wastewater irrigation increases abundance of potentially harmful

1

Wastewater irrigation increases abundance of 1

potentially harmful Gammaproteobacteria in 2

soils from Mezquital Valley, Mexico 3

Melanie Broszat1,2, ‡, Heiko Nacke3, ‡, Ronja Blasi1,2, Christina Siebe4, Johannes Huebner1,5, 4

Rolf Daniel3, Elisabeth Grohmann1,2# 5

1 University Medical Centre Freiburg, Division of Infectious Diseases, Freiburg, Germany 6

2 Albert-Ludwigs University Freiburg, Institute for Biology II, Microbiology, Freiburg, 7

Germany 8

3 Georg-August University Göttingen, Institute of Microbiology and Genetics, Göttingen, 9

Germany 10

4 Universidad Nacional Autónoma de México, Instituto de Geología, Ciudad Universitaria, 11

Mexico City, Mexico 12

5 Hauner Children's Hospital, Division of Pediatric Infectious Diseases, Ludwig-Maximilians 13

University Munich, Munich, Germany 14

# E-Mail: [email protected] 15

‡ These authors contributed equally to this work. 16

17

Running title: Gammaproteobacteria in wastewater-irrigated soils 18

19

20

AEM Accepts, published online ahead of print on 20 June 2014Appl. Environ. Microbiol. doi:10.1128/AEM.01295-14Copyright © 2014, American Society for Microbiology. All Rights Reserved.

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ABSTRACT 21

Wastewater contains a large amount of pharmaceuticals, pathogens, and antimicrobial 22

resistance determinants. Only little is known about the dissemination of resistance 23

determinants and changes in soil microbial communities affected by wastewater irrigation. 24

Community DNA from Mezquital Valley soils under irrigation with untreated wastewater for 25

0 to 100 years was analyzed by quantitative real time PCR for the presence of sul genes, 26

encoding resistance to sulfonamides. Amplicon sequencing of bacterial 16S rRNA genes from 27

community DNA from soils irrigated for 0, 8, 10, 85, and 100 years was performed revealing 28

a 14% increase of the relative abundance of Proteobacteria in rainy season and a 26.7% 29

increase in dry season soils irrigated for 100 years with wastewater. In particular, 30

Gammaproteobacteria, including potential pathogens like Pseudomonas, Stenotrophomonas 31

and Acinetobacter spp. were found in wastewater-irrigated fields. 16S rRNA gene sequencing 32

of 96 isolates from soils irrigated with wastewater for 100 years (48 from dry and 48 from 33

rainy season) revealed that 46% affiliated with Gammaproteobacteria (mainly potentially 34

pathogenic Stenotrophomonas strains) and 50% with Bacilli, whereas all 96 isolates from 35

rain-fed soils (48 from dry and 48 from rainy season) affiliated with Bacilli. Up to six 36

antibiotic resistances were found in isolates from wastewater-irrigated soils, sulfamethoxazole 37

resistance was the most abundant (33.3% of the isolates), followed by oxacillin resistance 38

(21.9% of the isolates). In summary, we detected an increase of potentially harmful bacteria 39

and larger incidence of resistance determinants in wastewater-irrigated soils which might 40

result in health risks for farmworkers and consumers of wastewater-irrigated crops. 41

42


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INTRODUCTION 43

Along with pharmaceuticals, wastewater can contain pathogenic microorganisms including 44

bacteria resistant to antimicrobial substances, and also antimicrobial resistance determinants 45

(1–6). In arid and semi-arid areas, wastewater is used for irrigation in agricultural production 46

to alleviate water shortages (7–10). The coexistence of antibiotics, pathogens and antibiotic 47

resistance determinants in wastewater raises concerns that antibiotic resistance genes are 48

mobilized from and disseminated into the environmental resistome and transferred to bacteria 49

that are potentially pathogenic to humans (11–13). The release of antibiotics together with 50

human-linked microbiota might be particularly important for the emergence of new evolving 51

antibiotic resistant pathogens (1,14). Environmental reservoirs for antibiotic resistances, 52

especially those impacted by anthropogenic activities (e.g., application of manure), can serve 53

as “hotspots” for the spread of antibiotic resistance genes and antibiotic resistant bacteria 54

through food and water, with unknown consequences for human health (14–16). D’Costa and 55

colleagues indicated that soil could serve as an underestimated reservoir for antibiotic 56

resistance that has already emerged or has the potential to emerge in clinically important 57

bacteria (17). The first report of a putative link between environmental and clinical antibiotic 58

resistance determinants was published in 1973 by Benveniste and Davies. They detected high 59

similarities between enzymes conferring gentamicin-resistance from soil-associated 60

Actinomycetes and enzymes that confer the same resistance in human pathogens such as 61

Escherichia coli and Pseudomonas aeruginosa (18). Recent studies have shown that the 62

CTX-M β-lactamases potentially originate from the environmental bacterium Kluyvera 63

ascorbata (19,20). Furthermore, the plasmid-encoded qnr genes encoding fluoroquinolone 64

resistance have originated from aquatic bacteria such as Shewanella algae (21–23). 65

Fluoroquinolones are a family of broad spectrum antibacterial agents that are active against a 66

wide range of Gram-positive and Gram-negative bacteria. They act by inhibition of type II 67

