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Influence of Soil Characteristics and Proximity to Antarctic Research Stations on Abundance of Antibiotic Resistance Genes in Soils Fang Wang, Robert D. Stedtfeld, Ok-Sun Kim, Benli Chai, Luxi Yang, Tiffany M. Stedtfeld, Soon Gyu Hong, Dockyu Kim, Hyoun Soo Lim, Syed A. Hashsham, James M. Tiedje, and Woo Jun Sul Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b02863 • Publication Date (Web): 31 Oct 2016 Downloaded from http://pubs.acs.org on November 2, 2016
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Influence of Soil Characteristics and Proximity to Antarctic Research
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Stations on Abundance of Antibiotic Resistance Genes in Soils
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Fang Wang†,‡,◊,♯, Robert D. Stedtfeld§, ♯, Ok-Sun Kim┴, ♯, Benli Chai†,‡, Luxi Yang†,‡,§,
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Tiffany M. Stedtfeld§, Soon Gyu Hong┴, Dockyu Kim┴, Hyoun Soo Lim△, Syed A.
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Hashsham†,‡,§, James M. Tiedje†,‡, and Woo Jun Sulǁǁ,∗
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†
Department of Plant, Soil and Microbial Sciences, ‡ Center for Microbial Ecology,
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§
Department of Civil and Environmental Engineering, Michigan State University, MI
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48824, USA
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┴
Division of Life Sciences, Korea Polar Research Institute, Incheon 21990, Republic
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of Korea
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ǁǁ
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Republic of Korea
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◊
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Science, Chinese Academy of Sciences, Nanjing 210008, PR China
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Department of Systems Biotechnology, Chung-Ang University, Anseong 17546,
Key Laboratory of Soil Environment and Pollution Remediation, Institute of Soil
△
Department of Geological Sciences, Pusan National University, Busan 46241,
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Republic of Korea
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♯
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∗
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[email protected], address: 4726 Seodong-daero, Anseong 17546, Republic of
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Korea.
F.W., R.D.S., and O.K. contributed equally to this work. Corresponding author, Tel: +82-31-670-4707, Fax: +82-31-675-3108, E-mail:
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TOC/ABSTRACT ART
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ABSTRACT
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Soil is an important environmental reservoir of antibiotic resistance genes (ARGs),
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which are increasingly recognized as environmental contaminants. Methods to assess
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the risks associated with the acquisition or transfer of resistance mechanisms are still
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underdeveloped. Quantification of background levels of antibiotic resistance genes
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and what alters those is a first step in understanding our environmental resistome.
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Towards this goal, 62 samples were collected over 3 years from soils near the 30-year
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old Gondwana Research Station and for 4 years before and during development of the
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new Jang Bogo Research Station, both at Terra Nova Bay in Antarctica. These sites
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reflect limited and more extensive human impact, respectively. A qPCR array with
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384 primer sets targeting antibiotic resistance genes and mobile genetic elements
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(MGEs) was used to detect and quantify these genes. A total of 73 ARGs and MGEs
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encompassing eight major antibiotic resistance gene categories were detected, but
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most at very low levels. Antarctic soil appeared to be a common reservoir for seven
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ARGs since they were present in most samples (42%-88%). If the seven widespread
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genes were removed there was a correlation between the relative abundance of MGEs
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and ARGs, more typical of contaminated sites. There was a relationship between
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ARG content and distance from both research stations, with a significant effect at the
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Jang Bogo Station especially when excluding the seven widespread genes, however
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the relative abundance of ARGs did not increase over the 4 year period. Silt, clay,
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total organic carbon and SiO2 were the top edaphic factors that correlated with ARG
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abundance. Overall, this study identifies that human activity and certain soil 3
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characteristics correlate with antibiotic resistance genes in these oligotrophic
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Antarctic soils and provides as a baseline on ARGs and MGEs for future comparisons.
