesting mixing with local dust. These results show,

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for the first time, that dust storms from different sources display distinct bacterial

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communities, suggesting possible diverse effects on the environment and public

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health.

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Introduction

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Dust-storms carry biological particles, such as plant debris, pollen, fungi and

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bacteria, along with soil and mineral particles, over vast distances1,2. These biological

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airborne particles play important roles in the Earth system by coupling between the

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biosphere and the atmosphere3-6. Airborne bacteria may affect human health by

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spreading pathogens7, they express proteins that serve as ice nuclei, potentially

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affecting cloud formation8, and could affect agriculture and ecosystems health by 2


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spreading pathogens and bacteria that impact biogeochemical cycles 7,9,10. This wide

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array of potential implications of bacterial transport through the atmosphere, brought

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about an increasing interest in the bacterial diversity in aerosols and dust (e.g. 2,11-

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14). The study of microbial diversity in dust previously relied mainly on culture-based

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methods15, which are usually time consuming, and capture only a fraction of the total

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bacterial diversity. Recent developments of culture independent methods for

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microbiological analysis open-up the possibility to extensively study and characterize

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the atmospheric microbiome12,15,16. A limited number of studies, using next-

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generation sequencing techniques for microbial community characterization have

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shown that different dust origins display diverse microbial communities2,11,16 in which

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up to 25% of the bacteria remain viable17,18. This variety in bacterial community

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composition could translate into various health, biogeochemical, or environmental

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effects1,9,19.Previous studies of the dust microbiome have monitored ambient changes

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in the airborne bacterial community in urban locations in the US, using PhyloChip

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detection7, and examined bacterial community differences between clear days and

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dust-storms in the Eastern Mediterranean using next-generation sequencing11. Other

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studies have mapped the differences between bacterial and fungal communities using

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next-generation sequencing in settled dust in different geographic locations across the

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US13, the seasonal variations in concentrations and composition of allergenic fungal

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spores were determined using qPCR and next-generation sequencing20,21, and the

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seasonal variability of airborne microbial communities in rural and urban locations in

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the US was examined over a period of 14 months14. Most of these studies explored

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ambient aerosols and settled dust, which often reflect their immediate surroundings11-

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represent the source bacterial community22,23. The role of dust storms in spreading

; in contrast, bacteria in dust storms are carried over large distances and may

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nutrients has been previously demonstrated, along with ecological changes attributed

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to dust deposition24-26. It was also shown that dust-borne bacteria can contribute to N2

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fixation in marine environments9, and that dust from different sources can produce a

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distinct effect on bacterial production and community composition in seawater25.

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However, the possible effect of deposition of dust-borne microorganisms on

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indigenous microbial communities, and the relationship between the sources of the

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atmospheric microbiome and microbial community composition are yet under-

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characterized, and represent an important gap in the scientific knowledge about Earth

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microbiomes27,28.

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Dust storms are known to pose health risks due to inhalation of particulate

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matter29,30, yet their role in spreading antibiotic resistance genes (ARGs), originating

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in soil bacteria, is still being unraveled11,31,32. The introduction of ARGs into

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pathogenic bacterial strains, via horizontal gene transfer, may result in increasing the

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abundance of antibiotic resistant pathogens33. Thus, soil dust could potentially

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become a vector for spreading antibiotic resistance genes, which is an increasing

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global health problem34. Conversely, recent evidence suggests that airborne ARGs

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originate from anthropogenic sources, such as chicken coops and agricultural plots,

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and are less abundant in storm dust from North Africa11. This, again, highlights the

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importance of the origin of the dust in assessing its potential affects.

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The Eastern Mediterranean is frequented by seasonal dust storms, usually lasting 1–

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2 days35. Global drying and warming trends are predicted to increase the frequency

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and intensity of dust storms from this region, and particulate matter measurements

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from Israel show that dust events have become more extreme, with higher daily and

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hourly levels, since 200936,37. Most dust storms in the Eastern Mediterranean originate

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in the Sahara Desert, while some originate in south-eastern deserts, such as in the

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Arabian Peninsula (Arabian Desert)37.

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On September 8, 2015, a dust storm that was unprecedented with respect to the

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conditions that initiated it, its origin, magnitude and duration, reached Israel from

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Northern Syria35,38,39. Another intense dust storm from Jordan and the Arabian

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Peninsula affected the region on November 3, 2015. These two storms were sampled

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at a single location at the Weizmann Institute of Science in Rehovot, Israel, and were

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compared to dust collected, in the same location, and described by Mazar et al.11

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during two major North African dust storms, on March 3, 2014, and on February 10–

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11, 2015. All storm samples were also compared to pooled aerosol samples collected

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on nine clear days (i.e., PM10 < 53 µg m-3).

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Here we present a first comparative study of bacterial communities in dust storms

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originating from three different locations, using next-generation sequencing. We also

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examine the contribution of these storms to the local airborne reservoir of selected

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ARGs and horizontal gene transfer related elements, to detect possible differences in

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ARG abundance between different dust origins.