DNA toposisomerases (gyrases) that are required for bacterial DNA replication. Three 68


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mechanisms of resistance are known. Some types of efflux pumps act to decrease intracellular 69

quinolone concentration. In Gram-negative bacteria, plasmid-mediated resistance genes 70

produce proteins that can bind to DNA gyrase, protecting it from the action of quinolones. In 71

addition, mutations at key sites in DNA gyrase or topoisomerase IV can decrease their 72

binding affinity to quinolones, decreasing the effectiveness of the drug (24). 73

There are strong indications for a link between antibiotic resistance determinants from the 74

environment and those found in hospitals (13). Another problem is the release of 75

antimicrobials to the environment which might influence the composition of natural bacterial 76

communities and may as well change the physiology of environmental bacteria (25). Thus, 77

wastewater irrigation and other anthropogenic activities, e.g., application of manure, might 78

also change the composition of soil bacterial communities. Some studies have shown that a 79

shift of soil bacterial community structure towards a higher abundance of 80

Gammaproteobacteria (8,26) results from an input of organic carbon sources or irrigation 81

with treated wastewater. Gammaproteobacteria are a class of medically, ecologically and 82

scientifically important groups of bacteria, such as the Enterobacteriaceae (e.g. E. coli), 83

Vibrionaceae, Pseudomonadaceae and Xanthomonadaceae (e.g. Stenotrophomonas 84

maltophilia). An exceeding number of important pathogens belongs to this class, such as 85

Salmonella (enteritis and typhoid fever), Vibrio cholerae (cholera), Pseudomonas aeruginosa 86

(lung infections), and Klebsiella pneumoniae responsible for causing pneumonia. S. 87

maltophilia is found in various natural environments, such as soil, water and plants, but also 88

occurs in the hospital environment and may cause infections that affect the bloodstream, 89

respiratory tract, urinary tract and surgical-sites. 90

Frenk et al. (8) compared pyrosequencing data of bacterial 16S rRNA genes from soils 91

irrigated with treated wastewater with those from soils irrigated with freshwater. They 92


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observed an increase in the proportion of Gammaproteobacteria during the irrigation season 93

(dry season) and a return to the “baseline state” in the rainy season. 94

However, the influence of long-term irrigation with untreated wastewater on the bacterial soil 95

communities has not been studied so far. Here, we investigated the effect of wastewater 96

irrigation for different time-periods on the occurrence of pathogenic bacteria and antibiotic 97

resistance determinants in the affected Mezquital Valley soils and compared it with rain-fed 98

agriculture in the same area incorporating possible season effects by sampling the same soils 99

in the rainy and the dry season. In previous studies we detected an increase in the relative 100

abundance of sul resistance genes encoding resistance towards sulfonamides and an 101

accumulation of antibiotics during long-term wastewater irrigation in the Mezquital Valley 102

soils (27). Sulfonamides are bacteriostatic antibiotics that inhibit conversion of p-103

aminobenzoic acid to dihydropteroate, which bacteria need for folate synthesis and ultimately 104

purine and DNA synthesis. Resistance in Gram-negative enteric bacteria is plasmid-borne and 105

is mainly due to the presence of sul1 and sul2 genes encoding drug-resistance variants of the 106

dihydropteroate synthase enzyme in the folic acid pathway (28). 107

We hypothesize that irrigation with untreated wastewater changes the composition of soil 108

bacterial communities towards increased abundances of potentially harmful bacteria and, that 109

wastewater-derived pathogens can survive in the environment, which might pose risks to 110

people living in the area and consumers of agricultural products from wastewater-irrigation 111

fields. 112

113

MATERIALS AND METHODS 114

Study sites and soil sampling 115

Over the past century the irrigated area in the Mezquital Valley increased due to the 116

expansion of the Mexico City Metropolitan Area (MCMA). We selected sites with different 117


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duration of irrigation with untreated wastewater (non-irrigated control, 8, 10, 85, and 100 118

years, further named soil chronosequence) for our study. All of them were either sampled in 119

August 2009 (rainy season) or in March 2011 (dry season). All soils have been irrigated with 120

MCMA wastewater, which has been well mixed especially over longer time periods because 121

of the extensive pumping and diversion of wastewater within the MCMA and the Mezquital 122

Valley irrigation system. From each field a sample composed of 48 subsamples distributed 123

equidistantly within the whole field was taken with an auger at a depth of 0–30 cm. Soil 124

samples were collected, transported to the laboratory at 4°C and stored at -20°C until DNA 125

extraction. Soil properties are given in Table 1. 126

127

Properties of the soil samples 128

To determine soil pH, 10 g of each soil sample were suspended at a soil-to-liquid ratio of 129

1:2.5 (soil/0.01 M CaCl2). Subsequently, pH was measured in the supernatant with a glass 130

electrode (31). For determination of the Total Organic Carbon content (TOC), the Total 131