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INTRODUCTION The recent emergence of multidrug-resistant bacteria has motivated proposed
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strategies toward containment of antimicrobial resistance. 1, 2 Recommendations
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include monitoring antibiotic resistance to examine pathways in which the natural
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resistome serves as a potential source of resistance in human and animal pathogens. 3-5
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Recent studies have demonstrated anthropogenic influences on the levels of antibiotic
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resistance genes (ARGs) in agriculture soils,6, 7 food,8, 9 and water habitats. 10-12
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However, the diversity and abundance of antibiotic resistance in regions less affected
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by anthropogenic influences may offer more insight into mechanisms for containment.
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Harsh environments such as the Antarctic may select for or against microorganisms
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with ARGs, in the former case by using antibiotic production and resistance to
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compete for very limited resources. 13, 14
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Previous studies have reported antibiotic resistance in a number of environments
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thought to be less impacted by anthropogenic influence including some soils, water,
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sediments, glaciers, and deep ocean. 15-19 ARGs have also been detected in remote
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human communities, 20 wild rodents, and porcine not exposed to antibiotics or
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external influences. 21 Antimicrobial resistance determinants have been observed in
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Escherichia coli isolates originating from Arctic birds. 22 However, studies examining
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ARGs in Antarctic samples are limited. A survey of six surface snow samples from 4
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Antarctica found only a single ARG from a site with 25 years of regular expeditions.
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Antarctic sponge samples. 23
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Contrary to this, multiple gentamicin resistance isolates were observed from three
Most antibiotics are produced by microorganisms that occur naturally in soil. 5, 24
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For example, soil is a natural habitat for Streptomyces, whose species account for a
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majority of naturally produced antibiotics. 4, 25, 26 Soil is also one of the most diverse
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and largest microbial habitats on earth and is recognized as a great repository of
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ARGs, 4, 15, 26, 27 which may also serve as a reservoir due to anthropogenic influenced
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selection. 5 As such, soil is a well-suited matrix for capturing the selective influences
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of human activity.
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ARGs can be dispersed by physical and biological forces such as wind, water,
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animals, and humans, resulting in their presence in many environments. 5, 22, 28 ARGs
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can also be widely disseminated by birds, 22 e.g. the Arctic tern travels to up to six
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continents and migrates to Antarctica for winter. From a micro view, ARGs may be
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mobilized and transferred by mobile genetic elements (MGEs), including transposons,
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integrons and plasmids. Many of the known ARGs are found on MGEs, which can be
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transferred to other bacteria of the same or different species.5
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Our main hypothesis was that ARGs and MGEs in Antarctic soil would reflect
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human impact caused by construction of the new Jang Bogo Research Station. A
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secondary aim was to assess the types and distribution of ARGs in Antarctic soil with
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no or low human activity. To examine long and short term influence of human
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activity on the distribution of ARGs, soil samples were collected at different 5
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proximities from the 30-year old Gondwana Research Station and the newly
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developed Jang Bogo Research Station, both in the Terra Nova Bay area of southwest
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Antarctica. A highly parallel qPCR array with 384 primer sets targeting 285 ARGs
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and 35 MGEs was used. Assays targeted three major resistance mechanisms: cellular
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protection, antibiotic deactivation, and efflux pumps, and conferred resistance to most
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major antibiotics.