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Experimental

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Dust collection

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Atmospheric particulate matter having an aerodynamic diameter smaller than 10 µm

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(PM10) was collected, as described in Mazar et al.11, on quartz microfiber filters

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(Whatman, 203 mm × 254 mm) using a high-volume air sampler (Ecotech, model:

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HiVol 3000, PM10 inlet, flow rate: 67.8 m3·h-1) situated on the roof of a four-story

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building in the Weizmann Institute of Science, Rehovot, Israel (31.9070 N, 34.8102

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E). Despite the wide distribution of particle sizes carried by dust storms, we focused

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on PM10 since small size particles tend to travel greater distances40, thus they should

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better represent the source of the dust.

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Prior to sampling, all filters were baked at 450°C for five hours to clean them of all

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organic matter. Post-sampling, all filters were kept at -20°C until DNA was extracted.

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Sampling took place during major dust storms between March 2014 and November

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2015 and during clear days exhibiting PM10 concentrations under 53 µg·m3 (exact

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dates of clear days are reported in Mazar et al.11 and in Table S1). The threshold for

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clear days was established to be lower than the annual mean of urban PM10

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concentrations in Israel, i.e., 53 µg·m3, according to the World Health Organization

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database41. The total estimated weight of sampled dust was approx. 0.2 g per filter.

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Backward trajectory calculations and meteorological data

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Identification of the origin for each storm event was achieved using backward

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trajectory calculations on the Hybrid Single Particle Lagrangian Integrated Trajectory

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Model (HYSPLIT)42, via the web-based interface (READY,

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http://ready.arl.noaa.gov/HYSPLIT_traj.php). The back-trajectories for the September

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2015 storm were more complex, as a dust plume that formed over northern Syria

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propagated south-west and was then spread along the eastern Mediterranean coast due

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to a wind reversal35,38. Data of atmospheric PM10 concentrations were obtained from

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the Israeli Ministry of Environmental Protection database, Rehovot Air Monitoring

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station (http://www.svivaaqm.net/StationReportFast.aspx?ST_ID=32).

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DNA extraction, amplification, and sequencing

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The DNA extraction procedure was described in Mazar et al.11. In short, dust was

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scraped from the filters using a sterile surgical scalpel and transferred to PowerSoil kit

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bead-tubes (MoBio). The extraction procedure followed the manufacturer’s

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recommended protocol with slight modifications. All DNA samples were kept at -

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20°C. DNA sequencing was conducted at the DNA Sequencing Facility (DNAS) at

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the University of Illinois at Chicago (UIC), using Illumina Miseq instrument. The

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targeted sequence is a segment of the V4 region in the 16S rRNA gene, the primers

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used were: CS1_515F

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(ACACTGACGACATGGTTCTACAGTGCCAGCMGCCGCGGTAA) and

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CS2_806R (TACGGTAGCAGAGACTTGGTCTGGACTACHVGGGTWTCTAAT)

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-SRR5247695). Merging of paired-end reads as well as quality trimming were

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conducted by the Research Resources Center of the UIC. The produced Fasta files

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were analyzed with mothur v. 1.39.044 software, according to the pipeline described in

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Kozich et al.45 and on the website: http://www.mothur.org/wiki/MiSeq_SOP, a

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complete command log is described in the supporting information. Taxonomic

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classification of the assembled sequences was conducted using Silva rRNA

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database46, v.123.

. All sequences were submitted to the NCBI SRA database (accession: SRR5247688

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Quantification of total bacteria and of selected genes was achieved by qPCR. The

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applied primers are listed in Table 1. The qPCR results for the storms dated March 3,

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2014 and February 10–11, 2015, and for clear days were obtained from Mazar et al.11.

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For samples obtained during the September 2015 and the November 2015 storms, the

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following 25 µl reaction mixture was prepared: 12.5 µl of SensiFAST™ SYBR mix

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(Bioline®), 1 µl of each primer (0.4 mM), and 7.5 µl of template DNA. Amplification

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took place in a StepOnePlus™ real-time qPCR (ThermoFisher Scientific®) as follows:

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3 min at 95°C, followed by 35 cycles of 2 s at 95°C and 30 s at 60°C. The standard

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curve for all qPCR reactions was plotted based on amplification of known

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concentrations of pNORM1 plasmid (see supporting information for description),

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along with a non-template control.

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Table 1: qPCR primers list.