Carbon content (TC) and the Total Nitrogen content (TN) 0.5 g of each composite soil sample 132

was suspended in 100 ml distilled water and homogenized with ULTRA-TURRAX® (T 10 133

basic, IKA-Werke GmbH & Co. KG, Staufen, Germany). The samples were measured with 134

the TOC analyzer (Shimadzu TOC-VCPN, Shimadzu Deutschland GmbH, Duisburg, 135

Germany). For the evaluation of TOC, TC and TN, standard curves were generated with serial 136

dilutions of the standards and measured five times. For TC measurement, a potassium 137

hydrogen phthalate solution (2.125 g/l potassium hydrogen phthalate, equivalent to 1 g carbon 138

per l) was used, for inorganic carbon, a sodium carbonate solution (4.100 g Na2CO3 and 3.500 139

g NaHCO3 per l, equivalent to 1 g inorganic carbon per l) and for TN measurement a 140

potassium nitrate solution (7.219 g potassium nitrate, equivalent to 1 g nitrogen per l) was 141

used following the manufacturer‘s instructions. 142


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143

Total DNA extraction from soils 144

Total DNA was extracted from 500 mg soil from fields irrigated for 0, 8, 10, 85, and 100 145

years with wastewater (triplicates of four soil samples from dry and four soil samples from 146

rainy season) using the NucleoSpin® Soil kit according to the manufacturer’s protocol 147

(Macherey-Nagel, Düren, Germany). Aliquots of total DNA from the soil samples were 148

analyzed by pyrosequencing of 16S rRNA genes. 149

150

Amplification of partial 16S rRNA genes and pyrosequencing 151

The V2-V3 region of 16S rRNA genes was amplified by PCR using total DNA from the 152

different soil samples as starting material. The PCR reaction mixture (50 µl) contained 10 µl 153

fivefold reaction buffer (Phusion HF buffer, Thermo Fisher Scientific, Inc., Waltham, MA, 154

USA), 200 µM of each of the four deoxynucleoside triphosphates, 5% DMSO, 0.5 U Phusion 155

hot start high fidelity DNA polymerase (Thermo Fisher Scientific, Inc.), 10 to 200 ng DNA as 156

template, and 4 µM of each of the primers. Primers used were 101F containing Roche 454 157

pyrosequencing adaptor B and 515R containing a sample-specific MID (Extended Multiplex 158

Identifier, size: ten nucleotides) and Roche 454 pyrosequencing adaptor A (Table 2). The 159

PCR reactions were initiated at 98°C (30 s), followed by 25 cycles of 98°C (10 s), 69°C (30 s) 160

and 72°C (20 s), and ended with incubation at 72°C for 10 min. All samples were amplified in 161

triplicate, purified using the peqGold gel extraction kit (Peqlab Biotechnologie GmbH, 162

Erlangen, Germany) as recommended by the manufacturer, and pooled in equal amounts. 163

Quantification of PCR products was performed using the Quant-iT dsDNA BR assay kit and a 164

Qubit fluorometer (Life Technologies, Darmstadt, Germany). The sequences of the partial 165

16S rRNA genes were determined using a Roche GS-FLX 454 pyrosequencer (Roche, 166

Mannheim, Germany) and Titanium chemistry as recommended by the manufacturer. All 167


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sequences have been deposited in the sequence read archive of the National Center for 168

Biotechnology Information under accession number SRP037963. 169

170

Pyrosequencing data processing and statistical analysis 171

Sequences shorter than 200 bp as well as those exhibiting an average quality value below 172

25, more than two primer mismatches or long homopolymers (> 8 bp) were removed from the 173

dataset by employing QIIME version 1.6 (38). All remaining primer sequences were truncated 174

using program cutadapt (39). Removal of potential chimeric sequences was performed by 175

applying Uchime (40) and Greengenes Gold dataset “gold_strains_gg16S_aligned.fasta” as 176

reference (41). The Acacia error-correction tool (42) was used to remove noise introduced by 177

amplicon pyrosequencing. Determination of operational taxonomic units (OTUs) was 178

performed using Uclust (43). To taxonomically classify OTUs, partial 16S rRNA gene 179

sequences were compared with the SILVA SSU Ref NR 115 database (44). A customized 180

script was used to remove all non-bacterial OTUs from the OTU table. Calculation of 181

rarefaction curves, Chao1 index (45), and the Shannon index (46) was conducted using 182

QIIME. 183

We used two sample t-test analyses and M-W-U-Test for non-parametric data to compare 184

relative abundances of bacterial groups, diversity and richness estimates between soils 185

collected during dry and rainy season as well as between wastewater-irrigated and rain-fed 186

soils using software package PAST (47). To compare bacterial community composition 187

across all samples based on weighted UniFrac (48) measures, principal coordinate analysis 188

was performed by using QIIME. For determination of the phylogenetic metric (weighted 189

UniFrac), a phylogenetic tree was calculated using a PyNAST (49) alignment. This alignment 190

was produced by aligning a representative sequence set (one sequence from each OTU at a 191

genetic distance of 3%) to Greengenes core set “core_set_aligned.fasta” (41). 192


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193

Isolation of soil bacteria 194

100 mg soil per analyzed sample were suspended in 900 µl sodium pyrophosphate (7.5 mM 195

with 0.05% Tween 80) and subsequently the bacteria were detached from the soil particles 196

through shaking at 1000 rpm for 45 min (50). After 5 min settling serial dilutions of the 197

bacteria suspensions were transferred onto TSA plates and incubated 24 h at 22°C. Single 198

colonies were picked and purified via two passages on TSA plates. 199

200

DNA extraction from bacterial soil isolates 201

DNA extraction from bacterial soil isolates was performed using MasterPure Gram Positive 202