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MATERIALS AND METHODS Sites and soil sampling. A total of 62 soil samples were collected from the Terra
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Nova Bay (east side of the Ross Sea) in southeast Antarctica in the summers of 2011,
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2012, 2013 and 2014, which is before and during construction of the Korean Antarctic
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Research Station, Jang Bogo (Fig. S1, Table S1). A wide variety of life forms, such as
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bryophytes, lichens, sea birds, marine mammals, and invertebrates have been
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observed in this area. This site is mainly composed of exposed bedrock and glacial
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moraines, 29 and with extreme low levels of organic matter for soil (total organic
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carbon contents are mainly lower than 0.08%) (Table S3). Samples were collected
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near the Jang Bogo Research Station to investigate the background level of ARGs
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before human activity, and then followed by samples collected during facility
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construction where the soil nearby were heavily plowed, hence reflecting short-term
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human activity. Samples were also collected near the 30-year old German Antarctic
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Research Station (Gondwana) to investigate long-term but minimal impact of human
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activity on ARGs in soil. The sites from the coast to the research station and partially 6
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up the mountain were selected for investigating the background level of ARGs in soil
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further from the research stations. At each sampling site, soil samples were collected
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from 0-3 cm layer, mixed to homogenize inside a plastic zip lock bag, and
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immediately frozen on dry ice. All soil samples were stored at -80 °C until DNA
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extraction. The environmental DNA was extracted from 0.5 g wet weight soil, using
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the Powersoil® kit (MO BIO, Carsbad, CA, USA). The DNA quality and
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concentration were measured with a Qubit Fluorometer (Life Technology, Eugene,
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OR, USA).
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Primer design. A total of 384 primer sets (Table S2) were assayed, which
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included 356 primers that were designed, validated, and used in previous studies. 18, 30
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For the present study, 28 additional primer sets were designed targeting additional
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MGEs, beta-lactamase and multidrug resistance genes. The same design parameters
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and protocol were used as previously described 31 with alleles collected using the
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Fungene Pipeline Repository. 32
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QPCR array. All quantitative PCR reactions were performed using a Wafergen
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SmartChip Real-time PCR system (Fremont, CA, USA) as reported previously. 19
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Briefly, the Wafergen array allows for 5,184 qPCR reactions each with 100 nl volume
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to be run in parallel. Sample and primers were dispensed into the SmartChip using a
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Multisample Nanodispenser (Fremont, CA, USA). PCR cycling conditions and initial
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data processing were performed as described. 19 As previously described, ~ 50% of 7
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tested assays had a detection limit lower than 10 genomic copies per reaction, and ~
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85% of tested assays had a detection limit below 100 genomic copies per reaction,
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based on low volume qPCR and the primer design strategy. 31 Translation to absolute
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detection limit will vary based on sample matrices and method of DNA extraction.
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Validation of ARG primer specificity has also been described previously, 18 including
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sequencing amplicons from 35 primer sets that commonly show positive amplification
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on the array. 33 In detail, over 98% of assembled amplicon reads (mapped to targeted
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references using FrameBot) were > 90% identical to a reference sequence. A more
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detailed discussion on specificity, sensitivity and limitations of the array is provided
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in the supplemental file (S1).
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The mass of template DNA varied among samples (Table S1). To normalize for
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differences in DNA template quantities and PCR inhibitors that could influence
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amplification efficiency, estimated quantities were calculated as the relative
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abundance. This was calculated by dividing the estimated gene copies of the specific
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gene by estimated copies of the 16S rRNA gene. Gene copy numbers were estimated
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using the equation 10^(30-Ct)/(10/3), where Ct equals the threshold cycle as
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described previously. 30 A threshold cycle of 30 was used as a cutoff to differentiate
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between true positive amplification and primer-dimers, which is more conservative
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than previously used. 19
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The relative abundance and standard deviations were calculated using Microsoft
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Excel 2010 as previously described. 30 Genes detected in only one of the three
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technical replicates in each sample were considered false positives and were removed 8
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from analysis. Negative controls (no added DNA template) were also run on the array,
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and that amplified were excluded.