Target Gene intI1

sulI

qnrS

16S

Primer

Sequence

Reference

intI1LC5 (F)

GATCGGTCGAATGCGTGT

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intI1LC1 (R)

GCCTTGATGTTACCCGAGAG

sul1-FW

CGCACCGGAAACATCGCTGCAC

sul1-RV

TGAAGTTCCGCCGCAAGGCTCG

qnrSrtF11

GACGTGCTAACTTGCGTGAT

qnrSrtR11

TGGCATTGTTGGAAACTTG

331F

TCCTACGGGAGGCAGCAGT

518R

ATTACCGCGGCTGCTGG

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49

50

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Results and Discussion

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Dust sources

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Sample names, dates and origins are listed in Table 2. Backward trajectories of the dust storms analyzed in this study are presented in

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Table 3. The March 2014 and February 2015 dust storms originated in the Saharan

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region of North Africa. However, the paths of these storms differed somewhat, as the

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March 2014 storm’s trajectory passed over the Mediterranean Sea, north of the Nile

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delta, whereas the February 2015 trajectory did not. During the first two sampling

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days (Arabia_d1 and Arabia_d2) of the November 2015 storm, the dust originated in

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Saudi Arabia and Jordan, whereas following a change in wind direction, the last

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sampling day (Arabia_d3) represented dust from the Red Sea, the Gulf of Eilat/Aqaba

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close to the Saudi Arabian coast, and the Israeli Negev. According to satellite images,

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as well as published data39, the September 2015 storm originated in north-east Syria,

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around the Euphrates valley and the city of A-Raqqa. Back trajectories show the dust

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progressed southwards towards the Golan heights and from there it was carried and

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spread over Israel due to wind reversal.

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Table 2: Sample names, sampling dates, dust concentration on each sampling day and dust source. PM10

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values represent the average daily concentration of particulate matter measuring 10 µm or less in diameter

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on each sampling date, as measured by the Rehovot Air-Monitoring station and available on:

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http://www.svivaaqm.net/StationReportFast.aspx?ST_ID=32

Sample name

Date

PM10 (µg·m-3)

Source

NCBI accession no.

Sahara1

03-Mar-14

838

North-Africa

SRR5247690

Sahara2_d1

10-Feb-15

482

North-Africa

SRR5247689

Sahara2_d2

11-Feb-15

1643

North-Africa

SRR5247688

Syria_d1

08-Sep-15

844

Syria

SRR5247693

Syria_d2

09-Sep-15

1859

Syria

SRR5247692

Syria_d3

10-Sep-15

928

Syria

SRR5247691

Arabia_d1

03-Nov-15

422

Saudi Arabia

SRR5247696

Arabia_d2

04-Nov-15

810

Saudi Arabia

SRR5247695

Arabia_d3

05-Nov-15

453

Saudi Arabia

SRR5247694

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Table 3: Back-trajectories of each storm sample as obtained from the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT)42 (http://ready.arl.noaa.gov/HYSPLIT_traj.php).

Sahara1

Sahara2_d1

Sahara2_d2

Syria_d1, d2, d3

Arabia_d1

Arabia_d2

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Arabia_d3

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Bacterial community composition

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The bacterial community composition of the collected dust is presented in Figure 1.

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For comparison, the 16S rRNA gene amplicon sequences extracted from dust samples

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during clear days and during North-African storms, obtained and presented by Mazar

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et al.11, were re-analyzed in tandem with the September 2015 and November 2015

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dust samples (clear days’ samples are detailed in Table S1). The most abundant phyla

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in all sampled storm dust microbiomes were varying proportions of Actinobacteria,

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Proteobacteria, Firmicutes, Chloroflexi, and Bacteroidetes.

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North African dust storms were characterized by the low abundance of Chloroflexi

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and relatively high abundance of Deinococcus-Thermus, compared to the other storm

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origins. The differences observed between the different North-African dust samples,

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may have arisen from different paths, as observed by their back-trajectories (Table 3).

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Sample Sahara1 represents dust that was carried shortly over the Mediterranean Sea,

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north of the Nile delta, whereas samples Sahara2_d1 and Sahara2_d2 represent a

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solely terrestrial trajectory, via northern Egypt and the Sinai desert. Other parameters

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that might have caused differences between these storms may be the time of their

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occurrence, almost a year apart; and/or the different seasons, since one took place

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during early spring (Sahara1 on March 2014) and the other during the winter

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(Sahara2 on February 2015).

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The dust storm from Syria was characterized by a high relative abundance of

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Cyanobacteria and Chloroflexi and low relative abundance of Firmicutes, compared

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with other dust origins. During the storm, an increase in the relative abundance of

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Firmicutes was observed, from 2% on sample Sahara_d1 to 8% on sample

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Sahara_d3.

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The Saudi Arabian storm differed from the other two dust storms in the relatively

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low abundance of Actinobacteria and the high abundance of Proteobacteria. A notable

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change in bacterial community composition was observed during this storm; while the

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first two days (samples Arabia_d1 and Arabia_d2) exhibited a similarity in bacterial

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community composition with 30% Actinobacteria, 29% Proteobacteria, 10%

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Bacteroidetes and 9% Chloroflexi in both samples, on the third day (Arabia_d3) the

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samples exhibited a relatively high abundance of Firmicutes, 29%, compared to

Origin-Dependent Variations in the Atmospheric Microbiome

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