DNA purification kit (Biozym Scientific GmbH, Hess. Oldendorf, Germany) according to the 203

manufacturer’s instruction from 1 ml overnight culture in TSB incubated at 22°C. The 204

isolated DNA was applied to amplify the 16S rRNA gene and antibiotic resistance genes by 205

PCR. 206

207

Amplification and sequencing of 16S rRNA genes of soil isolates 208

For the amplification of the 16S rRNA gene, each 50-μl PCR reaction contained 2.5 U Taq 209

polymerase and 1 × PCR buffer S (Peqlab Biotechnologie GmbH, Erlangen, Germany), 0.2 210

μM of each primer (27F and 1492R, Table 2), 0.2 mM of each of the four deoxynucleoside 211

triphosphates, 2 mM MgCl2, and 20 ng template DNA (genomic DNA of bacterial isolates). 212

DNA amplifications were carried out in an Eppendorf thermocycler (Eppendorf Mastercycler 213

for 96-well plates, Eppendorf AG, Hamburg, Germany). The temperature profile consisted of 214

an initial denaturation step at 95ºC for 2 min followed by 30 cycles of denaturation at 95°C 215

for 30 s, primer annealing at 58°C for 45 s and extension at 72°C for 1 min, followed by an 216


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additional 7-min elongation step at 72°C. PCR products were sequenced with the primer set 217

63F and 1387R (Table 2 by Beckman Coulter Genomics (Takeley, UK). Sequences were 218

analyzed by blastn using the 16S ribosomal RNA sequences reference data base for Bacteria 219

and Archaea (http://blast.ncbi.nlm.nih.gov/Blast.cgi) (51). 220

221

Assessment of antibiotic resistance genes by PCR 222

PCR assays specific for sul (32) and qnr (33) resistance genes were performed as follows: 223

each 25-μl PCR reaction mixture contained 12.5 µl KAPA2G Fast ReadyMix with dye 224

(Peqlab Biotechnologie GmbH, Erlangen, Germany), 2–3 mM MgCl2 and 20 ng genomic 225

DNA of bacterial isolates. DNA amplifications were carried out in an Eppendorf thermocycler 226

(Eppendorf Mastercycler for 96-well plates, Eppendorf AG, Hamburg, Germany). The 227

temperature profile consisted of an initial denaturation step at 95°C for 2 min followed by 30 228

cycles of denaturation at 95°C for 30 s, primer annealing at 57°C for 45 s for qnr genes and 229

65°C for 30 s for sul genes and extension at 72°C for 1 min, followed by an additional 7-min 230

elongation step at 72°C (only for qnr genes). Primers used are listed in Table 2. Absolute 231

quantifications of sul1 and sul2 genes were performed with serial diluted exogenous standards 232

that consisted of purified PCR products. Quantification of absolute target gene numbers was 233

carried out using the Light-Cycler 480 (Roche Diagnostics, Mannheim, Germany) as 234

described in (27). 235

236

Antimicrobial susceptibility testing of bacterial isolates 237

Resistance of the bacterial isolates to specific antibiotics was determined by the disc 238

diffusion method according to CLSI guidelines (52) with the following antibiotic discs 239

(Oxoid, Wesel, Germany): ampicillin (25 µg), chloramphenicol (30 µg), erythromycin (10 240

µg), gentamicin (10 µg), kanamycin (30 µg), oxacillin (5 µg), streptomycin (25 µg), 241


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ciprofloxacin (5 and 10 µg), doxycycline (30 µg), tetracycline (30 µg), vancomycin (30 µg), 242

and sulfamethoxazole (25 µg). Single colonies of bacterial soil isolates were diluted according 243

to McFarland to an OD630 of 0.16 and streaked-out with swabs according to DIN 58940-244

3:2007-10. Instead of Mueller-Hinton agar, TSA plates were used and incubated 24 h at 22°C. 245

246

RESULTS AND DISCUSSION 247

Characteristics of wastewater-irrigated and rain-fed soils 248

Irrigation with untreated wastewater releases organic carbon compounds and other nutrients 249

into soils. More nutrients and a higher humidity over the entire year provide better growth 250

conditions for indigenous bacteria and possibly also for wastewater-derived bacteria and thus 251

might change the composition of soil bacterial communities. The organic matter content of 252

the analyzed soils increased during long-term irrigation with wastewater (Table 1). In rain-fed 253

soils TOC ranged from 0.91 to 1.53% whereas in wastewater-irrigated soils TOC ranged from 254

1.06 to 3.35%. The total nitrogen content in the soils varied from 0.05 to 0.15% (rain-fed) and 255

0.10 to 0.30% (wastewater-irrigated). The soil pH values varied between 6.7 and 7.4. Increase 256

of soil organic matter content through wastewater irrigation has also been reported by others 257

(53–58). This results in rising microbial biomass and microbial activity (53,59–61). 258

Furthermore, increased water supply by wastewater irrigation in the dry season seems to 259

provide better conditions for microbial proliferation (53). This might also increase the 260

survival rate of wastewater-derived bacteria. 261

262

General analysis of the pyrosequencing-derived dataset and overall bacterial diversity and 263

richness 264


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Pyrosequencing of partial 16 S rRNA genes (V2-V3 region) yielded a total number of 265