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Data analysis. Multivariate analysis of the difference between ARG profiles in
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different samples was performed in R using the Vegan package. 34 Log2 transformed
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percentage values of the gene abundances relative to the 16S rRNA gene were used
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for Redundancy Analysis. A Mantel test was conducted to test the spatial effect on the
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distribution of ARGs in soil with the Bray method in Vegan package. Canonical
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correspondence analysis (CCA) between the relative abundance of ARGs and
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environmental variables - analyzed as previously reported -
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performed followed by Mantel test using Vegan package. Environmental variables
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were chosen based on significance calculated from individual CCA results and
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variance inflation factors (VIFs) calculated during CCA. While microbial data (Table
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S3) were not available for the fourth year, correlation analysis between the Shannon
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index of bacteria and of ARGs was performed for the 3 years’ samples. The Venn
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map was built in R with Vennerable package. Spearman correlation between
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abundances of ARG and MGE was performed with Sigmaplot 10.0. QPCR results
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from swine farms, park soils, sewage, river and lake samples18, 19, 35, 36 (Table S4)
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were included to compare ARG occurrence among sample types and to assess validity
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of the qPCR array data. RDA ordination was performed using the Log transformed
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summarization of relative abundance for all primers targeting a given gene. All
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(Table S3) were
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analyses were performed using R Studio v.3.1.3 37 and threshold for significance was
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selected at p < 0.05.
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RESULTS AND DISCUSSION ARGs in Antarctic soils. ARGs were detected in all the Antarctic soil samples
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with the most frequently detected gene being blaFOX (also fox5) (Fig. 1). The gene
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with the highest relative gene copy number as well as relative abundance was the
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mexF gene (Table S5). Overall, 67 ARGs were detected covering the eight major
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types of antibiotic resistances with the main ones conferring multiple drug resistances
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(Fig.1, Fig. S2a). ARGs detected include four main resistance mechanisms, with the
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highest number classified as multidrug efflux pumps (Fig. S2b). Contrary to a
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previous report in which only mefA/E gene was detected in one of the Antarctic
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glacial samples,17 the soil samples had a greater abundance of ARGs (Fig.1). The
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study by Segawa and coauthors 17 used only 96 TaqMan-based primer sets while our
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study used 384 SYBR-based primers. The different number of targets, coverage of
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primers, and sample matrices (surface snow versus underlying soil) confounds the
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comparison of results between the two studies.
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Among the genes detected, seven ARGs (blaTEM, blaSFO, blaFOX, cphA, mexF,
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oprD and oprJ) were frequently observed (Fig. 1) and evenly represented in all soil
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samples (Fig. S1), indicating that this Antarctic region is a reservoir for these genes or
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gene fragments. The blaTEM gene is one of the most widespread ARGs in the
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environment, and is usually associated with Enterobacteriaceae. 38 The blaFOX gene 10
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is associated with beta-lactam resistance 39 and is typically observed in gram negative
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enteric organisms (e.g. E. coli and Klebsiella). The cphA gene is intrinsic in the
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environmental isolates of Aeromonas hydrophila and A. jandaei. 40 The mexF, oprD
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and oprJ genes are components of two operons (mexC-mexD-oprJ and mexE-mexF-
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oprN) of Pseudomonas aeruginosa - a clinically significant pathogen but also in some
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soils. Over-expression of the two operons confers to cells resistance to
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fluoroquinolones, the “fourth-generation” cephems, tetracycline, imipenem and
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chloramphenicol and hypersusceptibility to most other β-lactams. 41, 42 MexCD-OprJ
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plays an important role in intrinsic multidrug resistance in wild-type P. aeruginosa
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which has resistance to many antimicrobial agents mediated by multidrug efflux
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pumps. 43 The mexF gene has previously been observed in many different
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environments, such as soil, sediments, river water and drinking water. 44 It is also
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prevalent in pigs not exposed to antibiotics, but interestingly is not found in pigs
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given antibiotic treatment. 45 The mexF and oprD genes are also proposed to naturally
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exist in water. 35
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Validity of the ARG qPCR array was demonstrated in comparing ARGs numbers
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detected in Antarctic soil samples with other samples types. As expected, lower
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detection frequency (proportion of qPCR positive assays to the total number of
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targeted assays) was found in the Antarctic soil than park soil, pig farms, sewage and
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river water samples, but similar to those found in the Michigan lake water samples
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(Fig. 2). 18, 19, 35, 36 Furthermore, the number of ARGs detected in the Antarctic soils is
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similar to numbers detected in oligotrophic sample types using a different method, i.e. 11
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shotgun metagenomics. For example, between 9 and 38 ARGs were detected by this
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method in seven influent and effluent drinking water samples.46 Regarding
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correspondence of individual genes, ARGs such as mexF (detected in 41 of 62
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Antarctica soil samples using qPCR) were also detected in all seven drinking water
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samples via shotgun metagenomics.
