AEM Accepts, published online ahead of print on 20 June 2014 Appl. Environ. Microbiol. doi:10.1128/AEM.01295-14 Copyright © 2014, American Society for Microbiology. All Rights Reserved.
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Wastewater irrigation increases abundance of
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potentially harmful Gammaproteobacteria in
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soils from Mezquital Valley, Mexico
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Melanie Broszat1,2, ‡, Heiko Nacke3, ‡, Ronja Blasi1,2, Christina Siebe4, Johannes Huebner1,5,
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Rolf Daniel3, Elisabeth Grohmann1,2# 1
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University Medical Centre Freiburg, Division of Infectious Diseases, Freiburg, Germany 2
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Albert-Ludwigs University Freiburg, Institute for Biology II, Microbiology, Freiburg, Germany
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Georg-August University Göttingen, Institute of Microbiology and Genetics, Göttingen, Germany
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Universidad Nacional Autónoma de México, Instituto de Geología, Ciudad Universitaria, Mexico City, Mexico
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University Munich, Munich, Germany
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# E-Mail:
[email protected]
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‡
Hauner Children's Hospital, Division of Pediatric Infectious Diseases, Ludwig-Maximilians
These authors contributed equally to this work.
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Running title: Gammaproteobacteria in wastewater-irrigated soils
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ABSTRACT
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Wastewater contains a large amount of pharmaceuticals, pathogens, and antimicrobial
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resistance determinants. Only little is known about the dissemination of resistance
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determinants and changes in soil microbial communities affected by wastewater irrigation.
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Community DNA from Mezquital Valley soils under irrigation with untreated wastewater for
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0 to 100 years was analyzed by quantitative real time PCR for the presence of sul genes,
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encoding resistance to sulfonamides. Amplicon sequencing of bacterial 16S rRNA genes from
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community DNA from soils irrigated for 0, 8, 10, 85, and 100 years was performed revealing
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a 14% increase of the relative abundance of Proteobacteria in rainy season and a 26.7%
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increase in dry season soils irrigated for 100 years with wastewater. In particular,
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Gammaproteobacteria, including potential pathogens like Pseudomonas, Stenotrophomonas
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and Acinetobacter spp. were found in wastewater-irrigated fields. 16S rRNA gene sequencing
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of 96 isolates from soils irrigated with wastewater for 100 years (48 from dry and 48 from
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rainy season) revealed that 46% affiliated with Gammaproteobacteria (mainly potentially
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pathogenic Stenotrophomonas strains) and 50% with Bacilli, whereas all 96 isolates from
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rain-fed soils (48 from dry and 48 from rainy season) affiliated with Bacilli. Up to six
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antibiotic resistances were found in isolates from wastewater-irrigated soils, sulfamethoxazole
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resistance was the most abundant (33.3% of the isolates), followed by oxacillin resistance
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(21.9% of the isolates). In summary, we detected an increase of potentially harmful bacteria
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and larger incidence of resistance determinants in wastewater-irrigated soils which might
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result in health risks for farmworkers and consumers of wastewater-irrigated crops.
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INTRODUCTION
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Along with pharmaceuticals, wastewater can contain pathogenic microorganisms including
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bacteria resistant to antimicrobial substances, and also antimicrobial resistance determinants
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(1–6). In arid and semi-arid areas, wastewater is used for irrigation in agricultural production
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to alleviate water shortages (7–10). The coexistence of antibiotics, pathogens and antibiotic
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resistance determinants in wastewater raises concerns that antibiotic resistance genes are
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mobilized from and disseminated into the environmental resistome and transferred to bacteria
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that are potentially pathogenic to humans (11–13). The release of antibiotics together with
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human-linked microbiota might be particularly important for the emergence of new evolving
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antibiotic resistant pathogens (1,14). Environmental reservoirs for antibiotic resistances,
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especially those impacted by anthropogenic activities (e.g., application of manure), can serve
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as “hotspots” for the spread of antibiotic resistance genes and antibiotic resistant bacteria
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through food and water, with unknown consequences for human health (14–16). D’Costa and
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colleagues indicated that soil could serve as an underestimated reservoir for antibiotic
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resistance that has already emerged or has the potential to emerge in clinically important
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bacteria (17). The first report of a putative link between environmental and clinical antibiotic
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resistance determinants was published in 1973 by Benveniste and Davies. They detected high
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similarities between enzymes conferring gentamicin-resistance from soil-associated
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Actinomycetes and enzymes that confer the same resistance in human pathogens such as
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Escherichia coli and Pseudomonas aeruginosa (18). Recent studies have shown that the
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CTX-M β-lactamases potentially originate from the environmental bacterium Kluyvera
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ascorbata (19,20). Furthermore, the plasmid-encoded qnr genes encoding fluoroquinolone
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resistance have originated from aquatic bacteria such as Shewanella algae (21–23).