452,999 sequences across all analyzed soil samples (n=24). After preprocessing including 266

quality-filtering, denoising and removal of non-bacterial or chimeric reads, 337,493 267

sequences with an average length of 353 bp were obtained for further analyses (Table S1). 268

Due to the fact that the number of analyzed sequences per sample has an effect on the 269

predicted number of operational taxonomic units (OTUs), OTU-based comparisons between 270

the analyzed 24 soils were performed at the same level of surveying effort (11,320 sequences 271

per sample) (62). 272

Rarefaction curve, richness and diversity analyses were based on OTUs determined at 3 and 273

20% genetic distance. Comparison of the rarefaction analyses with the number of OTUs 274

calculated by Chao1 richness estimator revealed that 72.6 to 86.8% (20% genetic distance) 275

and 31.0 to 48.2% (3% genetic distance) of the estimated richness were covered by the 276

sequencing effort (Table S2 and Fig. 1). (The Chao 1 nonparametric richness estimator was 277

employed to calculate the estimated true OTU diversity of the samples). Thus, we did not 278

survey the full extent of diversity, but particularly at 20% genetic distance (phylum level 279

according to Schloss and Handelsman (63), a substantial fraction of the bacterial diversity was 280

assessed within individual soil samples. Dry season samples exhibited significantly higher 281

OTU numbers, Chao1 richness estimates and bacterial diversity as assessed by Shannon index 282

(H’) than rainy season samples (3% genetic distance: P < 0.001; 20% genetic distance: P < 283

0.05) (Table S2 and Fig. 1), likely due to the larger input of wastewater-derived bacteria 284

during the irrigation season. Wastewater irrigation had no statistically significant impact on 285

overall bacterial diversity and richness (see Table S2 and Fig. 1) which is in agreement with 286

the studies of Frenk et al. (8). 287

288

Community composition in wastewater-irrigated and rain-fed soils 289


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Bacterial 16S rRNA gene sequences were affiliated to 23 phyla (Table S3) and 17 candidate 290

divisions (Table S4). The dominant phyla and proteobacterial classes across all 24 soil 291

samples were Actinobacteria (27.4%), Alphaproteobacteria (14.6%), Acidobacteria (14.0%), 292

Betaproteobacteria (9.5%), Chloroflexi (9.3%), Gammaproteobacteria (8.9%), Firmicutes 293

(5.2%), Deltaproteobacteria (2.7%), Gemmatimonadetes (2.5%), and Planctomycetes (1.9%). 294

These phyla and proteobacterial classes are typically encountered in soil and were also 295

reported in similar relative abundance in a meta-analysis of 32 soil-derived bacterial 16S 296

rRNA gene libraries (64) and recent metagenomic as well as metatranscriptomic microbial 297

community analyses (65,66). 298

The relative abundance of bacterial phyla and proteobacterial classes varied between 299

wastewater-irrigated and rain-fed soils (Fig. 2). A shift of the bacterial community towards a 300

higher relative abundance of Gammaproteobacteria was observed in both seasons (dry and 301

rainy season) in the wastewater-irrigated soils compared to the rain-fed soils (P = 0.002). 302

With respect to rain-fed soil samples, 3.2 to 5.5% (rainy season) and 3.4 to 4.2% (dry season) 303

of the bacterial sequences were affiliated to Gammaproteobacteria, whereas relative 304

abundances of gammaproteobacterial sequences determined for wastewater-irrigated soils 305

ranged from 5.8 to 10.3% (rainy season) and 8.5% to 17.7% (dry season) (Table S3). 306

Strikingly, more potentially harmful Gammaproteobacteria were detected in wastewater-307

irrigated than in rain-fed soils (Fig. 3). Up to 196, 28 and 20 fold higher relative abundances 308

of Acinetobacter, Stenotrophomonas and Pseudomonas, respectively, were determined in 309

wastewater-irrigated soil compared to rain-fed soil during the dry season (Fig. 3). Species 310

within these genera such as Pseudomonas aeruginosa and Acinetobacter baumanii are 311

representatives of the so called ESKAPE (Enterococcus faecium, Staphylococcus aureus, 312

Klebsiella species, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter 313

species) organisms that are frequently causing nosocomial infections (67,68). They are of 314

main concern due to the high abundance of multi-resistances. Another emerging organism 315


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that causes nosocomial and community-acquired infections is S. maltophilia (69–72). This 316

bacterium can be associated with respiratory tract infections (71,72), especially in 317

hospitalized patients on mechanical ventilation. The high prevalence of Stenotrophomonas, 318

Pseudomonas and Acinetobacter in the wastewater-irrigated soils indicates an adaptation of 319

wastewater-associated bacteria to the soil environment. These bacteria serve as carriers of 320

multiresistances and likely increase the dissemination of these resistance determinants in the 321

environment and to other potentially more dangerous bacteria. The high increase of the 322

relative abundance of Acinetobacter, Stenotrophomonas and Pseudomonas in wastewater-323

irrigated soil as determined for the dry season (P < 0.05) was not detected using statistical 324

analysis in the rainy season (Fig. 3). This result might be related to increased input of 325

wastewater-derived bacteria by wastewater irrigation in the dry season. These findings are in 326

agreement with the studies of Frenk et al. demonstrating that the relative abundance of 327