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MGEs in Antarctic soil. MGEs were also detected in all of the tested soil samples.
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Overall, six out of 35 targeted MGEs were detected (Fig. 1). Among these genes,
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pNI105 gene was detected in most of the soil samples (Fig. 1). The pNI105 gene has
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been described as a small plasmid, which is non-transmissible, but confers high-level
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resistance to kanamycin and neomycin. 47 However, ARGs associated with resistance
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to these antibiotics were not detected. The IncP-1 oriT genes were also found in some
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soil samples. The IncP-1 plasmids harbor determinants for resistance to several
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groups of antibiotics, i.e., tetracyclines, quinolones, aminoglycosides, sulfonamides,
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β-lactams, and chemotherapeutics. 48-50 These plasmids have also been described as
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key plasmids in the horizontal transfer of ARGs of all classes in the environment, i.e.,
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efflux pumps, enzymatic modification or hydrolysis of the antibiotic molecule. 48 No
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correlation was observed between the relative abundance of MGEs and ARGs (Fig.
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3a); however, exclusion of the seven ARGs present in most samples resulted in a
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significant positive correlation (Fig. 3b). A high correlation between abundance of
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ARGs and levels of MGEs has been reported in farm samples, 18 which suggests that
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horizontal gene transfer may have aided dissemination of ARGs, and hence may also
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have occurred at some point in their history for those genes currently in Antarctic
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soils.
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Proximity of ARGs to Antarctic stations. A redundancy analysis of relative
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abundance of detected ARGs in the soils based on geography was performed.
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Detected ARGs fell into three groups: soils near the Gondwana Station (1000 m
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radius) (GS), soils near the Jang Bogo Station (500 m radius) (JS) and soils farther
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away (further than 1350 m and 750 m, respectively) from the two stations (FS) (Fig.
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4a). Redundancy analysis showed significant grouping; however, some soil samples
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were outliers, showing that other factors also affect the ARG distribution. Therefore, a
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CCA analysis was performed using 25 soil parameters (Table S3), proximity to
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stations, and microbial community data (Fig. 5). From the CCA analysis, distance to
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the research stations had two of the four highest correlations with relative abundance
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to ARGs (Fig. 5a). A stronger correlation between relative abundance of ARGs and
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the proximity of the sampling site to Jang Bogo Station was observed compared to
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proximity to Gondwana Station (Fig. 5a), suggesting construction-based activities had
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a stronger effect on the distribution of ARGs in soil A Mantel test showed that the
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correlation of proximity to both stations was not significant, however when the seven
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ARGs presented in most of the samples were excluded, a significant correlation was
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observed between distance to Jang Bogo Station and the relative abundance of ARGs
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in soil (Table S6). Redistribution of microbes containing ARGs might be attributed to
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increased dust as a result of plowing soil during construction of Jang Bogo Station.
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In total, 22 ARGs were shared within the three groups with seven and two ARGs 13
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exclusively found in FS and GS groups, respectively, whereas 23 ARGs were
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exclusively in the JS group (Fig. S3). This also indicates that activity related to
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construction might contribute to ARGs solely observed near the Jang Bogo Station.
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More sites were sampled near the Jang Bogo Station (Fig. 1), which may, however,
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influence this result. The seven ARGs exclusively observed in FS samples may be the
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result of a higher number of FS samples tested compared to GS samples, or may be
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due to human activity resulting in organisms that do not harbor these genes. 51 A
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redundancy analysis of ARGs relative abundance showed that ARGs in the Antarctic
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soils are closer to those in the Michigan lake water sample 35, but very different from
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park soil, pig farms, sewage and river water samples (Fig. 4b), which is expected due
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to level of anthropogenic influence on latter sample sets.
