Effects of Swine Manure on Macrolide, Lincosamide, and Streptogramin B Antimicrobial Resistance in Soils

Farms and sampling.Three Illinois swine farms that routinely used antimicrobials (farms LF, MF, and HF), designated conventional farms, and two Illinois swine farms that used no antimicrobials (farms OF and OF2), designated organic farms, were included in this study. Details concerning antimicrobial use and farm management have been reported previously (10, 31, 33). Manure was applied using surface broadcasting or injection into fields with a corn-soybean crop rotation. The field soils were predominately silt loams (farms MF, LF, OF, and OF2), while the field sampled at farm HF contained silty clay loam and in some areas silt loam (28). The moisture content was between 0.28 and 0.30 g water/g sample. For each farm, five soil cores from each of five systematic locations were pooled to form a single composite sample that was used for antimicrobial quantification and molecular analysis.

For the soil batch tests, manure was collected from the building floor at farm OF2 and from the settling basin at farm LF in December 2005. The unamended soil used in the batch tests was a silty clay loam collected from a single location in an agricultural field at the University of Illinois at Urbana-Champaign South Farm (farm SF) that had not received manure in at least 40 years.

For molecular analysis, samples were fixed using ethanol as described previously (30) and stored at −20°C. The manure and soil samples used for liquid chromatography-mass spectrometry (LC-MS) were kept at temperatures below −20°C until they were shipped on ice. The manure and soil samples used in the batch tests were stored at 4°C.

Quantification of antimicrobials.Antimicrobials were quantified by triple quadrupole liquid chromatography-tandem mass spectrometry at the Institute of Agriculture and Natural Resources at the University of Nebraska (Lincoln, NE) (27, 32). Prior to analysis, the manure samples were diluted in 0.5 M potassium phosphate-citric acid buffer (pH 2.5) (tetracycline analysis) or a neutral phosphate solution (macrolide and lincosamide analysis) and extracted using Oasis HLB cartridges (Waters Corporation, Milford, MA). The soil samples were extracted twice with 1 M citric acid-sodium citrate (pH 4) and twice with a mixture of acetone and formic acid (pH 4) (27).

FISH methods.Fixed soil samples were diluted (1:100) in 0.1% sodium pyrophosphate (NaPPi) buffer (13). Then 10 μl of a diluted sample was sonicated in 2 ml 0.1% NaPPi buffer with a sonic dismembrator (5-s on-off pulses; output, 250 W; 60 s; model 500; Fisher Scientific, Pittsburgh, PA). Slides were prepared and FISH was performed as previously described (30). Details concerning oligonucleotide probes Bact338, Arc0915, Alf1b, Bet42a, Gam42a, HGC69A, and LGC354 are available at probeBase (17). The MLS_B and ClosXIVa probes and the FISH protocols used have been described previously (31). The Streptomyces probe (5′-ACC CCG TTT CCA GGG CTT GT) was originally developed for PCR (22); for use in FISH, a hybridization condition of 25% formamide was selected based on the fluorescence intensities of pure-culture positive and negative controls (negative control, Kitasatospora phosalacinea; positive controls, Streptomyces albus and Streptomyces chatrensis). In dual labeling experiments, the samples were first hybridized with the probe requiring more stringent conditions. Total cell counts were obtained after staining with 4′,6-diamidino-2-phenylindole (DAPI), and the cell counts obtained from the 10 random images for each replicate ranged from 325 to 8,277. The images were analyzed in an automated fashion using the Visilog image analysis software (version 6; Noésis, Les Ulis, France) as previously described (30). The prevalence of ribosomal methylation and presumed MLS_B resistance was calculated as follows: 1 − number of MLS_B-sensitive cells/total number of cells or Bact338-hybridized cells. Detection limits could not be quantified because for all of the soils sampled there were detectable levels of MLS_B resistance, as expected for naturally occurring antimicrobials.