Gammaproteobacteria increases in the irrigation season and decreases in the rainy season (8). 328

Like Gammaproteobacteria, Betaproteobacteria were more abundant in all dry season 329

wastewater-irrigated soil samples than in dry season rain-fed soils (P < 0.001) (Fig. 2). 330

However, no medically relevant betaproteobacterial species were detected. Principal 331

coordinate analysis at 3% genetic distance indicated that rain-fed soil samples harbor 332

similarity in overall bacterial community composition since they tend to cluster (Fig. 4). An 333

effect of season on overall bacterial community composition was not revealed. 334

335

Characterization of soil isolates 336

Bacterial isolates from soils irrigated with untreated wastewater for 100 years and from soils 337

which have only received rainwater, both from dry and rainy reason, were obtained by 338

incubation on TSA plates for 24 to 48 hours at 23°C. The incubation temperature was chosen 339

because it was the mean soil temperature at the Mezquital in the dry season. TSA is a rich 340


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medium and proved to be appropriate for isolation of diverse environmental bacteria as 341

already shown by e.g., Krishnamurthi and Chakrabarti for soil and by Yashiro et al. for 342

phyllosphere (73, 74); the predominantly isolated soil bacteria in their studies were members 343

of the phyla Firmicutes (most of them Bacillus spp.), followed by Actinobacteria and 344

Proteobacteria. In our study, most bacterial isolates from wastewater-irrigated soils (48 345

isolates from soil samples collected in the dry season and 48 isolates from soil samples 346

collected in the rainy season) belonged to the Bacilli (50%) and Gammaproteobacteria 347

(46%). Only 3% of the isolates belonged to Actinobacteria and 1% to the class of 348

Alphaproteobacteria (Fig. 5A and Table S6). The most abundant genera were Bacillus (47%) 349

and Stenotrophomonas (39%), followed by Pseudomonas (5%) and Acinetobacter (2%) (Fig. 350

5B). In rain-fed soils all of the 96 isolates (48 isolates from soil samples collected in the dry 351

season and 48 isolates from soil samples collected in the rainy season) belonged to the Bacilli 352

and within this class to the genus Bacillus (Table S5). Bacillus is ubiquitous in soil 353

environments (75,76) and can persist under a variety of conditions due to the ability to form 354

endospores (77,78). 355

The taxonomic groups detected (Proteobacteria, Actinobacteria and Bacilli) are typical taxa 356

found in agricultural soils. A rise in the available soil nutrients and moisture in wastewater-357

irrigated soils leads to an increase in Proteobacteria, particularly Gammaproteobacteria, 358

which is in agreement with previous studies (8,26). Consistent with the amplicon data, which 359

revealed a higher relative abundance of Gammaproteobacteria in wastewater-irrigated soils 360

compared to rain-fed soils, more isolates belonging to the Gammaproteobacteria 361

(Stenotrophomonas, Pseudomonas and Acinetobacter) were obtained from wastewater-362

irrigated soils than from rain-fed soils (46% of the isolates from wastewater-impacted soils vs. 363

no isolate from rain-fed soils). The fact that these microorganisms were derived from samples 364

collected in the dry as well as in the rainy season indicates that they have adapted to the 365

wastewater-irrigated soil environment. Some crops, maize and several herbs such as Rumex 366


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sp., Malva sp., and Chenopodium mexicanum that grow in wastewater irrigated fields are 367

consumed by the people in the Mezquital Valley. In particular, the near-ground herbs are in 368

direct contact with wastewater and wastewater-irrigated soils. This might imply health risks 369

for consumers of insufficiently washed crops containing wastewater-derived bacteria and 370

resistance determinants. 371

372

Prevalence of multi-antibiotic resistant isolates from wastewater-irrigated soils 373

All isolates from wastewater-irrigated soils and from rain-fed soils were tested for 374

susceptibility to 12 different antibiotics. In addition, the isolates that were resistant to 375

sulfamethoxazole (SMX) or ciprofloxacin (CIP) were analyzed for the presence of sul and qnr 376

resistance genes that encode resistance to sulfonamides and fluoroquinolones, respectively. 377

These genes were detected in total DNA of the chronosequence soils. The genes sul1, sul2, 378

qnrA, qnrB and qnrS were not found in total DNA of the isolates. For the qnr genes, this is 379

not surprising, as these genes were rarely found in the chronosequence soils (27). Resistance 380

to fluoroquinolones is often the result of point mutations in target genes such as gyrA 381

encoding DNA gyrase and parC encoding a type IV topoisomerase (79). Only three out of 96 382

isolates from wastewater-irrigated soils (one Stenotrophomonas, one Bacillus and one 383

Exiguobacterium isolate) and none of the 96 isolates from rain-fed soils were resistant to low 384

concentrations of the fluoroquinolone ciprofloxacin (5 µg) (Table S5 and Table S6). Several 385

isolates, 32 from wastewater-irrigated soils and 18 from rain-fed soils, were resistant to the 386

sulfonamide SMX (25 µg). Interestingly, a considerable number of isolates belonging to the 387