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Influence of soil characteristics and bacterial diversity on ARGs. Soil
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physiochemical properties were also measured to examine links between ARG
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prevalence, edaphic factors and bacterial community composition (Table S3). A
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positive correlation (R2=0.39, P=0.0001) was observed between bacterial Shannon
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index; measured via sequencing of 16S rRNA gene as previously described, 29 and
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Shannon index of ARGs in soil (Fig. S4). This result implies that a more diverse
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bacterial population contributes to diversity of ARGs, an expected result.52
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Soil properties also influenced the relative abundance of ARGs. Silt, clay and SiO2
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were the top three soil attributes that influenced the relative abundance of ARGs (Fig.
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5a). Among them, silt showed a significant negative correlation with the relative
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abundance of ARGs in soils, whereas SiO2 and clay only showed significant positive 14
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and negative correlations, respectively, when the seven widely distributed ARGs were
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excluded (Table S6). These results agree with previous reports that SiO2 and soil
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texture are main factors shaping the soil bacterial community structure in the Terra
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Nova Bay. 29 Soil metals (MnO) and pH also affected the distribution of ARGs (Fig.
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5a) with a significant correlation between pH and relative abundance of ARGs
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without the seven widely distributed ARGs (Table S6), which is expected as soil pH
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is a dominant factor affecting microbial community structure in this location. 29 Total
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organic carbon (TOC) may have an affect on the distribution of ARGs (Fig. 5a);
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however, the Mantel test only showed a weak positive correlation when excluding the
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seven widely distributed ARGs (Table S6), which may be due to the wide variation of
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the soil TOC content in a few samples (Table S3). When the samples with relatively
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high TOC (> 0.9%) were excluded, a very significant positive correlation was noted
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between TOC and relative abundance of ARGs without the seven widely distributed
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ARGs (Table S6) and TOC become the top soil attribute that influenced the relative
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abundance of ARGs (Fig. 5b). Distance to Jangbogo Station, clay and silt remained
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the main factors affect the distribution of ARGs in soil (Fig. 5b).
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Temporal abundance of ARGs in Antarctic soil. The relative abundance of
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ARGs in soils sampled was also compared over 4 years. Due to the lower DNA
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concentrations in soils sampled in the second year (Table S1), lower relative ARG
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abundance and detected gene number was observed in almost all soils (Fig. 6, Table
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S7). If the second year samples are excluded, both the average relative ARG
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abundance and detected gene numbers in the three groups of soils (FS, GS and JS) 15
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was nearly constant during four years regardless of whether the seven ARGs present
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in most samples were excluded, indicating that bacteria harboring ARGs in the
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Antarctic soil are quite stable. Nevertheless, seven genes - blaCMY2, blaIMP, bla-L1,
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mefA, marR_1, mexB, and sulII were exclusively found in soils sampled near and
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during the construction of the Jang Bogo station. Among these genes, blaCMY2,
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blaIMP, marR_1 and mexB are multidrug-resistant 53-56 and blaCMY2, blaIMP, and
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bla-L1 are related to beta-lactams.54,57,58 The other genes are related to antibiotics that
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are critical for human medicine 59 including macrolide (mefA) and sulfonamide (sulII),
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implying that the emergence of these genes might be a consequence of the human
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activity during the construction of Jang Bogo station (Fig. S1).