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Fluoroquinolones are a family of broad spectrum antibacterial agents that are active against a
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wide range of Gram-positive and Gram-negative bacteria. They act by inhibition of type II
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DNA toposisomerases (gyrases) that are required for bacterial DNA replication. Three
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mechanisms of resistance are known. Some types of efflux pumps act to decrease intracellular
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quinolone concentration. In Gram-negative bacteria, plasmid-mediated resistance genes
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produce proteins that can bind to DNA gyrase, protecting it from the action of quinolones. In
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addition, mutations at key sites in DNA gyrase or topoisomerase IV can decrease their
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binding affinity to quinolones, decreasing the effectiveness of the drug (24).
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There are strong indications for a link between antibiotic resistance determinants from the
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environment and those found in hospitals (13). Another problem is the release of
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antimicrobials to the environment which might influence the composition of natural bacterial
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communities and may as well change the physiology of environmental bacteria (25). Thus,
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wastewater irrigation and other anthropogenic activities, e.g., application of manure, might
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also change the composition of soil bacterial communities. Some studies have shown that a
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shift
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Gammaproteobacteria (8,26) results from an input of organic carbon sources or irrigation
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with treated wastewater. Gammaproteobacteria are a class of medically, ecologically and
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scientifically important groups of bacteria, such as the Enterobacteriaceae (e.g. E. coli),
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Vibrionaceae,
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maltophilia). An exceeding number of important pathogens belongs to this class, such as
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Salmonella (enteritis and typhoid fever), Vibrio cholerae (cholera), Pseudomonas aeruginosa
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(lung infections), and Klebsiella pneumoniae responsible for causing pneumonia. S.
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maltophilia is found in various natural environments, such as soil, water and plants, but also
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occurs in the hospital environment and may cause infections that affect the bloodstream,
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respiratory tract, urinary tract and surgical-sites.
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Frenk et al. (8) compared pyrosequencing data of bacterial 16S rRNA genes from soils
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irrigated with treated wastewater with those from soils irrigated with freshwater. They
of
soil
bacterial
community
Pseudomonadaceae
and
structure
towards
Xanthomonadaceae
a
higher
(e.g.
abundance
of
Stenotrophomonas
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observed an increase in the proportion of Gammaproteobacteria during the irrigation season
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(dry season) and a return to the “baseline state” in the rainy season.
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However, the influence of long-term irrigation with untreated wastewater on the bacterial soil
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communities has not been studied so far. Here, we investigated the effect of wastewater
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irrigation for different time-periods on the occurrence of pathogenic bacteria and antibiotic
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resistance determinants in the affected Mezquital Valley soils and compared it with rain-fed
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agriculture in the same area incorporating possible season effects by sampling the same soils
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in the rainy and the dry season. In previous studies we detected an increase in the relative
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abundance of sul resistance genes encoding resistance towards sulfonamides and an
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accumulation of antibiotics during long-term wastewater irrigation in the Mezquital Valley
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soils (27). Sulfonamides are bacteriostatic antibiotics that inhibit conversion of p-
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aminobenzoic acid to dihydropteroate, which bacteria need for folate synthesis and ultimately
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purine and DNA synthesis. Resistance in Gram-negative enteric bacteria is plasmid-borne and
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is mainly due to the presence of sul1 and sul2 genes encoding drug-resistance variants of the
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dihydropteroate synthase enzyme in the folic acid pathway (28).
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We hypothesize that irrigation with untreated wastewater changes the composition of soil
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bacterial communities towards increased abundances of potentially harmful bacteria and, that
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wastewater-derived pathogens can survive in the environment, which might pose risks to
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people living in the area and consumers of agricultural products from wastewater-irrigation
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fields.