Bacillaceae were resistant to SMX, 18 of the 96 Bacilli isolates from rain-fed soils and 21 of 388

the 46 Bacilli isolates from wastewater-irrigated soils. 389

In other studies, SMX-resistant Bacilli were isolated from different environments such as 390

wastewater, water and sediments on selective plates containing between 50 and 200 µg/ml 391


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SMX. But even when isolated under selective pressure not all resistant isolates contained 392

sul1, sul2 or sul3 genes (80). Sulfonamide resistance can also occur by other mechanisms, 393

such as modification of the antibiotic target, e.g., by mutations of the chromosomal 394

dihydropteroate synthase gene (81). Sulfonamide resistance (often also in combination with 395

trimethoprim) has been described for several Bacillus species (82). From wastewater-irrigated 396

soils 33% of the isolates (n=96) were resistant to SMX. Twenty-one of them were Bacillus 397

spp., the remaining 11 belonged to the genera Stenotrophomonas, Pseudomonas and 398

Acinetobacter. In wastewater irrigation fields more isolates (51%) were resistant to at least 399

one antibiotic than in rain-fed soils (34%). In particular the presence of multi-resistant 400

bacteria (resistance to ≥ 2 antibiotics) was more pronounced in wastewater-irrigated soils 401

(25%) compared to rain-fed soils (6%) (Table S5 and Table S6). 402

In the present study, resistance to oxacillin, erythromycin, vancomycin and ampicillin was 403

frequently found in isolates from wastewater-irrigated soils. Other resistances were less 404

frequent (< 10%) and no isolate resistant to doxycycline was found (summarized in Fig. 6, 405

Table S5 and Table S6). The higher abundance of multi-resistant isolates from wastewater- 406

irrigated fields is likely related to the different types of bacteria isolated from the two 407

irrigation regimes. In wastewater-irrigated soils three isolates were resistant to three 408

antibiotics, and nine were resistant to more than three antibiotics. For the isolates from rain-409

fed soils only two isolates showed resistance to three different antibiotics, none to more than 410

three antibiotics. The majority of multi-resistant bacteria belonged to the genus 411

Stenotrophomonas (Table S6). 16S rRNA gene sequences of the Stenotrophomonas isolates 412

showed highest identities (96 to 99%) to S. maltophilia, an opportunistic bacterial pathogen 413

with environmental origin, that is associated with several human diseases (69,70,72). 414

Treatment proves difficult due to the species’ intrinsic antibiotic resistance (69). An increase 415

of the relative abundance of Stenotrophomonas spp. in soils which have been treated by 416

sulfadiazine-amended manure was observed by Ding et al. (83). 417


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For the clinically relevant strains, S. maltophilia and P. aeruginosa, several studies reported 418

that multiple antibiotic resistances are due to the overexpression of multidrug efflux pumps 419

(e.g., SmeDEF, MexA-MexB-OprM) (84,85). For several environmental Pseudomonas 420

isolates intrinsic multi-drug resistance has been reported. Malik and co-workers have 421

demonstrated high prevalence of antibiotic resistances of Pseudomonas isolates from water 422

and soil (5). They have shown that 87.5% of the Pseudomonas isolates from wastewater-423

irrigated soils were resistant to the sulfonamide sulphadiazine. Furthermore, they revealed 424

that isolates from groundwater-irrigated soils were less resistant to antibiotics than isolates 425

from wastewater-irrigated soils, which is consistent with our data (5). 426

Finally, our data reveal a higher prevalence of Gammaproteobacteria, in particular of harmful 427

and multi-resistant bacteria like S. maltophilia in wastewater-impacted soil. To the best of our 428

knowledge, this is the first report on high incidence of Stenotrophomonas spp. in wastewater-429

irrigated soils. Most of the bacterial isolates from wastewater irrigated soils were resistant to 430

several antibiotics (up to five different antibiotic classes). The higher incidence of multiple 431

antibiotic resistant bacteria in wastewater-impacted soils indicates survival of wastewater-432

derived bacteria in the environment and thus represents an increased risk of antibiotic 433

resistance dissemination in the environment. A major health issue is related to the observation 434

that near-ground crops that are in direct contact with soil and wastewater are consumed raw 435

by the people in the Mezquital Valley. 436

437

ACKNOWLEDGMENTS 438

We thank R. Brämer and A. Henninger from the University of Applied Sciences Offenburg 439

for support with the measurement of the chemical soil parameters. This work was supported 440

by grants GR1792/4-1 and GR1792/4-2 from the German Research Foundation and the 441


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Mexican Consejo Nacional de Ciencia y Tecnología (CONACYT): grants CB 83767 and I 442

0110-193-10. 443

444

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683

684

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FIGURE LEGENDS 686

Figure 1: Rarefaction curves indicating the observed number of operational taxonomic units 687