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Emergence and spread of ARGs in soil. The detected ARGs in Antarctic soil
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might come from several origins including i) very long-term residence in Antarctic
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soils, i.e. a reservoir ii) distributed by animals or birds, iii) atmospheric transport and
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iv) human activity. Seven out of 67 ARGs were detected in most of the soil samples
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(Fig. 1), indicating that Antarctic soils may be a reservoir for these genes. These
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findings support the growing body of evidence that ARGs are widespread in relatively
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pristine habitats which have not been exposed to antibiotic resistant pathogens or
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commercial sources of antibiotics. 13, 15 In the Terra Nova Bay, the terrestrial surface
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is mainly composed of exposed bedrock and glacial moraines 29 and the microbial
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growth resources are limited. To survive in such a harsh environment, bacteria might
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produce antibiotics to inhibit or kill neighboring bacteria to acquire more resources. 5, 16
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13, 14
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have functions independent of resistance, such as efflux and electron transport, and
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will not always be associated with anthropogenic selective pressures. 60 It should also
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be noted that detection does not always represent activity in that: 1) assays only detect
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gene fragments, not complete genes, 2) fragments might be from non-viable
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organisms or extracellular DNA, 3) resistance may only be conveyed if other required
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genes or other mechanisms are present, and 4) the gene(s) must be expressed and
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translated into a functional protein. Nonetheless, detection and quantitation of ARGs
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with gene specific primers is currently the most feasible way to assess ARG ecology
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and a first level to assess reservoirs and potential risk.
On the other hand, ARGs might result from co-selection by metals. Some ARGs
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For dissemination related to animals or birds, a wide variety of life forms, such as
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sea birds, marine mammals, and invertebrates have been observed in the Terra Nova
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Bay. 29 Antibiotic resistance was found in the Antarctic Indian ocean seawater, 34 and
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amphibians might transfer resistance genes from the seawater to the terrestrial surface.
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Birds might also transmit resistance genes from great distances, as Arctic terns may
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travel up to six continents and do spend winter in the Antarctic. 22
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The atmospheric transport and deposition might also contribute to the
348
dissemination of ARGs to the Antarctic soil. Airborne particulate matter facilitated
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dispersal of veterinary antibiotics and microbial communities containing ARGs. 28
350
Dissemination of ARGs through airborne particulate matter by
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atmospheric circulation from other continents to Antarctica might occur as evidenced
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by long-range transport of persistent organic pollutants from temperate to polar
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regions.61
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Antarctic terrestrial ecosystem shifts in response to human activity and climate
355
change have been reported.62, 63 Our results showed that the intensive human activity
356
related to the construction of the Jang Bogo Research Station appears to have
357
influenced the distribution of resistance genes in Antarctic soil (Fig. 5a). However,
358
this human activity did not significantly increase the relative abundance of ARGs in
359
the soil over time (Fig. 6). Previous studies have shown that limited contact (e.g.,
360
sporadic travelers, wild animals) produced an influx of resistant isolates and
361
resistance genes in remote communities. 20 Resistance to quinolones was not detected
362
in the Arctic bird isolates, 22 deep ocean isolates, 13 or the Antarctic soils tested in the
363
present study (Fig. 1), however, the presence of this resistance has been observed in
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urban environments. 64 Resistance can be developed by the endogenous
365
microorganism through natural selection and adaptation to the harsh environment in
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the Antarctic and introduced from animals, birds, dust or humans. Both long and
367
short-term human activity could also influence dissemination of ARGs in the
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Antarctic. As the Antarctic attracts more travelers, 63 the influence of human activity
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on ARGs in the Antarctic may increase.
370
Environmental implications. Taken together, results show the presence of ARGs in
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Antarctic soils, which correlated with proximity to the research stations. Relative
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abundance of ARGs in the Antarctic soils also correlated with microbial biodiversity
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and select soil characteristics including silt, clay, TOC and SiO2. The natural 18
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resistome also serves as a reservoir for ARGs, which can be altered via anthropogenic
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activities. Intense human activity during construction of the Jang Bogo Research
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Station appears to influence ARGs in soil, however temporal results showed that this
377
activity did not significantly increase the overall level of ARGs in soil. Overall, this
378
study documents the resistome of Antarctic soils and should serve as a global baseline
379
data for future comparisons and understating the impacts of humans on the
380
environmental resistome.
381 382
383
Supporting Information
384
Supporting Information is available free of charge via the Internet
385
at http://pubs.acs.org.
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Soil sampling locations, primer sets, physiochemical property of soil and biodiversity
387
of bacteria, resistance genes classification, shared number of ARGs, maximum,
388
median and average of relative abundance of 16S rRNA genes, ARGs and MGEs,
389
information for different source of samples, relative abundance of ARGs in different
390
years.