Soil batch tests.The manure-to-soil ratio was estimated using recommended land application rates of manure based on the Illinois Best Management Plan (BMP) (https://webs.extension.uiuc.edu/immp/), measurements of soil density, and an assumed direct impact on the first 20 cm of soil (based on injection depth). Concentrations of resistant microorganisms and antimicrobials were based on previous farm measurements (33). The standard amendments (1×) were 8 g manure, 1.0 × 10⁹ cells of Clostridium spp., 160 μg lincomycin, and 80 μg chlortetracycline in 200 g soil. For increased resolution, rather than identical replicates, a concentration series was used for each amendment. Unamended soil was used as a control. The MLS_B-resistant Clostridium spp. were isolated from farm OF. For all soil batch tests, the materials were completely mixed in 250-ml glass bottles and incubated at 25°C and the soil wetness was maintained at the initial value (25% of the capacity). The bottles were sealed with Parafilm, and full-spectrum fluorescence light was supplied for 12 of every 24 h. To obtain a bulk measurement of resistance, for each batch test the contents were mixed before a 5-g sample was removed and fixed for molecular analysis.

Statistics.Student t tests were performed to compare the levels of antimicrobial resistance of manure-amended soils and unamended soils. Where specified below, one-way analysis of variance (ANOVA) was used for pairwise comparisons. Differences were considered significant at a P value of <0.05. Statistical analyses were carried out with the software R (http://www.r-project.org/).

Levels of antimicrobials and MLS_B resistance in field soils.The concentrations of MLS_B and tetracycline antimicrobials in soils that received no swine manure (unamended) and in soils that received swine manure from organic farms (farms OF and OF2) or swine manure from conventional farms (farms LF, MF, and HF), along with a summary of the antimicrobials used at the different farms, are shown in Table 1. Of the MLS_B antimicrobials, tiamulin, tilmicosin, and tylosin were not detected despite the fact that they were used at one or more farms. Of the tetracycline antimicrobials, chlortetracycline was the compound that was most commonly used and detected (Table 1). The concentrations of tetracyclines were significantly higher (P = 0.020) in soils that received swine manure from conventional farms (farms LF, MF, and HF) than in soils that received swine manure from organic farms (farms OF and OF2) or no manure (unamended).

For the six composite soil samples, each from a different farm, the prevalence of ribosomal methylation—and presumed resultant MLS_B antimicrobial resistance—was between 2.0 and 5.2% of the cells that hybridized with the bacterial domain probe. No significant differences were observed among the soil samples from unamended fields and the soil samples that received either organic or conventional farm manure (P = 0.690, ANOVA).

Effects of antimicrobials and antimicrobial-resistant microorganisms on MLS_B resistance in soil batch tests.The impact of land application of conventional and organic farm manure was also evaluated under controlled conditions using soil batch tests. To distinguish the effects of antimicrobials and MLS_B-resistant microorganisms, the test conditions included amendment with organic farm manure spiked with lincomycin, chlortetracycline, or MLS_B-resistant Clostridium spp. The conventional farm manure contained primarily oxytetracycline and its degradation product, β-apo-oxytetracycline (Table 2). Although, as expected, the organic farm manure contained lower concentrations of antimicrobials, surprising amounts of chlortetracycline and oxytetracycline were present (Table 2). Sorption and/or degradation of the antimicrobials occurred during the batch tests but was not complete, as the concentrations at day 90 were 7 to 35% of the estimated initial values (Table 2).

The prevalence of ribosomal methylation—and presumed resultant MLS_B antimicrobial resistance—in the soil batch tests for soils that received the highest concentrations of amendments (4×) is shown in Fig. 1A. As expected, the 4× amendments increased the prevalence of ribosomal methylation in the initial samples (P = 0.010). The increase was still evident in the day 10 samples (P = 0.008), but no significant difference from the unamended control was observed by day 20 (P = 0.084). Similar results were obtained for samples amended with 1× farm OF2 manure and various concentrations of resistant Clostridium spp. (Fig. 1B). Specifically, addition of resistant Clostridium spp. increased the prevalence of ribosomal methylation in the initial samples (P = 0.039), and the difference was still evident at day 10 (P = 0.019), but after 20 days of incubation there was no significant difference (P = 0.240). Throughout the experiment, there was no significant difference between the prevalence of MLS_B resistance in the unamended soil and the prevalence of MLS_B resistance in the soil amended with 1× farm OF2 manure. The prevalence of ribosomal methylation in soil samples amended with 1× farm OF2 manure and some concentrations of lincomycin appeared to increase over the first 10 days (Fig. 1C). However, like the results of the other batch tests, by day 20 the results were not significantly different from those for unamended samples (for comparisons of unamended and lincomycin-amended samples, at day zero P = 0.067, at day 10 P = 0.015, and at day 20 P = 0.076). Small differences in the prevalence of resistance may have been obscured by the variability.