(OTUs) at a genetic distance of 3 and 20% within the analyzed soil samples. Sample 688

abbreviations: RS0, rainy season rain-fed soil; RS10, rainy season, 10 years wastewater 689

irrigation; RS85, rainy season, 85 years wastewater irrigation; RS100, rainy season, 100 years 690

wastewater irrigation; DS0, dry season rain-fed soil; DS8, dry season, 8 years wastewater 691

irrigation; DS85, dry season, 85 years wastewater irrigation; DS100, dry season, 100 years 692

wastewater irrigation. Triplicates were analyzed (indicated by a, b and c). 693

694

Figure 2: Relative abundances of dominant phyla and proteobacterial classes determined for 695

the analyzed soil samples. Sample abbreviations: RS0, rainy season rain-fed soil; RS10, rainy 696

season, 10 years wastewater irrigation; RS85, rainy season, 85 years wastewater irrigation; 697

RS100, rainy season, 100 years wastewater irrigation; DS0, dry season rain-fed soil; DS8, dry 698

season, 8 years wastewater irrigation; DS85, dry season, 85 years wastewater irrigation; 699

DS100, dry season, 100 years wastewater irrigation. Analysis of triplicates has been 700

illustrated using error bars. 701

702

Figure 3: Heatmap showing relative abundances of gammaproteobacterial genera as affected 703

by wastewater irrigation during dry as well as rainy season. Triplicates were analyzed 704

(indicated by a, b and c). 705

706

Figure 4: Weighted UniFrac 2D Principal Coordinate Analysis plot for beta diversity 707

analysis. Sample abbreviations: RS0, rainy season rain-fed soil; RS10, rainy season, 10 years 708

wastewater irrigation; RS85, rainy season, 85 years wastewater irrigation; RS100, rainy 709


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30

season, 100 years wastewater irrigation; DS0, dry season rain-fed soil; DS8, dry season, 8 710

years wastewater irrigation; DS85, dry season, 85 years wastewater irrigation; DS100, dry 711

season, 100 years wastewater irrigation. 712

713

Figure 5: A: Abundance of bacterial classes in isolates from wastewater-irrigated soils, 714

B: Abundance of different bacterial genera in isolates from wastewater-irrigated soils. 715

716

Figure 6: Percentage of antibiotic resistant isolates from wastewater-irrigated soils and rain-717

fed soils. (CIP: Ciprofloxacin (5 µg), Kana: Kanamycin (30 µg), SMX: Sulfamethoxazole (25 718

µg), Tet: Tetracycline (30 µg), Doxy: Doxycycline (30 µg), Gm: Gentamycin (10 µg), Amp: 719

Ampicillin (25 µg), Sm: Streptomycin (25 µg), Oxa: Oxacillin (5 µg), Cm: Chloramphenicol 720

(30 µg), Van: Vancomycin (30 µg), Em: Erythromycin (10 µg)); ww: wastewater. 721


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Table 1: Characteristics of the analyzed soil samples.

Sample-

ID

Irrigation

time

[years]

season pH TOC % TC % TN % C/N

DS0 0 dry 6.3 0.91 0.95 0.05 17.8

RS0 0 rainy 7.3a 1.53a 1.62a 0.15a 10.8

DS8 8 dry 6.7 1.16 1.21 0.10 12.4

RS10 10 rainy 8.2 1.84 2.56 0.18 14.2

DS85 85 dry 6.7 2.06 2.15 0.19 11.3

RS85 85 rainy 6.4 2.26 2.30 0.29 7.9

DS100 100 dry 6.9 3.15 3.25 0.30 10.9

RS100 100 rainy 7.4a 2.43a 2.56a 0.25a 10.2

a: data from (29). (TOC, TC and TN measured according to (30)).


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Table 2: Primer sets used in this study.

Target Amplicon Oligonucleotide Sequence (5´ to 3´) Ta Reference

sul1 158 sul1-FW CACCGGAAACATCGCTGCA 65 (32)

sul1-RV AAGTTCCGCCGCAAGGCT

sul2 190 sul2-FW CTCCGATGGAGGCCGGTAT 65 (32)

sul2-RV GGGAATGCCATCTGCCTTGA

qnrA 543 qnrA-F GATAAAGTTTTTCAGCAAGAGG 56 (33)

qnrA-R ATCCAGATCGGCAAAGGTTA

qnrB 497 qnrB-F AGCGGCACTGAATTTAT 56 (33)

qnrB-R GTTTGCTGCTCGCCAGTC

qnrS 600 qnrS-F GGAAACCTACAATCATACATA 56 (33)

qnrS-R GTCAGGATAAACAACAATACC


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Bacteria 1465 27F GAGTTTGATCMTGGCTCAG 58 (34)

16S rDNA 1492R GGYTACCTTGTTACGACTT

Bacteria 1324 63fw CAGGCCTAACACATGCAAGTC 56 (35)

16S rDNA 1387rev GGGCGGWGTGTACAAGGC

Bacteria 414 101Fb CCTATCCCCTGTGTGCCTTGGCAGTCTCAG

AGTGGCGGACGGGTGAGTAA

69 (36, 37)

16S rDNAa 515Rc CCATCTCATCCCTGCGTGTCTCCGACTCAG-

MID-CCGCGGCTGCTGGCAC

Ta: annealing temperature; Y: C or T; a: primers for pyrosequencing; b: Roche 454 pyrosequencing adaptor B is underlined;

c: Roche 454 pyrosequencing adaptor A is underlined; MID, sample-specific Extended Multiplex Identifier (size: ten nucleotides).


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wastewater irrigation increases abundance of potentially harmful

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