391
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Corresponding Author
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* Tel: +82-31-670-4707, Fax: +82-31-675-3108, E-mail:
[email protected],
394
address: 4726 Seodong-daero, Anseong 17546, Republic of Korea.
ASSOCIATED CONTENT
AUTHOR INFORMATION
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Author Contributions
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♯
Fang Wang, Robert D. Stedtfeld and Ok-Sun Kim contributed equally to this work.
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Notes
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The authors declare no conflict of interest.
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400
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The authors thank Dr. Ji Hee Kim, Dr. Joohan Lee, Dr. Hyun Soo Lim and Ms.
402
Hyunjoo Noh for soil sampling and Dr. Teotonio Soares de Carvalho for help on data
403
analysis. Soil sampling was permitted by the Ministry of Foreign Affairs, Republic of
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Korea. The research was funded in part by the Center for Health Impacts of
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Agriculture (CHIA) at Michigan State University and by the Korea Polar Research
406
Institute (Grant PE16020, PE16070, & PP15101). F. Wang was partially supported
407
by the Outstanding Youth Fund of Natural Science Foundation of Jiangsu
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(BK20150050), National Natural Science Foundation of China (21677149) and the
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Institute of Soil Science, Chinese Academy of Sciences (ISSASIP1616). R.D.
410
Stedtfeld was partially supported by the Superfund Research Program (2 P42
411
ES004911-22A1) from the National Institute for Environmental Health Sciences.
ACKNOWLEDGMENTS
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Figure 1 Gene profiles of 68 antibiotic resistance genes (ARGs) and six mobile
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genetic elements (MGE) detected in the Antarctic soils sampled near the Gondwana
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Station (1000 m radius) and Jang Bogo Station (500 m radius) and soils farther away
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(further than 1350 m and 750 m, respectively) from the two stations. The heatmap
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shows soil samples as columns and detected ARGs as rows. The color scale indicates
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percent of ARG abundance values relative to the 16S rRNA gene. Grey indicates 31
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below the detection limit. MLSB, Macrolide-Lincosamide-Streptogramin B resistance;
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Figure 2 Comparison of detection frequency (proportion of qPCR positive assays to
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Antarctic soils compared to published data from other sample types. 18,19,35,36
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a
b
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Figure 3 Relationship between the Log2 transformed relative abundance of the
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antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) in soil for (a)
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all the ARGs, and (b) excluding the widely distributed genes: blaTEM, blaSFO,
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blaFOX, cphA, mexF, oprD and oprJ. 34
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b
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Figure 4 Redundancy Analysis (RDA) of log2 transformed relative abundance of antibiotic
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resistance genes in the soil, a: soils sampled far from the stations (FS) and near the Gondwana
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Station (GS) and Jang Bogo Station (JS); P values indicate that ordination of ARGs based on
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proximity to stations is significant .b: all the Antarctic soils and other samples from swine
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farms, park soils, sewage, river and lake samples.18,19,35,36 P values indicates that ordination of
645
ARGs based on sample type is significant.
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b
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Figure 5 Canonical correspondence analysis (CCA) of sampling site distance to Gondwana
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Station (Distance_G) or Jang Bogo Station (Distance_J) and soil characters and the relative
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abundance of antibiotic resistance genes in soil (symbols) (a) excluding those with relatively
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high total organic contents (> 0.9%) (b). Symbols are for soils.
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Figure 6 Relative abundance (a, b) and detected gene number (c, d) of antibiotic resistance
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genes (a, c) excluding the widely distributed blaTEM, blaSFO, blaFOX, cphA, mexF, oprD
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and oprJ (b, d) in soil sampled far from and near the Gondwana Station and Jang Bogo
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Station in years of 2011(1), 2012 (2), 2013 (3) and 2014 (4). The values, within one group,
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with different lower case letters were significantly different at p