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FIG. 1.

Influence of manure application on MLS_B resistance in batch tests. The prevalence of ribosomal methylation and the prevalence of presumed MLS_B resistance are shown for the batch tests in which soil was amended with the maximum concentrations (4×) of manure from farms OF2 and LF, with MLS_B-resistant Clostridium spp. (Clos.^R), with lincomycin (linc.), and with chlortetracycline (chlortet.) (A). The responses to a range of concentrations of MLS_B-resistant Clostridium spp. and lincomycin were also determined (B and C, respectively). The error bars indicate standard errors for triplicate hybridizations.

Initial microbial communities in soil batch tests.Laboratory incubation of soil changes the microbial community even when no amendments are added, and addition of the organic material and microorganisms present in manure was expected to affect the microbial community structure. Coarse characterization of the initial microbial community structure in soils that received the standard amendment of organic or conventional farm manure was performed to select groups to monitor during the batch tests (Fig. 2). This analysis characterized 71% of the total microorganisms (average value for cells hybridized with the Bact0338 and Arc0915 probes normalized with the total number of DAPI-stained cells) and 95% of the total bacteria (average value for cells hybridized with all phylogenetic probes except Arc0915 normalized with the number of cells hybridized with Bact0338) and identified Betaproteobacteria, Gammaproteobacteria, Clostridium cluster XIVa, and Firmicutes as the most abundant bacterial groups. The dynamics of these groups were then monitored during the batch tests (Fig. 3A). At the coarse resolution used, the levels of specific groups of bacteria were relatively stable during the soil batch tests.

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FIG. 2.

Microbial community analysis for manure-soil mixtures. Abundance was normalized with total cell counts by DAPI staining. Firmicutes and Streptomyces in the unamended soil were not quantified. The error bars indicate half-ranges for duplicate hybridizations.

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FIG. 3.

Abundance and prevalence of the MLS_B resistance of specific populations during batch tests. Unamended soil samples were compared to samples amended with 4× farm LF manure or 4× farm OF2 manure. (A) Abundance data, normalized to total cell counts by DAPI staining. (B) Prevalence of MLS_B resistance in specific populations. (C) Contributions of specific populations to overall resistance levels. The error bars indicate standard errors for triplicate hybridizations.

MLS_B resistance in specific microbial populations.While the results described above indicated that land application of manure did not result in increased levels of MLS_B resistance in the soil microbial community as a whole, measuring MLS_B resistance as a bulk parameter could have concealed important effects of land application, such as changes in the types of microorganisms exhibiting resistance. Therefore, we combined the phylogenetic FISH analysis with the MLS_B probe to characterize the prevalence of ribosomal methylation and the prevalence of presumed MLS_B antimicrobial resistance in the most abundant groups of bacteria throughout the batch tests (Fig. 3B). By combining data for the abundance and prevalence of resistance for specific groups, the relative contribution of each group to the total resistance could be calculated (Fig. 3C). The initial prevalence of resistance in Clostridium cluster XIVa was significantly higher for amended samples (P = 0.006) than for unamended samples. A decrease in the prevalence of resistance in this cluster corresponded with the overall decrease in resistance observed during the batch tests. Clostridium cluster XIVa accounted for the largest fraction of the identified resistant bacteria, comprising an average of 47.0% of the MLS_B-resistant microorganisms throughout the batch tests (Fig. 3C).