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MATERIALS AND METHODS
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Study sites and soil sampling
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Over the past century the irrigated area in the Mezquital Valley increased due to the
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expansion of the Mexico City Metropolitan Area (MCMA). We selected sites with different
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duration of irrigation with untreated wastewater (non-irrigated control, 8, 10, 85, and 100
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years, further named soil chronosequence) for our study. All of them were either sampled in
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August 2009 (rainy season) or in March 2011 (dry season). All soils have been irrigated with
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MCMA wastewater, which has been well mixed especially over longer time periods because
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of the extensive pumping and diversion of wastewater within the MCMA and the Mezquital
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Valley irrigation system. From each field a sample composed of 48 subsamples distributed
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equidistantly within the whole field was taken with an auger at a depth of 0–30 cm. Soil
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samples were collected, transported to the laboratory at 4°C and stored at -20°C until DNA
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extraction. Soil properties are given in Table 1.
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Properties of the soil samples
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To determine soil pH, 10 g of each soil sample were suspended at a soil-to-liquid ratio of
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1:2.5 (soil/0.01 M CaCl2). Subsequently, pH was measured in the supernatant with a glass
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electrode (31). For determination of the Total Organic Carbon content (TOC), the Total
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Carbon content (TC) and the Total Nitrogen content (TN) 0.5 g of each composite soil sample
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was suspended in 100 ml distilled water and homogenized with ULTRA-TURRAX® (T 10
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basic, IKA-Werke GmbH & Co. KG, Staufen, Germany). The samples were measured with
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the TOC analyzer (Shimadzu TOC-VCPN, Shimadzu Deutschland GmbH, Duisburg,
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Germany). For the evaluation of TOC, TC and TN, standard curves were generated with serial
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dilutions of the standards and measured five times. For TC measurement, a potassium
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hydrogen phthalate solution (2.125 g/l potassium hydrogen phthalate, equivalent to 1 g carbon
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per l) was used, for inorganic carbon, a sodium carbonate solution (4.100 g Na2CO3 and 3.500
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g NaHCO3 per l, equivalent to 1 g inorganic carbon per l) and for TN measurement a
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potassium nitrate solution (7.219 g potassium nitrate, equivalent to 1 g nitrogen per l) was
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used following the manufacturer‘s instructions.
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Total DNA extraction from soils
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Total DNA was extracted from 500 mg soil from fields irrigated for 0, 8, 10, 85, and 100
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years with wastewater (triplicates of four soil samples from dry and four soil samples from
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rainy season) using the NucleoSpin® Soil kit according to the manufacturer’s protocol
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(Macherey-Nagel, Düren, Germany). Aliquots of total DNA from the soil samples were
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analyzed by pyrosequencing of 16S rRNA genes.
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Amplification of partial 16S rRNA genes and pyrosequencing
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The V2-V3 region of 16S rRNA genes was amplified by PCR using total DNA from the
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different soil samples as starting material. The PCR reaction mixture (50 µl) contained 10 µl
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fivefold reaction buffer (Phusion HF buffer, Thermo Fisher Scientific, Inc., Waltham, MA,
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USA), 200 µM of each of the four deoxynucleoside triphosphates, 5% DMSO, 0.5 U Phusion
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hot start high fidelity DNA polymerase (Thermo Fisher Scientific, Inc.), 10 to 200 ng DNA as
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template, and 4 µM of each of the primers. Primers used were 101F containing Roche 454
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pyrosequencing adaptor B and 515R containing a sample-specific MID (Extended Multiplex
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Identifier, size: ten nucleotides) and Roche 454 pyrosequencing adaptor A (Table 2). The
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PCR reactions were initiated at 98°C (30 s), followed by 25 cycles of 98°C (10 s), 69°C (30 s)
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and 72°C (20 s), and ended with incubation at 72°C for 10 min. All samples were amplified in
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triplicate, purified using the peqGold gel extraction kit (Peqlab Biotechnologie GmbH,
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Erlangen, Germany) as recommended by the manufacturer, and pooled in equal amounts.
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Quantification of PCR products was performed using the Quant-iT dsDNA BR assay kit and a
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Qubit fluorometer (Life Technologies, Darmstadt, Germany). The sequences of the partial
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16S rRNA genes were determined using a Roche GS-FLX 454 pyrosequencer (Roche,
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Mannheim, Germany) and Titanium chemistry as recommended by the manufacturer. All
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sequences have been deposited in the sequence read archive of the National Center for
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Biotechnology Information under accession number SRP037963.
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Pyrosequencing data processing and statistical analysis
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Sequences shorter than 200 bp as well as those exhibiting an average quality value below
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25, more than two primer mismatches or long homopolymers (> 8 bp) were removed from the
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dataset by employing QIIME version 1.6 (38). All remaining primer sequences were truncated
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using program cutadapt (39). Removal of potential chimeric sequences was performed by
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applying Uchime (40) and Greengenes Gold dataset “gold_strains_gg16S_aligned.fasta” as
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reference (41). The Acacia error-correction tool (42) was used to remove noise introduced by
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amplicon pyrosequencing. Determination of operational taxonomic units (OTUs) was
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performed using Uclust (43). To taxonomically classify OTUs, partial 16S rRNA gene
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sequences were compared with the SILVA SSU Ref NR 115 database (44). A customized
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script was used to remove all non-bacterial OTUs from the OTU table. Calculation of
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rarefaction curves, Chao1 index (45), and the Shannon index (46) was conducted using
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QIIME.
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We used two sample t-test analyses and M-W-U-Test for non-parametric data to compare
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relative abundances of bacterial groups, diversity and richness estimates between soils
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collected during dry and rainy season as well as between wastewater-irrigated and rain-fed
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soils using software package PAST (47). To compare bacterial community composition
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across all samples based on weighted UniFrac (48) measures, principal coordinate analysis
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was performed by using QIIME. For determination of the phylogenetic metric (weighted
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UniFrac), a phylogenetic tree was calculated using a PyNAST (49) alignment. This alignment
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was produced by aligning a representative sequence set (one sequence from each OTU at a
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genetic distance of 3%) to Greengenes core set “core_set_aligned.fasta” (41).
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Isolation of soil bacteria
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100 mg soil per analyzed sample were suspended in 900 µl sodium pyrophosphate (7.5 mM
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with 0.05% Tween 80) and subsequently the bacteria were detached from the soil particles
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through shaking at 1000 rpm for 45 min (50). After 5 min settling serial dilutions of the
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bacteria suspensions were transferred onto TSA plates and incubated 24 h at 22°C. Single
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colonies were picked and purified via two passages on TSA plates.
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DNA extraction from bacterial soil isolates
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DNA extraction from bacterial soil isolates was performed using MasterPure Gram Positive
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DNA purification kit (Biozym Scientific GmbH, Hess. Oldendorf, Germany) according to the
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manufacturer’s instruction from 1 ml overnight culture in TSB incubated at 22°C. The
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isolated DNA was applied to amplify the 16S rRNA gene and antibiotic resistance genes by
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PCR.
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Amplification and sequencing of 16S rRNA genes of soil isolates
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For the amplification of the 16S rRNA gene, each 50-μl PCR reaction contained 2.5 U Taq
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polymerase and 1 × PCR buffer S (Peqlab Biotechnologie GmbH, Erlangen, Germany), 0.2
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μM of each primer (27F and 1492R, Table 2), 0.2 mM of each of the four deoxynucleoside
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triphosphates, 2 mM MgCl2, and 20 ng template DNA (genomic DNA of bacterial isolates).
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DNA amplifications were carried out in an Eppendorf thermocycler (Eppendorf Mastercycler
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for 96-well plates, Eppendorf AG, Hamburg, Germany). The temperature profile consisted of
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an initial denaturation step at 95ºC for 2 min followed by 30 cycles of denaturation at 95°C
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for 30 s, primer annealing at 58°C for 45 s and extension at 72°C for 1 min, followed by an
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additional 7-min elongation step at 72°C. PCR products were sequenced with the primer set
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63F and 1387R (Table 2 by Beckman Coulter Genomics (Takeley, UK). Sequences were
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analyzed by blastn using the 16S ribosomal RNA sequences reference data base for Bacteria
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and Archaea (http://blast.ncbi.nlm.nih.gov/Blast.cgi) (51).
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Assessment of antibiotic resistance genes by PCR
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PCR assays specific for sul (32) and qnr (33) resistance genes were performed as follows:
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each 25-μl PCR reaction mixture contained 12.5 µl KAPA2G Fast ReadyMix with dye
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(Peqlab Biotechnologie GmbH, Erlangen, Germany), 2–3 mM MgCl2 and 20 ng genomic
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DNA of bacterial isolates. DNA amplifications were carried out in an Eppendorf thermocycler
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(Eppendorf Mastercycler for 96-well plates, Eppendorf AG, Hamburg, Germany). The
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temperature profile consisted of an initial denaturation step at 95°C for 2 min followed by 30
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cycles of denaturation at 95°C for 30 s, primer annealing at 57°C for 45 s for qnr genes and
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65°C for 30 s for sul genes and extension at 72°C for 1 min, followed by an additional 7-min
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elongation step at 72°C (only for qnr genes). Primers used are listed in Table 2. Absolute
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quantifications of sul1 and sul2 genes were performed with serial diluted exogenous standards
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that consisted of purified PCR products. Quantification of absolute target gene numbers was
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carried out using the Light-Cycler 480 (Roche Diagnostics, Mannheim, Germany) as
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described in (27).
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Antimicrobial susceptibility testing of bacterial isolates
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Resistance of the bacterial isolates to specific antibiotics was determined by the disc
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diffusion method according to CLSI guidelines (52) with the following antibiotic discs
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(Oxoid, Wesel, Germany): ampicillin (25 µg), chloramphenicol (30 µg), erythromycin (10
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µg), gentamicin (10 µg), kanamycin (30 µg), oxacillin (5 µg), streptomycin (25 µg),
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ciprofloxacin (5 and 10 µg), doxycycline (30 µg), tetracycline (30 µg), vancomycin (30 µg),
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and sulfamethoxazole (25 µg). Single colonies of bacterial soil isolates were diluted according
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to McFarland to an OD630 of 0.16 and streaked-out with swabs according to DIN 58940-
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3:2007-10. Instead of Mueller-Hinton agar, TSA plates were used and incubated 24 h at 22°C.
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RESULTS AND DISCUSSION
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Characteristics of wastewater-irrigated and rain-fed soils
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Irrigation with untreated wastewater releases organic carbon compounds and other nutrients
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into soils. More nutrients and a higher humidity over the entire year provide better growth
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conditions for indigenous bacteria and possibly also for wastewater-derived bacteria and thus
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might change the composition of soil bacterial communities. The organic matter content of
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the analyzed soils increased during long-term irrigation with wastewater (Table 1). In rain-fed
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soils TOC ranged from 0.91 to 1.53% whereas in wastewater-irrigated soils TOC ranged from
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1.06 to 3.35%. The total nitrogen content in the soils varied from 0.05 to 0.15% (rain-fed) and
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0.10 to 0.30% (wastewater-irrigated). The soil pH values varied between 6.7 and 7.4. Increase
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of soil organic matter content through wastewater irrigation has also been reported by others
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(53–58). This results in rising microbial biomass and microbial activity (53,59–61).
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Furthermore, increased water supply by wastewater irrigation in the dry season seems to
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provide better conditions for microbial proliferation (53). This might also increase the
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survival rate of wastewater-derived bacteria.
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General analysis of the pyrosequencing-derived dataset and overall bacterial diversity and
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richness
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Pyrosequencing of partial 16 S rRNA genes (V2-V3 region) yielded a total number of
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452,999 sequences across all analyzed soil samples (n=24). After preprocessing including
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quality-filtering, denoising and removal of non-bacterial or chimeric reads, 337,493
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sequences with an average length of 353 bp were obtained for further analyses (Table S1).
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Due to the fact that the number of analyzed sequences per sample has an effect on the
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predicted number of operational taxonomic units (OTUs), OTU-based comparisons between
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the analyzed 24 soils were performed at the same level of surveying effort (11,320 sequences
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per sample) (62).
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Rarefaction curve, richness and diversity analyses were based on OTUs determined at 3 and
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20% genetic distance. Comparison of the rarefaction analyses with the number of OTUs
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calculated by Chao1 richness estimator revealed that 72.6 to 86.8% (20% genetic distance)
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and 31.0 to 48.2% (3% genetic distance) of the estimated richness were covered by the
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sequencing effort (Table S2 and Fig. 1). (The Chao 1 nonparametric richness estimator was
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employed to calculate the estimated true OTU diversity of the samples). Thus, we did not
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survey the full extent of diversity, but particularly at 20% genetic distance (phylum level
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according to Schloss and Handelsman (63), a substantial fraction of the bacterial diversity was
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assessed within individual soil samples. Dry season samples exhibited significantly higher
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OTU numbers, Chao1 richness estimates and bacterial diversity as assessed by Shannon index
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(H’) than rainy season samples (3% genetic distance: P < 0.001; 20% genetic distance: P
